text:
\section{Introduction}
Phylogenetic software has for a long time been applied in biological research, and biological findings relying on phylogenetic trees are frequent. Moreover, due to the emergence of single-cell sequencing, phylogenetic inference for bifurcating and multifurcating trees can now be utilized in medical studies of how cells differentiate during development and how tumor cells progress in cancer.

When attempting to infer the posterior distribution over phylogenetic trees for $|X|$ taxa, represented as sequences, the main obstacle is the exponential size of the tree space, i.e., the set of candidate trees having those taxa as leaves. In Markov chain Monte Carlo (MCMC) based Bayesian phylogenetic inference, e.g., MrBayes \cite{ronquist2012mrbayes} and RevBayes \cite{hohna2016revbayes}, this tree space is explored by performing local operations on the trees. In order to avoid local operations, Bouchard-C\^{o}t\'{e} et al. \cite{BouchardCote:2012ie} launched Sequential Monte Carlo (SMC) as an alternative methodology for Bayesian phylogenetic inference.

Probabilistic phylogenetic inference is a machine learning problem, and the key to unlocking this crucial application can be expected to be found in the machine learning methodology; in particular,  considering the capacity of the VI methodology, \cite{Wainwright:2007du,blei2017variational}, to deliver impressive performance gains for Bayesian inference, e.g., compared to MCMC. Expectedly, such gains have recently been made within the realm of phylogenetic analysis.

For instance, inference based on the computationally costly CAT model, which allows different equilibrium frequencies across sequence sites, has been made substantially more efficient by the application of VI, \cite{10.1093/molbev/msz020.Dang}.
Also, \cite{10.7717/peerj.8272.Fourment} applied VI to render the analysis of a sequence evolution model more efficient. They consider the efficiency improvements obtained by VI, in particular using the generic STAN software \cite{10.7717/peerj.8272.Fourment}, when analyzing a single fixed tree topology. Interestingly, the VI approach can also be used to analyze a large number of candidate phylogenetic trees. In \cite{zhang2018generalizing},
so-called subsplit Bayesian networks (SBNs) were introduced in order to represent the posterior over a given set of candidate trees. This approach has subsequently been developed further by introducing an edge (a.k.a. branch) length distribution \cite{zhang2018variational} and making the edge length distribution more expressive by taking advantage of normalizing flows \cite{Zhang0if}. In particular, \cite{zhang2018variational} obtains posterior distributions that improve on the marginal likelihood obtained by using MrBayes, \cite{huelsenbeck2001mrbayes}, in combination with the improved Stepping Stone (SS) method, \cite{10.1093/molbev/msq224.Fan}.

The SBN approach evades the exponentially sized tree space by considering a given set of candidate trees and the partitions of the given taxa defined by those candidate trees.
 It is noteworthy that the VI methodology earlier has been successfully applied to bipartite matching and a few other combinatorial problems \cite{BouchardCote:VC8xIIC9}; the phylogeny problem, however, involves both combinatorial and continuous parameters.

 Multifurcating trees are common in biology, and biologists are well familiar with them. For instance, in a clone tree that represents the evolutionary relationships between the subclones of a tumor, nodes may have more than two children. Even in cases with no biological support for multifurcating trees, biologists are used to working with multifurcating trees. E.g., the consensus method used to analyze the posterior of a MrBayes run may produce a multifurcating tree.

\begin{figure*}[!t]
    \centering
    \includegraphics[width=12cm]{figs/JC_sampler_visualization_2_b.png}
    \caption{Visualization of branch lengths, $b$, sampled directly from the Jukes-Cantor model. The figure shows samples for different numbers of estimated mutations along an edge, $\phi_{i,j}$, when the total number of sites are $M=2000$.}
    \label{fig:jc_sampler}
\end{figure*}

{\bf Contributions:}
We present a novel framework for phylogenetic inference that produces marginal likelihood estimates on par with the state-of-the-art VI methods while being up to 25 times faster than VBPI-NF on real datasets. The framework is on the top level a mean-field VI algorithm and is comprised of the following three novel methods:
\begin{itemize}

    \item \textbf{SLANTIS} is a proposal distribution that proposes multifurcating spanning trees.  Sampling from SLANTIS is performed following an approach suggested by \cite{Diaconis} for sampling a perfect matching in bipartite graphs: it is fast, and the sampled tree's compensation weight is easily computed without additional cost of time.
    \item \textbf{The JC sampler} is a novel scheme for sampling branch lengths directly from the Jukes-Cantor (JC69) model \cite{jukes1969evolution}. This is a significant contribution, as no previous sampling scheme is known for this task and the JC model arguably is a commonly used substitution model in phylogenetics.
    \item \textbf{VaiPhy} is a VI algorithm for obtaining posterior approximations over the set of branch lengths, the ancestral sequences, and tree topologies, given the leaf set observations. VaiPhy utilizes SLANTIS and the JC sampler in order to compute the importance weighted evidence lower bound (IWELBO; \cite{Burda}) and its update equations. Compared to existing VI methods in phylogenetics, VaiPhy extends the target distribution by considering an auxiliary variable, the ancestral sequences, and it does not require any input consisting of precomputed trees.
\end{itemize}
We demonstrate the flexibility of our framework by using its learned parameters to parameterize two new proposal distributions for the Combinatorial SMC (CSMC) algorithm. We compare our CSMC method, $\phi$-CSMC, with the other two main SMC based methods, outperforming them in terms of marginal likelihood estimation on real data.

Finally, we contribute to the field of Bayesian phylogenetic inference by benchmarking the most prominent methods in the field on seven popular real datasets.

\section{Background}
In the Bayesian phylogenetic setting, we are interested in the posterior distribution over phylogenies -- pairs of tree topologies and sets of branch lengths -- given observations on the leaves,
\begin{equation}
\label{eq:vanilla model}
    p_{\theta}(\tau, \mathcal{B}|X) = \frac{p_{\theta}(\tau, \mathcal{B}, X)}{p_{\theta}(X)},
\end{equation}
where $\tau$, $\mathcal{B}$, and $X$ denote the tree topology, the set of branch lengths and the observations, respectively. More specifically, $\mathcal{B}$ contains a single branch length per edge, $e$, in the set of edges in $\tau$, i.e., $\mathcal{B}=\{b(e) : e\in E(\tau)\}$. Unfortunately, $p_{\theta}(\tau, \mathcal{B}|X)$ is intractable,  so we need to approximate it using Bayesian inference. Before going into how to approximate this quantity, we first provide some crucial notation.

In phylogenetics, one is often concerned with bifurcating $X$-trees. These trees have labeled leaf nodes, and their internal vertices have either two (root in a rooted tree) or three degrees. Meanwhile, multifurcating trees' internal vertices can have higher degrees. We use $M$, $\Sigma$, and  $N$ to denote the sequence length, the set of nucleotides, and the number of vertices, respectively. Further, we let $|X|$ be the number of given taxa, $V$ and $E$ be the set of vertices and edges, while $(V, E)$ is an acyclic graph.

Let $Z_i^m$ be the probabilistic ancestral sequence of node $i$ at position $m$, and $\theta$ denote the model parameters, such as the branch length prior parameters or the parameter choices in the substitution model. Then, the evolutionary model along an edge, $e = (i,j)$, is $ p_{\theta} (Z_i^m = \alpha| Z_j^m = \beta) = exp( b(e)\; Q_{\alpha \beta} ) $, where $Q$ is the rate matrix, parameterized according to the JC69 model, and $\alpha, \beta \in \Sigma$ are nucleotides. The  likelihood is defined as

$$p_\theta(X|\tau, \mathcal{B})= \sum_{Z\in \Sigma^M }p_\theta(X, Z|\tau, \mathcal{B}),$$
and can be computed effectively using Felsenstein's pruning algorithm \cite{felsenstein1981evolutionary}.

\section{Proposed Framework}
Existing Bayesian phylogenetic approaches often perform inference in a sample space over bifurcating $X$-trees and branch length sets, $\Omega$. In contrast, we propose to work in an augmented sample space, $\mathrm{A}$. Firstly, we work in a tree topology space for multifurcating trees with labeled internal vertices. Secondly, we extend the target distribution in Eq. \eqref{eq:vanilla model} by considering ancestral sequences on the internal vertices as an auxiliary variable, $Z$.

Apart from that, our augmented space offers higher modeling flexibility (clearly, since $\Omega \subset \mathrm{A}$); it enables posterior estimation over $Z$, which further lets us estimate the number of mutations between all vertices in the sample space. This is a key insight that ultimately allows us to devise VaiPhy, a mean-field coordinate ascent VI \cite{hoffman2013stochastic}  algorithm.

\subsection{VaiPhy}

In the augmented space, $\mathrm{A}$, we wish to approximate the posterior distribution
\begin{equation}
    p_\theta(\tau, \mathcal{B}, Z|X) \propto p_\theta(X, Z |\mathcal{B}, \tau)p_\theta(\mathcal{B} |\tau) p_\theta(\tau),
\end{equation}
using a factorized variational distribution

\begin{equation}
\label{eq:factorized q}
     q(\tau, \mathcal{B}, Z|X) =  q( \mathcal{B} |X) q(\tau|X)q(Z|X),
\end{equation}

where $q(Z|X) = \prod_{i\in I(\mathrm{A})}q(Z_i|X)$. Here, $I(\mathrm{A})$ denotes the set of internal vertices in the augmented space. We will use $q(Z|X)$ to compute
$\phi_{ij}\in [0, M]$, the expected number of mutations over the edge $(i, j)$, for all possible edges. Notice that the maximum number of observed mutations between two vertices is the number of sites, $M$.

As is standard in classical VI, we alternatively update the distributions in Eq. \eqref{eq:factorized q} in order to maximize the evidence lower bound (ELBO),
\begin{equation}
    \label{eq:elbo}
    \mathcal{L} = \mathbb{E}_{ q(\tau, \mathcal{B}, Z|X)}\left[ \log \frac{p_\theta(X, Z |\mathcal{B}, \tau)p_\theta(\mathcal{B} |\tau) p_\theta(\tau)}{ q( \mathcal{B} |X) q(\tau|X)q(Z|X)} \right],
\end{equation}
over iterations. Each iteration, we also update $\phi$, following \cite{Friedman:2002bo}
\begin{equation}
\label{eq:phi update}
    \phi_{ij} =
    \sum_{\alpha\neq \beta}F^{\alpha, \beta}_{ij},
\end{equation}
where $F^{\alpha,\beta}_{ij}$ is the estimated number of times a nucleotide mutates from $\alpha$ to $\beta$, defined as
$
    F^{\alpha, \beta}_{ij} = \sum_{m=1}^M q(Z^m_i=\alpha|X^m)q(Z^m_j=\beta|X^m).
$

The update equations for the variational distributions are derived in a mean-field fashion. Starting with $q(Z_i|X)$, we find that
\begin{equation}
    \label{eq:upd z}
    \begin{aligned}
    \log q^*(Z_i|X) &\ensuremath \stackrel{+}{=} \mathbb{E}_{ q( \tau, \mathcal{B}, Z_{\neg i}|X)}\left[
    \log p_\theta(X, Z, \mathcal{B}, \tau)
    \right] \\
    &\ensuremath \stackrel{+}{=} \mathbb{E}_{ q(\tau, \mathcal{B}| X)} \left[ \sum_{Y_j \in Y_{N_\tau(i)}} q(Y_j|X) \log p_\theta(Y_j | Z_i, b(i,j))  \right],
    \end{aligned}
\end{equation}

where  $\ensuremath \stackrel{+}{=}$ denotes equal up to an additive constant, $Y_{N_\tau(i)}$ is the set of sequences of node $i$'s neighbors in $\tau$, and $\neg i$ is the set of latent nodes except node $i$. Continuing with the two other approximations, we have
\begin{equation}
    \label{eq: upd tau}
    \begin{aligned}
    \log q^*(\tau|X) &\ensuremath \stackrel{+}{=} \mathbb{E}_{ q(\mathcal{B}, Z|X)}\left[
    \log p_\theta(X, Z, \mathcal{B}, \tau)
    \right] \\
    &\ensuremath \stackrel{+}{=} \mathbb{E}_{ q(\mathcal{B}|X)}   \left[
    \sum_{{(i,j) \in E(\tau) \atop  Z_i, Z_j}} q(Z_i, Z_j|X) \log p_\theta(Z_i | Z_j, b(i,j))
    \right]
    \end{aligned}
\end{equation}

and

\begin{equation}
    \label{eq: upd B}
    \begin{aligned}
    \log q^*(b(i,j)|X) &\ensuremath \stackrel{+}{=} \mathbb{E}_{ q(\tau, \mathcal{B}_{\neg b(i,j)}, Z|X)}\left[
    \log p_\theta(X, Z, \mathcal{B}, \tau)
    \right]\\
    &\ensuremath \stackrel{+}{=} \mathbb{E}_{ q(\tau|X)} \left[ \sum_{Z_i, Z_j}   q(Z_i, Z_j|X) \log p_\theta(Z_i | Z_j, b(i,j), \tau) \right] + \log p_\theta(b(i,j)).
    \end{aligned}
\end{equation}

The exact computation of the expectations in Eq. \eqref{eq:upd z} and \eqref{eq: upd B} involves summing over all possible trees, which is computationally intractable. Luckily, we can easily approximate the expectation using importance sampling, and our new proposal distribution, $s_\phi(\tau)$, is outlined in the subsequent Sec. \ref{sec:slantis}. We direct the reader to Appendix~\ref{appendix:vaiphy_general} for the derivations of the above variational distributions and the details of the algorithm.

To obtain good starting points for the variational distributions, we initialize $\phi$ with trees obtained using the Neighbor-Joining algorithm \cite{gascuel1997bionj}. The details of the initialization are provided in Appendix~\ref{appendix:nj_init}.
Alg. \ref{alg:vaiphy} is a high-level algorithmic description of VaiPhy. The proof regarding the natural gradient is presented in Appendix~\ref{appendix:ng_proof}.

\begin{algorithm}[H]
\caption{VaiPhy in pseudocode -- $\iota$ is the total number of iterations and $\eta$ is the natural gradient step size}
\label{alg:vaiphy}
\begin{algorithmic}[1]
\STATE {\bfseries Input:} $X, \phi, \eta, \iota$

   \FOR{$\text{iter}=1,\ldots,\iota$}
   \STATE Approximate $\log q^*(Z|X)$ using $s_\phi(\tau)$ \COMMENT{Eq. \eqref{eq:upd z}}
   \STATE $q(Z_i)\leftarrow  (1-\eta)q(Z_i) + \eta q^*(Z_i)$
   \STATE $\phi_{ij}\leftarrow \sum_{\alpha\neq\beta}F^{\alpha,\beta}_{ij}$ \;\;  \COMMENT{Eq. \eqref{eq:phi update}}
   \STATE $ q(\tau|X) \leftarrow q^*(\tau|X)$ \;\COMMENT{Eq. \eqref{eq: upd tau}}
   \STATE $ q(\mathcal{B}|X) \leftarrow q^*(\mathcal{B}|X)$ using $s_\phi(\tau)$ \COMMENT{Eq. \eqref{eq: upd B}}
   \ENDFOR
   \STATE \textbf{return} $ q(\tau, \mathcal{B}, Z|X)$, $\phi$
\end{algorithmic}
\end{algorithm}

\subsection{SLANTIS}
\label{sec:slantis}
We propose the method Sequential Look-Ahead Non-local Tree Importance Sampling (SLANTIS), which enables sampling of a tree, $\tau$, from a distribution, $s_\phi(\tau)$. SLANTIS has support over multifurcating trees with labeled internal vertices and is parameterized by $\phi$. To describe the algorithm, we next introduce some notation.

Using $\phi$, SLANTIS immediately constructs $W$, an $N\times N$ matrix describing all pairwise edge weights based on the substitution model,
\begin{equation}
\label{eq:weight matrix}
    W_{ij} = \sum_{\alpha, \beta:\alpha\neq\beta} \phi_{ij} \; (b(i, j) \; Q_{\alpha\beta}) + \sum_{\alpha, \beta:\alpha=\beta} (M - \phi_{ij}) \; (b(i, j) \; Q_{\alpha\beta}),
\end{equation}
where $Q$ is the rate matrix of the JC69 model and $\alpha$ and $\beta$ are nucleotides.
Moreover, let $\mathcal{G}$ be a graph with vertex set $\{N\}$ with edge weights specified by $W$. Let $\mathcal{G_I} = \mathcal{G} \text{\textbackslash} \Lambda$, where $\Lambda$ is the $(V,E)$ of the leaves, i.e., the graph induced by the internal vertices of our trees. The pseudocode of the algorithm is presented in Appendix \ref{appendix:slantis}. The main idea, which  is borrowed from \cite{Diaconis}, is to order the edges of the graph and for each edge in the order, make a choice whether to include it in the sampled tree or not. The choice is made based on a Bernoulli trial, where the two probabilities are proportional to the weight of the maximum spanning tree (MST) containing the  already selected edges and the currently considered edge and that of the MST containing the  already selected edges but not the currently considered edge.\footnote{In \cite{Diaconis}, the candidate edges are selected from those that will make a \textit{perfect matching}, and the probability of each edge is uniform.} The action associated with the former outcome is to include the edge in the sampled tree, and the other outcome is not to include it.

To facilitate fast computation of the required MSTs, we first consider the edges of an MST $T_1$ of $\mathcal{G}$.
After the edges of $T_1$, the edges of an MST $T_2$ of $\mathcal{G}\setminus  T_1$ can be found. In general, $T_s$ is an MST of $\mathcal{G}\setminus \cup_{r=1}^{s-1} T_r$, and  after the edges of $\cup_{r=1}^{s-1} T_r$, the edges of $T_s$ can be found. In the algorithm, we repeatedly take advantage of the property that for any tree $T$ and edge $e$ not in $T$,  $T\cup e$ contains a unique cycle, and the removal of its heaviest edge different from $e$ produces the minimum weight sub-tree  of  $T\cup e$  containing $e$. If the considered edge is in $T$ and we choose to include it in the sampled tree, $\tau$, we recursively update $\log s_\phi(\tau)$ by adding the Bernoulli log probability corresponding to the edge. See Fig. \ref{fig:slantis} for an illustration.

\begin{figure}[b]
\begin{center}
\includegraphics[width=\textwidth]{figs/slantis.png}
\caption{Propagation step of SLANTIS. The solid line is $\tau$ so far, and bold \textbf{\textcolor{tab:green}{green}} lines are accepted edges. Dashed and dotted lines are the edges not in $\tau$. The \textcolor{tab:blue}{blue} color indicates the edge we consider
($e$),
and the \textcolor{tab:orange}{orange} color indicates the alternative edge, either
$c$ or $e^*$.
$r_e = W(e) / (W(e) + W(c))$ or $r_e = W(e) / (W(e) + W(e^*))$. At the end of SLANTIS, the spanning tree with bold green lines is reported.}
\label{fig:slantis}
\end{center}
\vskip -0.2in
\end{figure}

\subsection{The JC Sampler}
The JC69 model is arguably one of the most frequently used substitution models in Bayesian phylogenetics. However, as far as we are aware, the model has only been used for obtaining maximum likelihood estimates of branch lengths. Here, we observe that the JC69 model can be seen as an i.i.d. Bernoulli likelihood over sites and leverage the Beta-Bernoulli conjugacy for obtaining a normalized distribution over branch lengths in variational inference. Below we show how to sample from this distribution and evaluate its likelihood using the change-of-variables formula.

Given a branch length $b(e)=b$, the probability of the $m$'th nucleotide \textit{not} mutating along edge $e=(i,j)$ is, according to the JC69 model,
\begin{equation}
\label{eq:jc p}
    p = \left(\frac{1}{4} + \frac{3}{4}e^{-\frac{4}{3}b}\right)^{\mathbbm{1}\{Z_i^m=Z_j^m\}}.
\end{equation}
As all mutations are equiprobable for this model, the probability of the nucleotide mutating is thus $1-p$,
giving rise to the following distribution when all $M$ estimated mutations and non-mutations are observed and assuming mutations occur independently across sites
\begin{equation}
\begin{aligned}
    \text{Bern}\left( \phi_{ij} | p \right) &= \prod_{m=1}^M \text{Bern} \left( \phi_{ij}^m | p \right) = \prod_{m=1}^M p^{1-\phi_{ij}^m} (1-p)^{\phi_{ij}^m} = p^{M-\phi_{ij}}(1-p)^{\phi_{ij}},
\end{aligned}
\end{equation}
where $\phi_{ij}^m$ is the expected number of mutations over the edge $(i,j)$ at site $m$.
Assuming an uninformative Beta prior on the Bernoulli parameter, $p$, and recalling that Beta is a conjugate prior for the Bernoulli distribution, we get a posterior distribution over $p$,
    $\text{Beta}(p| M-\phi_{ij} + 1, \phi_{ij} + 1)$. Since we are ultimately interested in sampling $b$, not $p$, we find a transform, $f(\cdot)$, mapping $p$ to $b$, using Eq. \eqref{eq:jc p};

\begin{equation}
    f^{-1}\left(b\right) =
    \frac{1}{4} + \frac{3}{4}e^{-\frac{4}{3}b}
     = p
\end{equation}
\begin{equation}
\label{eq:f}
    f(p) = -\frac{3}{4}\log\left( \frac{4}{3}\left(p - \frac{1}{4}\right)\right) = b.
\end{equation}
In all, sampling branch lengths from the JC model include two straightforward steps, (i) draw $p$ from the Beta posterior distribution, and (ii) pass it through the transform, $b=f(p)$.

Of course, we are also interested in evaluating the likelihood of the sampled branch length. To do so, we use the
change-of-variables formula; we let
\begin{align}
\label{eq:change-of-variable}
    s_\phi(b) &= \text{Beta}(p| M-\phi_{ij} + 1, \phi_{ij} + 1)\left\vert\frac{df^{-1}(b)}{db} \right\vert\\
    &= \frac{p^{M-\phi_{ij}} (1-p)^{\phi_{ij}}e^{-\frac{4}{3}b}  }{\text{B}(M-\phi_{ij} + 1, \phi_{ij} + 1)},
\end{align}
where B$(\cdot)$ is the Beta function. This provides an efficient way of evaluating the likelihood of a branch length. In Alg. \ref{alg:jcsampler}, we summarize the JC sampler with an algorithmic description.

\begin{algorithm}[H]
\caption{The JC Sampler}
\label{alg:jcsampler}
\begin{algorithmic}[1]
\STATE {\bfseries Input:} $\phi, i,j$
   \STATE Sample $p\sim \text{Beta}(p| M-\phi_{ij} + 1, \phi_{ij} + 1)$
   \STATE Transform $b = f(p)$ \; \COMMENT{Eq. \eqref{eq:f}}
   \STATE Evaluate $s_\phi(b)$ \; \COMMENT{Eq. \eqref{eq:change-of-variable}}
   \STATE \textbf{return} $b, s_{\phi}(b)$
\end{algorithmic}
\end{algorithm}

\subsection{Assessing the Framework}
The framework learns its parameters and distributions by maximizing the ELBO in Eq. \eqref{eq:elbo}. However, the IWELBO offers a tighter lower bound on the marginal log-likelihood. Using SLANTIS and the JC sampler, we can easily evaluate our framework using the IWELBO:
\begin{equation}
    \label{eq:iwelbo}
    \mathcal{L}_{L} = \mathbb{E}_{\mathcal{B}_\ell, \tau_\ell \sim s_\phi(\mathcal{B},\tau)}\left[
    \log\frac{1}{L}\sum_{\ell=1}^L\frac{p_\theta(X, \mathcal{B}_\ell, \tau_\ell)}{s_\phi(\mathcal{B_\ell},\tau_\ell)}
    \right],
\end{equation}
where we may factorize the denominator as $s_\phi(\mathcal{B},\tau) = s_\phi(\mathcal{B}|\tau)s_\phi(\tau)$, and
$s_\phi(\mathcal{B}|\tau) = \prod_{e\in E(\tau)} s_\phi(b(e))$. Note that we have marginalized out the auxiliary variable, $Z$, in the target in Eq. \eqref{eq:iwelbo}, as we do not wish to compute $\mathcal{L}_{L}$ using our variational distributions.

\section{Using VaiPhy to Parameterize the CSMC}
\label{sec:vaiphy2csmc}
As the tree topology space in $\mathrm{A}$ is considerably larger than the bifurcating $X$-tree space, obtaining competitive  log-likelihood (LL) estimates is not straightforward. Namely, the uniform prior over the tree space in $\mathrm{A}$, $
    p_\theta(\tau) = 1/(N-|X|) ^{N - 2}$,
turns into a heavily penalizing term. When compared to baselines in smaller sample spaces, this will become a considerable negative factor for VaiPhy. Compare this to the prior when considering unrooted, bifurcating $X$-trees (which is the case for VBPI-NF): $
    p_\theta'(\tau) = 1/{(2|X| - 5)!!},$
where $|X|$ is the number of taxa. As an example, for $|X|=10$ and $N=18$, $p_\theta(\tau)$ distributes mass uniformly over $281$ trillion trees, while the latter one merely considers $2$ million trees.

Inspired by \cite{moretti2021variational}, we instead seek to use VaiPhy to parameterize a CSMC algorithm, thereby obtaining a procedure for projecting our trees to the  lower-dimensional leaf-labeled tree space. Here, the prior is instead $
    p_\theta''(\tau) = 1/{(2|X| - 3)!!}.
$

Since $\phi$ is not constrained to multifurcating trees, we can utilize the estimated number of mutations between vertices learned in $\mathrm{A}$, also in the bifurcating $X$-tree space, $\Omega$. Here arises an interesting obstacle. In the CSMC algorithm, the internal vertices are \textit{unlabeled}. Hence we are effectively blindfolded and need to estimate which entry in $\phi$ to use for a given edge. We achieve this by scoring edges based on how frequently the corresponding split of the leaf-set $X$ occurs in trees sampled from $s_\phi(\tau)$. See Appendix \ref{appendix:CSMC T proposal} for more information.

At each rank $\rho\in[1,R]$, the CSMC proposes (i) a forest, $\mathcal{T}_{\rho}$, by \textit{merging} the roots of two subtrees in $\mathcal{T}_{\rho-1}$, and (ii) a corresponding set of branch lengths, $\mathcal{B}_\rho$. This is done in parallel for $K$ \textit{particles}, resampling particles with probability proportional to their importance weights, $w^k_{\rho}$, at every rank.\footnote{For more details and background of the CSMC algorithm, we point the reader to \cite{moretti2021variational} and \cite{wang2015bayesian} for excellent descriptions.} However, the reason to take advantage of a CSMC is that it allows us to  estimate the marginal log-likelihood in the bifurcating $X$-tree space using the well-known formula,
\begin{equation}
\label{eq:logZ}
    \log p_\theta(X) \approx \log \prod_{\rho=1}^R\frac{1}{K}\sum_{k=1}^K w_\rho^k.
\end{equation}

We let $\phi$ parameterize our two novel CSMC proposal distributions, $r_\phi(\mathcal{B}_\rho|\mathcal{B}_{\rho-1}, \mathcal{T}_{\rho})$ and $r_\phi(\mathcal{T}_{\rho}|\mathcal{T}_{\rho-1})$. The former constructs a mixture of JC samplers and evaluates the proposal's likelihood in a multiple importance sampling fashion \cite{elvira2019generalized}, while the latter forms a categorical distribution over the roots in $\mathcal{T}_{\rho-1}$, parameterized by a function of the likelihoods of trees sampled by SLANTIS. The in-detail descriptions can be found in Appendix \ref{appendix:CSMC}.

\section{Experiments}
\subsection{Visualizing the JC Sampler}We conduct a toy experiment, investigating how the estimated number of mutations along an edge affects the behavior of the JC sampler. We would expect that a greater number of mutations should generate a larger branch length. This  is the case since the involved vertices are supposedly farther apart in terms of an evolutionary distance.

As demonstrated in Fig. \ref{fig:jc_sampler}, this advantageous behavior is indeed displayed. As $\phi_{ij}$ grows, the corresponding JC sampling distribution is shifted towards larger branch lengths. Interestingly, the JC sampler distributes its mass more symmetrically than the Log-Normal or Exponential distributions, which are typically used for modeling branch length distributions \cite{wang2015bayesian, zhang2018variational,Zhang0if,moretti2021variational}.

It follows from  Eq. \eqref{eq:f} that branch lengths grow infinitely large as $p$ goes to $0.25$. This phenomenon in phylogenetics is referred to as saturation. Saturation occurs for distantly related lineages and implies that the states of the nucleotides in these ancestral sequences are mutually independent. This is not an interesting case, hence the non-exhaustive parameter search of $\phi_{ij}$ in Fig. \ref{fig:jc_sampler}.

\subsection{Density Estimation}
Here we benchmark our methods, VaiPhy, and $\phi$-CSMC, in terms of LL estimates on seven real-world datasets, which we refer to as DS1-DS7  (\cite{hedges1990tetrapod, garey1996molecular, yang2003comparison, henk2003laboulbeniopsis,lakner2008efficiency,zhang2001molecular,rossman2001molecular}; in Appendix \ref{appendix:real_datasets}, we provide additional information about the datasets). Additionally, to the extent possible, we have used the open-source code of our baselines to survey the benchmarks on these popular datasets. We only considered baselines that employ the JC69 model. Moreover, we assumed an Exp($10$) prior over branch lengths and a uniform prior over tree topologies. This was aligned with the generative models used in all the original works of the baselines.

For all methods, we use the exact parameter configurations reported in the corresponding papers or specified in their available code. We let VBPI-NF \cite{Zhang0if} and VCSMC \cite{moretti2021variational} train for the number of iterations as specified in their works. For MrBayes \cite{ronquist2012mrbayes} with the SS method, we follow the protocol used in \cite{zhang2018variational}.

As we are benchmarking sophisticated versions of the phylogenetic inference CSMC \cite{wang2015bayesian}, it seems relevant to include a vanilla CSMC. We define the vanilla CSMC as one that proposes branch lengths using the model prior and merges subtrees uniformly. There are no learnable parameters in the vanilla CSMC.

Indeed, there exist particle MCMC based approaches for parameterizing the CSMC, e.g., \cite{wang2015bayesian} or  \cite{wang2021particle}; however, these have not previously been benchmarked on the datasets used here, and the latter uses the K2P substitution model. As such, we leave these comparisons for future work and constrain ourselves to VI based CSMCs.

Following \cite{moretti2021variational}, we give all CSMC methods $K=2048$ particles. The parameters of VCSMC, VaiPhy, and $\phi$-CSMC are selected based on their best iteration, measured in LL. Using these parameters, we compute the LL estimates averaged over ten random seeds. We run VaiPhy and $\phi$-CSMC for $200$ iterations and evaluate them on Eq. \eqref{eq:iwelbo} and Eq. \eqref{eq:logZ}, respectively. Vanilla CSMC is also evaluated using Eq. \eqref{eq:logZ}.

In Table \ref{tab:ds_results}, we provide the mean LL scores and standard deviations. On all datasets except DS2, our $\phi$-CSMC is the superior CSMC method (highlighted in red). It also produces significantly smaller variations in its LL estimates compared to VCSMC and the Vanilla CSMC. On DS2, the Vanilla CSMC is surprisingly the winning CSMC.

Overall, MrBayes SS is the superior method on these datasets, followed by VBPI-NF. VaiPhy, despite its heavily penalizing prior distribution over tree topologies (see Sec. \ref{sec:vaiphy2csmc}), still outperforms VCSMC and Vanilla CSMC on all datasets but DS2, with extremely low-variance estimates of the LL.

\begin{table*}[t]
\caption{Real dataset LL estimates for the different methods. Our $\phi$-CSMC is, on average, the best-performing CSMC method (\textcolor{red}{red}). Overall, MrBayes SS achieves the highest LL estimates (\textbf{bold}). *Not available due to unresolved memory issues.}
\label{tab:ds_results}
\vskip 0.15in
\begin{center}
\resizebox{\textwidth}{!}{
\begin{small}
\begin{sc}
\begin{tabular}{lccrrrrr}
\toprule
Data Set & (\#Taxa, \#Sites) & MrBayes SS & VBPI-NF & VCSMC (JC) & Vanilla CSMC & VaiPhy & $\phi$-CSMC \\
\midrule
DS1 & (27, 1949) & \textbf{-7032.45 $\pm$ 0.15} & -7108.40 $\pm$ 0.11 & -9180.34 $\pm$ 170.27 & -8306.76 $\pm$ 166.27 & -7490.54 $\pm$ 0 & \textcolor{red}{-7290.36 $\pm$ 7.23} \\
DS2 & (29, 2520) & \textbf{-26363.85 $\pm$ 0.33} & -26367.70 $\pm$ 0.03 & -28700.7 $\pm$ 4892.67 & \textcolor{red}{-27884.37 $\pm$ 226.60} & -31203.44 $\pm$ 3E$^{-12}$ & -30568.49 $\pm$ 31.34 \\
DS3 & (36, 1812) & \textbf{-33729.60 $\pm$ 0.74} & -33735.09 $\pm$ 0.05 & -37211.20 $\pm$ 397.97 & -35381.01 $\pm$ 218.18 & -33911.13 $\pm$ 7E$^{-12}$ & \textcolor{red}{-33798.06 $\pm$ 6.62} \\
DS4 & (41, 1137) & \textbf{-13292.37 $\pm$ 1.42} & -13329.93 $\pm$ 0.11 & -17106.10 $\pm$ 362.74 & -15019.21 $\pm$ 100.61 & -13700.86 $\pm$ 0 & \textcolor{red}{-13582.24 $\pm$ 35.08} \\
DS5 & (50, 378) & \textbf{-8192.96 $\pm$ 0.71} & -8214.61 $\pm$ 0.40 & -9449.65 $\pm$ 2578.58 & -8940.62 $\pm$ 46.44 & -8464.77 $\pm$ 0 & \textcolor{red}{-8367.51 $\pm$ 8.87} \\
DS6 & (50, 1133)& \textbf{-6571.02 $\pm$ 0.81} & -6724.36 $\pm$ 0.37 & -9296.66 $\pm$ 2046.70 & -8029.51 $\pm$ 83.67 & -7157.84 $\pm$ 0 & \textcolor{red}{-7013.83 $\pm$ 16.99} \\
DS7 & (64, 1008) & \textbf{-8438.78 $\pm$ 73.66} & -8650.49 $\pm$ 0.53 & N/A$^*$ & -11013.57 $\pm$ 113.49 & -9462.21 $\pm$ 1E$^{-12}$ & \textcolor{red}{-9209.18 $\pm$ 18.03} \\
\bottomrule
\end{tabular}
\end{sc}
\end{small}}
\end{center}
\vskip -0.1in
\end{table*}

\subsection{Wall-Clock Time and Memory Comparisons}
Being a mean-field VI algorithm, VaiPhy truly enjoys the related benefits in terms of speed, which we demonstrate in this section. The experiments are performed on a high-performance computing cluster node with two Intel Xeon Gold 6130 CPUs with 16 CPU cores each. Each node in the cluster has 96 GiB RAM.

We run VaiPhy for 200 iterations, and 128 trees are sampled using SLANTIS to compute the expectations in Eq. \eqref{eq:upd z} and \eqref{eq: upd B}. To compute $\mathcal{L}_L$, 3000 trees are sampled from SLANTIS after 200 iterations. The $\phi$-CSMC results include the aforementioned VaiPhy runs and 10 additional independent CSMC runs with 2048 particles. VBPI-NF runs for 400,000 iterations and uses 100,000 trees to estimate the lower bound after training.
Each experiment is repeated 10 times. The wall-clock time comparison of the methods on DS1 is presented in Fig. \ref{fig:runtime}.

\begin{figure}[ht]
\begin{center}
\includegraphics[width=6.5cm]{figs/runtime.png} \hskip 0.2in
\includegraphics[width=6.5cm]{figs/runtime_zoomed.png}
\caption{Wall-clock runtime results on DS1 data set with $\{2, 4, 8, 16\}$ cores. Left) Runtime results for VaiPhy, $\phi$-CSMC, and VBPI-NF. Right) A zoomed-in version of the top figure showing runtime results for VaiPhy and $\phi$-CSMC. Clearly, VaiPhy is consistently faster than its benchmarks.}
\label{fig:runtime}
\end{center}
\vskip -0.2in
\end{figure}

We were not able to run VCSMC on less than 16 cores due to the method producing memory issues on DS1. However, for 16 cores, their runtime was around $6840$ seconds, with too small variations to show in a boxplot. VCSMC is thus faster than $\phi$-CSMC on 16 cores but still slower than VaiPhy.

VaiPhy is remarkably faster than other variational methods for each number of cores investigated. Although VBPI-NF produces impressive LL estimates, it is considerably slower than VaiPhy and the CSMC methods (all CSMCs are not shown in the figure). Additionally, using two cores, the wall-clock time required by VBPI-NF to arrive at VaiPhy's approximation accuracy was close to 11x that of VaiPhy on DS1. For completeness, we compared wall-clock times with MrBayes, although this is not appropriate given that the software has been highly optimized over decades and is written in C. And, indeed, MrBayes is the fastest algorithm when allowed multiple cores. However, for a single core on DS1, MrBayes ran for approximately $100$ minutes while VaiPhy only needed an impressive $83$ minutes on average for the same setup.

Finally, we discuss memory requirements. Our main variational baseline, VBPI-NF, used 8.4 million neural network weights and biases on DS1, while the number of learnable parameters (i.e., the dimensions of $\phi$ and $q(Z|X)$) in VaiPhy was 0.8 million; less than 10\% of the former.

\section{Conclusion}
We have presented a modular framework for Bayesian phylogenetic inference, building on three novel methods: \textit{VaiPhy}, \textit{SLANTIS}, and the \textit{JC sampler}. At the heart of our framework lies $\phi$, the estimated number of mutations matrix. Although $\phi$ was learned in a multifurcating tree space with labeled internal vertices, we showed that the evolutionary distances also served useful in the bifurcating $X$-tree space. We demonstrated this by using $\phi$ to parameterize two new proposal distributions for the CSMC, also introduced by us in this work; we referred to this new algorithm as $\phi$-CSMC. Our $\phi$-CSMC proved to be the best-performing CSMC in terms of marginal log-likelihood estimation on real datasets. Additionally, VaiPhy was up to \textit{25 times faster} than its baselines on real data.

 Speed is essential for making Bayesian phylogenetics a reality for future large data sets, in particular, single-cell data sets in medical investigations. Moreover, speed and the opportunity to leverage the VI methodology for phylogeny, as provided by our framework, i.e., our graph-based representation of the VI distribution over trees, $\phi$, opens up novel research opportunities. For instance, recently, ensemble and mixture models in VI have received a lot of attention \cite{kviman2022multiple, morningstar2021automatic}. VaiPhy could obtain many ensemble components in parallel with low computational cost and thus has great potential to benefit from these findings. Moreover, more mixture components appear to imply significant improvements in terms of negative log-likelihood scores when learned by maximizing a multiple importance sampling-based objective, \textit{MISELBO} \cite{kviman2022learning}.
 This motivates researching how VaiPhy could be fitted using a MISELBO objective.

For many potential applications, models other than the JC69 model will be more suitable for the evolution that takes place over the edges of the phylogenetic tree. However, our JC sampler provides a great starting point. Reasonably, the JC sampler should serve as a better base distribution for normalizing flows than those currently employed \cite{Zhang0if}. Furthermore, in this work, the JC sampler samples the branch lengths independent of the tree topology. We expect that tree topology dependent branch sampling will enhance VaiPhy's performance. This will be investigated in our future work.

VI can facilitate Bayesian analysis of models that integrate phylogeny with other tasks that usually are performed as pre-processing or post-processing steps. The most important such example may very well be sequence alignment. Although Bayesian phylogenetic inference is currently considered state-of-the-art, this inference does not take the observed sequences associated with the taxa as input but a so-called multiple sequence alignment (MSA) of these, which is obtained by applying a heuristic to the sequences. This implies that the entire uncertainty related to the multitude of possible MSAs remains uncharacterized after a standard Bayesian phylogenetic inference, i.e., it does not affect the obtained posterior at all. For single-cell phylogenetic analysis of cancer cells, pre-processing may be even more involved. For instance, the so-called direct library preparation single-cell DNA data \cite{Zahn2017-nj} for tumors require a pre-processing step in which the cells are clustered into cancer clones. For these clones, it is then desirable to perform a phylogenetic inference. Interestingly, the VI has already been launched for Bayesian clustering for this pre-processing step \cite{safinianaini2020copymix}.

In conclusion, we have presented a VI algorithm for Bayesian phylogeny that, together with its building blocks, unlocks the potential of VI for fast Bayesian analysis in phylogeny and integrated phylogenetic analysis. The by now 25 year old methodology of MCMC based Bayesian phylogenetic analysis is certainly a mature and optimized methodology with great accuracy. However, VaiPhy is faster than MrBayes on a single core, and the underlying methodology is bound to lead to a sequence of increasingly faster and more accurate VI based phylogenetic software.  Moreover, it paves the way for integrated VI based phylogenetic inference.

\begin{ack}
First, we acknowledge the insightful comments provided by the reviewers, which have helped improve our work. This project was made possible through funding from the Swedish Foundation for Strategic Research grant BD15-0043, and from the Swedish Research Council grant 2018-05417\_VR. The computations and data handling were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC), partially funded by the Swedish Research Council through grant agreement no. 2018-05973.

The authors declare no competing interests.
\end{ack}

redpajama_set_name: RedPajamaArXiv


Produktfinder til vandringslængder på op til 13 m.
What is so convincing about iglidur® plastic bar stock plates is their high resistance to wear. In order to meet different requirements of use and the environment, the plastic plates are available in three materials from the iglidur® range, each of which has different properties. In the form of plastic plate that can be used in a wide variety of ways, is especially resistant to wear, is available in black or is FDA-compliant, the plastic bar stock can be used without lubrication and therefore satisfies demanding hygienic requirements of the environment in which it is used. iglidur® plastic bar stock plates are used in medical equipment or in the food and packaging industries, among others.
The plastic plates can be supplied cut to size, with thickness ranging from 2 mm to 40 mm, made of 3 different plastic materials and available in up to 7 standard sizes.
135 trillioner testbevægelser hvert år for alle slags applikationer.
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The Mayor of Kings Lynn and West Norfolk, Councillor Nick Daubney, recording his traditional Christmas message to listeners. Assisted by Annette, Emma, Keith, Michael and engineer Alan Lindsay. In the new NNAB offices.
The King's Lynn Talking Newspaper for the Blind (Vision Link) contains local news not available from other sources. It is available free to any visually impaired person. It is compiled from a local newspaper, The Lynn News, and recorded weekly by volunteers.
Following the closure of the Downham Market and Hunstanton Talking Newspapers, Vision Link now covers the whole of West Norfolk to provide a Talking Newspaper and even supplies locals who have moved away as far as London and Glasgow.
Recording uses facilities at the Norfolk and Norwich association for the Blind (NNAB) on the North Lynn industrial site. The Talking Newspaper is run entirely by volunteers and receives no funding from any statutory body.
The News is recorded onto USB memory sticks for play back on special players. These players are given to listeners for as long as they need them. They operate on battery or mains. The USB sticks are distributed and returned in special pouches by the Royal Mail free of charge as articles for the Blind. They can then be recycled.
We always need volunteers to keep this valuable service going. Apart from reading there are many other tasks, from preparing the script to operating the recording equipment, packing and unpacking the memory sticks and making copies. if you can spare just two hours a month please contact us.
One of the special USB players with the Usb stick inserted and the dispatch and return pouch. They are very easy to operate. The large dial is on\off and volume while on top you can pause, forward, rewind and stop just as you would with cassette tapes.


The Perfect Peel – thinking about skin differently. A leader in medical grade skin care worldwide and the only chemical peel in the world to contain Glutathione.
The Skin and Wellbeing Clinic Preston aims to provide safe and professional skin and wellbeing treatments in a stylish, luxurious and friendly environment.


Industrial applications range from machine control, health-care, and robotics to power generation, process control, and transportation. Each of these areas employ embedded processing to perform closed loop autonomous control, have high availability requirements, and are highly software defined. In these applications the designers take advantage of the advancements in processing, communications, software, and system design originating from the consumer world. On top of this foundation they typically make additions or modification to meet the performance, longevity, and reliability needs of their industry.
One area where modifications are often required is for distributed coordinated communications. Much of industry transitioned to using an Ethernet physical layer in the early 2000s. However unless strict traffic and access controls are implemented, standard Ethernet is unable to guarantee network latency. This makes it inappropriate for closed loop control where latency and reliability are paramount. To work around this limitation, common practice is installation of dedicated Ethernet networks (sometimes with multiple islanded networks running side by side in the same machine) or the use of modified network hardware layers to support bounded low latency network traffic.
As engineers optimize industrial productivity, control systems complexity has grown. Increasing network capabilities and software abstractions make system design more automated and easier to implement.
Today system designers are investing to incorporate IoT concepts into their systems to increase productivity, increase up-time, and improve other key performance indicators. Techniques such as remote system management and maintenance, centralized data collection for big data analytics, and in-built self organizing machine to machine coordination, promise to radically advance next generation industrial control and monitoring systems. To support these capabilities, industrial designers need reliable, converged, remote, secure access to all the components and devices in their designs. This requires fundamental improvements to standard Ethernet so that it will concurrently support both industrial control needs and IoT connectivity and data access.
Industrial applications such as machine control require bandwidth, timing, latency, openness, and compliance with IT standards. Standard Ethernet is being updated to enable these capabilities.
These improvements will enable a single network to support reliable multi-kHz closed loop control and dynamic un-managed standard Ethernet traffic. Because these capabilities are being incorporated in the core Ethernet standard, these upgrades promise broad adoption, increased flexibility, increased bandwidth, multi-vendor interoperability, and decreased cost.
John Garrity, Product Line Leader for General Electric Intelligent Platforms.
Mike Santori, Vice President Product Marketing, National Instruments.
Andreas Dreher, Strategic Technology Manager, Belden.
Anthony Neal-Graves, Vice President, Internet of Things Group, Intel.
Nicholas Ilyadis, Broadcom CTO, Infrastructure & Networking Group.
Kip Compton, VP and General Manager of the Internet of Things (IoT) Systems and Software Group, Cisco.
Networking for Power Generation: Advanced networking capabilities to support utility power plant designs.
Networking for Industrial Machine Building: Communications and IoT scaled to machine control.


text:
Congratulating Sarai Antoine, National Youth Leadership Award Winner April 4, 2018
Sarai Antoine, a senior at Evans High School, A Community Partnership School, will be nationally recognized for encouraging equity and building opportunities within her Pine Hills community.
Once bullied because of her appearance and heritage, Sarai found empowerment and support when she arrived at Children's Home Society of Florida's flagship Community Partnership School – Evans High School. In 2012, the Community Partnership School model ™ was implemented at Evans to build bridges to success for teens — like Sarai – to overcome tough community challenges including poverty, hunger, bullying and more. This successful model is a partnership among Children's Home Society of Florida, Orange Blossom Family Health Centers, Orange County Public Schools and the University of Central Florida.
You can see more about Sarai's award from The Coalition for Community Schools HERE.
Sarai overcame difficult obstacles to become a school leader and community inspiration. With the support of her mentor, Sarai gained the confidence to join student government and the Student Leadership Council. Understanding the difficulty firsthand of being an immigrant to this country, she also formed the first Haitian organization on campus, Club Kreole.
After she graduates, Sarai will be the first person in her family to attend college. One of her goals before graduation is to plan an empowerment summit for girls to address gender inequality.
Sarai is committed to helping more kids realize their full potential and cross bridges to success.
Children's Home Society of Florida

redpajama_set_name: RedPajamaCommonCrawl


Launching a business? Here are 8 important startup tips for entrepreneurs, which will help you succeed.
Understand the needs of the customer and give more than they expect. Never compromise with the quality. If the quality is excellent, then your business will be a success without plenty of marketing. Take frequent feedback from customers and improve your product or services according to their valuable feedback and need.
Can you reach your target audience?
Does the market need what you're offering?
Take time to do a lot of market research and survey about your audience to understand what they're most interested in and also you need to figure out demand for your product or service. Do an aggressive competitive analysis. Find an area to set up the store. And create a plan to differentiate your supply.
Starting a business is harder than a Job. To become a successful Entrepreneur, one needs to operate the variety of functions: sales, marketing, finance, operations, HR, etc. You must be more confident than anyone else is, in your business. If a person has a passion for his work, then he will overcome all his obstacles. If you love your work, then every day you can do it in all the best possible way.
It's far important to be open-minded and adaptable while doing out marketplace analysis, as some of the feedback won't be precisely what you were hoping for.
After engaging in a survey maybe you discover that clients are searching out a slightly different carrier or additional features. Do not scrap your concept, however, do take into account modifications to house your customers' needs.
In today's time, social media is a platform that lets you grow your business in a very short time. If you're a business owner, its advised to use social media marketing so people get know about your business as it provides you with the opportunity to grow relationships with your target audience.
In fact, 82 percent of small commercial enterprise owners are using websites like FB, Twitter, LinkedIn, Pinterest, and Instagram to assist in growing their businesses.
Some humans consider that entrepreneurs are risk takers. But the successful entrepreneur does not like to walk in the dark. Alternatively, they take controlled risks. They check a concept on a small scale, then construct on what works nicely.
Competition is a great factor. Do not get frightened of opposition. Their existence proves that there is a demand for the product that you're offering.


Capital expenditures for employee safety and health will rise 28 percent in 1980, according to the economics department of McGraw-Hill Publications Company. If current plans are met, business' 1980 expenditures on safety and health equipment will total $3.7 billion.
During 1981-83, average annual expenditure will fall to $3.5 billion if current plans are carried out. The 1980 figure represents the second-largest expenditure for safety and health since 1972.
In Gear Do gas prices really matter?


text:
1 is One is a 1956 picture book written and illustrated by Tasha Tudor. The book is a counting book going up to the number 20. The book was a recipient of a 1957 Caldecott Honor for its illustrations.

References

1956 children's books
American picture books
Caldecott Honor-winning works

redpajama_set_name: RedPajamaWikipedia


text:
January 3, 2022: Watching, Reading, Writing!
Previous Article January 2, 2022: Suji Sunday!
Next Article January 4, 2022: Here we go again!
As I mentioned the other day, this year I am going to make a concerted effort to read and watch (and, hopefully, write) more in 2022. More books. More comics. More shows. More movies. And every so often, I'll do capsule write-ups to help you decide what to check out and, perhaps, what to avoid.
Following her father's murder, a revenge-driven woman puts her trust in a powerful crime boss — and enters the police force under his direction.
No one does the gangster-theme quite like Korea. Movies like A Bittersweet Life and The Man from Nowhere rank among my top films off all time while shows like the high-concept, high-adrenaline Bad Guys leaves me to wonder why we can't – or won't – make t.v. like this? Outside of The Sopranos, there are few Western shows that offer the same level of heart, tragedy, depth of character, or genuinely surprising twists and turns. Although I did guess the big reveal in this series (But, in all fairness, I'm a writer. That's what I do.), it didn't lessen my enjoyment of this smart, well-directed, beautifully-acted series – or prepare me for one major unexpected surprise in the finale. It's a tight and compelling episode run that is well worth your time.
The year is 2100. The lack of trust that characterized the early Internet era is long behind us. Mathematical proof ensures neural implants can't be hacked, and the Board of Reality Overseers blocks false information from spreading.
When undergraduate Sergei Kraev, who dreams of becoming a professor, is accepted into the Technion's computer science graduate program, he throws himself into his research project: making it possible for neural implants to transmit information directly to the brain. If he succeeds, he'll earn a full professorship.
But Sergei falls under the influence of Sunny Kim, the beautiful and charismatic leader of a K-pop dance cult. Sergei believes in Sunny's good intentions and wants to protect her from critics, leading him to perform a feat of engineering that leaves billions of brains vulnerable to attack.
With the clock ticking towards catastrophe, can Sergei see the truth about Sunny and undo what he's done?
Okay, let's get one thing straight right off the bat. There is no K-pop dance cult. It's dance cult based on Korea. There is not even the remotest element of K-pop in this novel and, while most may not care, as someone who had my interest piqued for this very reason, it was a bait and switch. The lack of this potentially kooky/fun (promised) story element aside, this book offers some fascinating world-building as it imagines a future where our lowly internet evolves into a cyberspace that links users via brain implants which offer convenience and comforts…but at what cost? The set-up is great and fascinating aspects of the future tech off-sets the occasional info-dumps in much the same way most of the grounded, sympathetic characters that people this world outweigh the rather two-dimensional villain – Sunny, the dance-happy cult leader – at the heart of the novel. There are also instances where the author seems to be making a political statement about the dangers of misinformation and the need for state censorship which is ironic given that the antagonists of the story hail from the former North Korea. Overall, a solid read whose futuristic ideas are stronger than its narrative whole.
Christopher Chance has made a living out of being a human target-a man hired to disguise himself as his client to invite would-be assassins to attempt his murder. He's had a remarkable career until his latest case protecting Lex Luthor when things go sideways. An assassination attempt Chance didn't see coming leaves him vulnerable and left trying to solve his own murder…as he has 12 days to discover just who in the DCU hated Luthor enough to want him dead.
It's D.O.A. DC-style in a limited series that exudes a stylish noir coolness evocative of Brubaker/Phillips but with a splash of retro-fun compliments of Greg Smallwood's pencils and colors. I love King's ability to mine comic-lore – in this case, the old Justice League International – for story, giving new life to B (or lower) tier characters like Guy Gardner, Bosster Gold, and Ice, setting up an engaging mystery, its tragic underpinnings bolstered by flashes of heart and humor. In most every version of D.O.A. I've seen, the protagonist solve the mystery but loses his life in the end. It will be interesting to see how this version plays out and, while I'd be surprised if Chance doesn't manage to save the day – and his life – in the end, I'm curious to see if King can pull it off in a way that proves unexpected and narratively satisfying. Three issues into this 12 issue maxi-series, and I am firmly on board.
The Earth is all but done. The last remnants of humanity cling to a mountaintop island lost in endless floodwater. The Parliaments of the Green, the Red, and the Rot all agree: it's time to wipe the slate clean and start the cycle of life over again. And to do so, they've united their powers to summon an avatar-one of the most horrific monsters to ever stalk the surface of this forsaken planet…
It feels like a cross between Lovecraft and The Walking Dead with its old gods, gore, and humanity's last stand but one rooted in the supernatural world of the DC universe as evidenced by not one but two perhaps not-so-surprising cameos at first issue end. Lemire is one of the most original minds in comics, so I look forward how his take on the Swamp Thing reimagines the character, and subverts the expectations set up by issue #1. I'm in wait and see mode on this one.
A bright, shining day in Metropolis is interrupted by a mysterious drone that crash-lands in the city and starts wreaking havoc. This looks like a job for Superman! But where did the metallic menace come from, what is its purpose, and who is Brainiac?
Admission: I'm not a huge Superman fan (I found him kind of dull) and wasn't as enamored of the 1978 Superman movie (Hated the reverse time ex-deux machine but, in all fairness, I appreciated the first movie a lot more than its corny sequels), but this limited series that embraces the tone of that original film is surprisingly a hell of a lot of fun. Rich with humor and wonderful character moments, its source material echoes through each issue in the terrific character designs honoring Christopher Reeves, Margot Kidder, Gene Hackman, and others. Recommended.
I completed my polish of the Promise of Blood pilot (the adaptation of Brian McClellan's Powder Mage Trilogy) and am presently revising and running through the new and improved pitch. The plan is to start shopping it as soon as Hollywood loses its holiday hangover.
I have a zoom call on Friday to discuss next steps for Fronted, my SF/K-pop series (And I promise there WILL be K-pop in this one). We'll be discussing feedback on the pitch deck and pilot from a potential South Korean partner as well as talent attachment (I have some artists in mind) and next steps.
The story for the second of that two-pilot-deal is fast taking form. The pilot will be ambitious from a structural POV, but I love the fact that it's unique and sets up not one or two but three surprises at episode's end. Awaiting the official green light on this one.
And while I await word on some other projects, I'm hammering out a beat sheet for that feature script I was planning to write last year, but never got around to. Maybe 2022 is the year?
6 thoughts on "January 3, 2022: Watching, Reading, Writing!"
Quantum Mechanic®👽🌌 (@JamesEFinch) says:
I am meditating & asking the universe to get you a series and/or other projects going your way. I feel you will have a great year. On Human Target, gotta love Greg Smallwood's art. He reminds me of Dan Spiegle at little (Space Family Robinson, DNAgents, Crossfire) but more pristine. Always enjoy your vids with Akemi. Happy New Year with love and happiness always in your horizon.
I remember reading a tweet of yours a while back that had something to do with Powder Mage and Anthony Lemke. I don't suppose he might appear in the cast?
Joseph Mallozzi says:
Too early to say at this point.
Needless to say, we'd love to see him (and other Dark Matter alumni) in your future work! Doubtless you'd love to have him, too, if there's a part that fits and his availability works out.
Tim G says:
I am reading Human Target as well. Much better than I thought it would be.
I watched the My Name pilot then got sidetracked, thanks for the reminder.


Striped bass are a pleasant pastime for some and an obsession for others. Generations of anglers have fished the estuaries and shores of the Bay of Fundy in search of this prized catch, and Striped Bass touch many natural, economic, and cultural corners of the Maritimes. Striped Bass are a highly prized fish in the eyes of anglers, and are, therefore, very desirable for sport fishing. Anglers have been known to travel great distances, spending lots of money on bait, lures, rods, and reels just to get a chance to catch one. Their delicate white meat is extremely yummy, but with the demise of two thirds of the spawning populations in the Bay of Fundy, Striped Bass require heightened conservation efforts. Conservation is necessary so our children and their children to enjoy this wonderful fish.
Striped Bass are an important component of the aquatic ecosystem, and contribute to the biodiversity and health of our marine environment. They feed on invertebrates and bait fish and are typically found in estuaries and coastal waters, although a proportion of Canadian Striped Bass often spend the winter in rivers or lakes. Striped Bass can be used as an indicator of ecosystem health because they require high-quality habitats and food sources for successful reproduction. It is uncertain how economically important Striped Bass are, but estimates suggest they have surpassed the salmon sport fishery in Nova Scotia.


SKU: LMNBCAAPL. Categories: Amino Acids, BOGO, Intra Workout, Smart Picks.
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Oriental Chicken Salad: a delicious salad that is perfect all year round! Grilled chicken and lots of veggies makes this for a healthier lunch recipe and one the family will love!
If you have ever been to Applebee's restaurant you are probably familiar with their popular oriental chicken salad. It's delicious and filling but has way to many calories someone should consume in one sitting. 🙂 The first time I had the salad at the restaurant I knew I need to re-create it and make it lighter for my family. I love salads all year round but I definitely eat more salads during the summer time but sometimes lettuce, tomatoes and other veggies can get boring so it's nice to add a different flavor or some protein.
This salad is one of my families favorites and is on our dinner menu quite often. It's super simple to put together and the dressing is delicious! We used natural honey to sweeten the dressing and light mayo to keep the calories down. A dash of sesame oil adds that asian pop to the dressing that we just love!
We use grilled chicken that has been cut into bite sized pieces to save calories from a breaded version.
Open a can of mandarin oranges and add a few on top of your salad for an added citrus flavor! My husbands loves them!
If you have the time, toasting your almonds before adding them to your salad brings out the nuttiness and adds another crunch to every bite.
You can use light mayo to save a few calories when making the dressing.
Use a pre made bag of coleslaw in place of the red cabbage, carrots and napa cabbage to put this salad together even faster!
My favorite part of this easy oriental chicken salad is the crunch from the almonds and chow mein that you get in every bite. The flavors are delicious and it's a nice change from a traditional boring salad.
Top with grilled chicken breast pieces and drizzle with dressing.
You can use a premade coleslaw mix in place of the red cabbage, napa cabbage and carrots for an even faster salad.


Preceeded by Season 1, the second main arc of Mega Man X: Unit 49 is reffered as Season 2. Next: Season 3.
New allies join the 49th Unit, while the Neo Maverick Army begins its "Fanfare Operations" and spreads panic through the world with countless simultaneous attacks. The Maverick Hunters know they cannot protect all the people and being reactive will not stop Saturn. Due to that, they spread in three different squads to intercept the major Maverick operations while a fourth squad goes in a mission to investigate a liquid metal engineering facility occupied by the enemy.


Need more controls or operations?
The cost of the paid versions is a one-time payment required to download it. The one-time payment gives you right to use the plugin in your websites for an unlimited time.


Bob has been custom woodworking for over 35 years. He finished a very large project 6 years ago which took him over a year to do. He was contracted to do all the woodwork in the entry area (including the elevators) of the old Union Building at 6301 Rockhill Road in Kansas City, Missouri.
Lenten/Advent 3D sets made out of church pews. We sold these to purchase the lower octave bells at Southminster Presbyterian Church. In 1 year we were able to purchase the full lower octave of bells (C3-B3) and 3 cases with the proceeds.
Pew crosses: Crosses made out of discarded pew wood.
Wooden stoppers for wine bottles shaped like bells.


text:
Lagence nationale de documentation (AND) est un service de renseignement zaïrois créé le  et dissous en 1997.

Cadre législatif et structurel

Par l'ordonnance 83-193 du  fut porté à création l'agence nationale de documentationau Zaïre. Le , une ordonnance modificative fut adoptée afin d'en préciser ses attributions et son fonctionnement interne, en ce compris: 1° "la recherche, l'interprétation et la diffusion des renseignements politiques, économiques, sociaux, culturels et autres intéressant la sûreté de l'État" ; 2° "la recherche et la constatation des infractions contre la sûreté de l'État, la surveillance des personnes suspectes d'exercer une activité de nature à porter atteinte à la sûreté de l'État" ; 3° "la police des étrangers" ; 4° "l'identification dactyloscopique des Zaïrois".

Dans ses objectifs primaires, l'AND était donc le service de renseignement intérieur et extérieur du régime du Président Mobutu, qui en avait légalement "l'autorité personnelle et directe". Sur le plan du fonctionnement quotidien, les départements de cet organisme (Secrétariat général, Services de documentation intérieur et extérieur)  étaient néanmoins supervisés par un Administrateur général, portant le titre de commissaire d'État, et deux Administrateurs généraux adjoints. D'obédience civile, ce service avait des missions différentes du Service d'Action et de Renseignements Militaires (SARM) qui était le corps de renseignement des armées et du contre-espionnage militaire.

En 1997, dans la foulée de l'arrivée au pouvoir du président Laurent-Désiré Kabila, l'AND a été dissoute et remplacée par l'Agence nationale de renseignements.

Activités

Régulièrement mise en cause comme les autres services de sécurité pour des atteintes à la presse, aux mouvements d'opposition ainsi qu'aux droits et libertés individuelles, l'AND était tour à tour un instrument de maintien du régime zaïrois face aux risques contestataires de la part de la population (généralisation des indicateurs jusque dans les entreprises privées et publiques) mais aussi de soulèvements orchestrés par des pays tiers, en particulier dans le cadre des jeux d'alliance de la guerre froide en Afrique (le soutien apporté à l'UNITA angolaise et la rivalité latente avec le régime pro-URSS de Brazzaville).

Après plus d'une décennie de contrôles et de répressions, l'AND s'est montrée incapable de prévenir, d'évaluer et de contenir la première guerre du Congo, à l'instar des autres services de sécurité zaïrois dont l'armée. Cet échec marqua également celui du régime et la fin de la République du Zaïre.

Anecdotes

 L'AND est soupçonnée par la journaliste Anna Miquel d'être à l'origine de la disparition en 1985 du journaliste-reporter français Philippe de Dieuleveult.
 Selon l'auteur Jean I. N. Kanyarwunga, l'antenne au Shaba de l'AND a été directement impliquée dans l'organisation du massacre en 1990 d'étudiants à l'Université de Lubumbashi.
 Honoré Ngbanda, ancien chef en exil de l'AND, est le dirigeant de l'Alliance des patriotes pour refondation du Congo, un mouvement d'opposition au président Joseph Kabila.

Notes et références

Voir aussi

Articles connexes
 Agence nationale de renseignements
 République démocratique du Congo
 Zaïre
 Mobutu
 Liste des services de renseignement
 Liste des polices secrètes

Liens externes
 L'Express, missions très spéciales, 26 janvier 1996, in Aero.net
 Giscard et Mobutu vus par les Americains
 La Conscience, Honoré Ngbanda : « L'Occident ne pourra plus imposer un président en RDC »

Zaïre
Service de renseignement


TechDirt reported earlier this week about an exchange between Rep. Louis Gohmert (R-TX) and Google Law Enforcement and Information Security Director Richard P. Selgado. The incident occurred during a hearing on the Electronic Communications Privacy Act (ECPA) held by the House Subcommittee on Crime, Terrorism, Homeland Security and Investigations.
It was also reported earlier this week that the CIA had reached a $600 million, 10-year deal with Amazon for cloud computing services.
In one instance, a lawmaker seems to have difficulty understanding the technology, and in another, a powerful government representative discusses his agency's use of data maximization with unlimited retention.
What should the privacy and security communities think and do about these types of issues?


text:
Кріттеркам ( — від «critter» — створіння, тварина, та «cam»(«camera») — камера) — це невеликий комплект інструментів, до якого входить фото- або відеокамера, і який можна прикріпити до дикої тварини для вивчення її поведінки в середовищі дикої природи. Кріттеркам National Geographic — це дослідницький пристрій, розроблений так, щоб його було легко одягати на тварин. В ньому поєднується відео- та аудіозапис, а також збір даних про довкілля, таких як глибина (в океані), температура та прискорення. Перегляд всієї цієї інформації «на живо» дозволяє дослідникам визначити, чим займаються тварини кожного дня. Кріттерками були винайдені морським біологом, фотожурналістом National Geographic — Грегом Маршаллом у 1986 році. З того часу такі механізми застосовувалися для вивчення понад 40 морських та наземних видів тварин.

Історія кріттеркамів

Поява наземного кріттеркаму дала можливість дослідникам спостерігати за тваринами та їхньою діяльністю точнісінько в той час, коли ця діяльність відбувалась. Спершу такі камери могли лише записувати дані та робити знімки, які мали бути переглянуті в майбутньому — після того, як камеру знімуть із тварини. Вперше появившись у 2001 році, камера була розміром з півдюйма (13 мм). Мала роздільну здатність у 340 ліній і чутливість навіть до 3 люксів. На той час вона працювала на дев'ятивольтовій батареї, що давало змогу робити короткотривалі документальні записи активності тварин, а також на фунтовій (454 г) батареї для спостереження за тваринами протягом одного тижня. Розмір таких батарей постійно зростав, а разом з ним — і тривалість запису. Уривки з відеозаписів, отриманих за допомогою цього методу, транслювалися в таких телепередачах як «Great White Shark» (), «Sea Monsters» () та «Tiger shark» (). Перший пристрій для вимірювання глибини був винайдений наприкінці 1800-х. Однак перший вимірювач глибини насправді був одягнений на тварину, а саме — на тюленя Ведделла в Антарктиці, — лише у 1964 році. Подальший розвиток у сфері зйомки у виконанні тварин — став можливим завдяки мікропроцесору, який разом із відеокамерою монтувався у спеціальний футляр для занурювання під воду, і прикріплювався до панцира довгоголової черепахи. Цей футляр і став відомим під назвою «Кріттеркам». У Грега Маршалла, винахідника пристрою, вперше виникла ідея створення Кріттеркама під час підводної прогулянки у Белізі. Під час одного занурення він зустрів акулу із рибою-причепою на ній. Тоді ж він усвідомив, що якби сконструювати камеру так, аби її можна було розмістити на тілі акули замість риби-причепи, то вчені змогли б досліджувати довкілля та поведінку акул без необхідності спускатися глибоко під воду самим. Тож він негайно розпочав працю над втіленням своєї ідеї в життя, при цьому отримуючи невеличкі гранти від Американського музею природознавства для підтримки фінансової бази його досліджень. Пізніше він забезпечив собі ще й грант від Національного географічного товариства, і розпочав розробку значно вдосконалених зразків свого першого пристрою, який він колись начепив на довгоголову черепаху. Ці прототипи були успішно встановлені на тіла акул та морських черепах. З часу початку виробництва, кріттерками використовувалися для вивчення підводного життя зелених черепах, горбатих китів, тюленів-монахів, рифових акул та багатьох інших морських тварин. При застосуванні у випадку імператорських пінгвінів, камера доводить власну користь тим, що знімає поведінку цих тварин навіть під льодом, в антарктичних водах, де жодна людина не змогла б пірнути і зробити запис вручну через надзвичайно низькі температури. Аби запевнити безпеку тварин, якщо щось погане стане відбуватися із камерою, дослідники мають змогу відчепити її від тіла тварини за допомогою дистанційного керування.

Кріплення кріттеркама
Методи кріплення кріттеркама відрізняються, залежно від виду тварини, на яку його треба одягти. Для того, щоб одягати його на дельфінів, китів або шкірястих черепах, використовуються спеціальні всмоктувальні чашки. При одяганні на тюленів та панцирних черепах — використовуються липучі стрічки та клапті клейкого матеріалу. На акул кріттерками кріпляться за допомогою прищіпок — до плавника — щоб пристрій залишався нерухомим, коли тварини пливуть. Упряжі у вигляді наплічників для кріплення кріттеркамів — одягаються на пінгвінів. Наземні тварини, такі як леви та ведмеді — носять спеціальні нашийники для кріттеркамів. Постійно проводяться досліди та покращення в надії розробити ще більш вдосконалений метод кріплення. Маршалл стверджував, що його дуже здивувало те, наскільки швидко тварини призвичаювались до відчуття пристрою, начепленого їм на спини. Хоча початкові твердження Грега Маршалла були такі, що камера не справляє негативного впливу, і не турбує ніяким чином природної поведінки тварин у їхньому типовому середовищі, пізніше він все-таки визнав, що довжина занурень 40-, 50-фунтових пінгвінів — зменшилася на 20%, після того як на них одягли упряж. При використанні із імператорськими пінгвінами, камера доводить власну корисність, знімаючи поведінку цих тварин під льодом, у антарктичних водах, де жодна людина не змогла б пірнути і виконати запис вручну через надзвичайно низькі температури. Аби забезпечити захист тваринам на випадок, якщо щось трапиться із камерою, вчені мають змогу від'єднати її від тулуба тварини за допомогою дистанційного керування.

Вплив кріттеркамів на ЗМІ та поп-культуру
У 2011 році Містицький акваріум та дослідницький інстут — відкрив виставку-подорож, фінансовану товариством National Geographic, під назвою «Кріттеркам: світ очима тварин». Періодичне видання під назвою «Insight on the News» опублікувало статтю, в якій стверджувалось, що команда науковців під керівництвом Клайда Ропера захотіла використати кріттеркам для зйомки та вивчення Architeuthis dux, гігантського кальмара. У 2003 році було встановлено, що кріттерками одягалися на 41 тигрову акулу, 3-х дюгонів, 3-х китових акул та 34-х черепах, а їхнім місцем проживання є австралійська затока Шарк та риф Нінґалӯ. Камера може занурюватись разом із кашалотами на глибину до 200 метрів і навіть залишатися неушкодженою в гурті косаток. 13-серійний телевізійний серіал, прем'єра якого відбулася на кабельному телеканалі National Geographic 17 січня 2004 року, транслював справжнє відео, зняте за допомогою тварин, оснащених кріттеркамом.

Кітті-кам
Натхненні відкриттями, виконаними в результаті використання кріттеркама для вивчення поведінки різних видів тварин, National Geographic та Університет Джорджії розпочали працю над новим проектом, який дає змогу спостерігати за поведінкою домашніх котів. Пристрій, за допомогою якого має відбуватися спостереження — отримав назву «Kitty Cam» («котяча камера»). Кітті-ками забезпечують креативне рішення для вирішення частих і контроверсійних питань щодо взаємодії та поведінки котів у їхньому довкіллі. В результаті спільних зусиль дослідників були зроблені відкриття, які визначають загальні фактори, що становлять загрозу для здоров'я домашніх котів, яким доступна можливість вільно бродити по вулиці. Один з головних таких факторів — відкритість для інфекційних хвороб.
Кітті-ками кріпляться до нашийників, які в свою чергу одягаються на котів — в той же спосіб, як і кріттерками на наземних тварин. Камери надзвичайно легкі й водонепроникні, і можуть навіть виконувати нічну зйомку завдяки можливості вмикання світла LED. У м. Атенс, Джорджія, шістдесят котів було забезпечено нашийниками з камерами, і таким чином були проведені спостереження за маршрутами та діяльністю котів в той час, як вони вільно гуляли вулицями протягом  7-10 днів. Експеримент повторювався багато разів і завдяки йому було отримано багато різних результатів — із різноманітних територій та пір року. Після першого експерименту кріттерками 55-ти котів принесли результати, придатні для перегляду й дослідження — із середньою тривалістю у 37 годин зйомки на одного кота. Щодо хижацьких нахилів котів — то зйомки показали, що 44% котів у Атенс полюють на диких тварин. Більшістю тварин, на яких полювали кішки — були різноманітні дрібні ссавці, рептилії та безхребетні. Дослідження виявили, що вуличні коти проявляють хижацьку поведінку протягом тепліших періодів року. Звичними факторами ризику, з якими стикалося використання кітті-камів — були переходи вулиць, зіткнення з іншими котами, поїдання/пиття речовин поза домом, дослідження водостічних систем, а також потрапляння у підвали, які могли б стати пасткою для кота.

Інше
На даний момент найменшою твариною, на яку одягали справжній кріттеркам, є все-таки імператорський пінгвін. Інформація та відеоматеріали, отримані за допомогою кріттеркама, були використані у документальному фільмі, який удостоївся нагородження Оскаром — «Марш пінгвінів» ().

У Музеї науки (Бостон), існує виставка на тематику кріттеркамів. Виставка невдовзі почне переїжджати до інших музеїв. Вона дасть людям змогу брати участь в інтерактивних показах та на власні очі побачити різноманітні моделі кріттеркамів.

Примітки

Посилання

 Про кріттерками  на вебсайті National Geographic.
 Кріттерками на кішках.
  Кріттерками на черепахах.
 Кріттерками на китах.
 Кріттерками на імператорських пінгвінах.
 Новини в сфері застосування кріттеркамів.
 Створення кріттеркаму для акули.
 Котячі кріттерками.

Фотокамери


text:
April 14, 2011 News & Politics | Chicago Reader at Forty
The year in Chicago history via the pages of the Reader
By Michael Miner @hottype
"The congressman's wife's bottom I was aiming right in the face of the critics. In a nutshell, boldness and lack of any shame or apologeticness is going to be the nature of the Sun-Times in '85."
—Editor Frank Devine, explaining a photo choice to the Reader's Paul McGrath. March 1, 1985
Most weeks the Reader ran a "reading" column, which was not a review but an essay hung from a book, and not necessarily a book that more than four people would ever read. Musicologist Kyle Gann was exhilarated by Joseph T. Shipley's The Origins of English Words: A Discursive Dictionary of Indo-European Roots.
After discussion of Joseph Pujol, the famous "petomane" who convulsed fin-de-siecle Paris with his musico-anal powers, we find farting for entertainment traced back to 430 AD in, no less, Saint Augustine's City of God: "There are those who can break wind backward so artfully you would think they sang" (xiv, 24). To "razz" someone, as in giving him the raspberry – imitating the expulsion of anal wind with the lips – comes from an abbreviated old cockney rhyme, one line of which ended with "raspberry tart." March 22, 1985
Our Man in Beirut-on-the-Lake
City Hall: How Low They Can Go
By Gary Rivlin
These were the days of 29-21, a white machine majority led by aldermen Vrdolyak and Burke attempting to stymie, confound, and discredit Harold Washington and his aldermanic coalition of reformers and party hacks whose constituents demanded fealty to the new mayor.
In 1992 Rivlin would dissect the era of Harold in the masterly Fire on the Prairie. But his first draft of this history was for the Reader. One garrulous source was Alderman Richard Mell. Here's Mell explaining to Rivlin why the 29 intended to vote down a bond issue proposal that would clearly be good for Chicago.
"There are some who believe that to get rid of Harold Washington is good government because we simply can't take four more years of him. Maybe someone can make the case that, in the long run, two years of not having this [bond] is worth ten years of politicial stability in this city. It's a legitimate position; arguably, not voting for this bond is in the best interest of this city."...
The 29 continue to block the bond issue, Mell said, because some of them fear that in 1987 Washington would use the public works project in his campaign against them. Washington would be wise to do so, Mell said, but added, "It's also a valid political view to try and prevent that scenario from happening."
How will Mell vote when the bond proposal comes up again? "To keep a caucus of people together...sometimes you have to compromise your own position. In fact, to keep people together on major issues, you have to vote for things you're not happy with...
"I will sacrifice a vote that probably won't be popular in my community for the good of the coalition."
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Cook County let eviction court go unrecorded for six months.
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Escalating violence and lack of police response put the city's homeless even more at risk 4
A string of fires and stabbings have many advocates worried, and challenges in reporting and investigating these crimes leave little hope for justice.
By Adam M. Rhodes | 01.15.21
Inside the fight for racial equity at SAIC 36
Current and former students, staff, and faculty at the top-ranked art school describe microaggressions, discrimination, and a failed anti-racism campaign.
By Kerry Cardoza | 01.06.21
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Lake Michigan's turbulent waters offer die-hard surfers a prime opportunity to shred some waves
By Kevin Warwick | 11.14.12
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This week's Chicagoan: Rosita Arvigo, master herbalist 3
"Anywhere there's a crack of dirt in the sidewalk, a medicinal plant will grow."
Listen to The Ben Joravsky Show 26
Les Grobstein knows the score 9
It ain't easy being the world's biggest sports fan.
A case of disappearing hoops in gentrifying neighborhoods 8
In the last decade the Chicago Park District has removed 12 of 16 basketball courts from neighborhoods that have doubled and tripled in value, further marginalizing communities facing displacement.
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one × = six Required Please enter the correct value.
phillips curve explained
Iran is Now a Full-Blown Crisis, Stage Set for $200 Oil
GDP Is a Lie – It's Time for a New Measure of Economic Growth
The Debt-Ceiling Debate: Three Federal Tax Increases That Could Save the U.S. Economy
By Dr. Kent Moors, Global Energy Strategist, Oil & Energy Investor • @KentMoors_OEI - February 8, 2012
Just when it looked like we could take a breather from the Strait of Hormuz, all attention is back on Iran.
There are three reasons for this - all happening within the last week:
First was Tehran's successful launch of a satellite, viewed by all in the region as being for military intelligence.
Second, in his toughest talk to date, Iranian Supreme Leader Ayatollah Ali Khamenei voiced defiance to Western sanctions and pledged open retaliation if they are instituted.
Finally, last Thursday, U.S. Secretary of Defense Leon Panetta expressed concern that, if matters continue, Israel could attempt an air-strike takeout of Iranian nuclear facilities within a month. Iran has been frantically moving essential components of its nuclear program underground to withstand such an attack.
All of this is, once again, leading to a rise in crude oil prices.
What's more, the EU decision to stop importing Iranian crude starting July 1 will cripple any chance Tehran has to combat escalating economic and political turmoil at home.
Yet Khamenei's defiant tone during his Friday prayer meeting speech indicates that Iran's religious leadership will not wait for the system to unravel.
And that is what makes this both a full-blown and an intensifying crisis.
Brinksmanship in the Straits of Hormuz
So what's being done?
Washington has little - leverage, save its ability to temper an immediate escalation by Israel (leverage the U.S. can still apply, at least for the moment). It also has some indirect influence on what the E.U. does.
Meanwhile, Saudi Arabia also is a wild card. It will not tolerate a nuclear Iran.
And yes, there are ample indications that American and Israeli intelligence have concluded Iran will achieve the ability to develop nuclear weapons in the next 18 to 24 months.
Some elements of that process will be available earlier, but remember: A weapon is of little value unless it can be controlled and delivered. The logistical and infrastructure considerations need to be in place first.
Yet with such an inevitable conclusion staring them in the face, the West has decided to embark on a risky path...
The target here is not the nuclear project at all (over which there is less and less outside control). Instead, it has become about creating massive domestic instability to bring down a regime.
Now, this is not about ending the theocracy. With or without Mahmoud Ahmadinejad as president or Ali Khamenei as supreme leader, Iran will remain a Shiite-dominated country. Religion decisively controls politics, and the clergy oversees the society.
The West is seeking a more moderate application of what will remain the Iranian cultural reality.
However, as the brinksmanship intensifies, so will the price of crude oil. Tehran, in this dangerous game of international chicken, really only has one card to play - the Strait of Hormuz.
There has been much misinformation circulated about the strait. Here are the facts.
On any given day, 18% to 20% of the world's crude oil passes through it.
According to the Energy Information Administration, the Strait's narrowest point is 21 miles wide; however, the width of the shipping lane in either direction is just two miles, cushioned by another two-mile buffer zone.
Of greater significance, though, is the fact that most of the world's current excess capacity is Saudi. (This is the oil that can be brought to market quickly to offset unusual demand spikes or cuts in supply elsewhere.) And, unfortunately, Saudi volume must find its way through the same little strait.
If we're unable to access the Saudi excess, that loss guarantees the global market will be out of balance. That will intensify the price upsurge - an upsurge that is already happening.
Now for the question I'm being asked several times a day in media interviews...
Just how bad can it get?
By Martin Hutchinson, Global Investing Specialist, Money Morning - August 23, 2011
Gross domestic product (GDP) is the most commonly used measure of economic growth. But GDP isn't just inaccurate and misleading - it's the contrivance of Keynesian economists seeking to push their own, big-government agenda.
That's right. GDP is a financial ruse - the biggest of the past half-century. And it's time to move past it to another, more accurate measure of economic growth.
Keynesian economist Simon Kuznets designed GDP at the height of the New Deal era. Kuznets first revealed the measure in a report to Congress in 1934. GDP takes into account consumption, investment and government expenditure to create a measure of economic growth.
But the Keynesians employed some chicanery, or sleight-of-hand, to generate this statistic. A close look reveals the dirty little secret about GDP: It intentionally overplays the importance of government spending - and in doing so inflates the role that Washington plays in each of our lives.
And it's been doing this for 77 years ...
The Biggest Lie of the 20th Century
Gross domestic product is supposed to be a measure of all the goods and services produced here at home.
But there's a discrepancy.
You see, private-sector output is measured by the price people are prepared to pay for it. But government output is fudged: It's measured by its cost.
That means GDP increases any time the government spends money. It doesn't matter if that money is actually put to productive use or not - GDP rises nonetheless.
The bureaucrat devising regulations that damage business? His salary increases GDP. The $300 million Alaskan "bridge to nowhere" of a few years back? That was $300 million added to GDP. The jet-fighter project that costs billions, and is plagued by huge overruns that lead to its cancellation? Those billions add to GDP.
Even public-spending "stimulus" programs, however foolish, are always effective according to the GDP definition, because their cost is simply added to output.
It's obvious why big-government Keynesians would like this calculation: It substantiates their claim that government spending stimulates economic growth.
In the real world, however, this makes no sense. Indeed, none of the examples above actually add to economic welfare.
Don't misunderstand - some government output is very valuable. We could not exist in a free society without a court system that protects our property rights and a national defense that protects our borders. In most other cases, however, if government output were truly cost effective, the private sector would've already taken the initiative (and probably done so at lower cost and greater impact).
So how can you get an accurate measure of economic growth?
Arithmetically, there's a simple solution: You take Line 1, "Gross Domestic Product," in the Bureau of Economic Analysis' GDP Table and subtract from it Line 21, "Government Consumption Expenditures andGrossInvestment. "
That gives you a net number, which we can call "gross private product," or GPP. It's a measure of all the output produced by the private sector. In general, it will underestimate national "welfare" unless government is really bad. But it will give you a much better idea of the output the market economy is producing.
Indeed, looking at GPP's past performance helps to explain some things that GDP doesn't.
Keynesians like to proclaim that World War II got America out of the Great Depression: Thus, if you make stimulus big enough, it will solve economic problems.
This is the biggest lie of the 20th century.
By Martin Hutchinson, Global Investing Specialist, Money Morning - July 8, 2011
As the debt-ceiling debate escalates, U.S President Barack Obama says federal tax increases are necessary to close the U.S. budget deficit.
Although Republicans then said that tax hikes were "off the table," this statement is reminiscent of a toddler who threatens to hold his breath until he turns blue if you make him eat spinach.
Given that our elected leaders in Congress just can't seem to curb their spending addiction, the unpleasant reality is that some types of tax hikes are essentially inevitable.
Truth be told, I can show you three tax increases that should be enacted.
As a taxpayer, that statement will probably make you wince in anticipated pain.
But once I've made my case, I'm betting that the investor in you will agree that these three federal tax increases could save the U.S. economic recovery.
Let's take a look ...
Federal Tax Increases We Don't Want to See
If we ignore the debt-ceiling debate (and the Aug. 2 deadline for increasing the ceiling) for a minute, and just consider the health and welfare of the U.S. economy, we can see that there are a number of federal tax increases that would be highly counterproductive.
One example: boosting the corporate tax rate above 35%.
Except for Japan, the United States already has the highest corporate tax rate in the Organisation for Economic Co-operation and Development (OECD). Corporations don't pay much tax because they are able to keep profits overseas in tax-free jurisdictions and employ leasing and other tax breaks. It would make much more sense to lower the corporate tax rate - perhaps to 30% - and close many of the loopholes so that the "yield" (what's actually collected) is the same or perhaps even a little higher.
Similarly, it makes no sense to increase the 15% tax on dividend income. Dividends are paid by corporations out of their after-tax income. The levy on dividends - paid by the company's shareholders - means those companies actually suffer from a "double-taxation" rate of about 47%.
This encourages companies to fool around with stock options, repurchase agreements and with overpriced acquisitions, thus ripping off ordinary shareholders and reducing the economy's efficiency.


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Q: Use Spread Operator on Object with Type Safety in Dart I would like to use the Spread operator (...) on key-value-data with type safety. In TypeScript I would achieve this with Interfaces, but I could not figure out a way of doing this in dart.
Failed approach 1: Use Classes
class Foo {
  int aNumber;
  String aString;
}

Foo a = Foo();
Foo b = { ...a, 'aString': 'ipsum' }; // This literal must be either a map or a set.

Failed approach 2: Use Maps
Map<String, dynamic> a = { 'aNumber': 2, 'aString': 'lorem' };
Map<String, dynamic> b = { ...a, 'aString': 'ipsum' }; // No error, but also no type safety.

Note: In these approaches, b should not be a list.
TypeScript Example of what I need
interface Foo {
  aNumber: number;
  aString: string;
}
const a: Foo = { aNumber: 2, aString: 'lorem' };
const b: Foo = { ...a, aString: 'ipsum' }; // Has all the props of 'a' and overrides 'aString' to 'ipsum'.

A: You can achieve it with the first approach, but you have two problems with the snippet:
First check that the spread operator is implemented in iterable, so the line Foo a = Foo(); should be replaced with some iterable, a list for example.
The second problem, the compile error on Foo b = { ...a }; is because Dart uses {} for both sets and maps, so you must specify the type by adding one or two type parameters within <>.
Check this example:
  var a = <Foo>[];
  var b = <String>[];
  var c = <Foo>{...a}; // works, a is Foo list
  var d = <Foo>{...b}; // compile time error, 'String' can't be assigned to the set type 'Foo'.

Since we use only 1 argument in var d = <Foo>{...b}; dart knows that we want a set.
UPDATE:
For this case you cannot use spread operator. Spread operator was introduced to make easy work with Collections, and collections have the type given by the generics parameters. So if your class doesn't implements Iterable you cant call ... on a given instance. You will get a compile time error:
Spread elements in list or set literals must implement 'Iterable'

On the other hand, as you mention the second approach "doesn't give you" type safety because you are using dynamic. And also ONLY compile because you are declaring Map<String, dynamic> a = { 'aNumber': 2, 'aString': 'lorem' };, wich is a map and implements Iterable (you can use ...a).
For your current problem you need to find a different solution, maybe a custom function on Foo class that returns a Map and take care of types, and then use spread operator on that map.
Hope it helps!

A: just adding my pinch of salt: I got this error when using smart quotes by mistake for my map keys (" instead of " - options+maj+quote on macOS). Replacing them with regular quotes did the trick

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