text:
\section{Introduction}
\label{sec:intro}

Automated decision making systems based on statistical inference and learning are increasingly common in a wide range of real-world applications such as health care, law enforcement, education, and finance. These systems are trained based on historical data, which might be biased towards certain attributes of the data points \cite{dwork2012fairness, hardt2016equality, celis2017ranking}. Hence, such data without noticing possible biases could result in discrimination, which is defined as gratuitous distinction between individuals with different sensitive attribute. These attributes include sex, race, religion, and are referred to as protected attributes in the literature.
As an example, in the US justice system, courts use features of criminals such as their age, race, sex, years being in jail, etc., to estimate their possible recidivism--future arrest. After considering these features, the court assigns a score to each in-jail individual, and decides on whether to release that person. If the score exceeds some certain limit, it will be safe to release that individual. For instance, as noted by Angwin et al. analysis \cite{angwin2016machine}, risk scores in the criminal justice system--the COMPAS risk tool--are biased negatively towards African-Americans. They showed that this risk score unjustifiably shows high risk of recidivism for African-American people compared to what it should actually be.
As another example, the authors in \cite{kay2015unequal} have studied the accuracy of gender representation in online image searches. The results indicate that for instance, in a Google image search for ``C.E.O.'', 11 percent of the depicted results are women, even though 27 percent of U.S. chef executives are women; and in a search for ``telemarketer'', 64 percent of the people depicted were female, while the occupation is evenly split between men and women.

There is an interesting connection between the problem of fairness and differential privacy \cite{dwork2008differential, dwork2006calibrating, kalantari2016optimal}. As in the differential privacy problem, one tries to hide the identity of individuals, in the fairness problem, the goal is to hide the information about the protected attribute. More details regarding this connection is presented in \cite{dwork2012fairness}.

Different criteria for assessing discrimination has been suggested in the literature. The most commonly used criterion is the so-called \textit{demographic parity}, which requires the predictor to be statistically independent from the protected attribute. That is, denoting the protected attribute and the prediction by $A$ and $\hat{Y}$, respectively, demographic parity requires the model to satisfy
\[
P(A,\hat{Y})=P(A)P(\hat{Y}).
\]
While demographic parity and its variants have been used in several works \cite{zemel2013learning, feldman2015certifying, zafar2017fairness, edwards2015censoring}, in some scenarios this criterion fails to provide fairness to all demographics \cite{dwork2012fairness}. For example, in the case of hiring an employee, where majority of the applicants are from a certain demographic, if we force the decision making system to be independent of that demographic, the system has to pick equal number of applicants from each demographic. Therefore, the system may admit a lower qualified individual from the smaller demographic to guarantee that the percentages of hired people from different demographics matches. Moreover, denoting the true label by $Y$, in most of the cases, as in the image search example, $Y$ is correlated with the protected attribute (see Figure \ref{fig:GM}). Therefore, as demographic parity forces $\hat{Y}$ to be independent of $A$, this criterion will not be satisfied for the ideal predictor $\hat{Y}=Y$.

Hardt, Price and Srebro have recently proposed \textit{equalized odds} as a new criterion of fairness \cite{hardt2016equality}. This notion demands that the predictor should be independent of the protected attribute conditioned on the actual label $Y$. Therefore, equalized odds requires the model to satisfy
\begin{equation}
\label{eq:EO}
P(A,\hat{Y}|Y)=P(A|Y)P(\hat{Y}|Y).
\end{equation}
Returning to the example of hiring an employee, this measure implies that \textit{among the qualified applicants}, the probability of hiring two people from different demographics should be the same. That is, if two people from different demographics are both qualified, or both not qualified, the system should hire them with equal probability. Also, note that unlike demographic parity, equalized odds allows for the ideal predictor $\hat{Y}=Y$.

In this paper, we present a new framework for designing fair predictors from data. We utilize an information theoretic approach to model the information content of variables in the system relative to one another. We use equalized odds as the criterion to assess discrimination.
In our proposed scheme, a data variable $X$, is first mapped to an auxiliary variable $U$, to decontaminate it from the discriminatory attribute as well as ensuring generalization.
To design this auxiliary variable, for input variable $X$ and true label $Y$, we seek to find a compact representation $U$ of $X$ that contains at most a certain level of information about the variable $X$ (to avoid overfitting), but maximizes $I(Y;U)$ (quality of decision). The auxiliary variable $U$ is in turn used as the input for the prediction task.
Similar to \cite{hardt2016equality}, our framework is only based on joint statistics of the variables rather than functional forms; hence, such a formulation is more general. Furthermore, as in many cases, the functional form  of the score and underlying training data are not public. Our formulation (unlike that of \cite{hardt2016equality}, for instance) allows both $A$ and $Y$ to have arbitrary cardinality, which implies that we can have multi-level protected attributes and labels.
We cast the task of finding a fair predictor as an optimization problem and propose an iterative solution for solving this problem.
We observe that the proposed solution does not necessarily converge for some levels of fairness. This suggests that for a given requirement on the accuracy of a predictor, certain levels of fairness may not be achievable.

A somewhat similar idea to our approach is presented in \cite{zemel2013learning}, in which the authors used an intermediate representation space with elements called prototypes. However, besides the fact that in that work demographic parity is used as the measure of discrimination, the method used for choosing the prototypes is quite different. Specifically, the main approach to avoid overfitting in the learning process is limiting the number of prototypes\footnote{Unfortunately, nothing is said in that work about choosing the number of prototypes.}, while we achieve the same goal by controlling the information in the auxiliary variable about the data.
The approach in \cite{zemel2013learning} has extended in \cite{louizos2015variational} with deep variational auto-encoders with priors that encourage independence between sensitive and latent factors of variation.

The rest of the paper is organized as follows.
In Section \ref{sec:model} we review the notion of equalized odds and introduce our model as well as the details of our proposed learning procedure.
Additionally, we propose the optimization that must be solved to address the fairness issue.
 In Section \ref{sec:solve} we propose an iterative approach for solving the optimization problem introduced. Our concluding remarks are presented in Section \ref{sec:conc}.

\section{Model Description}
\label{sec:model}

We consider a purely observational setting in which we train a predictor from labeled data.
For each sample, we have a set of attributes, which includes protected attributes such as gender, race, religion, etc.
The protected attributes are denoted by $A$. We use $X$ to denote the rest of the attributes.
We denote the true label by $Y$ and the prediction of the label $Y$ by $\hat{Y}$.
For instance, for the example regarding risk of recidivism explained in Section \ref{sec:intro}, $A$ represents the race of each individual, $X$ represents other features of that individual (which could be correlated to the individual's race) and $Y$ determines whether he/she has committed any crimes after being released from the jail.

\begin{figure}
    \centering
    \includegraphics[scale=0.55] {GM}
    \caption{Graphical model of the proposed framework. $A$, $X$ and $Y$ denote the protected attribute, the rest of the attributes and the true label, respectively. $U$ is the compressed representor of $X$, which is used for designing the prediction $\hat{Y}$.}
    \label{fig:GM}
    \vspace{-3mm}
\end{figure}

The graphical model of our setup is depicted in Figure \ref{fig:GM}. As seen in this figure, $X$ and $A$ can be correlated, and given $X$, $A$ is independent of the true label $Y$. This property is essential, otherwise, the protected attribute is in fact a direct cause of the label and using this attribute in the prediction process should not be considered as discriminatory.

In order to find a fair predictor, if the joint distribution $P(A,X,Y)$ was known, we could find $P(\Hat{Y}|X)$ close to $P(Y|X)$ in the sense of equalized odds. However in reality only the empirical distribution $\Hat{P}(A,X,Y)$, which is obtained from data is available; therefore it is required to make sure that the predictor generalizes.

\textit{Generalization}: Since the number of available samples is finite, to prevent overfitting (ensuring generalization) we should constraint our hypothesis space. To do so, we compress our variable $X$ to an auxiliary variable $U$, which in turn is used for the prediction task. We also choose $U$ such that it is not contaminated by discrimination in the sense of equalized odds \cite{hardt2016equality} defined in the following.
\begin{definition}
\label{def:EO}
[Equalized odds] We say that a variable $U$ satisfies equalized odds with respect to protected attribute $A$ and outcome $Y$, if $U$ and $A$ are independent conditional on $Y$, that is,
\[
I(A;U|Y)=0.
\]
\end{definition}
\noindent
This definition is equivalent to the one in expression \eqref{eq:EO}.

Once $U$ is decontaminated from discriminatory attribute $A$, one can use any predictor to predict $Y$ from this auxiliary variable. We propose to apply a Bayesian empirical risk minimization decision rule in this work for the prediction task.

 To obtain the mechanism for generating the auxiliary variable, we seek for a compact representation $U$ of $X$ that maximizes the utility/quality of prediction $I(Y;U)$, while it contains at most a certain level of information about the variable $X$.
This is in essence similar to the goal in the information bottleneck (IB) method \cite{tishby2000information}.
Maximizing $I(Y;U)$ corresponds to maximizing the utility of $U$, and keeping $I(X;U)$ bounded could be viewed as regularization, which rejects complex hypotheses to ensure generalization. See \cite{xu2017information} for a detailed discussion regarding using mutual information for finding bounds on generalization error.
Note that the fact that we present fairness, accuracy and compactness via mutual information, provides us with a setting in which we do not need to have any requirement on the cardinality of variables (as opposed to \cite{hardt2016equality, zemel2013learning}).

Next, we present the details of designing the transition probability kernel for generating the auxiliary variable, as well as designing the final predictor.

\subsection{Designing the Auxiliary Variable}
\label{sec:aux}
As stated earlier, the goal of our learning scheme is to produce a compressed representor of $X$, which has as much information about the true label as possible, and is fair in the sense of Definition \ref{def:EO}. We relax the equalized odds requirement in that we allow $U$ to have a certain amount of information about the variable $A$ conditioned on $Y$. The reason for this choice will become clear in Section \ref{sec:solve}.
Therefore, the objective is to find mechanism $P(U|X)$, which maximizes $I(U;Y)$ as well as
\begin{enumerate}
\item Ensures fairness: The information shared between the protected attribute and $U$ given the true label does not exceed a certain threshold $C$, that is
\[
I(A;U|Y)\le C.
\]
\item Ensures generalization: The mutual information in $X$ and $U$ does not exceed a certain threshold $D$, that is
\[
I(X;U)\le D.
\]
\end{enumerate}
Therefore, we aim to solve the following optimization problem.
\vspace{-2mm}
\begin{align*}
&\max_{P(U|X)} ~I(U;Y)\\
&\text{s.t. }~~~I(A;U|Y)\le C,\\
&~~~~~~~I(X;U)\le D.
\end{align*}

\subsection{Designing the Predictor}
\label{sec:hat}
As stated before, after obtaining a decontaminated variable $U$, this variable can be used for the prediction task. We utilize a Bayesian decision rule described in the following.

Let $\mathcal{U}$ be the alphabet of the variable $U$ and $\mathcal{Y}$ be the alphabet of variables $Y$ and $\hat{Y}$. To quantify the quality of a decision, define a loss function $\ell:\mathcal{Y}\times\mathcal{Y}\rightarrow\mathbb{R}^+$, where $\ell(\hat{y},y)$ determines the cost of predicting $\hat{y}$ when the true label was $y$. The decisions are based on auxiliary variable $U$, which is statistically related to the true label. We denote the decision rule by $\delta:\mathcal{U}\rightarrow\mathcal{Y}$. The loss of the decision rule $\delta$ is defined as follows.
\[
L(\delta)=\mathbb{E}_{U,Y}[\ell(\delta(U),Y)].
\]
Using $L(\delta)$, the Bayesian risk minimization decision rule is
\[
\delta^*=\arg\min_{\delta}L(\delta).
\]
For instance, for the case of binary labels with Hamming loss, defined as $\ell(y,\hat{y})=\mathbbm{1}[y\neq\hat{y}]$, we have
\[
\delta^*(u)=\mathbbm{1}\bigg[P(Y=1|u)\ge P(Y=0|u)\bigg],
\]
which implies that we vote for the label with the maximum posterior probability.

\section{Solving the Fairness Optimization Problem}
\label{sec:solve}

In this Section, we propose a solution for the fairness optimization problem presented in Section \ref{sec:model}.
The Lagrangian for this problem will be as follows\footnote{Throughout the paper, uppercase letters for the argument of a distribution indicate all the parameters of the distribution, e.g., $P(U|X) \equiv \{P(u|x), ~\forall u,x\}$.}
\begin{equation}
\label{eq:lag}
    \mathcal{L}(P(U|X)) = \alpha I(X;U) +\beta I(A;U|Y)-I(U;Y),
\end{equation}
where the parameters $\alpha$ and $\beta$ determine the trade off between accuracy, information compression, and fairness.

Equation \eqref{eq:lag} is similar to the objective function in \cite{chechik2003extracting}, where for given variables $X$, $Y^+$, and $Y^-$, the authors aimed to uncover structures in $P(X,Y^+)$ that do not exist in $P(X,Y^-)$, used for hierarchical text categorization.

We propose an alternating optimization method to solve the aforementioned problem. The pseudo-code of the proposed approach is presented in Algorithm \ref{alg:itt}.
In each iteration, $\mathcal{L}$ is reduced by minimizing objective function over three distributions $Q(U|X)$, $R(U)$, and $S(Y|U)$ separately. Functions $f(X,U,\alpha,\beta)$ and $Z(X,\alpha,\beta)$ are used for updating $Q(U|X)$, which are defined as follows:
\begin{equation}
\label{eq:Z}
Z(x,\alpha,\beta)=\sum_u R(u)\exp(f(x,u,\alpha,\beta)),
\vspace{-4mm}
\end{equation}
and
\begin{equation}
\label{eq:f}
\begin{aligned}
\begin{aligned}
    f&(x,u,\alpha,\beta)=\\
    &\frac{\beta}{\alpha}\sum_{y'} P(y'|x)D(P(A|x)||\frac{\sum_{x''}Q(u|x'')P(x,y,A)}{\sum_{x''}Q(u|x'')P(x,y)})\\
    &-\frac{1}{\alpha}D(P(Y|x)|S(Y|u)).
\end{aligned}
\end{aligned}
\end{equation}

\begin{theorem}
\label{thm:1}
For values of $\beta$ small enough, and any arbitrary value $\alpha$, Algorithm \ref{alg:itt} converges to a stationary point of the Lagrangian functions $\mathcal{L}$ given in equation \eqref{eq:lag}.
\end{theorem}
\noindent
See Appendix \ref{sec:Ap1} for a proof.

\begin{algorithm}[t]
\begin{algorithmic}
\STATE {\bf Input:} Empirical distribution $\hat{P}(A,X,Y)$, initial distributions $Q^0{(U|X)}$, $R^0{(U)}$, and $S^0{(Y|U)}$ parameters $\alpha$, $\beta$, termination threshold $\epsilon > 0$.
\STATE Initiate $\mathcal{L}^0=0$, $\mathcal{L}^1=\epsilon$, and $t=1$.
\WHILE{$\mathcal{L}^t-\mathcal{L}^{t-1}\ge\epsilon$\vspace{2mm}}
\STATE $Q^t(u|x)\leftarrow\frac{R^{t-1}(u)}{Z^{t-1}(x,\alpha,\beta)}\exp(f^{t-1}(x,u,\alpha,\beta))$, $\forall u,x$.\vspace{2mm}
\STATE $R^{t}(u)\leftarrow\sum_{x'} Q^t(u|x')P(x')$, $\forall u$.\vspace{2mm}
\STATE $S^t(y|u)\leftarrow\frac{1}{R^t(u)}\sum_{x'} Q^{t}(u|x')P(y,x')$, $\forall u,y$.\vspace{2mm}

\STATE $\mathcal{L}^{t+1} \leftarrow\alpha I(X;U) +\beta I(A;U|Y)-I(U;Y)$.\vspace{1mm}
\STATE $t=t+1$.\vspace{1mm}
\ENDWHILE
\STATE {\bf Output:} Conditional distribution $Q(U|X)$.
 \caption{Designing the conditional distribution of $U$.}
 \label{alg:itt}
\end{algorithmic}
\end{algorithm}

In general there is no guarantee that Algorithm \ref{alg:itt} converges to the global minimum of the Lagrangian. Nevertheless, experimental results show that this altenative optimization algorithm almost always converges to a local minimum of the objective function in \eqref{eq:lag}. Note that since achieving the global optimum is not guaranteed, one should initiate the algorithm from several different starting distributions.

The fact that convergence occurs only for a certain range of values for parameter $\beta$, suggests that for a given requirement on the accuracy of a predictor, certain levels of fairness may not be achievable.
This can imply an inherent bound for the level of fairness that any algorithm can achieve, a conclusion which could have not been obtained from the other existing works.
\vspace{-2mm}
\section{Conclusion}
\label{sec:conc}

We studied the problem of fairness in supervised learning, which is motivated by the fact that automated decision making systems may inherit biases related to sensitive attributes, such as gender, race, religion, etc., from the historical data that they have been trained on.
We presented a new framework for designing fair predictors from data via an information theoretic machinery.
Equalized odds was used as the criterion for discrimination, which demands that the prediction should be independent of the protected attribute conditioned on the actual label.
In our proposed scheme, a data variable is first mapped to an auxiliary variable to decontaminate it from the discriminatory attribute as well as ensuring generalization.
We modeled the task of designing the auxiliary variable as an optimization problem which aims to force the variable to be fair in the sense of equalized odds and maximizes the mutual information between the auxiliary variable and the true label, whilst keeping the information that this variable contains about the data limited.
We proposed an alternative solution for solving this optimization problem.
We observed that the proposed solution does not necessarily converge for some levels of fairness. This suggests that for a given requirement on the accuracy of a predictor, certain levels of fairness may not be achievable.
The final predictor is obtained by applying a Bayesian decision rule to the auxiliary variable.
Finding an exact bound on the achievable level of fairness, as well as applying the proposed method to real data is considered as our future work.

\appendices
\section{Proof of Theorem \ref{thm:1}}
\label{sec:Ap1}
The Lagrangian in equation \eqref{eq:lag} can be written as follows:
\begin{equation}
\label{eq:prf2}
\begin{aligned}
\mathcal{L}(P(U|X))=&\alpha \sum_{x,u}P(x) P(u|x)\log\frac{P(u|x)}{P(u)}+\beta G(P(U|X))\\
&+\sum_{x,u,y}P(x,y)P(u|x)\log\frac{P(y|x)}{P(y|u)}-I(X;Y),
\end{aligned}
\end{equation}
where
\[
\begin{aligned}
&G(P(U|X))=I(A;U|Y)\\
&= \sum_{a,u,y,x} P(u|x)P(a,y,x) \log \frac{\sum_{x'}P(u|x')P(x',y,a)}{\sum_{x'}P(u|x')P(x',y)}.
\end{aligned}
\]
We note that, the only unknown parameters are $P(U|X)$, and all of the other distributions can be estimated from the given samples of $(X,Y,A)$.\\
Changing the notation of $P(u|x)$ to $Q(u|x)$ (to emphasize that it is designed), and  using \cite[Lemma 10.8.1]{cover2012elements}, we can write the optimization as follows:
\vspace{-2mm}
\[
\begin{aligned}
&\min_{Q(u|x)}\mathcal{L}(Q(U|X))=\min_{Q(u|x)}\Bigg[\alpha \sum_{x,u}P(x) Q(u|x)\log\frac{Q(u|x)}{P(u)}\\
&+\beta G(Q(U|X))
+\sum_{x,u,y}P(x,y)Q(u|x)\log\frac{P(y|x)}{P(y|u)}\Bigg] - I(X;Y)
\end{aligned}
\]
\[
\begin{aligned}
&=\min_{Q(u|x)}\Bigg[\min_{S(Y|U)}\min_{R(U)}\big[\alpha \sum_{x,u}P(x) Q(u|x)\log\frac{Q(u|x)}{R(u)}\\
&+\beta G(Q(U|X))
+\sum_{x,u,y}P(x,y)Q(u|x)\log\frac{P(y|x)}{S(y|u)}\Big]\Bigg] - I(X;Y),
\end{aligned}
\]
where the inner minimizations are over all probability distributions.
Changing the order of three minimizations, we obtain
\begin{equation}
\label{eq:finop}
\begin{aligned}
&\min_{S(Y|U)}\min_{R(U)}\min_{Q(u|x)}\alpha \sum_{x,u}P(x) Q(u|x)\log\frac{Q(u|x)}{R(u)}\\
&+\beta G(Q(U|X))
+\sum_{x,u,y}P(x,y)Q(u|x)\log\frac{P(y|x)}{S(y|u)} - I(X;Y).
\end{aligned}
\end{equation}
Since $x\mapsto x\log x$ is a convex function, and summation of a convex function with a linear function remains convex, the first and the third terms of equation \eqref{eq:finop} combined is a convex function of $Q(u|x),~ \forall u,x$. For any function $G(Q(U|X))$, there exist $\beta$ small enough such that the combination of the first three terms of equation \eqref{eq:finop} remains convex with respect to each $Q(u|x),~ \forall u,x$.

We add one more term $\lambda(x)(\sum_{u}Q({u|x})-1), ~\forall x$ to the Lagrangian for the constraint that for each $x$, $Q({u|x})$ should sum up to 1.
As a result, taking the derivative of this function with respect to $Q(u|x)~ \forall u,x$, and setting it equal to zero, the minimum of the function can be found. Below, the derivative of each term is taken separately:

\[
L_1=\sum_{x',u'}P(x')Q(u'|x')\log\frac{Q(u'|x')}{R(u')}.
\]
Therefore,
\begin{align*}
\frac{\partial L_1}{\partial Q(u|x)}&=P(x)\log\frac{Q(u|x)}{R(u)}
+\sum_{x',u'}P(x')\times\delta_{uu'}\delta_{xx'}\\
&=P(x)\log\frac{Q(u|x)}{R(u)}+P(x).
\end{align*}

For the second term in $\mathcal{L}$ we have
\begin{align*}
L_2&=I(A;U|Y)\\
&=\sum_{a',u',y',x'} P(a',u',y',x')\log\frac{P(u'|a',y')}{P(u'|y')}.
\end{align*}
Due to the graphical model in Figure \ref{fig:GM}, we have
\[
P(a',u',y',x') = P(a')P(x'|a')Q(u'|x')P(y'|x'),
\]
\begin{comment}
\[
P(u'|a',y') = \frac{1}{P(a',y')}\sum_{x''} P(y'|x'')Q(u'|x'')P(x''|a')P(a'),
\]
\[
P(u'|y') = \frac{1}{P(y')}\sum_{x''} P(y'|x'')Q(u'|x'')P(x'').
\]
\end{comment}
Therefore,
\begin{align*}
\frac{\partial P(a',u',y',x') }{\partial Q(u|x)}
= P(a')P(x'|a')\delta_{uu'}\delta_{xx'}P(y'|x').
\end{align*}
\begin{comment}

\begin{align*}
\frac{\partial P(u'|a',y') }{\partial P(u|x)}
=\frac{1}{P(a',y')} P(y'|x)\delta_{uu'}P(x|a')P(a'),
\end{align*}
\[
\frac{\partial P(u'|y') }{\partial P(u|x)} = P(x|y')\delta_{uu'}.
\]
\end{comment}
The derivative of $P(u|a,y)$ and $P(u|y)$ can be obtained similarly. Therefore, we have

\begin{align*}
&\frac{\partial L_2}{\partial Q(u|x)}
=\sum_{a',y'} P(y',x)P(a'|x)\log\frac{P(a'|y',u)}{P(a'|y')}\\
&=-\sum_{y'}P(y',x)D(P(A|x)||\frac{\sum_{x''}Q(u|x'')P(x,y,A)}{\sum_{x''}Q(u|x'')P(x,y)})\\
&+\sum_{y'}P(y',x)D(P(A|x)||P(A|y))
\end{align*}
For the third term in $\mathcal{L}$ we have
\[
L_3=\sum_{u',y'}P(u',y')\log\frac{S(y'|u')}{P(y')}.
\]
Therefore,
\begin{align*}
\frac{\partial L_3}{\partial P(u|x)}=&-P(x)D(P(Y|x)||S(Y|u))\\
&+P(x)D(P(Y|x)||P(Y)).
\end{align*}
Summing up all terms of the derivative and setting it equal to zero, we get the desired result in \eqref{eq:Z} and \eqref{eq:f}.

Using the calculated $Q(u|x), ~\forall u,x$, we can minimize over $R(U)$ and $S(Y|U)$. Again using \cite[Lemma 10.8.1]{cover2012elements}, minimum is achieved in marginal distributions $P(Y|U)$ and $P(U)$, which can be found from $Q(U|X)$ according to Algorithm \ref{alg:itt}.

Regarding convergence, we note that the Lagrangian in equation \eqref{eq:lag} could be written as follows
\begin{align*}
\mathcal{L}&
= \alpha \mathbb{E}_{X}[D(P(U|x)||P(U))]\\
&+\beta \mathbb{E}_{A,Y}[D(P(U|a,y)||P(U|y))]\\
&+\mathbb{E}_{X,U}D(P(Y|x)||P(Y|u))\\
&-I(X;Y).
\end{align*}
Since the first three terms of $\mathcal{L}$ are linear combinations of KL-divergences, and hence non-negative, $\mathcal{L}$ is lower bounded by $-I(X;Y)$ which is a constant. In addition, in Algorithm \ref{alg:itt}, assuming small enough $\beta$, in each of three steps of the alternating algorithm, the value of $\mathcal{L}$ decreases. Therefore, there exists $\beta_\max$, such that for values of $\beta\le\beta_\max$, the algorithm converges to a stationary point of the objective function in \eqref{eq:lag}.

\section*{Acknowledgment}

This work was in part supported by MURI grant ARMY W911NF-15-1-0479, Navy N00014-16-1-2804 and NSF CNS 17-18952.

\bibliographystyle{IEEEtran}

redpajama_set_name: RedPajamaArXiv


text:
by David Lennon via twitter 9/25/2014 10:25:09 PM
We've got a bunch of pregame fan photos from around Yankee Stadium as the game draws near:
by Nick Klopsis 9/25/2014 10:27:37 PM
One last look at Derek Jeter's retirement gifts before we add to this gallery over the weekend in Boston
Derek Jeter retirement gifts - Newsday
NewsdayA look at the gifts given to Jeter during his farewell tour.
How many Jeter-related stories tomorrow will lead with some form of "It couldn't rain on Jeter's big day" approach?
Fun fact: Today would have been Phil Rizzuto's 97th birthday.
by Newsday Sports 9/25/2014 10:39:01 PM
Career hit No. 3,408 for Derek Jeter came off tonight's starter Kevin Gausman
For the first time in many years, the Yankees will not make their rookies dress up in costumes this year in a "hazing" ritual.
by New York Yankees via twitter 9/25/2014 10:43:48 PM
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Jeter currently has 3,461 career hits. How many do you think he'll finish with?
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Get a glimpse of each of those hits here.
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Will Derek Jeter play this weekend in Boston? "I'm not thinking about Boston," he said. "Right now I'm thinking about today. Let's just go through today first, then I can give you what our plan is for Boston."
by frankwhyte85 via Instagram 9/25/2014 10:57:06 PM
by Greg Zaccheo via Instagram 9/25/2014 10:57:14 PM
Derek Jeter on the field with teammates for pre-game warmups
Oh, how wish I could be watching this game tonight!
by fan1224 9/25/2014 11:00:54 PM
My 3 favorite things about all the old clips being shown of Jeter this past week:
3) That duck-bill haircut he had.
2) Non-baggy uniforms on players.
1) Phil Rizzuto as the analyst
A little fun fact amid all the Jeter tributes: Tonight is the last night that the late Bob Sheppard's voice will announce a player at Yankee Stadium.
Jeter is on the field now, along with his teammates, as Hiroki Kuroda makes what likely will be his final career start at Yankee Stadium
And the first pitch of the Jeter finale is a ball in the dirt by Kuroda.
Here comes the JEter roll call.
And it's dampened quickly by a Markakis leadoff home run.
Orioles 2, Kuroda 0.
At this rate, Jeter may not make it 5 innings, let alone Kuroda.
One of the fans on the video tribute to Jeter was wearing an Orioles hat. #edit
by Miguel Ángel Cárdenas via Instagram 9/25/2014 11:14:56 PM
by Scott Salling via Instagram 9/25/2014 11:15:02 PM
by Joe Seman via Instagram 9/25/2014 11:15:13 PM
The Empire State Building will be lit in its signature white. Sorry, Jeter fans. No Yankee Blue for Jeets.
That large ovation you hear is not for Gardner's single
. It means Jeter is about to come to the plate.
Jay Z in the house for Jeter night. Sorry, Hovah, but Jeter made the Yankee hat more famous than you did.
Always admired Jeter's ice in the veins. He didn't even step out of the box and give a nod to fans cheering his name tonight in his first at-bat.
Gausman wants no part of Jeter here. 3-0 count. Doesn't want to give up career hit 3,462 after giving up 3,408.
Jeter rips a 3-1 double off the wall in left-center. Missed a home run by just a few feet.
granted this game has no postseason implications, but Jeter always managed to rise to the occasion. Remember that 5-for-5 day on his 3,000th hit day.
Jeter takes third on a passed ball. Slides in feet first. No injury. Yankee fans will get more innings of Jeter tonight.

redpajama_set_name: RedPajamaCommonCrawl


I recently began using the Other World Computing (OWC) ThunderBay 4 unit to add external RAID storage to my 2013 Mac Pro. As you may know, the 2013-2017 Mac Pro has limited internal storage due to its "innovative" design and the limitations presented by the computer bus itself (no second SSD possible). So, adding external Thunderbolt 2 storage is almost a requirement if you do anything interesting with your Mac Pro.
My ThunderBay 4 was acquired as a New-Demo unit and it came equipped with four (4) 3TB Toshiba drives and a SoftRAID software-RAID license. Because this chassis doesn't include hardware RAID support, it's a little more flexible and cost-effective than full-hardware-RAID versions.
The unit arrived quickly and came pre-configured with RAID 5, which allows the 12TB unit to have 9TB of usable space. I removed and reseated each drive and powered up the unit. While the Toshiba drives have a wide-range of online ratings and comments, I found them reasonably quiet, but the ThunderBay front panel had an occasional vibration that stopped when I touched it. The use of a self-adhesive pad to inhibit vibration would make sense there.
The SoftRAID product needs to be installed on your Mac, and there are trial versions on the SoftRAID.com website. I experimented with the Trial version while I waited for my delivery, and input the serial number from the ThunderBay 4 case sticker once that arrived. A new download then installed a ThunderBay-limited non-trial version of SoftRAID, and that will be fine for most people. I opted to upgrade to the full version, not ThunderBay-limited, and that was an additional US$99 for the upgrade, and involved an additional download and install.
I did a fair amount of research on different RAID levels because it had been some time since I considered which RAID level to use, and disk space has expanded significantly in that time. After a fair amount of reading (lots of opinions), I opted to reconfigure the TB4 as RAID 1+0, often quotes as the safest RAID if you worry about data loss. After running storage benchmarks using the Blackmagic Disk Speed Test, I decided that RAID 1+0 was not providing the performance levels I expected. Further reading pointed out that RAID 1+0 does not use a Write cache. My Write throughput was 350MBps, which was far below the advertised 550MBps of the hardware. At this point it was obvious I needed to go back to RAID 5. The advantages of more space (9TB versus 6TB) and better performance ( +40% ) more than offset the perceived risk of data loss in a power failure event. I am on UPS, anyway, and have seen the switch-over go flawlessly. What really impressed me was how little time it took to make the switch.
Switching from one RAID level to another means wiping out your data, usually. There are Conversions you can do, from RAID 0 to RAID 1+0, without data loss, but a switch from RAID 1+0 to RAID 5 wipes out your data. So you need to backup and restore your data. I used Carbon Copy Cloner (CCC) to do this to an ancient WD MyBook over Firewire 800 (using an Apple TB-FW adapter) and things went flawlessly. The RAID change itself took very little time, and the restore of the backup with CCC was flawless.
So, what do I think? As a person who has used Network Area Storage (Netgear ReadyNAS) and hardware-RAID for years, I'm impressed. I can launch large virtual machines from the TB4 and not feel like I'm waiting and waiting and waiting. The difference between a 20Gbps TB4 and a 1Gbps Ethernet connection is obvious, and you can certainly feel it. With Thunderbolt 3 emerging, you can imagine six-bay units are about to roll out, too.
Some math for Thunderbolt. Thunderbolt 1 was two (2) 10Gbps channels. Thunderbolt 2 combined those two channels into a single 20Gbps channel. Four (2) SATA drives, each of 6Gbps, would have theoretical throughput of 4×6 or 24Gbps, so having a 20Gbps interface to four drives makes a lot of sense.
SoftRAID payments are through OWC Holdings, so you can imagine there is some relationship there. I was disappointed to find the TB4-included license limited to ThunderBay units, but upgrading that limited license to a full license was a financial wash. I just think OWC should highlight that the included license is limited to better manage your expectations.
One side note: the SoftRAID "Certify" command is outstanding, and you should run this on any drive you intend to use for long-term storage. It will make two painfully slow passes through your disk writing random patterns to the storage and reading them back to make sure they are correct. Then a third-pass is written as zeroes. I have a 50% pass rate on the discks I have in my spares and I label them SoftRAID Certified and know to use the others as scratch temporary disks. Nice feature, but it can take days to do a large disk. Be patient.
I will provide updates as I gain more experience with the OWC ThunderBay 4 and SoftRAID, but it seems to "just work". Pretty simple.


text:
Fate/kaleid liner Prisma☆Illya 3rei!!
Synonyms: Prisma Illya 3rei!!
Japanese: Fate/kaleid liner プリズマ☆イリヤ 3rei!!
Aired: Jul 6, 2016 to Sep 21, 2016
Premiered: Summer 2016
Broadcast: Wednesdays at 23:00 (JST)
Producers: Lantis, Kadokawa Shoten, AT-X, DAX Production, KlockWorx, Tokyo MX, Kadokawa Media House, Plus One
Studios: Silver Link.
Genres: Action, Comedy, Magic, Fantasy
Ranked: #12702
Fate/kaleid liner Prisma☆Illya...
Ranked #1270Popularity #1415Members 69,778
Summer 2016TVSilver Link.
Add to List Select(10) Masterpiece(9) Great(8) Very Good(7) Good(6) Fine(5) Average(4) Bad(3) Very Bad(2) Horrible(1) Appalling
Episodes: /12
PV 3
Illya and the gang have finished their battle against the heroic spirit residing in the eighth class card. They're back in vacation mode again, looking to make the most of what they have left of summer break. But their hopes get crushed in the blink of an eye.
An all-too-unrealistic silhouette appears before them when they go to investigate the strange event at Mount Enzou. After a short skirmish, the entire space ends up being warped. Illya wakes up in a wintry Fuyuki City... in a parallel world.
This is the world where Miyu was born and raised.
No background information has been added to this title. Help improve our database by adding background information here.
Adaptation: Fate/kaleid liner Prisma☆Illya 3rei!!
Prequel: Fate/kaleid liner Prisma☆Illya 2wei Herz!
Side story: Fate/kaleid liner Prisma☆Illya 3rei!! Specials
Sequel: Fate/kaleid liner Prisma☆Illya Movie: Sekka no Chikai
Characters & Voice Actors
Endou, Aya
von Einzbern, Illyasviel
Kadowaki, Mai
von Einzbern, Chloe
Saito, Chiwa
Edelfelt, Miyu
Nazuka, Kaori
Toosaka, Rin
Ueda, Kana
Emiya, Shirou
Sugiyama, Noriaki
Kotomine, Kirei
Nakata, Jouji
Matou, Sakura
Shitaya, Noriko
Edelfelt, Luviagelita
Itou, Shizuka
Fraga McRemitz, Bazett
Nabatame, Hitomi
Oonuma, Shin
Jinbo, Masato
Takahashi, Ken
Tsuchiya, Masaki
Edit Opening Theme
"Asterism" by ChouCho
Edit Ending Theme
#1: "WHIMSICAL WAYWARD WISH" by TECHNOBOYS PULCRAFT GREEN-FUND feat. Yumeha Kouda (eps 1-8, 10-12)
#2: "Cuddle" by ChouCho (ep 9)
More reviewsReviews
12 of 12 episodes seen
-Darkbolt- (All reviews)
Overall 8
Enjoyment 10
Completely spoiler-free review.
TL:DR section is at the bottom
Story: 7/10
This season has a very good story compared to its earlier seasons + loli-service. Sometimes the comedic scene comes at an unnatural spot, eg a close friend dies and then protagonist thinks "I wonder if I should throw this body to the sewage..."
Art 10/10
Art is just amazing but to behonest I just read the subtitles so I couldn't look at the background that much.
Only if the dubs would be better... (If you've heard the dubs on the earlier series you will agree with me.)
Sound 3/10
Intro, outro, ost were pretty bad, and they used the same music over and over again. It's like listening to Gangnam Style 24/7. (If you do listen to Gangnam Style 24/7 I'm sorry, but have you considered going to a psychologist?)
Character 9/10
Lolis.
Enjoyment 10/10
Comedy 10/10, Fanservice 10/10. Love Nakata-san. Shirou-san should be castrated because of harem. Kiss Kuro.
Story is good.
Art is amazing.
Same soundtrack is being used over and over again.
Loli-service.
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BanjoTheBear (All reviews)
Enjoyment 0
(This review has been adapted from my blog/reddit thread. Spoilers ahead!)
I've only "acted" in a "play" one time, and it is one of the most embarrassing moments of my life.
It was a small presentation within our English class. I took on the role of Jesus as he carried his cross to his inevitable death. But I had no beard. No robes. No sandals. Even the cross was just a meter stick. In short, I looked like any other nerdy, lanky teenager with glasses, a polo, and a pair of jeans.
So, there I am, starting at the back of the class, pretending to fumble and trip and hurt as I make my way to the front. Everyone stared at this bumbling, dumb high-school kid who couldn't even properly hold a marked piece of wood – and I wanted to run away from this whole ordeal.
Fate/kaleid liner Prisma☆Illya 3rei!! features a host of villains who believe that they are in a play of sorts themselves. But, while nothing the anime does is to the same level of embarrassment as my "performance," it seems that it, too, does not deserve an encore.
3rei (need to shorten it per usual) resumes right where 2wei Herz left off. Illya, Miyu, and Kuro finish their summer-vacation homework – only to have Rin and Luvia summon them for yet another magical happening. However, everything goes immediately wrong when strange new foes kidnap Miyu, and Illya finds herself in a familiar yet unknown world.
This season marks the fourth in the series. A feat that not many anime can claim to hold. Like its other seasons, this one focuses on a fresh plot, featuring both new and old characters alike – as well as one that seems uncannily similar.
3rei, though, in a welcome move, goes back to its first-season roots. Where 2wei focused mostly on Kuro, and 2wei Herz was almost entirely slice-of-life shenanigans, this season focuses mostly on Illya while melding the slice-of-life antics with its drama and action.
Episode seven and eight are a perfect example. Illya's stuffed-animal predicament is beyond ridiculous, but the combination of her weak magic against the possessed Rin and Luvia, which later turns into her fighting for her life alongside Kuro to save Miyu, is both hilarious and intense.
The anime also takes its Fate franchise connection to heart more so than usual. Kirei appears, running a local ramen shop. Sakura's yandere tendencies come to light. And Rin uses her rare, red life gem on Shirou to save his life. This series has always had these references, from the setting's city to the characters themselves, but it seems apparent throughout 3rei that, like its plot, it wants to stick with, well, sticking with its roots.
So, why all the roots? It deals with what much of the narrative centers on. The plot of the anime centers on saving Miyu who has gone back to her roots (against her will). Gil wants to get his item back to go back to his roots. The Ainsworth family wants to save the Earth to bring humanity back to its roots. Illya fights to bring back her best friend, her life in general back to her roots. Miyu wants to help her Shirou (and vice versa) to bring their lives back to their roots.
In a sense, 3rei is about bringing it all back to normal. While this theme is not explored, it has ties to the not-so-normal situations they find themselves in as well as the notion that life is simply better when it is familiar and whole (which the setting can Illya finds herself in can attest to). Thus, seeing this (small) throughput in many of the plot's events bolsters the anime.
What the plot contains, though, does not measure up well. One of the major issues is how many of the fights resolve. More specifically, how they don't. Almost all of them involve an interruption of some kind: told to stop, phone call, don't pursue when they can, Ainsworth father just walks away after Tanaka says something. It makes each encounter worthless since a meaningful outcome nearly never occurs.
The anime also has some overly convenient plot points that push the narrative along in an eyebrow-raising manner.
In episode three, Illya just-so-happens to find Ruby stashed away amongst the thousands of other weapons, and, immediately afterwards, she randomly gains the power to use the cards they have been chasing these past three seasons.
Gil going away briefly when the Ainsworth family's daughter and father arrive is not as convenient a moment, but it still comes off as unnatural.
And Tanaka throwing her flaming sword arm (literally) is technically foreshadowed by the constant mentions of her warmth and ability to sustain massive amounts of damage. Yet getting the weapon, that ultimately saves everyone, out of nowhere and only because Tanaka woke up at the opportune time, makes for a less-than-fair development.
Even the motivation behind the plot doesn't work. Last season, it boiled down to "save Miyu." This season, it also boils down to "save Miyu." Yes, the dilemma this time is to a much higher degree than last time, but, when the plots at their core are almost the same back-to-back, it makes 3rei seem as though it does not know what else it wants to do (which is somewhat understandable being four seasons in).
Its action sequences at least hold up well. Angelica using Gil's Noble Phantasm against him. Illya personifying Lancer, Rider, and Saber as she dukes it out with Kuro. And the entire final battle (Shirou's "Trace…on!", Illya performing "Excalibur!", Kuro coinciding with the Archer mindset). These are just a few examples that not only further highlight 3rei's Fate roots but also present some really cool battles.
And the "twist" – that Illya and the gang are the "bad guys" in that they want to save Miyu and therefore doom this world to death – gives 3rei some much-needed intrigue. Granted, the villains are still overly evil, like when the father (awkwardly) spanks Erica to punish his child or when Beatrice goes psycho during the fights. Meaning, it's clear that Illya is still in the right and their enemy is still in the wrong. But it was a nice change to the plot.
3rei somewhat punches itself, though, when Illya declares how she'll save both Miyu and this world. But it's at least a very magical-girl stance if there ever was one. Which, once again, demonstrates 3rei going back to its roots.
Not much else can be said about the art and the animation that has not already been reiterated for these past few seasons.
The dreary city is a bit dull, and both the snowbound school and the open crater do not contain much in terms of detail. But the summer-sitting castle and the different magical backgrounds do what they can to make up for the general lack of intrigue.
The battles help with this, too, persisting in their flashiness thanks mostly to the Noble Phantasms wielded all over the place. Beatrice's Mjolnir, with its intense lightning effects, is a prime example of how over the top the particle effects and extravagance can go.
Character designs for the main cast (perhaps obviously) remain just as pretty per usual. Kuro's dark skin and multi-colored eyes, Illya's numerous transformations, and Miyu's damsel-in-distress black dress continue to impress.
Not to be outdone, the newcomers are likewise impressive.
Angelica's attractive design: white blouse, long skirt, long blonde hair, ample figure, golden armor with red tattoos and a bikini to boot (when fighting with Gil's Noble Phantasm).
Beatrice gnashes her spiky teeth and glares with her creepy yellow eyes while wearing a black, white, and red outfit with fiery twin-tails for hair.
And Erica's blue eyes, green jacket, and high socks give her a cute look that fits her character well.
Also, deserving its own mention is Illya's stuffed-animal design. Her lanky arms, big head, and small body made each scene with the bear that much more silly.
As for the actual animation, it remains in a solid spot for most of its run. Downtime is filled with reactions from Illya or Tanaka bumbling around like a buffoon. Its singular yuri scene, where Illya and Kuro "transfer mana" with as much passion as possible, arguably receives the most attention when compared to everything else offered.
But it also picks up during those fight scenes without any noticeable drops. Kuro soloing Angelica while Illya contemplates what route to take. The entire final battle that involves numerous heroes made of muck. The two-on-one duel on the giant sword. Throwing people with one's fist to catch a falling brother. Flailing chains atop a rocky outcrop. A climactic and cinematic flying segment to end the whole battle.
Lots of movement and fighting and action that proves the series has yet to let up on an animation front.
This section is very tough to analyze because there's just not a lot there.
That's due to what the anime places priority on – the action and the plot itself – and where the anime is at this point in the series – in its fourth season where not many new experiences or developments can be had for the cast.
Still, 3rei tries.
Illya is arguably the most important, and, despite Miyu's predicament, is the focus of this season. This time around, the anime targets her trepidation. How she feels fearful of where she's at and the way she approaches the world around her.
Kuro's there to push her in the right direction (through a fight to the death). She explains how Miyu never complained about her situation when she was thrust into an unfamiliar world, so it's unfair for Illya to think any differently. And, when it comes time for her to decide to protect Miyu or this strange world, Illya chooses both because, as she says, it's illogical to believe it must only be one way or the other.
What Miyu receives on a character level is more fundamental: sides.
She's always cared for Illya and Kuro, but the audience sees her willingness to sacrifice herself as well as the extreme elation she has in hearing and seeing her two best friends fight for her.
Furthermore, her having a brother who looked like Shirou from Illya's world was always implied, but it was not until this season that such an allusion was no longer an illusion. She disregards her own safety to protect him, and she drops some of her coolness to replace it with cuteness when she talks with him in a more personable manner.
Kuro herself sits on the sidelines for most of the season (and, indeed, for the first few episodes, only shows up briefly). It's not until later that the anime gives her slightly more attention. She fights in Illya's stead while she contemplates what to do, demonstrating Kuro's usual steadfastness and willingness to push forward even if she may be in the wrong.
But, more interestingly, when she pairs up with Miyu's Shirou during the two-on-one duel with Angelica, she starts to express how she can pull off moves, feel what to do next, despite never really fighting in such a blazing manner before. It's an obvious connection to Shirou's own Archer background, and, while it technically does not get explored before the season finishes, it gives Kuro an opening in the future to possibly upgrade her own prowess.
For Illya, Miyu, and Kuro, it's all very minor happenings. 3rei arguably cares more about its plot: the funny skits and the kidnapping drama and the high amounts of action. Meaning, the main trio are there more to be themselves rather than go through sweeping arcs like in the first or second seasons.
Thus, it falls on the new characters – specifically the Ainsworth family – to bring something new. For the most part, though, they do not hold up well.
Angelica is arguably the best. She's thought of as a doll. One who only listens to orders like fighting against their enemies or stitching up Erika's stuffed animals when they rip. She control's Gil's Noble Phantasm as well as the space-shifting magic of the family.
She does not understand Kuro's illogical thought process of saving Miyu (just one person) and dooming the whole Earth in return (literally everybody else). But she only becomes interesting when she loses to Shirou and Kuro (mirroring the fight between the "real" and the "fakes.") Upon doing so, Beatrice (and by extension the Ainsworth family) abandon her, leaving her with nowhere to go.
Except with Illya and the others. For, while she sees herself as a doll, as a tool and nothing else, the others are willing to accept her. This foundation sets her up for eventual discussions and developments related to free will, but, given that this all appears at the end of the season, the audience will not see this for some time to come.
The others – Julian, Beatrice, and Erica – have their characteristics that set them up as the villains and the victims.
Julian gets into extreme fits of rage and holds an immense amount of power.
Beatrice is a psychopath, obsessing over Julian beyond what anyone would consider healthy.
And Erica's insistence that she is a lady that never needs any help (but she really does), and the fact that Miyu turns down Erica when the little girl asks if they are friends (which is arguably the best writing moment of the season), gives her the cuteness and the sympathy needed to make her Holy-Grail transformation an unwelcome sight.
The Ainsworth family also have a quirk in that they often see themselves as actors and the world about them their stage. As if what they are doing is more of a performance rather than just a bunch of mindless actions. It gives them a narcissistic personality which in turn feeds into their villainy as the opposing (when compared to Illya and the rest) "stars" of this "show."
Are they strong villains? Not particularly. Mostly because their connection and overall motivations in relation to Illya are not too intricate. They kidnapped Miyu, but that doesn't make them worthwhile antagonists in the long run. At the minimum, the idea that they may in fact be the "good guys" given what they want to do (even if Julian's ritual near the end does seem a little like an end-of-the-world scenario rather than a save-the-world one) adds a small twist to their characters.
That leaves Tanaka – and ends her analysis, too. For, beyond her warmth, her carefree, jokey attitude, and strange ability to yank off her arm and have it turn into a flaming sword, not much else is known, let alone given, about her. She does have a deeply rooted hatred for the Ainsworth family that seems to flip a switch within her, turning her from bubbly to berserk. But this mystery is left as such – most likely for the next season to unravel.
3rei's opening track starts off in a rather intriguing way with the rising tone and vocalist – before immediately dropping for a moment. Then, once the piece officially starts, the acoustic guitar, steady beat, and continued vocal work carry it along. The piece gets stronger in the second half when the violins kick in and the background choir has more of a stage presence (relevant phrase here), so, overall, it's a solid song to lead with.
The ending track gets groovier, mixing a slight techno feel with a pop-like composition. Some quick lyrical sections, futuristic drums, and harmonizing form an odd piece that may not fit 3rei itself but still manages to come off as catchy and interesting.
However, per usual, the voice-acting performances are the strongest part of the sound department. Everyone reprises their roles again, such as Mai Kadowaki as Illya with her frantic reactions and Noriaki Sugiyama as Shirou giving his ultimate speech. The newcomers are worthy of praise, too. Especially Mariya Ise as Tanaka for her teasing behavior and Sumire Morohoshi as Erica for her embarrassment and general cuteness.
While the original soundtrack is what it is, the sound-effects are more noteworthy. The different blades, chains, magics, actions, and abilities come off as a lot more impactful thanks to the sound design supporting it all.
I'll be totally honest; I am only watching this series because I am already this far into it.
I like the Fate universe, but more so the main characters from it rather than the spin-off ones here. Illya is funny, Kuro is cool, and Miyu is cute, but I am never actively impressed by them, and I do not bring them up within other discussions.
This season once again had very little of Bazett and next to no mention of Leysritt – my two favorite characters from the series. Angelica, Tanaka, and Erica were a few of the new characters introduced. Angelica is attractive, Tanaka is fun, and Erica is cute (this trio somewhat like the main trio), but, again, they are characters I do no particularly care for.
The fights have their spectacle, the small Fate references are neat, and the slice-of-life segments are funny when they want to be. I very much liked the stuffed-animal arc for how silly it all was. But the show overall did not do enough to get me invested in the cast or the plight at large.
What is amazing to me is that, even after this season (and given how the promotional video was just released), the anime is not done. It has a whole movie left to give, and I wouldn't be surprised if another season was in the works, too.
Given how it ended – the Ainsworth family were not fully defeated, Tanaka is still an enigma, Shirou and Miyu were just about to explain their own story – it's essentially required to have a continuation. And, despite me not liking the anime that much, I'll be there. I have come this far already; there's no sense in backing away now.
Fate/kaleid liner Prisma☆Illya 3rei!! is more of the same. An action-filled plot, pretty art, weak characters, passable music, and not enough to invest in. At least it didn't have to walk around with a meter stick.
Story: Bad, a theme on going back to one's roots exists, but the interrupted fights, the too-convenient plot points, and the repeated overall motivation only get in the way
Animation: Good, okay artistic direction, nice character designs, and above average actual animation
Characters: Bad, Illya, Kuro, and Miyu don't have much going for them this time around, and the new Ainsworth villains are not the most thrilling
Sound: Fine, okay OP, okay ED, okay OST, nice sound-effects, and above average VA performances
Enjoyment: Bad, just in it for the long haul at this point
Final Score: 4/10
6 of 12 episodes seen
Lord_Rutsah (All reviews)
Story 10
No, really, why are you even reading this?
Do you seriously need someone's confirmation that Fate Kaleid is good? At this point it's almost blasphemous to even question the quality of the series. We didn't start watching this latest arc to find out if it's good, we started watching it because we knew it was good. And of course it is, of course it's always gonna be. The sky is blue, the grass is green, Fate Kaleid is pedoph... Good.
After all 8 cards have finally been gathered, disturbances start happening in the mountain where the battle with Gilgamesh Jr. took place, with parts of the land completely disappearing and getting replaced with others. Alerted by this, Illya and crew go up there to investigate, only for two mysterious intruders to appear. These two women are using the same install power that Miyu has been using for saber, and with it quickly fend off both Illya and Bazzett, while kidnapping Miyu. Trying to run after them, Illya gets wrapped in a parallel world, where the city she lives in has been abandoned and the Ainsworth family rules everything through their install abilities.
And let me tell you folks, the install ability KICKS ASS. By far one of the most interesting ideas and the central plot of the series, the install ability allows for far more variety in combat that almost forgets it's a magical girls anime. In a later mock battle, Illya defeats Kuro by transforming from lancer to rider to saber. The enemies are also formidable, possessing far more cards than the main cast, including both Gilgamesh'es power and Thor's. The main villain, head of the Ainsworth family, is a black wizard that will honestly send chills to your spine with his creepy over-exaggerated poses and eye-movements (kinda reminds you of Petelgeuse from Re: Zero only slightly lase insane)... (emphasis on "slightly"), who wants to create a new grail out of Miyu.
Keep in mind, I'm leaving A LOT out here. Gilgamesh Jr., who has sided with Illya's crew to get his powers back from the Ainsworth card, basically steals the show in every scene he's in. Erica, Ainsworth's heir is also a glorious addition, with her twisted upbringing being in complete contrast with her kind personality, as the girl completely confuses the meaning of "good" and "evil" and ends up plain f@cked-up. Kudos for Kirei Kotomine as the crew's rip-off cook. Tanaka is the only one who didn't click me the right way, but she has shown great chemistry with some characters other than Illya so I'm giving her the benefit of the doubt.
Normally I'd comment on the quality of the animation now but... Do I actually have to?
-Heart-wrenching moments, excellent humor, big battles, fantastic animation etc etc. Basically everything you love Fate Kaleid for.
-Intimidating villains that are more cruel than anything we've seen in the series so far.
-By far the most interesting battle mechanic in the series, "install" is utilized to its fullest.
-Kuro reaches new cuteness levels despite the arc not being remotely focused on her.
-Illya's getting more pussy than the average harem protagonist.
-Gilgamesh Jr.'s "You mongrel!"phrase on episode 3.
-The entirety of episode 4.
-Erica's completely wrapped mind.
-Mjolnir!!!
-Miyu's character develops nicely.
-For the first time in anime history the kidnapped person doesn't spout bullsh!t about how they don't want to be saved, thus creating useless internal conflict for the main lead, but instead properly begs for help. Good job Miyu, good job. See Rukia? See Innoue? See Hinata? THIS is how a good hostage behaves.
Keep in mind I'll be neat-picking to death here:
-To be honest I preferred it when Kuro was all meek during mana-sucking, it feels a tiny bit disappointing here.
-Up until now the battles have ended somewhat fast. Don't get me wrong, they're still well-made and don't feel rushed, just none of the overly-dragging stuff we had gotten used to in previous seasons. Then again only 6 episodes have come out thus far and Fate Kaleid usually picks up the pace as it goes.
-The fights do feel "slightly" worse than the rest of the series. We didn't have a big boss battle either.
-Ends in a cliffhanger.
-The villain saying he didn't want to hurt Miyu more than needed was kinda out of character.
-It feels like the Ainsworths have too few servants. Illya's crew basically outnumbers them 2 to 1 at this point. New characters might be revealed later though.
-Does this even qualify as a magical girls anime anymore? I'm all for the "install" battles mechanic but I can see how other people wouldn't like it as much.
-Tanaka's character does feel slightly annoying at times (nothing unbearable though).
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'Fate/kaleid liner Prisma☆Illya' Receives Anime Movie
The broadcast of Fate/kaleid liner Prisma☆Illya 3rei!!'s final episode announced that the franchise will be receiving an anime movie. Fate/kaleid liner Prisma☆I...read more
Sep 21, 2016 12:19 PM by Sakana-san | Discuss (56 comments)
Summer 2016 Simulcast List [Update 7/8]
In this thread, you'll find a comprehensive list of anime acquired for simulcast release during the Summer 2016 season. Anime series licensed for home video rel...read more
Jun 27, 2016 12:23 PM by Snow | Discuss (78 comments)
Poll: Best girl in loli/Fate series?
--ALEX-- - Aug 18, 2016 24 replies by RavBTW »»
Jul 7, 7:55 AM
Poll: Fate/kaleid liner Prisma☆Illya 3rei!! Episode 12 Discussion ( 1 2 3 4 )
Stark700 - Sep 21, 2016 154 replies by RavBTW »»
The Definitive Guide to the Fate Series
The Fate series has come a long way over the last decade in anime, creating an expansive universe that can bewilder newcomers. So, in this analysis, we'll take a comprehensive look into all the anime related to it and trace the threads of Fate.
by Kvasir369
Background AnalysisMagicalSupernatural
The Fate/Stay Night Game and the Epic Series it Started
Fate/stay night started as a visual novel, but it has since become so much, you may need a little help keeping track...
by fatlouierox
ActionHonorMagical


Investigating a class action against Riddell on behalf of former and current football players. Beginning in 2008, Riddell falsely advertised its Revolution football helmets as reducing the concussion risk of players wearing the helmet by 31%. In 2013, the Federal Trade Commission sent a letter to Riddell reprimanding the company for falsely advertising the safety of their helmets and finding Riddell based its 31% safer claim on a flawed scientific study. In fact, Riddell's Revolution helmets suffer from design defects in the interior padding of the helmet meant to absorb shock sustained from blows to the head while playing football, despite the company marketing the helmet as having "concussion reduction technology." Riddell continued to market its Revolution helmet as safer compared to its competitors and in doing so, took advantage of parents' and players' concerns over the danger of concussions. If you were or are a football player or the parent of a football player who sustained a head injury while wearing a Riddell Revolution helmet, please contact us.


PHOTOS: MYX VJ Search 2017 Finals Night! - MYX | YOUR CHOICE. YOUR MUSIC.
Home Features Photos PHOTOS: MYX VJ Search 2017 Finals Night!
PHOTOS: MYX VJ Search 2017 Finals Night!
We welcomed four new members of the MYX Squad: JC Tevez, Debbie Then, Kim Cruz and Turs Daza! Check out our MYXclusive photos from the the MYX VJ Search 2017 Finals Night here!
Congratulations to the new MYX VJs.


text:
Life Wine
The wine buff: The reds of Veneto
Vines with a view: The Valpolicella region is surrounded by sea, lake and mountains
Rizzardi Pojega
Rizzardi Villa Amarone
Corinna Hardgrave
October 12 2019 2:30 AM
With a patchwork of vineyards, olive groves and a smattering of cylindrical cypress trees, playing a 'guess the country' game is easy. The only place you could possibly be is in Italy. And for me, on a recent wine trip, it was Veneto.
https://www.independent.ie/life/food-drink/wine/the-wine-buff-the-reds-of-veneto-38577647.html
https://www.independent.ie/life/food-drink/wine/f47b5/38577646.ece/AUTOCROP/h342/2019-10-12_lif_53872634_I4.JPG
With the Dolomite Mountains to the north, the Adriatic Sea to the east and Lake Garda to the west, there is a lot more to this region than its famous canal-laced city.
Veneto is the biggest wine producing area in Italy, producing as much wine as Australia, and they are wines that will be familiar - Prosecco, Soave and Valpolicella.
The Valpolicella region is tucked into the western part of Veneto, about 15km west of Lake Garda. From the lake, you can see the Lessini Mountains to the north, and the combination of the warm wind from the lake and cool air blowing down from the mountains into the hills and valleys contributes to the ideal growing conditions. The soil types are diverse, ranging from volcanic rock to muddy clay and alluvial soils.
One of the leading producers is Guerrieri Rizzardi, a company that dates back to 1913 and the marriage between two noble wine-producing families. The winery is run by two Rizzardi brothers: Giuseppe, a Bordeaux-trained winemaker, and Agostino, who heads the business end of things.
It was harvest time when I visited their five-hectare Calcarole vineyard in the heart of Negrar in the Valpolicella Classico region. It runs across the hill in maronge, traditional stepped terraces that are supported by 100-year-old dry stone walls made from hand-cut limestone. There is just 50-80cm of topsoil on each terrace, and the roots of the vines dig down into the crumbly rock.
The grape varietals here are mainly Corvina and Corvinone, but Molinara, Rondinella and Oseleta can also be used in the blend for making Valpolicella wine.
Vines love poor soil, and these were laden with beautiful tasting grapes. The whole bunches were being hand-picked and put into small white crates, which were then transported to the fruttai (purpose-built drying lodges), where breezes blow through the room. This process is called appassimento, and over the winter months, the grapes start to dry out, losing 30-50pc of their water content, and the flavours and sugars in the grapes concentrate.
This results in a wine that is rich and is often referred to as a meditation wine, something that should be sipped rather than consumed too eagerly.
For Giuseppe, it is important to allow the terroir to show through in his wines. To ensure this, he picks the grapes a little early and allows them to dry for three to three and a half months. This means that the wine remains elegant and doesn't become overblown with too much alcohol, raisined fruit and concentrated sugar.
I have two Amarones in today's line-up as well as a lighter Ripasso wine.
Kevin Judd, one of New Zealand's most highly acclaimed winemakers, will be visiting Adare Manor to host a wine dinner in The Carriage House on October 24. Kevin will talk through five of his low-intervention Greywacke wines as they are served with a four-course dinner, which includes canapés, a sea bass fish course, roast duck breast with butternut squash and lemon tart. Tickets €85, tel: 061 605 271.
Rizzardi Pojega Ripasso 2016
€16.95, reduced from €20.45, 14.5pc, from O'Briens and obrienswine.ie
Ripasso is made by pouring a Valpolicella wine over the pomace left behind after an Amarone has been made, which adds a bit of polish and concentration. This one has a fresh purity of fruit, with flavours of red cherry and a touch of herbs.
Rizzardi Villa Amarone 2011
€39.95, reduced from €44.95, 16pc, from O'Briens and obrienswine.ie
Made primarily from Corvina and Corvinone, this spends 36 months in oak barrels, letting the dark fruit flavours develop polish, complexity and spice while maintaining a lovely fresh acidity.
Tommasi Amarone 2013
€45, 15pc, from Fresh, Deveney's, Dollard & Co, Jus de Vin, Kelly's, Whelehan's, O'Neill's SCR, Joyces.
Aged for three years in large Slavonian oak casks, this is complex and dark with rich flavours of dark plum, black cherry, raisin and spice, with plush tannins.
Follow @Indo_Life
The wine buff: Green Chile
Corinna Hardgrave Never before has there been so much emphasis on sustainability, and for me, it is always good news when I hear of one of the big wine producers taking this seriously, as this is what will drive change on a large scale. After introducing a conservation programme in 2011, Concho y Toro, the company that makes Cono Sur wine in Chile,...
The wine buff: Trends for 2020
Corinna Hardgrave Welcome to a new decade of drinks and wine, and it's probably as good a time as any to take a look at some of the trends we're likely to see over the next year.
The wine buff: A toast to the new decade
Corinna Hardgrave I don't know about you, but I find it hard to believe that it was 20 years ago when we were all worrying about planes dropping out of the sky when the clock struck 12 to ring in the new millennium. Time flies, as they say, and here we are, gearing up for a new decade.
The wine buff: Green Chile Wine
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text:
Title: Application of the doubly labelled water technique for measuring CO2 production in sheep
Author: Midwood, Andrew J.
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Order from print. A scan fee will apply.
The doubly labelled water technique (DLW) allows the estimation of the carbon dioxide production (rco2) of a free-living animal from which, with knowledge of the respiratory quotient (RQ), energy expenditure may be predicted. The aim of this project was to assess the performance of this technique in ruminant animals using sheep as a model. In a series of preliminary experiments physiological processes which may affect this technique were examined. It was found the administered isotopes equilibrated throughout the body water after 6 hours following either an oral or intravenous dosing. 2H lost in the form of methane was estimated to lead to errors in rco2 of between -3.27 and -6.54% and may be corrected for by use of a methane to urine enrichment ratio of 0.6536. Losses of 2H in exchangeable sites in faeces were estimated to lead to errors in rco2 of between -5.35 to -6.54%, again corrections factors were proposed. Sequestration of 2H into carcase fat was also quantified, a maximum error of 0.67% was estimated on rco2, although more 2H was detected in the fat free carcase this was assumed to be exchangeable 2H. A maximum error of -2.39% on water turnover (rH20) was estimated to arise from the recycling of 2H due to the catabolism of labelled body solids, although this was probably an overestimate. No convincing evidence was found to suggest the fractionation factors applied to human subjects are not equally applicable to ruminant animals. The baseline body water enrichment was altered by a change in diet from synthetic concentrates to fresh chopped grass. Isotopic estimates of rco2 were compared with respiration chamber measurements of rco2. A number of curve fitting procedures were considered together with three multi-point, three ratio plot and three two-point estimations of rco2. Using a multi-point calculation and after making corrections for fractional water loss, loss of 2H in methane and faecal solids, rH20 was underestimated by 16.24%. The isotopic rco2 estimates were on average 1.52% (SD 15.31) lower than the chamber measurements, although one animal was markedly different from the others, omitting this animal led to an average error of + 5.95% (SD 4.34). In applying this technique to animals in the field the influence of a free-living existence on the performance of the method was assessed. A number of rco2 calculation procedures were again considered. Preliminary chamber measurements were used to estimate methane production and faecal dry matter output in the field. Estimates of rH2O in the field (mean 7.218.1. day-1) were lower than those measured in the chambers (mean 9.812 1.day-1). From predictions of dry matter intake in the field RQ was estimated (mean 1.067), using the isotopic rco2 estimates (mean 590 1.day-1) energy expenditure was then predicted (mean 11586 kJ.day-1). In the light of this work it was concluded the DLW technique may be usefully applied to ruminant animals and a number of practical suggestions were made.
Keywords: Ruminants' lipid metabolism


Big-time sliding fun for little guests at H2OBX.
Her eyes lit up when she saw water slides that were just her size! Laughing and squealing, she tried the two brightly colored looping body slides first. She'd hardly splashed down into the shallow landing when she was up and ready to explore more. Two more body slides and a three-lane racer kept her occupied and happy for hours. I was so excited to relax and watch her get her first taste of OBX adventure.
Maximum individual rider weight 200 lbs.
Maximum rider weight: 200 lbs.
Maximum rider weight 200 lbs.


You're looking for a nice cup of tea or coffee while you're in the area? Or just fancy fresh,organic vegetables for your dinner tonight? You have a cold and are looking for a natural remedy? So whatever brings you here you are very welcome!


Electric alarm systems are over 100 years old, one of the earliest being patented by Alexander Pope of Boston. His system was very similar to modern alarms, consisting of magnetic contacts placed at the openings and interconnected by pairs of wires to a battery and a bell. The disturbance of any of the openings closed the circuit and caused the bell to ring.
This system was, of course, much simpler than modern alarms and its main disadvantage was that it could be defeated by cutting the wire.
There are two basic "levels of protection" provided by a security system: exterior (or perimeter) protection and interior protection. The ideal security system uses a combination of both types.
Exterior or perimeter protective devices generally consist of sensing mechanisms attached to doors and windows leading into the home. These devices are wired in such a way that they will sound the alarm if an entry is attempted and send an emergency call for help to a central monitoring center.
Magnetic contacts are the most widely used for perimeter protection. These devices work with a switching mechanism. The contacts are attached to doors or windows and, when these protected areas are opened the magnet moves away from the switch and the alarm is activated. In the event that an intruder attempts to bypass the magnet contacts by breaking the glass in a door or window, specially developed sensors can detect the sound of glass breaking and activate the alarm.
It is important to have a method for detecting an intruder should he elude the perimeter security system. This is where an interior system comes into play.
One of the more commonly used interior protective devices are motion detectors. There are three basis types: infrared, microwave and ultrasonic. These protect the interior by detecting the body heat or movement of an intruder and sounding the alarm.
Both smoke and heat detectors should be included in any security system for fire prevention and life safety. Like the security system, a fire prevention system will not only make your protection complete, but also reduce your homeowner"s insurance premiums.
Smoke detectors should be located in each bedroom, outside all sleeping areas and on all levels of the home. They work by detecting the presence of smoke particles in the air.


Czech China Club invites you to its very first badminton tournament!
It will take place on the 11th of February in Olsanka Hotel sport center.
Entry fee is only 80 CZK and it includes refreshements and spare shuttlecocks.


Looking for Western Kentucky Hilltoppers vs. Florida Atlantic Owls free picks? Week 11 betting sees the Hilltoppers taking on the Owls Saturday November 10th at the FAU Football Stadium, Boca Raton, Florida. Cappers Picks provides complimentary handicapping picks all NCAA football season long so stay tuned for more FREE college football predictions like this Hilltoppers Owls free pick.
We have reached week eleven of the college football season which means most games are conference showdowns. In this game it's Conference USA showdown when the Western Kentucky Hilltoppers make the trip to Boca Raton to take on FAU.
It was just a few years ago the Western Kentucky Hilltoppers were one of the most popular and best mid majors in the country but fast forward a few years and that has changed.
They come into this game with only one win over Ball State and they have lost five games in a row. The biggest issue for the Hilltoppers has been their offensive production.
Coming into this game they are averaging only 18.7 points per game, and although the defense hasn't been awful the offense hasn't done enough.
The biggest issue for the Hilltoppers is they can't seem to find a quarterback to stick with. They have used three quarterbacks so far this year and none of them have had much success.
In this game the Hilltoppers need to find a way to get the offense going. They are facing a good offensive team and 20 points isn't going to be enough to cut it.
On the other side of this matchup is the Florida Atlantic Owls who are led by Lane Kiffin but they haven't had a ton of success so far this year.
They currently have four wins but the way they were getting talked about before the season most believed this team would finish with at least eight.
The Owls have been decent on the offensive side of the ball but they are only averaging 30 points a game, a number most believed would be higher.
On the defensive side of the ball is where the Owls have struggled giving up 33.1 points per game.
If they want to win this game the defense is going to need to be good. They are facing a bad offense and they need to keep them down.
Under is 7-1 in WKU last 8 games as an underdog.
WKU are 17-6 ATS in their last 23 games on grass.
Over is 8-3 in WKU last 11 games on grass.
Over is 8-2 in FAU last 10 games in November.
FAU are 2-7 ATS in their last 9 games overall.
Under is 7-2 in FAU last 9 games as a favorite.
This has been a series where the underdog has kept it close and that will continue in this game.
The Owls will win, but Hilltoppers will keep it close.
If you're looking for more picks like this Western Kentucky Hilltoppers vs. Florida Atlantic Owls matchup we'll be providing 4* free College football game predictions on the blog all bowl season long, and check out our Experts for guaranteed premium & free CFB Football picks!


IN TODAY'S business environment, we anticipate that the convergence of risk-finance measures will become the performance "norm." In fact, risk-finance is fast becoming the new language of business, not just in terms of financial stability standards.
Traditionally, investors look at Return on Equity (ROE) as a measure of the profitability of their investments. Management also uses ROE and Return on Resources Deployed to evaluate the performance of business units. ROE is based on generally accepted accounting principles (GAAP) and continues to be an objective measure of historical performance.
Recently, however, companies have faced pressures (both internal and external) that influenced the way they do business. For example, banks now need to follow stringent regulatory standards on risk and capital management. There is a supervisory expectation for banks to involve business units in the budgeting and capital planning processes, and allocate to them the necessary capital to cover their risk-taking activities.
Accordingly, risk capital frameworks are embedded in the business decision-making processes of banks, and this has made the risk management function more prominent. Banks need to move beyond pure regulatory compliance and optimize the use of new tools required by regulations to manage risk and grow the businesses. While the finance function reports on the historical performance of business units, risk managers monitor and report future-oriented figures (e.g., expected loss) to senior management and the Board. They report whether the risk exposures of business units are within the risk appetite of the bank.
These developments have challenged the continuing relevance of traditional performance metrics which are not risk-based. For many institutions, risk and finance frameworks are not yet fully integrated into business operations and decision-making. They continue to measure the profitability of business units using traditional operating profit and ROE. Silo risk management reports are used more for information only, and are not used to drive business units to optimize their risk/return profile and adopt risk-based pricing.
Leading banks responded to these issues by adopting Risk-Adjusted Performance Measurement (RAPM) as the key profitability metric of each of the business units. RAPM progressed ROE to Risk-Adjusted Return on Capital (RAROC). But instead of using accounting net income and accounting capital, RAROC is computed as risk-adjusted income over risk capital. Risk-adjusted income is computed as accounting net income less expected losses, and after internal allocation for funds transfer pricing (FTP) credits/charges, revenue sharing and cost allocation. Risk capital is an amount required by banks to cover unexpected losses from market risk (losses from adverse movements in market prices or rates), credit risk (losses from the failure of counterparty to perform) and operational risk (losses from operational errors, fraud, technical failures, legal and natural hazards). Using internal assessment, risk capital is attributed to individual business units according to their risk profile.
RAPM is useful to companies in many ways. A well-designed RAPM dashboard shows integrated risk and finance views of business units. Its FTP mechanism reflects charges for liquidity and interest rate risks which are managed centrally outside the businesses. Expected losses cover anticipated losses from market, credit (aligned with Basel and IFRS requirements) and operational risks. Revenue sharing and cost allocation attribute common operating income and expenses, respectively, to appropriate business units. Unexpected losses are represented with risk capital. RAPM also shows RAROC and economic profit as relative and absolute returns in excess of cost of capital, respectively. RAROC and economic profit are different measures of performance using the same components. Together, they provide a sound understanding of business performance.
In addition, RAPM can be used to project future performance (budgets) and capital requirements. Strategic planners have used it to evaluate optimal capital and balance sheet structure, and allocate capital resources among business units. RAPM also provides tools for understanding and managing profitability at customer, product and portfolio levels. It recognizes both FTP and expected losses as part of the regular cost of doing business that should be factored in the pricing of products and services (i.e., risk-based pricing).
Further, RAPM satisfies the regulatory expectations on risk-based performance measurement and capital allocation. RAPM also improves external disclosures as it shows a truer economic picture of companies and helps address distortions inherent in GAAP-based results.
Most importantly, RAPM encourages behavior and a culture that is consistent with the organization's financial objectives, and demonstrates rigor around value-driven financial management. With the appropriate reward mechanism, it drives and aligns the behavior of each business unit toward the creation of maximum value.
All these factors support the reality that RAPM has become a standard business need in today's industry. It breaks down silos in businesses, finance, risk and strategy, and binds them together to optimize value for shareholders. Banks and non-bank financial institutions now face a very exciting opportunity to realize these tangible benefits as they fully adopt RAPM.
Christian G. Lauron is a Partner while Belvin L. Armenion is an Associate Director, respectively, of SGV & Co.


Labour has stepped up calls for Amber Rudd to resign after her former deputy confirmed she did set an "ambition" for the Home Office to increase the number of illegal immigrants it was deporting.
The Home Secretary faces the Commons on Monday with opposition MPs accusing her of having misled Parliament after she told a Commons committee last week that the Government did not have targets for removals.
Her position appeared to weaken after the former immigration minister Brandon Lewis disclosed he had weekly discussions with her about how they could get the numbers up when he was in the Home Office.
However, appearing on BBC One's The Andrew Marr Show, Mr Lewis, the current Conservative Party chairman, insisted they had not talked about specific targets.
He was accused by shadow home secretary Diane Abbott of "hiding behind semantics", saying his disclosure made it clear she knew what was going on in the department.
"Beneath the spin, he let the truth slip and sealed her fate. Amber Rudd knew of the targets she pretended didn't exist. It's time for Rudd to go," she said.
But while Ms Rudd is likely to face a tough time in the Commons chamber, there appears to be little appetite among Conservatives to see her fall, despite continuing controversy over the Home Office's handling of the Windrush scandal.
Downing Street has said she continues to enjoy the "full confidence" of Theresa May while she has received public support from both senior ministers and Tory backbenchers.
Ms Rudd's difficulties began on Wednesday when she told the Commons Home Affairs Committee that the Home Office did not have targets for removals.
The following day, however, she returned to the Commons to admit that Immigration Enforcement managers did use "local targets" but she said they were "not published targets against which performance was assessed".
The pressure then ratcheted up on Friday with the leak of a Home Office memo, which referred to a target of 2,800 enforced returns for 2017-18, and the progress that had been made towards a "10% increased performance on enforced returns, which we promised the Home Secretary earlier this year".
He position now is likely to hinge on her ability to convince MPs that she did not "knowingly" mislead them earlier in the week.
Mr Lewis said that while he had worked with her "on a weekly basis" about their efforts to increase the numbers of illegal immigrants being removed, they had never discussed "particular numbers" in the way that was suggested at the Home Affairs Committee.
"Yes, I did talk to the Home Secretary about that and the overall work that we were doing and the overall ambition to see an increase in numbers, but not on the detailed numbers and targets," he said.
Labour has said the targets contributed to the Government's "hostile environment" for illegal immigrants which led to members of the Windrush generation who were entitled to be in the UK being wrongly threatened with deportation.
More than 200 MPs have written to Mrs May urging her to enshrine in law the promises made to those affected - including a commitment to resolve their immigration status as quickly as possible.
The letter, co-ordinated by Labour backbencher David Lammy, was signed by MPs from Labour, the Liberal Democrats, the SNP, Plaid Cymru and the Greens as well as lone Tory, Anne-Marie Morris.
"Detailed policy guidance and amendments to existing secondary legislation, where necessary, will be brought forward as soon as possible - and in some areas, we will want to consult with the communities affected first to ensure it best meets their needs," the spokesman said.


Edge of Escape: Who Lives in Mountain View, California?
One of the fun things about writing a blog is seeing where all the readers come from. That little "feedjit" app in the sidebar tells me I have viewers from every continent, countries I've never heard of, and cities with interesting or hard to pronounce names.
There have been times when I have had more visitors from Russia than the U.S. And there is someone from Mountain View, CA, who has been systematically going through past postings. Curiosity has me wondering if this is a former classmate, a stalker, a faithful blog reader, or one of those search engine spiders.
If you're from Mountain View, tell me, what's the weather like?