Dataset Viewer
id
string | image
image | latex
string | title
string | caption
string | newcommands
string | categories
string |
|---|---|---|---|---|---|---|
2307.04457v2
|
\begin{tabular}{l|cc|cc|cc}
\hline
& \multicolumn{2}{c}{\textbf{Heat stability}} & \multicolumn{2}{|c}{\textbf{Casein content}} &\multicolumn{2}{|c}{\textbf{RCT}} \\
& RMSEP&$\widehat{\ttQ}_y$ &RMSEP&$\widehat{\ttQ}_y$& RMSEP&$\widehat{\ttQ}_y$ \\
\hline
BBPLS & 0.875 (0.172) & 6.5 (2.5) & 0.376 (0.027) & 6.8 (1.5) & 0.815 (0.139) & 5.5 (1.9) \\
ss-BPLS & 0.874 (0.164) & 4.3 (0.5) & 0.376 (0.031) & 6.3 (1.3) & 0.813 (0.141) & 5.3 (1.0) \\
L-BPLS & \textbf{0.823} (0.156) & 15.8 (1.0) & \textbf{0.360} (0.041) & 15.8 (2.1) & \textbf{0.782} (0.126) & 18.3 (3.0) \\ \hline
PLS & 0.896 (0.117) & 5.5 (0.6) & 0.395 (0.028) & 4.5 (0.6) & 0.863 (0.141) & 5.5 (1.7) \\
PLS-1s & 0.849 (0.125) & 7.8 (1.5) & 0.397 (0.022) & 4.5 (0.6) & 0.810 (0.105) & 7.3 (1.3) \\
sPLS & 0.879 (0.173) & 14.5 (4.0) & 0.376 (0.044) & 8.5 (4.4) & 0.801 (0.128) & 14.3 (3.5) \\
PCR & 0.877 (0.112) & 11.3 (1.9) & 0.402 (0.024) & 4.8 (1.5) & 0.824 (0.089) & 14.3 (7.2) \\
LASSO & 0.846 (0.121) & -- & 0.406 (0.024) & -- & 0.845 (0.125) & -- \\
RIDGE & 0.992 (0.145) & -- & 0.446 (0.027) & -- & 0.925 (0.108) & -- \\
PPLS &0.987 (0.127) & $^*$2.0 (0.0) & 0.682 (0.082) & $^*$2.0 (0.0) & 0.970 (0.095) & $^*$2.0 (0.0) \\
\hline
\end{tabular}
|
Predicting milk traits from spectral data using Bayesian probabilistic partial least squares regression
|
Accuracy of predictions of the standardised heat stability, casein content and RCT traits from the milk MIR spectral data using each of the proposed BPLS and existing methods. Estimates are given as ``mean (standard deviation)'' of thee RMSEP over the four test folds, with bold font indicating optimal performance. $^*$Due to numerical instability, $\widehat{\ttQ}_y$ was picked manually.
|
['\\newcommand\\myshade{95}', '\\newcommand{\\R}{\\mathbb{R}} ', '\\newcommand{\\Z}{\\mathbb{Z}}', '\\newcommand{\\N}{\\mathbb{N}}', '\\newcommand{\\Q}{\\mathbb{Q}}', '\\newcommand{\\C}{\\mathbb{C}}', '\\newcommand{\\E}{\\mathbb{E}}', '\\newcommand{\\V}{\\mathbb{V}}', '\\newcommand{\\dd}{\\mathsf{d}}', '\\newcommand{\\Lcal}{\\mathcal{L}}', '\\newcommand{\\Nb}{\\mathsf{N}}', '\\newcommand{\\Tcal}{{\\mathcal{T}}}', '\\newcommand{\\Mcal}{\\mathcal{M}}', '\\newcommand{\\Hcal}{\\mathcal{H}}', '\\newcommand{\\Vcal}{\\mathcal{V}}', '\\newcommand{\\Scal}{\\mathcal{S}}', '\\newcommand{\\Bcal}{\\mathcal{B}}', '\\newcommand{\\Ical}{\\mathcal{I}}', '\\newcommand{\\Ucal}{\\mathcal{U}}', '\\newcommand{\\Kcal}{\\mathcal{K}}', '\\newcommand{\\Ccal}{\\mathcal{C}}', '\\newcommand{\\Ecal}{\\mathcal{E}}', '\\newcommand{\\Pcal}{\\mathcal{P}}', '\\newcommand{\\Dcal}{\\mathcal{D}}', '\\newcommand{\\bigo}{\\mathcal{O}}', '\\newcommand{\\lamo}{{\\lambda_0}}', '\\newcommand{\\bfA}{{\\bf{A}}}', '\\newcommand{\\bfR}{{\\bf{R}}}', '\\newcommand{\\bft}{{\\bf{t}}}', '\\newcommand{\\bfI}{{\\bf{I}}}', '\\newcommand{\\bfJ}{{\\bf{J}}}', '\\newcommand{\\bfK}{{\\bf{K}}}', '\\newcommand{\\Fbar}{{\\bar{F}}}', '\\newcommand{\\Fhat}{{\\hat{F}}}', '\\newcommand{\\pihat}{{\\hat{\\pi}}}', '\\newcommand{\\bfX}{{\\mathbf{X}}}', '\\newcommand{\\bfY}{{\\mathbf{Y}}}', '\\newcommand{\\bfZ}{{\\mathbf{Z}}}', '\\newcommand{\\bfx}{{\\mathbf{x}}}', '\\newcommand{\\bfy}{{\\mathbf{y}}}', '\\newcommand{\\bfz}{{\\mathbf{z}}}', '\\newcommand{\\bfu}{{\\mathbf{u}}}', '\\newcommand{\\bfv}{{\\mathbf{v}}}', '\\newcommand{\\bfw}{{\\mathbf{w}}}', '\\newcommand{\\bfc}{{\\mathbf{c}}}', '\\newcommand{\\bfb}{{\\mathbf{b}}}', '\\newcommand{\\bmeps}{{\\bm{\\varepsilon}}}', '\\newcommand{\\bmmu}{{\\bm{\\mu}}}', '\\newcommand{\\bmbeta}{{\\bm{\\beta}}}', '\\newcommand{\\bmeta}{{\\bm{\\eta}}}', '\\newcommand{\\bmzeta}{{\\bm{\\zeta}}}', '\\newcommand{\\bmtau}{{\\bm{\\tau}}}', '\\newcommand{\\bmx}{{\\bm{x}}}', '\\newcommand{\\bmy}{{\\bm{y}}}', '\\newcommand{\\bmz}{{\\bm{z}}}', '\\newcommand{\\bma}{{\\bm{a}}}', '\\newcommand{\\bmc}{{\\bm{c}}}', '\\newcommand{\\ttP}{{\\mathtt{P}}}', '\\newcommand{\\ttQ}{{\\mathtt{Q}}}', '\\newcommand{\\ttR}{{\\mathtt{R}}}', '\\newcommand{\\Pois}{{\\mathsf{Pois}}}', '\\newcommand{\\Unif}{{\\mathsf{Unif}}}', '\\newcommand{\\Normal}{{\\mathsf{N}}}', '\\newcommand{\\p}{\\mathsf{p}}', '\\newcommand{\\iid}{i.i.d.\\ }', '\\newcommand{\\pitil}{\\tilde{\\pi}}', '\\newcommand{\\eps}{\\varepsilon}', '\\newcommand{\\Real}{\\mathbb{R}}', '\\newcommand{\\Natural}{\\mathbb{N}}', '\\newcommand{\\pos}{\\textsf{pos}}', '\\newcommand{\\e}{\\textsf{e}}', '\\newcommand{\\half}{\\dfrac{1}{2}} %1/2', '\\newcommand{\\third}{\\dfrac{1}{3}} %1/3', '\\newcommand{\\quarter}{\\dfrac{1}{4}} %1/4', '\\newcommand{\\const}{\\! {\\rm const.}\\; } %constant', '\\newcommand{\\recip}[1]{\\frac{1}{#1}} %reciprocal - 1/x', '\\newcommand{\\inv}{^{-1}}', '\\newcommand{\\set}[1]{\\left\\{ #1 \\right\\} } %{---}', '\\newcommand{\\seq}[1]{\\left( #1 \\right)} %(---)', '\\newcommand{\\sech}{\\mathsf{sech}}', '\\newcommand{\\cov}{\\mathsf{Cov}}', '\\newcommand{\\diag}{\\mathsf{diag}}', '\\newcommand{\\Prob}[1]{\\mathbb{P}\\left(#1\\right)}', '\\newcommand{\\Ind}[1]{\\mathbb{I}_{\\left\\{#1\\right\\}}} %Indicator Function', '\\newcommand{\\Id}[1]{{I}_{#1}} ', '\\newcommand{\\tr}[1]{\\mathsf{Tr}\\left[ #1 \\right]}', '\\newcommand{\\limit}[2]{\\stackrel{\\lim }{_{ #1 \\to #2 }}}%Limit', '\\newcommand{\\maxover}[1]{\\stackrel{\\max }{_{ #1 }}} %max', '\\newcommand{\\minover}[1]{\\stackrel{\\min }{_{ #1 }}} %min', '\\newcommand{\\OVec}{\\mathbf{0}} %Zero Vector', '\\newcommand{\\IVec}{\\mathbf{1}} %Ones Vector', '\\newcommand{\\todo}[1]{\\textcolor{violet}{[\\textbf{TODO:} #1 ]}}', '\\newcommand{\\su}[1]{\\textcolor{blue}{[\\textsf{SU:} \\emph{#1}]}}', '\\newcommand{\\st}{\\textsuperscript{st}~} %st superscript', '\\newcommand{\\nd}{\\textsuperscript{nd}~} %nd superscript', '\\newcommand{\\rd}{\\textsuperscript{rd}~} %rd superscript', '\\newcommand{\\Th}{\\textsuperscript{th}~} %th superscript', '\\newcommand{\\normal}{\\mathsf{N}}', '\\newcommand{\\pois}{\\mathsf{Pois}}', '\\newcommand{\\unif}{\\mathsf{Unif}}', '\\newcommand{\\gamdist}{\\mathsf{Gamma}}', '\\newcommand{\\betadist}{\\mathsf{Beta}}', '\\newcommand{\\Exp}{\\mathsf{Exp}}', '\\newcommand{\\cm}{\\,\\mathrm{cm}}', '\\newcommand{\\Cor}{\\mathsf{Cor}}']
|
stat.ME, stat.AP
|
|
2309.04013v1
|
\begin{tabular}{|c|c|c|} \hline
Species & \bf Mean & \bf Std.~Dev. \\ \hline
1 & 3.4 & 1.2 \\
2 & 5.4 & 0.6 \\ \hline
\end{tabular}
|
An Element-wise RSAV Algorithm for Unconstrained Optimization Problems
|
Example table.
|
['\\newcommand{\\bx}{\\boldsymbol{x}}']
|
math.OC, cs.LG, stat.ML, 90C26, 68T99, 68W40
|
|
2307.00516v1
|
\begin{tabular}{|c|c|c|c|c|c|}
\hline
$m\times n$ & 500$\times$ 1000 & 500$\times$ 2000 & 500$\times$ 4000 & 500$\times$ 8000 \\
\hline
GP-P1 & 4.015903385 & 16.7774142 & 70.75651123 & 388.644996 \\
\hline
GP-P2 & 3.56448103 & 24.74755891 & 68.75088813 & 327.9051987 \\
\hline
GP-P3 & 3.63770008 & 28.046205 & 70.57155305 & 415.8329173 \\
\hline
AN-P1 & 0.96336885 & 7.640021525 & 29.68469773 & 184.6441526 \\
\hline
AN-P2 & 0.9824258 & 9.923623106 & 29.76016001 & 168.6180109 \\
\hline
AN-P3 & 1.004097328 & 7.583189344 & 30.76611231 & 168.8091549 \\
\hline
BCDSPCA$_{\ell_1}$ & 7.2781 & 27.68084787 & 136.8822897 & 471.04013 \\
\hline
GPBB & 2.500841875 & 14.11177175 & 53.84681762 & 184.9348276 \\
\hline
\end{tabular}
|
A re-examination to the SCoTLASS problems for SPCA and two projection-based methods for them
|
The solving speed comparison of different constrained algorithms for $m$ is fixed at 500 (in seconds)
| null |
math.ST, stat.TH
|
|
2311.09497v1
|
\begin{tabular}{|l|c|}
\hline
$\alpha_f$ (Objective Quality Variance) & 0.581\\ \hline
$\alpha_{b,1} / \alpha_f$ (Meta-Reviewer Offset Variance) & 0.458 \\ \hline
$\alpha_{b,2} / \alpha_f$ (Reviewer Offset Variance) & 0.432 \\ \hline
$\alpha_{b,3} / \alpha_f$ (Author Offset Variance) & 0.780 \\ \hline
$\alpha_{b,4} / \alpha_f$ (External Offset Variance) & 0.441 \\ \hline
$\sigma^2 / \alpha_f$ (Subjective Score Variance) & 1.467 \\ \hline
\end{tabular}
|
Peer Reviews of Peer Reviews: A Randomized Controlled Trial and Other Experiments
|
Fit parameters of linear calibration model.
|
['\\newcommand{\\ns}[1]{{\\color{blue} \\textbf{ns: #1}}}', '\\newcommand{\\is}[1]{{\\color{green} \\textbf{is: #1}}}', '\\newcommand{\\ag}[1]{{\\color{red} \\textbf{ag: #1}}}', '\\newcommand{\\confx}{NeurIPS 2022{}}', '\\newcommand{\\externalrev}{external reviewers}', '\\newcommand{\\understanding}{understanding}', '\\newcommand{\\coverage}{coverage}', '\\newcommand{\\constructiveness}{constructiveness}', '\\newcommand{\\substantiation}{substantiation}', '\\newcommand{\\indicator}{\\mathbb{I}}', '\\newcommand{\\shortmean}{268.1}', '\\newcommand{\\longmean}{754.5}', '\\newcommand{\\test}{\\tau}', '\\newcommand{\\numreview}{n}', '\\newcommand{\\revset}{\\mathcal{R}}', '\\newcommand{\\cntrrev}{\\revset^{\\text{short}}}', '\\newcommand{\\tstrev}{\\revset^{\\text{long}}}', '\\newcommand{\\tstscore}{X}', '\\newcommand{\\cntrscore}{Y}', '\\newcommand{\\longScore}{x^{\\ell}}', '\\newcommand{\\shortScore}{x^{s}}', '\\newcommand{\\paper}{p}', '\\newcommand{\\longSet}{L_\\paper}', '\\newcommand{\\shortSet}{S_\\paper}', '\\newcommand{\\acceptScore}{x_i^{\\text{accept}}}', '\\newcommand{\\rejectScore}{x_i^{\\text{reject}}}']
|
cs.DL, cs.GT
|
|
2310.16470v1
|
\begin{tabular}{crrr|crrr}
\hline
& Coefficient & Std. err. & $t$ value & & Coefficient & Std. err. & $t$ value\\
\hline
$\gamma$ & 216.41 & 0.81 & $^{*}$268.16 & & & & \\
$\alpha_{\rm{c}1}$ & 161.30 & 9.51 & $^{*}$16.97 & $\alpha_{\rm{s}1}$ & 138.52 & 11.52 & $^{*}$12.02 \\
$\alpha_{\rm{c}2}$ & -30.96 & 2.67 & $^{*}$-11.61 & $\alpha_{\rm{s}2}$ & 1.29 & 3.13 & 0.41 \\
$\alpha_{\rm{c}3}$ & -2.75 & 18.46 & -0.15 & $\alpha_{\rm{s}3}$ & -46.88 & 20.04 & $^{*}$-2.34 \\
$\alpha_{\rm{c}4}$ & -12.54 & 1.53 & $^{*}$-8.19 & $\alpha_{\rm{s}4}$ & -4.75 & 1.61 & $^{*}$-2.95 \\
$\alpha_{\rm{c}5}$ & 95.96 & 41.68 & $^{*}$2.30 & $\alpha_{\rm{s}5}$ & 35.37 & 41.88 & 0.84 \\
$\alpha_{\rm{c}6}$ & -9.17 & 5.14 & -1.78 & $\alpha_{\rm{s}6}$ & -9.70 & 4.93 & $^{*}$-1.97 \\
$\alpha_{\rm{c}7}$ & 71.91 & 35.59 & $^{*}$2.02 & $\alpha_{\rm{s}7}$ & 30.41 & 34.64 & 0.88 \\
$\alpha_{\rm{c}8}$ & -30.56 & 6.18 & $^{*}$-4.95 & $\alpha_{\rm{s}8}$ & 3.95 & 6.10 & 0.65 \\
$\beta_{\rm{c}2}$ & -16.49 & 1.42 & $^{*}$-11.61 & $\beta_{\rm{s}2}$ & -0.36 & 1.67 & -0.21 \\
$\beta_{\rm{c}4}$ & -14.96 & 2.03 & $^{*}$-7.38 & $\beta_{\rm{s}4}$ & -10.02 & 2.19 & $^{*}$-4.58 \\
$\beta_{\rm{c}6}$ & -11.45 & 5.64 & $^{*}$-2.03 & $\beta_{\rm{s}6}$ & 10.08 & 5.88 & 1.71 \\
$\beta_{\rm{c}8}$ & -20.13 & 6.34 & $^{*}$-3.18 & $\beta_{\rm{s}8}$ & -25.09 & 6.48 & $^{*}$-3.87 \\
\hline
\end{tabular}
|
Understanding Impact of Angle in Urban Transportation
|
Estimated parameters of Case 3.
| null |
stat.AP
|
|
2312.09955v1
|
\begin{tabular}{ c c c c c }
\hline
Metrics & Fattal's & DehazeNet & Gao \emph{et al.} & Proposed \\
\hline
MPSNR & 17.74 & 22.39 & 23.26 & 26.83 \\
MSSIM & 0.803 & 0.817 & 0.917 & 0.924 \\
MFSIM & 0.901 & 0.952 & 0.921 & 0.978 \\
\hline
\\
\end{tabular}
|
DHFormer: A Vision Transformer-Based Attention Module for Image Dehazing
|
Mean PSNR, SSIM, and FSIM of the given methods over the HSTS dataset.
| null |
cs.CV, eess.IV
|
|
2311.18446v1
|
\begin{tabular}{cccc}
\hline
& \multicolumn{1}{c}{Beran} & \multicolumn{2}{c}{SBeran} \\ \noalign{\hrule height 1pt}
\hspace*{0.2cm} $x$ \hspace*{0.2cm} & \hspace*{0.2cm} $ h^*$ \hspace*{0.2cm} & $h_2^*$ & $g_2^*$ \\
40 & 4.765306 & 5.507370 & 1.266695 \\
60 & 4.571429 & 5.548651 & 0.784956 \\
80 & 13.387760 & 30.000000 & 2.348188 \\
\hline
\end{tabular}
|
Length-of-stay times in hospital for COVID-19 patients using the smoothed Beran's estimator with bootstrap bandwidth selection
|
Bootstrap bandwidth for Beran's estimation and the smoothed Beran's estimation of the conditional survival function of the time in ward for some different values of age.
| null |
stat.CO, stat.AP, stat.ME
|
|
2305.17922v1
|
\begin{tabular}{|l|r|r||r|r|} \hline
& \multicolumn{2}{|c||}{IM EN-prior} & \multicolumn{2}{c|}{IM PC-prior} \\ \hline
RMSE & $4.22$ & $4.24$ & $4.21$ & $4.21$\\ \hline
Bias & $0.71$ & $0.68$ & $0.73$ & $0.86$ \\ \hline
& \multicolumn{1}{|c|}{Base} & \multicolumn{1}{c||}{Feedback} & \multicolumn{1}{c|}{Base} & \multicolumn{1}{c|}{Feedback} \\ \hline \hline
& \multicolumn{2}{|c||}{PM EN-prior} & \multicolumn{2}{c|}{PM PC-prior} \\ \hline
RMSE & $2.90$ & $2.76$ & $3.39$ & $2.77$\\ \hline
Bias & $0.13$ & $0.05$ & $0.11$ & $0.11$ \\ \hline
& \multicolumn{1}{|c|}{Base} & \multicolumn{1}{c||}{Feedback} & \multicolumn{1}{c|}{Base} & \multicolumn{1}{c|}{Feedback} \\ \hline \hline
\end{tabular}
|
Bayesian feedback in the framework of ecological sciences
|
Median values of the RMSE along the $108$ scenarios for the median posterior prediction values.
|
['\\newcommand{\\iosu}{\\color{orange}}', '\\newcommand{\\david}{\\color{orange}}']
|
stat.AP, 62P10
|
|
2310.02046v1
|
\begin{tabular}{|p{54mm}|p{54mm}|p{54mm}|}
\hline
\textbf{Examples that indicate that Comparison operator is used to find the target} & \textbf{Examples that indicate that Semantic understanding is used to find the target} & \textbf{Examples that indicate that Context awareness is used to find the target} \\ \hline
Both elements have "span" as one of their 'tag' attribute. & The text "Beauty, Health \& Hair" in the element with widget\_id "201" is closely related to the text "Health \& Beauty" in the given element. & The 'location', 'shape', 'is\_button', and 'neighbor\_text' attributes in both elements have similar values, indicating that they might be close to each other on the layout of the website and have a similar structure. \\ \hline
Both elements have "a" or "span" as their 'tag' attribute. & The text "Sign up" in the element with widget\_id "8065" is closely related to the text "Log in" in the given element, as both texts are related to account actions. & Although the given element has an 'href' attribute and the element with widget\_id "201" does not, this could be a minor change during the evolution of the web application, and the overall similarity of other attributes makes it the best candidate. \\ \hline
The 'class' attribute values in both elements are very similar, containing "nav-logo-base" and "nav-sprite". & The text "Order Status" in the element with widget\_id "1823" is not exactly the same as the text "Shopping History" in the given element, but both texts are related to account and order information, which leads to the assumption that they are similar in purpose. & Both elements have a similar 'location' attribute, indicating that they might be close to each other on the layout of the website. \\ \hline
The 'href' attribute in both elements is the same, as they both point to the same URL ("https://www.cnn.com/us"). & The text "Account" in the element with widget\_id "1815" is not exactly the same as "Store Locator" in the given element, but there's no other candidates with the text "Store Locator". In this case, "Account" may represent a location-related functionality. & Both elements have relatively large 'area' and 'shape' attributes, suggesting that they are both prominent elements on the webpage. \\ \hline
The 'location' attribute in both elements is the same: "20,20". & The text "Upgrade to premium" in the element with widget\_id "8817" is closely related to the text "Get premium" in the given element. & The 'location' attribute indicates that they might be far apart in the layout of the website, but the 'neighbor\_text' attribute has some overlapping words (e.g., "spotify", "support", "download", "premium"). \\ \hline
The text "Enterprise" is exactly the same in both elements. & The text "Start your free trial" in the element with widget\_id "3214" is closely related to the text "Try free for 30 days" in the given element. & Both elements have a similar 'location' attribute with only a minor difference in the x coordinate, indicating that they are situated near each other on the layout of the website. \\ \hline
The 'id' attribute in both elements is the same: "hero-banner-get-office-link". & The text "Support" in the element with widget\_id "10880" is closely related to the text "Help" in the given element. Both serve the same purpose of assisting users with issues or questions. & Despite some differences in 'xpath', both elements seem to be part of the navigation menu, as suggested by the 'neighbor\_text' attribute. \\ \hline
The text "Find jobs" in the element with widget\_id "7973" is identical to the text "Find Jobs" in the given element. & The 'neighbor\_text' attribute is similar in both elements, with both mentioning social platforms like "twitter", "instagram", "snapchat", "youtube", and "the espn daily podcast". & The text "Items in cart" in the given element is related to the functionality of a shopping cart, and the element with widget\_id "12341" also has a cart-related functionality, although the text is not present. \\ \hline
Both elements share the same 'href' attribute, which points to "https://www.instructure.com/". & The text "Claims Support" in the element with widget\_id "11882" is closely related to the text "Delivery Issues" in the given element, as both deal with issues regarding deliveries. & The 'xpath' and 'neighbor\_text' attributes also show similarities, suggesting that they are part of the same group of links within the footer of the website. \\ \hline
The text "Cart" is present in both elements. & The text "Plans \& Pricing" in the element with widget\_id "13858" is closely related to the text "PLANS" in the given element. & Although the 'href' attribute is different, the change could be due to the updated web application using a different method to handle account sign-in functionality. \\ \hline
\end{tabular}
|
Improving web element localization by using a large language model
|
Example motivations from GPT-4 classified as comparison operator, semantic understanding, or context awareness.
| null |
cs.SE
|
|
2309.00239v2
|
\begin{tabular}{lll}
\hline
Parameters & Montreal$^{1}$ & La Plata\\
\hline
\Teff & $1460-150\,000$\,K & $2750-80\,000$\,K\\
\logg & $6.7-9.3$ & $6-9.45$\\
Mass ($\rm{M_{WD}}$) & $0.2-1.3$\,\Msun & $0.2-1.3$\,\Msun\\
Core composition & CO core & He Core $(\rm{M_{WD}}<0.5\,\Msun)^{2}$\\
& entire mass range & CO core $(0.5 \leq \rm{M_{WD}} \leq 1.0 \,\Msun)^{3}$\\
& & O-Ne core $(\rm{M_{WD}}\geq 1.1\,\Msun)^{4}$\\
H envelope mass & $\sim10^{-4}$ & $\sim10^{-3}$ ($\rm{M_{WD}} \leq 0.32\,\Msun)^{2}$\\
($\rm{M_{H}}/M_{WD}$) & entire mass range & $\sim10^{-3.5}-10^{-4.5}$ \\
&&$(0.5 \leq \rm{M_{WD}} \leq 0.88\,\Msun)^{3}$\\
& & $\sim10^{-6} (\rm{M_{WD}}\geq 1.1\,\Msun)^{4}$\\
\hline
\label{tab:M-Rrel}
\end{tabular}
|
An HST COS ultra-violet spectroscopic survey of 311 DA white dwarfs.I. Fundamental parameters and comparative studies
|
Model parameters of the two mass-radius relations from the Montreal and La Plata models for a progenitor metallicity of $Z=0.02$.
|
['\\newcommand{\\cmark}{\\ding{50}}%', '\\newcommand{\\xmark}{\\ding{53}}%', '\\newcommand{\\Y}{\\checkmark}%', '\\newcommand{\\N}{\\xmark}%', '\\newcommand{\\vdag}{(v)^\\dagger}', '\\newcommand\\aastex{AAS\\TeX}', '\\newcommand\\latex{La\\TeX}', '\\newcommand{\\Line}[3]{\\Ion{#1}{#2}~#3\\,\\AA}', '\\newcommand{\\Lines}[3]{\\Ion{#1}{#2}\\,#3\\,\\AA}', '\\newcommand{\\Ion}[2]{#1{\\,\\sc#2}}', '\\newcommand{\\orcid}[1]{\\href{https://orcid.org/#1}{\\includegraphics[width=10pt]{orcid.pdf}}}', '\\newcommand{\\Teff}{\\mbox{$T_{\\mathrm{eff}}$}}', '\\newcommand{\\logg}{\\mbox{$\\log g$}}', '\\newcommand{\\Msun}{\\mbox{$\\mathrm{M_\\odot}$}}', '\\newcommand{\\totalnumber}{311}', '\\newcommand{\\SIAM}{SIAM Journal on Numerical Analysis}']
|
astro-ph.SR
|
|
2311.13498v1
|
\begin{tabular}{ |c| }
\hline
$\Omega_{\rm m0}h^2 = 0.139 \pm 0.017$ \\
\hline
\end{tabular}
|
Unveiling $Ω_{\rm m0}$ independently: a journey and consistency quest with first-order perturbation theory
|
The estimated value of the $\Omega_{\rm m0}h^2$ parameter and the associated 1$\sigma$ error.
|
['\\newcommand*{\\pb}{\\textcolor{red}}', '\\newcommand{\\Mpl}{M_{\\textrm{Pl}}}', '\\newcommand{\\orcid}[1]{\\href{https://orcid.org/#1}{\\,\\includegraphics[width=8px]{ORCID.eps}}}']
|
astro-ph.CO, gr-qc
|
|
2310.20138v2
|
\begin{tabular}{c|c|c|cc|cc|c}
\hline
\multirow{2}*{Models} & \multirow{2}*{\shortstack{\# Edited Neurons}} & \multirow{2}*{Time} &\multicolumn{2}{c|}{Before Editing} & \multicolumn{2}{c|}{After Editing} & \multirow{2}*{Reduction Rate} \\
\cline{4-7}
& & & Valid-PPL & Exposure & Valid-PPL & Exposure \\
\hline
bert-small & 100 & 0.26h & 4.09 & 5.10 & 4.57 & 3.39 & 33.5\% \\
bert-base & 200 & 1.59h & 3.07 & 15.74 & 3.11 & 9.78 & 37.86\%\\
bert-large & 400 & 7.66h & 2.93 & 18.10 & 2.98 & 7.63 & 57.84\%\\
\hline
\end{tabular}
|
DEPN: Detecting and Editing Privacy Neurons in Pretrained Language Models
|
The privacy leakage risk reduction rate for models of different sizes.
|
['\\newcommand{\\theHalgorithm}{\\arabic{algorithm}}']
|
cs.CR, cs.CL
|
|
2310.14702v2
|
\begin{tabular}{c|l}
\hline
Blocks & \multicolumn{1}{c}{Settings} \\
\hline
Voxel Feature Encoder (VFE) & use normalization and absolute 3D coordinates, 64 filters \\
\hline
PointPillar Scatter & 64-channel output \\
\hline
\multirow{6}{*}{BEV backbone} & ResNet backbone: \\
& layers=$[3, 4, 5]$ \\
& strides=$[2, 2, 2]$ \\
& filters=$[64, 128, 256]$\\
& upsample\_strides=$[1, 2, 4]$ \\
& upsample\_filters=$[128, 128, 128]$ \\
\hline
Shrink Header & shrink from 384 channels to 256 channels with stride 3 \\
\hline
Detect Head & 256-channel output with 2 anchors \\
\hline
\end{tabular}
|
BM2CP: Efficient Collaborative Perception with LiDAR-Camera Modalities
|
Details of unified network architecture.
| null |
cs.CV, cs.AI, cs.RO
|
|
2307.05467v1
|
\begin{tabular}{p{4.0cm}p{2.3cm}}
\hline
%\multicolumn{4}{|c|}{Country List} \\
\hline
$\kappa$ & $T_c$ \\
\hline
1.0 & 1.728(5) \\
%\hline
0.8 & 1.894(5) \\
%\hline
0.6 & 2.041(5) \\
%\hline
0.4 & 2.161(5) \\
%\hline
0.2 & 2.241(5) \\
%\hline
0.001 & 2.269(5) \\
\hline
\hline
\end{tabular}
|
Is Kaniadakis $κ$-generalized statistical mechanics general?
|
Estimates of critical temperatures of 2D Ising model with the $\kappa$-generalized Metropolis rate in Eq.\ (\ref{ising-metropolis-kaniadakis}), for some values of $\kappa$. Estimates of the critical temperature $T_c$ were obtained from the crossings of Binder Cumulant, as seen in panel (a) of Fig.\ \ref{ising-collapses}.
| null |
hep-th, cond-mat.stat-mech, math-ph, math.MP
|
|
2312.15382v1
|
\begin{tabular}{|c|c|c|c|}
\hline
Nodes & Reference & Computed value & Error \\
\hline
(2, 10, 12) & 0.5389714947317054 & 0.5386865717999949 & $2.84922 \cdot 10^{-4} $ \\
(2, 10, 14) & 0.5953434982171909 & 0.5951583168446205 & $1.85181 \cdot 10^{-4}$ \\
(4, 12, 18) & 0.7121629047455362 & 0.7125335341761537 & $3.70629 \cdot 10^{-4}$ \\
(6, 16, 24) & 0.7718690862645192 & 0.7711328152834294 & $7.36271 \cdot 10^{-4}$ \\
(8, 22, 32) & 0.8319009599091923 & 0.8314586378776063 & $4.42322 \cdot 10^{-4}$ \\
\hline
\end{tabular}
|
Efficient simulation of mixed boundary value problems and conformal mappings
|
Moduli of quadrilaterals \( (Q_{B}; e^{im\pi/24}\), \(e^{in\pi/24}\), \(e^{ir\pi/24}, 1) \) for several integer triples \( (m, n, r) \)
| null |
math.NA, cs.NA, math.CV, math.PR, 30-08, 30C20, 31-08, 31A15, 60J65, 65C05, G.1.8; G.3; I.3.5
|
|
2308.06279v2
|
\begin{tabular}{lccccc} \hline
& L13 & L14 & L15 & L16 & L17 \\
VARIABLES & W & W & W & W & W \\ \hline
& & & & & \\
Closed & -0.465** & -0.448** & -0.670 & -0.391 & -0.476** \\
& (0.211) & (0.216) & (0.498) & (0.240) & (0.221) \\
Home Team & & & & & YES \\
Away Team & & & & & YES \\
Calendar & & & & & YES \\
Constant & -0.243*** & -0.260*** & 0.218* & -0.374*** & -0.445 \\
& (0.0238) & (0.0520) & (0.119) & (0.0583) & (0.332) \\
& & & & & \\
Observations & 7,261 & 1,605 & 303 & 1,302 & 7,261 \\ \hline
\multicolumn{6}{c}{ Standard errors in parentheses} \\
\multicolumn{6}{c}{ *** p$<$0.01, ** p$<$0.05, * p$<$0.1} \\
\end{tabular}
|
Visitors Out! The Absence of Away Team Supporters as a Source of Home Advantage in Football
|
Logits regressions of models in Table \ref{tab:REG_ADD1}
| null |
econ.GN, q-fin.EC
|
|
2305.09065v2
|
\begin{tabular}{c || c | c | c | c | c | c | c | c | c | c }
\hline
$a/b$ & $10^{-4}$ & 0.01 & 0.05 & 0.10 & 0.20 & 0.25 & 0.30 & 0.50 & 0.75 & 0.99 \\ [0.5ex]
\hline%\hline
$n=1$ & 0.0979 & 0.1784 & 0.2503 & 0.3028 & 0.3832 & 0.4191 & 0.4537 & 0.5906 & 0.7766 & 0.9900 \\
$n=2$ & 0.1086 & 0.2158 & 0.3228 & 0.4038 & 0.5197 & 0.5660 & 0.6077 & 0.7463 & 0.8841 & 0.9957 \\
$n=3$ & 0.1148 & 0.2406 & 0.3673 & 0.4529 & 0.5668 & 0.6110 & 0.6504 & 0.7779 & 0.9001 & 0.9963 \\
$n=4$ & 0.1194 & 0.2582 & 0.3884 & 0.4743 & 0.5869 & 0.6302 & 0.6684 & 0.7909 & 0.9066 & 0.9966 \\
%$n=5$ & 0.1230 & 0.2686 & 0.4004 & 0.4864 & 0.5981 & 0.6408 & 0.6783 & 0.7981 & 0.9102 & 0.9967 \\
$n=8$ & 0.1310 & 0.2836 & 0.4175 & 0.5035 & 0.6139 & 0.6556 & 0.6922 & 0.8080 & 0.9150 & 0.9969 \\
%$n=\infty$ & 0.1456 & 0.3073 & 0.4438 & 0.5296 & 0.6376 & 0.6778 & 0.7130 & 0.8225 & 0.9221 & 0.9972 \\
\hline
\end{tabular}
|
Robust Auction Design with Support Information
|
Maximin ratio as a function of relative support information $a/b$ for various numbers of buyers $n$.
| null |
econ.TH, cs.GT, cs.MA
|
|
2302.06098v1
|
\begin{tabular}{l|cccccc}
\hline
Arrangement & B-1 & B-4 & M & R & C & S \\
\hline
LSA + SA & 81.1 & 39.6 & 29.1 & 59.0 & 133.4 & \textbf{22.8} \\
SA + LSA & \textbf{81.2} & \textbf{39.7} & \textbf{29.3} & \textbf{59.1} & \textbf{133.6} & \textbf{22.8} \\
SA \& LSA & 81.0 & 39.5 & 28.9 & 59.0 & 132.7 & 22.7 \\
\hline
\end{tabular}
|
Towards Local Visual Modeling for Image Captioning
|
Ablation studies on various arrangements of SA and LSA. + is sequential connection, \& represents parallel connection.
| null |
cs.CV, cs.MM
|
|
2311.11231v2
|
\begin{tabular}{c|c|c|c|c|cc}
\hline
\multirow{2}[4]{*}{Industry} & \multirow{2}[4]{*}{Total} & \multicolumn{5}{c}{Percentage} \\
\cline{3-7} & & $G_1$ & \multicolumn{1}{c|}{$R_1$} & \multicolumn{1}{c|}{$R_2$} & $R_3$ & $R_4$ \\
\hline
$S_1$& 1780 & 29.2 & 85.9 & 5.9 & 6.7 & 6.8 \\
$S_2$& 566 & 34.2 & 88.3 & 5.9 & 3.5 & 11.3 \\
$S_3$& 764 & 26.4 & 72.6 & 7.8 & 16.5 & 7.5 \\
$S_4$& 797 & 71.6 & 74.6 & 16.0 & 7.3 & 9.0 \\
$S_5$& 988 & 68.1 & 78.0 & 16.3 & 4.0 & 9.8 \\
$S_6$& 835 & 50.3 & 83.1 & 9.9 & 4.3 & 11 \\
% \hline
% & Total & 181,759 & 121,908 & 19,937 & 10,615 & 29,299 \\
\hline
\end{tabular}
|
Workforce pDEI: Productivity Coupled with DEI
|
Employed Persons by Detailed Occupation .
| null |
econ.GN, q-fin.EC
|
|
2312.07312v1
|
\begin{tabular}{c|c|c|c}
& \(\Lambda < 0\) & \(\Lambda = 0\) & \(\Lambda > 0\)\\[0pt]
\hline
\(\kappa = 1\) & no solution & no solution & de Sitter\\[0pt]
& & & \(a = \cosh(q t) / q\)\\[0pt]
\hline
\(\kappa = 0\) & no solution & Minkowski & de Sitter\\[0pt]
& & \(a = 1\) & \(a = \exp(q t)\)\\[0pt]
\hline
\(\kappa = -1\) & anti de Sitter & Minkowski & de Sitter\\[0pt]
& \(a = \sin(q t) / q\) & \(a = t\) & \(a = \sinh(q t) / q\)\\[0pt]
\end{tabular}
|
Inflationary scenarios in an effective polynomial affine model of gravity
|
\label{tab:summary-vacuum-friedmann-cosmologies}Classification of vacuum Friedmann cosmologies in General Relativity . The quantity \(q\) is defined as \(q = \sqrt{|\Lambda|/3}\).
|
['\\newcommand{\\Ag}{\\mathcal{A}}', '\\newcommand{\\Fg}{\\mathcal{F}}', '\\newcommand{\\Popl}{\\operatorname{Popl}}', '\\newcommand{\\R}{\\mathbb{R}}', '\\newcommand{\\Riem}{\\operatorname{Riem}}', '\\newcommand{\\Ric}{\\operatorname{Ric}}', '\\newcommand*{\\diag}{\\operatorname{diag}}', '\\newcommand{\\sgn}{\\operatorname{sgn}}', '\\newcommand{\\N}{\\ensuremath{\\mathscr{N}}}', '\\newcommand{\\W}{\\ensuremath{\\mathscr{W}}}', '\\newcommand{\\Op}{\\mathcal{O}}', '\\newcommand{\\we}{\\mathop{\\scriptstyle\\wedge}}', '\\newcommand*{\\de}[1]{\\mathop{\\mathrm{d}#1}\\nolimits}', '\\newcommand{\\dn}[2]{{\\mathrm{d}}^{#1}\\!{#2}\\;}', '\\newcommand{\\tors}[3]{\\mathcal{T}{}_{#1}{}^{#2}{}_{#3}}', "\\newcommand\\UTFSM{Departamento de F\\'isica, Universidad T\\'{e}cnica Federico Santa Mar\\'\\i a\\\\ Casilla 110-V, Valpara\\'iso, Chile}", "\\newcommand\\UTFSMmat{Departamento de Matem\\'aticas, Universidad T\\'{e}cnica Federico Santa Mar\\'\\i a\\\\ Casilla 110-V, Valpara\\'iso, Chile}", "\\newcommand\\CCTVal{Centro Cient\\'ifico Tecnol\\'ogico de Valpara\\'iso\\\\ Casilla 110-V, Valpara\\'\\i so, Chile}", "\\newcommand{\\UdelaR}{Instituto de F\\'isica, Facultad de Ciencias\\\\Igu\\'a 4225, esq. Mataojo, 11400 Montevideo, Uruguay.}", "\\newcommand{\\IFIC}{Departamento de F\\'isica Te\\'orica and IFIC, Centro Mixto Universidad de Valencia - CSIC\\\\ Universidad de Valencia, Burjassot-46100, Valencia, Spain.}"]
|
gr-qc, hep-th, math-ph, math.MP
|
|
2309.11390v1
|
\begin{tabular}{lcccccccccc}
\hline\hline
\noalign{\smallskip}
Observatory & Aperture & Filter & Date & Start & End & Length & Exp. Time & Airmass & Comp. & Precision\\
& (m) & & (UTC)& (UTC) & (UTC) & (min.) & (sec.) & Range & Stars (n) & (ppt/10 min) \\
\noalign{\smallskip}
\hline
\noalign{\smallskip}
Hazelwood & 0.32 & $i'$ & 2019-08-28 & 15:23 & 19:36 & 253 & 120 & 1.45 - 1.04 & 3 & 1.4 \\
Brierfield & 0.36 & B & 2019-11-05 & 11:07 & 18:01 & 414 & 180 & 1.46 - 1.10 - 1.33 & 4 & 2.6 \\
Evans & 0.36 & B & 2019-12-05 & 01:08 & 06:28 & 320 & 150 & 1.26 - 1.09 - 1.25 & 4 & 1.3 \\
\hline
\end{tabular}
|
TOI-858 B b: A hot Jupiter on a polar orbit in a loose binary
|
TFOP photometric follow-up observation log.
|
['\\newcommand{\\Nstar}{TOI-858\\,B}', '\\newcommand{\\NstarBTIC}{TIC-198008002}', '\\newcommand{\\Nplanet}{TOI-858\\,B\\,b}', '\\newcommand{\\NstarB}{TOI-858\\,A}', '\\newcommand{\\kms}{km\\,s$^{-1}$}', '\\newcommand{\\kmssquared}{km$^2\\,s^{-2}$}', '\\newcommand{\\ms}{m\\,s$^{-1}$}', '\\newcommand{\\flux}{erg\\, cm$^{2}$\\,s$^{-1}$}', '\\newcommand{\\luminosity}{erg\\,s$^{-1}$}', '\\newcommand{\\cmss}{cm\\,s$^{-2}$}', '\\newcommand{\\countss}{counts\\,s$^{-1}$}', '\\newcommand{\\gccc}{g\\,cm$^{-3}$}', '\\newcommand{\\masy}{mas\\,yr$^{-1}$}', '\\newcommand{\\mpl}{M$_{p}$}', '\\newcommand{\\rpl}{R$_{p}$}', '\\newcommand{\\teff}{$T_{\\rm eff}$}', '\\newcommand{\\arcsecpix}{arcsec\\,pixel$^{-1}$}', '\\newcommand{\\LSO}{La Silla Observatory}', '\\newcommand{\\PAR}{Paranal Observatory}', '\\newcommand{\\kepler}{{\\it Kepler}}', '\\newcommand{\\corot}{{\\it CoRoT}}', '\\newcommand{\\tess}{{\\small \\it TESS}}', '\\newcommand{\\plato}{{\\small \\it PLATO}}', '\\newcommand{\\gaia}{{\\it Gaia}}', '\\newcommand{\\JWST}{{\\small \\it JWST}}', '\\newcommand{\\NGTS}{{\\small \\it NGTS}}', '\\newcommand{\\EDRTHREE}{{\\small EDR3}}', '\\newcommand{\\TWOMASS}{{\\small 2MASS}}', '\\newcommand{\\WISE}{{\\small \\it WISE}}', '\\newcommand{\\exofast}{{\\it EXOFASTv2}}', '\\newcommand{\\emp}{\\textsc{SpecMatch-emp}}', '\\newcommand\\LEt[1]{\\textcolor{LimeGreen}{\\textbf{#1}}}']
|
astro-ph.EP
|
|
2307.12087v1
|
\begin{tabular}{|c|c|}
\hline
encoding & 734401 \\ \hline
round id & 1 \\ \hline
number of Pairs & 3 \\ \hline
number of Pongs or Kongs & 2 \\ \hline
number of Character tiles & 3 \\ \hline
number of wind tiles & 11 \\ \hline
number of legal actions & 3 \\ \hline
regret sum & [-0.598, 2.128, -1.356] \\ \hline
strategy sum & [1.359, 1.975, 0.667] \\ \hline
\end{tabular}
|
CFR-p: Counterfactual Regret Minimization with Hierarchical Policy Abstraction, and its Application to Two-player Mahjong
|
An Example of Nodes
| null |
cs.AI, econ.GN, q-fin.EC
|
|
2306.04992v1
|
\begin{tabular}{c|c|ccccccccc}
\hline \hline
Crust &Core & $M_{\rm max}[M_{\odot}]$ & $R_{\rm max}$[km] & $\rho_c\rm[fm^{-3}]$ & $R_{1.4}$[km] & $\Lambda_{1.4}$ & $R_{0.77}$[km] & $\rho_{0.77}\rm[fm^{-3}]$ \\
\hline
\multirow{3}*{$L=47$}
&$L=26$ & 1.93 & 10.10 & 1.23 & 11.61 & 316 & 11.50 & 0.34 \\
&$L=30$ & 1.93& 10.11 & 1.23 & 11.63 & 312 & 11.60 & 0.34 \\
&$L=40$ & 1.93 & 10.12 & 1.23 & 11.70 & 307 & 11.87 & 0.34 \\
\hline
\multirow{3}*{$L=110$}
&$L=26$ & 1.93 & 10.04 & 1.23 & 11.44 & 321 & 11.14 & 0.34 \\
&$L=30$ & 1.93& 10.04 & 1.23 & 11.47 & 318 & 11.24 & 0.34 \\
&$L=40$ & 1.93 & 10.06 & 1.23 & 11.55 & 308 & 11.52 & 0.34 \\
\hline \hline
\end{tabular}
|
The hadronic equation of state of HESS J1731-347 from the relativistic mean-field model with tensor coupling
|
Neutron star properties generated by the sets from Table. \ref{table.differL}.
|
['\\newcommand{\\nc}{\\newcommand} % new command', '\\newcommand{\\renc}{\\renewcommand} % re-new command', '\\newcommand{\\red}[1]{\\textcolor[rgb]{1.0,0.0,0.0}{\\bfseries #1}}', '\\newcommand{\\blue}[1]{\\textcolor[rgb]{0.0,0.0,1.0}{\\bfseries #1}}']
|
nucl-th, astro-ph.HE
|
|
2308.11991v1
|
\begin{tabular}{lllll}
\hline
& \multicolumn{2}{c}{\textbf{Rock-Paper-Scissors}} & \multicolumn{2}{c}{\textbf{Hanoi}} \\
& \multicolumn{1}{c}{\textbf{Before Interv.}} & \multicolumn{1}{c}{\textbf{After Interv.}} & \multicolumn{1}{c}{\textbf{Before Interv.}} & \multicolumn{1}{c}{\textbf{After Interv.}} \\
\hline
R-CBM Linear$^*$ & $49.46 \pm 1.11$ & $47.83 \pm 2.19$ & & \\
R-CBM Deep$^*$ & $51.35 \pm 2.00$ & $82.02 \pm 6.34$ & & \\
R-DCR$^*$ & $54.47 \pm 1.64$ & $100.00 \pm 0.00$ & & \\
CBM Linear & $49.41 \pm 0.89$ & $47.75 \pm 1.81$ & & \\
CBM Deep$^*$ & $50.83 \pm 0.93$ & $47.78 \pm 1.94$ & & \\
DCR & $51.22 \pm 1.26$ & $49.07 \pm 1.60$ & & \\
\hline
\end{tabular}
|
Relational Concept Based Models
|
\textbf{CBMs response to interventions}.
|
['\\newcommand{\\note}[1]{\\textcolor{red}{#1}}', '\\newcommand{\\mc}{\\mathcal}', '\\newcommand{\\B}{\\mathbf}']
|
cs.LG, cs.AI, cs.NE
|
|
2305.08559v3
|
\begin{tabular}{l|l|l}
\hline
& Later Sunset Counties (Robust) & Manipulation \\ \hline
County Index & $0.083^{***}(0.024)$ & No \\ \hline
Family Unity & $0.098^{***}(0.022)$ & No \\ \hline
Community Health & $-0.0443^{**}(0.019)$ & No \\ \hline
Institutional Health & $0.073^{**}(0.024)$ & No \\ \hline
Efficacy & $0.047^{**}(0.019)$ & No \\ \hline
\end{tabular}
|
Designing Discontinuities
|
Designed Discontinuity Counterfactual Prediction on Social Capital: Local non-parametric regression discontinuity estimates
|
['\\newcommand{\\lav}[1]{\\textcolor{blue}{#1}}', '\\newcommand{\\ibtihal}[1]{\\textcolor{red}{#1}}']
|
cs.IT, cs.LG, econ.EM, math.IT
|
|
2311.03120v2
|
\begin{tabular}{ll@{\hspace{4em}}ll}
\dag & \verb"\dag" & \S & \verb"\S" \\
\copyright & \verb"\copyright"& \ddag & \verb"\ddag"\\
\P & \verb"\P" & \pounds & \verb"\pounds" \\
\# & \verb"\#" & \$ & \verb"\$"\\
\% & \verb"\%" & \& & \verb"\&" \\
\_ & \verb"\_" & \{ & \verb"\{" \\
\} & \verb"\}" & & \\
\end{tabular}
|
Near-Infrared Ca II Triplet As An Stellar Activity Indicator: Library and Comparative Study
|
Miscellaneous symbols
|
['\\newcommand{\\head}[1]{\\subsubsection*{#1}}', '\\newcommand{\\btx}{\\textsc{Bib}\\TeX}', '\\newcommand{\\thestyle}{\\texttt{\\filename}}']
|
astro-ph.SR, astro-ph.EP
|
|
2312.14692v1
|
\begin{tabular}{c|l}
0 & No measures\\
1 & Screening\\
2 & Quarantine arrivals from high-risk regions\\
3 & Ban on high-risk regions\\
4 & Total border closure\\
\end{tabular}
|
Socioeconomic reorganization of communication and mobility networks in response to external shocks
|
International travel controls
| null |
physics.soc-ph
|
|
2312.10819v1
|
\begin{tabular}{|c|c|c|c|c|}
\hline
Metric & Precision (UA) & Recall (PA) & True Positive Rate & False Positive Rate \\
\hline \hline
Stable cropland & $0.42 \pm 0.14$ & $0.44 \pm 0.10$ & $0.32$ & $0.11$\\
Stable non-crop & $0.83 \pm 0.05$ & $0.75 \pm 0.04$ & $0.72$ & $0.38$ \\
Cropland gain & $0.18 \pm 0.12$ & $0.25 \pm 0.16$ & $0.33$ & $0.10$ \\
Cropland loss & $0.10 \pm 0.09$ & $0.27 \pm 0.25$ & $0.44$ & $0.11$ \\
\hline
\end{tabular}
|
Satellite Data Shows Resilience of Tigrayan Farmers in Crop Cultivation During Civil War
|
Accuracy metrics for four-class cropland change reference sample in Southern zone of Tigray. Overall accuracy is $0.65 \pm 0.04$.
| null |
cs.CY
|
|
2308.15553v1
|
\begin{tabular}{lrrrrl}
{} & length (cm) & width (cm) \\
sepal & 5.4 & 3.0 & \\
petal & 4.5 & 1.5 & \\
\end{tabular}
|
Dimensionality Reduction Using pseudo-Boolean polynomials For Cluster Analysis
|
Transformed instance\label{Tab:Tcr_restructured}
| null |
cs.IR, cs.LG, 62H30 (Primary), E.4; G.2.1
|
|
2308.02849v1
|
\begin{tabular}{lrccccccccc}
\hline\hline
Line & \multicolumn{1}{c}{$\lambda$} & $L_\mathrm{flx}$ & $L_\mathrm{lum}$\\
& \multicolumn{1}{c}{[nm]} & [erg s$^{-1}$ cm$^{-2}$] & [L$_\odot$] \\
\hline
H15 & 371.20 & \sci{3.12}{-14} $\pm$ \sci{7.10}{-16} & \sci{2.35}{-5} $\pm$ \sci{5.33}{-7}\\
H14 & 372.19 & \sci{4.58}{-14} $\pm$ \sci{5.49}{-16} & \sci{3.44}{-5} $\pm$ \sci{4.12}{-7}\\
H13 & 373.44 & \sci{7.42}{-14} $\pm$ \sci{5.37}{-16} & \sci{5.57}{-5} $\pm$ \sci{4.03}{-7}\\
H12 & 375.02 & \sci{8.54}{-14} $\pm$ \sci{6.86}{-16} & \sci{6.41}{-5} $\pm$ \sci{5.15}{-7}\\
H11 & 377.06 & \sci{1.95}{-13} $\pm$ \sci{9.40}{-16} & \sci{1.47}{-4} $\pm$ \sci{7.06}{-7}\\
H10 & 379.79 & \sci{2.87}{-13} $\pm$ \sci{9.88}{-16} & \sci{2.15}{-4} $\pm$ \sci{7.42}{-7}\\
H9 & 383.54 & \sci{4.02}{-13} $\pm$ \sci{1.07}{-15} & \sci{3.02}{-4} $\pm$ \sci{8.02}{-7}\\
H8 & 388.90 & \sci{7.12}{-13} $\pm$ \sci{1.13}{-15} & \sci{5.35}{-4} $\pm$ \sci{8.50}{-7}\\
Ca II K & 393.37 & \sci{7.46}{-13} $\pm$ \sci{8.80}{-16} & \sci{5.60}{-4} $\pm$ \sci{6.61}{-7}\\
Ca II H & 396.85 & \sci{7.07}{-13} $\pm$ \sci{7.95}{-16} & \sci{5.31}{-4} $\pm$ \sci{5.97}{-7}\\
H$\epsilon$ & 397.01 & \sci{4.97}{-13} $\pm$ \sci{7.93}{-16} & \sci{3.73}{-4} $\pm$ \sci{5.95}{-7}\\
He I & 402.62 & \sci{4.42}{-14} $\pm$ \sci{4.39}{-16} & \sci{3.32}{-5} $\pm$ \sci{3.29}{-7}\\
H$\delta$ & 410.17 & \sci{9.47}{-13} $\pm$ \sci{9.99}{-16} & \sci{7.11}{-4} $\pm$ \sci{7.50}{-7}\\
H$\gamma$ & 434.05 & \sci{1.04}{-12} $\pm$ \sci{8.84}{-16} & \sci{7.81}{-4} $\pm$ \sci{6.64}{-7}\\
He I & 447.15 & \sci{8.84}{-14} $\pm$ \sci{3.88}{-16} & \sci{6.64}{-5} $\pm$ \sci{2.92}{-7}\\
He II & 468.58 & \sci{3.83}{-14} $\pm$ \sci{2.74}{-16} & \sci{2.88}{-5} $\pm$ \sci{2.06}{-7}\\
He I & 471.31 & \sci{1.27}{-14} $\pm$ \sci{2.19}{-16} & \sci{9.54}{-6} $\pm$ \sci{1.65}{-7}\\
H$\beta$ & 486.13 & \sci{1.10}{-12} $\pm$ \sci{8.45}{-16} & \sci{8.28}{-4} $\pm$ \sci{6.35}{-7}\\
He I Fe I & 492.19 & \sci{7.00}{-14} $\pm$ \sci{2.95}{-16} & \sci{5.25}{-5} $\pm$ \sci{2.22}{-7}\\
He I & 501.57 & \sci{2.12}{-14} $\pm$ \sci{1.95}{-16} & \sci{1.59}{-5} $\pm$ \sci{1.46}{-7}\\
He I & 587.56 & \sci{1.16}{-13} $\pm$ \sci{3.15}{-16} & \sci{8.68}{-5} $\pm$ \sci{2.36}{-7}\\
Na I & 589.00 & \sci{3.52}{-14} $\pm$ \sci{1.96}{-16} & \sci{2.64}{-5} $\pm$ \sci{1.47}{-7}\\
Na I & 589.59 & \sci{2.20}{-14} $\pm$ \sci{1.86}{-16} & \sci{1.66}{-5} $\pm$ \sci{1.39}{-7}\\
H$\alpha$ & 656.28 & \sci{1.79}{-12} $\pm$ \sci{5.37}{-16} & \sci{1.35}{-3} $\pm$ \sci{4.03}{-7}\\
He I & 667.82 & \sci{4.65}{-14} $\pm$ \sci{1.93}{-16} & \sci{3.49}{-5} $\pm$ \sci{1.45}{-7}\\
He I & 706.52 & \sci{2.47}{-14} $\pm$ \sci{1.33}{-16} & \sci{1.86}{-5} $\pm$ \sci{1.00}{-7}\\
O I & 777.31 & \sci{3.26}{-14} $\pm$ \sci{1.44}{-16} & \sci{2.45}{-5} $\pm$ \sci{1.08}{-7}\\
O I & 844.64 & \sci{2.30}{-14} $\pm$ \sci{1.53}{-16} & \sci{1.73}{-5} $\pm$ \sci{1.15}{-7}\\
Ca II & 849.80 & \sci{1.82}{-13} $\pm$ \sci{1.80}{-16} & \sci{1.37}{-4} $\pm$ \sci{1.35}{-7}\\
Ca II & 854.21 & \sci{2.22}{-13} $\pm$ \sci{1.78}{-16} & \sci{1.67}{-4} $\pm$ \sci{1.33}{-7}\\
Ca II & 866.21 & \sci{1.86}{-13} $\pm$ \sci{1.79}{-16} & \sci{1.40}{-4} $\pm$ \sci{1.34}{-7}\\
Pa10 & 901.49 & \sci{1.17}{-14} $\pm$ \sci{9.80}{-17} & \sci{8.77}{-6} $\pm$ \sci{7.36}{-8}\\
Pa9 & 922.90 & \sci{2.40}{-14} $\pm$ \sci{1.57}{-16} & \sci{1.80}{-5} $\pm$ \sci{1.18}{-7}\\
Pa8 & 954.60 & \sci{6.64}{-14} $\pm$ \sci{2.11}{-16} & \sci{4.99}{-5} $\pm$ \sci{1.58}{-7}\\
Pa$\delta$ & 1004.94 & \sci{7.23}{-14} $\pm$ \sci{4.05}{-16} & \sci{5.43}{-5} $\pm$ \sci{3.04}{-7}\\
Pa$\gamma$ & 1093.81 & \sci{9.86}{-14} $\pm$ \sci{2.52}{-16} & \sci{7.41}{-5} $\pm$ \sci{1.89}{-7}\\
Pa$\beta$ & 1281.81 & \sci{9.25}{-14} $\pm$ \sci{2.14}{-16} & \sci{6.95}{-5} $\pm$ \sci{1.61}{-7}\\
Br$\gamma$ & 2166.12 & \sci{1.14}{-14} $\pm$ \sci{6.74}{-17} & \sci{8.56}{-6} $\pm$ \sci{5.06}{-8}\\
\hline
\end{tabular}
|
Brightness and mass accretion rate evolution during the 2022 burst of EX~Lupi
|
Line flux and line luminosities for the 2022 July 29 observations. Their calculation in explained in Sect.~\ref{ss:acclum}.\label{table:lflx_llum_202207}
|
['\\newcommand{\\sci}[2]{\\ensuremath{#1\\times10^{#2}}}', '\\newcommand{\\exl}{\\object{EX~Lupi}}', '\\newcommand{\\macc}{\\ensuremath{\\dot{M}_{\\mathrm{acc}}}}', '\\newcommand{\\lacc}{\\ensuremath{L_{\\mathrm{acc}}}}', '\\newcommand{\\msun}{M\\ensuremath{_\\odot}}']
|
astro-ph.SR
|
|
2308.06540v1
|
\begin{tabular}{lrrr}
Parameter & Measured arrival flux & Trapezoid arrival flux & Rectangular arrival flux \\
\hline
$t_1$ (hour) & - & 9:00 & 9:00 \\
$t_2$ (hour) & - & 23:00 & 23:00 \\
b & - & 4.98 & 4.98 \\
$a_1^{Sun}$ & - & 26.94 & 23.38 \\
$a_1^{Mid}$ & - & 22.39 & 20.42 \\
$a_1^{Fri}$ & - & 21.58 & 17.54 \\
$a_1^{Sat}$ & - & 12.1 & 15.55 \\
$a_2^{Sun}$ & - & 20.02 & - \\
$a_2^{Mid}$ & - & 17.96 & - \\
$a_2^{Fri}$ & - & 14.59 & - \\
$a_2^{Sat}$ & - & 19.61 & - \\
$\beta^{Sun}$ & 0.224 & 0.220 & 0.225 \\
$\beta^{Mid}$ & 0.244 & 0.241 & 0.245 \\
$\beta^{Fri}$ & 0.280 & 0.282 & 0.271 \\
$\beta^{Sat}$ & 0.304 & 0.295 & 0.271 \\
$\sigma_1$ & $1.10\pm0.015$ & $1.12\pm0.02$ & $1.20\pm0.02$ \\
$\sigma_2$ & $0.36\pm0.01$ & $0.350\pm0.005$ & $0.315\pm0.01$ \\
\hline
\end{tabular}
|
Mitigating Emergency Department Crowding With Stochastic Population Models
|
Fitted parameter values, for the measured arrival flux (A), trapezoid arrival-flux model (B), and rectangular arrival-flux model (C), used in the main text. The latter resembles model (B) [Eq.~(\ref{trap_flux})], but with a constant value during rush hours: $a^i_1 = a^i_2$ for every part of the week.
| null |
physics.soc-ph, cond-mat.stat-mech, q-bio.PE
|
|
2308.08918v1
|
\begin{tabular}{l|cccc}
\hline
% \hline
& EPnL[$10^3$] & MAP[unit] & PnLMAP
% & RPT[$\%$]
& \#T \\
\hline
IMM$_{PnL}$
%RB
% & 16143.91 & { 68071.77} & 1735.32 & 182.77 & 8.10 & 38.58 & -0.33 & 1.33 & 3.80 & 0.96
%FU
& 58.76 $\pm$ 94.43 & 2156 $\pm$ 655 & 31 $\pm$ 48
% & 167$\pm$ 400
& 4.43 $\pm$ 0.94\\
IMM$_{PnL+C}$
% RB
% & 2411.68 & 66711.42 & 1649.04 & 244.53 & 2.34 & 42.47 &-0.07 & 1.10 & {\bf 4.05} & {\bf 1.04}
%FU
& 42.86 $\pm$ 123.04 & 2041 $\pm$ 465 & 27 $\pm$ 68
% & 126 $\pm$ 107
& { 4.85} $\pm$ { 1.09} \\
IMM$_{PnL+IP}$
% RB
% & {\bf 21620.43} & {\bf 19062.62} & 328.01 & 122.61 & 62.37 & 38.94 & {\bf 0.84} & {\bf 0.53} & 3.71 & 0.98
%FU
& {\bf 73.07} $\pm$ {\bf 53.83} & 756 $\pm$ 289 & 90 $\pm$ 46
% & {\bf 238} $\pm$ {\bf 129}
& 4.42 $\pm$ 0.96 \\
% \hline
IMM
%RB
% & {16459.91} & {9096.85} & {\bf 96.40} & {\bf 13.37} & {\bf 164.72} & {\bf 73.52} & { 0.64 } & { 0.20} & 3.96 & 1.06
%FU
&{ 28.097} $\pm$ { 10.27} & {\bf 103} $\pm$ {\bf 15} & {\bf 274} $\pm$ {\bf 89}
% & 87 $\pm$ 18
& {\bf 5.15} $\pm$ {\bf 1.19}\\
\hline
\end{tabular}
|
IMM: An Imitative Reinforcement Learning Approach with Predictive Representation Learning for Automatic Market Making
|
Performance of IMM variations trained with different reward preferemces on FU dataset.
| null |
cs.LG, cs.AI, q-fin.TR
|
|
2307.10453v1
|
\begin{tabular}{l|c c c c c c c c c c}
Facility & $E_l$[J] & $\Delta\tau$[fs] & $P_{\rm peak}$ [PW] & $w_0$[$\mu$m] & $\lambda_l$[$\mu$m] & $I_{\rm peak}$[W/cm$^2$] & $a_{\rm peak}$ & $\epsilon_w$ & $\epsilon_t$ & Rep.[Hz] \\\hline
%Baseline & 20 & 300 & 2.6 & 1 & $4.25\times 10^{20}$ & 17.7 & 0.0612 & 0.0111 & ?? \\\hline
\TPW f/1 & 150 & 150 & 1 & 1.25 & 1.054 & $2.76\times 10^{22}$ & 142.5 & 0.127 & 0.022 & $10^{-4}$\\\hline
\ELInp & 244 & 22.5 & 10.8 & 2 & 0.8 & $1.17 \times 10^{23}$ & 234.6 & 0.064 & 0.119 & 0.02 \\\hline
\Arc & 7 & 30 & 0.23 & 1.1 & 0.8 & $8.26\times 10^{21}$ & 62.34 & 0.115 & 0.089 & 5 \\\hline
\ELIhapl\footnote{Original specifications used here rather than best performance to date}
& 30 & 28 & 1.1 & 1.9 & 1.054 & $1.28\times 10^{22}$ & 102.38 & 0.088 & 0.126 & 10 \\\hline
\Cor\footnote{CoReLS can now achieve $>10^{23}$ W/cm$^2$ with $>100$ J pulse }
& 50 & 30 & 1.67 & 1.8 & 0.8 & $2.22\times 10^{22}$ & 127.7 & 0.088 & 0.111 & 0.1 \\\hline
\OPAL & 600 & 20 & 30 & 1.25 & 0.9 & $8.28\times 10^{23}$ & 702.4 & 0.0839 & 0.156 & $10^{-4}$
%Malka 2 & 20 & 50 & 2.6 & 1& $2.55\times 10^{21}$ & 43.3 &&\\\hline
%Berkeley & 40 & 30 & 1.8 & 0.8 & $1.77\times 10^{22}$ & $91.4$ && \\\hline
%TPW f/3 & 50 & 150 & 2.6 & 1& $2.13\times 10^{21}$ & 39.55 && \\\hline
\end{tabular}
|
Luminosity for laser-electron colliders
|
The pulse duration is measured as intensity full-width half-max. For peak intensity estimates, the temporal profile is assumed to be gaussian. \label{tab:facilities}
|
['\\newcommand{\\tcb}[1]{\\textcolor{blue}{ #1}}', '\\newcommand{\\abs}[1]{\\lvert#1\\rvert}', '\\newcommand{\\norm}[1]{\\lVert#1\\rVert}', '\\newcommand{\\eq}[1]{Eq.\\,\\eqref{eq:#1}}', '\\newcommand{\\fig}[1]{Fig.\\,\\ref{fig:#1}}', '\\newcommand{\\mum}[1]{\\SI{#1}{\\micro\\meter}}', '\\newcommand{\\thetai}{\\theta^{(i)}}', '\\newcommand{\\Ei}{E^{(i)}}', '\\newcommand{\\pxi}{p_x^{(i)}}', '\\newcommand{\\pyi}{p_y^{(i)}}', '\\newcommand{\\pzi}{p_z^{(i)}}', '\\newcommand{\\pzf}{p_z^{(f)}}', '\\newcommand{\\chie}{\\chi_{\\rm e}}', '\\newcommand{\\chib}{\\chi_{b}}', '\\newcommand{\\chimax}{\\chi_{\\rm max}}', '\\newcommand{\\LeL}{L_{\\rm e\\ell}}', '\\newcommand{\\Arc}{Arcturus\\,}', '\\newcommand{\\TPW}{TPW\\,}', '\\newcommand{\\Cor}{CoReLS\\,}', '\\newcommand{\\OPAL}{OPAL\\,}', '\\newcommand{\\ELInp}{ELI-NP\\,}', '\\newcommand{\\ELIhapl}{ELI-L3\\,}']
|
hep-ph, physics.acc-ph, physics.plasm-ph
|
|
2304.02723v1
|
\begin{tabular}{|c|ccccccccc|c|}
\hline
Data Set &
\multicolumn{9}{|c|}{Number of Accidents} & Total Number \\[-0.5ex]
& 0 & 1 & 2 & 3 & 4 & 5 & 6 & 7 & $\geq 8$ & of Policies \\
\hline
\hline
O (original) &
7,840 & 1,317 & 239 & 42 & 14 & 4 & 4 & 1 & 0 & 9,461 \\
M1 (modified \#1) & {\em 7,700} & 1,317 & {\em 379} & 42 & 14 &
4 & 4 & 1 & 0 & 9,461 \\
M2 (modified \#2) & {\em 7,700} & 1,317 & {\em 279} & {\em 62} &
{\em 34} & {\em 24} & {\em 24} & {\em 21} & 0 & 9,461 \\
M3 (modified \#3) & {\em 7,700} & 1,317 & 239 & 42 & 14 & 4 & 4 &
{\em 141} & 0 & 9,461 \\
\hline
\end{tabular}
|
Measuring Discrete Risks on Infinite Domains: Theoretical Foundations, Conditional Five Number Summaries, and Data Analyses
|
Original and modified data sets consisting of the numbers of
accidents per policy.
|
['\\newcommand{\\red}{\\color[rgb]{1,0,0}}', '\\newcommand{\\blue}{\\color[rgb]{0,0,1}}', '\\newcommand{\\magenta}{\\color[rgb]{1,0,1}}']
|
stat.AP, econ.GN, q-fin.EC, stat.ME
|
|
2310.04022v1
|
\begin{tabular}{|c|cccc|}
\hline
& $\tau = 1$ & $25$ & $75$ & $100$ \\ \hline
NI Grid&\multicolumn{4}{c|}{Iterations}\\
\hline
$M_1$ & $26$ & $34$ & $39$ & $41$ \\
$M_2$ & $15$ & $39$ & $70$ & $59$ \\
$M_3$ & $7$ & $25$ & $53$ & $50$ \\
$M_4$ & $8$ & $17$ & $69$ & $26$ \\
$M_5$ & $1$ & $7$ & $11$ & $11$ \\
$M_6$ & $0\ (75)$ & $0\ (102)$ & $1\ (152)$ & $1\ (148)$ \\
\hline
$F^k$ & $-19.88\ (-19.88)$ & $-15.04\ (-15.04)$ & $-12.31\ (-12.31)$ & $-12.02\ (-12.02)$ \\
\hline
Runtime [sec] & $16.05\ (1,151.91)$ & $28.43\ (1,566.53)$ & $62.59\ (2,336.07)$ & $54.24\ (2,260.82)$ \\
\hline
\end{tabular}
|
Nonlinear Methods for Shape Optimization Problems in Liquid Crystal Tactoids
|
Subproblem A: Iteration count for QN with NI on each grid level. Iteration count for QN without NI is given on level $M_6$ in parenthesis. The final energy, $F^k$, and runtime in seconds for the full simulation of QN with NI (QN without NI in parenthesis) are also given. Both QN and QN with NI converge to the same energies for all $\tau.$ NI improves efficiency in terms of iteration and runtime by taking minimal, if any, steps on the finest grid.
|
['\\newcommand{\\curl}{\\vec{\\nabla}\\times}', '\\newcommand{\\mydiv}{\\vec{\\nabla}\\cdot}', '\\newcommand{\\mygrad}{\\vec{\\nabla}}', '\\newcommand{\\be}{\\begin{equation}}', '\\newcommand{\\bi}{\\begin{itemize}}', '\\newcommand{\\func}{\\mathcal{F}}', '\\newcommand{\\vw}{\\mbox{\\boldmath$\\omega$}}', '\\newcommand{\\vb}{\\mbox{\\boldmath$\\beta$}}', '\\newcommand{\\anca}{\\textcolor{blue}}', '\\newcommand{\\james}{\\textcolor{red}}', '\\newcommand{\\tim}{\\textcolor{teal}}']
|
math.NA, cs.NA
|
|
2306.10946v4
|
\begin{tabular}{lccc}
\hline
\textbf{d} & \textbf{AUC}& \textbf{F1-score} \\\hline
8 & 0.973 & \bfseries 0.944 \\\hline
16 & \bfseries 0.976 & 0.923 \\\hline
32 & 0.941 & 0.897 \\\hline
64 & 0.936 & 0.892 \\\hline
128 & 0.884 & 0.831 \\\hline
\end{tabular}
|
Att-KGCN: Tourist Attractions Recommendation System by using Attention mechanism and Knowledge Graph Convolution Network
|
$AUC$ and $F1$-$score$ Results on different d for Att-KGCN model.
The best performance is highlighted in bold.
|
['\\newcommand{\\AF}[1]{\\textcolor{red}{[Afifa Khaled: #1]}}', '\\newcommand{\\AM}[1]{\\textcolor{blue}{[Ahmed Mubarak: #1]}}']
|
cs.IR, cs.AI, cs.GR, cs.LG
|
|
2307.14231v1
|
\begin{tabular}{ |c|c|c| }
\hline
Substrates & Normalised Area & Raman Shift (cm$^{-1}$) of quinoid mode \\
\hline
Pristine & 0.8 & 1408 \\
Glass & 2.5 & 1404 \\
PDMS & 4.3 & 1402 \\
\hline
\end{tabular}
|
Giant conductance of PSS:PEDOT micro-surfaces induced by microbubble lithography
|
Characteristics of the Raman peak due to the quinoid mode in PEDOT:PSS in the pristine form and after patterning on different substrates.
|
['\\newcommand*\\mycommand[1]{\\texttt{\\emph{#1}}}']
|
physics.chem-ph, cond-mat.mtrl-sci
|
|
2311.04148v1
|
\begin{tabular}{c c}
\hline
\textbf{Spoof} & \textbf{Number of Images} \\
\hline
DRAGONSKIN & 1700 \\
ECOFLEX & 300 \\
GELAFIX & 100 \\
GELATIN & 100 \\
GLUE & 200 \\
KNETOSIL & 200 \\
LATEX & 100 \\
MOULDABLE-CLAY & 100 \\
MOULDABLE-GLUE & 900 \\
PAPER PRINTOUT & 1200 \\
PLAYDOH & 1700 \\
SILLY-PUTTY & 600 \\
\hline
\end{tabular}
|
Contactless Fingerprint Biometric Anti-Spoofing: An Unsupervised Deep Learning Approach
|
Statisitcs of the COLFISPOOF dataset
| null |
cs.CV, cs.AI, cs.CR, cs.LG
|
|
2305.08394v1
|
\begin{tabular}{l l l l}
stand\_sce 0 & KAI0-blue & KAI1-blue \\
\hline
KAI0-red & 0.450/114.7 & 0.500/278.3\\
KAI1-red & 0.510/109.1 & 0.470/110.2 \\
\hline
\end{tabular}
|
More Like Real World Game Challenge for Partially Observable Multi-Agent Cooperation
|
Results of built-in bots compete against each other in all scenarios of all sub-environments, and the number xxx/xxx means win rate/average time steps used.
| null |
cs.MA
|
|
2310.04620v2
|
\begin{tabular}{c|c|lll}
\multicolumn{1}{l|}{Dive Type} & Parameter Estimate & Descent & Bottom & Ascent \\ \hline
\multirow{3}{*}{1} & $\hat \mu$ & 0.70 & 0.02 & -0.67 \\
& $\hat \sigma$ & 0.45 & 0.23 & 0.40 \\
& $\hat p$ & \bf{0} & \bf{0} & 0.12 \\ \hline
\multirow{3}{*}{2} & $\hat \mu$ & 0.33 & 0.00 & -0.44 \\
& $\hat \sigma$ & 0.15 & 0.15 & 0.21 \\
& $\hat p$ & \bf{0} & \bf{0} & 0.47 \\ \hline
\multirow{3}{*}{3} & $\hat \mu$ & 2.71 & 0.01 & -2.50 \\
& $\hat \sigma$ & 1.85 & 0.64 & 1.58 \\
& $\hat p$ & \bf{0} & \bf{0} & 0.04
\end{tabular}
|
Variance-Reduced Stochastic Optimization for Efficient Inference of Hidden Markov Models
|
Maximum likelihood parameter estimates from the Killer Whale case study described in the main text. Recall that $D_t$ represents the change in depth in meters at time index $t$ and $E_t \in \{0,1\}$ encodes whether a dive ends at time index $t$. The parameter $\mu$ corresponds to the state-dependent mean of $D_t$, $\sigma$ corresponds to the state-dependent standard deviation of $D_t$, and $p$ corresponds to the state-dependent probability that $E_t=1$.
|
['\\newcommand{\\conditional}[3][]{\\bbE_{#1}\\bigCond*{#2}{#3}}', '\\newcommand{\\argdot}{{\\,\\vcenter{\\hbox{\\tiny$\\bullet$}}\\,}} %generic argument dot', '\\newcommand{\\C}{{\\mathbb{C}}}', '\\newcommand{\\F}{{\\mathcal{F}}}', '\\newcommand{\\R}{{\\mathbb{R}}}', '\\newcommand{\\N}{{\\mathbb{N}}}', '\\newcommand{\\Q}{{\\mathbb{Q}}}', '\\newcommand{\\statespace}{\\mathcal{X}}', '\\newcommand{\\states}{\\textbf{x}}', '\\newcommand{\\augstates}{\\textbf{z}}', '\\newcommand{\\pis}{\\boldsymbol{\\pi}}', '\\newcommand{\\rstates}{\\textbf{X}}', '\\newcommand{\\Ps}{\\textbf{P}}', '\\newcommand{\\K}{{\\textbf{K}}}', '\\newcommand{\\Kcomm}{\\K^{\\textrm{comm}}_n}', '\\newcommand{\\Kexpl}{\\K^{\\textrm{expl}}}', '\\newcommand{\\KSEO}{\\K^{\\textrm{SEO}}}', '\\newcommand{\\KDEO}{\\K^{\\textrm{DEO}}_n}', '\\newcommand{\\Kodd}{\\K^{\\textrm{odd}}}', '\\newcommand{\\Keven}{\\K^{\\textrm{even}}}', '\\newcommand{\\Kswap}{\\K^{(i,i+1)}}', '\\newcommand{\\KPT}{\\K^{\\textrm{PT}}_n}', '\\newcommand{\\Rn}{\\mathcal{R}_n}', '\\newcommand{\\Tn}{\\mathcal{T}_n}', '\\newcommand{\\Bs}{\\textbf{B}}', '\\newcommand{\\partition}{\\mathcal{P}}', '\\newcommand{\\PSEO}{\\mathbb{P}_{\\textrm{SEO}}}', '\\newcommand{\\PDEO}{\\mathbb{P}_{\\textrm{DEO}}}', '\\newcommand{\\ESEO}{\\mathbb{E}_{\\textrm{SEO}}}', '\\newcommand{\\EDEO}{\\mathbb{E}_{\\textrm{DEO}}}', '\\newcommand{\\nexpl}{n_\\textrm{expl}} ', '\\newcommand{\\nv}{n_\\textrm{var}}', '\\newcommand{\\tauSEO}{\\tau_{\\textrm{SEO}}}', '\\newcommand{\\tauDEO}{\\tau_{\\textrm{DEO}}}', '\\newcommand{\\punif}{\\mathcal{P}_{\\textrm{uniform}}}', '\\newcommand{\\popt}{\\mathcal{P}_{\\textrm{optimal}}}', '\\newcommand{\\A}{\\mathcal{A}}', '\\newcommand{\\norm}[1]{\\|{#1}\\|}', '\\newcommand{\\Norm}[1]{\\left\\|{#1}\\right\\|}', '\\newcommand{\\rank}{{\\mathrm{rank}}}', '\\newcommand{\\Var}{\\mathrm{Var}}', '\\newcommand{\\Bern}{\\mathrm{Bern}}', '\\newcommand{\\I}{{\\mathbb{I}}}', '\\newcommand{\\eps}{\\varepsilon}', '\\newcommand{\\ud}{\\textrm{d}}', '\\newcommand\\deq{\\stackrel{\\scriptscriptstyle d}{=}}']
|
stat.CO
|
|
2309.06039v1
|
\begin{tabular}{c|c|c|c|c}
\hline
& Water outflow [m$^3$/h] & Volume [m$^3$] & Surface [m$^2$] & Ventilation [m$^3$/h]\\ \hline
Main hall & Top: 0.4, bottom: 70 & 120,000 & 5500 & 52,000 \\ \hline
LS room & 4 & 2700 & 650 & 3000 \\ \hline
Tunnel & 450 & 180,000 & - & 100,000 \\
\hline
\end{tabular}
|
Environmental radon control in the 700-m underground laboratory at JUNO
|
\label{tab:ventilation} The optimized ventilation inside the experimental hall at the JUNO site from October 2022. The area of the surface includes both the rock and floor, and the ventilation is calculated based on the wind speed shown in Fig.~\ref{fig:ventilation}.
| null |
physics.ins-det, hep-ex
|
|
2307.01107v1
|
\begin{tabular}{|c c c c c|}
\hline
$A^{(0)}_{HT}$ & $B^{(0)}_{HT}$ & $B1^{(0)}_{HT}$ & $B2^{(0)}_{HT}$ & $\chi^2/d.o.f.$ \\ [0.5ex]
\hline\hline
$-0.335823(2)$ & $-0.5234(2)$ & $-0.179(7)$ & $-0.51(7)$ & $1.89$ \\
\hline
\end{tabular}
|
Sampling the lattice Nambu-Goto string using Continuous Normalizing Flows
|
Results for the coefficients of the fit of eq.~(\ref{eq:logZHT2}) (upper table), for the coefficients of eq.~(\ref{eq:perHT}) (middle table) and for the coefficients of eq.~(\ref{eq:logZHT3}) (lower table).
|
['\\newcommand{\\dd}{{\\rm{d}}}', '\\newcommand{\\DD}{{\\rm{D}}}', '\\newcommand{\\tmb}[1]{{\\mbox{\\tiny{#1}}}}', '\\newcommand{\\Scl}{S_{\\mbox{\\tiny{cl}}}}', '\\newcommand{\\eq}{\\begin{equation}} ', '\\newcommand{\\en}{\\end{equation}} ', '\\newcommand{\\eqa}{\\begin{eqnarray}}', '\\newcommand{\\ena}{\\end{eqnarray}}', '\\newcommand{\\rev}[1]{ {\\color{red}{#1}}}']
|
hep-lat, cs.LG, hep-th
|
|
2312.01273v1
|
\begin{tabular}{|c|cc|cc|}
\hline
& \multicolumn{2}{c|}{SDPCP}
& \multicolumn{2}{c|}{SDPNAL+} \\
\cline{1-5}
success & 69 & 100.0\% & 69 & 100.0\% \\
fastest & 53 & 76.8\% & 16 & 23.2\% \\
fastest under success & 53 & 76.8\% & 16 & 23.2\% \\
not slower 1.2 times & 60 & 87.0\% & 25 & 36.2\% \\
not slower 1.2 times under success & 60 & 87.0\% & 25 & 36.2\% \\
\hline
\end{tabular}
|
An Augmented Lagrangian Primal-Dual Semismooth Newton Method for Multi-Block Composite Optimization
|
A statistic of computational results of SSNCP and SDPNAL+ for theta problems
|
['\\newcommand{\\comm}[1]{{\\color{red}#1}}', '\\newcommand{\\revise}[1]{{\\color{blue}#1}}', '\\newcommand{\\T}{\\top}', '\\newcommand{\\E}{\\mathbb{E}}', '\\newcommand\\numberthis{\\addtocounter{equation}{1}\\tag{\\theequation}}', '\\newcommand{\\etal}{ et al. }', '\\newcommand{\\br}{\\mathbb{R}}', '\\newcommand{\\ba}{\\begin{array}}', '\\newcommand{\\ea}{\\end{array}}', '\\newcommand{\\Snn}{\\mathbb{S}^{n\\times n}}', '\\newcommand{\\upcite}[1]{\\textsuperscript{\\textsuperscript{\\cite{#1}}}}', '\\newcommand{\\bit}{\\begin{itemize}}', '\\newcommand{\\eit}{\\end{itemize}}', '\\newcommand{\\be}{\\begin{equation}}', '\\newcommand{\\ee}{\\end{equation}}', '\\newcommand{\\bea}{\\begin{eqnarray}}', '\\newcommand{\\eea}{\\end{eqnarray}}', '\\newcommand{\\zero}{\\textbf{0}~}', '\\newcommand{\\mvec}{\\mbox{vec}}', '\\newcommand{\\mat}{\\mbox{mat}}', '\\newcommand{\\orth}{\\mathsf{St}_{n,p}}', '\\newcommand{\\stief}{\\mathsf{St}_{d,r}}', '\\newcommand{\\grass}{\\mathsf{Gr}_{d,r}}', '\\newcommand{\\mskew}{\\mathrm{skew}}', '\\newcommand{\\mF}{f}', '\\newcommand{\\mL}{\\mathcal{L}}', '\\newcommand{\\Rbb}{\\mathbb{R}}', '\\newcommand{\\mbC}{\\mathbb{C}}', '\\newcommand{\\mT}{\\mathcal{T}}', '\\newcommand{\\teigs}{\\textbf{eigs}}', '\\newcommand{\\mN}{\\mathcal{N}}', '\\newcommand{\\mbsign}{\\mbox{\\bf sign}}', '\\newcommand{\\st}{\\mathrm{s.t.}}', '\\newcommand{\\mE}{\\mathcal{E}}', '\\newcommand{\\mR}{\\mathcal{R}}', '\\newcommand{\\wR}{\\widetilde{R}}', '\\newcommand{\\wN}{\\widetilde{N}}', '\\newcommand{\\mM}{\\mathcal{M}}', '\\newcommand{\\mD}{\\mathcal{D}}', '\\newcommand{\\Drho}{D_{\\rho}}', '\\newcommand{\\argmin}{\\mathop{\\mathrm{arg\\,min}}}', '\\newcommand{\\argmax}{\\mathop{\\mathrm{arg\\,max}}}', '\\newcommand{\\odr}{\\overline{\\delta r}}', '\\newcommand{\\udr}{\\underline{\\delta r}}', '\\newcommand{\\oq}{\\overline{q}}', '\\newcommand{\\uq}{\\underline{q}}', '\\newcommand{\\ola}{\\overline{\\lambda}}', '\\newcommand{\\ula}{\\underline{\\lambda}}', '\\newcommand{\\oom}{\\overline{\\omega}}', '\\newcommand{\\uom}{\\underline{\\omega}}', '\\newcommand{\\myarg}{\\mathop{\\mathrm{arg}}}', '\\newcommand{\\Drhok}{D_{\\rho, k}}', '\\newcommand{\\mP}{h}', '\\newcommand{\\mTr}{\\text{Tr}}', '\\newcommand{\\mtr}{\\mbox{tr}}', '\\newcommand{\\tW}{\\widetilde{W}}', '\\newcommand{\\mK}{\\mathcal{K}}', '\\newcommand{\\tJ}{\\widetilde{J}}', '\\newcommand{\\tF}{\\widetilde{F}}', '\\newcommand{\\eqreff}[1]{(\\eqref{#1})}', '\\newcommand{\\nii}{\\noindent}', '\\newcommand{\\qf}{\\text{qf}}', '\\newcommand{\\nn}{\\nonumber}', '\\newcommand{\\diag}{\\text{diag}}', '\\newcommand{\\Diag}{\\text{Diag}}', '\\newcommand{\\proj}{h}', '\\newcommand{\\by}{\\mathrm{\\bf y}}', '\\newcommand{\\bs}{\\mathrm{\\bf s}}', '\\newcommand{\\bx}{\\mathbf{x}}', '\\newcommand{\\bw}{\\mathbf{W}}', '\\newcommand{\\mfS}{\\mathbf{S}}', '\\newcommand{\\mfY}{\\mathbf{Y}}', '\\newcommand{\\mfR}{\\mathbf{R}}', '\\newcommand{\\LBB}{\\mathrm{LBB}}', '\\newcommand{\\SBB}{\\mathrm{SBB}}', '\\newcommand{\\mfD}{\\mathbf{D}}', '\\newcommand{\\mfL}{\\mathbf{L}}', '\\newcommand{\\mscrL}{\\mathscr{L}}', '\\newcommand{\\nF}{\\nabla \\mathcal{F}}', '\\newcommand{\\rmn}[1]{\\romannumeral#1}', '\\newcommand{\\Rmn}[1]{\\uppercase\\expandafter{\\romannumeral#1}}', '\\newcommand{\\rev}[1]{{\\color{red}{#1}}}', '\\newcommand{\\rblue}[1]{{\\color{blue}{#1}}}', '\\newcommand{\\rblack}[1]{{\\color{black}{#1}}}', '\\newcommand{\\Fsf}{\\mathsf{F}}', '\\newcommand{\\Tsf}{\\mathsf{T}}', '\\newcommand{\\Xcal}{\\mathcal{X}}', '\\newcommand{\\Ebb}{\\mathbb{E}}', '\\newcommand{\\BB}{\\mathrm{BB}}', '\\newcommand{\\Bsf}{\\mathsf{B}}', '\\newcommand{\\Tcal}{\\mathcal{T}}', '\\newcommand{\\Rcal}{\\mathcal{R}}', '\\newcommand{\\llangle}{\\left \\langle}', '\\newcommand{\\rrangle}{\\right \\rangle}', '\\newcommand{\\tx}{\\tilde{X}}', '\\newcommand{\\tX}{\\tilde{X}}', '\\newcommand{\\Gcal}{\\mathcal{G}}', '\\newcommand{\\Dcal}{\\Gcal^{\\mathrm{R}}}', '\\newcommand{\\Pcal}{h}', '\\newcommand{\\Fcal}{\\mathcal{F}}', '\\newcommand{\\Kcal}{\\mathcal{K}}', '\\newcommand{\\Ocal}{\\mathcal{O}}', '\\newcommand{\\Tbf}{\\mathbf{T}}', '\\newcommand{\\Rscr}{\\mathcal{R}}', '\\newcommand{\\ud}{\\mathrm{d}}', '\\newcommand{\\Pbb}{\\mathbb{P}}', '\\newcommand{\\Dbf}{\\mathbf{D}}', '\\newcommand{\\Drm}{\\mathrm{D}}', '\\newcommand{\\drm}{\\mathrm{d}}', '\\newcommand{\\rgrad}{\\mathrm{grad}}', '\\newcommand{\\up}{\\mathrm{up}}', '\\newcommand{\\qr}{\\mathrm{qr}}', '\\newcommand{\\Mcal}{\\mathcal{M}}', '\\newcommand{\\xbf}{\\mathbf{x}}', '\\newcommand{\\ubf}{\\mathbf{u}}', '\\newcommand{\\abf}{\\mathbf{a}}', '\\newcommand{\\bbf}{\\mathbf{b}}', '\\newcommand{\\cbf}{\\mathbf{c}}', '\\newcommand{\\dbf}{\\mathbf{d}}', '\\newcommand{\\fbf}{\\mathbf{f}}', '\\newcommand{\\Lbf}{\\mathbf{L}}', '\\newcommand{\\Nsf}{\\mathsf{N}}', '\\newcommand{\\TR}{\\#\\mathrm{N}_{\\Rscr}}', '\\newcommand{\\TCG}{\\#\\mathrm{N}_{\\mathrm{cg}}}', '\\newcommand{\\TT}{\\#\\mathrm{N}_{\\mathrm{\\mathcal{T}}}}', '\\newcommand{\\1}{\\mathbf{1}}', '\\newcommand{\\grad}{\\mathrm{grad}}', '\\newcommand{\\sym}{\\mathrm{sym}}', '\\newcommand{\\R}{\\mathbb{R}}', '\\newcommand{\\hess}{\\mathrm{Hess}}', '\\newcommand{\\prox}{\\mathrm{prox}}', '\\newcommand{\\iprod}[2]{\\left \\langle #1, #2 \\right \\rangle }', '\\newcommand{\\V}{\\mathcal{V}}', '\\newcommand{\\tr}{\\mathrm{tr}}', '\\newcommand{\\Diff}{\\mathrm{Diff}}', '\\newcommand{\\creflastconjunction}{, and~}']
|
math.OC
|
|
2309.05974v1
|
\begin{tabular}{|c|c|}
\hline
Decision Variable & References \\ \hline \hline
Blocklength & ,, \\ \hline
Transmit power and blocklength & \\ \hline
Time duration of energy collected & \\ \hline
Blocklength with ARQ & \\ \hline
Blocklength for retransmissions \& analysis of AoI behavior& \\
\hline
Blocklength allocation for multiple users & \\
\hline
Transmitter's average transmit power and blocklength & \\
\hline
Blocklength and queuing policy & \\
\hline
Blocklength and update rate & \\
% \hline
% Transmit diversity & \\
\hline
% PPV error bound & ,,,,,, \\ \hline
% RAoI part of state & ,, \\ \hline
% MDP based optimization & ,, \\ \hline
% Convex optimization & , \\ \hline
\end{tabular}
|
Optimizing Reported Age of Information with Short Error Correction and Detection Codes
|
A summary of decision variables in previous works on finite-blocklength communication for AoI optimization.
|
['\\newcommand{\\argmax}{\\arg\\!\\max}', '\\newcommand{\\argmin}{\\arg\\!\\min}', '\\newcommand{\\sgn}{\\operatorname{sgn}}', '\\newcommand\\numberthis{\\addtocounter{equation}{1}\\tag{\\theequation}}']
|
cs.IT, math.IT
|
|
2304.05189v1
|
\begin{tabular}{l|c|c|c|c}
\multicolumn{5}{c}{Short data}\\
Cosine & General & Conformal & Split & Jackknife \\ \hline
diffpred & 0.57 & 0.34 & 0.39 & 0.98 \\
diffpredr & 0.31 & 0.28 & 0.4 & 0.26 \\
diffpredrs & 0.29 & 0.27 & 0.35 & 0.25 \\
diffpredl & 0.55 & 0.34 & 0.34 & 0.98 \\
diffpredlr & 0.3 & 0.28 & 0.4 & 0.22 \\
diffpredlrs & 0.3 & 0.29 & 0.35 & 0.26 \\
diffpredk & 0.32 & 0.3 & 0.34 & 0.31 \\
diffpredkr & 0.6 & 0.8 & 0.57 & 0.44 \\
diffpredkrs & 0.93 & 1.1 & 0.58 & 1.11 \\ \hline
\%pred & 60.25 & 42.49 & 42.38 & 95.87 \\
\%predr & 37.08 & 35.18 & 38.15 & 37.92 \\
\%predrs & 37.27 & 34.79 & 41.6 & 35.41 \\
\%predl & 60.31 & 42.49 & 42.56 & 95.89 \\
\%predlr & 35.65 & 35.18 & 38.15 & 33.62 \\
\%predlrs & 38.18 & 36.4 & 41.6 & 36.54 \\
\%predk & 38.41 & 36.05 & 42.7 & 36.49 \\
\%predkr & 89.13 & 102.14 & 99.06 & 66.2 \\
\%predkrs & 144.67 & 153.04 & 99.05 & 181.92 \\ \hline
int & 3.26 & 2.53 & 3.58 & 3.67 \\
intr & 3.1 & 2.53 & 3.89 & 2.89 \\
intrs & 2.74 & 2.53 & 2.99 & 2.69 \\
intl & 3.24 & 2.53 & 3.52 & 3.66 \\
intlr & 3.33 & 2.58 & 3.89 & 3.5 \\
intlrs & 2.74 & 2.58 & 2.99 & 2.64 \\
intk & 2.56 & 2.53 & 2.64 & 2.49 \\
intkr & 2.93 & 2.86 & 3.41 & 2.52 \\
intkrs & 2.91 & 3.37 & 2.68 & 2.67 \\ \hline
ab & 0.59 & 0.63 & 0.61 & 0.52 \\
abr & 0.65 & 0.88 & 0.55 & 0.53 \\
abrs & 0.57 & 0.59 & 0.6 & 0.53 \\
abl & 0.58 & 0.63 & 0.6 & 0.52 \\
ablr & 0.64 & 0.87 & 0.55 & 0.5 \\
ablrs & 0.57 & 0.6 & 0.6 & 0.51 \\
abk & 0.62 & 0.61 & 0.63 & 0.62 \\
abkr & 0.62 & 0.37 & 0.54 & 0.94 \\
abkrs & 0.73 & 0.62 & 0.58 & 0.99 \\ \hline
\end{tabular}
|
Individualized Conformal
|
Short data cosine
| null |
stat.ME, stat.OT, 62, G.3
|
|
2306.04704v1
|
\begin{tabular}{|c|c|c|c|c|c|c|c|}
\hline
Experiment & $N_{\rm dat}$ & Observable & Target & $\sqrt{s}$ [GeV]& $Q^2$ [GeV$^2$] &$y$ & Ref. \\
\hline
\hline
HERA (p) & 136 & $A_{\rm PV}$ for $e^+$ & proton & 319 & 120 - 30000 & 0.033 - 0.9 & \\
\hline
HERA (p) & 138 & $A_{\rm PV}$ for $e^-$ & proton & 319 & 120 - 30000 & 0.033 - 0.9 & \\
\hline
PVDIS (d) & 2 & $A_{\rm PV}$ for $e^-$ & deuteron & 4.77 & 1.085; 1.901 & 0.20; 0.28 & \\
\hline
E122 (d) & 11 & $A_{\rm PV}$ for $e^-$ & deuteron & 5.5 - 6.5 & 0.92 - 1.96 & 0.15 - 0.36 & \\
\hline
\hline
Total & 287 & & & & & &\\
\hline
\end{tabular}
|
Signals of strong parity violation in deep inelastic scattering
|
Breakdown of the data sets considered in this analysis.
For each data set, the table includes information on: the number of data
points ($N_{\rm dat}$), the measured observable, the hadronic target, the center-of-mass energy $\sqrt{s}$, the covered range(s) in $Q^2$, the inelasticity $y$, and the published reference.
The total number of data points amounts to 287.
|
['\\newcommand{\\dd}{\\mathop{}\\!\\mathrm{d}}', '\\newcommand{\\Pperp}{\\boldsymbol{P}_{hT}}', '\\newcommand{\\PhT}{\\boldsymbol{P}_{hT}}', '\\newcommand{\\kperp}{\\boldsymbol{k}_T}', '\\newcommand{\\Phperp}{\\bm{P}_{hT}}', '\\newcommand{\\bT}{\\xi_T}', '\\newcommand{\\xbj}{x}', '\\newcommand{\\nslash}{n\\kern -0.50em /}', '\\newcommand{\\Sslash}{\\kern 0.2 em S\\kern -0.50em /}']
|
hep-ph, hep-ex, nucl-ex, nucl-th
|
|
2310.12581v1
|
\begin{tabular}{ccc|ccc}
\hline
$p'$ & $p''$ & event scale & $A$ & $h^{\rm{A}}(p')$ & $p=f^{A}(p',p'')$ \\
\hline
\multirow{2}{*}{$1-k_{i} e_2$} & \multirow{2}{*}{$1-k_{j} e_2$} & \multirow{2}{*}{$O(1)$ or $O(e_2)$} & $\rm{C}$ & $1-k_{i}e_2$ & $1-e_2$ \\
& & & $\rm{D}$ & $k_{i}e_2$ & $(k_{i}+1)e_2$ \\
$1-k_{i} e_2$ & $l_{j} e_2$ & $O(e_2)$ & $\rm{C}$ & $1$ & $1-\{(1-\snptil^{\rm{CBB}})k_{i}+1\}e_2$ \\
$l_{i} e_2$ & $1-k_{j} e_2$ & $O(e_2)$ & $\rm{D}$ & $1$ & $1-\{l_{i} +(1-\snptil^{\rm{DBB}})k_{j}+1\} e_2$ \\
\hline
\end{tabular}
|
Evolutionary stability of cooperation by the leading eight norms in indirect reciprocity under noisy and private assessment
|
How to calculate $\phi_{t+1}(p)$ from $\phi_{t}(p)$ for Type-1 norms.
|
['\\newcommand{\\bs}{\\boldsymbol} % by Fujimoto', '\\newcommand{\\mc}{\\mathcal} % by Fujimoto', '\\newcommand{\\CG}{\\mathrm{CG}} % by Fujimoto', '\\newcommand{\\CB}{\\mathrm{CB}} % by Fujimoto', '\\newcommand{\\DG}{\\mathrm{DG}} % by Fujimoto', '\\newcommand{\\DB}{\\mathrm{DB}} % by Fujimoto', '\\newcommand{\\GG}{\\mathrm{GG}} % by Fujimoto', '\\newcommand{\\GB}{\\mathrm{GB}} % by Fujimoto', '\\newcommand{\\BG}{\\mathrm{BG}} % by Fujimoto', '\\newcommand{\\BB}{\\mathrm{BB}} % by Fujimoto', '\\newcommand{\\CGG}{\\mathrm{CGG}} % by Fujimoto', '\\newcommand{\\CGB}{\\mathrm{CGB}} % by Fujimoto', '\\newcommand{\\CBG}{\\mathrm{CBG}} % by Fujimoto', '\\newcommand{\\CBB}{\\mathrm{CBB}} % by Fujimoto', '\\newcommand{\\DGG}{\\mathrm{DGG}} % by Fujimoto', '\\newcommand{\\DGB}{\\mathrm{DGB}} % by Fujimoto', '\\newcommand{\\DBG}{\\mathrm{DBG}} % by Fujimoto', '\\newcommand{\\DBB}{\\mathrm{DBB}} % by Fujimoto', '\\newcommand{\\red}[1]{\\textcolor{red}{#1}}', '\\newcommand{\\blue}[1]{\\textcolor{blue}{#1}}', '\\newcommand{\\sn}{\\textit{Norm}} % social norm', '\\newcommand{\\snp}{n} % social norm probability', '\\newcommand{\\snptil}{\\tilde{n}} % social norm probability with tilde', '\\newcommand{\\ac}{\\textit{Action}} % action rule', '\\newcommand{\\acp}{a} % action rule probability', '\\newcommand{\\self}{s}', '\\newcommand{\\inte}{\\textrm{int}}']
|
q-bio.PE, cs.GT, cs.MA, physics.soc-ph
|
|
2312.06579v1
|
\begin{tabular}{|c|c|}
\hline
Locker Name & $\%$ Accuracy \\ \hline
\hline
Boson & 98.9 \\
Seth & 92.6 \\
Berlin & 96.1 \\
Grape & 99.3 \\
\hline
\end{tabular}
|
Amazon Locker Capacity Management
|
Simulation system accuracy metrics
|
['\\newcommand{\\elite}{\\mathcal{E}}']
|
math.OC, cs.AI, 68T05, 90B05, 90B06, 90C90, G.1.6; I.2.6; I.2.8; I.6.3
|
|
2301.08274v3
|
\begin{tabular}{l|c|c}
\hline \hline
Source & \quad $\delta \amuLW$ (\%) \quad & \quad $\delta \amuLWTwo$ (\%) \quad \\
\hline
Monte Carlo statistics & 0.19 & 2.44 \\
Continuum extrapolation ($a \to 0$, $\Delta_{\textrm{TB}}$) & 0.34 & 1.05\\
Finite-volume correction ($\Delta_{\textrm{FV}}$) & 0.16 & 0.23 \\
Pion-mass adjustment ($\Delta_{M_\pi}$) & 0.06 & 0.96 \\
Scale setting ($w_0$ (fm), $w_0 / a$) & 0.21 & 1.28 \\
Current renormalization ($Z_V$) $\quad \quad \quad \quad \quad \quad \quad \quad \quad $ & 0.17 & 0.16 \\
\hline
Total & 0.50\% & 3.18\% \\
\hline \hline
\end{tabular}
|
Light-quark connected intermediate-window contributions to the muon $g-2$ hadronic vacuum polarization from lattice QCD
|
Approximate error budgets for $\amuLW$ and $\amuLWTwo$. \vspace{1mm}
|
['\\newcommand{\\creflastconjunction}{, and\\nobreakspace}', '\\newcommand{\\bi}{\\begin{itemize}}', '\\newcommand{\\ei}{\\end{itemize}}', '\\newcommand{\\ii}{\\item}', '\\newcommand{\\ben}{\\begin{enumerate}}', '\\newcommand{\\een}{\\end{enumerate}} ', '\\newcommand{\\be}{\\begin{equation}}', '\\newcommand{\\ee}{\\end{equation}}', '\\newcommand{\\bea}{\\begin{eqnarray}}', '\\newcommand{\\eea}{\\end{eqnarray}}', '\\newcommand{\\nn}{\\nonumber}', '\\newcommand{\\MSbar}{\\ensuremath{\\overline{\\rm MS}}}', '\\newcommand{\\chpt}{$\\chi$PT}', '\\newcommand{\\amu}{a_\\mu}', '\\newcommand{\\amuL}{a_\\mu^{ll}(\\mathrm{conn.})}', '\\newcommand{\\amuHVP}{a_\\mu^{\\mathrm{HVP,LO}}}', '\\newcommand{\\amuWin}{a^{\\mathrm{win}}_{\\mu}}', '\\newcommand{\\amuW}{a^{\\mathrm W}_{\\mu}}', '\\newcommand{\\amuSD}{a^{\\mathrm{SD}}_{\\mu}}', '\\newcommand{\\amuLD}{a^{\\mathrm{LD}}_{\\mu}}', '\\newcommand{\\amuWTwo}{a^{\\mathrm{W2}}_{\\mu}}', '\\newcommand{\\amuLW}{a^{ll,{\\mathrm W}}_{\\mu}(\\mathrm{conn.})}', '\\newcommand{\\amuLWTwo}{a^{ll,\\mathrm {W2}}_{\\mu}(\\mathrm{conn.})}', '\\newcommand{\\amuLWRes}{a^{ll,{\\mathrm W}}_{\\mu}(\\mathrm{conn.}) = 206.6(1.0) \\times 10^{-10}}', '\\newcommand{\\amuLWTwoRes}{a^{ll,\\mathrm {W2}}_{\\mu}(\\mathrm{conn.}) = 100.7(3.2) \\times 10^{-10}}', '\\newcommand{\\amuOS}{a^{\\mathrm{O.S.}}_{\\mu}}', '\\newcommand{\\amuOStTwo}{a^{\\mathrm{O.S.}}_{\\mu}(t_1)}', '\\newcommand{\\amuOSTwo}{a^{\\mathrm{O.S.}}_{\\mu}(t_1=2)}', '\\newcommand{\\gmtwo}{$g-2$} ', '\\newcommand{\\pr}{\\operatorname{pr}}', '\\newcommand{\\coloaf}{Department of Physics, University of Colorado, Boulder, Colorado 80309, USA}', '\\newcommand{\\fnalaf}{Theory Division, Fermi National Accelerator Laboratory, Batavia, Illinois, 60510, USA}', '\\newcommand{\\iuaf}{Department of Physics, Indiana University, Bloomington, Indiana 47405, USA}', '\\newcommand{\\mitaf}{Center for Theoretical Physics, Massachusetts Institute of Technology, Cambridge, \\\\MA 02139, USA}', '\\newcommand{\\msuaf}{Department of Computational Mathematics, Science and Engineering, and Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA}', '\\newcommand{\\ucsbaf}{Department of Physics, University of California, Santa Barbara, California 93106, USA}', '\\newcommand{\\ugraf}{CAFPE and Departamento de Física Teórica y del Cosmos, Universidad de Granada, \\\\E-18071 Granada, Spain}', '\\newcommand{\\uiucaf}{Department of Physics, University of Illinois, Urbana, Illinois, 61801, USA}', '\\newcommand{\\icasuuiaf}{Illinois Center for Advanced Studies of the Universe, University of Illinois, Urbana, Illinois, \\\\61801, USA}', '\\newcommand{\\unizar}{Departmento de Física Teórica, Universidad de Zaragoza, 50009 Zaragoza, Spain}', '\\newcommand{\\utahaf}{Department of Physics and Astronomy, University of Utah, Salt Lake City, UT 84112, USA}', '\\newcommand{\\glasaf}{SUPA, School of Physics and Astronomy, University of Glasgow, Glasgow, G12 8QQ, \\\\United Kingdom}', '\\newcommand{\\cornaf}{Laboratory for Elementary-Particle Physics, Cornell University, Ithaca, NY 14853, USA}', '\\newcommand{\\plyaf}{Centre for Mathematical Sciences, University of Plymouth, Plymouth PL4 8AA, \\\\United Kingdom}']
|
hep-lat, hep-ph
|
|
2307.10618v1
|
\begin{tabular}{cccccc}
\hline
\multirow{2}{*}{Monitors} & \multicolumn{5}{c}{Memory size (MB) on frequency intervals} \\
& {[}0,20) & {[}20,40) & {[}40,60) & {[}60,80) & {[}80,100{]} \\ \hline
{\bf Base scan (baseline)} & {\bf 19171} & {\bf 184} & {\bf 79} & {\bf 11} & {\bf 1029} \\
Huge scan & 330 & 124 & 163 & 1528 & 18186 \\
Split scan & 19243 & 183 & 82 & 11 & 955 \\
Zero scan & 20344 & 3 & 19 & 3 & 1 \\
Sampling scan & 1144 & 38 & 491 & 975 & 17830 \\
PEBS-5000 & 20479 & \textless{}1 & \textless{}1 & \textless{}1 & \textless{}1 \\
PEBS-500 & 19593 & 885 & \textless{}1 & \textless{}1 & \textless{}1 \\
PEBS-50 & 19185 & 4 & 2 & 2 & 1284 \\
FHPM & 19271 & 183 & 70 & 10 & 943 \\ \hline
\end{tabular}
|
FHPM: Fine-grained Huge Page Management For Virtualization
|
Full monitoring Results on Redis.
| null |
cs.OS
|
|
2307.12707v1
|
\begin{tabular}{c l l l}
\hline
Parameters & Value ($n=1$) & Unit & Source\\
\hline
$\Lambda$ & $3032$ & day$^{-1}$ & assumed based on \\
$\beta$ & $0.15\times 10^{-8}$ & day$^{-1}$ & assumed based on \\
$\mu$ & $3.653 \times 10^{-5} $ & day$^{-1}$ & assumed based
on \\
$\epsilon$ & $0.15\times 10^{-8}$ & day$^{-1}$ & assumed based on \\
$t'$ & $1/120 $ & day$^{-1}$ & assumed based on \\
$\lambda$ & $0.8$ & day$^{-1}$ & assumed based on \\
$d$ & $0.02$ & day$^{-1}$ & assumed based on \\
$\alpha_1$ & $0.01$ & day$^{-1}$ & assumed \\
$\alpha_2$ & $0.01$ & day$^{-1}$ & assumed \\
$\omega$ & $4$ & day$^{-1}$ & \\
{$\varphi$} & $2$ & day$^{-1}$ & \\
$\kappa$ & $20000$ & copies $/$day & assumed based on \\
$\xi$ & {$0.125$} & day$^{-1}$ & \\
$\delta$ & $0.06$ & day$^{-1}$ & assumed based on \\
$\sigma$ & $0.01$ & day$^{-1}$ & \\
\end{tabular}
|
Dynamics of a mathematical model of virus spreading incorporating the effect of a vaccine
|
Biologically meaningful parameters used in Fig. \ref{Fig:SIRV}.
|
['\\newcommand{\\e}{{\\rm e}}']
|
math.DS, q-bio.QM, 00A71 34D20 37M05 37N25 92D30
|
|
2311.00820v2
|
\begin{tabular}{l c cccc c cccc c cccc}
& & \multicolumn{4}{c}{$\rho = 0.90$} & & \multicolumn{4}{c}{$\rho = 0.95$} & & \multicolumn{4}{c}{$\rho = 0.99$}\\
& & $\beta_1$ & $\beta_2$ & $\beta_3$ & $\beta_4$ & & $\beta_1$ & $\beta_2$ & $\beta_3$ & $\beta_4$ & & $\beta_1$ & $\beta_2$ & $\beta_3$ & $\beta_4$ \\
\textsc{lm} & & 0.92 & 0.65 & 0.71 & 0.76 & & 0.95 & 0.71 & 0.82 & 0.84 & & 0.99 & 0.86 & 0.93 & 0.93 \\
\textsc{qp} & & 0.94 & 0.91 & 0.90 & 0.93 & & 0.96 & 0.95 & 0.96 & 0.95 & & 0.99 & 1.00 & 0.99 & 1.00 \\
\end{tabular}
|
Bayesian inference for generalized linear models via quasi-posteriors
|
\small Heteroscedastic continuous data example. Frequentist coverage of credible intervals with nominal level $\rho \in \{0.90, 0.95, 0.99\}$ for Gaussian linear model (\textsc{lm}) and quasi-posterior (\textsc{qp}).
|
['\\newcommand{\\Y}{\\bm{Y}}', '\\newcommand{\\y}{\\bm{y}}', '\\newcommand{\\X}{\\bm{X}}', '\\newcommand{\\x}{\\bm{x}}', '\\newcommand{\\bmbeta}{\\bm{\\beta}}', '\\newcommand{\\hbmbeta}{\\Hat{\\bm{\\beta}}}', '\\newcommand{\\dd}{\\mathrm{d}}', '\\newcommand{\\var}{\\mathrm{var}}', '\\newcommand{\\E}{\\mathds{E}}', '\\newcommand{\\PP}{\\mathds{P}}', '\\newcommand{\\R}{\\mathds{R}}', '\\newcommand{\\at}[2][]{#1|_{#2}}']
|
stat.ME
|
|
2309.08249v1
|
\begin{tabular}{|c|c|c|c|}
\hline
& $\check{d}(v,u)$ & $\hat{d}(v,u)$ & $\bar{d}(v)$ \\ \hline
$\beta=0$
& $vu^{-1}$ & $\log(u)$ & $u(\log(v)-1)$ \\
$\beta \in [1,2] $
& $d_{\beta}(v,u)$ & 0 & 0 \\ \hline
\end{tabular}
|
Deep Nonnegative Matrix Factorization with Beta Divergences
|
Differentiable convex-concave-constant decomposition of the $\beta$-divergence under the form \eqref{eq:3}~.
|
['\\newcommand{\\ngc}[1]{{\\color{brightpink} (\\textbf{NG:} #1)}}', '\\newcommand{\\ngi}[1]{{{\\color{brightpink} #1}}}', '\\newcommand{\\vlc}[1]{{\\color{blue} (\\textbf{VL:} #1)}}', '\\newcommand{\\vli}[1]{{{\\color{blue} #1}}}', '\\newcommand{\\Akwum}[1]{{{\\color{red} Akwum: #1}}}', '\\newcommand{\\hien}[1]{{{\\color{magenta} Hien: #1}}}', '\\newcommand{\\mcalX}{\\mathcal{X}}']
|
cs.LG, cs.NA, eess.SP, math.NA, stat.ML
|
|
2308.15270v2
|
\begin{tabular}{cllll}
& $A$ & 118 & 120 & 122 \\\hline
& $Q_\beta$ (keV) & 527(21) & 1770(40) & 2960(50) \\
AME20& $T_{1/2}$ & 50.3(2) m & 50.80(21) s & 5.24(3) s \\
& $\log(ft)$ & 3.93(6) & 4.09(4) & 4.02(4) \\\hline
& $Q_\beta$ (keV) & 587.1(28) & 1752.1(46) & 2861.1(25) \\
JYFLTRAP & $T_{1/2}$ & 50.3(2) m & 50.80(21) s & 5.98(10) s \\
& $\log(ft)$ & 4.089(8) & 4.077(5) & 4.019(8) \\
\end{tabular}
|
High-precision Penning-trap mass measurements of Cd and In isotopes at JYFLTRAP remove the fluctuations in the two-neutron separation energies
|
\label{tab:logft}A comparison of the $\log(ft)$ values for the $^{A}\mathrm{Cd}(0^+_{gs})\longrightarrow$ $^{A}\mathrm{In}(1^+_1)$ decay calculated with the $\log(ft)$ calculator using the $Q_\beta$ and the half-lives $T_{1/2}$ values from AME20/NUBASE20 with the results from JYFLTRAP (this work and Ref. ).
|
['\\newcommand*{\\ak}[1]{\\textcolor{blue}{AK: #1}}', '\\newcommand*{\\ms}[1]{\\textcolor{red}{MS: #1}}']
|
nucl-ex
|
|
2310.09302v2
|
\begin{tabular}{cl}
\hline
Model ID & Formula \\
\hline
1 & PM25 $\sim$ X \\
2 & \texttt{PM25} $\sim$ \texttt{X + Season} \\
3 & \texttt{PM25} $\sim$ \texttt{X : Season} \\
4 & \texttt{PM25} $\sim$ \texttt{X * Season} \\
5 & \texttt{PM25} $\sim$ \texttt{X + Milano} \\
6 & \texttt{PM25} $\sim$ \texttt{X + Season + Milano} \\
7 & \texttt{PM25} $\sim$ \texttt{(X : Season) : Milano} \\
8 & \texttt{PM25} $\sim$ \texttt{X : Season * Milano} \\
9 & \texttt{PM25} $\sim$ \texttt{(X * Season): Milano} \\
10 & \texttt{PM25} $\sim$ \texttt{(X * Season)* Milano} \\
\hline
\end{tabular}
|
To what extent airborne particulate matters are influenced by ammonia and nitrogen oxides?
|
Regression models considered. \\
\texttt{X = lag(PM2.5)+NH3:nl+NOX+T+RH+WS+BLH+RainyDay}
| null |
physics.ao-ph
|
|
2305.06056v2
|
\begin{tabular}{|c|c|c|c|}
\hline
$n_{1}$ & $n_{2}$ & Effective Hamiltonian \\
\hline
0 & 0 & $E=0$ \\
\hline
0 & 2 & $E=V$ \\
\hline
2 &0 & $E=V$ \\
\hline
2&2&$E=3V$\\
\hline
0&1&$H=J(a_{2}^{\dagger}b_{2}+ {\rm H.c.})$\\
\hline
1&0&$H=J(a_{1}^{\dagger}b_{1}+ {\rm H.c.})$\\
\hline
1&2&$H=J(a_{1}^{\dagger}b_{1}+ {\rm H.c.})+Vb_{1}^{\dagger}b_{1}+V$\\
\hline
2&1&$H=J(a_{2}^{\dagger}b_{2}+ {\rm H.c.})+Va_{2}^{\dagger}a_{2}+V$\\
\hline
1&1&$H=J(a_{2}^{\dagger}b_{2}+a_{1}^{\dagger}b_{1}+ {\rm H.c.})+Vn_{b,1}n_{a,2}$\\
\hline
\end{tabular}
|
Dynamical localization and slow thermalization in a class of disorder-free periodically driven one-dimensional interacting systems
|
\label{effHa_twosite} Allowed configurations and the corresponding
effective Hamiltonians for two unit cells at a DL point with $\mu \gg V$ for a
period-4 model.
|
['\\newcommand\\bea{\\begin{eqnarray}}', '\\newcommand\\eea{\\end{eqnarray}}', '\\newcommand\\beq{\\begin{equation}}', '\\newcommand\\eeq{\\end{equation}}', '\\newcommand\\bib{\\bibitem}', '\\newcommand{\\new}{\\newpage}', '\\newcommand{\\noi}{\\noindent}', '\\newcommand{\\non}{\\nonumber}', '\\newcommand{\\al}{\\alpha}', '\\newcommand{\\de}{\\delta}', '\\newcommand{\\De}{\\Delta}', '\\newcommand{\\ga}{\\gamma}', '\\newcommand{\\ep}{\\epsilon}', '\\newcommand{\\ka}{\\kappa}', '\\newcommand{\\lm}{\\lambda}', '\\newcommand{\\si}{\\sigma}', '\\newcommand{\\ta}{\\theta}', '\\newcommand{\\om}{\\omega}', '\\newcommand{\\da}{\\dagger}', '\\newcommand{\\pa}{\\partial}', '\\newcommand{\\la}{\\langle}', '\\newcommand{\\ra}{\\rangle}', '\\newcommand{\\bra}[1]{\\langle #1|}', '\\newcommand{\\ket}[1]{|#1\\rangle}']
|
cond-mat.stat-mech, cond-mat.dis-nn, cond-mat.str-el
|
|
2309.02354v2
|
\begin{tabular}{c c c c c }
\hline
Brick & Height & Support & Controller & Success Rate\\
\hline
\multirow{8}{*}{1x2} & \multirow{4}{*}{1} & \multirow{4}{*}{Solid} & \multirow{2}{*}{Joint JPC} & (\textbf{100\%} / 96\%)\\
& & & & [\textbf{100\%}/\textbf{100\%}]\\
& & & \multirow{2}{*}{Cartesian JPC} & (\textbf{100\%} / 86.8\%)\\
& & & & [\textbf{100$\%$} / \textbf{100$\%$}]\\
\cline{2-5}
& \multirow{4}{*}{10} & \multirow{4}{*}{Solid} & \multirow{2}{*}{Joint JPC} & (\textbf{100\%} / 89.2\%)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
& & & \multirow{2}{*}{Cartesian JPC} & (\textbf{100\%} / 85.2$\%$)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
\hline
\multirow{12}{*}{1x4} & \multirow{4}{*}{1} & \multirow{4}{*}{Solid} & \multirow{2}{*}{Joint JPC} & (\textbf{100\%} / 92\%)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
& & & \multirow{2}{*}{Cartesian JPC} & (\textbf{100\%} / 93.2\%)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
\cline{2-5}
& \multirow{8}{*}{10} & \multirow{4}{*}{Solid} & \multirow{2}{*}{Joint JPC} & (\textbf{100\%} / 89.6\%)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
& & & \multirow{2}{*}{Cartesian JPC} & (\textbf{100\%} / 90.8\%)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
\cline{3-5}
& & \multirow{4}{*}{Hollow} & \multirow{2}{*}{Joint JPC} & (\textbf{100\%} / 88\%)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
& & & \multirow{2}{*}{Cartesian JPC} & (\textbf{100\%} / 83.6\%)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
\hline
\multirow{8}{*}{2x2} & \multirow{4}{*}{1} & \multirow{4}{*}{Solid} & \multirow{2}{*}{Joint JPC} & (\textbf{100\%} / 94.8$\%$)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
& & & \multirow{2}{*}{Cartesian JPC} & (\textbf{100\%} / 98\%)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
\cline{2-5}
& \multirow{4}{*}{10} & \multirow{4}{*}{Solid} & \multirow{2}{*}{Joint JPC} & (\textbf{100\%} / 93.2\%)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
& & & \multirow{2}{*}{Cartesian JPC} & (\textbf{100\%} / 94\%)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
\hline
\multirow{12}{*}{2x4} & \multirow{4}{*}{1} & \multirow{4}{*}{Solid} & \multirow{2}{*}{Joint JPC} & (\textbf{100\%} / 96\%)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
& & & \multirow{2}{*}{Cartesian JPC} & (\textbf{100\%} / 92.4\%)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
\cline{2-5}
& \multirow{8}{*}{10} & \multirow{4}{*}{Solid} & \multirow{2}{*}{Joint JPC} & (\textbf{100\%} / 95.2\%)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
& & & \multirow{2}{*}{Cartesian JPC} & (\textbf{100\%} / 98\%)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
\cline{3-5}
& & \multirow{4}{*}{Hollow} & \multirow{2}{*}{Joint JPC} & (\textbf{100\%} / 94.8\%)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
& & & \multirow{2}{*}{Cartesian JPC} & (\textbf{100\%} / 84.4\%)\\
& & & & [\textbf{100\%} / \textbf{100\%}]\\
\hline
\end{tabular}
|
A Lightweight and Transferable Design for Robust LEGO Manipulation
|
\footnotesize Success rate of LEGO brick manipulation. $(\cdot/\cdot):$ assembling and disassembling success rate without safe learning. $[\cdot/\cdot]:$ optimized assembling and disassembling success rate with safe learning.\label{table:EOAT_performance}
|
['\\newcommand{\\ie}{\\textit{i}.\\textit{e}., }', '\\newcommand{\\eg}{\\textit{e}.\\textit{g}., }', '\\newcommand{\\st}{\\text{s.t. }}', '\\newcommand\\ruixuan[1]{{\\color{magenta}{#1}}}']
|
cs.RO, cs.LG, cs.NE
|
|
2309.16532v1
|
\begin{tabular}{c c | c c}
\hline\hline
\noalign{\smallskip}
BJD & $v_{\rm rad}$ & BJD & $v_{\rm rad}$\\
$-$ 2\,450\,000 &(km\,s$^{-1}$) & $-$ 2\,450\,000 & (km\,s$^{-1}$)\\
\noalign{\smallskip}
\hline
\noalign{\medskip}
9459.6291 & $+$363.2(11) & 9525.4729 & $+$359.0(11)\\
9461.6065 & $+$355.9(27) & 9528.4326 & $+$337.6(14)\\
9493.5252 & $+$375.9(40) & 9530.4650 & $+$294.3(26)\\
9494.5583 & $+$348.3(28) & 9550.3652 & $+$208.3(34)\\
9512.4829 & $+$238.8(25) & 9559.3702 & $+$357.5(16)\\
9518.4816 & $+$211.8(12) & 9560.3423 & $+$337.4(23)\\
9521.4845 & $+$247.9(32) & 9628.3107 & $+$300.5(40)\\
9523.4583 & $+$325.9(19) & 9630.2836 & $+$280.0(30)\\
\noalign{\smallskip}
\hline
\end{tabular}
|
Exploring extreme brightness variations in blue supergiant MACHO 80.7443.1718: Evidence for companion-driven enhanced mass loss
|
Barycentric radial velocities $v_{\rm rad}$ of the primary component of ExtEV extracted from the SALT/HRS spectra.
|
['\\newcommand{\\comm}[1]{\\textcolor{comm}{#1}}', '\\newcommand{\\old}[1]{\\textcolor{old}{#1}}', '\\newcommand{\\new}[1]{\\textcolor{new}{#1}}', '\\newcommand{\\done}[1]{\\textcolor{done}{#1}}', '\\newcommand{\\todo}[1]{\\textcolor{todo}{#1}}', '\\newcommand{\\idea}[1]{\\textcolor{idea}{#1}}', '\\newcommand{\\kms}{km\\,s$^{-1}$}', '\\newcommand{\\cd}{d$^{-1}$}']
|
astro-ph.SR, astro-ph.HE
|
|
2309.03486v1
|
\begin{tabular}{lcccccc}
config. id & cub. & s. cub. & sph. & s. sph. & cyl. & s. cyl. \\
\hline
1 DEISM & 1.918 & 1.214 & 2.268 & 1.143 & 2.062 & 0.950 \\
1 DEISM-LC & 1.669 & 1.070 & 2.206 & 1.125 & 2.007 & 0.916 \\
\hline
2 DEISM & 1.974 & 1.051 & 2.521 & 1.003 & 1.900 & 0.964 \\
2 DEISM-LC & 1.855 & 1.003 & 2.060 & 0.984 & 1.809 & 0.943 \\
\hline
3 DEISM & 0.423 & 0.204 & 0.841 & 0.170 & 0.920 & 0.154 \\
3 DEISM-LC & 0.427 & 0.206 & 0.883 & 0.174 & 0.952 & 0.155 \\
\hline
4 DEISM & 7.018 & 8.187 & 6.457 & 7.418 & 6.350 & 7.287 \\
4 DEISM-LC & 6.864 & 8.149 & 6.461 & 7.298 & 6.240 & 7.211 \\
\hline
5 DEISM & 6.887 & 6.810 & 7.077 & 6.309 & 7.011 & 6.425 \\
5 DEISM-LC & 6.792 & 6.807 & 6.986 & 6.277 & 6.968 & 6.397 \\
\end{tabular}
|
Simulating room transfer functions between transducers mounted on audio devices using a modified image source method
|
Root-mean-square log spectral distance in decibel between DEISM and FEM, and between DEISM-LC and FEM. (s. denotes small.)
|
['\\newcommand{\\round}[1]{\\ensuremath{\\lfloor#1\\rceil}}', '\\newcommand{\\pluseq}{\\mathrel{+}=}', '\\newcommand{\\tc}[1]{\\textcolor{blue}{#1}}']
|
eess.AS, cs.SD
|
|
2306.07228v1
|
\begin{tabular}{||c||c|c|c|c|c|c|c| c||}
\hline
~~~ ensemble ~~~ & ~~~ $\beta$ ~~~ & ~~~ $V/a^{4}$ ~~~ & ~~~ $a$\,(fm) ~~~ & ~ $M_{\pi}$\,(MeV) ~ & ~ $M_{D_{s}}$(GeV) ~ & ~ $L$ (fm) ~ & ~ $N_{g}$ ~ & ~ $N_{\rm s}$ ~\\
\hline
cB211.072.64 & $1.778$ & $64^{3}\cdot 128$ & $0.07957~(13)$ & $140.2~(0.2)$ & $1.990~(3)$ & $5.09$ & $300$ & 4 \\
\hline
\end{tabular}
|
Spectral-function determination of complex electroweak amplitudes with lattice QCD
|
\it \small Parameters of the single ETMC ensemble used in this work. We give the lattice spacing $a$, the pion mass $M_\pi$, the $D_{s}$ meson mass $M_{D_{s}}$, the lattice extent $L$, the number of gauge configurations analyzed $N_{g}$, and the number $N_{\rm s}$ of random stochastic sources that have been used for each inversion of the Dirac operator. The random sources we used are randomly distributed over time, diagonal in spin and dense in the color.
|
['\\newcommand{\\be}{\\begin{equation}}', '\\newcommand{\\ee}{\\end{equation}}', '\\newcommand{\\bea}{\\begin{eqnarray}}', '\\newcommand{\\eea}{\\end{eqnarray}}', '\\newcommand{\\bs}{\\boldsymbol}', '\\newcommand{\\beq}{\\begin{equation}}', '\\newcommand{\\eeq}{\\end{equation}}', '\\newcommand{\\msbar}{\\overline{\\footnotesize\\textrm{MS}}}', '\\newcommand{\\nn}{\\nonumber}', '\\newcommand{\\gev}{{\\rm GeV}}', '\\newcommand{\\mev}{{\\rm MeV}}', '\\newcommand{\\msb}{\\overline{\\rm{MS}}}', '\\newcommand{\\<}{\\langle} ', '\\newcommand{\\la}{\\langle} ', '\\newcommand{\\ra}{\\rangle} ', '\\newcommand{\\wt}{\\widetilde} ', '\\newcommand{\\idnty}{\\hbox{1$\\!\\!$1}} ', '\\newcommand{\\vettq}{\\mbox{\\bf{q}}} ', '\\newcommand{\\vettx}{\\mbox{\\bf{x}}} ', '\\newcommand{\\Li}{{\\cal L}} ', '\\newcommand{\\bfr}{{\\bf r}} ', '\\newcommand{\\bfp}{{\\bf p}} ', '\\newcommand{\\half}{\\frac{1}{2}} ', '\\newcommand{\\V}{\\mathcal{V}} ', '\\newcommand{\\G}{\\Gamma}', '\\newcommand{\\QCD}{\\mathrm{QCD}}', '\\newcommand{\\QED}{\\mathrm{QED}}', '\\newcommand{\\EM}{\\mathrm{em}}', '\\newcommand{\\ZO}{Z_{O}}', '\\newcommand{\\ZOQCD}{Z_{O}^\\mathrm{QCD}}', '\\newcommand{\\Zq}{Z_q}', '\\newcommand{\\ZqQCD}{Z_q^\\mathrm{QCD}}', '\\newcommand{\\LO}{\\Lambda_{O}}', '\\newcommand{\\LOzero}{\\Lambda_{O}^{0}}', '\\newcommand{\\LOem}{\\Lambda_{O}^{\\EM}}', '\\newcommand{\\LOA}{\\Lambda_{O}^{\\mathrm{A}}}', '\\newcommand{\\LOB}{\\Lambda_{O}^{\\mathrm{B}}}', '\\newcommand{\\GO}{\\Gamma_{O}}', '\\newcommand{\\GAMMAOzero}{\\Gamma_{O}^{\\,0}}', '\\newcommand{\\GAMMAOem}{\\Gamma_{O}^{\\,\\EM}}', '\\newcommand{\\GAMMAOA}{\\Gamma_{O}^{\\,\\mathrm{A}}}', '\\newcommand{\\GAMMAOB}{\\Gamma_{O}^{\\,\\mathrm{B}}}', '\\newcommand{\\GOzero}{G_{O}^{\\,0}}', '\\newcommand{\\GOem}{G_{O}^{\\,\\EM}}', '\\newcommand{\\SQCD}{S_\\QCD}', '\\newcommand{\\SSIGMA}{S_\\Sigma}', '\\newcommand{\\SEM}{S_\\EM}', '\\newcommand{\\DEM}{\\Delta_\\EM}', '\\newcommand{\\RIMOMprime}{{RI\\textquotesingle -MOM}}', '\\newcommand{\\mr}{(m,r)}', '\\newcommand{\\mrprime}{(m^\\prime,r^\\prime)}', '\\newcommand{\\alphaem}{\\alpha_{em}}', '\\newcommand{\\eq}{\\alphaem q_f^2}', '\\newcommand{\\mydelta}{\\mathbf{\\Delta}}', '\\newcommand{\\Zcal}{\\mathcal{Z}}', '\\newcommand{\\gol}{\\raisebox{-0.0\\totalheight}{\\includegraphics[scale=.4]{pics/g1l.pdf}}}', '\\newcommand{\\goi}{\\raisebox{-0.3\\totalheight}{\\includegraphics[scale=.4]{pics/g1i.pdf}}}', '\\newcommand{\\goip}{\\raisebox{-0.3\\totalheight}{\\includegraphics[scale=.4]{pics/g1ip.pdf}}}', '\\newcommand{\\golself}{\\raisebox{-0.0\\totalheight}{\\includegraphics[scale=.4]{pics/g1l_self.pdf}}}', '\\newcommand{\\golltad}{\\raisebox{-0.0\\totalheight}{\\includegraphics[scale=.4]{pics/g1l_ltad.pdf}}}', '\\newcommand{\\gexc}{\\raisebox{-0.4\\totalheight}{\\includegraphics[scale=.7]{pics/G11.pdf}}}', '\\newcommand{\\gin}{\\raisebox{-0.4\\totalheight}{\\includegraphics[scale=.7]{pics/G20.pdf}}}', '\\newcommand{\\gout}{\\raisebox{-0.4\\totalheight}{\\includegraphics[scale=.7]{pics/G02.pdf}}}', '\\newcommand{\\Gselfin}{\\raisebox{-0.45\\totalheight}{\\includegraphics[scale=.7]{pics/G4f_1.pdf}}}', '\\newcommand{\\Gselfout}{\\raisebox{-0.45\\totalheight}{\\includegraphics[scale=.7]{pics/G4f_2.pdf}}}', '\\newcommand{\\Gexch}{\\raisebox{-0.45\\totalheight}{\\includegraphics[scale=.7]{pics/G4f_3.pdf}}}', '\\newcommand{\\Gexchin}{\\raisebox{-0.45\\totalheight}{\\includegraphics[scale=.7]{pics/G4f_4.pdf}}}', '\\newcommand{\\Gexchout}{\\raisebox{-0.45\\totalheight}{\\includegraphics[scale=.7]{pics/G4f_5.pdf}}}', '\\newcommand{\\dtwo}{d^{\\hspace{1pt}2}}', '\\newcommand{\\dthree}{d^{\\hspace{1pt}3}}', '\\newcommand{\\dfour}{d^{\\hspace{1.35pt}4}}', '\\newcommand{\\rev}{\\clubsuit}', '\\newcommand{\\Romatre}{Dipartimento di Matematica e Fisica, Universit\\`a Roma Tre and INFN, Sezione di Roma Tre,\\\\ Via della Vasca Navale 84, I-00146 Rome, Italy}', '\\newcommand{\\RomatreINFN}{Istituto Nazionale di Fisica Nucleare, Sezione di Roma Tre,\\\\ Via della Vasca Navale 84, I-00146 Rome, Italy}', '\\newcommand{\\Romadue}{Dipartimento di Fisica and INFN, Universit\\`a di Roma ``Tor Vergata",\\\\ Via della Ricerca Scientifica 1, I-00133 Roma, Italy}', '\\newcommand{\\LaSapienza}{Physics Department and INFN Sezione di Roma La Sapienza,\\\\ Piazzale Aldo Moro 5, 00185 Roma, Italy}', '\\newcommand{\\soton}{Department of Physics and Astronomy, University of Southampton,\\\\ Southampton SO17 1BJ, UK \\\\}']
|
hep-lat
|
|
2312.08625v1
|
\begin{tabular}{|c|c|c|}
\hline
{No.} & {Feature} & {Quantity} \\ \hline
{1.} & {${p}^n$} & {current pressure}\\
{2.} & {${S}^n_w$} & {current water saturation}\\
{3.} & {${k}$} & {permeability}\\
{4.} & {${\phi}$} & {porosity}\\
{5.} & {${V}$} & {cell bulk volume}\\
{6.} & {${D}$} & {cell depth}\\
{7.} & {${W}$} & {well index (for well cells)}\\
{8.} & {${p^w}$} & {wellbore pressure (for well cells)}\\
{9.} & {${e}$} & {encoding of node type}\\
{10.} & {${p}_{1p}$} & {single-phase steady-state pressure}\\
\hline
\end{tabular}
|
Graph Network Surrogate Model for Subsurface Flow Optimization
|
Node features used in the GNSM
|
['\\newcommand{\\Ud}{\\mathrm{d}} ', '\\newcommand{\\Bx}{\\mathbf{x}}', '\\newcommand{\\By}{\\mathbf{y}} ', '\\newcommand{\\Bh}{\\mathbf{h}} ', '\\newcommand{\\Ba}{\\mathbf{a}}', '\\newcommand{\\Bb}{\\mathbf{b}}', '\\newcommand{\\Bxstar}{\\mathbf{x}^{*}}', '\\newcommand{\\Bz}{\\mathbf{z}}', '\\newcommand{\\Bxi}{\\boldsymbol{\\xi}}', '\\newcommand{\\BXi}{\\boldsymbol{\\Xi}}', '\\newcommand{\\Bximap}{\\boldsymbol{\\xi}_\\text{map}}', '\\newcommand{\\Bxirml}{\\boldsymbol{\\xi}_\\text{rml}}', '\\newcommand{\\Bxiuc}{\\boldsymbol{\\xi}_p}', '\\newcommand{\\Bm}{\\mathbf{m}}', '\\newcommand{\\Bw}{\\mathbf{w}}', '\\newcommand{\\BM}{\\mathbf{M}}', '\\newcommand{\\Bg}{\\mathbf{g}}', '\\newcommand{\\Bmref}{\\Bm_{\\text{ref}}}', '\\newcommand{\\Bmbar}{\\bar{\\mathbf{m}}}', '\\newcommand{\\Bmuc}{\\mathbf{m}_\\text{uc}}', '\\newcommand{\\Bmpca}{\\mathbf{m}_\\text{pca}}', '\\newcommand{\\Bmopca}{\\mathbf{m}_\\text{opca}}', '\\newcommand{\\Bmcnnpca}{\\mathbf{m}_\\text{cnn}}', '\\newcommand{\\Bu}{\\mathbf{u}}', '\\newcommand{\\argmin}[1]{\\underset{#1}{\\text{argmin}}}', '\\newcommand{\\erf}[1]{\\text{erf}(#1)}', '\\newcommand{\\Bd}{\\mathbf{d}} ', '\\newcommand{\\Bdobs}{\\mathbf{d}}', '\\newcommand{\\Cd}{C_{\\text{d}}}', '\\newcommand{\\Cdinv}{C^{-1}_{\\text{d}}}', '\\newcommand{\\Cm}{C_{\\text{m}}}', '\\newcommand{\\Cminv}{C^{-1}_{\\text{m}}}', '\\newcommand{\\Nr}{N_{\\text{r}}}', '\\newcommand{\\Nx}{N_x}', '\\newcommand{\\Ny}{N_y}', '\\newcommand{\\Nb}{N_{\\text{b}}}', '\\newcommand{\\Nc}{N_{\\text{c}}}', '\\newcommand{\\Nt}{N_{\\text{t}}}', '\\newcommand{\\Nh}{N_{\\text{h}}}', '\\newcommand{\\Nep}{N_\\text{ep}}', '\\newcommand{\\Nz}[1]{N_{z,#1}}', '\\newcommand{\\Nct}{N_{\\text{c}}^{\\text{t}}}', '\\newcommand{\\td}{\\text{d}}', '\\newcommand{\\Bnu}{\\boldsymbol{\\nu}}', '\\newcommand{\\COtwo}{\\text{CO}_2}', '\\newcommand{\\Smap}{S_\\text{map}}', '\\newcommand{\\Srml}{S_\\text{rml}}', '\\newcommand{\\Sd}{S_\\text{d}}', '\\newcommand{\\Sm}{S_\\text{m}}', '\\newcommand{\\lr}{l_\\text{r}}', '\\newcommand{\\Swir}{S_\\text{wir}}', '\\newcommand{\\Sor}{S_\\text{or}}', '\\newcommand{\\nw}{{n_\\text{w}}}', '\\newcommand{\\no}{{n_\\text{o}}}', '\\newcommand{\\Bmkr}{\\mathbf{m}_\\text{kr}}', '\\newcommand{\\Bmkrbar}{\\bar{\\mathbf{m}}_\\text{kr}}', '\\newcommand{\\Bmkruc}{\\mathbf{m}_\\text{kr,uc}}', '\\newcommand{\\Ckr}{C_\\text{kr}}', '\\newcommand{\\Ckrinv}{C_\\text{kr}^{-1}}', '\\newcommand{\\cmpd}{\\text{m}^3/\\text{day}}', '\\newcommand{\\StdGauss}{N(\\boldsymbol{0},I)}', '\\newcommand{\\Nrml}{N_\\text{rml}}', '\\newcommand{\\Niter}{N_\\text{iter}}', '\\newcommand{\\Nd}{N_\\text{d}}', '\\newcommand{\\tsim}{t_\\text{sim}}', '\\newcommand{\\textapprox}{\\raisebox{0.5ex}{\\texttildelow}}', '\\newcommand{\\BBR}{\\mathbb{R}}', '\\newcommand{\\mref}{M_\\text{ref}}', '\\newcommand{\\hp}{\\hspace{8px}}', '\\newcommand{\\hps}{\\hspace{4px}}', '\\newcommand{\\Lt}{L_\\text{t}}', '\\newcommand{\\Lc}{L_\\text{c}}', '\\newcommand{\\Ls}{L_\\text{s}}', '\\newcommand{\\Lh}{L_\\text{h}}', '\\newcommand{\\al}{\\alpha_l}', '\\newcommand{\\bl}{\\beta_l}', '\\newcommand{\\Nl}{N_l}', '\\newcommand{\\Dl}{D_l}', '\\newcommand{\\FO}{F_l[O]}', '\\newcommand{\\FI}{F_l[I]}', '\\newcommand{\\Fd}{F_l[\\cdot]}', '\\newcommand{\\GO}{G_l[O]}', '\\newcommand{\\Gd}{G_l[\\cdot]}', '\\newcommand{\\GS}{G_l[S]}', '\\newcommand{\\TI}{\\text{TI}}', '\\newcommand{\\CF}{\\text{CF}}', '\\newcommand{\\Ne}{N_\\text{e}}']
|
physics.geo-ph, cs.LG
|
|
2307.02896v1
|
\begin{tabular}{ll|ll}
\hline
Parameter & Value & Parameter & Value\\
\hline
$K$ & 64 & $T_s$ & 5 $\rm \mu$s \\
$G_t^s,\,G_r^s$ & 30 dB & $N_s$ & 16 \\
$G_r^c$ & 30 dB & $\sigma^2$ & -174 dBm/Hz \\
$G_s^c$ & 0 dB & $|a_k|^2$ & 1 W \\
$\eta$ & 1 m$^2$ & $\mu$ & 0.5 \\
\hline
\end{tabular}
|
Robust Deployment and Resource Allocation for Robotic Aerial Base Station Enabled OFDM Integrated Sensing and Communication
|
Parameter Settings
| null |
cs.NI
|
|
2306.14691v1
|
\begin{tabular}{|c|c|c|}
\hline
\textbf{Time width [ms]} & \textbf{Average $\mu$ [V]} & \textbf{Variance $\sigma$ [V]} \\
\hline
0.05 & 2.31 & 0.38 \\
\hline
0.10 & 2.11 & 0.33 \\
\hline
0.15 & 1.86 & 0.30 \\
\hline
0.50 & 1.73 & 0.22 \\
\hline
1.00 & 1.21 & 0.16 \\
\hline
2.00 & 0.61 & 0.15 \\
\hline
5.00 & 0.59 & 0.11 \\
\hline
\end{tabular}
|
Tunable Synaptic Working Memory with Volatile Memristive Devices
|
Values of $\mu$ and $\sigma$ calculated for different pulse time widths.
|
['\\newcommand{\\erika}[1] {{\\color[rgb]{0 0.8 0.4} { \\textbf{Erika:} #1}}}']
|
cs.ET
|
|
2312.16280v1
|
\begin{tabular}{|c|c|}
\hline
$\alpha$ & $(a,\sigma)$ \\
\hline
$\beta$ & $(b,\sigma^\prime)$ \\
\hline
$\gamma$ & $(c,\sigma^{\prime\prime})$ \\
\hline
$\alpha^\prime$ & $(a_1,\sigma_1)$ \\
\hline
$\beta^\prime$ & $(a_2,\sigma_2)$ \\
\hline
$\gamma^\prime$ & $(a_3,\sigma_3)$ \\
\hline
$\delta^\prime$ & $(a_4,\sigma_4)$ \\
\hline
\end{tabular}
|
Two-particle self-consistent approach for broken symmetry phases
|
Relation between indices expressed in the compact and extended notations.
|
['\\newcommand{\\ket}[1]{\\left|#1\\right>}', '\\newcommand{\\bra}[1]{\\left<#1\\right|}', '\\newcommand{\\LK}[1]{\\textcolor{red}{#1}}', '\\newcommand{\\LC}[1]{\\textcolor{magenta}{#1}}', '\\newcommand{\\LD}[1]{\\textcolor{blue}{#1}}', '\\newcommand{\\up}{\\uparrow}', '\\newcommand{\\dow}{\\downarrow}', '\\newcommand{\\bR}{\\mathbf{R}}', '\\newcommand{\\br}{\\mathbf{r}}', '\\newcommand{\\bX}{\\mathbf{X}}', '\\newcommand{\\cc}{c^{\\phantom{\\dagger}}}', '\\newcommand{\\bq}{\\mathbf{q}}', '\\newcommand{\\bQ}{\\mathbf{Q}}', '\\newcommand{\\bk}{\\mathbf{k}}', '\\newcommand{\\bx}{\\mathbf{x}}', '\\newcommand{\\heff}{H_{\\mbox{\\footnotesize \\emph{eff}}} }', '\\newcommand{\\by}{\\mathbf{y}}', '\\newcommand{\\bo}{\\mathbf{0}}', '\\newcommand{\\cd}{c^\\dag}', '\\newcommand{\\bd}{b^\\dag}', '\\newcommand{\\psid}{\\psi^\\dag}', '\\newcommand{\\Psid}{\\Psi^\\dag}', '\\newcommand{\\phid}{\\phi^\\dag}', '\\newcommand{\\tphid}{\\widetilde{\\phi}^\\dag}', '\\newcommand{\\chid}{\\chi^\\dag}', '\\newcommand{\\bhi}{\\boldsymbol\\varphi}', '\\newcommand{\\pphi}{\\varphi}', '\\newcommand{\\thi}{\\tilde{\\varphi}}', '\\newcommand{\\dd}{d^\\dag}', '\\newcommand{\\ddd}{d^{\\ }}', '\\newcommand{\\av}[1]{\\left <#1\\right>}']
|
cond-mat.str-el, cond-mat.quant-gas, cond-mat.supr-con
|
|
2310.17348v1
|
\begin{tabular}{|c|c|c|c|}
\hline \multicolumn{4}{|c|}{Inductive} \\
\hline Class Name & Precision & Recall & F1-Score \\
\hline Benign & 26.73\% & 92.18\% & 0.41\\
\hline DDos & 100.00\% & 91.70\% &0.96\\
\hline Dos & 39.13\% & 97.71\% &0.56 \\
\hline Reconnaissance & 99.68\% & 85.08\% & 0.92 \\
\hline Theft & 16.06\% &74.35\% &0.26 \\
\hline Weighted Average & 96.11\% & 89.41\% & 0.92\\
\hline
\end{tabular}
|
Network Intrusion Detection with Edge-Directed Graph Multi-Head Attention Networks
|
Multi-class classification results of the proposed EDGMAT on dataset NF-BoT-IoT under the inductive setting.
| null |
cs.CR
|
|
2311.13166v1
|
\begin{tabular}{c|c|cl|c|c}
\hline
\multicolumn{1}{c|}{\textbf{Type}} & \multicolumn{1}{c|}{\textbf{Device}} & \multicolumn{2}{c|}{\textbf{Comp}} & \textbf{Mem} & \textbf{Num} \\ \hline
Client-Weak & Raspberry Pi 4B & \multicolumn{2}{c|}{ARM Cortex-A72 CPU} & 2G & 4 \\
Client-Medium & Jetson Nano & \multicolumn{2}{c|}{128-core Maxwell GPU} & 8G & 10 \\
Client-Strong & Jetson Xavier AGX & \multicolumn{2}{c|}{512-core NVIDIA GPU} & 32G & 3 \\ \hline
Server & Workstation & \multicolumn{2}{c|}{NVIDIA RTX 4090 GPU} & 64G & 1 \\ \hline
\end{tabular}
|
AdaptiveFL: Adaptive Heterogeneous Federated Learning for Resource-Constrained AIoT Systems
|
Real test-bed platform settings
| null |
cs.LG, cs.DC
|
|
2309.01864v2
|
\begin{tabular}{c c c c c c}
\hline
Quantity & L1 & L2 & L3 & L4 & L5 \\
\hline
$E_b$ [MeV] & -15.677 & -15.677 & -15.677 & -15.677 & -15.677 \\
$K$ [MeV] & 275 & 275 & 275 & 275 & 275 \\
$J$ [MeV] & 30.7 & 30.7 & 30.7 & 30.7 & 30.7 \\
$L$ [MeV] & 35 & 45 & 55 & 65 & 75 \\
\hline
\end{tabular}
|
Far-from-equilibrium bulk-viscous transport coefficients in neutron star mergers
|
\label{L EoS nuclear} Nuclear properties of our EoSs L1 to L5. $E_b$ is the binding energy. $K$ is the nuclear compressibility. $J$ is the nuclear symmetry energy. $L$ is the slope of the nuclear symmetry energy. See for details on constraints on nuclear-matter properties.
|
['\\newcommand{\\cA}{\\mathcal A}', '\\newcommand{\\cB}{\\mathcal B}', '\\newcommand{\\cC}{\\mathcal C}', '\\newcommand{\\cD}{\\mathcal D}', '\\newcommand{\\cE}{\\mathcal E}', '\\newcommand{\\cF}{\\mathcal F}', '\\newcommand{\\cG}{\\mathcal G}', '\\newcommand{\\cH}{\\mathcal H}', '\\newcommand{\\cI}{\\mathcal I}', '\\newcommand{\\cJ}{\\mathcal J}', '\\newcommand{\\cK}{\\mathcal K}', '\\newcommand{\\cL}{\\mathcal L}', '\\newcommand{\\cM}{\\mathcal M}', '\\newcommand{\\cN}{\\mathcal N}', '\\newcommand{\\cO}{\\mathcal O}', '\\newcommand{\\cP}{\\mathcal P}', '\\newcommand{\\cQ}{\\mathcal Q}', '\\newcommand{\\cR}{\\mathcal R}', '\\newcommand{\\cS}{\\mathcal S}', '\\newcommand{\\cT}{\\mathcal T}', '\\newcommand{\\cU}{\\mathcal U}', '\\newcommand{\\cV}{\\mathcal V}', '\\newcommand{\\cW}{\\mathcal W}', '\\newcommand{\\cX}{\\mathcal X}', '\\newcommand{\\cY}{\\mathcal Y}', '\\newcommand{\\cZ}{\\mathcal Z}', '\\newcommand{\\ccB}{\\mathscr{B}}', '\\newcommand{\\ccE}{\\mathscr{E}}', '\\newcommand{\\ccD}{\\mathscr{D}}', '\\newcommand{\\ccL}{\\mathscr{L}}', '\\newcommand{\\ccW}{\\mathscr{W}}', '\\newcommand{\\al}{\\alpha}', '\\newcommand{\\ga}{\\gamma}', '\\newcommand{\\Ga}{\\Gamma}', '\\newcommand{\\de}{\\delta}', '\\newcommand{\\ep}{\\varepsilon}', '\\newcommand{\\la}{\\lambda}', '\\newcommand{\\La}{\\Lambda}', '\\newcommand{\\si}{\\sigma}', '\\newcommand{\\Si}{\\Sigma}', '\\newcommand{\\vfi}{\\varphi}', '\\newcommand{\\om}{\\omega}', '\\newcommand{\\Om}{\\Omega}', '\\newcommand{\\TT}{\\mathbb T}', '\\newcommand{\\RR}{\\mathbb R}', '\\newcommand{\\CC}{\\mathbb C}', '\\newcommand{\\HH}{\\mathbb H}', '\\newcommand{\\CP}{\\mathbb C \\mathbb P}', '\\newcommand{\\ZZ}{\\mathbb Z}', '\\newcommand{\\NN}{\\mathbb N}', '\\newcommand{\\vx}{\\vec{x}}', '\\newcommand{\\vy}{\\vec{y}}', '\\newcommand{\\vz}{\\vec{z}}', '\\newcommand{\\vk}{\\vec{k}}', '\\newcommand{\\vu}{\\vec{u}}', '\\newcommand{\\vv}{\\vec{v}}', '\\newcommand{\\vp}{\\vec{p}}', '\\newcommand{\\vq}{\\vec{q}}', '\\newcommand{\\vb}{\\vec{b}}', '\\newcommand{\\Bracket}[1]{\\left \\langle #1 \\right \\rangle }', '\\newcommand{\\cqd}{\\hfill $\\qed$\\\\ \\medskip}', '\\newcommand{\\rar}{\\rightarrow}', '\\newcommand{\\imp}{\\Rightarrow}', '\\newcommand{\\tr}{\\operatorname{tr}}', '\\newcommand{\\vol}{\\operatorname{vol}}', '\\newcommand{\\id}{\\operatorname{id}}', '\\newcommand{\\dive}{\\operatorname{div}}', '\\newcommand{\\p}{\\parallel}', '\\newcommand{\\norm}[1]{\\left\\Vert#1\\right\\Vert}', '\\newcommand{\\abs}[1]{\\left\\vert#1\\right\\vert}', '\\newcommand{\\pa}{\\partial}', '\\newcommand{\\mss}{\\hspace{0.2cm}}', '\\newcommand{\\ms}{\\hspace{0.25cm}}', '\\newcommand{\\msm}{\\hspace{0.3cm}}', '\\newcommand{\\msb}{\\hspace{0.35cm}}', '\\newcommand{\\kl}{k^\\prime{}}', '\\newcommand{\\wl}{\\omega^\\prime{}}', '\\newcommand{\\lan}{\\langle}', '\\newcommand{\\ran}{\\rangle}', '\\newcommand{\\bsi}{\\bar{\\sigma}}', '\\newcommand{\\bom}{\\bar{\\omega}}', '\\newcommand{\\brho}{\\bar{\\rho}}', '\\newcommand{\\bps}{\\bar{\\psi}}', '\\newcommand{\\be}{\\begin{equation}}', '\\newcommand{\\ee}{\\end{equation}}', '\\newcommand{\\bea}{\\begin{aligned}}', '\\newcommand{\\eea}{\\end{aligned}}', '\\newcommand{\\bfk}{\\mathbf{k}}', '\\newcommand{\\bfx}{\\mathbf{x}}', '\\newcommand{\\bfn}{\\mathbf{n}}', '\\newcommand{\\bfu}{\\mathbf{u}}', '\\newcommand{\\bml}{\\begin{subequations}}', '\\newcommand{\\eml}{\\end{subequations}}', '\\newcommand{\\nn}{N}', '\\newcommand{\\mass}{\\mathcal{M}}', '\\newcommand{\\vcal}{\\mathcal{V}}', '\\newcommand{\\qcal}{\\mathcal{Q}}', '\\newcommand{\\eqent}{S}', '\\newcommand{\\bbm}{\\begin{bmatrix}}', '\\newcommand{\\ebm}{\\end{bmatrix}}', '\\newcommand{\\bvm}{\\begin{vmatrix}}', '\\newcommand{\\evm}{\\end{vmatrix}}', '\\newcommand{\\overbar}[1]{\\mkern 1.5mu\\overline{\\mkern-1.5mu#1\\mkern-1.5mu}\\mkern 1.5mu}', '\\newcommand{\\jn}[1]{\\textcolor{red}{{\\textbf{jn: #1}}} }', '\\newcommand{\\yang}[1]{\\textcolor{blue}{{\\textbf{yang: #1}}} }', '\\newcommand{\\es}[1]{\\textcolor{magenta}{{\\textbf{es: #1}}} }', '\\newcommand{\\mh}[1]{\\textcolor{purple}{{\\textbf{mh: #1}}} }']
|
nucl-th, astro-ph.HE, hep-ph
|
|
2311.01879v1
|
\begin{tabular}{l c c c c c c c c c}
\hline
& ID & Cr & Al & Ti & Y & C & O & N & Ar \\
\hline
Fe12Cr9Al & SP12 & 11.93 & 8.65 & 0.53 & 0.38 & 0.029 & 0.22 & 0.003 & 0.006 \\
Fe15Cr9Al & SP13 & 14.25 & 8.4 & 0.51 & 0.38 & 0.03 & 0.22 & 0.003 & 0.006 \\
Fe18Cr9Al & SP14 & 16.63 & 8.09 & 0.49 & 0.37 & 0.032 & 0.22 & 0.003 & 0.006 \\
\hline
\end{tabular}
|
Effects of Cr content on ion-irradiation hardening of FeCrAl ODS ferritic steels with 9 wt\% Al
|
Chemical compositions of FeCrAl ODS ferritic steels (wt\%, Bal. Fe)
| null |
cond-mat.mtrl-sci
|
|
2310.08941v1
|
\begin{tabular}{lccc}
\hline
\hline
$\alpha$ & Silicate & Carbonate & Iron \\
\hline
$-3.5$ & 1.5$\times 10^{-14}$ & 1.0$\times 10^{-14}$ & 3.6$\times10^{-14}$\\
$-3.0$ & 6.0$\times 10^{-12}$ & 4.1$\times 10^{-12}$ & 1.4$\times10^{-11}$\\
$-2.5$ & 3.0$\times 10^{-9}$ & 2.0$\times 10^{-9}$ & 7.2$\times 10^{-9}$\\
$-2.0$ & 1.5$\times 10^{-6} $& 1.0$\times 10^{-6}$ & 3.6$\times 10^{-6}$\\
\hline
\end{tabular}
|
Polarized microwave emission from space particles in the upper atmosphere of the Earth
|
Nominal spatial density distribution $\rho_\mathrm{d}$ (g\,cm$^{-3}$) for each dust
family and size distribution.
| null |
astro-ph.EP, astro-ph.IM, physics.space-ph
|
|
2312.07208v1
|
\begin{tabular}{c c c}
\hline
ML algorithm & Training time in s & Prediction time in s\\
\hline
Linear CLF & 0.6493 & 0.0035\\
KNN & 0.1562 & 0.0040 \\
SVC & 0.6760 & 0.3854 \\
CLT & 0.6452 & 0.0045 \\
RFC & 0.7884 & 0.0080 \\
VAE-NN & 34.3143 & 0.0872\\
VAE-GAN & 1074.3471 & 0.1285\\
\end{tabular}
|
Experimental Investigation of Machine Learning based Soft-Failure Management using the Optical Spectrum
|
Execution time of different ML algorithms for soft-failure identification.
| null |
cs.NI, cs.LG
|
|
2312.03121v2
|
\begin{tabular}{|c|ll|}
\multicolumn{3}{c}{\bf Approval(k=5)}\\
\hline
Rank & Agent & Score\\
\hline
1 & {\tt text-davinci-003} & 4\\
2 & {\tt Cohere Command beta (52.4B)} & 4\\
3 & {\tt text-davinci-002} & 3\\
4 & {\tt TNLG v2 (530B)} & 3\\
5 & {\tt Anthropic-LM v4-s3 (52B)} & 3\\
6 & {\tt YaLM (100B)} & 2\\
7 & {\tt text-ada-001} & 2\\
8 & {\tt text-babbage-001} & 2\\
9 & {\tt text-curie-001} & 2\\
10 & {\tt ada (350M)} & 2\\
\hline
\end{tabular}
|
Evaluating Agents using Social Choice Theory
|
VasE methods Approval, Borda, and Copeland on HELM Core Scenarios. \label{tab:helm-core-full1}
|
['\\newcommand{\\argmin}{\\operatornamewithlimits{argmin}}', '\\newcommand{\\argmax}{\\operatornamewithlimits{argmax}}', '\\newcommand{\\BR}{\\textsc{BR}}', '\\newcommand{\\bE}{\\mathbb{E}}', '\\newcommand{\\bI}{\\mathbb{I}}', '\\newcommand{\\ba}{\\mathbf{a}}', '\\newcommand{\\bpi}{\\bar{\\pi}}', '\\newcommand{\\pik}{{\\pi^k}}', '\\newcommand{\\bg}{\\mathbf{g}}', '\\newcommand{\\bone}{\\mathbf{1}}', '\\newcommand{\\bp}{\\mathbf{p}}', '\\newcommand{\\bu}{\\mathbf{u}}', '\\newcommand{\\bU}{\\mathbf{U}}', '\\newcommand{\\bx}{\\mathbf{x}}', '\\newcommand{\\by}{\\mathbf{y}}', '\\newcommand{\\bw}{\\mathbf{w}}', '\\newcommand{\\bv}{\\mathbf{v}}', '\\newcommand{\\bX}{\\mathbf{X}}', '\\newcommand{\\bY}{\\mathbf{Y}}', '\\newcommand{\\bZ}{\\mathbf{Z}}', '\\newcommand{\\bPi}{\\mathbf{\\Pi}}', '\\newcommand{\\bR}{\\bar{R}}', '\\newcommand{\\btheta}{\\boldsymbol\\theta}', '\\newcommand{\\cA}{\\mathcal{A}}', '\\newcommand{\\cB}{\\mathcal{B}}', '\\newcommand{\\cD}{\\mathcal{D}}', '\\newcommand{\\cPi}{\\mathcal{\\Pi}}', '\\newcommand{\\cI}{\\mathcal{I}}', '\\newcommand{\\cC}{\\mathcal{C}}', '\\newcommand{\\cH}{\\mathcal{H}}', '\\newcommand{\\cG}{\\mathcal{G}}', '\\newcommand{\\cL}{\\mathcal{L}}', '\\newcommand{\\cN}{\\mathcal{N}}', '\\newcommand{\\cO}{\\mathcal{O}}', '\\newcommand{\\cS}{\\mathcal{S}}', '\\newcommand{\\cT}{\\mathcal{T}}', '\\newcommand{\\cZ}{\\mathcal{Z}}', '\\newcommand{\\cU}{\\mathcal{U}}', '\\newcommand{\\tta}{\\mathtt{a}}', '\\newcommand{\\ttm}{\\mathtt{m}}', '\\newcommand{\\A}{\\mathcal{A}}', '\\newcommand{\\playerset}{\\mathscr{N}}', '\\newcommand{\\gameoracle}{\\mathcal{G}}', '\\newcommand{\\NashConv}{\\textsc{NashConv}\\xspace}', '\\newcommand{\\PW}{\\mbox{PW}}', '\\newcommand{\\ERM}{ERM}', '\\newcommand{\\RM}{RM}', '\\newcommand{\\defword}[1]{\\textbf{\\boldmath{#1}}}', '\\newcommand{\\ie}{{\\it i.e.},~} % AK - so Mike tells me.', '\\newcommand{\\eg}{{\\it e.g.},~} % AK', '\\newcommand{\\Var}{\\mathbb{V}\\text{ar}}', '\\newcommand{\\Cov}{\\mathbb{C}\\text{ov}}', '\\newcommand{\\Proof}{{\\noindent\\bf Proof. }}', '\\newcommand{\\citepjustyear}[1]{\\citep{#1}}', '\\newcommand{\\Qed}{$\\blacksquare$}', '\\newcommand{\\abs}[1]{\\left|#1\\right|}', '\\newcommand{\\breturn}{{\\bf return}\\xspace}']
|
cs.AI, cs.GT, cs.MA
|
|
2312.17414v1
|
\begin{tabular}{|p{3.5cm}|p{3.5cm}|p{3.5cm}|}
\hline
\multicolumn{3}{|c|}{\textbf{4D Extended Flips}} \\
\hline
$1D \Rightarrow 4D$ & $2D \Rightarrow 4D$ & $3D \Rightarrow 4D$\\
\hline
$(1 \rightarrow 2) \Rightarrow (4 \rightarrow 8)$ & $(1 \rightarrow 3) \Rightarrow (3 \rightarrow 9)$ & $(1 \rightarrow 4) \Rightarrow (2 \rightarrow 8)$\\
& $(2 \rightarrow 2) \Rightarrow (6 \rightarrow 6)$ & $(2 \rightarrow 3) \Rightarrow (4 \rightarrow 6)$\\
& $(2 \rightarrow 4) \Rightarrow (6 \rightarrow 12)$a & $(4 \rightarrow 4) \Rightarrow (8 \rightarrow 8)^*$\\
& & $(2 \rightarrow 6) \Rightarrow (4 \rightarrow 12)$\\
& & $(3 \rightarrow 6) \Rightarrow (6 \rightarrow 12)$b\\
& & $(4 \rightarrow 8) \Rightarrow (8 \rightarrow 16)$\\
\hline
\end{tabular}
|
Space-time hypervolume meshing part 1: Point insertion, geometric predicates, and bistellar flips
|
Lower dimensional flips extended to four dimensions. The * indicates that the $(8 \rightarrow 8)$ flip has three different realizations.
|
['\\newcommand{\\bbold}{\\bm{b}}', '\\newcommand{\\ebold}{\\bm{e}}', '\\newcommand{\\fbold}{\\bm{f}}', '\\newcommand{\\gbold}{\\bm{g}}', '\\newcommand{\\hbold}{\\bm{h}}', '\\newcommand{\\Lbold}{\\bm{L}}', '\\newcommand{\\Tbold}{\\bm{T}}', '\\newcommand{\\nbold}{\\bm{n}}', '\\newcommand{\\nhatbold}{\\hat{\\bm{n}}}', '\\newcommand{\\qbold}{\\bm{q}}', '\\newcommand{\\rbold}{\\bm{r}}', '\\newcommand{\\Rbold}{\\bm{R}}', '\\newcommand{\\Mbold}{\\bm{M}}', '\\newcommand{\\Ubold}{\\bm{U}}', '\\newcommand{\\Gbold}{\\bm{G}}', '\\newcommand{\\Fbold}{\\bm{F}}', '\\newcommand{\\ubold}{\\bm{u}}', '\\newcommand{\\zbold}{\\bm{z}}', '\\newcommand{\\vbold}{\\bm{v}}', '\\newcommand{\\wbold}{\\bm{w}}', '\\newcommand{\\whatbold}{\\hat{\\bm{w}}}', '\\newcommand{\\wtildebold}{\\bm{\\phi}}', '\\newcommand{\\xbold}{\\bm{x}}', '\\newcommand{\\ybold}{\\bm{y}}', '\\newcommand{\\sigmabold}{\\bm{\\sigma}}', '\\newcommand{\\edgeE}{\\mathcal{E}}', '\\newcommand{\\sBox}{\\text{\\scalebox{0.7}{$\\square$}}}', '\\newcommand{\\ipt}[2]{\\left(#1,#2\\right)_{\\mathcal{T}_h}}', '\\newcommand{\\iptT}[2]{\\left(#1,#2\\right)_{\\mathcal{T}_k}}', '\\newcommand{\\iptk}[2]{\\left(#1,#2\\right)_{K}}', '\\newcommand{\\ipbt}[2]{\\left\\langle#1,#2\\right\\rangle_{\\partial \\mathcal{T}_h}}', '\\newcommand{\\ipbtbd}[2]{\\left\\langle#1,#2\\right\\rangle_{\\partial \\Omega}}', '\\newcommand{\\ipbtf}[2]{\\left\\langle#1,#2\\right\\rangle_{\\partial \\mathcal{T}_h/\\mathcal{F}^{\\partial}_{h}}}', '\\newcommand{\\ipbtk}[2]{\\left\\langle#1,#2\\right\\rangle_{\\partial K}}', '\\newcommand{\\ipbf}[2]{\\left\\langle#1,#2\\right\\rangle_{\\mathcal{F}_h}}', '\\newcommand{\\iipbf}[2]{\\left\\langle#1,#2\\right\\rangle_{\\mathcal{F}_h^i}}', '\\newcommand{\\iptj}[2]{\\left(#1,#2\\right)_{\\mathcal{T}_{h,j}}}', '\\newcommand{\\ipbtj}[2]{\\left\\langle#1,#2\\right\\rangle_{\\partial \\mathcal{T}_{h,j}}}', '\\newcommand{\\llbracket}{\\left[\\!\\left[}', '\\newcommand{\\rrbracket}{\\right] \\! \\right]}', '\\newcommand{\\llcurve}{\\left\\{\\!\\left\\{}', '\\newcommand{\\rrcurve}{\\right\\} \\! \\right\\}}', '\\newcommand{\\vertiii}[1]{ \\left\\| #1 \\right\\|}']
|
math.NA, cs.NA, 65M50, 52B11, 31B99, 76M10
|
|
2312.07665v1
|
\begin{tabular}{l|c|c|c|}\hline \hline
&$\sigma$ [pb]&$\delta$(PDF)&$\delta$(scale)
\\ \hline
NNLO (QCD) &0.624& ${}^{+0.008}_{-0.010}$&${}^{+0.002}_{-0.002}$\\
\hline
NNLO (QED) &0.621& ${}^{+0.008}_{-0.010}$&${}^{+0.001}_{-0.002}$\\
\hline
N${}^3$LO (QCD, NNLO PDF) &0.618& ${}^{+0.008}_{-0.010}$&${}^{+0.002}_{-0.002}$\\
\hline
N${}^3$LO (QCD) &0.622& ${}^{+0.010}_{-0.010}$&${}^{+0.002}_{-0.002}$\\
\hline
N${}^3$LO (QED) &0.619& ${}^{+0.010}_{-0.010}$&${}^{+0.001}_{-0.002}$\\
\hline
\end{tabular}
|
Combining QED and Approximate N${}^3$LO QCD Corrections in a Global PDF Fit: MSHT20qed_an3lo PDFs
|
\sf $W^- H$ cross section predictions at $\sqrt{s}=$ 14 TeV and their corresponding PDF and scale uncertainties (with the central scale $\mu_F=\mu_R=M_{WH}$. Cross sections are calculated with \texttt{n3loxs}~, while the scale uncertainty is calculated using the 7--point variation described in this reference.
|
['\\newcommand{\\LHL}[1]{\\textcolor{blue}{\\bf[NOTE: LHL -- #1]}}', '\\newcommand{\\TC}[1]{\\textcolor{green}{\\bf[NOTE: TC -- #1]}}', '\\newcommand{\\RST}[1]{\\textcolor{red}{\\bf[NOTE: RST -- #1]}}', '\\newcommand{\\bs}[1]{\\boldsymbol{#1}}', '\\newcommand{\\MSbar}{\\overline{\\text{MS}}}', '\\newcommand{\\anlo}{a${\\rm N}^3$LO }']
|
hep-ph, hep-ex
|
|
2312.13962v1
|
\begin{tabular}{|l|c|c||l|c|c|}
\hline
$j_{\mathrm{eff}}$ & 3 band & 5 band & $d$ & 3 band & 5 band \\
\hline
\hline
$ \left| 3/2,1/2 \right\rangle$ & 0.987 & 0.985 & $\left| d_{xz} \right\rangle$ & 0.814 & 0.803\\
$ \left| 3/2,3/2 \right\rangle$ & 0.990 & 0.989 & $\left| d_{yz} \right\rangle$ & 0.814 & 0.803\\
$ \left| 1/2, 1/2 \right\rangle$ & 0.519 & 0.517 & $\left| d_{xy} \right\rangle$ & 0.868 & 0.856 \\
$ \left| \tilde{d}_{x^2-y^2} \right\rangle$& / & 0.003& $\left| d_{x^2-y^2} \right\rangle$ & / & 0.020\\
$ \left| \tilde{d}_{z^2} \right\rangle$& / & 0.006& $\left| d_{z^2} \right\rangle$ & / & 0.017 \\
\hline
\end{tabular}
|
The rich phase diagram of the prototypical iridate Ba$_2$IrO$_4$: Effective low-energy models and metal-insulator transition
|
%
Band fillings within DMFT.
%
For both models, the fillings are reported with respect to the $j_{\mathrm{eff}}$ basis (left) and the orbital basis (right) respectively.
%
The calculations used cRPA values for the Coulomb tensor and $\beta = 80$ eV$^{-1}$.
|
['\\newcommand{\\R}{\\textbf{R}}', '\\newcommand{\\cdag}{\\hat{c}^{\\dagger}}', '\\newcommand{\\bairo}{Ba$_2$IrO$_4$}', '\\newcommand{\\jeff}{$j_{\\mathrm{eff}}=1/2$}', '\\newcommand{\\JEFF}{$j_{\\mathrm{eff}}=3/2$}', '\\newcommand{\\jeffT}{$\\tilde{j}_{\\mathrm{eff}}=1/2$}', '\\newcommand{\\JEFFT}{$\\tilde{j}_{\\mathrm{eff}}=3/2$}', '\\newcommand\\numberthis{\\addtocounter{equation}{1}\\tag{\\theequation}}']
|
cond-mat.str-el, cond-mat.mtrl-sci
|
|
2312.07018v1
|
\begin{tabular}{|l|r|c|c|c|c|c|c|c}
\hline
$~~\gamma$ & $-0.2~~~$ & $-0.1$ & $0$ & $0.1$ & $0.2$ \\
\hline
$~~b_{c_{1}}$ & $5.01561$ & $5.10779$ & $5.19615$ & $5.28114$ & $5.36311$ \\
\hline
$~~r_{ph_{1}}$ & $2.86015$ & $2.93178$ & $3$ & $3.06525$ & $3.12788$ \\
\hline
$~~b_{c_{2}}$ & $6.08691$ & $6.16221$ & $6.23538$ & $6.30659$ & $6.37602$\\
\hline
$~~r_{ph_{2}}$ & $3.48523$ & $3.54356$ & $3.6$ & $3.65472$ & $3.70788$ \\
\hline
\end{tabular}
|
Observational appearance and additional photon rings of the Horndeski asymmetric thin-shell wormhole
|
The critical impact parameter $b_{c_{i}}$ of the Horndeski ATW for various values of the parameter $\gamma$. We set $M_{1}=1$ and $M_{2}=1.2$.
| null |
gr-qc
|
|
2310.10526v2
|
\begin{tabular}{|r|r r r r r r|}
\hline
$h_1$ & $10^{-4}$ & $10^{-5}$ & $10^{-6}$ & $10^{-7}$ & $10^{-8}$ & $10^{-9}$ \\
\hline
$s\,\backslash\,N$ & 626 & 857 & 1088 & 1320 & 1551 & 1783\\
\hline
1~~~~ & *** & *** & *** & *** & *** & *** \\
2~~~~ & 3.73e-06 & 2.43e-07 & 5.40e-08 & 5.38e-08 & 5.37e-08 & 5.37e-08 \\
3~~~~ & 5.81e-07 & 3.78e-08 & 2.40e-09 & 1.52e-10 & 4.64e-11 & 4.64e-11 \\
4~~~~ & 1.47e-07 & 9.60e-09 & 6.11e-10 & 3.86e-11 & 2.44e-12 & 1.56e-13 \\
5~~~~ & 5.29e-08 & 3.46e-09 & 2.20e-10 & 1.39e-11 & 8.79e-13 & 5.37e-14 \\
6~~~~ & 2.04e-08 & 1.33e-09 & 8.49e-11 & 5.37e-12 & 3.41e-13 & 2.32e-14 \\
7~~~~ & 1.19e-08 & 7.81e-10 & 4.98e-11 & 3.15e-12 & 1.97e-13 & 1.08e-14 \\
8~~~~ & 4.26e-09 & 2.77e-10 & 1.76e-11 & 1.11e-12 & 7.18e-14 & 7.91e-15 \\
9~~~~ & 4.56e-09 & 3.03e-10 & 1.94e-11 & 1.22e-12 & 7.57e-14 & 7.91e-15 \\
10~~~~ & 1.89e-09 & 1.22e-10 & 7.79e-12 & 4.90e-13 & 2.96e-14 & 7.91e-15 \\
20~~~~ & 1.84e-09 & 1.22e-10 & 7.77e-12 & 4.90e-13 & 2.96e-14 & 7.91e-15 \\
\hline
\end{tabular}
|
A spectrally accurate step-by-step method for the numerical solution of fractional differential equations
|
\label{tab1} Maximum error for Problem (\ref{prob1}), $r=1.01$ and $k=30$.
| null |
math.NA, cs.NA, 65L05, 65L03, 65L99
|
|
2312.07815v1
|
\begin{tabular}{lcccccc} \hline
\rule{0pt}{10pt}
& \MC{2}{c}{AGC227973=J1250+0520 } % \\ \hline
& \MC{2}{c}{PGC1264260=J1253+0409 } % \\ \hline
& \MC{2}{c}{UGC08055=J1256+0348 } \\ \hline
\rule{0pt}{10pt}
$\lambda_{0}$(\AA) Ion & F($\lambda$)/F(H$\beta$)&I($\lambda$)/I(H$\beta$) & F($\lambda$)/F(H$\beta$)&I($\lambda$)/I(H$\beta$) & F($\lambda$)/F(H$\beta$)&I($\lambda$)/I(H$\beta$) \\ \hline
%
3727\ [O\ {\sc ii}]\ & 0.977$\pm$ 0.090 & 0.977$\pm$ 0.102 & 3.402$\pm$ 0.072 & 3.180$\pm$ 0.086 & 2.578$\pm$ 0.070 & 2.637$\pm$ 0.081 \\
3868\ [Ne\ {\sc iii}]\ & ... & ... & ... & ... & 0.169$\pm$ 0.015 & 0.171$\pm$ 0.016 \\
3889\ He\ {\sc i}\ +\ H8\ & ... & ... & ... & ... & 0.083$\pm$ 0.012 & 0.172$\pm$ 0.033 \\
3967\ [Ne\ {\sc iii}]\ +\ H7\ & ... & ... & ... & ... & 0.123$\pm$ 0.015 & 0.205$\pm$ 0.030 \\
4101\ H$\delta$\ & 0.263$\pm$ 0.032 & 0.342$\pm$ 0.048 & 0.074$\pm$ 0.006 & 0.270$\pm$ 0.031 & 0.179$\pm$ 0.011 & 0.250$\pm$ 0.018 \\
4340\ H$\gamma$\ & 0.384$\pm$ 0.033 & 0.460$\pm$ 0.046 & 0.339$\pm$ 0.035 & 0.480$\pm$ 0.062 & 0.420$\pm$ 0.039 & 0.475$\pm$ 0.048 \\
4363\ [O\ {\sc iii}]\ & ... & ... & 0.049$\pm$ 0.025 & 0.043$\pm$ 0.026 & ... & ... \\
4861\ H$\beta$\ & 1.000$\pm$ 0.053 & 1.000$\pm$ 0.060 & 1.000$\pm$ 0.024 & 1.000$\pm$ 0.029 & 1.000$\pm$ 0.028 & 1.000$\pm$ 0.030 \\
4959\ [O\ {\sc iii}]\ & 0.256$\pm$ 0.032 & 0.231$\pm$ 0.031 & 0.576$\pm$ 0.017 & 0.485$\pm$ 0.017 & 0.642$\pm$ 0.019 & 0.606$\pm$ 0.019 \\
5007\ [O\ {\sc iii}]\ & 0.759$\pm$ 0.042 & 0.685$\pm$ 0.041 & 1.675$\pm$ 0.033 & 1.408$\pm$ 0.033 & 2.069$\pm$ 0.051 & 1.949$\pm$ 0.051 \\
6548\ [N\ {\sc ii}]\ & 0.007$\pm$ 0.045 & 0.006$\pm$ 0.041 & 0.055$\pm$ 0.027 & 0.042$\pm$ 0.024 & 0.049$\pm$ 0.028 & 0.043$\pm$ 0.026 \\
6563\ H$\alpha$\ & 3.241$\pm$ 0.166 & 2.716$\pm$ 0.166 & 3.460$\pm$ 0.075 & 2.749$\pm$ 0.077 & 3.181$\pm$ 0.085 & 2.810$\pm$ 0.086 \\
6584\ [N\ {\sc ii}]\ & 0.053$\pm$ 0.068 & 0.043$\pm$ 0.061 & 0.168$\pm$ 0.031 & 0.129$\pm$ 0.028 & 0.156$\pm$ 0.032 & 0.137$\pm$ 0.030 \\
%
& & & & & & \\
C(H$\beta$)\ dex & \MC {2}{c}{0.13$\pm$0.07} & \MC {2}{c}{0.14$\pm$0.03} & \MC {2}{c}{0.10$\pm$0.03} \\
EW(abs)\ \AA\ & \MC {2}{c}{2.05$\pm$0.23} & \MC {2}{c}{2.35$\pm$0.04} & \MC {2}{c}{1.45$\pm$0.17} \\
EW(H$\beta$)\ \AA\ & \MC {2}{c}{21.0$\pm$0.7} & \MC {2}{c}{13.2$\pm$0.2} & \MC {2}{c}{27.3$\pm$0.6} \\
\hline
$T_{\rm e}$(OIII)(K)\ & \MC {2}{c}{22082$\pm$2307} & \MC {2}{c}{18780$\pm$6534} & \MC {2}{c}{13997$\pm$1160} \\
$T_{\rm e}$(OII)(K)\ & \MC {2}{c}{16220$\pm$502 } & \MC {2}{c}{14954$\pm$306 } & \MC {2}{c}{13334$\pm$731 } \\
O$^{+}$/H$^{+}$($\times$10$^5$)\ & \MC {2}{c}{0.700$\pm$0.097} & \MC {2}{c}{2.910$\pm$0.200} & \MC {2}{c}{3.501$\pm$0.661} \\
O$^{++}$/H$^{+}$($\times$10$^5$)\ & \MC {2}{c}{0.322$\pm$0.067} & \MC {2}{c}{0.926$\pm$0.691} & \MC {2}{c}{2.519$\pm$0.556} \\
O/H($\times$10$^5$)\ & \MC {2}{c}{1.023$\pm$0.118} & \MC {2}{c}{3.836$\pm$0.719} & \MC {2}{c}{6.020$\pm$0.864} \\
12+log(O/H)(d)\ & \MC {2}{c}{...} & \MC {2}{c}{7.58$\pm$0.08} & \MC {2}{c}{...} \\
12+log(O/H)(s)\ & \MC {2}{c}{7.05$\pm$0.06} & \MC {2}{c}{7.46$\pm$0.04} & \MC {2}{c}{...} \\
12+log(O/H)(mse,c)\ & \MC {2}{c}{7.01$\pm$0.10} & \MC {2}{c}{...} & \MC {2}{c}{7.79$\pm$0.11} \\
12+log(O/H)(PT05)\ & \MC {2}{c}{...} & \MC {2}{c}{...} & \MC {2}{c}{7.79$\pm$0.10} \\
\MC{3}{l}{~~} \
\end{tabular}
|
Dwarfs in nearby voids: results of SALT spectroscopy
|
Line intensities and derived parameters of AGC227973, PGC1264260 and UGC08055
|
['\\newcommand{\\apj}{ApJ}', '\\newcommand{\\apjl}{ApJL}', '\\newcommand{\\aap}{A\\&A}', '\\newcommand{\\aaps}{A\\&AS}', '\\newcommand{\\aj}{AJ}', '\\newcommand{\\mnras}{MNRAS}', '\\newcommand{\\nat}{Nature}', '\\newcommand{\\pasp}{PASP}', '\\newcommand{\\apjs}{ApJS}', '\\newcommand{\\MC}{\\multicolumn}', '\\newcommand{\\kms}{km~s$^{-1}$}', '\\newcommand{\\Te}{T$_{\\rm e}$}', '\\newcommand{\\Hb}{H$\\beta$}', '\\newcommand{\\HI}{H{\\sc i}}', '\\newcommand{\\HII}{H{\\sc ii}}', '\\newcommand{\\sunn}{$_{\\odot}$}', '\\newcommand{\\p}{$\\pm$}', '\\newcommand{\\acc}{atoms~cm$^{-2}$}', '\\newcommand{\\logOH}{12+\\log(\\textrm{O/H})}', '\\newcommand{\\dg}{$\\dagger$}', '\\newcommand{\\qq}{\\addtocounter{qub}{1}\\arabic{qub}}']
|
astro-ph.GA
|
|
2307.00393v1
|
\begin{tabular}{c|cc|cc}
\hline
& \multicolumn{2}{c|}{Seen Speaker} & \multicolumn{2}{c}{Unseen Speaker} \\ \hline
& \multicolumn{1}{c|}{Same Language} & Different Language & \multicolumn{1}{c|}{Same Language} & Different Language \\ \hline
BNE-PPG-VC & \multicolumn{1}{c|}{1} & 1 & \multicolumn{1}{c|}{1} & 1 \\
ConsistencyXVC-w/o loss & \multicolumn{1}{c|}{4} & 3.93 & \multicolumn{1}{c|}{4.31} & 4.08 \\
ConsistencyXVC& \multicolumn{1}{c|}{4.15} & 4.18 & \multicolumn{1}{c|}{4.48} & 4.26 \\ \hline
Ground Truth &\multicolumn{4}{c}{4.43$\pm$0.08} \\ \hline
\end{tabular}
|
Using joint training speaker encoder with consistency loss to achieve cross-lingual voice conversion and expressive voice conversion
|
Naturalness MOS of XVC
| null |
eess.AS
|
|
2312.07510v1
|
\begin{tabular}{|c|c|}
\hline
Parameter & Value \\
\hline
$\beta_e$ & $0.5$ \\
$\beta_\mu$ & $0.0$ \\
$\beta_\tau$ & $2.5$ \\
$\lambda_{dark}$ & $5$ \\
$\kappa$ & $-1$ \\
$M_N$ & $50$[GeV]\\
$M_{med}$ & $200-800$[GeV]\\
\hline
\end{tabular}
|
Chasing leptophilic dark fermions at CLIC: the role of helicity
|
Parameter setting for the simulations, note that $\kappa$ is a non-minimal gauge interaction that is present only in the vector mode, see Ref. for details.
| null |
hep-ph
|
|
2310.14571v1
|
\begin{tabular}{llcclcrrrrl}
\hline
\hline
GLEAM name & S$_{162}$ & MRC name & Type & $z$ & FLASH & NSI\_fit & NSI\_err & LAS$_{\rm 5GHz}$\\
& (Jy) & & & & components & IPS & IPS & (arcsec) \\
(1) & (2) & (3) & (4) & (5) & (6) & (7) & (8) & (9) \\
\hline
\hline
J234045-230243 & 1.53 & MRC 2338-290 & Q & 0.449 & 4 & $<$0.013 & .. & 73 \\ %upper_limit
J234324-214129 & 4.52 & MRC 2340-219 & G & 0.766 & 3 & 0.052 & 0.004 & 27.1 \\ %detected
J234412-240744 & 2.20 & MRC 2341-244 & G & 0.590 & 1 & 0.466 & 0.035 & 2.1 \\ %detected
J234545-240232 & 3.66 & MRC 2343-243 & G & 0.600 & 4 & 0.074 & 0.006 & 48.3 \\ %detected
J235128-231708 & 2.82 & MRC 2348-235 & G & 0.952 & 2 & $<$0.035 & .. & 68.7 \\ %upper_limit
\hline
\hline
\end{tabular}
|
The FLASH pilot survey: an HI absorption search against MRC 1-Jy radio sources
|
continued..
|
['\\newcommand{\\kms}{km\\,s$^{-1}$} % kilometres per second', '\\newcommand{\\HI}{H{\\sc i}}', '\\newcommand{\\bibtex}{\\textsc{Bib}\\!\\TeX} % bibtex. ', '\\newcommand\\mjyb{mJy beam$^{-1}$}', '\\newcommand\\Msun{M$_{\\odot}$}', '\\newcommand\\Lsun{L$_{\\odot}$}', '\\newcommand\\cmc{cm$^{-3}$}', '\\newcommand\\hi{\\mbox{H\\,{\\sc i}}\\ }', '\\newcommand\\hix{\\mbox{H\\,{\\sc i}}}', '\\newcommand\\mgii{\\mbox{Mg\\,{\\sc ii}}\\ }', '\\newcommand\\Hii{H~\\textsc{ii}}', '\\newcommand\\nhi{$N_{\\rm HI}$} ', '\\newcommand\\ts{$T_{\\rm s}$} ', '\\newcommand\\lya{Ly-$\\alpha$\\ }']
|
astro-ph.GA
|
|
2309.04000v1
|
\begin{tabular}{llllllll}%{p{10pt}p{50pt}p{10pt}p{50pt}p{10pt}p{50pt}p{20pt}p{100pt}}
\hline
$E_1$ & 100 GPa & $E_2$ & 100 GPa & $G_{12}$ & 40 Gpa & $\nu_{12}$ & 0.25\\
$\nu_{23}$ & 0.25 & $l_0$ & $1\times10^{-2}$ m & $\alpha_r$ &0.002 & $\rho_{r}$ & $1.0\times10^{3}$ kg/m$^3$ \\
$k$ &$1\times10^{-9}$ & $c_1$ & 0.4 & $c_2$ & 1.0 & $\varepsilon_{pr}$ & 0.002 \\
$\rho_{f}$& $1.0\times10^{3}$ kg/m$^3$ & $c_r$ & $1\times10^{-8}$ 1/Pa & $c_f$ & $1\times10^{-8}$ 1/Pa & $\mu_r$ & $1\times10^{-3}$ Pa$\cdot$s \\
$\mu_f$ & $1\times10^{-3}$ Pa$\cdot$s & $q_r$ & 0 & $q_f$ & 0 & $k_{r1}$ & $1\times10^{-15}$ m$^2$ \\
$k_{r2}$ & $1\times10^{-15}$ m$^2$ & $k_{f1}$ & $1\times10^{-6}$ m$^2$ & $k_{f2}$ & $1\times10^{-6}$ m$^2$& $G_{c1}$ & 10 N/m \\
$G_{c2}$ & 10 N/m &&&&&&\\
\hline
\normalsize
\end{tabular}
|
Phase field modeling of hydraulic fracture propagation in transversely isotropic poroelastic media
|
Parameters for an isotropic specimen subjected to internal fluid pressure
| null |
physics.geo-ph
|
|
2303.14280v1
|
\begin{tabular}{l|ccc}
Molecule & $N_A$ & $N_b$ & $N_\mathrm{aux}$ \\
\hline\hline
Taxol & 113 & 1,032 & 3,599\\
Olestra & 453 & 3,181 & 11,633\\
Crambin & 642 & 5,559 & 19,500\\
Ubiquitin & 1,231 & 10,292 & 36,419
\end{tabular}
|
Distributed Memory, GPU Accelerated Fock Construction for Hybrid, Gaussian Basis Density Functional Theory
|
Representative systems considered in this study. $N_A$ is the number of atoms, $N_b$ is given for Cartesian 6-31G(d) and
$N_\mathrm{aux}$ for def2-tzvp-j.
|
['\\newcommand{\\mat}[1]{\\ensuremath\\mathbf{#1}}', '\\newcommand{\\matspace}[3]{\\ensuremath\\mathbb{#1}^{#2 \\times #3}}', '\\newcommand{\\nbas}[0]{\\ensuremath N_b}', '\\newcommand{\\ngrid}[0]{\\ensuremath N_g}', '\\newcommand{\\needcite}{[{\\color{red} cite}]}', '\\newcommand{\\dbwy}[1]{\\textcolor{red}{DBWY:{#1}}}', '\\newcommand{\\efv}[1]{{\\textcolor{green}{#1}}}', '\\newcommand{\\tlw}[1]{{\\textcolor{blue}{#1}}}', '\\newcommand{\\bdj}[1]{{\\textcolor{orange}{#1}}}', '\\newcommand{\\NCCL}[0]{\\texttt{NCCL}~}']
|
physics.comp-ph, physics.chem-ph
|
|
2307.15204v1
|
\begin{tabular}[c]{lccccc}\\
%\hline
Estimator & Effects & Emp.Estimates & Emp.Var & Emp.S.D. & Var Estimate \\
\hline
$ \widehat{\delta}_{{HT,tot}}$ & 7 & 7.1931 & 9.6277 & 3.1028 & 11.2033 \\
$ \widehat{\delta^*}_{{HT,tot}}$ & 7 & 7.1931 & 9.6277 & 3.1028 & 11.2033 \\
$\widehat{\delta}_{{HT,dir}}$ & 1 & 1.1654 & 9.7750 & 3.1265 & 10.5230 \\
$ \widehat{\delta^*}_{{HT,dir}}$ & 1 & 1.1045 & 2.4792 & 1.5745 & 4.3616 \\
$\widehat{\delta}_{{HT,ind}}$ & 6 & 6.0277 & 3.5973 & 1.8966 & 5.4461 \\
$ \widehat{\delta^*}_{{HT,ind}}$ & 6 & 6.0885 & 4.0546 & 2.0136 & 5.9402 \\
$\widehat{\delta}_{{HT,1^{st}}}$ & 3 & 3.0547 & 1.3709 & 1.1708 & 1.7503 \\
$\widehat{\delta^*}_{{HT,1^{st}}}$ & 3 & 3.0192 & 0.6476 & 0.8047 & 1.4636 \\
$\widehat{\delta}_{{HT,2^{nd}}}$ & 2 & 1.9923 & 2.9090 & 1.7056 & 4.1353 \\
$\widehat{\delta^*}_{{HT,2^{nd}}}$ & 2 & 1.9428 & 2.0746 & 1.4403 & 3.9275 \\
$\widehat{\delta}_{{HT,3^{rd}}}$ & 1 & 0.9806 & 5.3764 & 2.3187 & 6.7556 \\
$\widehat{\delta^*}_{{HT,3^{rd}}}$ & 1 & 1.1264 & 4.5503 & 2.1331 & 6.0993 \\
\hline
\end{tabular}
|
Estimation of Causal Effects Under K-Nearest Neighbors Interference
|
Estimates Under Bernoulli Randomization Model 8
|
['\\newcommand{\\blind}{1}', '\\newcommand{\\nn}{\\nonumber}']
|
stat.ME
|
|
2309.13498v1
|
\begin{tabular}{|p{0.10\linewidth}|p{0.15\linewidth}|p{0.15\linewidth}|p{0.10\linewidth}|p{0.15\linewidth}|p{0.15\linewidth}|}
\hline
\textbf{Differences} & \textbf{Goal} & \textbf{Model} & \textbf{Roles} & \textbf{Protocol} & \textbf{Recovery} \\
\hline
CFT & Ensure system reliability despite crash failures & Assumes crash failures only & No specific roles & Varies based on specific implementation & Relies on replication and backups \\
\hline
Paxos & Ensure consistency and agreement in distributed systems & Assumes crash failures only & Proposers, Acceptors, Learners & Three phases: Prepare, Propose, Learn & Learners apply committed decisions \\
\hline
RAFT & Ensure consistency and agreement in distributed systems & Assumes crash failures only & Leader, Followers, Candidates & Three phases: Leader Election, Log Replication, Safety & Nodes store and apply committed entries \\
\hline
\end{tabular}
|
Consensus Algorithms of Distributed Ledger Technology -- A Comprehensive Analysis
|
Comparison of CFT Family In Term of Operations.
| null |
cs.DC, cs.CR
|
|
2311.05170v1
|
\begin{tabular}{cccccccc}
\hline
$h $ & $|\vec{u}_c -\vec{u}_{ch}^{n+1}|_1$ &
Rate &
$|p_F -p_{Fh}^{n+1}|_1$&
Rate &
$\|p_f -p_{fh}^{n+1}\|_0$&
Rate \\
\hline
$\frac{1}{16} $ & 0.146752 & -- & 0.063144 &-- &0.001342 & --
\\
$\frac{1}{25} $ & 0.090678 & 1.08 & 0.043460 &0.84 &0.000612 & 1.76 \\
$\frac{1}{36} $ & 0.064652 & 0.93 & 0.028193 &1.19 &0.000364 & 1.43 \\
$\frac{1}{49} $ & 0.047235 & 1.02 & 0.020150 &1.09 & 0.000265 & 1.03 \\
\hline
$|p_f-p_{fh}^{n+1}|_1$ &
Rate &
$\|p_m-p_{mh}^{n+1}\|_0$ &
Rate &
$|p_m-p_{mh}^{n+1}|_1$ &
Rate &
CPU(s)\\
\hline
0.028997 & -- & 0.002830 &-- &0.035546 & -- & 500.89\\
0.018563 & 1.00 & 0.001933 & 0.85 &0.023046 & 0.97 &8115.85 \\
0.012313 & 1.13 & 0.001443 & 0.80 &0.016263 & 0.96 &29756.13
\\
0.009163 & 0.96 & 0.000993 & 1.21 &0.011930 & 1.00 &56663.52
\\
\hline
\end{tabular}
|
A Local Parallel Finite Element Method for Super-Hydrophobic Proppants in a Hydraulic Fracturing System Based on a 2D/3D Transient Triple-Porosity Navier-Stokes Model
|
\label{T4}The convergence performance and computational cost of Algorithm \ref{Algorithm-1}(Traditional Algorithm) in 3D
|
['\\newcommand*{\\abs}[1]{\\lvert#1\\rvert}', '\\newcommand*{\\norm}[1]{\\lVert #1 \\rVert}', '\\newcommand*{\\tnorm}[1]{\\interleave#1\\interleave}', '\\newcommand*{\\bi}[1]{\\textbf{\\emph{#1}}}', '\\newcommand*{\\tu}[1]{\\textup{#1}}', '\\newcommand\\mathd{d}', '\\newcommand\\bsm{\\boldsymbol}', '\\newcommand{\\curl}{\\operatorname{ curl}}', '\\newcommand{\\Div}{\\operatorname{div}}']
|
math.NA, cs.NA
|
|
2309.15380v1
|
\begin{tabular}{c c c c c c} \hline\hline
~~~~Coupled-structure~~~~& ~~~~~~~$E_{th}^{Theo}$ (Channel)~~~~~~~ & ~~~~~~$E_{cc}$~~~~~~ & ~~~~~~~$E_{B}$~~~~~~~ & ~~~~~~$E_{th}^{Exp}$~~~~~~ & ~~~~~$E'$~~~~~ \\ \hline
$qss-\bar{q}c$ & 3235 ($\Xi D$) & 3237 & ub & 3187 & 3190 \\
$qsc-\bar{q}s$ & 3060 ($\Xi_c \bar{K}$) & 3065 & ub & 2962 & 2967 \\
$ssc-\bar{q}q$ & 3548 ($\Omega_c \omega$) & 3545 & -3 & 3477 & 3474 \\
$qss-\bar{q}c,~ssc-\bar{q}q$ & 3235 ($\Xi D$) & 3230 & -5 & 3187 & 3192 \\
$qss-\bar{q}c,~qsc-\bar{q}s,~ssc-\bar{q}q$ & 3060 ($\Xi_c \bar{K}$) & 3064 & ub & 2962 & 2966 \\ \hline\hline
\end{tabular}
|
Investigating excited $Ω_c$ states from pentaquark perspective
|
\label{cc 1/2}The coupled-channel energies of the $ssc\bar{q}q$ pentaquark system with $J^P=\frac{1}{2}^-$ (unit: MeV).
| null |
hep-ph, nucl-th
|
|
2311.15820v1
|
\begin{tabular}{ |p{4cm}||p{3cm}|p{3cm}| }
\hline
& Wind energy&Solar energy\\
\hline
Average production 12am-7am (MWh) and $\%$ & 600 MWh /37.69$\%$ &7 MWh /1.01$\%$\\
\hline
Average production 7am-7pm (MWh) and $\%$& 601 MWh /37.75$\%$ & 676 MWh /97.97$\%$\\
\hline
Average $\%$ of the daily demand &391 MWh /24.56$\%$ & 7 MWh /1.01$\%$\\
\hline
\end{tabular}
|
Meeting Energy Needs by Balancing Cost and Sustainability through Linear Programming
|
Production based on the time of the day
| null |
math.OC, 90C05
|
|
2310.16095v1
|
\begin{tabular}{p{0.97\columnwidth}}
% \label{nonexplainable}
\hline
\textbf{Section of Industry} -
{{Example}} {{[Document]}} \\
\hline
\hline
\textbf{Consumer Non-Durables} - Total general and administrative costs decreased by \$79,000 in 1995 due primarily to the absence of a management fee for 1995. [Highwater Ethanol, LLC, January, 2017]\\
\hline
\textbf{Consumer Durables} - Bank borrowings during 1995 were attributable to the Silver Furniture acquisition and the refinancing of Silver Furniture's bank indebtedness. [Chromcraft Revington, Inc., March, 1997]\\
\hline
\textbf{Manufacturing} - Because components are sold directly to the Company's manufacturing sources, the Company is not aware of the precise quantities sourced from particular suppliers. [Fossil, Inc., March, 1997]\\
\hline
\textbf{Energy} -
Due to the apparent age of the material, no fine or enforcement action is expected. [Arabian Shield Development Co, March, 1997]\\
\hline
\textbf{Chemicals} - Due to personnel additions to the department, employee wages increased approximately \$56,700 in 1996. [American Vanguard Corp., March, 1997]\\
\hline
\textbf{Business Equipment} - Government contracts are subject to negotiated overhead rates, and work performed under government contracts is subject to audit and adjustments of amounts paid to the Company. [Ibis Technology Corp., 1997]\\
%Due to a variety of factors including differences in relational database product performance across wide area networks, differences in speed of various communication links, differences in hardware platform performance, and other factors, there is a limited ability to accurately predict product performance under certain of these environments. [Peoplesoft, Inc., March, 1997]\\
\hline
\textbf{Telephone} - Cost of services related to the wireless telephone operations during the year ended May 31, 1996 was \$26,129, an increase of \$3,977 or 18.0\% as compared to the year ended May 31, 1995. [Century Communications Corp., August, 1997]\\
\hline
\textbf{Utilities} - The remainder of the increase was attributable to increases in ad valorem taxes, repair and maintenance expense mainly related to the WCLSF and the employee incentive plan which rewards certain of Tejas' employees with bonuses when the company achieves certain annual financial growth targets. [Tejas Gas Corp., March, 1997]\\
\hline
\textbf{Shops} - The Board may increase or decrease the number of shares under the Program or terminate the Program in its discretion at any time. [Boise Cascade Co., February, 2017]\\
\hline
\textbf{Health} - The 1995 results were also negatively impacted by a reduction of the Company's income tax benefit resulting from reserves established related to the expiration of certain state operating losses. [American White Cross Inc., April, 1997]\\
\hline
\textbf{Finance} - In the last three years, inflation has not had a significant impact on the Company because of the relatively low inflation rate. [Weeks Corp., March, 1997]\\
\hline
\textbf{Others} - In addition, the timing of revenue is difficult to forecast because the Company's sales cycle is relatively long. [Claremont Technology Group Inc., September, 1997]\\
\hline
\end{tabular}
|
CR-COPEC: Causal Rationale of Corporate Performance Changes to Learn from Financial Reports
|
Examples of non-causal rationale of sentences by each section.
|
['\\newcommand{\\revised}[1]{\\textcolor{black}{#1}}', '\\newcommand\\BibTeX{B\\textsc{ib}\\TeX}']
|
cs.CL, cs.CE
|
|
2308.09075v1
|
\begin{tabular}{|l|l|}
\hline
Type & Variable \\
\hline
\multirow{3}{*}{Vertiport States} & Availability - $P_a$ \\
& Port type - $P_t$ \\
& Location - $(x_p, y_p)$ \\
\hline
\multirow{4}{*}{VTOL States} & Current status - $c_i$ \\
& Battery capacity - $b_i$ \\
& Schedule status - $l_i$ \\
& Location - $(x_i, y_i)$ \\
\hline
\multirow{5}{*}{Action Space} & Stay still \\
& Takeoff \\
& Move/ land in normal port - 1,2 \\
& Move/ land in battery port - 1 \\
& Move to hover spots - 1,2,3,4 \\
& Continue previous action \\
& Avoid collision \\
\hline
\end{tabular}
|
Fast Decision Support for Air Traffic Management at Urban Air Mobility Vertiports using Graph Learning
|
MDP formulation
|
['\\newcommand{\\vport}{vertiport} % What we call a vertiport ', '\\newcommand{\\port}{helipad} % What we call a port inside of the vertiport', '\\newcommand{\\lenactions}{11 actions} %This number keeps changing', '\\newcommand{\\learningrate}{$1E-5$}', '\\newcommand{\\threshold}{3 meters}']
|
cs.MA, cs.AI, cs.LG, cs.RO
|
|
2303.14510v1
|
\begin{tabular}{c|c|lllllll}
\hline \hline
\multirow{2}{*}{\textbf{Dataset}} & \multirow{2}{*}{\textbf{u}} &
\multicolumn{6}{c}{\textbf{\# minimum utility by varying $k$}} \\ \cline{3-8}
& &$k_1$ & $k_2$ & $k_3$ & $k_4$ & $k_5$ & $k_6$ \\ \hline
chainstore & $u_1$ & 1643,851 & 697,152 & 488,009 & 407,079 & 348,233 & 310,306\\
\{16967\} & $u_2$ & 1643,851 & 697,152 & 488,009 & 407,079 & 348,233 & 310,306\\ \hline
ecommerce & $u_1$ & 976,618 & 954,154 & 940,042 & 929,362 & 920,962 & 913,834 \\
\{150561222\} & $u_2$ & 976,618 & 954,154 & 940,042 & 929,362 & 920,962 & 913,834 \\ \hline
retail & $u_1$ & 1,381 & 1,379 & 1,377 & 1,377 & 1,376 & 1,375 \\
\{976\} & $u_2$ & 1,381 & 1,379 & 1,377 & 1,377 & 1,376 & 1,375 \\ \hline
foodmart& $u_1$ & 6,266 & 4,319 & 5,541 & 6,530 & 7,420 & 7,978 \\
\{1340\} & $u_2$ & 6,266 & 4,319 & 5,541 & 6,530 & 7,420 & 7,978 \\\hline
mushroom & $u_1$ & 449,193 & 358,323 & 256,158 & 125,079 & 93,238 & 73,171 \\
\{110\} & $u_2$ & 449,193 & 358,323 & 256,158 & 125,079 & 93,238 & 73,171 \\\hline
T10I4D100K & $u_1$ & 93,238 & 39,273 & 30,843 & 27,984 & 26,228 & 25,716 \\
\{71\} & $u_2$ & 93,238 & 39,273 & 30,843 & 27,984 & 26,228 & 25,716 \\
\hline
\hline
\end{tabular}
|
Targeted Mining of Top-k High Utility Itemsets
|
The minimum utility of TMKU with different $k$ values
| null |
cs.DB
|
|
2311.06714v1
|
\begin{tabular}{ccccc} \textbf{Review Group} & \textbf{Median} & \textbf{Mean} & \textbf{Std.} \\
\hline
Popular & 1.9\% & 2.12\% & 1.73\%\\
Non-Popular & 1.60\% & 1.87\% & 2.18\% \\
\hline
\end{tabular}
|
What factors influence the popularity of user-generated text in the creative domain? A case study of book reviews
|
The presence of named-entity
| null |
cs.CL, cs.IR
|
|
2304.04372v1
|
\begin{tabular}{c|c|c|c||c|c|c||c|c|c}
\hline\hline
Estimator & SV1F & SV2F & RH & SV1F & SV2F & RH & SV1F & SV2F & RH\\
\hline\hline
& \multicolumn{3}{c||}{d=5, $\bar{\sigma}_\eta=3$} & \multicolumn{3}{c||}{d=5, $\bar{\sigma}_\eta=3.5$} & \multicolumn{3}{c}{d=5, $\bar{\sigma}_\eta=4$}\\
\hline
PDF & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% \\
LMM & 100\% & 99.96\% & 99.96\% & 99.25\% & 98.95\% & 99.18\% & 92.79\% & 91.65\% & 91.31\% \\
STS & 89.60\% & 82.73\% & 84.52\% & 72.26\% & 72.97\% & 74.06\% & 61.17\% & 60.53\% & 63.01\%\\
\hline
& \multicolumn{3}{c||}{d=10, $\bar{\sigma}_\eta=3$} & \multicolumn{3}{c||}{d=10, $\bar{\sigma}_\eta=3.5$} & \multicolumn{3}{c}{d=10, $\bar{\sigma}_\eta=4$}\\
\hline
\hline
PDF & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% \\
LMM & 99.85\% & 99.73\% & 99.77\% & 95.78\% & 95.74\% & 95.61\% & 79.97\%& 80.03\% &81.27\%\\
STS & 45.15\% & 44.82\% & 45.95\% & 36.34\% & 36.11\% & 36.38\% & 30.33\% & 29.74\% &30.45\%\\
\hline
& \multicolumn{3}{c||}{d=15, $\bar{\sigma}_\eta=3$} & \multicolumn{3}{c||}{d=15, $\bar{\sigma}_\eta=3.5$} & \multicolumn{3}{c}{d=15, $\bar{\sigma}_\eta=4$}\\
\hline
\hline
PDF & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 100\%& 100\% \\
LMM & 99.12\% & 98.02\% & 99.25\% & 90.68\% & 89.58\% & 91.22\% & 67.04\%& 66.54\%& 68.96\% \\
STS & 30.58\% & 29.88\% & 30.81\% & 23.92\% & 23.39\%& 23.66\%& 19.40\% & 19.32\%& 18.94\% \\
\hline
& \multicolumn{3}{c||}{d=20, $\bar{\sigma}_\eta=3$} & \multicolumn{3}{c||}{d=20, $\bar{\sigma}_\eta=3.5$} & \multicolumn{3}{c}{d=20, $\bar{\sigma}_\eta=4$}\\
\hline
\hline
PDF & 100\% & 100\% & 100\% & 100\% & 100\% & 100\% & 100\%& 100\% & 100\% \\
LMM & 97.58\% & 97.09\% & 97.58\% & 83.06\% & 80.64\% & 83.44\% & 52.92\%& 51.88\% & 55.24\% \\
STS & 21.37\% & 21.37\% & 21.30\% & 15.77\% & 15.66\%& 15.31\%& 11.09\% & 11.05\% & 10.99\% \\
\hline
\end{tabular}
|
Symmetric positive semi-definite Fourier estimator of instantaneous variance-covariance matrix
|
\% of psd matrix produced by each estimator, when the efficient price process is produced by alternative models, in presence of heteroskedastic noise.
| null |
stat.ME, q-fin.ST
|
|
2306.13428v1
|
\begin{tabular}{lcccc}
& $\alpha$ & $I$ & $\eta$ & $m$\\
\hline
NGD (Algorithm \ref{algo:NGD}) &0.990 &10000 &0.003 &- \\
rMLE (Algorithm \ref{algo:rMLE.b}) &0.975&- &- &- \\
ONGD (Algorithm \ref{algo:ONGD}) &- &- &0.001 &100 \\
\end{tabular}
|
On tracking varying bounds when forecasting bounded time series
|
Hyperparameter values for each algorithm: forgetting factor $\alpha$, number of iterations $I$, learning rate/step size $\eta$ and minibatch size $m$.
|
['\\newcommand{\\blind}{0}']
|
stat.ML, cs.LG, stat.AP
|
|
2304.13128v3
|
\begin{tabular}{lccc}
\hline
\textbf{Model} & \textbf{Training Time} & \textbf{MAE} &\textbf{MAPE}\\
\hline
IV-ANN & 446.204831 & $2.3235e^{-5}$ &$0.044106\%$ \\
GAN-2 & 209.194824 & $2.1376e^{-5}$ & $0.039810\%$\\
\hline
\end{tabular}
|
Computing Volatility Surfaces using Generative Adversarial Networks with Minimal Arbitrage Violations
|
Timing and error comparison between GAN-2 and IV-ANN
| null |
q-fin.CP
|
|
2309.13498v1
|
\begin{tabular}{|p{0.10\linewidth}|p{0.05\linewidth}|p{0.05\linewidth}|p{0.05\linewidth}|p{0.05\linewidth}|p{0.05\linewidth}|p{0.05\linewidth}|p{0.05\linewidth}|p{0.05\linewidth}|p{0.05\linewidth}|p{0.08\linewidth}|p{0.05\linewidth}|}
\hline
\textbf{Attributes} & \textbf{Hard.} & \textbf{Trust } & \textbf{Toler.} & \textbf{Compu.} & \textbf{Centra.} & \textbf{Scala.} & \textbf{Late.} & \textbf{Cost} & \textbf{Secu.} & \textbf{Interoper.} & \textbf{Compl.}\\
\hline
\textbf{PoC} & M & M & M2H & M & M & M & M & M & M2H & M & M \\ \hline
\textbf{PoI} & M & M2H & M2H & M & M2H & M2H & M2H & M & M2H & M & M \\ \hline
\textbf{PoCon} & M & M & M2H & M & M & M2H & M2H & M & M2H & M & M \\ \hline
\textbf{PoR} & M & M2H & M2H & M & M2H & M2H & M2H & M & M2H & M & M \\ \hline
\textbf{PoW} & H & L & M2H & H & H & L & M & H & H & M & H \\ \hline
\textbf{Tangle} & L & L & H & L & L & H & M & L & H & M2H & M \\ \hline
\textbf{PoA} & M & H & H & L & M2H & H & M2H & L & H & M2H & M \\ \hline
\textbf{PoAct} & M & M & M2H & M & M & M & M & M & M2H & M & M \\ \hline
\textbf{ConsensusX} & L2M & L2M & M2H & L & L2M & H & L & L & H & H & L2M \\ \hline
\end{tabular}
|
Consensus Algorithms of Distributed Ledger Technology -- A Comprehensive Analysis
|
Candidates List 3.
| null |
cs.DC, cs.CR
|
|
2308.13642v1
|
\begin{tabular}{||c |c |c |c|c||}
\hline
\textbf{Model} &\textbf{Entanglement Scheme} & \textbf{Dimensionality Reduction} & \textbf{Accuracy} & \textbf{F-Score} \\ [0.5ex]
\hline\hline
XG Boost &None & None & 51.58\% & 58.18\% \\
\hline
SVM & None & PCA-3 & 51.58\% & 58.18\% \\
\hline
SVM & None & PCA-5 & 53.68\% & 60.71\% \\
\hline
SVM & None & PCA-8 & 51.58\% & 57.40\% \\
\hline
Decision Tree & None & Quantum Annealing-3 & 57.89\% & 62.26\% \\
\hline
K- Nearest Neighbours & None & Quantum Annealing-5 & \textbf{62.10\%} & \textbf{68.96\%} \\
\hline
XGBoost & None & Quantum Annealing-8 &52.61\% & 57.94\% \\
\hline
Quantum SVM & Linear & Quantum Annealing-3 & 52.63\% & 55.45\% \\
\hline
Quantum SVM & Full & PCA-3 & 55.78\% & 61.81\% \\
\hline
Quantum SVM & Circular & Quantum Annealing-5 & 56.84\% & 61.68\% \\
\hline
Quantum SVM & Circular & Quantum Annealing-5 & 56.84\% & 61.68\% \\
\hline
Quantum SVM & Linear & PCA-5 & 57.89\% & 65.51\% \\
\hline
Quantum SVM & Full & PCA-5 & 57.89\% & 65.51\% \\ [1ex]
\hline
\hline
\end{tabular}
|
The Potential of Quantum Techniques for Stock Price Prediction
|
Best Models for Honeywell dataset
| null |
q-fin.CP
|
|
2312.00705v1
|
\begin{tabular}{lcrrrrc}
%\hline
%\textbf{Molecule}
& \textbf{Coupling} & \textbf{CC3$^a$} & \textbf{CCSD$^a$} & \textbf{SOPPA} & \textbf{HRPA(D)} & \textbf{exp$^b$} \\ \hline
CO & $^1J_{CO}$ & 14.62 & 15.07 & 20.26 & 18.40 & 16.4 \\ \hline
%OF$_2$ & $^2J_{FF}$ & 1327.34 & 1211.78 & 1416.08 & 773.52 & \\
% & $^1J_{OF}$ & -251.99 & -269.13 & -363.28 & -182.24 & (-)300 \\ \hline
HCCH & $^1J_{CH}$ & 240.44 & 243.83 & 261.67 & 260.45 & 248.29 \\
& $^1J_{CC}$ & 180.96 & 187.61 & 190.66 & 188.56 & 169.82 \\
& $^3J_{HH}$ & 9.95 & 10.27 & 11.89 & 11.20 & 9.47 \\
& $^2J_{CH}$ & 53.07 & 51.55 & 52.08 & 50.86 & 49.26 \\ \hline
FCCH & $^3J_{FH}$ & 14.45 & 12.72 & 11.61 & 10.28 & 21 \\
& $^1J_{CF}$ & -277.68 & -280.42 & -305.21 & -266.28 & \\
& $^2J_{CF}$ & 25.56 & 26.74 & 22.31 & 23.49 & \\
& $^1J_{CC}$ & 268.11 & 272.31 & 277.77 & 274.67 & \\
& $^2J_{CH}$ & 68.53 & 66.84 & 67.85 & 65.63 & \\
& $^1J_{CH}$ & 270.08 & 272.55 & 292.06 & 289.69 & \\ \hline
FCCF & $^3J_{FF}$ & 2.56 & 7.26 & -11.94 & 8.36 & 2.1 \\
& $^1J_{CF}$ & -256.58 & -260.83 & -289.18 & -248.55 & (-)287.3 \\
& $^2J_{CF}$ & 45.54 & 45.14 & 39.85 & 38.24 & 28.7 \\
& $^1J_{CC}$ & 401.65 & 407.83 & 417.66 & 410.89 & \\ \hline
F$_2$CO & $^1J_{CF}$ & -294.39 & -292.43 & -320.82 & -279.61 & (-)308 \\
& $^2J_{FF}$ & -100.20 & -105.05 & -120.56 & -85.35 & \\
& $^2J_{OF}$ & 39.78 & 38.65 & 41.81 & 32.38 & \\
& $^1J_{CO}$ & 12.08 & 12.32 & 18.90 & 12.50 & \\ \hline
H$_2$CO & $^2J_{HH}$ & 37.29 & 36.56 & 40.76 & 38.52 & 40.22 \\
& $^2J_{OH}$ & -3.01 & -2.82 & -2.74 & -3.08 & \\
& $^1J_{CH}$ & 167.89 & 169.12 & 178.42 & 178.38 & \\
& $^1J_{CO}$ & 26.98 & 27.18 & 32.34 & 25.49 & \\ \hline
HCN & $^1J_{CH}$ & 249.95 & 253.82 & 272.40 & 272.74 & 267.3 \\
& $^1J_{C^{15}N}$ & -18.19 & -18.46 & -15.30 & -17.96 & (-)18.5 \\
& $^2J_{^{15}NH}$ & -7.47 & -7.56 & -7.47 & -8.31 & (-)8.7 \\
% \hline
\end{tabular}
|
On the performance of HRPA(D) for NMR spin-spin coupling constants: Smaller molecules, aromatic and fluoroaromatic compounds
|
All the calculated SSCCs (in Hz) for set I including known experimental values.
|
['\\newcommand\\spas[1]{\\color{red} #1\\normalcolor}']
|
physics.chem-ph
|
|
2304.07620v1
|
\begin{tabular}{l|c|c|c}
\hline
\multicolumn{4}{c}{\textbf{Temperature Anomaly under RCP 4.5 at 2300: Methane Oxidation Inclusion}} \\ \hline
Scenario & From Permafrost (1) & None (2) & From Permafrost, Fossil Fuels (3) \\ \hline
Baseline & 3.90 & 3.90 & 3.93\\
1\% & 3.90 & 3.89 & 3.92 \\
10\% & 3.89 & 3.89 & 3.92\\
\end{tabular}
|
Effect of Methane Mitigation on Global Temperature under a Permafrost Feedback
|
Temperature anomaly at 2300 between differing inclusions of methane oxidation. We compare different inclusions between the baseline RCP 4.5, and 1\% and 10\% annual methane emission reduction scenarios. Column (1) shows inclusion of methane oxidation from permafrost methane emissions. Column (2) reflects no methane oxidation, as used in our paper. Column 4 shows inclusion of permafrost methane oxidation and 25\% of anthropogenic methane oxidation, an estimate used to reflect the fact that some sources of methane emissions are not from fossil fuels.
|
['\\newcommand{\\coo}{\\ensuremath{\\mathrm{CO_2}} }', '\\newcommand{\\meth}{\\ensuremath{\\mathrm{CH_4}} }', '\\newcommand{\\nit}{\\ensuremath{\\mathrm{N_2O}} }', '\\newcommand{\\NPP}{\\ensuremath{\\mathrm{NPP}} }', '\\newcommand{\\RH}{\\ensuremath{\\mathrm{RH}} }', '\\newcommand{\\soo}{\\ensuremath{\\mathrm{SO_2}} }']
|
physics.ao-ph, math.DS
|
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