text:
\section{Introduction}
Finding talents is one among the most difficult challenges for organizations. Hiring talents means performing better, get more revenue and evolve the business. Where hiring talents is relatively easy, the biggest challenge for organizations today is to find talents they have already hired: finding and creating knowledge is important, but so it is to be able to search and mine knowledge that is already owned. The social networking revolution allowed the creation of tools to evaluate competencies, expertise and skills, like Linkedin\footnote{\url{http://www.linkedin.com/}}. Before social networks, talent management activities were restricted to a marketing oriented approach: to discover talents among their employees, organizations promote internal contests or invest into assessment activities and campaigns. However, during the last few years, organizations started also to put efforts on social talent management, often connected to wider social related initiatives (social CRM, enterprise social networking, etc.). Social talent management is nowadays based on dedicated pages or applications whose aim is to discover interesting professionals. Social networks are also used by organizations to get unofficial information about their employees or candidates, to understand what they do and who they really are.

To understand where and how an employee is positioned on a skill network will enable organizations to find previously hidden sources of knowledge, innovation and know-how. Resumes can provide structured information about studies and working experiences, but they are not useful to understand skills and experiences that do not belong directly to the employee, but to his friends and colleagues. If a candidate does not master a topic but has a strong relationship with somebody who does, then he is an important gateway in that topic, although different relationships allow for different gateway values (i.e. two friends in the same company represents a stronger connection than two friends in competing companies).

If an employee is involved on specific tasks, and she has always been involved only on those tasks, this does not mean she could not have strong competencies and skills on completely different subjects: hobbies, passions, interests can be worth some, sometimes a lot of, value in the \textit{prosumers} age. People are digitally involved throughout their life and there is not a clear separation between personal and professional network. Understanding the position of somebody among different skills and knowledge networks or rankings can let this value emerge. This data richness and hidden knowledge demands for a multidimensional and multiskill approach to the employee ranking problem: the definition of a ranking algorithm on networks, able to capture the role of different kinds of relations and the importance of different skill sets.

Given a person with a set of skills and a neighborhood of friends in a social network, the skills of the friends to some extent are accessible through that person, and therefore they should be considered when evaluating her. More formally, each node $n$ in a network has some skills $S$ each with a given intensity, and it is connected, with different kinds of edges, to other nodes ($n_2, n_3, ...$) with their own skill set ($S_2, S_3, ...$). The real value of node $n$ is then defined by a function $f$ that takes as input not only $S$, but also $S_2, S_3, ...$, by accounting for the different dimensions connecting $n$ to $n_2, n_3, ...$. This idea has been proven in the economic field at the macro level: in \cite{moretti} the author proved that the social return of higher skill levels is higher than the personal return, i.e. higher skilled people make their colleagues to be more valuable as well.

Current ranking algorithms can only provide multiple rankings on monodimensional networks, or simple rankings in multidimensional networks. In this paper we propose an algorithm whose aim is to provide multiple rankings (one for each skill) for nodes in a multidimensional network, a network with multiple types of edges. Our approach is called ``you (U) know Because I Know'', or UBIK. We test UBIK on real world networks, showing that its ranking is less trivial and more flexible than the current state-of-the-art methods.

Our contribution can be then summarized as follows. We introduce a novel ranking algorithm for multidimensional networks with multiple node attributes, able to provide a different ranking for each skill. We provide a fast implementation able to scale linearly in the number of edges of the network. We provide a new ranking for real world scenarios, including co-authorship in computer science and corporate emails.

In Section \ref{sec:related} we present the related works. The intuition and the formal model behind this work is explained in Section \ref{sec:idea}, while the actual implementation of the UBIK algorithm is described in Section \ref{sec:UBIK}. We provide our experimental setting in Section \ref{sec:experiments}. Finally, Section \ref{sec:conclusion} concludes the paper.

\section{Related Works}\label{sec:related}
How to evaluate and manage the human resources of an organization is an endemic problem in management. We are not the first researchers pointing out that social network analysis is a useful tool in this area, as \cite{hr-sna} starts from the assumption that the value of a person is not only determined by the extent of what she knows, but also to her position in a social network, validating our starting point. However, \cite{hr-sna} only uses a centrality concept, without looking at the skills of the nodes of the network, nor it builds a computer science framework to solve the problem. The social dimension enters in the problem of human resources management not only as an evaluation tool of the skills of a person, but also on how much she can influence the behaviors of other employees \cite{hr-influence}.

To rank nodes according to their importance in a network structure is a classical problem in complex network analysis \cite{wagner}. Our final aim is to have multiple rankings over a multidimensional network. To the best of our knowledge, no algorithm is able to perform this task. The current state of the art in this research branch can be divided in four categories.

In the first category, there are popular ranking algorithms (PageRank, SALSA and related \cite{pagerank,salsa,sidiropoulos}) which provide a single ranking in a monodimensional network.

In the second category, we have ranking algorithms that can provide multiple rankings, but on a non-multidimensional network. The oldest and best-known approach is HITS \cite{hits}, which provides only two rankings (hub and authorities). Another example is topic-sensitive PageRank \cite{ppr}, that can provide an arbitrary number of rankings.  However, in the topic-sensitive PageRank there is no way to exploit different kinds of relations, so it cannot perform the task requested.

In the third category, the ranking algorithms deal with multidimensional network, but they provide a simple ranking, much like the PageRank does for monodimensional networks. This branch has been thoroughly tackled in recent years, for example in \cite{multirank, har, topic-level}. Since we are interested in a multi-ranking, none of these works can help us.

Finally, this work aims to be included in the fourth category, multidimensional approaches to the multi-ranking problem. There is already one method in literature in this category, namely TOPHITS \cite{tophits}. However, just like HITS, TOPHITS provides only two different rankings, hubs and authorities, therefore its application to real world scenarios in the evaluation of many skills is questionable. With this aim in mind, we proceed explaining our methodology.

\section{Network-Based Human Resources}\label{sec:idea}
\subsection{Problem Definition}\label{sec:blocks}
As stated in Introduction and Section \ref{sec:related}, our paper aims to tackle the problem of multiple rankings in multidimensional network. Our problem definition is the following:

\begin{definition}\label{def:problem}
Let $G=(V,E,D,S)$ be a multigraph where each node $v \in V$ is connected to its neighbors through multiple edges $e \in E$, each carrying a label $d \in D$; and $S$ be a skill set, such that each node $v$ is labeled with one or more skills $s \in S$, each with a given weight $w \in R^+$. Given a query $q$ containing a set of skills $S_q \subseteq S$ and the importance $r(d) \forall d \in D$, we want to rank nodes accordingly to the weight of each $s \in S_q$ they posses directly or indirectly through their connections. \hfill \ensuremath{\Box}
\end{definition}

The intuition behind our idea is the following. Suppose we have a set of people, each with her own skills and acquaintances, and a task to be performed. In a world without social knowledge interaction, the best way to perform the task is to assign it to the person, or to a set of people (i.e. a team), possessing the highest value of the related skill. However, each person can access to the external knowledge of their acquaintances, thus possibly modifying her skill set value, and therefore the decision of the composition of the team. Each person can also access to the acquaintances' acquaintances skills, but with an increasing cost at each degree of separation, causing at some point the external skill to be useless.

Now, we need to define the social connections, and their different types. We need to formally define the skills carried by each individual as the initial state of the system and how the expertise propagates through social connections.

\subsection{The Model}\label{sec:model}
Following \cite{multidim-asonam} we model our problem with a multidimensional network (also studied in \cite{kazi-net}). We now present the basics of multidimensional networks and then the extensions we apply to the basic model.

In the case of a multidimensional setting, a convenient way to model a network is a \emph{labeled multigraph}. Intuitively, a labeled multigraph is a graph where both nodes and edges are labeled, and where there can exist two or more edges between two nodes. Just as any regular labeled graph, also labeled multigraphs may be directed and undirected, thus we allow edges to be both directed and undirected, when the analytic aim requires it. Such a graph is denoted by a triple $G=(V,E,D)$ where: $V$ is a set of nodes; $D$ is a set of labels representing our dimensions; $E$ is a set of labeled edges, i.e., it is a set of triples of the form $(u,v,d)$ where $u,v \in V$ are nodes and $d \in D$ is a label. We assume that given a pair of nodes $u, v \in V$ and a label $d \in D$ it may exist only one edge $(u,v,d)$.

In \cite{multidim-asonam}, the previous paragraph fully describes a multidimensional network. We need to add several things in order to fit into our problem definition. First, we need to introduce weighted node labels. In other words, each node $v \in V$ is a collection of couples in the form $(s, w)$ where $s$ is the label and $w \in R^+$ is the value of label $s$ for node $v$. Therefore, $v = \{(s_1, w_1), (s_2, w_2), \ldots, (s_n, w_n)\}$. The set of node labels describes what in our data are the skills of the node, along with their value. The set of all possible skills is fixed for the network, and we refer to it as $S$.

In \cite{multidim-asonam}, dimensions are considered distinct but equal. In our case, each dimension can have a different importance: in the real world a friendship tie may be more or less strong than a working collaboration, given the social environment where this tie may play its role. Therefore, each dimension $d \in D$ is represented not only by its label, but also by a value $r(d) \in R^+$, quantifying how much relevant is a relation expressed in dimension $d$, according to the query requested.

At this point we have all the building bricks of the static part of our model. Next, we define how the knowledge exchange dynamics takes place in the model itself, generating the flow that allows us to rank the nodes in the network. The idea is that each node passes the entire set of its skills to each one of its neighbors. This procedure is similar to the one employed by the classical PageRank formulation, but with a few distinctions. First, our method is not based on random walks, but on the percolation of the various skills without random jumps. Second, the amount of skill value passed to the neighborhood of a node is not equally divided and assigned to each neighbors. The amount of value that node $u$ passes to the neighbor $v$ is proportional to the importance of the dimensions connecting $u$ and $v$. It is also inversely proportional not only to the degree of the node passing the skill, but also to the degree of the node receiving the skill. Third, the knowledge exchange may be or may be not mutual, i.e. we are not narrowing our model only to directed graphs, but to general graphs.

\begin{figure}
\centering
\footnotesize
\begin{tabular}{c|l|c|}
\cline{2-3}
\multirow{13}{*}{\includegraphics[width=.25\columnwidth]{toy.pdf}} \qquad\qquad &
Node & Skill-Value\\
\cline{2-3}
& 1 & ${(a, 115), (b, 0), (c, 0), (d, 0)}$\\
& 2 & ${(a, 100), (b, 0), (c, 0), (d, 0)}$\\
& 3 & ${(a, 100), (b, 0), (c, 0), (d, 0)}$\\
& 4 & ${(a, 100), (b, 0), (c, 0), (d, 0)}$\\
& 5 & ${(a, 100), (b, 0), (c, 0), (d, 0)}$\\
& 6 & ${(a, 0), (b, 0), (c, 0), (d, 80)}$\\
& 7 & ${(a, 0), (b, 90), (c, 20), (d, 0)}$\\
& 8 & ${(a, 0), (b, 20), (c, 90), (d, 0)}$\\
& 9 & ${(a, 100), (b, 0), (c, 0), (d, 0)}$\\
& 10 & ${(a, 100), (b, 0), (c, 0), (d, 0)}$\\
& 11 & ${(a, 100), (b, 0), (c, 0), (d, 0)}$\\
& 12 & ${(a, 100), (b, 0), (c, 0), (d, 0)}$\\
\cline{2-3}
\multicolumn{3}{c}{}\\
\multicolumn{1}{c}{(a)} & \multicolumn{2}{c}{(b)}\\
\end{tabular}
\caption{Our toy example. (a) The multidimensional network structure (each line style represents a different network dimension; (b) The skill table, recording the values of each skill ($a$, $b$, $c$ and $d$) for each node.\vspace{-0.5cm}}
\label{fig:toy-example}
\end{figure}

We use also the range parameter $\alpha$, commonly used for centrality scores, handling the following situation. If $u$ and $v$ are connected through a node $v_2$, then the amount of knowledge they exchange is lower than a direct connection, just like the resistance loss in an electric circuit. If $x$ is the amount of value passed by a direct connection, the amount of skills received from nodes $\ell$ degrees away is corrected as $x^{\frac{1}{\ell \alpha}}$. Traditionally, directly connected nodes should be at zero degrees of separation, because no other \textit{nodes} should be crossed to reach them. For practical purposes, in this paper we assume $\ell = 1$ for neighboring nodes, as we need to cross one \textit{edge} to reach them. The introduction of $\alpha$ is due both to logical and practical reasons. Logically, it makes our model more realistic, as a person is a gateway of her friends' skills, thus she is to some extent also a gateway for her friends' friends' skills, but of a much lower importance. Without the $\alpha$ parameter the skill percolation could potentially continue indefinitely, and the computation may not be able to stop.

In Figure \ref{fig:toy-example} we represented a simple toy example. The network structure of social connections is depicted in Figure \ref{fig:toy-example}(a), while Figure \ref{fig:toy-example}(b) is the skill table associated with the structure. From the skill table we know that all nodes start with some global skill value (not equal for everybody, as it happens in reality), distributed along four skills ($a$, $b$, $c$ and $d$). The social connections do not have all the same value: solid line has a $50\%$ efficiency in the knowledge transfer, dashed line has a $33\%$ efficiency, while the dotted line has only a $17\%$ efficiency. By looking only at the network structure, node 1 is the most central node. It also has the highest global skill value. According to the closeness centrality, also nodes 5 and 9 are more central than 6. However, our algorithm will propagate skills $a$, $b$ and $c$ to 6 with the maximum efficiency, while 6 will retain also its unique $d$ skill. At the end of the process, node 6 ends up as the most valuable node in general in the network, while node 1 can only specialize in skill $a$. With relaxed values for the $\alpha$ parameter (like $\alpha = 1$) node 1 can still get some parts of skill $d$ ($\sqrt{\frac{1}{6}\frac{1}{2}80}$ from node 5 and $\sqrt{\frac{1}{6}\frac{1}{3}80}$ from node 9, that is $\sim 4$.$69017$) and even less of $b$ and $c$. If $\alpha = 3$ then the contributions to node 1 of skills different from $a$ is negligible.

\subsection{The Data}\label{sec:data}
Our model is describing, according to our hypothesis, how knowledge flows in a face-to-face social environment, following the proven macro level mechanism of the social effect of schooling \cite{moretti}. However, the data about the face-to-face interactions are usually part of the tacit realm of knowledge. If we cannot find direct or proxy data sources about these interactions, any algorithm solving the problem of evaluating people on the basis of our hypothesis is practically useless. In this section, we present how we use two real-world datasets, adapting them to our model and problem definition, and providing an interpretation of the knowledge that our model can unveil. Of course in both cases we are in front of an approximation. Table \ref{tab:networks} provides the general statistics about the extracted networks for each dataset.

\begin{table}
\centering
\begin{tabular}{|l|rrrrr|}
\hline
Network & $|V|$ & $|E|$ & $|D|$ & $|S|$ & $|D_r|$ \\
\hline
DBLP & 38,942 & 100,983 & 16 & 50 & 1,187 \\
Enron & 5,913 & 49,058 & 7 & 8 & 0 \\
\hline
\end{tabular}
\caption{The statistics of the extracted networks.\vspace{-0.5cm}}\label{tab:networks}
\end{table}

DBLP\footnote{\url{http://www.dblp.org/db/}} is an online bibliography containing information about scientific publications in the field of computer science. Using the data from this dataset, our problem definition may be adapted as follows: we want to evaluate the actual knowledge possessed by scientific authors in different topics and sub-topics, focusing on different branches of their disciplines. Being our aim to rank authors, they should be the nodes of our network. The link is the co-authorship relation: two authors are connected if they have written together a paper. The dimension of the connection should represent the ``quality'' of their relation, in this case the venue where the publication appeared (we chose 16 top-tier conferences in computer science, including VLDB, SIGKDD, CIKM, ACL, SIGGRAPH and others). The set of skills should describe the expertise of the author, therefore we chose to represent them as the keywords used in their publications. We eliminated stopwords, we applied a stemming algorithm \cite{Porter80} on the remaining words and then we selected the 50 most commonly used keywords in a paper title. The number of times author $u$ used the keyword $s$ is used to evaluate how much the author considers himself an expert over $s$, i.e. it is used as its $w$ value for $s$.

Enron dataset\footnote{\url{http://www.cs.cmu.edu/~enron/}} is a collection of publicly available emails exchanged by the employees of the energy company, distributed after the well known bankruptcy case. We are interested in ranking the employees, that are the nodes of our network. With this network we are able to unveil who are the real knowledge gateways in an organization, by looking at the internal communication even in the absence of more structured social information (see Section \ref{sec:rankings} for the results). Therefore, to apply our algorithm is not necessary for an organization to actually create a social media platform for their employees (or to download information from other social media). We took only the email addresses ending with ``@enron.com''. We connected two employees if they wrote to each other at least once. Then we used as dimensions the day of the week when the communication took place (ending up with seven dimensions from Monday to Sunday). For the set of skills, we considered the 8 most used keywords in the subject field of the emails (again eliminating stopwords and stemming the remaining words and directly evaluating the relation between an employee and the keyword by the number of times she used the word in an email subject).

\section{The UBIK Algorithm}\label{sec:UBIK}
In this section we discuss the implementation details of our algorithm. We called it UBIK (``you (U) know Because I Know''). UBIK requires the following input: a network $G=(V,E,D,S)$ with the characteristics presented in Section \ref{sec:model}; a range parameter $\alpha$ regulating how much information is lost after each degree of separation; and a set specifying, for each $d \in D$, what is the relevance $r(d)$ of $d$ (defined by the analyst accordingly to the ranking aims).

\begin{algorithm}[t]
\small
\begin{algorithmic}[1]
\REQUIRE{$G=(V,E,D,S); \alpha  \in \left[0\ldots\infty\right]$; $r(D)$}
\ENSURE{Node set $V$ with updated skill values.}
\smallskip
\STATE $\ell \leftarrow 1$
\WHILE{$\ell < \delta$}
\FORALL{$u\ \in\ V$}
\FORALL{$v\ \in\ N(u)$}
\FORALL{$s\ \in\ S$}
\STATE $w'_{u, s} \leftarrow w_{u, s} + \sum_{d \in D} \frac{(f(v, s) \times r(d))^{\frac{1}{\ell \alpha}}}{|N(u)| + |N(v)|}$
\ENDFOR
\ENDFOR
\ENDFOR
\STATE $UPDATE(V, u'(s))$
\STATE $\ell \leftarrow \ell + 1$
\ENDWHILE
\STATE $NORMALIZE(V)$
\STATE {\bf return} $V$
\end{algorithmic}
\caption{The pseudo-code of UBIK.}
\label{alg:pseudocode}
\end{algorithm}

Aim of UBIK is to update $\forall s \in S$ and $\forall u \in V$ the value $w$, i.e. how much node $u$ possesses of skill $s$. The pseudocode of UBIK is Algorithm \ref{alg:pseudocode}. UBIK cycles for each node, using the following master equation:

$$ f(u, s) = \sum_{d \in D} \sum_{v \in N(u, d)} \dfrac{(f(v, s) \times r(d))^{\frac{1}{\ell \alpha}}}{|N(u)| + |N(v)|} $$

where $N(u, d)$ is a function returning all the neighbors of $u$ that are reachable through dimension $d$ (if a dimension is not specified, it returns the entire neighborhood). Notice that the contribution of each $d$ is different, corrected with the value $r(d)$, i.e. the relevance of dimension $d$. Also note that, at the first iteration, $f(v, s)$ (i.e. how much node $v$ possesses of skills $s$) is equal to just the weight $w_{v, s}$, but at the second iteration it will be updated with the master equation.

One important caveat must be discussed about the $\ell$ parameter. In our model (Section \ref{sec:model}) we said that $\ell$ represent the degrees of separation of the nodes $u$ and $v$, exchanging their skill values. Therefore, the exact implementation of our model would require to scan for each $u$ each node of the network, calculate the shortest path between the two, and then update the contribution accordingly to the $\ell$ value. However, this implementation is inefficient, as it is an equivalent of finding all the shortest paths in the network (that is a cubic problem in terms of the number of nodes, or $|V|^3$ \cite{spalgorithms}) and then apply our calculation. Instead, Algorithm \ref{alg:pseudocode} provides an approximation of the result. The approximation reduces the main loop time complexity as linear in terms of number of edges, usually approximated as $|V| \log |V|$.

We set $\ell = 1$ and we apply the master function to every node and every skill. Then, we increase $\ell$ by 1 and we apply the master function again, using not the original skill values of nodes, but the ones updated at the first iteration. In this way, all the neighbors of $u$ are passing to $u$ also the skills that they have inherited from their neighbors. We avoid to pass back to $u$ the skills that $u$ itself passed to its neighbors at the previous iteration. At the $n$-th iteration, the neighbors of $u$ pass to $u$ the skill values obtained by the nodes $n-1$ degrees away.

The stop criterion is dependent on the $\ell$ value. On average, nodes that are beyond three or four degrees of separation cannot influence significantly the skills accessible from one node. Therefore, in Algorithm \ref{alg:pseudocode}, at step 2 we stop if $\ell \geq \delta$, with $3 \leq \delta \leq 6$, dependent on the application.

When we calculate the new skill values at step 6, we store the result in a temporal variable for each node. Then, we apply the $UPDATE$ function at step 10 to update the value of skill $s$ for node $u$ in the node set $V$. Each element of the master equation is either fixed ($\alpha$, $D$, $r(d)$, $N(u)$ and $N(v)$ are always the same) or it only depends on the previous iteration ($\ell$, $u(s)$ and $v(s)$). By forcing this condition, UBIK becomes order-independent: the computed value of each $u(s)$ at a particular iteration is always the same, regardless if $u$ was considered as the first node of the iteration or as the last.

The $NORMALIZE$ function at step 13 scales for each skill the values obtained for each node in the $[0,1]$ interval. Moreover, it combines all the skill values in a general network ranking. The general value of node $u$ is evaluated by simply extending the $u(s)$ function in the following way: $u(*) = \sum_{s \in S} u(s),$ where $*$ symbolizes the sum of all $s_1, s_2, \ldots, s_n \in S$. This function is run at the end of the main UBIK loop and does not add any complexity to it.

\subsection{Time Complexity}
Algorithm \ref{alg:pseudocode} has five nested loops. From the inner to the outer, they cycle over: the set of dimensions (the sum at step 6), the set of skills (step 5), the neighbors of a node (step 4), the nodes of the network (step 3) and until the $\ell < \delta$. Since cycling over the nodes and their neighbors (steps 3-4) is equivalent to cycle twice over the edges, the complexity of those two loops is $\mathcal{O}(|E|)$. Steps 5-6 have complexity of $\mathcal{O}(|S|)$, while the outer loop generally terminates after very few iterations: in real world networks, usually $\delta = \log |V|$. The final estimate for the time complexity is then $\mathcal{O}(\log|V|\times|E|\times|S|)$. We also report that usually for real world networks, the number of skills and dimensions (both in the order of $10^1$ or $10^2$) is usually much lower than the number of edges (usually ranging from $10^5$ to $10^8$ and more), making the average case complexity in the order of $\Theta(\log |V| \times |E|)$.

\section{Experiments}\label{sec:experiments}
\begin{figure}
\centering
\subfloat[First series.]{\includegraphics[width=0.475\columnwidth]{runtimes.pdf}}
\subfloat[Second series.]{\includegraphics[width=0.475\columnwidth]{runtimes-2.pdf}}
\caption{Running times in milliseconds for different random networks with given number of edges, dimensions or skills.\vspace{-0.75cm}}
\label{fig:runtimes}
\end{figure}

We tested our Java implementation of UBIK\footnote{Freely available with our test datasets at \url{http://www.michelecoscia.com/?page_id=480}}, on a Dual Core Intel i7 64 bits @ 2.8 GHz, 8 GB of RAM and a kernel Linux 3.2.0-23-generic, using as virtual machine the Java OpenJDK version 1.6.0\_24. Our implementation took on average 22 seconds on DBLP and less than 2 seconds on Enron. Our networks are small in scale, thus we created some benchmark networks to show how UBIK scales in terms of number of nodes, average degree, dimensions and skills. The results are depicted in Figures \ref{fig:runtimes}a and \ref{fig:runtimes}b.

First, we fixed the number of dimensions and of skills at 5. Then for the ``Increasing Nodes'' series we fixed the average degree at 3 and we increased the number of nodes; while for the ``Increased AVG Degree'' series we fixed the number of nodes at 50k and we increased the average degree of the nodes. Both techniques increase the number of edges: UBIK is able to scale linearly in this dimension. UBIK is able to analyze a network with 455k nodes and 1.3M total edges over all dimensions in less than a minute and a half, or with 50k nodes and the same number of edges in less than 40 seconds. The difference in the linear slope between the two is given by the increasing of both nodes and edges. We can conclude that UBIK is scalable and applicable to large scale networks, as it is linear on the number of edges. In Figure \ref{fig:runtimes}b we fixed the number of nodes at 25,000 and the average degree at 3. Then for the ``Increasing Dimensions'' series we increased the number of dimensions from 1 to 40, while for the series ``Increasing Skills'' we increased the number of skills from 1 to 40. Our implementation, paying a preprocessing phase, is independent from the number of dimensions, the runtime increases linearly with the number of skills\footnote{To assure repeatability, also the random network generator is provided at the same page of the algorithm and the networks}.

We now proceed to evaluate the results of UBIK, comparing its results with some of the state-of-the-art node rank approaches (in Section \ref{sec:comparison}) and presenting some knowledge extraction from real world networks (in Section \ref{sec:rankings}).

\subsection{Comparison with other methods}\label{sec:comparison}
We compare the rankings provided by UBIK with some state-of-the-art algorithms. The algorithms used for comparison are the Personalized PageRank \cite{ppr} and TOPHITS, a tensor eigenvector-based approach to ranking. Personalized PageRank is implemented in the R statistical software, TOPHITS is part of the Tensor Toolbox for MatLab \cite{tophits}, freely available for download\footnote{\url{http://www.sandia.gov/~tgkolda/TensorToolbox/index-2.5.html}}. For our comparison, we used the DBLP network.

We used UBIK without giving to any dimension any particular value of $r(d)$ and we took the global ranking of the nodes without selecting any particular skill. In this way, the comparison with PageRank and TOPHITS is fair, because we are evaluating the general rank of our nodes without using anything else than the network structure, that both the Personalized PageRank and TOPHITS can handle. Also, we set $\alpha = 2$ and $\delta = 6$.

The task of confronting different ranking methods is not easy, as it is not explicit why a ranked list is better than a different one on absolute terms. However, there are several properties that we would like to have in the results of a ranking algorithm. We evaluate the results of the algorithm based on quantitative tests on the following properties:

\begin{enumerate}
\item Ranking results should not be trivial: if the results are highly correlated with a trivial ranking method, then the algorithm is not telling us something interesting.
\item Ranking results should not be trivially boosted: if there is a simple mechanism to increase one's rank, the flaw of the algorithm makes its results less important.
\item Given a gold standard calculated in an independent way, a ranking algorithm is good if it is quantitatively similar, to some extend, to the gold standard.
\end{enumerate}

Let us start from the first element of the list. One of the most trivial criterion for ranking nodes in a network is to check their degree: the more edges are connected to a node, the more important it is. Of course, this ranking method is not optimal, as it takes only an artificial creation of many edges centered on a node to obtain the maximum rank (as it happens in the World Wide Web). Therefore, the most similar to the degree ranking are the results of the algorithm, the less interesting they are. This is only the first test to be satisfied, but it is necessary to satisfy also the other two. For example, a ranking method that uses the inverse of the degree to rank node will pass this test, as it anti-correlates with the trivial degree ranking method, but it will not satisfy the other two conditions.

\begin{figure}
\centering
\subfloat[UBIK.]{\includegraphics[width=0.32\columnwidth]{q-q_plot_skirun.pdf}}
\subfloat[PageRank.]{\includegraphics[width=0.32\columnwidth]{q-q_plot_pagerank.pdf}}
\subfloat[TOPHITS.]{\includegraphics[width=0.32\columnwidth]{q-q_plot_hits.pdf}}
\caption{The q-q plots of various ranking algorithms against the ranking obtained ordering the nodes by degree.\vspace{-0.5cm}}
\label{fig:q-q}
\end{figure}

\begin{table}
\centering
\begin{tabular}{|r|lll|}
\hline
R & Degree & PageRank & UBIK\\
\hline
1&	Jiawei Han&	Jiawei Han&	Philip S. Yu\\
2&	Philip S. Yu&	Philip S. Yu&	Jiawei Han\\
3&	Christos Faloutsos&	Christos Faloutsos&	Qiang Yang\\
4&	Qiang Yang&	Qiang Yang&	Hans-Peter Kriegel\\
5&	Divesh Srivastava&	Divesh Srivastava&	Gerhard Weikum\\
6&	Zheng Chen&	Jian Pei&	Divesh Srivastava\\
7&	Jian Pei	&Zheng Chen&	Zheng Chen\\
8&	Raghu Ramakrishnan&	Hector Garcia-Molina	&Elke A. Rundensteiner\\
9&	Beng Chin Ooi&	Beng Chin Ooi&	C. Lee Giles\\
10&	Hector Garcia-Molina&	Gerhard Weikum&	Christos Faloutsos\\
11&	Haixun Wang&	Raghu Ramakrishnan&	Wei-Ying Ma\\
12&	Wei-Ying Ma&	Haixun Wang&	Yong Yu\\
13&	Gerhard Weikum&	Wei-Ying Ma&	Tao Li\\
14&	Michael J. Carey&	Michael Stonebraker&	Ming-Syan Chen\\
15&	Jeffrey Xu Yu&	Rakesh Agrawal&	Jian Pei\\
\hline
\end{tabular}
\caption{The top 15 researchers according to different ranking criteria.}\label{tab:q-q-table}
\end{table}

Figure \ref{fig:q-q} depicts the q-q plots of UBIK, PageRank and TOPHITS against the degree ranking for the 1,000 nodes with highest degree. Each point $x(i,j)$ of a q-q plot corresponds to some node $x$. The coordinates of the point $(i,j)$ mean that the node is ranked at the $i$-th position by the first algorithm (x-axis) and at the $j$-th position by the second algorithm (y-axis). In Figure \ref{fig:q-q}, the y axis is the degree rank, while on the x axis we have UBIK (Figure \ref{fig:q-q}a), PageRank (Figure \ref{fig:q-q}b) and TOPHITS (Figure \ref{fig:q-q}c). The interpretation of the picture is clear: especially for the 300 highest ranked nodes, having a high degree implies having a high PageRank, while this consideration does not hold for UBIK and TOPHITS results. We also report the top 15 researchers in Table \ref{tab:q-q-table} for UBIK and PageRank (TOPHITS omitted due to lack of space, but the interesting confront of the table is with the PageRank algorithm, as TOPHITS does not show the rank-degree correlation). Again, we can easily see the correlation between the Degree and the PageRank column. The rank-degree correlation for PageRank is not our finding, as it has already been studied in literature \cite{gourab}. In practice, the logic of the degree centrality is ``The more collaborators a researcher has, the more important he is''. Both PageRank and UBIK modify this philosohpy in ``The more important collaborators a researcher has, the more important he is''. However the ``important'' in PageRank is still a quantitative measure on the number of collaborations, while UBIK uses more qualitative information. For the first criterion, we conclude that UBIK rankings are less trivial than the ones returned by PageRank.

\begin{table}
\centering
\begin{tabular}{|l|rrrrr|}
\hline
Algorithm & (1) & (2) & (3) & (4) & (5)\\
\hline
UBIK & 0.0204 & 1\% & 1.2\% &  4\%& 5.5\%\\
PageRank & 0.0166 & 0\% & 0.8\% & 2\% & 5.3\%\\
TOPHITS & 0.0857 & 39\% & 33.6\% & 34.8\% & 37.5\%\\
\hline
\end{tabular}
\caption{The share of high clustering nodes in the top rankings per algorithm.\vspace{-0.5cm}}\label{tab:k-plot}
\end{table}

So far we have shown the main defect of PageRank, i.e. it provides a trivial ranking. What is the main defect of TOPHITS? In literature, it is studied as the Tightly-Knit Community (TKC) effect: being the TOPHITS rank self-enforced through eigenvector calculation, if we highly clustered nodes in the network, it may happen that all members of this group are ranked high by TOPHITS, even though the nodes are not particularly central. This is the second point we want to prove: UBIK rankings are not prone to these easily applicable ranking boost strategies.

Table \ref{tab:k-plot} reports the share of high clustering nodes for the top k ranked nodes, accordingly to UBIK, PageRank and TOPHITS. The column (2) reports the percentage of nodes in the top 100 ranked by the algorithm that have a local clustering $k > .1$, the column (3) reports the same statistic for the top 250 nodes, and so on. The local clustering $k(i)$ of a node $i$ is defined as:

$$k(i) = \frac{2|\{(u, v) \mid u, v \in N(i) \wedge (u, v) \in E\}|}{|N(i)| \times (|N(i)| - 1)}$$

(note that we calculate the monodimensional clustering, without specifying a $d$ for $N(i)$). We can see that both UBIK and PageRank tend not to return high ranks for nodes with a high local clustering value. On the other hand, in the TOPHITS ranks 39 nodes out of the most important 100 have high clustering values. Table \ref{tab:k-plot} also reports the average local clustering value for the top ranked 100 nodes in column (1) and again this value is $> 4 \times$ higher for TOPHITS. We conclude that both UBIK and PageRank are not affected by the TKC, and that UBIK is the only example that is not dependent both on degree and local clustering.

\begin{table}
\centering
\begin{tabular}{|l|@{\hspace{1mm}}r@{\hspace{1mm}}r@{\hspace{1mm}}r@{\hspace{1mm}}r@{\hspace{1mm}}r@{\hspace{1mm}}r@{\hspace{1mm}}r@{\hspace{1mm}}r@{\hspace{1mm}}r@{\hspace{1mm}}r@{\hspace{1mm}}|}
\hline
&App.&Search&Stream&Obj.&Analysis&Sys.&User&Model&Network&Context\\
\hline
P. S. Yu&1&3&4&7&4&7&5&6&2&6\\
J. Han&5&1&3&5&3&6&4&3&3&4\\
Q. Yang&11&15&1&13&5&14&8&18&7&10\\
H-P. Kriegel&3&2&5&1&7&12&6&10&16&2\\
G. Weikum&7&9&15&2&1&17&2&11&5&5\\
D. Srivastava&18&5&24&21&11&1&12&2&11&7\\
Z. Chen&17&17&2&20&6&22&1&14&20&17\\
Rundensteiner&2&7&11&14&9&15&14&1&8&11\\
C. Lee Giles&14&16&16&16&10&19&7&23&1&14\\
C. Faloutsos&21&6&34&30&15&28&15&20&30&1\\
\hline
\end{tabular}
\caption{The top 10 researchers according to the general UBIK ranking and their rank for 10 different skills.\vspace{-0.5cm}}\label{tab:multiple-rankings-1}
\end{table}

Let us now address the third important feature that a ranking algorithm should have: the comparison with a quantitative gold standard. In scientific publishing, a useful indicator about the quality and the impact of a researcher is quantified using several different indexes. One of them, the h-index, measures both the amount of publications and citations of an author, and it is logically not related to the co-authorship network. A researcher has an h-index of $h$ if he has at least $h$ publications cited at least $h$ times. We use the h-index as our ground truth.

For this comparison we could use a q-q plot, but we need a more quantitative and objective measure than simply looking at the plot. Therefore, we follow \cite{sidiropoulos} and we use a function computing the distance of the points in a q-q plot from the line $y = x$ that represent identical rankings. The distance of point $(i, j)$ from the line $y = x$ is equal to $\frac{|i - j|}{\sqrt{2}}$. Thus, the distance measure $D$ of two rankings $r_1$ and $r_2$ is:

$$ D(r_1, r_2) = \dfrac{1}{|V|} \sum_{\forall v \in V} \frac{|r_1(v) - r_2(v)|}{|V|} $$

where $r_x(v)$ is the rank of $v$ according to the ranking $r_x$.

We calculate this function for UBIK, PageRank and TOPHITS against h-index ranking. We obtained the h-index values from an updated webpage who is collecting data from Google Scholar\footnote{\url{http://www.cs.ucla.edu/~palsberg/h-number.html}}. From that list, we removed the authors that have not published a single paper in the set of conferences with which we have built our multidimensional network, because they are not part of the network structure at all. UBIK's ranking is closer to the ground truth, computed independently from the network structure, provided by the h-index ranking, with a score of 22.43. Therefore, not only UBIK is not affected by the biases of PageRank and TOPHITS, but it also yields results closer to an independent ground truth, as they scored 23.50 and 37.54 respectively. We can now take a look to the actual multiskill and multidimensional rankings provided by the algorithm, as the comparison section is over and we can use the features, not handled by PageRank nor TOPHITS.

\subsection{Rankings}\label{sec:rankings}
We now report some rankings extracted with UBIK. We already saw in Table \ref{tab:q-q-table} the top 15 researcher setting no particular dimension weight (i.e. $r(d)$ is equal for all $d \in D$). However, now we want to take advantage of the fact that UBIK is able to return different rankings for each skill. In Table \ref{tab:multiple-rankings-1} we report the list of researchers who can master some skills, and their ranking for the other skills. As we can see, no researcher dominates over all the skills, and the different rankings can enlighten us about different leaders in different sectors. We remind that we took only authors of a very specific set of conferences, thus a possible specialist in one or more reported skills may not be part of the rankings because she never published in one of the selected conferences. Also, the skill name is the substantive of the stemmed form, thus it includes all the possible declination of the term (e.g. ``Stream'', ``Streaming'', ``Streamed'', and so on).

UBIK is able to customize the ranking even further, in an additional degree of freedom. Instead of looking at some skills taken separately, we can populate our set of dimension relevance functions with different importance $r(d)$ values for different dimensions. A proper definition of the dimension importance set results in a very specific ranking analysis. To show this feature, we decide to create two different definition classes for the Enron network. We recall that in the Enron network each dimension is the day in the week when the email was sent. In the first variant, we populate our set of rules with a $10\times$ multiplier for the dimensions of Saturday and Sunday; in the second variant we apply the same $10\times$ multiplier, but this time to each of the weekday, and nothing to the weekend days. The choice of the $10\times$ multiplier is \textit{ad hoc}, to represent a query that focuses on the relations established mainly during weekdays (first case) or during weekends (second case).

\begin{table}
\centering
\begin{tabular}{|l|rr|}
\hline
Employee&Weekday Rank&Weekend Rank\\
\hline
Victor Lamadrid&1&34\\
Jeff Dasovich&2&4\\
Lisa Jacobson&3&39\\
Michael Kass&4&2\\
Joannie Williamson&5&37\\
Bob Ambrocik&6&68\\
Chris Germany&7&8\\
Kay Chapman&8&27\\
Tana Jones&9&23\\
Drew Fossum&10&18\\
Forrest Lane&238&1\\
Jennifer Blevins&1760&3\\
Shubh Shrivastava&857&5\\
Kay Mann&14&6\\
Scott Neal&50&7\\
Vince Kaminski&18&9\\
Rosalee Fleming&21&10\\
\hline
\end{tabular}
\caption{The top 10 employees according to the UBIK for the weekday and the weekend variants of the ranking.\vspace{-0.5cm}}\label{tab:multiple-rankings-2}
\end{table}

Table \ref{tab:multiple-rankings-2} reports the top 10 employees according to both criteria (please note that some employees are part of both top 10 and they are not repeated). As we can see, the two rankings are quite distinct. There are three employees very important in both criteria (Jeff Dasovich, Michael Kass and Chris Germany). We also observe one expected phenomenon: the important employees during the weekdays are also somewhat important during the weekends, while the vice versa is not true. It is expected that important employees receive emails during the entire week, while the communications during the weekend may follow a different logic and promote unexpectedly low ranked employees (maybe because they perform a weekend shift or due to particular emergencies outside office hours).

The most notorious elements of the top management of Enron are not present in either rankings. Kenneth Lay is ranked 617th in weekdays and 224th in weekends, while Jeffrey Skilling is ranked 725th in weekdays and 458th in weekends. Joannie Williamson, who worked as a secretary for both of them\footnote{\scriptsize \url{http://money.cnn.com/2006/04/03/news/newsmakers/enron\_defense/index.htm}}, is instead present in Table \ref{tab:multiple-rankings-2}, and highly ranked. This is an expected result of UBIK, able to unveil who is a knowledge gateway in an organization.

\begin{table}
\centering
\scriptsize
\begin{tabular}{|l|rrrrrrr|}
\hline
Author&ACL&CIKM&ICDE&KDD&GRAPH&VLDB&WWW\\
\hline
D. Marcu&1&3893&3511&2606&2309&1608&3327\\
Boughanem&2768&1&3892&2966&2643&1946&3658\\
T. Ichikawa&3070&4549&1&3266&2982&2260&3994\\
Nakhaeizadeh&2606&4036&3709&1&2484&1783&3507\\
D. Salesin&2101&3538&3149&2304&1&1300&2980\\
P. Dubey&3093&4570&4198&3274&2988&1&3999\\
J. Nieh&2976&4453&4134&3185&2865&2158&1\\
\hline
P. S. Yu&574&32&27&10&860&10&684\\
J. Han&689&106&60&12&999&29&708\\
Q. Yang&933&634&967&384&1258&232&930\\
H-P. Kriegel&1024&517&66&330&1304&146&1476\\
G. Weikum&1100&472&91&888&1348&51&1355\\
\hline
\end{tabular}
\caption{The top authors for some conferences (taken singularly) comparative rankings.\vspace{-0.5cm}}\label{tab:multiple-rankings-3}
\end{table}

The same multidimensional ranking can be done for the DBLP network. In this case, we are able to spot the collaboration hubs in several different conferences. We applied the $10\times$ multiplier to a collection of conferences. The results for some of our conferences are provided in Table \ref{tab:multiple-rankings-3}, where for each conference we record the top ranked author and then we report also his ranking for the other conferences. We can see that UBIK is able to identify specialists who are highly ranked only in one conference. On the other hand, as expected, the top authors in the general ranking score average high rank in all conference, but they are rarely in the top 10 of a specific conference, as their impact is more broad and it spreads over many different venues (the bottom rows of Table \ref{tab:multiple-rankings-3} records the ranking for each single conference for the top 5 general authors in the network taken without any dimension multiplier).

\section{Conclusion}\label{sec:conclusion}
In this paper we addressed a problem of human resources: the ranking of employees according to their skills. We did so following an intuition about the intellectual value of a person: her evaluation should not be based only on her set of skills, but also on her friends' set of skills. We created an algorithm, UBIK, to tackle this problem: UBIK is able to rank nodes in a multidimensional network, with weighted labels referring to their set of skills. We applied UBIK to two real world networks, confronting its output with popular ranking algorithms, showing that our results are less trivial and more significant. Our contributions are: the creation of a feasible tool to address a problem in organizations in the real world; the address of the multiple ranking over multidimensional networks problem, not tackled in literature; and increased ranking performances over the current most used methodologies.

Our work opens the way to a number of future works. First, following \cite{multirank}, we can extend UBIK to rank also the relations. UBIK can be applied to several different datasets with different semantics and properties, from Linkedin to evaluate people's expertise; to networks of international organizations, to detect the most important organizations given a set of topics. Lastly, we can create a more efficient implementation, confront with other algorithms and evaluation measures.

\textbf{Acknowledgements}. This work has been partially supported by the European Commission under the FET-Open Project n. FP7-ICT-270833, DATA SIM.

\balance

\bibliographystyle{IEEEtranS}

redpajama_set_name: RedPajamaArXiv


text:
Self-Improvement Kick
A perfectly normal guy gets rid of everything he owns, changes his name, says goodbye to his friends — and begins walking. In the name of peace. And Honduran government officials try to heal their corrupt country by starting a perfect city, from scratch. For the new year, we bring you stories about how far some people go in hopes of a better life.
The birth of a city: This napkin drawing shows a map of Honduras. The dot is where a brand new city would be built, free of the country's ills.
Julia Lurie is an American teaching English at an all-girls high school in Gwangju, a city in South Korea. When she first got there, some things struck her as strange: On every floor of the school there was a full-length mirror, as well as a scale. And the girls used them constantly. They seemed openly preoccupied by their looks and their weight. South Korea, she finds out, has the highest per capita rate of plastic surgery in the world — some of her students had already had plastic surgery, and more were planning to get it. Julia tells what happened when she decided to teach a lesson on "beauty" to her students. (8 minutes)
Is that a Compass, a Map, a Toothbrush and a Bottle of Purell in Your Pocket, or Are You Just Happy To See Me?
Elna Baker
Elna Baker tells a story about her friend Daryl Watson. Daryl was a talented playwright working in New York City. In 2009, Elna got a mass-email from him explaining how he was going to walk across the country in the name of peace. And that he was changing his name to "Peace Pilgrim." He plans to spend six months walking, in hopes that he'll figure out his purpose in life. He gives away everything he owns and all his money, and sets off from Delaware. He lasts three days. Elna never knew what had happened, so recently she met up with Daryl and got him to tell the story. Elna is the author of a memoir, The New York Regional Mormon Singles Halloween Dance. Daryl's newest play is "Unbound." In February there will be a reading of Daryl's newest play, "Unbound," at the IAMA Theatre Company in Los Angeles. (21 minutes)
Act Two
Some Like it Dot
Chana Joffe-Walt
A young idealist named Octavio Sanchez is chief of staff to the president of Honduras. He gets an idea: What if you could cure all your country's ills by just ... starting over? In one little spot, you could create a whole new, perfect city. Do all the reforms you want to do in that one place — and if it works, it could spread to the whole country. But how could he pull off such a radical project? Then Octavio sees a TED Talk by a famous American economist, Paul Romer. Romer has more or less the same idea: poor countries could invite richer countries to found and run ideal "charter cities." It's not colonialism, Romer explains, because the poor countries are asking for help. Octavio and Paul get together and persuade the Honduran president. They're off and running. They choose a spot, they change the constitution to make it legal, they start searching for investors. But then, the whole thing starts to sour — for reasons both inevitable, and surprising. Chana Joffe-Walt and Jacob Goldstein of our Planet Money team went to Honduras to find out how it all went down. (28 minutes)
"Utopia" by Ruby Cube
If you enjoyed this episode, you may like these
76: Mob
Act One: The Freshman
Writer Sarah Vowell explains why she watched The Godfather every day while she was in college.
599: Seriously?
Act Two: Judges with Grudges
In this election year we look at the story of one small ballot initiative, in one state.
418: Toxie
Act One: Fire Sale in Kansas City
David and Chana buy a toxic asset, from a guy named Wit Solberg, who used to work on Wall Street and now helps small banks who've been saddled with toxic assets.
The Giant Pool of Money
The surprisingly entertaining story of how the U.S. got itself into a housing crisis.

redpajama_set_name: RedPajamaCommonCrawl


Main Point: No matter where we are, no matter what is going on, no matter what we've done, Jesus is just one call away.
One Call Away is one of the latest singles from the young and uber-talented crooner, Charlie Puth. For a while, Puth has been teaming up with other artists, for example with Wiz Khalifa in See You Again and Meghan Trainor in Marvin Gaye. But with One Call Away, Puth goes solo…and is showing the world he doesn't need any help.
One Call Away contains a very simple premise. It shows Puth trying to win over the affections of one of his beautiful classmates. He wants the girl to know that he's there for her should she ever decide to call on him. Pretty cool back story: the song was actually inspired by one of Puth's real life friends who was commenting on his long distance relationship with a girl. The official music video has been viewed on YouTube more than 325 million times, and the single will be featured on his debut album entitled Nine Track Mind releasing in early November of 2016.
The music video is completely clean, shows a simple love story, and provides a wonderful opportunity for us to share the Gospel.
When listening to this catchy little song, it probably makes most of us think of our best friend, or a really close family member, whoever it may be who's always telling you, "I got your back. I'm there for you if you ever need me. All you gotta do is call." Interestingly, the exact same can be said of Jesus. It doesn't matter where we are, what is going on, what the situation may be, He is literally only one call away. I want to prove that to you by sharing a great Bible story with you in your small groups.
AROUND THE CIRLCE: As we get started, let's all take a second to share our names and your favorite song right now.
ASK SOMEONE: What was the message that Charlie was trying to convey to the girl in the music video?
ASK A FEW: Who is that person in your life that you KNOW has your back? Who is the person who is just one call away?
ASK A FEW: Can you share a time when you had to call on them for help? What happened?
ASK A FEW: But, have you ever been in a situation so deep so dark so bad that they couldn't help you…even if they wanted to? What did you do then?
ASK A FEW: Do you think it's fair to say that Jesus is just one call away? Why or why not?
ASK A FEW: How would you have reacted to being in that storm in the middle of the sea in a tiny little fishing boat?
ASK A FEW: Why do you think Peter wanted to go to Jesus on the water?
ASK A FEW: Would you have done what Peter did? Would you have stepped out of the boat in that situation? Why or why not?
ASK A FEW: So, Peter was walking on water, took his eyes off Jesus, became afraid, and began to sink. In the middle of all that, he called out to Jesus. What do you think Jesus should do? Why?
ASK A FEW: So, we're told that Jesus reached out and saved Peter "immediately." How important is the "immediately" part?
ASK A FEW: Why didn't Jesus just let Peter sink? I mean, it was Peter's own failure and doubt that caused him to sink?
ASK A FEW: Have you ever been in a situation that compelled you to call out to Jesus? If so, what happened?
ASK A FEW: Why is Jesus so eager to be with us, save us, and love us?
AROUND THE CIRCLE: What is one thing in your life that you're facing right now that you need to call out to Jesus about?
One Call Away. That's what Charlie Puth was trying to tell the girl in his music video.
I think Jesus is trying to tell us the same thing from the pages of His Word. There are plenty of stories in the Bible in which God's people call on Him and He comes to them and saves them. That's what Jesus did for Peter in this story we read a moment ago.
Peter was the one who took his eyes off of Jesus. He was the one who paid closer attention to the wind and the waves than he did to Jesus. He was the one who allowed himself to be overcome with fear. Maybe some of us are thinking Jesus should have just let him drowned. But that's not what happened. Jesus IMMEDIATELY saved Peter! Jesus rescued him and brought him back to the boat. There, in the boat, Peter and the rest of the disciples worshipped Jesus as the Son of God…because that's exactly who Jesus is.
Chances are good that each and every one of us will be in a situation that we can't handle. A situation that causes us fear. A situation in which we'll need help. In that situation, I strongly suggest you call on Jesus. He is literally just a call away.
So if you are facing something bad right now, something scary right now, something sinful right now, call out to Jesus. He is literally just a call away.


text:
2019 Leg Session, Columnists, Electoral College, Gold Dome, Governor Polis, Jon Caldara, National Popular Vote, Politics
Caldara: Democrats are outsourcing the governing of Colorado
February 7, 2019 By Jon Caldara
Maybe I'm off base here, but I can't help but notice a theme. Democrats in charge of our state government don't want the people of Colorado to be in control of their own state.
Hell, the elected Democrats in charge of Colorado don't even want themselves to be in charge of Colorado. They're hell-bent to get out-of-staters to do the job.
Maybe that's great delegation skills because it certainly isn't expedient to push a leftist agenda.
Let me offer just three examples.
First, just before he moved out of the governor's mansion, President-elect John Hickenlooper signed an executive order condemning Coloradans to follow the dictates of the governor of California. He "adopted" the California low-emission vehicle standards.
Fortunately, the Colorado Automobile Dealers Association has challenged this unconditional surrender in court, arguing that if Hick wants our car choices to be limited by Gavin Newsome's whims, he needed to at least get the permission of our state legislature first.
In my quixotic quest to find the three remaining principled liberals of yore who still believe "the ends don't justify the means," I'm waiting for the Dems now in control of the legislature to support this legal challenge. While they may love the idea of forcing Coloradans to replace their pickups with Telsas at gunpoint, you'd think they'd want to do it themselves, via their legal authority.
If they're fine with the governor giving their power away to another state's governor, then Colorado lawmakers can't whine when a future Republican governor lets Texas regulate our oil wells.
Second example. Our new Attorney General, Phil Weiser, plans to join other Democrat AGs to appeal a federal judge's ruling in December that Obamacare cannot remain in place now that Republicans have removed the tax penalty for those who don't have health insurance.
It wasn't that long ago when former Colorado Attorney General John Suthers went to bat for Colorado, suing the feds on the principle they couldn't control the insurance and health care policies of Colorado — that was up to our state lawmakers.
Fast forward to today and now our new AG is suing to make sure that bureaucrats in Washington control both our health-care policies and how the state spends our Medicaid funding.
This is particularly odd given our new governor's love of socialized medicine, warmly called "Medicare for all." Should the ruling by this federal judge t hat Obamacare is unconstitutional hold, it could give Jared Polis and his leftist legislature the legal and political room to socialize Colorado's health care their way.
Third example. Our Democrat-controlled state Senate passed a bill to change the way we in Colorado vote for U.S. president, endorsing the "national popular vote." If ultimately successful, this would force Colorado's nine (likely to be ten after the next census) electors in the Electoral College to cast all their votes to the presidential candidate that received the most popular votes nationwide.
Or to put it differently, our electors could no longer vote for the president that the majority of Coloradans supported. This bill disenfranchises Colorado voters and makes us subservient to large population centers of New York and Los Angeles.
It creates a system the Founders wished to avoid where states race to inflate their vote counts. Today that could mean a state allowing 16-years-olds, felons, and undocumented immigrants to vote.
The bill goes even further. In order for the Colorado Secretary of State (SOS) to count who "won" the national popular vote, she must accept the vote counts reported by other state's secretaries of state by a date certain. Even if some of the reports are uncertain or obviously falsified, she can't wait for the matter to be legally resolved. She must use the vote count another secretary of state tells her to use.
Imagine a crooked Texas SOS (since we're beating up on Texas) who "officially" reports 99 percent of all Texans, living and dead, voted for Trump. Before the courts might officially reverse his lie, our secretary of state must order our ten electors to cast their votes for him.
I get that the progressives now in charge of our state want what they want in the fastest, most expedient, heavy-handed way they can get it. Power is intoxicating.
But I ask them to take a step back and see they are disempowering all the power-hungry Colorado politicians to come. Oh. And the people too, if that matters.
Jon Caldara is president of the Independence Institute, a free market think tank in Denver.
Tax rate reduction measure earns high-profile praise; Bill Owens, Hank Brown among Prop 116 endorsers
Signatures to lower state income tax, seek voter approval for fees turned in to Secretary of State's office
Caldara: Citizens' initiative a weapon conservatives should be wielding
VIDEO: 'National Popular Vote' as a third world system
Caldara: Governor Polis just increased your health care costs
Tags: Jared Polis, Jon Caldara, National Popular Vote, obamacare
Author: Jon CaldaraJon Caldara is president of the Independence Institute


text:
Home — Essay Samples — Literature — Novel — A Self-Aware Mind
A Self-Aware Mind
Subcategory: Literary Genre
Topic: Novel
The past acts as a tabernacle for experiences and memories. The past not only lives in Henry but also makes up Henry's very nature. Henry is his past. Life's faded memories shape choices. Author Jamie Ford builds the relationship between experience and conscience through Henry, his protagonist, in his novel Hotel on the Corner of Bitter and Sweet. Henry reflects on his experiences—with Keiko and with his father during the evacuation—before making difficult decisions. Henry's experiences instruct his conscience.
Experiencing Keiko's humanity forces Henry not only to accept but also to cherish Japanese culture. Henry's acceptance and love of Japanese culture portrays a transformation of conscience. At the novel's start, Henry partakes in the American prejudice against Japanese. The prejudice manifests itself when Henry's childhood antagonist, Chaz Preston, jeers at Henry: " 'Oh, that's right, you Japs don't salute American flags, do you?' Henry wasn't sure which was worse, being picked on for being Chinese, or being accused of being a Jap" (17). Henry's prejudice reflects the era's American prejudice and origin; it stems from ignorance. Never encountering a Japanese until Keiko allows Henry to alienate the Japanese and unconsciously further the prejudice. After spending only one day with Keiko, Henry's opinion metamorphoses. Keiko, and by extension her Japanese culture, transitions from alien to familiar for Henry. Henry's feelings for Japanese culture allow him to establish connections with the Japanese residents of Nihonmachi. These physical and metaphysical connections require an indisputable recognition of humanity, a humanity that renders defending basic rights and respects essential. The connections that Henry establishes force his conscience to defend the Japanese culture of Nihonmachi. When he sabotages his father's meeting with Mr. Preston, Henry reconciles his actions by reflecting on his experience with the Japanese people: "He'd never disobeyed his father so blatantly. But he had to. He had seen the fires in Nihonmachi and people burning their prized possessions . . . He needed to find Keiko" (90). Ford nurtures conscience's transformation—inspired by experience—by creating new divisions between Henry and his father and opening the doors of Japanese culture to Henry. Henry's priorities have changed; his malnourished experience and intimacy with his father weaken the patristic bond. As a result of the weak bond, Henry's conscience faces no challenge or remorse. Contrastingly, Henry's connections with Keiko, her family, and the Japanese-American population of Nihonmachi are fresh and intimate. These experiences compel Henry's conscience to act in favor of Japanese-Americans. Henry furthers his inclusivity with the Japanese culture when he assumes a Japanese identity to gain entrance into Camp Minidoka. Henry considers the situation: "For once in his life, there was a benefit to Caucasian people thinking that he was one of them—that he was Japanese" (226). Allowing this view, Henry not only accepts Japanese culture, but also appropriates it. Henry ventures beyond his connection with Nihonmachi and connects himself as analogous to the rest of Japanese America. Henry's experience with Keiko makes the strong connection to Japanese-American culture possible.
Similarly, Henry's consistent defense of Nihonmachi and the Japanese culture makes the record's presence at the hotel, along with other remnants of Japanese culture, possible. Henry, his conscience guarding Nihonmachi's culture, delivers the caveat for traveling to China; his father must impede the sale of the Panama Hotel. Henry learns much earlier that the hotel doubles as a refuge for Nihonmachi's cultural remnants. Henry negotiates: "I'll go, but only on this condition . . . if you can prevent the sale, I will do as you wish, I will go and finish my schooling in China . . . don't thank me, I'm not doing this for you, I'm doing it for me, for the girl, the one you hated so much" Henry didn't know quite why. Or did he? The hotel was a living, breathing memory for him. (251) In stopping the sale of the Panama Hotel, Henry preserves the record and his connection to Japantown for decades. All of Henry's childhood experiences contribute to the pinnacle of Henry's character and conscience transformation. Henry moves from disdaining the Japanese to finally self-proclaiming himself as Japanese: " 'Yes! I'm Japanese.' Henry bobbed his head. 'Of course I am' " (64). Henry's conscience alters his attitude about the Japanese dramatically. Henry loves Japanese-American culture because Keiko is Japanese-American.
Ford further validates experience's power in forming the conscience through Henry's love for Keiko and the physical choices that love impels him to make. Henry's love for Keiko pushes him to make choices that express that love, despite the conflicts those choices may create. This connection between the emotions elicited by Henry's romantic experiences with Keiko and Henry's risky choices emerges at the novel's beginning. Henry meets Keiko at Kobe Park after curfew. Keiko, unable to burn her family's photos, requests that Henry keep them safe. Henry, more than willing to help Keiko, agrees after reflecting on his experiences and his feelings for Keiko: "Henry remembered the horrible scene in Japantown that afternoon, the photographer from the Ochi-Studio—visibly shaken. 'I can hide them in my room. Do you have more?' . . . Keiko hugged Henry for a brief moment. He found himself hugging her back. His hand touched her hair. She was warmer than Henry had imagined" (95-96). Henry, aware of the danger that comes with abetting Keiko and her family, chooses to hide Keiko's photos and commits a crime in doing so. His love transcends law's arbitrary fetters and rests among palpable truths. Henry's conscience, after connecting the pain of the Japanese people to the pain of Keiko, instructs Henry to help Keiko. Henry cannot bear to think of Keiko, a girl he loves, as a girl who must undergo the same emotional trauma experienced by the photographer in Japantown.
Similarly, Henry makes conscientious choices influenced by his love for Keiko, aware that they may create familial conflicts. Henry returns to his Canton Alley apartment after shopping for Keiko's birthday. When he walks into his house, he sees that his father has discovered Keiko's photos. At the climax of this quarrel, Henry's father throws Keiko's photos out the window. The images of Keiko and her family falling to the earth flash across Henry's mind. Henry expresses his love for Keiko: He turned to his father. "I'm leaving to get her photos. I told her I'd keep them for her—just until she gets back." His father pointed to the door "If you walk out that door you are no longer part of this family. You are not part of us anymore. Not a part of me." Henry didn't even hesitate. He touched the doorknob feeling the brass cold and hard in his hand. "I am what you made me, Father." He opened the heavy door. (185) Henry separates himself from his father and family and binds himself to Keiko and her family—a Chinese boy in a Japanese family, analogous to the way that Henry grafts and nurtures his Ume tree—a Chinese tree in a Japanese Park. Henry makes this decision thoughtfully—he is conscientious: his senses are heightened and he perceives much. His mind notes the cold brass and the weight of the door. The weight of the door represents the gravity of Henry's choice. Henry's conscience urges him to make a life-changing decision.
Ford culminates the idea that one's experience instructs the conscience by depicting the reconciliation between Henry and his son. Henry's experience with his own father makes him conscious of how he carries on a relationship with Marty, his own son. Henry makes the connection between his behavior and his father's: "[H]e was his father's son, and he could be equally stubborn . . . His father was a horrible communicator. After all the time he'd rebelled against his father's wishes and his father's ways, Henry hated the fact that he wasn't that different form him at all—not where it mattered anyway" (209). Henry, aware of his father's faults, realizes his own. The faults in the relationship between Henry and his father are the same faults in the relationship between Henry and Marty. This reflection moves Henry to work toward mending the problem: "Henry hated being compared with his own father. In Marty's eyes, the plum hadn't fallen far form the tree . . . that's what I've taught by my example, Henry thought, realizing that having Marty help him in the basement might ease more than the physical burden" (84). Henry wants a good relationship with his son. Henry's conscience, longing for good experiences with Marty, urges him to act on experience.
The past that lives within Henry lives within humanity. Henry's struggle to reconcile the past by conscientiously shaping the future mirrors the struggle of every man. Conscience does not act alone in molding outcomes; it needs an acolyte. Just as the conscience instructs the hands and mouth, something must instruct the conscience. Experience speaks to conscience.
GradesFixer. (2018, May, 05) A Self-Aware Mind. Retrived July 19, 2019, from https://gradesfixer.com/free-essay-examples/conscious-conscience/
"A Self-Aware Mind." GradesFixer, 05 May. 2018, https://gradesfixer.com/free-essay-examples/conscious-conscience/. Accessed 19 July 2019.
GradesFixer. 2018. A Self-Aware Mind., viewed 19 July 2019, <https://gradesfixer.com/free-essay-examples/conscious-conscience/>
GradesFixer. A Self-Aware Mind. [Internet]. May 2018. [Accessed July 19, 2019]. Available from: https://gradesfixer.com/free-essay-examples/conscious-conscience/
Review of Mary Rowlandson's Biography, the House Slave, and Incidents in the Life of a Slave Girl Essay
Tennessee Williams' Depiction of Blanche as a Casualty As Illustrated In His Play, A Streetcar Named Desire Essay
True to a Lie: Two Perspectives on Moral Responsibility in "Return of the Soldier" Essay
Peace-Out Troublemaker Essay
Edgar Allan Poe: A Genius or a Psycho? Essay
I Stood There Alone or the Fall of Troy Essay
Whisper of the Devil Essay
Re-Creation and Immortal Fame: The Search for Eternal Life in Macbeth and Coriolanus Essay
The Unusual Allure And Power Of Women In Ulysses And One Hundred Years Of Solitude Essay
Troilus and Criseyde Essays
A Place to Stand Essays
The Art of War Essays
Ode Essays
Wide Sargasso Sea Essays


text:
Topping-out ceremony for Martini Clinic's prostate cancer centre
Clinic among leading global centres for treating prostate tumours - important step for "UKE Future Plan 2050"
© University Hospital Hamburg-Eppendorf (UKE)
The Martini Clinic celebrated the completion of its shell with the traditional raising of the topping-out wreath Thursday (August 5, 2021) at a ceremony attended by Katharina Fegebank, Senator for Science. The new building has been built at a cost of EUR 70 million is expected to open in 2023 as part of the UKE's "Future Plan 2050". The increased capacity should meet the rising demand for care among men with prostate cancer. The Martini Clinic counts among the world leaders in the treatment of prostate tumours and performs around 2,500 operations per year at present.
High standard of care at UKE
"The topping-out ceremony in a far-reaching pandemic demonstrates both the future viability of health care in our city and the metropolitan region, but also the unwavering energy and spirit of the entire team at the Martini Clinic and all those involved in the construction. The new building impressively symbolises the high standard of care that patients with prostate cancer experience here and which is recognised worldwide," said Fegebank. Prof. Dr. Burkhard Göke, Medical Director and Chairman of UKE'S Board, said: "The new Martini Clinic will create ideal conditions for early MRI diagnostics through to chemotherapy under one roof."
Clinic for treatment of prostate cancer
The UKE's overall, forward-looking strategy foresees the construction of ten more buildings and extensions on the campus by 2050. Founded in 2005, the Martini Clinic started with only eight beds and later grew to 72 beds. The new building will have 100 beds and eight operating theatres featuring robot-assisted surgical systems, among other state-of-the-art technology.
cb/sb/pb
uke.de | Press Release
uke.de/2050
Hamburg Metropolitan Region
Hamburg and Berlin to co-operate on digital planning and building
Digitalised administration - agreement signed on construction and planning - first project planned
UKE closes fiscal year 2020 on "satisfactory" note
Net income of EUR 1.2 million - no loss incurred amid pandemic thanks to support from city and German government
New accommodation for XFEL's global researchers
Guest house inaugurated on European XFEL's campus
Staatsoper Hamburg and UKE helping long-term COVID-19 patients
Opera singers coaching people with breathing difficulties in digital voice sessions


text:
Interviews/Reviews
As It Ought To Be
"Blue Collar Blues: The Poetry of Wayne F. Burke"
Posted on March 30, 2020 March 30, 2020 by asitoughttobemagazine
Blue Collar Blues:
The Poetry of Wayne F. Burke
By Arthur Hoyle
Wayne F. Burke is a populist poet living in central Vermont, where he works as a Licensed Practical Nurse. His biography on Amazon tells us that he was born in 1954 in a small Massachusetts manufacturing town. His father had served in the U.S. Marine Corps before becoming the manager of a Mobil Flying-A gas station, and his mother worked in a textile mill. Both his parents died while he was a boy, and he and his three siblings were raised by their paternal grandparents and an uncle. He graduated from Goddard College in 1979 with a degree in Regional and Urban Planning, then took to the road, traveling around the country, working in a variety of occupations unrelated to his degree, and writing. He began publishing his poetry in 2013, when he was fifty-nine years old.
It is not surprising that a poet of such blue-collar origins would write blue collar poems, notable for their blunt honesty, visceral imagery, and gritty situations à la Bukowski. But what really distinguishes Burke, for me, is his persistent use of a deadpan irony that brings both humor and surprise to scenes and situations with dark and often malevolent undertones. This signature attitude, or tone, he uses with skilled effect to jolt his reader into a state of awareness⎯one of the high aims of all art. To sample his unique style and technique, and hear his plain, unpretentious voice, read Escape from the Planet Crouton (Luchador Press, 2019), under review here.
A glance at the titles of the poems in this collection reveals that we are in the presence of a poet of the ordinary and the everyday, the world of highways, farms, tattoos, naps, raindrops, firecrackers, speeding tickets, seedy bars, and sordid streets. But a feral, menacing reality lurks below the surface of this world. The tattoo is worn by an employer who fires the speaker of the poem for coming to work drunk. The tattoo is the number branded on the employer's arm by his captors in a World War II concentration camp. "Raindrops on the eaves/sound like a beautiful/loneliness," the poet lyrically writes, but we learn immediately that he is listening to them to escape "her/talking/ in the darkened room,/high on medication/or on . . ./whatever." The "Nap" is not a restful snooze on a cozy couch; it is the sleep of the homeless narrator in an empty parking lot behind a credit union, "the curb stone a hard cushion/but welcome one."
Burke's sensory language immerses the reader in this dreary underworld. "Polio" is not about polio. It describes a Halloween prank perpetrated in his boyhood by the narrator and his friend Charlie, who "stripped the thorny pulp off horse chestnuts/and put the ebony nuts into/a brown shopping bag/and threw the nuts that night/Halloween/at the Camel's house across the street/until cops came with their shining blue/light." Aged seven, the narrator runs away from his harsh home "down the road/along cracked and gouged sidewalk/a quarter mile to the lime kiln/loud waterfall-roar of machinery/white dust in the air and/smoky white buildings,/trucks banging along the highway/over railroad tracks." The stubby lines with their short rhythms throb a relentless drumbeat of despair.
Many of Burke's poems locate the reader in a scene or situation and tell a story. The stories are often edged with irony and morbid resignation. The runaway boy, frightened by a chained German Shepherd watchdog that barks at him, hightails it home to discover that "Nobody there knew that I had been gone," a line that hints at his neglect and loneliness. While working with a highway maintenance crew he waves at a female high school classmate who drives by in her Cadillac without acknowledging him. In another incident as an adult, he tries to escape homelessness by staying in a room at the YMCA, but gives up when he cannot think of a name to enter in the "in case of emergency notify" box on the registration form. Loneliness and alienation are persistent themes in the collection. In the final poem, titled ungrammatically "It a Lie," the speaker insists "I will never/be in need/never cry/at night/not me/not me/I am/different/breed of/liar."
Escape from the Planet Crouton is arranged into eight sections, several of which have a clear organizing principle, but nearly all of which give voice to the speaker's sense of isolation from the people and society around him. The first section, which opens with the epigraph "the clapboard Inn/My grandfather owned⎯/marble in the dream," deals with the narrator's childhood upbringing in a severe, loveless home. The next section covers his high school and college years, marked by heavy drinking, brushes with the law, and glimpses of the rawness in the wider world. There is a section on his turbulent relationships with women, including a very funny dialogue with "The Old Lady" (his wife), and scattered poems about his health and drinking problems.
An exception to the pattern is Section 3, which is prefaced by the meditative lines "busy/all/morning/watching/the/clouds," a lead-in to poems about art and artists, where Burke finds salvation from the drabness of his ordinary existence. His portrait of Van Gogh is especially moving as it honors "canvases/like portals so vast/and deep/with emptiness/nothing could fill them/but/eternity." He also writes about Kurt Schwitters, Jackson Pollock ("a momma's boy"), fellow poets he met in college, and his progenitor Charles Bukowski, "a misanthrope and/hater of the herd." Henry Miller gets a mention too.
The poem "I Write for the Factory Workers" sums up this poet's artistic sensibility and mission, and so I quote it here in full to give the reader an undiluted dose of Wayne F. Burke.
I Write for the Factory Workers
the bums,
the burn-outs
the renegades who
left town and never returned,
the unmarried
the unheralded,
lumpen and prole
who never made the honor roll
in High School
never were handed a job
or a promotion
or a trophy,
but got probation,
parole,
an eviction notice,
a Dear John letter,
a court summons,
a pink slip,
a knuckle sandwich,
a room in a nut house,
a ride in the paddy wagon,
a jail sentence,
divorce papers,
bad acid,
food poisoning,
herpes simplex,
crabs,
bronchitis,
mononucleosis,
and hangovers that
lasted for days.
It remains to ponder the significance of the title of this volume, and the design of its cover, which pictures a pink and yellow science fiction rocket ship zooming across the star-filled night sky. At the start of Section 5, Burke tells us that "in Croutonville everyone is guilty/until they prove themselves innocent;/the bums gather in the park,/and hot-rodders roar up and down/the empty streets;/dogs bark at all hours/of the spot-lit nights,/and the primary cause of death/is O.D."
Croutonville sounds very much like the hollowed-out core of the American dream of which so many are now dispossessed. Burke has made his escape in the rocket ship of poetry.
Escape from the Planet Crouton is available via Luchador Press
About the Author, Arthur Hoyle: I am the author of The Unknown Henry Miller: A Seeker in Big Sur (Skyhorse/Arcade March 2014). I have also published essays in Huffington Post, Empty Mirror, Across the Margin, and Counterpunch. My second non-fiction book, Mavericks, Mystics, and Misfits: Americans Against the Grain, was published March 17, 2020 by Sunbury Press.
Tagged American Literature, American Poetry, Arthur Hoyle, Blue Collar, Escape from the Planet Crouton, Luchador Press, Wayne F. Burke
Previous Post Mike Acker: "Unholy"
Next Post Sue Blaustein "A Song for Harvest Spiders"
AIOTB Magazine


text:
PHOTO BY: Joe Andrucyk/Executive Office of the Governor
Maryland Governor Larry Hogan
Editor, India America Today & White House Correspondent.
Annapolis – The gubernatorial offices of Maryland got a shot in the arm as Federal Emergency Management Agency (FEMA) announced that federal emergency aid was approved for the state of Maryland to supplement the state, tribes and local recovery efforts in the areas affected by the Coronavirus Disease 2019 (COVID-19) pandemic beginning on January 20, 2020, and continuing. MaryAnn Tierney has been named as the Federal Coordinating Officer for federal recovery operations in the affected area.
Welcoming the announcement, Maryland Governor Larry Hogan said, "We are pleased that our federal partners answered our calls for action and swiftly granted Maryland's request for a Major Disaster Declaration."
"This declaration will help provide much-needed funding for state and local governments and nonprofits, and it will be another important step in Maryland's aggressive and coordinated response to COVID-19," Governor Hogan added.
The announcement came just hours after Governor Hogan pushed for disaster declarations for the states during a teleconference earlier in the day with the White House.
Noting that the "COVID-19 pandemic is having a significant impact on our entire state and country unlike anything we have seen before," Russell Strickland, Executive Director for the Maryland Emergency Management Agency, said, "We have been working alongside Governor Hogan and our local partners to ensure the continued safety and wellbeing of all Marylanders. This declaration is an important and necessary step to continue on our path of resilience."
Tonight's announcement means Maryland will be eligible for reimbursement for the Emergency Protective Measures taken by state and local government agencies and certain non-profit groups under its Public Assistance program under the Robert T. Stafford Act.
Federal funding is available to state, tribal, and eligible local governments and certain private nonprofit organizations on a cost-sharing basis for emergency protective measures (Category B), including direct federal assistance under Public Assistance, for all areas affected by COVID-19 at a federal cost share of 75 percent.
Previous articleGovernor Hogan Urges "Stay Home" Amid Rising COVID-19 Cases
Next articleBloomberg, Hogan Put Faith in Casadevall for COVID-19 Cure


text:
University to construct new surface parking lot west of the current Lot F
This spring, Marquette will begin construction on a new surface lot immediately west of the former Lot F. As the university will soon begin construction of the Athletic and Human Performance Research Center, the former Lot F (located on 12th Street north of Zilber Hall, across from the Al McGuire Center) remains closed. University staff and faculty who parked in that lot will continue parking in Structure 2 (Wells Street Structure). Once completed, the new surface lot will be available to Gesu parishioners on weekends, and Parking Services will continue to share updates about parking designations in Marquette Today.
This summer, the university will also begin implementing its initial phase of the North Commons – an initiative outlined in the Master Plan to significantly enhance green space in the heart of campus (north of Wisconsin Avenue in between Schroeder Hall, the Dr. E. J. O'Brien Jesuit Residence and the Alumni Memorial Union).
President Michael R. Lovell and Fr. Jim Flaherty, S.J., pastor of Church of the Gesu, shared plans this weekend of a mutually agreeable plan for a parking collaboration between Marquette and Gesu.
In their joint letter, President Lovell and Fr. Flaherty said that "Gesu and Marquette have long enjoyed a relationship that goes far beyond our proximity to one another — it is a bond rooted in our Catholic, Jesuit tradition and one built on mutual respect. We want all of you to know that we are both committed to fostering this relationship to the benefit of both institutions. It is in this spirit that we have agreed to meet regularly and maintain an open dialogue with respect to important topics that mutually affect Marquette and the parish.
Further, as outlined in our shared services agreement, Gesu will continue to support Marquette's campus ministry efforts and Marquette will provide Gesu a number of services, including information technology infrastructure and support, facilities services, and public safety."
Filed Under: For Faculty/Staff, For Students, Home - Top Stories, News


text:
Cicurina neovespera is een spinnensoort in de taxonomische indeling van de kaardertjes (Dictynidae).

Het dier behoort tot het geslacht Cicurina. De wetenschappelijke naam van de soort werd voor het eerst geldig gepubliceerd in 2004 door Cokendolpher.

Kaardertjes

redpajama_set_name: RedPajamaWikipedia


This plan helps employees save and invest for retirement on a pre-tax and/or Roth basis. The firm offers a 401(k) matching program. We also offer discretionary profit-sharing contributions after two years of service. Employees decide how to invest their account, choosing from a range of options. Employees can also take advantage of personalized investment and savings advice.
50% match on the first 6% of your salary. Managed by Schwab with decent low-fee fund options. Employer contribution does not fully vest until you reach three years with the company.
The matching is a great perk, and one of the best parts of the benefits package.
What can you tell job seekers about Cornerstone Research's 401K Plan?"
Glassdoor is your resource for information about the 401K Plan benefits at Cornerstone Research. Learn about Cornerstone Research 401K Plan, including a description from the employer, and comments and ratings provided anonymously by current and former Cornerstone Research employees.


text:
Rosenberg vs. Pasha: Distinguishing Two Questions of Foreign Official Immunity
by William S. Dodge
Last week, I responded to my friend John Bellinger's comments about the district court's ruling on foreign official immunity in the Singh case. John has a new post at Lawfare reporting on the Second Circuit's decision in Rosenberg v. Pasha, which affirmed dismissal of the Mumbai bombing case on foreign official immunity grounds. He ends his post by noting the distinction between two different questions: (1) whether gross violations of human rights are official acts to which conduct-based immunity attaches under federal common law; and (2) whether courts should recognize a jus cogens exception to foreign official immunity once that immunity has attached. Since the difference between these two questions may not be obvious to everyone, a few words of explanation may help clarify an important distinction. (For more extensive discussion of the analytical structure of immunities, see here and here.)
Foreign official immunity can attach for various reasons. Some foreign officials are entitled to immunity based on their status. This is often called status-based immunity. Under the doctrine of head-of-state immunity, for example, sitting heads of state, heads of government, and foreign ministers are immune from suit in U.S. courts for any act, official or not. Courts have refused to recognize a jus cogens exception once head-of-state immunity has attached on the basis of the defendant's status. See, e.g., Ye v. Zemin, 383 F.3d 620, 625-27 (7th Cir. 2004); SOS Attentats et Béatrice Castelnau d'Esnault v. Gadafy, 125 Int'l L. Rep. 490 (French Court of Cassation) (Mar 13, 2001); Case Concerning the Arrest Warrant of 11 April 2000 (Dem. Rep. Congo v. Belg.), 2002 I.C.J. 3, ¶ 58 (Feb. 14). Sometimes immunity is granted by statute, and courts have refused to recognize jus cogens exceptions to statutory schemes extending immunity to foreign states and/or foreign officials. See, e.g., Siderman de Blake v. Republic of Argentina, 965 F.2d 699, 718-19 (9th Cir. 1992); Jones v. Ministry of Interior of Saudi Arabia, [2007] 1 A.C. 270, ¶¶ 14-28 (H.L. 2006) (Lord Bingham); id. ¶¶ 66-99 (Lord Hoffman); Zhang v. Zemin, NSWSC 1296, ¶¶ 20–23 (New South Wales S. Ct. 2008); Bouzari v. Islamic Republic of Iran, 71 OR (3d) 675, at ¶ 95 (Ontario Ct. of App. 2004). In other words, once immunity has attached—by international law, by federal common law, or by statute—courts have been reluctant to find an exception even for gross violations of human rights.
Foreign officials not entitled to immunity based on their status, are immune from suit in U.S. courts only for their "official acts." This is often called conduct-based immunity. U.S., foreign, and international courts have consistently held that gross violations of human rights are not official acts to which conduct-based immunity attaches. See, e.g., Yousuf v. Samantar, 699 F.3d 763, 776 (4th Cir. 2012); Enahoro v. Abubakar, 408 F.3d 877, 893 (7th Cir. 2005); Hilao v. Estate of Marcos, 25 F.3d 1467, 1472 (9th Cir. 1994); Doe v. Qi, 349 F. Supp. 2d 1258, 1287 (N.D. Cal. 2004); Cabiri v. Assasie-Gyimah, 921 F. Supp. 1189, 1198 (S.D.N.Y. 1996); Xuncax v. Gramajo, 886 F. Supp. 162, 175-76 (D. Mass. 1995); Regina v. Bow Street Metropolitan Stipendiary Magistrate ex parte Pinochet Ugarte (No.3), [2000] 1 A.C. 147, 205 (H.L. 1999) (Lord Browne-Wilkinson); Attorney General of Israel v. Eichmann, 36 I.L.R. 277, 309-10 (Israel S. Ct. 1962); 1 Trial of the Major War Criminals Before the International Military Tribunal 223 (1947). Courts have not had to reach the question whether there is a jus cogens exception to conduct-based immunity, because no immunity attaches to the jus cogens violation in the first instance. In short, as D.C. Circuit Judge Stephen Williams has noted, the question whether an immunity attaches is "quite distinct" from the question whether to recognize exceptions to an existing immunity. Belhas v. Ya'alon, 515 F.3d 1279, 1292 (D.C. Cir. 2011) (Williams, J., concurring).
John says that the Second Circuit's decision in Rosenberg clarifies a split with the Fourth Circuit's decision in Samantar. Not on the jus cogens issue. The Second Circuit has held that it is absolutely bound by State Department determinations of immunity, including determinations conduct-based immunity. Matar v. Dichter, 563 F.3d 9, 15 (2d Cir. 2009). The question for the Second Circuit has not been whether gross human rights violations are official acts—it considers itself bound by the executive's determination in each case—but whether to recognize a jus cogens exception to immunity that has attached by virtue of the executive's determination. The Fourth Circuit, on the other hand, has held that it is not absolutely bound by the State Department's conduct-based immunity determinations (although it gives them "substantial weight"). Yousuf v. Samantar, 699 F.3d 763, 773 (4th Cir. 2012). It has therefore had to answer the question whether jus cogens violations are "official acts" to which conduct-based immunity attaches, and it said no. Id. at 776. (For further discussion, see here.)
In other words, the Fourth Circuit in Samantar answered the first question (whether gross violations of human rights are official acts to which conduct-based immunity attaches under federal common law), while the Second Circuit in Rosenberg and Matar answered the second question (whether courts should recognize a jus cogens exception to foreign official immunity once that immunity has attached). Because these courts have addressed different questions, there is currently no circuit split that the Supreme Court needs to resolve (the apparent split over the level of deference to the State Department did not affect the outcome in Samantar, because the Fourth Circuit agreed with the executive's determination that Samantar was not immune).
It is also important to note that the State Department's determination of immunity in the Rosenberg case was not based on a theory that jus cogens violations are official acts entitled to conduct-based immunity. As I have explained before, the executive's determination in Rosenberg was based on the failure of the complaint to plead facts sufficiently establishing the defendants' complicity in the Mumbai bombings. In this and other filings, the Obama Administration has been careful to leave the door open to denying conduct-based immunity in cases of well-substantiated human rights violations, something it did in the Samantar case. As I said when the Rosenberg determination was originally filed, "[i]f the plaintiffs' claims were well substantiated, it would be remarkable to conclude that planning and supporting terrorist attacks against American citizens were 'official acts' entitled to immunity from suit in U.S. courts."
Alien Tort Statute,
Immunity,
immunity for official acts,
official act immunity,
Rosenberg vs Pasha,
Samantar v. Yousuf,
status-based immunity
William S. Dodge
Martin Luther King, Jr. Professor of Law at the University of California, Davis, School of Law and Co-Reporter for the Restatement (Fourth) of Foreign Relations Law: Jurisdiction. From August 2011 to July 2012, he served as Counselor on International Law to the Legal Adviser at the U.S. Department of State.
Annie Donaldson is Not the President's "Alter Ego"
June 24, 2019 by Ryan Goodman and John T. Nelson
The Three-Level Game in the White House Effort to Block McGahn's Testimony
May 21, 2019 by Bob Bauer
Somalia War Crimes Trial Starts Monday, as Another Survivor Seeks Justice
May 10, 2019 by Amanda McCaffrey
A Confusing ICC Appeals Judgment on Head-of-State Immunity
May 7, 2019 by Ben Batros
Preview of the International Criminal Court Appeals Judgment on Al-Bashir and Head of State Immunity
Letter to the Editor – Germany's Extradition Request for Gen. Jamil Hassan, with U.S. Support
March 13, 2019 by Claus Kreß
Liberian War Crimes Claims Survive in Alien Tort Statute Case
February 27, 2019 by Ela Matthews, Nushin Sarkarati, Megan Corrarino and Elizabeth Nielsen
December 11, 2018 by Ted R. Bromund
Jam v. International Finance Corp.: May International Organizations Violate Rights with Impunity?
October 30, 2018 by Harold Hongju Koh and Patrick Pearsall
Dispelling Some Myths About Consular Immunity and the Khashoggi Investigation
October 18, 2018 by Chimène Keitner


Limelight: "The Last Five Years"
Thurs., Fri., and Sat. from July 29 to August 21, 2016 at Limelight Theatre, Inc.
The Limelight Theatre presents the musical "The Last Five Years" from July 29 to August 21, 2016. Showtimes are 7:30 p.m. on Thursdays through Saturdays and 2:00 p.m. on Sundays for the duration of the show. The play will take place in the Koger-Gamache Studio.
The musical "The Last Five Years" features the five-year relationship between rising novelist Jamie and struggling actress Cathy. Set in New York, the musical has a unique storytelling approach. Jamie travels chronologically in time while Cathy travels from the end of their relationship back to the very beginning. The two characters only meet once in the middle of the show for their wedding. The musical is an emotionally explosive exploration of a relationship's anatomy.
The Limelight Theatre production of "The Last Five Years" is directed by Bradley Akers, with Shelli Long as Music Director, and features Jamie Wellerstein and Catherine Hiatt in the two main roles.
Admission: Tickets are $26. Tickets for the "Terrific Tuesday" show on August 2, 2016, are $15. For this show only, the Limelight is offering a special price of $15 for teachers.
When: From July 29 to August 21, 2016: Thursdays, Fridays, and Saturdays at 7:30 p.m.; Sundays at 2:00 p.m. Preview night is 7:30 p.m. on Wednesday, July 28; special "Terrific Tuesday" show at 7:30 p.m. on August 2, 2016.


Two friends compete to see who can do more push ups.
A street performer does some cartwheels.
berlingerl bookmarked the world Calvin & Hobbes.
diamondshirt168 liked the world Through the Rabbit Hole.
diamondshirt168 bookmarked the world Through the Rabbit Hole.
cleverspy88 bookmarked the world Through the Rabbit Hole.
bazeball liked the world Calvin & Hobbes.
bazeball commented on the world Calvin & Hobbes.
awesomeness123 liked the world Push up competition.
bluesky bookmarked the world The Race between Rabbit and Turtle.
bluesky bookmarked the world Through the Rabbit Hole.
bluesky bookmarked the world Push up competition.