The Boss in Katherine Mansfield's "The Fly"
The development of short stories as a genre can be seen as a new way of negotiating with the newly understood complex fields of modern and post modern human experiences. From this perspective, Katherine Mansfield's "The Fly" may be seen as both a suspended moment within a spacio-temporal context as well as a boundless expanse of human existence. The characters, despite being very few in number, are richly drawn. The Boss is no exception.
It might be from a sense of superiority that he can not accept such uniformity of human destiny beyond death. We see in him a constant state of denial. Equally disturbing is the way in which he makes a conscious preparation to mourn his son's death over again with deliberate weeping. The failure to do so becomes, as James Joyce would have called it, a moment of epiphany. The moment of motionless contemplation extends in a flashback to construct a roadmap for the readers into the Boss's mindscape. The fly episode becomes a correlative of the complex maze inside the Boss's mind.
Short stories can be like photographs, catching people at some moment in their lives and trapping the memory for ever . There they are, smiling or frowning, looking sad, happy, serious, surprised ... And behind those smiles and those frowns lie all the experience of life, the fears and delights, the hopes and the dreams.
His initial desire to torture the fly, followed swiftly by an equally intense desire to support it and relieve it of its misery, could be a result of his duality in accepting his son's death. A child can understand this as a simple proposition—the fly was suffering in ink, his son had suffered in the murky trenches; the son had died, so the fly should also die. Following such a line of logic, the desire to save the fly may be seen as an urgency in the Boss to control at least one destiny. His words transform into a feverish chanting: "…that was the way to tackle thing… never say die". On the other hand, his ingrained feeling of superiority made him unwilling to allow the fly any privilege that was denied to his son. What appears as cruelty on his part could have been a result of his failure to stabilize his mind about suffering, destiny and death.
The "grinding feeling of wretchedness", transforming into fear, triggered in his mind an almost deliberate amnesia. This is the moment when the father in him breaks through the bounds of his external persona to appeal to every father of all times. This is where the particular becomes the universal, the limited becomes the boundless and we understand the true significance of his namelessness.
"As flies to wanton boys, are we to the gods. They kill us for their sport".
The questions raised by the father of the five-year-old girl in "Pearl", or the words uttered by Maurya in Synge's Riders to the Sea, reiterate in the actions of the Boss. The egoism in his initial high-handed attitude shown to Woodifield transforms into a humble surrender and an awareness of his barrenness, through a potent handling of parallelism and contrast. Ironically, despite his deliberate urge to establish his superiority, the boss becomes one with his aged subordinate. The story begins with Woodifield's forgetting. It ends with the Boss's failure to remember.
Within a brief span, we come to a full circle sans pity sans fear, experiencing a catharsis that leaves a mark in our memories. The Boss becomes a universal figure of despair who has no refuge but in forgetfulness. For him, even the memory of his encounter with a petty fly needs to be flipped off into a waste-paper basket. He becomes the microcosm of a generation which was left to mourn the onslaught of the all-pervasive World Wars. His plight is not just the suffering but the futility to eradicate suffering in others. The boss is a sum total of the post-modern man's sense of denial and despair, which sees every bit of action as a reinforced reminder of his worthlessness.
Why did the Boss kill the fly?


Our smartphones can both bind us and liberate us in a myriad of ways. They put us in touch with others, help us automate things, and guide us when we're on our way. All this requires the basic ability to tap a finger on the phone's screen. Yet, the very people that would most benefit from that capabilities of smartphones are the ones least able to use them. Specifically, paraplegics that can't move their arms can't make phone calls, turn lights on and off, and direct a wheelchair through a single interface. To make this possible, project called Sesame is aiming to empower standard smartphones to be used by people who only have movement left above the neck.
The Sesame uses the phone's built-in camera to track the person's face motion, essentially coupling the person's nose to the cursor on the screen. The software is adjustable to match the motor abilities of the person using it. The project is not far from commercial reality, as 10 beta users are already testing the technology, initially being designed for the Nexus 5, but is expected to eventually work on a variety of phones. The folks behind the Sesame are looking to raise some funds on Indiegogo to help them push it towards completion and allow them to begin shipping the ready-to-go Nexus 5 phones with the software pre-installed.


text:
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Research Article| September 01 1996
Mediation of interleukin-11-dependent biological responses by a soluble form of the interleukin-11 receptor
Julia KAROW;
Julia KAROW
*CRC Growth Factor Group, Department of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, U.K.
Keith R. HUDSON;
Keith R. HUDSON
Mark A. HALL;
Mark A. HALL
Ann B. VERNALLIS;
Ann B. VERNALLIS
Jacky A. TAYLOR;
Jacky A. TAYLOR
Achim GOSSLER;
Achim GOSSLER
†The Jackson Laboratory, 600 Main St., Bar Harbor, ME 04609-1500, U.S.A.
John K. HEATH
John K. HEATH §
‡Department of Biochemistry, University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K.
§To whom correspondence should be addressed.
https://doi.org/10.1042/bj3180489
Julia KAROW, Keith R. HUDSON, Mark A. HALL, Ann B. VERNALLIS, Jacky A. TAYLOR, Achim GOSSLER, John K. HEATH; Mediation of interleukin-11-dependent biological responses by a soluble form of the interleukin-11 receptor. Biochem J 1 September 1996; 318 (2): 489–495. doi: https://doi.org/10.1042/bj3180489
Interleukin-11 (IL-11) is a polyfunctional cytokine whose biological actions require a specific IL-11 receptor (IL-11R) and the transmembrane transducer gp130. Here we report the production of a soluble form of the murine IL-11R and demonstrate that it interacts with IL-11 ligand with high affinity. The affinity of IL-11 alone for gp130 is below the level of detection, but a complex of IL-11 and soluble IL-11R interacts with gp130 with high affinity. The addition of soluble IL-11R potentiates the effects of exogenous IL-11 in cells that are normally responsive to IL-11. A biological response to IL-11 can be reconstituted in BAF cells transfected with gp130 by addition of IL-11 and soluble IL-11R. These findings show that the cytoplasmic domain of the IL-11R is not required for the biological effects of IL-11 and that a complex of IL-11 and IL-11R mediates signalling by association with gp130.
The Biochemical Society, London © 1996
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I'm back again with another fashion week related post because I've hated all my outfits this week and I havent got any time to shoot them anyway (although don't worry, I have great plans for this weekend ;) ANYWHO, The other collection I did was very "me," but now I can honestly say this collection is very "Caelan" or "Kaelen" lol. I chose Kaelen Haworth's collection for her brand Kaelan mostly because A) I'd never heard of it before B) I thought "oh hey, that's almost my name and C) because I was actually very impressed by what I saw. So, without further adue, my girl Kaelen.
KAELEN HAWORTH is a Canadian living in and running her eponymous label in New York City. While attending Parsons, The New School for Design, Kaelen interned for Jenni Kayne, Stella McCartney and lingerie brand, The Lake & Stars.
One year after graduating, KAELEN launched with a collection shown during New York Fashion week in 2010. Designing from a minimalist perspective with a focus on subtle details, KAELEN seeks to combine the traditional and the innovative, exploring the dichotomies of masculine and feminine, classic and modern. KAELEN strives to create pieces that are at once intelligent, archival and treasured.
Her idols include Tilda Swinton, Jeff Bridges and Joan Didion. Point Break, Overboard and The Great Outdoors are some of her favorite movies. She is in love with almost all music, excluding crossover country-pop.
Information provided from her website!


Put the Easter egg hunt money in the eggs before hiding them and keep the prizes on the table. When the children have found the money, let them spend it on the items they like. This bill is yellow and has a picture of a chick; it's worth five pretend dollars.


text:
\section{AOT-Hexadecane Electrolyte}

\subsection{Conductivity Measurements}

We measured the conductivity of the AOT-hexadecane electrolytes using the same chamber used for the Quincke experiments described in the main text.  The electrode separation was $L=110~\mu$m; the electrode area was $A=1.0\times2.0$ cm$^2$. Using a sourcemeter (Keithley 2410), we applied different voltages $V$ across the chamber and measured the current $I$ and resistance $R=V/I$ at regular intervals of 0.15 s for a duration of six minutes. The conductivity $\sigma$ was evaluated from this data as
\begin{equation}
    \sigma=\frac{\langle R\rangle A}{L}
\end{equation}
where $\langle R\rangle$ denotes the average resistance over the duration of each experiment. Figure \ref{fig:conductivity} shows the conductivity $\sigma$ as a function of the applied field $E_{\text{e}}=V/L$ for the three AOT concentrations used in our experiments.

\begin{figure}[h]
    \centering
    \includegraphics[width=13cm]{Figure/S1_conductivity.pdf}
    \caption{Conductivity $\sigma$ vs.\ field strength $E_{\text{e}}$ for AOT-hexadecane solutions of different concentrations (left). The lines show best linear fits of the form $\sigma=\sigma_0 \exp(b E_{\text{e}})$ with $b=0.301~\mu$m\,$V^{-1}$ and $\sigma_0=0.819$, $2.29$, and $4.12\times10^{-8}$ S\,m$^{-1}$ for AOT concentrations $\text{[AOT]}=0.05$, $0.1$, and $0.15$ M, respectively.  The zero field conductivity $\sigma_0$ increases faster than linearly with AOT concentration as approximated by the relation, $\sigma_0\propto \text{[AOT]}^{1.47}$ (right).}
    \label{fig:conductivity}
\end{figure}

\subsection{Zero-Field Conductivity}

The anionic surfactant, AOT (sodium bis-2-ethyl hexyl sulphosuccinate), forms inverse micelles in hexadecane above a  critical micelle concentration (CMC) of $\sim\!10^{-6}$ M.\autocite{Sainis2008}  Small-angle neutron scattering (SANS) data suggest that each inverse micelle contains $N\approx20$ AOT molecules with a polar core of radius $a_{\text{c}} \approx 1$ nm and a hydrodynamic radius of $a_{\text{h}} \approx 1.7$ nm.\autocite{Kotlarchyk1985} At equilibrium,  the charge fluctuation theory\autocite{Prieve2017} predicts the number density of charged micelles to be
\begin{equation}
    n_z = n_0 \exp{\left(\frac{-z^2\lambda_{\text{B}}}{2 a_{\text{c}}}\right)}
\end{equation}
where $n_0$ is the concentration of uncharged micelles, $z$ is the valence of charged micelles, and $\lambda_{\text{B}}$ is the Bjerrum length
\begin{equation}
    \lambda_{\text{B}} = \frac{e^2}{4\pi \varepsilon k_{\text{B}} T} \approx 27 \text{ nm}
\end{equation}
where $e$ is the elementary charge, $\varepsilon = 2.05\varepsilon_0$ is the permittivity of hexadecane, $k_{\text{B}}$ is the Boltzmann constant, and $T=298$ K is the temperature.  The fact that $\lambda_{\text{B}}/2a_{\text{c}}\approx 14\gg 1$ implies that nearly all of the charged micelles have unit valence, $z=\pm 1$.  The equilibrium (zero-field) conductivity of the solution is estimated to be
\begin{equation}
    \sigma_0 = \sum_z  z^2 e^2 \mu n_z\approx 2 e^2 \mu n_0 \exp{\left(-\frac{\lambda_{\text{B}}}{2a_{\text{c}}}\right)}
\end{equation}
where $\mu\approx (6\pi\eta a_{\text{h}})^{-1}$ is the micelle mobility, and $\eta=2.9$ mPa$\cdot$s is the dynamic viscosity of hexadecane.

This model predicts that the conductivity increases linearly with the AOT concentration in agreement with previous experiments.\autocite{Sainis2008}  By contrast, our conductivity measurements at high AOT concentrations suggest that the conductivity increases faster than linearly with AOT concentration (Figure~\ref{fig:conductivity}, right).  This observation is explained by the increase in the dielectric constant of the solution with increasing AOT concentration. Using Maxwell's theory, the effective permittivity for a dispersion of particles (here, micelles) of permittivity $\varepsilon_{\text{p}}$ in a fluid of permittivity $\varepsilon_{\text{f}}$ is
\begin{equation}
    \varepsilon = \varepsilon_{\text{f}}\frac{2 \varepsilon_{\text{f}} + \varepsilon_{\text{p}} + 2 \phi (\varepsilon_{\text{p}} - \varepsilon_{\text{p}})}{2\varepsilon_{\text{f}} + \varepsilon_{\text{p}} - \phi (\varepsilon_{\text{p}} - \varepsilon_{\text{f}} )} = \varepsilon_{\text{f}} + 3 \varepsilon_{\text{f}}  \left(\frac{\varepsilon_{\text{p}}-\varepsilon_{\text{f}}}{\varepsilon_{\text{p}} + 2 \varepsilon_{\text{f}}}\right)\phi + O(\phi^2)
\end{equation}
where $\phi\approx \tfrac{4}{3}\pi a_{\text{h}}^3 n_0$ is the volume fraction of particles (micelles).  The experimental data for the zero-field conductivity are well described by the parameter estimates, $a_{\text{c}}=1.16$ nm and $\varepsilon_{\text{p}}=4.22\varepsilon_0$, which are physically reasonable.

\subsection{Ionization Kinetics}

Two uncharged micelles can ``react'' to form two oppositely charged micelles with a rate approximated as
\begin{equation}
    r = k_{\r}(n_{\text{eq}}^2  - n_+ n_-)
\end{equation}
where $n_{\text{eq}} = n_0 \exp(-\lambda_{\text{B}}/2a_{\text{c}})$ is the equilibrium ion concentration predicted by the charge fluctuation theory, $n_{\pm}$ is the concentration of positive/negative ions, and $k_{\r}$ is the rate constant for ion-ion recombination.  As only a small fraction of micelles are charged, the concentration of neutral micelles can be approximated from the AOT concentration as $n_0=[\text{AOT}]/N$. If recombination is assumed to be diffusion-limited, the rate constant can be estimated\autocite{Debye1942,Saville1997} as
\begin{equation}
    k_{\r} = 8\pi D \lambda_{\text{B}} = \frac{2 e^2 \mu}{ \varepsilon} \approx 2.9\times 10^{-17} \text{ m}^3/\text{s} \label{eq:kr}
\end{equation}
where $D=k_{\text{B}} T \mu$ is the micelle diffusivity.  The micelles approach their equilibrium ionization with a characteristic time scale $(2k_{\r} n_{\text{eq}})^{-1}$, which is equal to one half of the charge relaxation time $\varepsilon/\sigma_0$. For a 0.1 M AOT solution, the equilibrium ion concentration is $n_{\text{eq}}\approx 7\times 10^{-8}$ M and the ion relaxation time is $(2 k_{\r} n_{\text{eq}})^{-1}\geq 0.4$ ms with equality for diffusion-limited recombination.

\subsection{Field-Dependent Conductivity}

The measured conductivity increases with the magnitude of the applied field as approximated by the empirical relation
\begin{equation}
    \sigma = \sigma_0 \exp(b E_{\text{e}})
\end{equation}
where $\sigma_0$ is the zero-field conductivity, and $b=0.301~\mu$m\,V$^{-1}$ is a fitted parameter independent of AOT concentration (Figure \ref{fig:conductivity}). This functional form and the value of $b$ can be rationalized by a simple kinetic model that describes the charging of two neutral micelles following their collision in the presence of the applied field. In this model, the rate of ionization is approximated as
\begin{equation}
    r_{\text{i}} = k_{\text{i}} n_0^2 \exp\left(- \frac{U_{\aa}}{k_B T} \right)  \quad \text{with} \quad U_{\aa} = \frac{2e^2}{8\pi\varepsilon a_{\text{c}}} - \frac{e^2}{4\pi\varepsilon \lambda_{\text{B}}} - e \lambda_{\text{B}} E_{\text{e}}
\end{equation}
where $k_{\text{i}}$ describes the rate of collisions between neutral micelles present at concentration $n_0$. Here, $U_{\aa}$ describes the activation energy required to create a pair of oppositely charged micelles separated by the Bjerrum length $\lambda_{\text{B}}$. It includes the Born self-energy of the two charged micelles, the Coulomb energy of interaction between them, and the energy of separating the charged pair in the electric field. Balancing the rate of ionization with that of recombination, $r_{\text{r}}=k_{\text{r}} n_+ n_-$, we obtain the following expression for the ion concentration
\begin{equation}
    n_{\pm} = n_0  \exp\left(-\frac{\lambda_{\text{B}}}{2a_{\text{c}}}  +  b E_{\text{e}} \right) \quad \text{with} \quad b = \frac{e \lambda_B}{2k_{\text{B}} T} \approx 0.5~\mu\text{m\,V}^{-1}
\end{equation}
where we have chosen, $k_{\text{i}} = k_{\text{r}} e^{-1}$, to ensure consistency with the charge fluctuation theory in the zero field limit. The parameter $b$ agrees to within in a factor of two with the value determined experimentally.  Among the many simplifying approximations of this model, we have assumed that the process of ion-ion recombination does not depend on the magnitude of the external field.

\clearpage
\section{Data Collection \& Analysis}

\subsection{Experimental Details}
Polystyrene (PS) spheres of radius $a=1.5$, 2.5, or 5 $\mu$m (ThermoFisher Scientific) are washed and dried overnight at  55$^{\circ}$C prior to dispersing in hexadecane solutions of AOT surfactant (Sigma-Aldrich). Dilute particle suspensions (volume fraction $< 0.0002$) are injected into a microfluidic chamber created by two ITO-coated glass electrodes (Sigma-Aldrich) separated by one or more glass coverslips as spacers. Once filled, the chamber is sealed with epoxy. A constant voltage $V=$ 0--900 V is applied between the two electrodes by a source measure unit (Keithley 2410). The magnitude of resulting electric field $E_{\text{e}}=V/L=$ 0--6 V/$\mu$m is limited primarily by the dielectric strength of the hexadecane solution.  The motion of the particles at the lower electrode is imaged from below using an optical microscope (Nikon Eclipse Ti-U) equipped with high speed camera (Phantom V310); videos are captured at 2000 frames per second. From the videos, we use TrackPy v0.4.2 in Python to detect particles and link their trajectories.

\subsection{Bayesian Model Section}

For each track, we analyze the 2D particle position $\ve{x}=(x,y)$ as a function of time $t$ using three different models: stationary (denoted $M_s$), rolling ($M_r$), and oscillatory ($M_o$). We use Bayesian model selection to determine the posterior probability of each model given the tracking data. These probability assignments are used to color the markers in Figures 1c and 2 of the main text.

Each model is characterized by uncertain parameters denoted by the vector $\ve{w}$---for example, the initial particle position $\ve{x}_0$ and the particle velocity $\ve{U}$ in the rolling model. Given data consisting of the particle positions $\ve{x}_i$ at times $t_i$ (denoted $\mathcal{D}=\{\ve{x}_i,t_i\}$ for $i=1,...,n$), the posterior distribution for the parameters $\ve{w}$ of model $M$ is given by Bayes theorem
\begin{equation}
    p(\ve{w}\mid\mathcal{D},M) = \frac{ p(\mathcal{D}\mid \ve{w},M) p(\ve{w}\mid M)}{ p(\mathcal{D}\mid M)} \label{eq:posterior}
\end{equation}
where $p(\ve{w}\mid M)$ is the prior, and $ p(\mathcal{D}\mid \ve{w},M)$ is the likelihood. The denominator, representing the evidence for the model $M$, is evaluated by marginalizing over the parameters $\ve{w}$ as
\begin{equation}
    p(\mathcal{D}\mid M) = \int p(\ve{w}\mid \mathcal{D},M)p(\ve{w}\mid M) d\ve{w}
\end{equation}
This quantity is required in estimating the probability that model $M$ is true, relative to the competing models
\begin{equation}
    p(M\mid \mathcal{D}) \propto p(\mathcal{D}\mid M) p(M)
\end{equation}
Here, we assume that each model has equal prior probabilities such that $p(M_s)=p(M_r)=p(M_o)$; the ``best'' model is that with the greatest evidence $p(\mathcal{D}\mid M)$.

\subsection{Stationary, Rolling, and Oscillatory Models}

For each experiment, we divide the reconstructed tracks for all particles into non-overlapping windows of $n$ frames ($n=20$ for $[\text{AOT}]=150$ mM, $n=60$ for $[\text{AOT}]=50$ and 100 mM); each window contains the positions $\{\ve{x}_i\}$ of a single particle at $n$ time points.  The size of the windows is long enough to distinguish between the three types of motion but short enough to neglect the changing orientation of particle rolling or oscillation. We analyze each window independently of the others and pool the resulting parameter estimates.  Within each window, the three models are given by
\begin{align}
    M_s:\quad \ve{x}_i &= \ve{x}_0 + \xi_i
    \\
    M_r:\quad\ve{x}_i &= \ve{x}_0 + \ve{U} t_i + \xi_i
    \\
    M_o:\quad \ve{x}_i &= \ve{x}_0 + \ve{A}\cos(\omega t_i) + \ve{B}\sin(\omega t_i) + \xi_i
\end{align}
where $i=1,\dots,n$ and $\xi_i\sim\mathcal{N}(0,\sigma^2)$ is Gaussian noise with zero mean and standard deviation $\sigma = 1$ pixel (0.5 $\mu$m). The stationary and rolling models depend linearly on their parameters and are treated using standard methods for linear models (see below).

\subsubsection*{Normal Linear Models}

Here, we briefly summarize the necessary results for inference and model selection using normal linear models.\autocite{williams2006gaussian}  These results are applied in analyzing the experimental data using the stationary and rolling models, which have the following linear form
\begin{equation}
    \ve{y} = X^{\top} \ve{w} + \varepsilon
\end{equation}
where $\ve{y}$ is an $n$-dimensional vector of outputs, $\ve{w}$ is a $D$-dimensional vector of weights (i.e., parameters of our linear model), $X$ is the $D\times n$ design matrix, and $\xi\sim\mathcal{N}(\ve{0},\sigma^2 I)$ is independent identically distributed Gaussian noise.  Given data consisting of the outputs $\ve{y}$ and the design matrix $X$, we aim to infer the values of the parameters $\ve{w}$ as
\begin{equation}
    p(\ve{w}\mid \ve{y}, X) =  \frac{p(\ve{y}\mid \ve{w}, X)p(\ve{w})}{p(\ve{y}\mid X)}
\end{equation}
Here, the prior for the parameters $\ve{w}$ is assumed to be a normal distribution with zero mean and covariance matrix $\Sigma_p$
\begin{equation}
    p(\ve{w}) = \mathcal{N}(\ve{0},\Sigma_p)
\end{equation}
The posterior distribution is also normally distributed
\begin{align}
    p(\ve{y}\mid \ve{w}, X)p(\ve{w}) &= C \exp\left(-\frac{1}{2\sigma^2}(\ve{y}-X^{\top}\ve{w})^{\top}(\ve{y}-X^{\top}\ve{w})\right)\exp\left(-\frac{1}{2} \ve{w}^{\top} \Sigma_p^{-1} \ve{w}\right)
    \\
    & = C \exp\left(-\frac{1}{2}(\ve{w}-\bar{\ve{w}})^{\top} A^{-1} (\ve{w}-\bar{\ve{w}})\right) \exp\left(- \frac{\ve{y}^{\top}\ve{y}}{2\sigma^2} + \frac{1}{2} \bar{\ve{w}}^{\top} A^{-1}\bar{\ve{w}}\right)
\end{align}
where $\bar{\ve{w}}=A X\ve{y}/\sigma^2$ is the posterior mean, $A=(\Sigma_p^{-1}+X X^{\top}/\sigma^2)^{-1}$ is the posterior convariance matrix, and the constant $C=(2\pi \sigma^2)^{-n/2} |2\pi \Sigma_p|^{-1/2}$.  The evidence is
\begin{align}
    p(\ve{y}\mid X) &= \int  p(\ve{y}\mid \ve{w}, X)p(\ve{w}) d\ve{w}
    \\
    &= \frac{|2\pi A|^{1/2}}{(2\pi \sigma^2)^{n/2} |2\pi \Sigma_p|^{1/2}} \exp\left(- \frac{\ve{y}^{\top}\ve{y}}{2\sigma^2} + \frac{1}{2} \bar{\ve{w}}^{\top} A^{-1}\bar{\ve{w}}\right)
\end{align}
The logarithm of the evidence provides a useful measure by which measure the performance of one model versus another
\begin{equation}
    \ln p(\ve{y}\mid X) = \frac{1}{2} \ln\frac{|A|}{|\Sigma_p|} - \frac{n}{2} \ln (2\pi \sigma^2) - \frac{\ve{y}^{\top}\ve{y}}{2\sigma^2} + \frac{1}{2} \bar{\ve{w}}^{\top} A^{-1}\bar{\ve{w}}
\end{equation}

\paragraph{Stationary Model.}
In the stationary model $M_s$, the unknown parameters $\ve{w}$ include only the constant particle position $\ve{x}_0$.  Prior to analysis, we center the tracking data for each window such that $\sum_i \ve{x}_i=0$.  We adopt a Gaussian prior for $\ve{x}_0$ with zero mean and covariance matrix $\Sigma_p = I(10 \text{ pixels})^2$, where $I$ is the $2\times2$ identity matrix. We use the same prior on $\ve{x}_0$ in the rolling and oscillatory models.

\paragraph{Rolling Model.}
In the rolling model, the unknown parameters $\ve{w}$ are augmented to include the particle velocity $\ve{U}$ as well as the initial position $\ve{x}_0$.  We adopt a Guassian prior for the velocity with zero mean and a standard deviation of 10 pixels/frame (ca.\ 5,000 $\mu$m/s) in both the $x$ and $y$-directions.  Figure \ref{fig:rolling} shows a typical result for the speeds $U$ inferred from windows classified as ``rolling''.

\begin{figure}[t]
    \centering
    \includegraphics[width=\textwidth]{Figure/S2_Rolling.png}
    \caption{(left) Tracking data for 10 $\mu$m spheres immersed in a 0.15 M AOT hexadecane solution between parallel electrodes separated by 150 $\mu$m and subject to a voltage of 525 V. The tracking data was divided into 636 windows of $n=50$ frames, of which 73\% were classified as rolling.  (right) Histogram of the MAP estimates for particle speed $U$ for those 462 windows classified as rolling.  The dashed line shows the mean speed.}
    \label{fig:rolling}
\end{figure}

\paragraph{Oscillatory Model.}
The oscillatory model is non-linear in the frequency $\omega$ but linear in the other parameters. Building on our review of linear models in the previous section, we now have a model of the form
\begin{equation}
    \ve{y} = X^{\top}_{\omega} \ve{w} + \varepsilon \label{eq:oscillatory}
\end{equation}
where the design matrix depends non-linearly on the frequency $\omega$. For a given value of the frequency, this model can be analyzed using the methods of the previous section. The posterior for the frequency can be written as
\begin{equation}
    p(\omega \mid \ve{y}) = \frac{p(\ve{y}\mid X_{\omega})p(\omega)}{p(\ve{y})}
\end{equation}
We use a uniform prior on the domain $2\pi/n\Delta t < \omega < \pi/\Delta t$, where $n$ is the number of frames in the window, and $\Delta t$ is the time step between consecutive frames  (i.e., $\Delta t = 1$ frame). The minimum frequency corresponds to a single oscillation cycle over the length of the window; the maximum frequency is the Nquist frequency. We use numerical optimization to identify the maximum a posterior probability (MAP) estimate of the frequency $\omega^{*}$. We use this point estimate of the frequency to analyze the oscillatory model (\ref{eq:oscillatory}) as a linear model using the methods of the previous section.

\paragraph{Gaussian Process Model.}
For some windows, none of the three models describe the data well. We therefore introduce a forth model using a Gaussian process\autocite{williams2006gaussian}, which provides a general purpose alternative.  The Gaussian process models the data as
\begin{equation}
    y = f(t) + \varepsilon \quad\text{with}\quad f(t) = \mathcal{GP}(m(t),k(t,t'))
\end{equation}
Here, the mean function is assumed to be zero, $m(t)=0$, and the covariance function (or kernel) is chosen as a squared exponential
\begin{equation}
    k(t,t') = \sigma_f^2 \exp(\tfrac{1}{2}|t-t'|^2 / \tau)
\end{equation}
with hyperparameters $\sigma_f$ and $\tau$ characterizing the amplitude and correlation time, respectively.  We use values of $\sigma_f=5$ pixels and $\tau=2$ frames for the analysis of all experiments. Gaussian process regression is implemented using the scikit-learn package in Python, which provides the log-evidence $\ln p(\ve{y}\mid \sigma_f,\tau)$ needed for model selection.

\clearpage
\section{Additional Experimental Data}

\subsection{Effect of AOT Concentration $[\text{AOT}]$}
\vspace{1cm}
\begin{figure}[h]
    \centering
    \includegraphics{Figure/S3_aot_concentration.pdf}
    \caption{Time-averaged particle speed vs.\ external field strength $E_{\text{e}}$ for $a=5~\mu$m PS spheres at three different AOT concentrations. The electrode separation is $L=150~\mu$m. The plot is (c) is reproduced from Figure 1c in the main text. As in Figure 1c, we compute the mean and standard deviation of the particle speed for each 20 ms trajectory. Markers denote the median of these mean speeds; error bars denote the median of the corresponding standard deviations. The plotted data are colored based on probability assignments of the Bayesian classifier.}
    \label{fig:aot_concentration}
\end{figure}

\clearpage
\subsection{Effect of Particle Radius $a$}
\vspace{1cm}
\begin{figure}[h]
    \centering
    \includegraphics{Figure/S4_particle_size.pdf}
    \caption{Time-averaged particle speed vs.\ external field strength $E_{\text{e}}$ for PS spheres of three different radii. The AOT concentration is $\text{[AOT]}=0.15$ M; electrode separation is $L=150~\mu$m. The plot is (c) is reproduced from Figure 1c in the main text. As in Figure 1c, we compute the mean and standard deviation of the particle speed for each 20 ms trajectory. Markers denote the median of these mean speeds; error bars denote the median of the corresponding standard deviations. The plotted data are colored based on probability assignments of the Bayesian classifier.}
    \label{fig:particle_size}
\end{figure}

\clearpage
\subsection{Oscillatory Rolling in the Transition Region}

\vspace{1cm}

\begin{figure}[h]
   \centering
    \includegraphics{Figure/S5_transition.pdf}
    \caption{Instantaneous speed and accumulated displacement of a PS particle with radius $a=5~\mu$m as a function of time for a field strength $E_{\text{e}}=4~$V/$\mu$m. The AOT concentration is $\text{[AOT]}=0.15$ M; electrode separation is $L=150~\mu$m. These conditions correspond to the transition between steady rolling and back-and-forth oscillations (see Figure 1c).}
    \label{fig:transition}
\end{figure}

\clearpage
\subsection{Arrested Motion of $1~\mu$m Particles}
\vspace{1cm}
\label{sec:1um}
\begin{figure}[htp]
   \centering
    \includegraphics{Figure/S6_1um.pdf}
    \caption{(a) Brownian trajectory of a 1 $\mu$m PS sphere in a 150 mM solution of AOT in hexadecane. (b) Application of an external field $E_{\text{e}}=2$ V/$\mu$m arrests the particle's motion. (c) Mean squared displacement (MSD) vs.\ lag time for the trajectories in (a) and (b). In the absence of the field, the particle has an apparent diffusivity of $D_{\text{p}}=0.095~\mu\text{m}^2$/s. The particle does not diffuse upon application of the field.}
\end{figure}

\clearpage
\subsection{Oscillation Frequency $\omega \tau_{\text{mw}}$ vs.~Field Strength $E_{\text{e}}/E_{\text{c}}$ }
\vspace{1cm}
\begin{figure}[h]
   \centering
    \includegraphics{Figure/S7_FrequencyVsField.pdf}
    \caption{Oscillation frequency $\omega$ scaled by the Maxwell-Wager time $\tau_{\text{mw}}$ vs.\ external field strength $E_{\text{e}}$ scaled by the critical field strength $E_{\text{c}}$ for three different AOT concentrations. These data are identical to those shown in Figure 3b but are here scaled by $\tau_{\text{mw}} = 3.5, 1.3, 0.70$ ms and $E_{\text{c}}=0.41, 0.68, 0.91$ V/$\mu$m for $[\text{AOT}]=50$, 100, 150 mM, respectively. The particle radius is $a=5~\mu$m.  Markers denote the mean frequencies within populations of particle trajectories of equal duration; error bars denote standard deviations of these populations. The dashed curve is the equation $\omega \tau_{\text{mw}} = 0.09 E_{\text{e}} / E_{\text{c}}$ stated in the main text.}
\end{figure}

\clearpage
\subsection{Acoustic Levitation Experiments}
\vspace{1cm}
\begin{figure}[h]
   \centering
    \includegraphics{Figure/S8_levitated.pdf}
    \caption{Time-lapse microscopy images showing the dynamics of a single particle oscillating at the electrode surface (left) and rotating within the bulk fluid (right). Dashed circles highlight the particle position. The external field strength in both experiments is $E_{\text{e}}=4~$V/$\mu$m. Scale bars are $40~\mu$m. Here, we use 40 $\mu$m polyethylene Janus spheres with a white  hemisphere coated on black core (HCMS-BLK-WHT-Polymer from Cospheric Inc.).  Also visible in the images are 1 $\mu$m fluorescent particles (white), which aid in visualizing the motion of the larger particle. Particle levitation is achieved using a piezoelectric transducer adhered to the outside of the top electrode. The transducer is driven by a sinusoidal voltage signal with an amplitude of 10 V and a frequency of 3.6 MHz. The precise frequency is tuned to create a standing acoustic field with wavelength equal to twice the electrode separation $L=200~\mu$m. Under these conditions, particles levitate at the mid-plane equidistant from the two parallel electrodes.}
    \label{fig:levitated}
\end{figure}

\clearpage
\section{Analysis of a Model Electrolyte in 1D}
\label{sec:model_electrolyte}

Following Saville,\autocite{Saville1997} we consider a binary monovalent electrolyte, in which the charge carriers are created by the homogeneous ionization of neutral species.  The concentration of positive and negative charge carriers is governed by the Nernst-Planck equation
\begin{equation}
    \frac{\partial n_\pm}{\partial t}+\nabla\cdot \left(n_{\pm}\ve u  -D \nabla n_\pm \pm \frac{e D}{k_{\text{B}} T} n_\pm \ve E \right) = k_{\r} (n_{\text{eq}}^2 - n_+n_-) \label{eq:npm}
\end{equation}
where $\ve u$ is the fluid velocity. The electric field $\ve{E}=-\nabla \phi$ is related to the local charge density by the Poisson equation
\begin{equation}
    \nabla^2 \phi = -\frac{e}{\varepsilon}(n_+ - n_-) \label{eq:phi}
\end{equation}
Here, we analyze the behavior of this model---the so-called Poisson-Nernst-Planck (PNP) equations---in 1-dimension for different boundary conditions in the presence of strong electric fields $E\gg k_{\text{B}} T/e \ell$. First, we consider a semi-infinite electrolyte in contact with an absorbing boundary at which the concentration of charge carriers is zero. Analysis of this problem reveals the electric boundary layer of thickness $\ell$ anticipated by the scaling arguments presented in the main text. Next, we consider a 1D electrolyte confined between two absorbing boundaries.  We show how the electric current is limited by the rate of ionization when the domain size is smaller than the boundary layer thickness.  Finally, we consider the effects of electrolyte confinement on the transient charging of a no-flux boundary.

\subsection{Semi-Infinite Electrolyte with an Absorbing Boundary}

We first consider an absorbing boundary at $x=0$ in contact with our model electrolyte on the domain $x>0$.  Introducing the total ion concentration, $n_{\text{s}}=n_+ + n_-$, and the concentration difference, $n_{\text{d}}=n_+ - n_-$, the governing equations can be written as
\begin{align}
\begin{split}
    \frac{\partial n_{\text{d}}}{\partial t} + e \mu \frac{\partial(n_{\text{s}} E)}{\partial x}&= 0
    \\
    \frac{\partial n_{\text{s}}}{\partial t} + e \mu \frac{\partial(n_{\text{d}} E)}{\partial x} &= 2k_{\r} \left[n_{\text{eq}}^2-\frac{1}{4}\left(n_{\text{s}}^2-n_{\text{d}}^2\right)\right]
    \\
    \frac{\partial E}{\partial x} &= \frac{e}{\varepsilon} n_{\text{d}} \label{eq:1D}
\end{split}
\end{align}
where $\mu = D/k_{\text{B}} T\approx (6\pi \eta a_{\text{h}})^{-1}$ is the mobility of the charged micelles. Here, we have omitted convective and diffusive transport which are negligible for the strong fields of interest as confirmed below. Due to our neglect of the diffusive flux, it is not possible to simultaneously satisfy the conditions, $n_{+}(0)=0$ and $n_{-}(0)=0$, at the absorbing boundary.  For a field in the positive $x$-direction ($E_{\text{e}}>0$), we require only that the concentration of positive ions vanish at the boundary
\begin{equation}
    n_+(0) = \frac{1}{2} \left(n_{\text{s}}(0) + n_{\text{d}}(0)\right) = 0 \label{eq:1D_bc1}
\end{equation}
By contrast, the concentration of negative ions is expected to fall to zero within a thin diffusive boundary layer neglected in our present analysis. Far from the boundary ($x\rightarrow\infty$), the ion concentrations approach their equilibrium values in the presence of an external field $E_{\text{e}}$
\begin{equation}
    n_{\text{d}}(\infty) = 0, \quad n_{\text{s}}(\infty) = 2 n_{\text{eq}},  \quad E(\infty)=E_{\text{e}} \label{eq:1D_bc2}
\end{equation}

At steady-state, equations (\ref{eq:1D}) can be combined to give a single differential equation for the field squared $E^2$.
Charge conservation implies that the electric current density is everywhere constant and equal to $j_{\text{e}}= e^2 \mu n_{\text{s}} E = 2 e^2 \mu n_{\text{eq}} E_{\text{e}}$, where the second equality follows from the boundary condition (\ref{eq:1D_bc2}).  The total ion concentration is therefore related to the applied field as $n_{\text{s}} =2 n_{\text{eq}} E_{\text{e}}/E$. The concentration difference $n_{\text{d}}$ is related to the field by Gauss's law. Substituting these expressions for $n_{\text{d}}$ and $n_{\text{s}}$ into the second line of equation (\ref{eq:1D}), we obtain the following nonlinear equation for the field squared
\begin{equation}
    \frac{d^2 E^2}{d x^2} = \frac{4 k_{\r} n_{\text{eq}}^2}{\mu \varepsilon} \left[1 - \frac{E_{\text{e}}^2}{E^2} + \frac{1}{E^2} \left(\frac{\varepsilon}{4e n_{\text{eq}}} \frac{d E^2}{d x} \right)^2 \right] \label{eq:E2}
\end{equation}
At $x=0$, the boundary condition (\ref{eq:1D_bc1}) becomes
\begin{equation}
    2 n_{\text{eq}} \frac{E_{\text{e}}}{E(0)} + \frac{\varepsilon}{e} \left.\frac{d E}{dx}\right\rvert_0 = 0 \quad \text{such that} \quad \left.\frac{d E^2}{d x}\right|_0 = -\frac{4 en_{\text{eq}} E_{\text{e}}}{\varepsilon}  \label{eq:E2bc1}
\end{equation}
Far from the boundary, the field approaches the asymptotic value $E(x\rightarrow \infty) = E_{\text{e}}$.

Equation (\ref{eq:E2}) is characterized by a length scale $\lambda$ over which the field approaches its asymptotic value.  Linearizing about this value, perturbations in the field squared---denoted $u = E^2 - E_{\text{e}}^2$---are governed by
\begin{equation}
    \frac{d^2 u}{d x^2} = \frac{4 k_{\r} n_{\text{eq}}^2}{\mu \varepsilon E_{\text{e}}^2} u + O(u^2)
\end{equation}
Perturbations decay over a characteristic length scale
\begin{equation}
    \lambda = \frac{E_{\text{e}}}{2 n_{\text{eq}}} \sqrt{\frac{\mu \varepsilon}{k_{\r}}} = \frac{1}{2} \beta \ell
\end{equation}
This length scale $\lambda$ is closely related to the scale, $\ell = e\mu E_{\text{e}}/k_{\r} n_{\text{eq}}$, described in the introduction of the main text. The two are related by the dimensionless parameter $\beta =(k_{\r} \varepsilon / e^2 \mu)^{1/2}$, which characterizes the relative rates of charge formation ($2 k_{\r} n_{\text{eq}}$) and charge relaxation ($2 e^2\mu n_{\text{eq}}/\varepsilon$). Assuming the diffusion-limited approximation (\ref{eq:kr}) for the recombination rate constant $k_{\r}$, these rates are approximately equal, $\beta=\sqrt{2}$, as are the two length scales, $\ell/\lambda =\sqrt{2}$. For a 0.1 M AOT-hexadecane solution subject to an external field of $E_{\text{e}}= 5$ V/$\mu$m, this length is estimated to be $\lambda\approx 5~\mu$m.  For comparison, the Debye length is $\lambda_{\text{D}}=(\varepsilon k_{\text{B}} T/2e^2 n_{\text{eq}})^{1/2}\approx 0.2~\mu$m.

\paragraph{Numerical Solution.} Figure \ref{fig:Profiles} illustrates the electric field and the ion distribution computed numerically for the experimental conditions.  To facilitate our analysis, we non-dimensionalize the problem using the following scales
\begin{align}
\begin{split}
    \text{Concentration:} &\quad n_{\text{eq}}
    \\
    \text{Field:} &\quad E_{\text{e}}
    \\
    \text{Length:} &\quad \lambda = \frac{E_{\text{e}}}{2 n_{\text{eq}}} \sqrt{\frac{\mu \varepsilon}{k_{\r}}}
    \\
    \text{Time:} &\quad \frac{\varepsilon}{2 e^2 \mu n_{\text{eq}}}
    \label{eq:E2_scales}
\end{split}
\end{align}
The dimensionless field is governed by
\begin{equation}
    \frac{d^2 E^2}{d x^2} = 1 - \frac{1}{E^2} + \frac{\beta^2}{4 E^2} \left( \frac{d E^2}{d x} \right)^2  \label{eq:E2_nd}
\end{equation}
where $\beta^2 = k_{\r} \varepsilon / e^2\mu$ is the ratio between the rate of charge formation ($2 k_{\r} n_{\text{eq}}$) and that of charge relaxation ($2 e^2\mu n_{\text{eq}}/\varepsilon$). For simplicity of notation, we used the same symbols to denote dimensional and dimensionless quantities alike; the distinction should be made clear by the context. At the boundary ($x=0$), the condition that the positive ion concentration goes to zero implies that
\begin{equation}
    \left.\frac{d E^2}{d x}\right|_0 = -\frac{2}{\beta}  \label{eq:E2_nd_bc1}
\end{equation}
Far from the boundary, the solution to the linearized equation implies that
\begin{equation}
    \frac{d E^2}{d x} = 1 - E^2 \quad \text{for} \quad x \gg 1 \label{eq:E2_nd_bc2}
\end{equation}
We compute $E^2$ numerically on a finite domain using equation (\ref{eq:E2_nd}) subject to the boundary conditions (\ref{eq:E2_nd_bc1}) and (\ref{eq:E2_nd_bc2}).  Given the field, the dimensionless ion concentrations are computed as
\begin{equation}
    n_{\text{s}} = \frac{2}{E},  \quad n_{\text{d}} = 2 \beta \frac{d E}{d x}
\end{equation}

\begin{figure}[t]
    \centering
    \includegraphics[width=9cm]{Figure/S9_Profiles.pdf}
    \caption{\textbf{One Absorbing Boundary.} Number density of positive and negative ions, $n_+$ and $n_-$, and the electric field $E$ as a function of distance $x$ from a plane boundary. Here, ion concentrations are scaled by the equilibrium concentration $n_{\text{eq}}$, the field by the external field $E_{\text{e}}$, and position by the characteristic length $\lambda$. The recombination parameter is $\beta^2=2$ corresponding to diffusion-limited ion recombination. The dashed green curve shows the asymptotic prediction of the linearized model.}
    \label{fig:Profiles}
\end{figure}

\paragraph{Validating Assumptions.}  In deriving the above results, we neglected the convective and diffusive contribution to the ion flux.  To validate these assumptions, we compare the magnitude of the terms retained to those neglected.  Diffusive contributions to the flux are small when
\begin{equation}
    \frac{D n_{\text{eq}}}{\lambda} \ll \frac{e D}{k_{\text{B}} T} n_{\text{eq}} E_{\text{e}} \quad \text{such that} \quad \frac{ e \lambda E_{\text{e}} }{k_{\text{B}} T} \gg 1
\end{equation}
For a 0.1 M AOT-hexadecane solution subject to an external field of $E_{\text{e}} = 5$ V/$\mu$m, this condition is satisfied as $e \lambda E_{\text{e}}/k_B T\sim 10^3\gg $1.  Diffusive transport becomes relevant near the boundary within a thin region of thickness $k_{\text{B}} T/e E_{e}\sim 10$ nm.   Similarly, convective transport is negligible provided that the characteristic flow velocity $U$ is sufficiently small
\begin{equation}
    U \ll e \mu E_{\text{e}} \sim 10 \text{ mm/s}
\end{equation}

\paragraph{Limiting Regimes.} The results above describe the specific scenario of diffusion-limited recombination, for which $\beta^2 = 2$. Here, we consider the structure of the solution for the limiting scenarios of $\beta\ll1$ and $\beta\gg1$. When the rate of ion recombination is much slower than the diffusion-limited rate ($\beta\ll1$; Figure \ref{fig:limiting}, left), the solution can be divided in two regions characterized by the following dominant terms in the dimensionless governing equation (\ref{eq:E2_nd})
\begin{align}
    \text{Region 1: } \quad \frac{d^2 E^2}{d x^2} &\approx 1 \quad \text{for} \quad  0\leq x \ll \frac{2}{\beta}
    \\
    \text{Region 2: } \quad \frac{d^2 E^2}{d x^2} &\approx E^2 - 1 \quad \text{for} \quad  x \gg\frac{2}{\beta}
\end{align}
Under these conditions ($\beta\ll1$), the thickness of the boundary region becomes $\ell = 2\lambda/\beta$ as predicted by the simple scaling argument in the main text.

\begin{figure}[t]
    \centering
    \begin{subfigure}{.5\textwidth}
        \centering
        \includegraphics[width=0.95\textwidth]{Figure/S10_Profiles_beta_small.pdf}
    \end{subfigure}%
    \begin{subfigure}{.5\textwidth}
        \centering
        \includegraphics[width=0.95\textwidth]{Figure/S10_Profiles_beta_large.pdf}
    \end{subfigure}
    \caption{\textbf{Limiting Regimes.} Field squared $E^2$ vs.~position $x$ for slow recombination with $\beta = 0.05$  (left) and fast recombination with $\beta=20$ (right). Solid curves denote the numerical solution of equation (\ref{eq:E2_nd}) with boundary conditions (\ref{eq:E2_nd_bc1}) and (\ref{eq:E2_nd_bc2}). The field is scaled by the external field $E_{\text{e}}$, and position by the characteristic length $\lambda$. For $\beta\ll1$, dashed and dotted curves denote the approximate relations, $ E^2\approx x^2/2 - 2x/\beta + C_1$ and $E^2\approx 1 - C_2 e^{-(x-2/\beta)}$, where the constants $C_1\sim 2\beta^{-2}$ and $C_2\sim 2$ are determined by matching these two solutions at $x\sim 2\beta^{-1}$. For $\beta\gg1$, dashed and dotted curves denote the approximate relations, $ E^2 \approx -4\beta^{-2}\ln \left(\beta/2 +\beta ^2 x/4 \right) + C_1 $  and $E^2 \approx 1 - C_2 e^{-(x-1)} $, where the constants $C_1\sim 1$ and $C_2\sim 4 \beta^{-2}$ are determined by matching these two solutions at $x\sim 1$. }
    \label{fig:limiting}
\end{figure}

The opposite limit of $\beta\gg1$ is unphysical as it implies ion-ion recombination faster than the diffusion-limited rate. We consider it here for the sake of completeness (Figure \ref{fig:limiting}, right). As above, the solution is divided in two regions characterized by the following dominant balances
\begin{align}
    \text{Region 1: } \quad \frac{d^2 E^2}{d x^2} &\approx \frac{\beta^2}{4}\left(\frac{d E^2}{d x}\right)^2 \quad \text{for} \quad  0\leq x \ll 1
    \\
    \text{Region 2: } \quad \frac{d^2 E^2}{d x^2} &\approx E^2 - 1 \quad \text{for} \quad  x \gg 1
\end{align}

\subsection{Finite Electrolyte between Two Absorbing Boundaries}

\begin{figure}[b!]
    \centering
    \begin{subfigure}{.5\textwidth}
        \centering
        \includegraphics[width=0.95\textwidth]{Figure/S11_twoabsorb.pdf}
    \end{subfigure}%
    \begin{subfigure}{.5\textwidth}
        \centering
        \includegraphics[width=0.95\textwidth]{Figure/S11_Current.pdf}
    \end{subfigure}
    \caption{\textbf{Two Absorbing Boundaries.} (left) Number density of positive and negative ions, $n_+$ and $n_-$, and the electric field $E$ as a function of position $x$ between two absorbing boundaries separated by $L=1$. Ion concentrations are scaled by the equilibrium concentration $n_{\text{eq}}$, the field by the external field $E_{\text{e}}$, and position by the characteristic length $\lambda$. The recombination parameter is $\beta^2=2$ corresponding to diffusion-limited ion recombination. (right) Electric current density $j_{\text{e}}$ (scaled by $e^2 \mu n_{\text{eq}} E_{\text{e}}$) as a function of the boundary separation $L$.  For small separations ($L\ll2$), the current is $j_{\text{e}}\approx \beta L/2$; for large separations ($L\gg2$), it approaches $j_{\text{e}}=2$.}
    \label{fig:Current}
\end{figure}

We now consider our model electrolyte sandwiched between two absorbing boundaries separated by a distance $L$ (Figure \ref{fig:Current}).  The potential difference across the electrolyte is specified as $L E_{\text{e}}$ such that
\begin{equation}
    \int_0^L E(x) d x = L E_{\text{e}}
\end{equation}
This condition is used to determine the electric current density $j_{\text{e}}$, which is now unknown.  Using the same scales (\ref{eq:E2_scales}), the dimensionless governing equation for the field squared is
\begin{equation}
    \frac{d^2 E^2}{d x^2} =1 - \frac{j_{\text{e}}^2}{4 E^2} + \frac{\beta^2}{4 E^2} \left( \frac{d E^2}{d x} \right)^2
\end{equation}
where the current $j_{\text{e}}$ is scaled by $e^2 \mu n_{\text{eq}} E_{\text{e}}$.  The conditions at the absorbing boundaries are
\begin{equation}
    \left.\frac{d E^2}{d x}\right|_0 = -\frac{j_{\text{e}}}{\beta} \quad \text{and} \quad \left.\frac{d E^2}{d x}\right|_L = \frac{j_{\text{e}}}{\beta}
\end{equation}
Figure \ref{fig:Current} (left) shows the electric field and the ion profiles for $L=1$ and $\beta^2=2$.  Due to the confined volume in which ions are generated, the associated current is only $j_{\text{e}}=0.655$ as compared to two in the limit of large separations ($L\rightarrow \infty$).  Figure \ref{fig:Current} (right) shows the computed current density $j_{\text{e}}$ as a function of the boundary separation $L$.  For $L\ll2$, the current is limited by the rate at which ions are generated within the electrolyte: $j_{\text{e}} \approx \beta L/2$.  In dimensional units, the apparent conductivity of the electrolyte depends linearly the boundary separation as
\begin{equation}
    \sigma = \frac{j_{\text{e}}}{E_{\text{e}}} \approx \frac{e k_{\r} n_{\text{eq}}^2 L}{E_{\text{e}}}  \quad \text{for} \quad L \ll 2\lambda
\end{equation}

\subsection{Semi-Infinite Electrolyte with a No-Flux Boundary}

\begin{figure}[b!]
    \centering
    \includegraphics[height=6cm]{Figure/S12_NoFlux.pdf}
    \caption{\textbf{One No-Flux Boundary.}  Transient electric field $E(x,t)$ near a no-flux boundary at $x=0$. The field was computed numerically for $\beta^2=2$ and $k_{\text{B}}T/e\lambda E_{\text{e}}=0.01$. All quantities are made dimensionless using the scales of equation (\ref{eq:E2_scales}): the field is scaled by the external field $E_{\text{e}}$, position by the characteristic length $\lambda$, and time by the charge relaxation time $\varepsilon/2e^2\mu n_{\text{eq}}$. The dashed line shows the predictions of equation (\ref{eq:relax}) that $E(x,t)=\exp(-t)$ for $x\gg 1$.}
    \label{fig:noFlux}
\end{figure}

We next consider a no-flux boundary at $x=0$ in contact with our model electrolyte on the domain $x>0$.  At the boundary, we specify the electric field $E_{\text{e}}$, which drives the accumulation of charge within the diffusive boundary layer. For strong fields ($E_{\text{e}} \gg k_{\text{B}} T/e\lambda$), we can approximate this boundary layer by a region of vanishing thickness containing charge $q(t)$ per unit area
\begin{equation}
    E(0,t) = E_{\text{e}} + \frac{q(t)}{\varepsilon}
\end{equation}
The surface charge density evolves in time due to migration of ions as
\begin{equation}
    \frac{dq}{d t} = -e^2 \mu n_{\text{s}}(0,t) E(0,t) = -\frac{e^2 \mu n_{\text{s}}}{\varepsilon} (\varepsilon E_{\text{e}} + q)
\end{equation}
For a field in the positive $x$-direction ($E_{e}>0$), we require that the concentration of positive ions vanish at the boundary as described by equation (\ref{eq:1D_bc1}). Far from the boundary, the ion concentrations approach their bulk values
\begin{equation}
    n_{\text{d}}(\infty,t) = 0 \quad \text{and} \quad n_{\text{s}}(\infty,t) = 2 n_{\text{eq}}
\end{equation}
Subject to these boundary conditions, equation (\ref{eq:1D}) describes the spatiotemporal evolution of the ion concentrations $n_{\pm}(x,t)$ and the electric field $E(x,t)$.

At steady-state, the applied field $E_{\text{e}}$ is fully screened by the charge accumulated at the boundary.  As a result, the ion concentrations and the field approach their initial values at long times
\begin{equation}
    q(\infty)=-\varepsilon E_{\text{e}}, \quad n_{\text{d}}(x,\infty) = 0, \quad n_{\text{s}}(x,\infty)=2n_{\text{eq}}, \quad E(x,\infty) =0
\end{equation}
Small perturbations about this asymptotic solution decay as
\begin{equation}
    \frac{\partial n'_{\text{d}}}{\partial t} = - \frac{2 e^2 \mu n_{\text{eq}}}{\varepsilon} n'_{\text{d}},
    \quad
    \frac{\partial n'_{\text{s}}}{\partial t} = - 2 k_{\r} n_{\text{eq}}  n'_{\text{s}},
    \quad
    \frac{\partial q'}{\partial t} = - \frac{2 e^2 \mu n_{\text{eq}}}{\varepsilon} q
\end{equation}
where $n'_{\text{d}}=n_{\text{d}}$, $n_{\text{s}}'=n_{\text{s}}-2n_{\text{eq}}$, and $q'=q+\varepsilon E_{\text{e}}$.  The rate $2k_{\r}n_{\text{eq}}$ describes the characteristic rate of ion generation and recombination; the rate $2 e^2 \mu n_{\text{eq}}/ \varepsilon$ is the charge relaxation rate of the electrolyte.  The ratio of these rates is the dimensionless parameter $\beta^2$ introduced above.

Figure \ref{fig:noFlux} shows the numerical solution for the case of diffusion-limited ion association with $\beta=2$. The field-induced boundary layer grows to a characteristic thickness $\lambda$ during a characteristic time $\lambda/e \mu E_{\text{e}}$. Meanwhile, the bulk field outside of the boundary layer decays exponentially as
\begin{equation}
    E(x,t) = E_{\text{e}} \exp\left(-\frac{2e^2 \mu n_{\text{eq}} }{\varepsilon}t\right) \quad \text{for} \quad x\gg \lambda \label{eq:relax}
\end{equation}
Note that this result applies only when the electrolyte domain is thicker than the boundary layer thickness $\lambda$ for ion recombination.

\subsection{Finite Electrolyte between No-Flux and Absorbing Boundaries}

Finally, we consider our model electrolyte confined between an no-flux boundary at $x=0$ and an absorbing boundary at $x=L$ (Figure \ref{fig:Absorb_NoFlux}). This configuration is similar to the gap separating a solid particle (no-flux) from the electrode surface (absorbing).  When the gap is small relative to the recombination length ($L\ll \lambda$), the rate of charge accumulation on the no-flux boundary is limited by the finite rate of ion generation within the electrolyte. Following a short time during which the initial charge carriers are removed ($\Delta t \sim L/e\mu E_{\text{e}}$), the charge on the no-flux boundary increases linearly with time as
\begin{equation}
    q(t) = e k_{\r} n_{\text{eq}}^2 L  t \label{eq:charge}
\end{equation}
resulting in the gradual attenuation of the applied field. This charging process continues for a duration $\Delta t \sim \varepsilon E_{\text{e}} / e k_{\r} n_{\text{eq}}^2 L$, at which point the applied field is fulled screened.  Importantly, the charging time for the confined electrolyte is much slower than that of the unbounded electrolyte, which is equal to the charge relaxation time $\varepsilon / 2e^2\mu n_{\text{eq}}$.  The ratio between these times is $4\lambda / \beta L \gg 1$  (or, equivalently, $2\ell / L \gg 1$).

\begin{figure}[b!]
    \centering
    \includegraphics[height=6cm]{Figure/S13_Absorb_NoFlux.pdf}
    \caption{\textbf{Absorbing and No-Flux Boundaries.} Transient electric field $E(x,t)$ for an electrolyte confined between a no-flux boundary at $x=0$ and an absorbing boundary at $x=0.1$. The field was computed numerically for $\beta^2=2$ and $k_{\text{B}}T/e\lambda E_{\text{e}}=0.01$. All quantities are made dimensionless using the scales of equation (\ref{eq:E2_scales}): the field is scaled by the external field $E_{\text{e}}$, position by the characteristic length $\lambda$, and time by the charge relaxation time $\varepsilon/2e^2\mu n_{\text{eq}}$. The dashed lines show that the field decreases at a constant rate $\beta L/4$ as predicted by equation (\ref{eq:charge}).}
    \label{fig:Absorb_NoFlux}
\end{figure}

\clearpage
\section{Leaky Dielectric Model}

We consider a solid dielectric sphere of radius $a$ immersed in a model electrolyte (Section \ref{sec:model_electrolyte}) at a distance $\delta$ from a plane electrode. The application of an external field $\ve{E}_{\text{e}}$ normal to the electrode drives the migration of charge carriers, which accumulate at the particle-fluid interface. For strong fields $E_{\text{e}} e \lambda/ k_{B} T\gg 1$ and large particles $a/\lambda\gg 1$, the majority of this charge is confined within a thin region of thickness $k_{\text{B}} T/e E_{\text{e}}$ at the particle surface (see Fig.\ \ref{fig:noFlux}). This charged region is assumed to lie within the idealized surface of shear that separates the rigid particle from its fluid surroundings; consequently, the charge moves in lock-step with the particle as it rotates. Following Melcher \& Taylor,\autocite{Melcher1969,Saville1997} we neglect any free charge remaining outside of the shear plane---for example, that in the boundary layer of thickness $\lambda$.  In doing so, we neglect also any electrokinetic flows that might originate from the action of the electric field on this charge.

With these simplifications, the electric field $\ve{E}_{\text{f}}$, fluid velocity $\ve{u}$, and pressure $p$ within the fluid are governed by
\begin{align}
    \nabla\cdot(\varepsilon_{\text{f}} \ve{E}_{\text{f}}) &= 0 \label{eq:leaky_Ef}
    \\
    -\nabla p + \eta \nabla^2 \ve{u} &=0
    \\
    \nabla \cdot \ve{u} &= 0
\end{align}
Note that we have omitted inertial contributions to the Navier-Stokes equations owing to the small Reynolds numbers characterizing particle motion. The dielectric particle moves as a rigid body with angular velocity $\ve{\Omega}$; the electric field within the particle is governed by
\begin{equation}
    \nabla\cdot(\varepsilon_{\text{p}} \ve{E}_{\text{p}}) = 0 \label{eq:leaky_Ep}
\end{equation}

At the interface between the particle and the fluid (denoted $r=a$), the electric potential is continuous while the normal component of electric displacement changes discontinuously by an amount equal to the surface charge density $q$
\begin{equation}
    \begin{drcases}
    \phi_{\text{p}} = \phi_{\text{f}} \label{eq:leaky_bc_phi}
    \\
    \ve{n}\cdot (\varepsilon_{\text{p}} \ve{E}_{\text{p}} - \varepsilon_{\text{f}} \ve{E}_{\text{f}}) = q
    \end{drcases}  \quad \text{for } r = a
\end{equation}
where $\ve{n}$ is the unit normal vector directed into the fluid. The surface charge evolves in time due both to the rotation of the sphere and to the flow of charge from the surrounding fluid
\begin{equation}
    \frac{\partial q}{\partial t} + \nabla_{\text{s}}\cdot (q \ve{u}) + \ve{n}\cdot \ve{j}_{\text{e}} = 0 \quad \text{for } r = a
\end{equation}
where $\ve{j}_{\text{e}} = \sigma_{\text{f}} \ve{E}_{\text{f}}$ is the electric current in the fluid, $\ve{u}=\ve{\Omega}\times a \ve{n}$ is the velocity of the sphere surface, and $\nabla_{\text{s}}$ is the surface divergence. Here, the conductivity of the dielectric particle is assumed to be zero. At the electrode surface (denoted $\mathcal{S}_{\text{e}}$), the electric potential $\ve{\phi}$ is zero as is the fluid velocity
\begin{equation}
    \begin{drcases}
    \phi_{\text{f}} = 0
    \\
    \ve{u} = 0
    \end{drcases}  \quad \text{for } \ve{r}\in \mathcal{S}_{\text{e}}
\end{equation}
Far from the sphere, the field approaches a constant value and the fluid velocity approaches zero
\begin{equation}
    \begin{drcases}
    \ve{E}_{\text{f}} = \ve{E}_{\text{e}}
    \\
    \ve{u} = 0
    \end{drcases}  \quad \text{for } r\rightarrow \infty \label{eq:leaky_bc_infty}
\end{equation}

Rather than solve the Stokes equation directly for the fluid velocity, we use the resistance matrix formulation\autocite{Kim2005} to relate the angular velocity of the sphere to the electric torque as
\begin{equation}
    \ve{R} \cdot \ve{\Omega} = \ve{L}_{\text{e}}
\end{equation}
where $\ve{R}$ is the resistance matrix for a sphere rotating above a solid plane.\autocite{Goldman1967} The relevant components have the form $R_{xx}=R_{yy}=8\pi\eta a^3 f(\delta/a)$ where $f(\delta/a)$ is a dimensionless coefficient that depends on the surface separation $\delta$ scaled by the particle radius. The electric torque on the particle is given by
\begin{equation}
    \ve{L}_{\text{e}}= \oint \ve{r} \times (\ve{n}\cdot \ve{\Sigma}_{\text{e}})~dS
\end{equation}
where the integral is taken over a spherical surface enclosing the particle and its surface charge $q$. Here, the electric stress tensor within the fluid is defined as $\ve{\Sigma}_{\text{e}}=\varepsilon_{\text{f}} \ve E_{\text{f}} \ve E_{\text{f}} - \tfrac{1}{2}\varepsilon_{\text{f}} (\ve E_{\text{f}} \cdot \ve E_{\text{f}}) \ve I$.

In previous works,\autocite{Das2013, Hu2018} the governing equations (\ref{eq:leaky_Ef})--(\ref{eq:leaky_Ep}) together with boundary conditions (\ref{eq:leaky_bc_phi})--(\ref{eq:leaky_bc_infty}) have been solved using multipole expansion approaches, which generally truncate at the dipole moment level. In our case, the particle is close to a planar electrode, and the effects of higher order moments must be taken into account. We therefore solve the governing equations self-consistently with the finite element method.

All numeric simulations are performed using the commercial finite-element software COMSOL. The Poisson equation is solved by the electrostatic module of COMSOL; the surface charge conservation equation is implemented as a user-defined partial differential equation via the boundary PDE module of COMSOL. Since the surface charge conservation equation is a partial differential equation defined on a 2D surface, the surface divergence operator $\nabla_s \cdot$ needs to be the covariant divergence, which depends on the metrics of the surface. For the convenience of numeric implementation, the surface charge conservation equation of a spherical surface can be expressed in the Cartesian coordinate as:
\begin{equation}
    \frac{\partial q}{\partial t}+\ve n \cdot (\sigma_{\text{f}}\ve E_{\text{f}}) + \ve u \cdot \nabla q=0
\end{equation}

\clearpage
\section{Oscillations of Cylindrical Particles}
\vspace{1cm}

\begin{figure}[h]
   \centering
    \includegraphics{Figure/S14_other_shape.pdf}
    \caption{Phase diagram showing the observed dynamics for cylindrical particles of different aspect ratios as a function of the external field strength $E_{\text{e}}$. Plotted markers denote the three observed behaviors: stationary, rolling, and oscillating. The illustrations on the left show the dimensions of the cylindrical particles, which were fabricated from SU-8 photoresist by photolithography. Cylinders with 1:1 aspect ratio rotate about their axis of symmetry; the other cylinders (1:2 and 1:4 aspect ratios) rotate about an axis normal to their symmetry axis.}
    \label{fig:othershape}
\end{figure}

\clearpage
\printbibliography
\end{document}

redpajama_set_name: RedPajamaArXiv


text:
Shellfish Permit Database
Byelaws
Beachy Head East MCZ
Beachy Head East is a Marine Conservation Zone (MCZ) designated on the 31st May 2019. The site contains two marine Sites of Nature Conservation Importance (mSNCIs); the Royal Sovereign Shoals and the Horse of Willingdon Reef. Two protected wrecks are also incorporated in the site; Norman's Bay and the Amsterdam.
The site is a large, inshore area approximately 193km². It is located east of Beachy Head and runs to Hastings, stretching out to just beyond six nautical miles from the coast at its furthest point.
Now the site has been designated, Sussex IFCA can start discussions with stakeholders regarding management measures. It is likely that it will take about two years for management to come into force, after designation, and we will endeavour to ensure that all interested parties are consulted during the development of the management. Stakeholders' views are always considered during management development. We also take into account advice from Natural England and other organisations, as well as scientific evidence.
Designated features
The area is characterised by the Royal Sovereign Shoals, an area of highly biodiverse sandstone and chalk, with areas of mixed sediments, sandy sediments and biogenic reef structures. Important subtidal chalk ledges, peat and clay exposures are also present. A diverse mixture of marine species are found at Beachy Head East, including sponges, anemones, sea squirts, erect bryozoans, encrustations of ross coral and starfish.
Rocky ridges at the Pound, near Eastbourne run roughly in line with the cliffs creating pools and lagoons at low tide. These are full of seaweed and other marine species.
Some of the best blue mussel beds in the region are contained within the site. The diverse habitats provide important feeding grounds for many fish species, including short-snouted seahorses, black seabream, native oysters and European eel. It is believed that herring spawn on the gravel beds in the early spring.
To see more information on the habitats and video clips of seabed surveys click here for our interactive map.
Links to further information
DEFRA MCZ pages
The Wildlife Trusts Beachy Head East Marine Conservation Zone page
Marine Conservation Society Beachy Head East (Royal Sovereign Shoals) MCZ page
Site MapContact
© Copyright 2022 Sussex IFCAWeb Design By Toolkit Websites


times and 1.2 times (respectively) more active cellphones than people.
All these numbers add up to a challenge for those in the Test and Measurement field. With companies pushing to put more and more new products that are faster, more rugged, smaller, bigger, cheaper, or more efficient in the market, engineers are struggling with making sure the products are ready to hit the shelves. With each surge towards a better phone or tablet comes a push for shorter time-to-market, which means that time has to come out of the manufacturing and design process.
Oftentimes, the test and measurement phases are being cut short to accommodate the condensed timeline. For our cover story, we focused on intrinsic semiconductor reliability testing with an article called iFail: Predicting end-of-life for future mobile devices (page 14). Speaking of iFail, products that do fail can have a huge effect on reputation, revenue, and, obviously, on how the product works. The focus on Reducing system failure costs (page 16) is highlighted in an article by Taqi Mohiuddin, senior director of marketing for the Evans Analytical Group (EAG).
We're also featuring a new writer in our On Design department.
application behind hot topics and old favorites in the design world.
As always, we've worked to put together some great new content along with your old favorites. Don't forget to check out our Everything E department (page 12) and see what we've been working on at www. ecnmag.com.
This issue marks a renewal of my relationship with the ECN readers. Between 2002 and 2007, I penned several editorials, produced online technical-confer-ence sessions, and served on the magazine's editorial board.
As a contributing columnist, my focus tends toward the application-centric. As fascinating as products and technologies can be in their own right, absent an application, discussions about them lack context. The constraints that applications, their operating environments, and their markets force onto designs often inform implementation decisions as much as do available components, technologies, and their various attributes.
I hope you enjoy this month's column. Feedback is welcome at ECNjoshua@jas-technicalmedia.com.


The Gainesville Times in Gainesville, Ga., reports on hometown triplets, Jaclyn, Jessica and Jocelyn Kerr, recent graduates of Belmont University.
The Kerrs, who have no other children, moved to their Pine Vale Road home about one year ago from Kentucky, where the daughters lived when they decided to attend Belmont, all on scholarships. At the time, the triplets also entertained scholarship offers from Tennessee Tech and Western Kentucky University. "Belmont was their fantasy place to go, so when the doors opened up for all of them to go there, that's the place they chose," Kerr said.
The siblings' strikingly similar lives don't end there. All three competed on the high school swim team, with each sibling cultivating a favorite stroke. They were members of the Belmont Bruins Dance Team. They received Dean's List recognition all eight semesters and are members of Sigma Beta Delta, Alpha Chi and Beta Gamma Sigma honor societies. Also, each received the Massey School of Business Outstanding Student of the Year award for 2003.


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Adelaide 500 tickets 2018
How to see Cardi B, Offset and more during Super Bowl weekend
Arizona will be hoppin' over Super Bowl weekend with parties and shows from top artists. The Super Bowl kicks off in Glendale — a suburb of metro Phoenix — on Feb. 12, bringing a swarm of visitors to the Valley of the Sun for the Big Game. Halftime headliner Rihanna isn't the only celebrity who will take the stage; you can also catch performances from Cardi B, Diplo, Snoop Dogg and so many more at Super Bowl parties around the region. If you're looking to imbibe in a chic atmosphere, consider heading to Second Story Liquor Bar in Old Town Scottsdale, where you'll find plush booths, chairs and chandeliers as well as a cocktail program that is one of the best in town. The bar's location makes it easy to hop from party to party. ESPN will host a Main Street Tailgate in the area Feb. 8-12 with pregame coverage; "NFL Live" and "Sunday NFL Countdown" will broadcast live. Here's how to get tickets for Super Bowl parties and performances: Cardi B and Offset Cardi B and … [Read more...] about How to see Cardi B, Offset and more during Super Bowl weekend
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California's winter storms have been deadlier than any wildfire since 2018
This is a carousel. Use Next and Previous buttons to navigate 3 Relentless wind and rain has killed people sleeping in homes and in tents. It has taken the lives of those sheltering indoors and those working outside. Some victims have been elderly, others very young. And they are spread across 10 California counties and more than 500 miles, one measure of this disaster's massive, difficult-to-manage scope. After two weeks of nearly nonstop downpours, the official statewide death toll from multiple atmospheric rivers stands at 19. That figure will rise, authorities say, but already it is greater than the number of people killed during the last two fire seasons combined. The parade of storms has been deadlier than any single wildfire since 2018, a jolting fact for a state whose worst recent disasters have been the product of too little water, not too much. And it's not over. At least two more storms have California in their crosshairs. Once the … [Read more...] about California's winter storms have been deadlier than any wildfire since 2018
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Two-time Indy 500 winner Sato joins Ganassi for oval races · RaceFans
Two-times Indianapolis 500 winner Takuma Sato has moved to Chip Ganassi Racing for 2023, downscaling his IndyCar presence to an oval-only programme. Advert | Become a Supporter & go ad-free Former Jordan, British American Racing and Super Aguri Formula 1 driver Sato has been racing full-time in IndyCar since 2010, and Ganassi will be his sixth different team in the series. He will drive the number number 11 car at five rounds, including the Indy 500, while Formula 2 graduate Marcus Armstrong will pilot the car at the 12 road and street circuit races. "First of all, I would like to thank Chip and Mike [Hull, managing director] for helping put this all together," said Sato. The Ganassi organisation "has been at the top of our sport for decades and needless to say, extremely competitive," Sato continued. "Focusing on the oval races is a new chapter for me but I'm thrilled to have the ability to race with team members and team mates that have won the championships … [Read more...] about Two-time Indy 500 winner Sato joins Ganassi for oval races · RaceFans
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2018 IndyCar will require a tire rethink on some tracks
September 24, 2017 by www.motorsport.com Leave a Comment
Listen to this article From 2015-'17 the heavy downforce levels of the manufacturer aerokits have demanded a harder tire, as Honda's 2018 car tester Oriol Servia highlighted earlier this week . With next year's universal aerokit introducing reduced downforce overall and a more forward weight distribution, Adams says there will be changes necessary on some (but not all) tracks on the IndyCar schedule. "There is a lot of crossover between what we've been using this year and what we'll use next year," Adams told Motorsport.com. "The feedback from Juan Pablo Montoya and Oriol Servia during the 2018 aerokit tests suggests that as far as they've been pushed so far, the current tire specs seem to react well on the new car. "At Indianapolis Motor Speedway, the cars were very good on this year's tires, but we'll still make small changes in reaction to the weight distribution changes. With more forward weight, you see more of a load on the right front and less on the right rear … [Read more...] about 2018 IndyCar will require a tire rethink on some tracks
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Isle of Man TT makes changes after 2018 course car collision
April 20, 2019 by www.motorsport.com Leave a Comment
Listen to this article English rider Steve Mercer suffered serious injuries when he was struck by a course car on its way to the incident which claimed the life of Tyco BMW rider Dan Kneen during practice for TT 2018. In immediate reaction to the incident, the ACU implemented a new red flag procedure , whereby all riders would only return to the paddock in the event of a stoppage under guidance from the travelling marshals. Following multiple operations, Mercer is still undergoing treatment for limb and spinal injuries, and admitted in a recent interview with the Isle of Man Examiner newspaper that there is still a possibility he could lose a leg. An inquiry into the incident, specifically looking at why riders were instructed to ride the wrong on the 37.73-mile course to return to the paddock, was carried out last year by former MSA head Rob Jones. The findings of the inquiry have not been made public, with Mercer revealing he has also been denied access to the … [Read more...] about Isle of Man TT makes changes after 2018 course car collision
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2018 United States Grand Prix TV Times · RaceFans
October 15, 2018 by www.racefans.net Leave a Comment
Join us on RaceFans Live throughout every session of the United States Grand Prix weekend. Look out for the live page on the site during every session and follow all the action with your fellow RaceFans. 2018 United States Grand Prix local session times Friday 19th October 2018 Free Practice 1: 10:00-11:30 Saturday 20th October 2018 Free Practice 3: 13:00-14:00 Sunday 21st October 2018 United States Grand Prix: 13:10 2018 United States Grand Prix TV Times Here are the details of Sky and Channel 4's coverage of the 2018 United States Grand Prix in the UK: Friday 19th – Saturday 21st October 2018 Day Session Channel Coverage starts Session starts Session ends Friday United States Grand Prix first practice live More 4 15:55 16:00 17:30 Friday United States Grand Prix first practice live Sky Sports F1 15:45 16:00 17:30 Friday United States Grand Prix second practice live More 4 19:55 20:00 21:30 … [Read more...] about 2018 United States Grand Prix TV Times · RaceFans
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Miami Grand Prix increases grandstand capacity as ticket demand rises further
The Miami Grand Prix has added a further 3,000 seats to their capacity as Formula 1 demand in the US reaches an all-time high. The 2023 season will be a landmark year for the United States and Formula 1 with three races set to be hosted in the country, only the third time that has happened in the sport's history. Las Vegas has been given a November slot while COTA will take place in its usual spot of October meaning the Miami Grand Prix will kick proceedings off in May. The event is in its second year after Max Verstappen won the inaugural race in 2022 and more fans will be able to see the 2023 race with the organisers adding 3,000 more seats to the grandstand. The addition raises the capacity of the grandstand located at the start/finish line to 56,000 with tickets for a three-day package in the stand costing $2,379. The organisers say there has been "high demand" for tickets and have also introduced a 'Campus Pass' which allows general admission fans access to areas such … [Read more...] about Miami Grand Prix increases grandstand capacity as ticket demand rises further
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Triple Crown "still a target" for Alonso after Indy 500 blow · RaceFans
May 20, 2019 by www.racefans.net Leave a Comment
Fernando Alonso says winning the 'Triple Crown' remains his target following his failure to qualify for this year's Indianapolis 500. Advert | Become a Supporter & go ad-free Yesterday Alonso missed out on a place in the 33-car field for Sunday's race by less than 0.02mph over a four-lap run . Alonso, who has already won the Monaco Grand Prix and the Le Mans 24 Hours, would become the second driver after Graham Hill to sweep all three races if he takes a victory at Indianapolis. Following yesterday's setback, the earliest that could now happen is next year. Alonso says he won't begin considering his options until after his return to Le Mans next month. "Right now I think it's difficult to make any promise," said Alonso on Sunday evening at Indianapolis. "It's just too soon to make decisions. "I don't know even what I will do after next month's Le Mans 24 hours, [finishing] my program in the world endurance championship. I wanted to have the 2020 open … [Read more...] about Triple Crown "still a target" for Alonso after Indy 500 blow · RaceFans
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Forza Motorsport Will Launch With Over 500 Cars And 20 Tracks
January 25, 2023 by www.motor1.com Leave a Comment
We have good news and bad news from the world of sim racing regarding the latest Forza Motorsport title for Xbox Series X/S and PC. In a video announcement, Turn 10 Studios shared all kinds of details for the forthcoming game but a confirmed launch date wasn't among them. That's the bad news. As for the good news, well, that's pretty much everything else . That obviously calls for more explanation, but it's not something handled in a sentence or two so let's start with content. Forza Motorsport will launch with over 500 cars, including more new race cars than any previous title in the franchise. Over 100 cars are completely new to the game, and there are 800 unique upgrades available for customization. These cars will race in 20 locations, five of which are brand new. The first Forza Motorsport teaser from June 2022 revealed two: Hakone in Japan and Kyalami in South Africa. However, our keen Motor1.com eyes may have glimpsed Mid-Ohio in the recent video, though it's not … [Read more...] about Forza Motorsport Will Launch With Over 500 Cars And 20 Tracks
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Fresh Podcast Alert – Adventures by Disney trip recap with Shannon & Troy – Part 2 – Welcome to WDW & Beyond!
Hello and welcome to Episode #65 of WDW & Beyond. In this week's episode Shannon & Troy tell us about the rest of their Adventures by Disney trip to Germany.
Shannon & Troy pick up where Show #60 left off and continue to tell us about their experience and all of the fun and interesting things that happen when you go on an Adventures by Disney trip.
Thank you for listening and please visit us at WDWNBeyond.com or on our Facebook page at WDW & Beyond podcast.
Next Article Tune In To Some Fresh Disney News!
Hiya pals! My name is Paul and I'm one of the Web Administrators here at WDW & Beyond. The team and I are thrilled to provide you the very best of everything Disney and beyond. If you have any questions or comments email us at [email protected] We're here to help!


At Tribe of Lambs we do everything with a purpose and the way we make our jewelry is no exception. We hand-pick every stone, crystal, and metal to make gorgeous pieces that tell a story. Working hand-in-hand with artists and distributors allows us to make our jewelry truly unique.
Our materials are all chosen specifically by us and have some pretty exciting benefits besides being beautiful! Here are some of the stones and crystals in our jewelry that we currently have on our site, and what they can do for you.
Black Onyx: A stone of protection that can increase strength, stamina, and self-control.
Rose Quartz: The crystal of love… Promotes compassion, peace, and comfort and can encourage physical and emotional healing.
Red Garnet: This stunning red stone can boost your energy and vitality and is said to be excellent for manifestation.
Chalcedony: Brings the mind, body, and spirit into harmony. Eases self doubt and creates openness and enthusiasm.
Moss Agate: The miraculous healing stone! A strengthening, stabilizing stone of abundance and wealth.
Lapis Lazuli: Brilliantly blue and brilliant for you! This stone is symbolic of honour, power, and wisdom. It is also said to be quite effective for enhancing memory.
Labradorite: A powerful protector against negativity. Brings out the best in people and helps to provide clarity and insight.
Moonstone: The calming stone of intuition and hope.
Coming soon: Amethyst, Tigers Eye, Rutilated Quartz, Sodalite, Kyanite, Druzy, and Citrine.
Why 925 Silver? 925 Sterling Silver is the brightest of all the precious metals. It is extremely durable and can easily be polished back to its natural sparkle – my favorite way to clean silver is simply with a bit of dish soap. In addition, Sterling Silver also has some great health benefits! Since it's a 100% non-reactive metal it can safely be worn on the body – even on people with sensitive skin. Sterling Silver is also believed to increase energy flow in the body.
We are currently in India developing our 2017 Collection & look forward to sharing it with you soon!


This lovely chenin blanc offers floral and festive with attractive aromas of white peach. A terrific very early spring This A.C. Vouvray features lemon zest, mango and some lovely, luxurious candle wax notes (the latter, more texture than flavour). Very viscous, voluptuous and mouth-filling. Bring it!
Vouvray food pairings: honey-glazed pork, mango chicken, Coquilles St. Jacques.


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Galaxy Note 10 fast charge speed could be higher than 25W
There's only one model of the Galaxy S10 that features Samsung's new 'super fast charging' and you won't find it in most markets. The Galaxy S10 5G supports 25W fast charging compared to the 15W fast charging on the company's recent devices. However, there's one non-flagship with super fast charging and it's the Galaxy A70.
So would you put your money on 25W fast charging for the Galaxy Note 10? We've already confirmed that it's going to have a 5G model so the assumption would be that it also gets super fast charging. If you believe recent reports, the Galaxy Note 10 fast charge speed could be even higher than 25W.
Galaxy Note 10 fast charge speed may hit 50W
We have already discussed just how quick is Samsung's 25W super fast charging in detail. There were some noticeable advantages of super fast charging on the Galaxy A70 that we ran our tests on. If there's going to be another Samsung device this year to get support for super fast charging, you can bet it will be the Galaxy Note 10.
Noted tech leakster Ice Universe predicts that the Galaxy Note 10 fast charge speed could be more than 25W. No specific figure has been provided, though, but he mentions that the battery capacity and charging speed won't be a weak point for the device. Gordon Kelly over at Forbes hears something similar from a trusted source. He was told that the figure will likely be higher and not lower than 25W. Fans can expect to be "pleasantly surprised and not disappointed" when the charging specs are made public.
There is some speculation about the Galaxy Note 10 having support for 50W super fast charging. That might sound like hogwash to some people but it won't exactly be new territory for the market. Oppo's SuperVOOC charging technology already delivers a maximum charging power that's close to 50W. It claims that this can fully charge a smartphone in 35 minutes (in controlled lab conditions).
Expect to hear more about the Galaxy Note 10's battery capacity and charging speed in the coming weeks. These upgrades may prove to be crucial in getting more people to purchase Samsung's upcoming flagship.
Galaxy Note 10 super fast charging
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"hears something similar from a trusted source."
What about your exclusive sources ?
From Ice universe
"no longer be Samsung's weaknesses, or even advantages."
What this mean ? It should be advantage.
I don't think higher than 25 watt charging would sway me either way. I will get the Note10 anyway. It is not necessary and it's very bad for long term battery health. Even if it is higher, I charge it in the evening anyway and will keep to standard 15w charging. I only keep my phone one year anyway, but when I sell it before upgrading I like to give the next user a healthy battery that's going to last a couple of years for them.
Well, it is kinda odd they didn't do this before. Now they have big batteries on their flagships so it's not as necessary to have faster charging as it was before since they last longer now. Kind of a chicken and egg thing I guess, although I still want faster charging for the first half an hour because I don't get anywhere near the crazy screen times in India as you guys. 😛 And anyway, I think even the faster ones switch to regular charging speeds as the charge climbs higher, so it's not really that much of an effect… Read more »
That's true Abhijeet to some extent as battery tech is improving but not by much. In my early career days I was involved in lithium battery manufacturing for Motorola phones, and we did quality studies on charging speeds. Even that 30 minutes super charge does have some affect. I would always say to people particularly those who keep their expensive device for a number of years to use standard charging as much as possible. I'm just a nice guy who wants to give a good battery to the next owner! 😇😆
Yeah, can't say anything on that front as someone who works with phones and isn't holding on to phones for more than a year or so. Also, does not fast charging it also result in slightly longer battery life compared to what we get with fast charging? I used to feel that's the case when I had disabled fast charging 2-3 years back, but don't disable it anymore.
siaho
Slower charging can get "denser charge" in the cells = longer battery life, true. Also worth noting that all phones show 100% a lot earlier before the battery is really full, it keeps charging around 40-90m after the phone is stating 100% (slowly, but when you really top it out, it makes a difference comparable to few percents more).
The last 20% will always be slower to charge as the charging method is different. Still, the effect of the fast charge is not that small at all if one uses it every day for years. When such effects are analysed one does not look at the battery health after 50 cycles, you should look at 300-500 cycles. Fun fact, normal quality li-ion battery will reach 80% of initial capacity after around 1000 cycles. Smartphones ones does that in like 350-400 cycles. Now go tell me how the charging methods are totally fine and does not affect the battery degradation.… Read more »
As long as they keep using Lithium ion batteries, they're gonna have the same problems. Smartphones have been around for over 10 years now, and I've had a smartphone since the S4, battery life has barely improved – I still can't get through a full day, after 6 months of use. Starts out phenomenal enough. But it degrades so quickly. So, samsung might as well got for the faster charging because it makes no difference in the long run.
If you can't get through a day after only 6 months you should talk to customer service. You obviously have a bad battery. After having every Note ever made I've never had a battery problem. Never even had to swap the replaceable ones…..in those days when we could do that! lol. Even though the battery is not normally covered a failing battery after just 6 months will be investigated.
And to answer you on that one, my Note 4, bought on the same day as the headphones I mentioned above, had in 2.5 years before it finally died a Samsung death (updated to sluggish slowlessness), 5 batteries, original ones from Samsung – that is one every 6.5 months – swapped due to cell death and/or degradation (even swollen batteries had two of them, and you have to fight Samsung for it, as warranty covered only 6 months).
bayfisher
use to have a note 9.
now s10 plus 11 SOT.
A good point though not the case. Faster charging stresses a battery. It will be ok for at least a year but then will suffer.
It does make a huge difference on both, charging and discharging. So basically, the batteries today are killed two fold, charging and discharging. The problem with phones is: they charge too fast, they draw to much current under heavy load (and since OS is not really optimised, even the most menial tasks mean heavy load for your phone) and then additionally they generate a lot of heat near to the lithium cell itself, which also makes the battery to not be very happy about it. To that add the expansion / shrinking under temperature changes of a plastic bag filled… Read more »
we need a solar powered battery soon.
thats innovation.
Vuk995
Why someone at Sammobile doesnt remove galaxy s9 and note9 from shortcuts, and put note 10 instead, leaving s10 and fold? Its about time you collect all rumors and news of note 10 in one section
lfcrodrigues
25W still slower than the competition so they better hurry up
but faster that 3 s10s. all but the S 10 5g.
note will be 3 times faster than the 10s and double the s10 5g.