text:
package eu.bcvsolutions.idm.ic.filter.api;

import eu.bcvsolutions.idm.ic.api.IcConnectorObject;

/**
 * Basic interface to match a {@link IcConnectorObject}.
 *
 * @author Will Droste
 * @since 1.0
 */
public interface IcFilter {
    /**
     * Determines whether the specified {@link IcConnectorObject} matches this
     * filter.
     *
     * @param obj
     *            - The specified IcConnectorObject.
     * @return {@code true} if the object matches (that is, satisfies all
     *         selection criteria of) this filter; otherwise {@code false}.
     */
    boolean accept(IcConnectorObject obj);

    /**
     * Applies a {@code IcFilterVisitor} to this {@code IcFilter}.
     *
     * @param <R>
     *            The return type of the visitor's methods.
     * @param <P>
     *            The type of the additional parameters to the visitor's
     *            methods.
     * @param v
     *            The filter visitor.
     * @param p
     *            Optional additional visitor parameter.
     * @return A result as specified by the visitor.
     * @since 1.4
     */
    <R, P> R accept(IcFilterVisitor<R, P> v, P p);
}

redpajama_set_name: RedPajamaGithub


text:
Die Liste der Mannschaftskader der Primera División (Schach) 1975 enthält alle Spieler, die in der spanischen Primera División im Schach 1975 mindestens eine Partie spielten mit ihren Einzelergebnissen.

Allgemeines

Während CA Schweppes Madrid, CA Peña Rey Ardid Bilbao und RCD La Coruña mit je fünf Spielern auskamen, spielten bei Asociación Barcinona acht Spieler mindestens eine Partie. Insgesamt kamen 63 Spieler zum Einsatz, von denen 12 an allen Wettkämpfen teilnahmen.

Punktbester Spieler war Juan Manuel Bellón López (CA Schweppes Madrid) mit 8,5 Punkten aus 9 Partien. Antonio Medina García (CE Espanyol Barcelona) erreichte 6,5 Punkte aus 9 Partien, Ricardo Calvo Mínguez (CA Schweppes Madrid) 6 Punkte aus 8 Partien. Ángel Fernández Fernández (Caja Insular de Ahorros) erreichte als einziger Spieler 100 %, dieser spielte vier Partien.

Legende

Die nachstehenden Tabellen enthalten folgende Informationen:

 Nr.: Ranglistennummer
 Titel: FIDE-Titel; GM = Großmeister, IM = Internationaler Meister
 Land: Verbandszugehörigkeit gemäß Elo-Liste von Januar 1975; ARG = Argentinien, DEN = Dänemark, ESP = Spanien
 Elo: Elo-Zahl in der Elo-Liste von Januar 1975
 G: Anzahl Gewinnpartien
 R: Anzahl Remispartien
 V: Anzahl Verlustpartien
 Pkt.: Anzahl der erreichten Punkte
 Partien: Anzahl der gespielten Partien

CA Schweppes Madrid

CE Espanyol Barcelona

CE Terrassa

CA Caja Insular de Ahorros

Asociación Barcinona

CA Peña Rey Ardid Bilbao

UGA Barcelona

RCD La Coruña

CA Maspalomas

GE Aviaco Madrid

Weblinks
 Saisonübersicht bei olimpbase.org (englisch)

Primera División (Schach)
Wikipedia:Liste
Schach 1975

redpajama_set_name: RedPajamaWikipedia


text:
\section{INTRODUCTION}
\IEEEPARstart{D}{esigning} robot team systems remains a grand challenge in robotics and will have great advances and impacts in the next 5 to 10 years \cite{yang2018grand}.
Aerial robot teams, as a popular topic in the team community, can solve many challenges faced by human civilization, such as natural disasters, space colonization, and air traffic.

Judging by the way to deploy computation and communication resources, the planning of aerial robot teams can be categorized as centralized and decentralized methods.
Centralized methods \cite{mellinger2012mixed,augugliaro2012generation,honig2018trajectory,park2020efficient} simultaneously solve the planning problem for all agents and then allocate
the plans to each one.
However, the interaction among agents makes the complexity grow combinatorially.
Also, it is impractical to share information across the large-scale robot teams online.
The abovementioned issues prevent the application of centralized methods to large robot teams in real world.
Recently, our community witnesses the emergence of decentralized methods \cite{tordesillas2021mader,zhou2020ego,zhou2021decentralized}. Although they can be applied to larger-scale teams by amortizing the computation and communication, the planning only uses single agent's environmental information. Therefore, the planning quality and success rate deteriorate as scale increases, especially in obstacle-dense environments.

\begin{figure}[t]
	\centering
	\includegraphics[width=1.0\linewidth]{indoor_7b}
	\captionsetup{font={small}}
	\caption{Indoor experiments.}
	\label{pic:indoor}
	\vspace{-0.4cm}
\end{figure}

\begin{figure}[t]
	\centering
	\includegraphics[width=1.0\linewidth]{sim_ben}
	\captionsetup{font={small}}
	\caption{Passing through a 0.8x1.5m gate with EGO-Swarm, DSTO and the proposed method.}
	\label{pic:sim_ben}
	\vspace{-1.6cm}
\end{figure}

Investigating the above issues, we propose an enhanced decentralized aerial robot team system with group planning.
This paper tackles the conflict between efficiency and quality, balances the coordination of individuals and groups, and introduces a robust and flexible framework (in Fig. \ref{pic:system_framework}) for aerial robot teams.
We consider the key challenges for building an applicable large-scale aerial robot team to be twofold.
There is a need for a powerful trajectory planning backbone, as well as a flexible grouping mechanism to solve potential conflicts originating from agents and environments.
When agents cluster in a narrow space, we dynamically form several groups based on their spatial distribution, while regarding each agent as an independent individual when they disperse.
As for groups, we propose a method called \textit{group planning}, as a portable plugin for fully decentralized methods. It conducts trajectory planning utilizing complete information of multiple agents where hard-to-resolve inter collisions may happen.
We first implement an online multi-agent pathfinding method to generate multiple collision-free paths. Based on these paths, we propose a trajectory optimization method such that all trajectories can converge to the joint optimum.
Exploiting our \textit{group planning} strategy, the proposed system is a significantly enhanced decentralized one over the solution in \cite{zhou2021decentralized}.

We compare our method with state-of-the-art methods. The results show that our method can generate the shortest flight time and distance of trajectory with the fewest replan times.
In addition, we implement a systematic solution for decentralized autonomous aerial robot teams, including onboard perception, planning, control, and communication.
The contributions of this paper are summarized as follows:

1) A more efficient three-dimensional online multi-agent pathfinding method, combined with the ECBS\cite{Barer2014SuboptimalVO}, for finding multiple collision-free paths that are close to the optimal trajectories.

2) An enhanced decentralized autonomous aerial robot team system with group planning where joint optimization is conducted on demand to significantly improve planning quality and success rate.

3) Open-source code\footnote{https://github.com/ZJU-FAST-Lab/EDG-TEAM} of our system that is extensively validated by simulations and real-world experiments.

\section{RELATED WORK}

\subsection{Multi-Agent Pathfinding}

\begin{table}[h]
	\centering
	\caption{Evaluation of MAPF algorithms}
	\label{tab:mapf_eva}
	\renewcommand{\arraystretch}{1.35}
	\begin{tabular}{|c|c|c|c|c|}
		\hline
		\textbf{Method} &
		\textbf{Optimality} &
		\textbf{Completeness} &
		\textbf{Scalability} &
		\textbf{\begin{tabular}[c]{@{}c@{}}Run\\  Time\end{tabular}} \\ \hline
		CA*           & Sub-optimal & Incomplete & \multirow{2}{*}{Very Small} & \begin{tabular}[c]{@{}c@{}}Very\\  Slow\end{tabular}          \\ \cline{1-3} \cline{5-5}
		\begin{tabular}[c]{@{}c@{}}A*+\\ ID/OD\end{tabular} &
		\multirow{4}{*}{Optimal} &
		\multirow{5}{*}{\textbf{Complete}} &
		&
		\multirow{4}{*}{Slow} \\ \cline{1-1} \cline{4-4}
		M*            &             &            & \multirow{3}{*}{Small}      &                                                               \\ \cline{1-1}
		ICT           &             &            &                             &                                                               \\ \cline{1-1}
		CBS           &             &            &                             &                                                               \\ \cline{1-2} \cline{4-5}
		\textbf{ECBS} & Sub-optimal &            & \textbf{Very Large}         & \textbf{\begin{tabular}[c]{@{}c@{}}Very\\  Fast\end{tabular}} \\ \hline
	\end{tabular}
\end{table}

The MAPF problem is to find a spatial-temporal collision-free path for each agent in a group, given prescribed start and goal positions. Table \ref{tab:mapf_eva} summarizes the properties of the search-based methods corresponding to MAPF.

If the A* search is simply performed by joining the state spaces of all agents, the search space will grow exponentially with the number of the agents, resulting in computational intractability.
Cooperative A* (CA*)\cite{silver2005cooperative} performs A* searches in priority order to solve the combinatorial explosion problem, which is suboptimal and incomplete.
A*+ID\cite{standley2010finding} breaks the problem down into several independent subproblems and solves each one separately. When there is a conflict between any two subproblems, the corresponding subproblems are combined to solve the conflict. The solutions of all subproblems are combined as the final solution until no conflict occurs, but the algorithm's scalability is restricted.
A*+OD\cite{standley2010finding} specifies that only one agent can move at a time, reducing the search dimension but increasing the depth of the search tree.
M*\cite{wagner2011m} dynamically changes the search dimension based on whether or not a conflict occurs. When there is no conflict, each agent takes the best action possible on its own; otherwise, the local search dimension is increased during the conflict.
Conflict-based methods address the problem on two levels. The high level converts conflicts into constraints added to agents, while the low level performs a search.
ICTS algorithm\cite{sharon2013increasing} searches on an increasing cost tree (ICT).
CBS algorithm\cite{sharon2015conflict} performs searching on a constraint tree (CT). When there is a conflict, the high level creates a new node and converts the conflict into a constraint added to the agents, while the low-level agents perform A* searches. When all agents reach their respective targets with no conflict, the node is the final solution. The CBS is optimal and complete, but it is more time-consuming to solve.
ECBS algorithm\cite{Barer2014SuboptimalVO} sacrifices a small amount of solution quality in exchange for greater efficiency and scalability.

The methods mentioned above have limitations, and there is no universal winner. The paper uses MAPF to generate the initial paths and provide an initial value for the back-end optimization. We prefer algorithms with high completeness, scalability, and efficiency, even slightly sacrificing some optimality.
We choose the ECBS algorithm as the front-end of group planning based on comparisons. Because most current MAPF implementations are in a two-dimensional or offline three-dimensional environment\cite{Barer2014SuboptimalVO,honig2018trajectory,park2020efficient}, we implement the ECBS algorithm in an online three-dimensional gridmap and add a tie breaker function to improve search efficiency and solution quality.

\subsection{Aerial Robot Teams}

For centralized strategies, the methods proposed by Mellinger and Augugliaro\cite{mellinger2012mixed,augugliaro2012generation} can generate feasible trajectories for small aerial robot teams in a few seconds. However, they hardly handle large aerial robot teams and have limited application scope.
Honig and Park\cite{honig2018trajectory,park2020efficient} use B-spline or B\'ezier to generate safe and dynamically feasible trajectories for aerial robot teams in an offline known environment. The convex hull of the B-spline or the B\'ezier compresses the solution space, preventing a trajectory from being aggressive near its physical limits. Similar to ours, they also use the ECBS algorithm for a front-end search. However, our implementation is more efficient, and the generated paths are closer to the optimal trajectories.

\begin{figure*}[ht]
	\centering
	\includegraphics[width=0.9\linewidth]{system_framework}
	\captionsetup{font={small}}
	\caption{Enhanced Aerial Robot Team Framework}
	\label{pic:system_framework}
	\vspace{-0.5cm}
\end{figure*}

For decentralized strategies,
Tordesillas et al.\cite{tordesillas2021mader} propose a decentralized asynchronous solution that employs MINVO basis to alleviate the issue of compressed solution space. However, the work is only validated through simulation.
Zhou et al.\cite{zhou2020ego} propose a decentralized and asynchronous systematic solution that can be used in real world. Due to the use of B-spline, optimizing the time term is difficult, which results in twisted trajectories when multiple drones cluster.
To solve the problem of the trajectory twist, Zhou et al.\cite{zhou2021decentralized} propose a spatial-temporal optimization solution based on MINCO\cite{wang2021geometrically}. However, the planning quality and success rate decrease dramatically when multiple drones cluster. The proposed method solves the problem.

\section{Enhanced Aerial Robot Team Framework}
\textbf{Group Planning Criteria}~ \textit{A team contains $n$ agents, and the distance between the agents$\{a_i, a_j\}$ is $d_{ij}$, if and only if
	\begin{gather}
	n_{min} \leq n \leq n_{max}~(n_{min} \geq 2),\\
	d_{ij} \leq d_{safe} ~(1 \leq i \leq n-1,~i \textless j \leq n),
	\end{gather}
	the n agents satisfy the group planning criteria, where $n_{min}$ and $n_{max}$ are the upper and lower limits of the team number. $d_{safe}$ is the safety distance.}

The proposed framework is illustrated in Fig. \ref{pic:system_framework}. The \textit{Group Check} module receives agents' odometry data, and the agent who meets the group planning criteria switches to the group planning mode. Each agent shares the start and local target positions and local map with the core agent in the group. Because of the cooperation among these agents, we define these agents as a group. Otherwise, the agent that does not meet the group planning criteria switches to single-agent planning\cite{XinZhou2020EGOPlannerAE}.

The \textit{group planning} consists of front-end \textit{efficient multi-agent pathfinding} (Section \ref{sec:path}) and back-end \textit{group trajectory joint optimization} (Section \ref{sec:traj}). The \textit{efficient multi-agent pathfinding} performs two-level searches based on obstacles and conflicts among agents to generate multiple collision-free paths. Based on these paths, the \textit{group trajectory joint optimization} generates multiple optimal trajectories in a coarse-to-fine process. It first prunes the paths and creates the intial trajectories as the initial value of the optimization problem. Then, these trajectories are jointly optimized. Finally, multiple safe, dynamically feasible, and minimum control trajectories\cite{wang2021geometrically} are executed.

\section{Efficient Multi-agent Pathfinding}
\label{sec:path}

This section aims to find a collision-free path closer to the optimal trajectory for each agent in the group. For the first time, we implement a more efficient online multi-agent pathfinding (EMAPF) method on a three-dimensional (3D) gridmap based on ECBS\cite{Barer2014SuboptimalVO}.

Like ECBS, our method performs high-level and low-level searches in Algorithm 1. The two level searches use focal search ($f_1, f_2$)\cite{Barer2014SuboptimalVO}, where $f_1$ and $f_2$ have different meanings at two levels. The focal search contains two lists OPEN and FOCAL, which can limit the maximum cost of the solution to $\omega*C^*$ ($\omega$ is the suboptimal factor. $C^*$ is the minimum cost of the node in OPEN.). $f_1$ determines the nodes in FOCAL. FOCAL is subset of OPEN that includes all nodes n in OPEN where $f_1(n) \leq \omega * f_{1_{min}}$ ($f_{1_{min}}$ is the minimal value of $f_1$.). $f_2$ determines which node in FOCAL should be expanded.

In high level, the search is performed on a Conflict Tree (CT) consisting of multiple nodes. The solution of a node contains the paths of all the agents$\{a_1, ..., a_i, ..., a_k\}$ in the group. If a conflict exists among the paths in the extended node, it is converted into a low-level constraint to form a new node. The search terminates until we get a collision-free node containing all agents' collision-free paths in the group. In low level, the agent performs constraint-based pathfinding, and the node represents the agent's position. The specific implementation of the two level searches in our method is detailed as follows.

\subsection{High-level Search}

High-level search applies focal search $(f_1, f_2)$ on a CT. The goal is to find a conflict-free node. In high level, $f_1$ is the cost of a CT's node, and $f_2$ is an inadmissible heuristic function that represents the number of the CT's node conflicts. The lower bound ($LB$) and the FOCAL of the CT are as follows:
\begin{equation}
LB = min (LB(n)|n \in OPEN),
\end{equation}
\begin{equation}
FOCAL = \{n|n\in OPEN, n.cost \leq LB \cdot \omega\},
\end{equation}
where $n$ is a CT's node. $LB(n)$ and $n.cost$ come from the return value of low-level search.

\subsection{Low-level Search}

\setlength{\textfloatsep}{-15pt}
\begin{algorithm}[t]
	\label{alg:emapf}

	\KwIn{startPositions, goalPositions, 3D Gridmap\\
		S.constraints = $\emptyset$ // S is start node.\\
		S.solution = find paths using \textbf{lowLevelSearch()}\\
		S.cost = $\sum_{i} S.solution[i].cost$\\
		S.LB = $\sum_{i} S.solution[i].f_{min}$\\}
	\KwOut{Goal node solution}

	Insert S to OPEN\\
	Insert S to FOCAL\\
	\While{OPEN not empty}{
		\If{the lowest solution cost increase in OPEN}{expand FOCAL from OPEN}
		N $\leftarrow$ lowest conflict node from FOCAL\\
		\If{N not conflict}{\Return{N.solution} // N is goal node.}
		Constraints $\leftarrow$ getFirstConflict(N)\\
		\ForEach{$a_{i}$ in Constraints}{
			P $\leftarrow$ new node\\
			P.constraints $\leftarrow$ N.constraints + ($a_i$,s,t)\\
			P.solution = N.solution\\
			Update P.solution by invoking \textbf{lowLevelSearch($a_i$)}\\
			P.cost = $\sum_{i} P.solution[i].cost$\\
			P.LB = $\sum_{i} P.solution[i].f_{min}$\\
			Insert P into OPEN\\
			\If{P.cost satisfies the condition of FOCAL}{Insert P in FOCAL}
		}
	}
	\caption{Efficient Multi-Agent Pathfinding}

\end{algorithm}

\begin{figure}[h]
	\centering
	\includegraphics[width=1.0\linewidth]{traversal_space_comparison}
	\captionsetup{font={small}}
	\caption{The impact of tie breaker on traversal space; The light blue area indicates traversal space. The red line indicates the path.}
	\label{pic:traversal_space_comparison}
	\vspace{-0.1cm}
\end{figure}

Low-level search applies focal search $(f_1, f_2)$ to find a path for each agent $a_i$. In low level, we set $f_1 = g + h + t$, where $g$ is the current best estimate of the accumulated cost from the start node to the current node, $h$ is the estimated lowest cost from the current node to the goal node. Function $t$ is the distance from the current traversed node to the connection line between the start and goal nodes, called the $tie~breaker$ function. $f_2$ is an inadmissible heuristic function representing the number of conflicts in the current path.
The purposes of designing the $tie~breaker$ function $t$ are: (1) to reduce the traversal space; In Fig. \ref{pic:traversal_space_comparison}, if $f_1$ is set to $f = g + h$ as in the $A^*_\epsilon$ algorithm \cite{Pearl1982StudiesIS}, there will be multiple nodes with the same $f$ value when searching the path, which would result in a larger traversal space; (2) to make the searched path closer to the optimal trajectory.
The entire search is performed on a real-time updated 3D gridmap, and it only takes $O(1)$ time complexity to determine whether the traversed node is occupied.

A lower bound on the cost of the path for agent $a_i$ is $f_{min}(i)$ in the low-level search. Therefore, we can construct the lower boundary $LB(n)$ and the cost of the current CT's node $n$ in high-level search as follows:
\begin{gather}
LB(n) = \sum_{i=1}^k f_{min}(i),\\
n.cost = \sum_{i=1}^k cost(i),
\end{gather}
where $k$ is the number of agents in the group. The low-level search will return to the high-level search with newly updated $LB(n)$ and $n.cost$ of the CT's node $n$.

In summary, our method reduces traversal space during the search process while efficiently checking the information about obstacles. The obtained paths are close to the optimal trajectories (see Fig. \ref{pic:ecbs}), providing a good initial value for trajectory optimization. The quantitative comparison is shown in the TABLE \ref{tab:comparisons}.

\section{Group Trajectory Joint Optimization}
\label{sec:traj}

This section aims to make all agents' trajectories in the group converge on a joint optimum. Therefore, we jointly optimize all trajectories. However, it is challenging to achieve reciprocal avoidance among dynamically changing trajectories. We address the problem in Section \ref*{sec:swarm_avoid}. The trajectory representation and the joint trajectory optimization problems are detailed as follows.

\subsection{MINCO Trajectory Class}

In this paper, we adopt $\mathfrak{T}_{\mathrm{MINCO}}$\cite{wang2021geometrically} for trajectory representation, which is a minimum control effort polynomial trajectory class defined as
\begin{align*}
\mathfrak{T}_{\mathrm{MINCO}} = \Big\{&p(t):[0, T]\mapsto\mathbb{R}^m \Big|~\mathbf{c}=\mathcal{M}(\mathbf{q},\mathbf{T}),~\\
&~~\mathbf{q}\in\mathbb{R}^{m(M-1)},~\mathbf{T}\in\mathbb{R}_{>0}^M\Big\},
\end{align*}
where $\mathbf{q}=(\mathbf{q}_1,\dots,\mathbf{q}_{M-1})$ denotes the intermediate waypoints and $\mathbf{T}=(T_1, T_2, \dots, T_M)\tp$ denotes the duration for all pieces. p(t) is an $m$-dimensional $M$-piece polynomial trajectory with degree $N = 2s - 1$, $s$ is the order of integrator chain. The $i$-th piece of $p(t)$ is defined by\\
\begin{equation}
p_i(t)=\mathbf{c}_i\tp\beta(t),~\forall t\in[0,T_i],
\end{equation}
where $\mathbf{c} = (\mathbf{c}_1\tp, \dots, \mathbf{c}_M\tp)\tp \in \mathbb{R}^{2Ms \times m}$ the polynomial coefficient, $\mathbf{c}_i\in\mathbb{R}^{2Ms \times m}$ is the cofficient matrix of the $i$-th piece.$\beta(t)=[1, t, \cdots, t^N]\tp$ is the natural basis.

All trajectories in $\mathfrak{T}_{\mathrm{MINCO}}$ are compactly parameterized by only $q$ and $T$. Evaluating an entire trajectory from $q$ and
$T$ can be done via the linear-complexity
formulation:
\begin{equation}
\label{eq:mapping}
\mathbf{c}=\mathcal{M}(\mathbf{q},\mathbf{T}).
\end{equation}

The task-specific second-order continuous penalty functions $F(\mathbf{c},\mathbf{T})$ with available gradients are applicable to $\mathfrak{T}_{\mathrm{MINCO}}$ trajectories. The corresponding objective of $\mathfrak{T}_{\mathrm{MINCO}}$ is computed as:
\begin{equation}
J(\mathbf{q},\mathbf{T})=F(\mathcal{M}(\mathbf{q},\mathbf{T}), \mathbf{T}).
\end{equation}
The mapping Eq.\ref{eq:mapping} gives a linear-complexity way to compute $\partial J/\partial\mathbf{q}$ and $\partial J/\partial\mathbf{T}$ from the corresponding $\partial F/\partial\mathbf{c}$ and $\partial F/\partial\mathbf{T}$. Sequentially, a high-level optimizer can optimize the objective efficiently.

\subsection{Joint Optimization Problem Formulation}

The basic requirements for trajectories in the group include safety, smoothness, and dynamical feasibility. Meanwhile, it is preferable to minimize control effort cost and execution time of all trajectories.

We adopt the compact parameterization of $\mathfrak{T}_{\mathrm{MINCO}}$, temporal constraint elimination, and constraint penalty to transform trajectories generation problem into an unconstrained nonlinear optimization problem:
\begin{equation}
\label{eq:objfun}
\min_{\cup_{K}\mathbf{q},\mathbf{T}}~ \sum_{K}{\lambda\cdot{[J_e, J_t, J_d, J_o, J_w, J_u]}},
\end{equation}
where K is the number of agents in the group, $\lambda$ is the weight vector.

\subsubsection{Control Effort $J_e$}
The control effort cost of the k-th agent trajectory and the gradients for its $i$-th piece are:
\begin{gather}
J_e = \sum_{i}{\int_{0}^{T_i}{\norm{p^{(s)}_i(t)}^2\df{t}}},\\
\frac{\partial J_e}{\partial \mathbf{c}_i}=2 \left( \int_{0}^{T_i} \beta^{(s)}(t)\beta^{(s)}(t)^{\tp} dt \right) \mathbf{c}_i,\\
\frac{\partial J_e}{\partial T_i}=\mathbf{c}_i\tp\beta^{(s)}(T_i)\beta^{(s)}(T_i)^{\tp}\mathbf{c}_i.
\end{gather}

\subsubsection{Temporal Constraint Elimination}
An open-domain constraint is $\mathbf{T} \succ \mathbf{0}$, which is directly eliminated by variable transformations as is done in\cite{wang2021geometrically}:
\begin{equation}
\label{eq:TDiffTransformation1}
T_i=e^{\tau_i},
\end{equation}
where $\tau_i$ is the unconstrained virtual time.

\textit{Execution Time Cost $J_t$:}
The execution time cost $J_t=\sum_{i=1}^{M} T_i$ and its gradient ${\partial J_t}/{\partial \mathbf{c_i}} = \mathbf{0}$, ${\partial J_t}/{\partial \tau_i} = ({\partial J_t}/{\partial T_i}) e^{\tau_i}$.

\subsubsection{Penalty for Continuous-Time Constraints}
Continous-time constraints $\mathcal{G}(p(t),\dots,p^{(s)}(t)) \preceq \mathbf{0}, \forall t\in[0,T]$ contain infinite inequality constraints that cannot be directly solved using constrained optimization. We transform $\mathcal{G}$ into finite inequality constraints using integral of constraint violations\cite{Jennings1990ACA}. The penalty with gradient for k-th agent trajectory can be derived:
\begin{subequations}
\label{eq:PieceTimeIntegralPenalty}
\begin{gather}
\allowdisplaybreaks[4]
J_\Sigma(\mathbf{c},\mathbf{T})=\sum_{i=1}^{M}{J_i(\mathbf{c}_i,T_i,\kappa_i)},\\
J_i(\mathbf{c}_i,T_i,\kappa_i)=\frac{T_i}{\kappa_i}\sum_{j=0}^{\kappa_i}\bar{\omega}_j\chi^\mathrm{T}\max{(\mathcal{G}(\mathbf{c}_i,T_i,\frac{j}{\kappa_i}),\mathbf{0})^3},\\
\frac{\partial J_\Sigma}{\partial \mathbf{c}_i} = \frac{\partial J_\Sigma}{\partial \mathcal{G}} \frac{\partial \mathcal{G}}{\partial \mathbf{c}_i},~
\frac{\partial J_\Sigma}{\partial T_i} = \frac{J_i}{T_i} + \frac{\partial J_\Sigma}{\partial \mathcal{G}} \frac{\partial \mathcal{G}}{\partial t} \frac{\partial t}{\partial T_i},\\
\frac{\partial J_\Sigma}{\partial \mathcal{G}} = 3 \frac{T_i}{\kappa_i}\sum_{j=0}^{\kappa_i}\bar{\omega}_j\max{(\mathcal{G}(\mathbf{c}_i,T_i,\frac{j}{\kappa_i}),\mathbf{0})^2\circ\chi},
\end{gather}
\end{subequations}
where $\kappa_i$ is the sample number on the i-th piece, $\bar{\omega}_j$ the quadrature coefficients from the
trapezoidal rule\cite{WilliamHPress1996NumericalRI}, $\chi\in\mathbb{R}^{n_g}_{\geq0}$ is a vector of penalty weights. We define the points determined by $\{\mathbf{c}_i,T_i,{j}/{\kappa_i}\}$ as \textit{constraint points} $\mathring{\mathbf{p}}_{i,j} = p_i(({j}/{\kappa_i})T_i)$ with the $i$-th piece $p_i(t)$.

\paragraph{Dynamical Feasibility Penalty $J_d$}
According to the limit of agent maximum velocity $v_m$, acceleration $a_m$, jerk $j_m$, constraints of dynamic are denoted as
\begin{equation}
\label{eq:Jd_cost}
\mathcal{G}_v = \dot{p}(t)^2 - v_m^2,~\mathcal{G}_a = \ddot{p}(t)^2 - a_m^2,~\mathcal{G}_j = \dddot{p}(t)^2 - j_m^2.
\end{equation}
The corresponding gradients are
\begin{equation}
\label{eq:Jd_gradient}
\frac{\partial \mathcal{G}_x}{\partial \mathbf{c}_i}=2{\beta^{(n)}(t)} {p^{(n)}}(t)\tp, ~~\frac{\partial \mathcal{G}_x}{\partial t}=2{\beta^{(n+1)}}(t)\tp \mathbf{c}_i p^{(n)}(t),
\end{equation}
where $x=\{v,a,j\}$, $n=\{1,2,3\}$, and $t=jT_i/\kappa_i$.
By substituting Eq. \ref{eq:Jd_cost} \ref{eq:Jd_gradient} into Eq. \ref{eq:PieceTimeIntegralPenalty} we get the penalty $J_d$ and the gradient about $\mathbf{c}_i$ and $\mathbf{T}_i$.

\paragraph{Obstacle Avoidance Penalty $J_o$}
We adopt collision evaluation from Zhou et al\cite{XinZhou2020EGOPlannerAE}, which defines the distance from agent to obstacle as $d(p(t))$. To enforce the safety requirement, we formulate a collision penalty, which is triggered when the distance to obstacles is less than a safe clearance $\mathcal{C}_o$. The obstacle avoidance constraint and its gradient are as follows
\begin{gather}
\mathcal{G}_{o}(p(t)) = \mathcal{C}_o - d(p(t)),\\
\frac{\partial \mathcal{G}_{o_k}}{\partial c_{i}} =  -\beta(t) \mathbf{v}\tp , ~~ \frac{\partial \mathcal{G}_{o_k}}{\partial t} =  -\mathbf{v}\tp\dot{p}(t),
\end{gather}
where $\mathcal{C}_o \geq d(p(t)),0)$ and $t=jT_i/\kappa_i$.

\paragraph{Group Reciprocal Avoidance Penalty $J_w$}
\label{sec:swarm_avoid}

We jointly optimize all trajectories, which means that the trajectories of other agents change dynamically during the iterative optimization of one agent's trajectory.
The optimization problem will not converge if we consider only the gradients about $c$ and $T$ for the current agent's trajectory.
Therefore, in each iteration, we consider the influence of the current agent on all trajectory gradients.

In Fig. \ref{pic:swarm_avoidance}, we demonstrate the reciprocal avoidance process of the $u$-th agent's trajectory $p_u(t)$ and one of the other trajectories in the group ($k$-th agent's trajectory $p_k(t)$) at the time stamp $\tau$. $\tau$ is denoted as:

\begin{figure}[h]
	\centering
	\includegraphics[width=1.0\linewidth]{reciprocal}
	\captionsetup{font={small}}
	\caption{Group Reciprocal Avoidance. $c$ and $T$ indicate the coefficient and time duration of a trajectory segment. $\mathcal{C}_w$ is the safe clearance.}
	\label{pic:swarm_avoidance}
	\vspace{0.6cm}
\end{figure}

\begin{equation}
 \tau=T_{u1} + \cdots + jT_{ui}/\kappa_i = T_{k1} + \cdots + T_{k(n-1)} + t',
\end{equation}
where $t=jT_i/\kappa_i$ is the relative time of $u$-th agent. $t'$ is the relative time of $k$-th agent. $\tau$ locates in the $i$-th piece of $u$-th agent and the n-th piece of $k$-th agent. We define the constraint at the $j$-th constraint point on the $i$-th piece of $p_u(t)$ as
\begin{gather}
\mathcal{G}_w^{i,j}(p_u(t),\tau) = \left(\cdots, \mathcal{G}_{w_k}(p_u(t),\tau), \cdots\right)\tp\in\mathbb{R}^{K},\\
\mathcal{G}_{w_k}^{i,j}(p_u(t),\tau) = \begin{cases} \mathcal{C}_w^2 - d^2(p_u(t), p_k(t')) & k\neq u,\\ 0 & k=u, \end{cases} \\
d(p_u(t), p_k(t')) = \left\| \mathbf{E}^{1/2}(p_u(t) - p_k(t')) \right\|,
\end{gather}
where the matrix $\mathbf{E}$ is the downwash model of agent.

When $\mathcal{C}_w^2 \geq d^2(p_u(t), p_k(t'))$, the gradient to $\mathbf{c}_{ui}, \mathbf{c}_{kn}$ is
\begin{gather}
\label{equ:G_wk_to_cu}
\frac{\partial \mathcal{G}_{w_k}^{i,j}}{\partial \mathbf{c}_{ui}} = \begin{cases} -2\beta_{ui}(t)(p_u(t) - p_k(t'))\tp\mathbf{E} & k\neq u,\\ \mathbf{0} & k=u, \end{cases}\\
\label{equ:G_wk_to_ck}
\frac{\partial \mathcal{G}_{w_k}^{i,j}}{\partial \mathbf{c}_{kn}} = \begin{cases} 2\beta_{kn}(t')(p_u(t) - p_k(t'))\tp\mathbf{E} & k\neq u,\\ \mathbf{0} & k=u. \end{cases}
\end{gather}
The gradient to $T_{ul}$ for any $1\leq l\leq i$ can be computed as
\begin{align}
\frac{\partial J_{w}}{\partial T_{ul}}&=\sum_{k=1}^{K}\frac{\partial J_{w_k}}{\partial T_{ul}}=\sum_{k=1}^{K}\sum_{i=1}^{M}\sum_{j=0}^{\kappa_i}\frac{\partial J_{w_k}^{i,j}}{\partial T_{ul}},\\
\frac{\partial J_{w_k}^{i,j}}{\partial T_{ul}} &= \frac{J_{w_k}^{i,j}}{T_{ui}}+\frac{\partial J_{w_k}^{i,j}}{\partial \mathcal{G}_{w_k}^{i,j}} \frac{\partial \mathcal{G}_{w_k}^{i,j}}{\partial T_{ul}}, \\
\frac{\partial \mathcal{G}_{w_k}^{i,j}}{\partial T_{ul}}&=\frac{\partial \mathcal{G}_{w_k}^{i,j}}{\partial t}\frac{\partial t}{\partial T_{ul}}+\frac{\partial \mathcal{G}_{w_k}^{i,j}}{\partial t'}\frac{\partial t'}{\partial T_{ul}},\\
\frac{\partial \mathcal{G}_{w_k}^{i,j}}{\partial t} &= \begin{cases} 2\left(p_k(t') - p_u(t)\right)\tp\mathbf{E}\dot{p}_u(t) & k\neq u,\\ 0 & k=u, \end{cases} \\
\frac{\partial \mathcal{G}_{w_k}^{i,j}}{\partial t'} &=  \begin{cases} 2\left(p_u(t) - p_k(t')\right)\tp\mathbf{E}\dot{p}_k(t') & k\neq u,\\ 0 & k=u, \end{cases} \\
\frac{\partial t}{\partial T_{ul}} =&\begin{cases} \frac{j}{\kappa_i} & l=i,\\ 0 & l<i, \end{cases}~~\frac{\partial t'}{\partial T_{ul}} = \begin{cases} \frac{j}{\kappa_i} & l=i,\\ 1 & l<i. \end{cases}
\end{align}
The gradient to $T_{km}$ for any $1\leq m\leq n-1$ can be computed as
\begin{align}
\frac{\partial J_{w}}{\partial T_{km}} &= \sum_{i=1}^{M}\sum_{j=0}^{\kappa_i}\frac{\partial J_{w_k}^{i,j}}{\partial T_{km}},\\
\frac{\partial J_{w_k}^{i,j}}{\partial T_{km}} &= \frac{\partial J_{w_k}^{i,j}}{\partial \mathcal{G}_{w_k}^{i,j}} \frac{\partial \mathcal{G}_{w_k}^{i,j}}{\partial T_{km}},\\
\frac{\partial \mathcal{G}_{w_k}^{i,j}}{\partial T_{km}}&=\frac{\partial \mathcal{G}_{w_k}^{i,j}}{\partial t'}\frac{\partial t'}{\partial T_{km}},\\
\frac{\partial t}{\partial T_{km}} &= -1, ~~~1\leq m \leq n-1.
\end{align}

\paragraph{Uniform Distribution Penalty $J_u$}
Since finite constraint points constrain the collision avoidance, non-uniform distribution increases the possibility of skipping some thin obstacles. Therefore, we penalize the variance of the squared distances between pairs of adjacent constraint points. For more details, please refer to \cite{zhou2021decentralized}.

\section{Evaluation}

In this section, we conduct detailed evaluation tests on the proposed contributions. All programs run on an Intel Core i7-10700KF 5.1GHz CPU.

\subsection{Efficient Multi-Agent Pathfinding}
\label{sec:eva_ecbs}
\begin{figure}[t]
	\centering
	\includegraphics[width=1.0\linewidth]{ecbs}
	\captionsetup{font={small}}
	\caption{The paths searched by the front-end of RBP and the proposed method. The start points of the four agents are the vertices of a $4\times4m$ square. The goal point of each agent is the diagonal position of the start point. The average distance between obstacles is $0.5m$. The resolution of gridmap is $0.1m$. The suboptimal factor $\omega$ is $1.3$. }
	\label{pic:ecbs}
	\vspace{-0.6cm}
\end{figure}

In Fig. \ref{pic:ecbs}, we show that four agents search paths using RBP\cite{park2020efficient} and the proposed method under the same conditions. The initial paths searched by the proposed method are closer to the optimal trajectories, providing a good initial value for the nonlinear optimization problem. The flight time and distance of the proposed method are shorter. The numerical comparison is shown in TABLE \ref{tab:comparisons}.

In Fig. \ref{pic:EMAPF}, to demonstrate the performance of our method, we test the search time from three aspects: the number of agents, the density of obstacles, and the size of the search space. All data shows the average of $10$ runs. We consider the search time of more than $0.1s$ unacceptable for real-time scenarios.
As a result, we set $n_{max} = 8$ in the Group Planning Criteria. The maximum search space is $1276m^3$.
The average search time is $0.0381s$, which is adequate for real-time usages.

\begin{figure*}[h]
	\centering
	\includegraphics[width=1.0\linewidth]{EMAPF}
	\captionsetup{font={small}}
	\caption{The Performance of Efficient Multi-Agent Path Finding(EMAPF); $d$ indicates the average distance between obstacles. $n$ indicates the number of agents. $v$ indicates the space size. The factor $\omega$ is 1.3.}
	\label{pic:EMAPF}
	\vspace{-0.1cm}
\end{figure*}

\begin{comment}

\begin{table}[H]
	\centering
	\caption{Comparisons in an $6\times6\times5$ m space containing four agents with the same start and end positions. Factor $\omega=1.3$, gridmap resolution is 0.1m. The units of distance and time are meters and milliseconds.}
	\label{tab:ecbs search time}
	\begin{tabular}{|c|c|}
		\hline
		\textbf{\begin{tabular}[c]{@{}c@{}}average distance\\  between obstacles (m)\end{tabular}} & \textbf{search time (ms)} \\ \hline
		1.0   & 6.84  \\ \hline
		0.75  & 9.72  \\ \hline
		0.5   & 11.93 \\ \hline
		0.25  & 19.23 \\ \hline
		0.125 & 34.02 \\ \hline
	\end{tabular}
\end{table}

\end{comment}

\begin{table*}[]
	\setlength{\abovecaptionskip}{-0.7cm}
	\parbox{.185\textwidth}{\caption{Comparisons in a radius r = 15m circle empty space containing eight agents with radius of $0.25m$. \textbf{int($j^2$)} is time integral of squared jerk, indicating control effort. The units of time and distance are seconds and meters. }
	\label{tab:comparisons}}
    \renewcommand{\arraystretch}{1.45}
	\begin{tabular}{|c|c|c|c|c|c|c|c|c|}
		\hline
		\textbf{\begin{tabular}[c]{@{}c@{}}Offline\\ /Online\end{tabular}} &
		\textbf{Method} &
		\textbf{\begin{tabular}[c]{@{}c@{}}Decentralized\\  Solver Time\end{tabular}} &
		\textbf{\begin{tabular}[c]{@{}c@{}}Centralized\\  Solver Time\end{tabular}} &
		\textbf{\begin{tabular}[c]{@{}c@{}}Replan\\  Times\end{tabular}} &
		\textbf{\begin{tabular}[c]{@{}c@{}}Flight\\  Time\end{tabular}} &
		\textbf{\begin{tabular}[c]{@{}c@{}}Flight\\  Distance\end{tabular}} &
		\textbf{int($j^2$)} &
		\textbf{Safe?} \\ \hline
		\multirow{2}{*}{Offline} &
		\begin{tabular}[c]{@{}c@{}}RBP\\ (bacth size = 1)\end{tabular} &
		\textbackslash{} &
		2.07333 &
		\textbackslash{} &
		42.3539 &
		35.16 &
		0.029 &
		\multirow{6}{*}{Yes} \\ \cline{2-8}
		&
		\begin{tabular}[c]{@{}c@{}}RBP\\ (batch size = 4)\end{tabular} &
		\textbackslash{} &
		1.91592 &
		\textbackslash{} &
		42.3539 &
		35.66 &
		\textbf{0.028} &
		\\ \cline{1-8}
		\multirow{4}{*}{Online} &
		MADER &
		0.007187 &
		\textbackslash{} &
		19573 &
		28.0175 &
		30.28 &
		278.423 &
		\\ \cline{2-8}
		&
		EGO &
		0.000360 &
		\textbackslash{} &
		240 &
		28.4841 &
		31.10 &
		107.079 &
		\\ \cline{2-8}
		&
		DSTO &
		\textbf{0.000154} &
		\textbf{\textbackslash{}} &
		228 &
		21.4581 &
		30.42 &
		44.669 &
		\\ \cline{2-8}
		&
		Proposed &
		0.000353 &
		\textbf{0.02214} &
		\textbf{98} &
		\textbf{20.7576} &
		\textbf{30.06} &
		\textbf{37.407} &
		\\ \hline
	\end{tabular}
	\vspace{-0.5cm}
\end{table*}

\subsection{Comparisons}

In TABLE \ref{tab:comparisons}, we compare the proposed method with RBP\cite{park2020efficient}, Mader\cite{tordesillas2021mader}, EGO (EGO-Swarm)\cite{zhou2020ego}, and DSTO\cite{zhou2021decentralized}. All data is the average of 8 agents in 10 experiment runs. Maximum velocity and acceleration are set to $1.7m/s$ and $6.2m/s^2$.
We can see from the comparison that RBP has sub-optimal and more conservative trajectories with better smoothness and the longest flight time and distance. Compared with the offline method, the online methods have a replan mechanism and require less solution time. EGO and Mader generate more aggressive trajectories and appear to be more conservative solution spaces because the convex hull constrains the trajectories. EGO, DSTO, and especially Mader need high-frequency replan when the drones cluster.

In Fig. \ref{pic:sim_ben}, we create an extremely challenging environment, consisting of a wall with a narrow gate. There are three drones in each side of the wall with goal points diagonal positions on the other side. We can see that all drones pass through this narrow gate only with the proposed method.

From the comparison, the proposed method shows top-level performance with the shortest flight time, distance, and the fewest replan times. This is attributed to the group planning with the coordination ability.
All simulations and experiments show that the nonlinear optimization problem is always solved in the proposed method, indicating that the safety constraints can be met. However, we still cannot theoretically guarantee that the solution always exists. To ensure safety, we further perform post-check on the optimized trajectories, and only safe trajectories are executed.
If a safety constraint is violated, the planner increases the constraint's weight and solves the problem again. If a safety issue persists, the drone enters an emergency stop mode.

\subsection{The Large-scale Simulation}

In a $50\times50m$ map, we simulate future air traffic scenarios. The initial positions of 50 drones are generated at random, and each drone must pass through three randomly generated goal positions. Fig. \ref{pic:large_scale} depicts a screenshot of the mission at a certain moment. When multiple drones meet the group planning criteria, group planning is triggered (the drones turn red.). Group planning is triggered $35$ times during the whole mission. The robustness and flexibility of the proposed method in large-scale aerial robot teams are verified.

\begin{figure}[h]
	\centering
	\includegraphics[width=0.95\linewidth]{large_scale_flat}
	\captionsetup{font={small}}
	\caption{Large-scale air traffic simulation; Colored curves indicate the positions that the drones have passed. Maximum velocity and acceleration are set to $1.7m/s$ and $6.2m/s^2$. The average distance between obstacles is $0.5m$.}
	\label{pic:large_scale}
	\vspace{-0.6cm}
\end{figure}

\subsection{Discussion On Map Sharing}
\begin{figure}[h]
	\centering
	\includegraphics[width=0.6\linewidth]{map_share_1}
	\captionsetup{font={small}}
	\caption{The impact of shared maps on trajectory; The red curve indicates the trajectory with shared maps. The green curve indicates the trajectory without shared maps.}
	\label{pic:sharemap}
	\vspace{0.25cm}
\end{figure}
In group planning, each drone's local map is compressed and shared within the group. Therefore, the proposed method can produce safer trajectories, as shown in Fig. \ref{pic:sharemap}.

\section{REAL-WORLD EXPERIMENTS}

\begin{figure*}[ht]

	\centering

	\includegraphics[width=1.0\linewidth]{outdoor}

	\captionsetup{font={small}}

	\caption{Outdoor experiment}

	\label{pic:outdoor}

	\vspace{-0.46cm}

\end{figure*}

\subsection{Indoor}
In the indoor experiments, we place eight drones on two concentric circles with diameters of $10m$ and $4m$ respectively (four drones on each circle). We set the speed limit to $1.0 m/s$. The mission of each drone is to go to the diagonal position of the other circle. In Fig. \ref{pic:indoor}, we set up two environmental experiments: (1) sparse environment (left); (2) dense environment (right);
In the mission, the entire system completes the mode switch in a manner of ``Single-agent Planning to Group Planning to Single-agent Planning".

\subsection{Outdoor}

In the outdoor experiment, the four drones cross and exchange positions every $8m$ in the longitudinal direction in a dense environment. The entire mission has $5$ cross-flights, and each cross-flight performs the mode switch in a manner of ``Single-agent Planning to Group Planning to Single-agent Planning". In Fig. \ref{pic:outdoor}, the process of one cross-flight is shown. When four drones disperse, each drone performs single-agent planning. When four drones cluster, group planning is triggered. Please watch the video for more information.

\section{CONCLUSIONS AND FUTURE WORK}

In this work, we propose an enhanced decentralized autonomous aerial robot team system with group planning. The system tackles the conflict between planning efficiency and trajectory quality and balances the coordination of individuals and groups. Extensive evaluations demonstrate top-level planning quality and the ability to deploy in a large-scale aerial robot team. Real-world experiments demonstrate the robustness and flexibility of the system. In the future, we will further improve the efficiency and scalability of the multi-agent pathfinding method while considering the kino-dynamic constraints. We will also explore applications in the field of transportation.

\addtolength{\textheight}{-12cm}

\bibliographystyle{ieeetr}

redpajama_set_name: RedPajamaArXiv


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Today we celebrate the feast of Pentecost sometimes referred to as the birthday of the Church. We know the story. The Apostles hide behind locked doors on Easter evening. They are filled with fear wondering will they be arrested and put to death as friends of Jesus. Besides they do not know what to do without Jesus their leader. Suddenly the risen Jesus appears inside the locked room and breathes new life into the Apostles "Receive the Holy Spirit." From that moment on they are a changed people, filled with courage and strength, eager to go forth to promote their mission. They know what to do to bring the peace of Christ to all people.
Come Spirit, source of our Peace.
All boys and girls from 7th grade and above are eligible to join the ministry of Altar Server, if you are attending Catholic School or are enrolled in the Religious Education program. This is a very important ministry; a wonderful way to participate as our faith community comes together to celebrate Eucharist.
If you are interested please call Gene or Anna May. Training will take place shortly.
As a Parish Community, we pray...that young people who are graduating may be filled with the Holy Spirit and proclaim the Good News of Jesus' love in word and in action.
We pray for the ill: Sharon Aiello, Marilyn Arancibia, Robert Bacci, Genaro Badiable, Lito Badiable, Marcia Bourne, Maricris Candelaria, Arthur Candia, Carmen Capella, Josie Clarke, Nan Connolly, Cindy Corona, Ana Cosgaya, Walton & June Dickhoff, William & Sandra Dill, Carl Edwards, Joyce Flax, Adela Florez, Jesse Grube, Denise Hawald, Dominique Hauscarriague,Jr, Viko Ivancich, Joanne Johnson, Koret Koelman, Muriel Krause, Sisilia Langi, Shirley Latham, Josephine Lavoie, Austin Lehman, Marky, Michael Martinez, Daniel McHale, Rosemary McHale, Terry McLeod, Josie Mercado, Mary Novickas, Thomas O'Brien, David Papageorgiou, Lara Pinten, Jason Pimentel, James Piazza, Mary Shick, Pauline Speranza, Justo Tan, Mafi Tukumoatu, Kristi Varni, Don Vickery, Diana Walter, Jennifer Westbrook & Frank Wright.
On Saturday, June 5th, following the 8:30 am Mass and continuing until 10 a.m. we will celebrate Adoration of the Blessed Sacrament. Jesus gave us everything He had: His love, His Body, His Blood, His Life. He continues to do this in His gift to us of the Eucharist. He has said to us: "I will be with you always, to the end of the age." Come sit in silence and let Jesus speak to your heart.
Today is the Feast of Pentecost, the birthday of the Church. Remember those old Westerns when one (usually bad) guy would say to another: "This town isn't big enough for both of us." As a small child, I used to think that Jesus had to leave because earth wasn't big enough for Jesus and the Spirit to be here at the same time! As adults hopefully, we understand that Jesus, who was limited to being in one place as a human being, could now through the Spirit be present to all of us at the same time. The Acts reading which we hear today and which is used at many confirmations, struggles to convey a most amazing experience: the noise of a strong driving wind, tongues as of fire resting on each one. Being filled with the Holy Spirit, they had to speak; they couldn't hold it in. Those who heard them, who came from the entire known world at that time and spoke languages they'd never heard of, understood them! The confusion of the Tower of Babel is undone and people are made one again.
The gospel is also wonderful. John's community has Jesus promising that if we love him and keep his word, he and the Father will come to us and make their dwelling with us. The Jerusalem Bible translation says they will make their home with us. Imagine living with Jesus and the Father within you! (The Spirit who will be sent by the Father will also dwell with us.) What aspect of our "home" needs a bit of tidying up for such houseguests? What bad habit needs to be swept away? What window of narrowness or prejudice needs to be opened? What closet filled with depression or ignored bitterness needs to be cleared out? And the most amazing thing is that this Spirit of God will actually do within us whatever needs to be done that we might become a more fitting dwelling place for the Trinity. Just ask for the grace (strength, humility, trust) to open up to the gentle power of God. May the Spirit renew and restore us all!
Have you ever thought about becoming a bit more involved at St. Robert's? If you're a regular at the 4:30 pm or 7:30 am Mass, why not serve your fellow parishioners as a lector or Eucharistic minister? The training is very simple and will be arranged at your convenience. Please call the rectory at 650-589-2800 and leave a message for Sr. Sheral or Gene May.
Thank you to the Men's Club and to the representatives of the various parish groups who were present for the 4:30 pm Mass last Saturday. Some groups are primarily social; others visit the sick or respond to the needs of poor families in our area. If you would like to become a part of one of these groups, please call the rectory and we'll gladly provide the phone number of the group leader.
on receiving the Pius X award in Recognition of 5 years of Catechetical Ministry (teaching in CCD) here at St. Robert's.
We are grateful for their generous committment to Religious Education.
Thank you for your generous donaton of $2,973.43 to Catholic Charities.
at the 9 a.m. Mass.
Spiritual Reading is available at Saint Robert's every other Sunday morning after the Masses in the vestibule of the church. Please, take a few minutes and check out an interesting book to read.
Recently we had our first social night for parents and their young children. About twelve families attended with their preschool and infant children. . Everyone had a fantastic time.


Woke up feeling good after the rest day. My recovery has been getting better over the last 2 weeks. I'm not sure what to attribute it to, but I feel like I'm putting in some solid work that would have crushed me in the past, but I'm starting to adapt and recover better.


The Albertavia Mummers Collective began their magical journey in Fall 2008 and made their official debut at the 2nd Deep Freeze Winter Byzantine Festival. But what is a Mummers play? To the Albertavia Mummers Collective it is team of artists that bring together mythical lore, history, and the essence of communities in a 20-minute play for all to enjoy. Since the premier of their first play, "Knighty Knight", they have grown the tale into an absurdly wonderful trilogy.


One of the biggest issues encountered each year by property owners across Melbourne is the pest invasion. Having your home or office invaded by pests can cause a lot of distress, unnecessary headaches, and routine clean-ups. With pest control, it is no good just "managing" the situation; it often requires professional attention for pest control experts.
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Heavy arms fire was heard during much of Tuesday night in the Ain Zara district on the southeastern outskirts of Tripoli as military strongman Khalifa Haftar's forces pressed an assault aimed at taking the capital from the UN-backed Government of National Accord (GNA).
"The clashes have intensified. We're afraid to leave the house," a resident told AFP by telephone from the area, where roads were reported to have been blocked, hindering people's efforts to flee.
The violence has already displaced thousands and left several dozen people dead.
The Libyan Red Crescent said it had evacuated civilians on Wednesday morning but had so far only had access to combat zones controlled by the GNA.
Thirty families were evacuated from Ain Zara and Wadi Rabi, a district further south, to reception centres or to homes of relatives and friends, the Red Crescent said on its Facebook page.
The UN has warned that nearly half a million children in Tripoli were "at immediate risk".
Haftar's self-styled Libyan National Army (LNA), which controls swathes of the country's east, said it had seized a barracks in the Aziziya area around 50 kilometres (31 miles) south of Tripoli after "ferocious clashes".
The internationally recognised government carried out several air raids against LNA positions south of Tripoli, and also hit supply lines in central Libya, GNA spokesman Colonel Mohamed Gnounou said Tuesday.
Haftar has defied international calls, including from the Security Council and the United States, to halt the surprise offensive launched on Thursday.
The UN's high commissioner for refugees, Filippo Grandi, called for the warring parties to "spare civilians, including refugees and migrants trapped in the country".
The UN children's agency (UNICEF) urged all parties "to refrain from committing grave violations" against children, including the recruitment of child soldiers.
"Nearly half a million children in Tripoli and tens of thousands more in the western areas are at a direct risk due to the intensification of fighting," it said.
The GNA's health ministry on Monday put the death toll in the fighting at 35. Haftar's forces have said 14 of their fighters have died.
Led by Fayez al-Sarraj, the GNA's authority is not recognised by a parallel administration in the east of the country, which is allied with Haftar.
LNA spokesman Ahmad al-Mesmari accused the unity government of "allying itself with Islamist militias" from the city of Misrata 200 kilometres (120 miles) east of the capital.
Rival leaders agreed last year to hold elections before December 10, 2018 under a French plan, but that vote never materialised.
UN envoy Ghassan Salame, announcing its postponement, said: "We cannot ask people to take part in the conference during gunfire and air strikes."
He expressed hope the meeting would take place "as soon as possible".
Haftar, whose key allies are the United Arab Emirates, Egypt, Saudi Arabia and Russia, is a former Kadhafi military chief who has emerged as a major player in Libya's political struggle.


It can be understandably difficult to leave your pet in someone else's care, but sometimes it's necessary. Whether you're traveling or hosting an allergy-prone guest at home, boarding your pet in a facility that you trust can be an excellent opportunity. The good news is that New Haven Pet Hospital offers comfortable and safe pet boarding, so you don't have to worry. The solution is that we are your best friend's home away from home.


Roohome.com – Do you want to make your living room looks fascinating with fashionable decor inside? There are variety of luxury living room decorating ideas which can make your living room become more attractive. The designer here applying with enticing and fabulous concept design in it. It will make your room bring out an outstanding impression. To make your living looks awesome it is a must. Why? Because this is the important part in a house that you can use to gathering for your beloved family. So, better you follow these kind of luxury living room design ideas which apply with chic and attractive color ideas inside. Do you want to see how the designs look like?
Here, the designer offers you luxury living room design ideas which combine with a modern and remarkable design in it. When you see the design below the designer has arranged it into a luxurious design that looks so awesome and perfect. This luxury living room decor has the beautifulness which can present in this room design which applied with colorful design ideas that can bring out a fashionable look in it. It also looks so trendy because the designer also adds some ornaments which very compatible with this awesome living room decor with a beautiful color on it. A compatible color in this colorful living room design will make it looks awesome and remarkable.
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Microsoft is bringing early access to consoles for the first time with Xbox preview.
Early access is a system where players can play games that are partway through development. Made popular on the PC, this is a first for consoles. Every game made available through Xbox preview will have a free trial so players can make informed choices.
Elite Dangerous and The Long Dark will be available immediately with DayZ promised for the future along with creator Dean Hall's new title, ION.


Chanonry Park is in Fortrose, one of the most charming and historic towns on the Black Isle. Fortrose lies between Avoch and Rosemarkie, and boasts an attractive harbour and fine, secluded beaches. Along the shoreline, Chanonry Point is both a distinctive landmark and a famous location for dolphin-watching.
The idyllic location offers a real feel of rural seclusion – which is only a short drive from Inverness, with its lively mix of cultural attractions and commercial activities. Locally, you'll discover a range of excellent amenities with a choice of restaurants. Good primary schools and the renowned Fortrose Academy ensure sound education opportunities for the whole family. Leisure hours can be spent happily between local golf and sailing, or simply enjoying the scenic variety and wildlife of the Black Isle.
Rail: Inverness Railway Station (13 miles). Services run to Perth, Edinburgh, Glasgow, London, Aberdeen, Thurso, Wick and Kyle of Lochalsh. Inverness is also connected to London by the Caledonian Sleeper.
Bus: Stagecoach runs regular bus services between Fortrose and Inverness.
Primary: Avoch Primary School. Includes nursery, after school care, and after school and lunchtime activities.
Fortrose Playgroup is based at the Black Isle Leisure Centre, Deans Road, Fortrose.
Fortrose Surgery, Station Road, Fortrose.
There are several cafes, bistros, restaurants and public bars and lounges in Fortrose, Avoch and Rosemarkie.
Inverness is the nearest city, where a wide range of bars, nightclubs, restaurants and coffee shops are available.
There are also cafes, bars and local hotels available in Dingwall.
Black Isle Leisure Centre, Deans Road, Fortrose. The centre has modern facilities including a multi-purpose sports hall and fitness suite. The sports hall accommodates a variety of indoor sports including football, badminton, gymnastics, trampolining, volleyball and more.
The centre's fitness is one of the up to date facilities in the Highland area. The individual weight stations have been designed to cover every major muscle group for that all-over body tone, as well as eight cardio-vascular units for exercising the heart and lungs. Fortrose Leisure Centre takes part in the discounted High Life Card Scheme and runs a variety of group fitness classes.
Dingwall also has its own leisure centre including swimming pool and gym.
Golfers can play at the highly acclaimed Fortrose and Rosemarkie Golf Club or at Muir of Ord Golf Club, one of the oldest clubs in the north of Scotland. There are also many opportunities for walking and hiking in the area, including the popular Fairy Glen walk.
Sports clubs in the area include Beauly Angling Club, Cromarty Tennis and Sports Club and Cromarty Boat Club.
The nearest main theatre is Eden Court Theatre, Bishop's Road, Inverness. The nearest cinema is Vue Cinema at Inverness Retail Park.
Chanonry Point between Fortrose and Rosemarkie is one of the best spots in the UK to view Bottlenose Dolphins from land. The dolphins are often visible particularly on an incoming tide when they play and fish in the strong currents. Other wildlife, including porpoises and grey seals, can also regularly be spotted. Dolphin watching boat trips also run from Cromarty and Avoch.
In the heart of Fortrose is Cathedral Square, home to the red stone remains of Fortrose Cathedral, built in the 13th century. A free attraction, it is available all year round to view.
As Fortrose and the surrounding area are rich in history, the area also boasts several museums including Hugh Miller's Cottage, the 17th birthplace of Hugh Miller, stonemason, geologist, author, journalist and editor. Groam House Museum is a Pictish centre in nearby Rosemarkie and Cromarty Courthouse is based at Church Street, Cromarty.
Other attractions in the Black Isle area include the Glen Ord Distillery in Muir of Ord and the Black Isle Brewery in Munlochy, both open for visitors to tour.
There are also child friendly facilities including Robertsons Children's Farm and Larder in Beauly, and the Highland Museum of Childhood at the Old Station building in Strathpeffer.
Popular attractions are also available within a relatively short drive at Loch Ness, in Inverness and Aviemore.
Fortrose has a Co-operative Store, Post Office and shop, newsagents and pharmacy. There is also an antiques shop.
The city of Inverness is the nearest shopping centre, offering a range of outlets from national retailers to smaller independently run stores.
Dingwall offers a number of shops as well as a large Tesco supermarket and LIDL store.


text:
Aristotle on Actions from Lack of Control
Jozef Müller
Philosophers' Imprint 15 (2015)
The paper defends three claims about Aristotle's theory of uncontrolled actions (akrasia) in NE 7.3. First, I argue that the first part of NE 7.3 contains the description of the overall state of mind of the agent while she acts without control. Aristotle's solution to the problem of uncontrolled action lies in the analogy between the uncontrolled agent and people who are drunk, mad, or asleep. This analogy is interpreted as meaning that the uncontrolled agent, while acting without control, is still in possession of her knowledge but she is unable to use it as knowledge due to the temporary disablement of her reason by appetite. Due to this disablement, the uncontrolled agent is temporarily unable to be motivated to act by her knowledge and acts merely on her appetite. Second, I argue that the second part of NE 7.3 provides an analysis of the particular mental state from which the uncontrolled action issues. Its central passage is a description of the uncontrolled agent's state of mind before the uncontrolled action and not, as it has been traditionally understood, a description of her state of mind during the uncontrolled action. Third, I argue that, on Aristotle's view, the transition from the state before the uncontrolled action to the state in which the agent already acts without control does not involve any psychological state that would constitute the agent's choice to abandon her decision and give in to her desires but proceeds on a purely physiological level
Keywords Aristotle Akrasia Action Desire Decision Reason
Aristotle: Character in Ancient Greek and Roman Philosophy
Aristotle: Free Will and Agency in Ancient Greek and Roman Philosophy
Aristotle: Pleasure in Ancient Greek and Roman Philosophy
Aristotle: Voluntary and Involuntary in Ancient Greek and Roman Philosophy
Aristotle: Weakness of Will in Ancient Greek and Roman Philosophy
Philosophy of Action, Misc in Philosophy of Action
Weakness of Will in Philosophy of Action
hdl.handle.net (no proxy)
The Problem of the Essential Indexical.John Perry - 1979 - Noûs 13 (1):3-21.
A Plea for Excuses.John Austin - 1957 - Proceedings of the Aristotelian Society 57:1--30.
Intention and Weakness of Will.Richard Holton - 1999 - Journal of Philosophy 96 (5):241.
Aristotle on the Apparent Good: Perception, Phantasia, Thought, and Desire.Jessica Moss - 2012 - Oxford University Press.
The Brute Within: Appetitive Desire in Plato and Aristotle.Hendrik Lorenz - 2006 - Oxford University Press.
Aristotle on the Structure of Akratic Action.Elena Giovanna Cagnoli Fiecconi - 2018 - Phronesis 63 (3):229-256.
What Aristotelian Decisions Cannot Be.Jozef Müller - 2016 - Ancient Philosophy 36 (1):173-195.
Self-Control and Akrasia.Christine Tappolet - forthcoming - In Meghan Griffith, Kevin Timpe & Neil Levy (eds.), Routledge Companion to Free Will. Routledge.
Aristotle on Prohairesis.Liu Wei - 2016 - Labyrinth 18 (2):50-74.
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redpajama_set_name: RedPajamaCommonCrawl


text:
Audrey Taylor Gonzalez author of South of Everything
Women Worldwide episode Audrey Taylor Gonzalez, South of everything 0
The host of Women Worldwide, Deirdre Breakenridge, welcomes her guest to the show, Audrey Taylor Gonzalez. Audrey is an accomplished author, and, at 76 years of age, is launching her new book, South of Everything, a powerful parable about the changing South after World War II.
On the show, Audrey discusses her experiences; from her travels and volunteerism to her poetry and writing, and the inspiration behind her life's work. She shares her thoughts on what it is like to work with prison inmates, as an ordained minister, and how she was selected by the governor of Tennessee as a Commissioner on TCCY (Tennessee Commission on Children and Youth). Audrey imparts advice on living your life to the fullest and you can overcome the disappointments you may face..
A little more about Audrey Taylor Gonzalez…Audrey has been a journalist, TV host, art gallery owner, racehorse breeder, mountain climber, world traveler, breast cancer survivor, and the first woman to be ordained to holy orders in the Southern Cone of South America in Uruguay.
You can learn more about Audrey on her website and connect with Audrey on Instagramand Facebook.
Melissa Izbicki and Annie Truex Discuss Women in Film Gustaaf Vocking and Nathalie Soeteman discuss leadership and success
Making Transparency Your Brand
Building an Unbreakable Bond in Your Business
The Journey to a Best Seller with Paul Brodie


Maple Leaf Square - 1B/1 Bath Unit With Large Balcony And 9 Ceilings. Upgraded Throughout. Direct Access To Acc Union Station And The Underground Path. Boutique Hotel Fine Dining Restaurant Lcbo And Sports Bar Right Where You Live! Longos Supermarket In The Building For Your Daily Shopping Needs.


text:
Bones of freed slaves 'haunt' St. Helena island
Oketch kicked out poverty with wooden flasks...
A ray of hope for Zimbabwe's ruined economy?...
Added 23rd November 2017 06:47 PM
As bulldozers tore through the earth, they stumbled on human bones -- the remains of 325 people, most of them in mass graves, mainly children with an average age of 12
Rupert's Valley resident Deborah Fowler looks on as she recalls her parents' stories on finding bones while walking through the valley on October 19, at Rupert's valley in the British Overseas Territory of Saint Helena. AFP photo
The only pointer of what lies inside the stone storehouse within the grounds of the prison is a printed note pasted to an old grey door.
"This is to mark the temporary resting place of 325 liberated African slaves brought to St. Helena against their will. They now wait in this room for their final resting place," it reads.
Candles and a bouquet of wilting white arum lilies sit in front of the wooden door on the remote British island of St. Helena in the middle of the South Atlantic Ocean.
Nine years ago, the skeletons of the former slaves were discovered during the construction of the island's first airport.
Since then the remains have been kept in cardboard boxes in the prison storehouse.
Every Sunday, Annina Van Neel Hayes, 30, an environmentalist born in Namibia, pays homage to the forgotten dead by laying flowers in front of the padlocked door.
It was she and her friends who put up the epitaph.
"Still 10 years later, nothing is being done," she said, suggesting that proper reburial of the former slaves' remains "has never been a priority of St. Helena government".
After abolishing its slave trade in 1807, Britain intercepted mainly Portuguese slave ships sailing near St. Helena, which lay on the notorious slave-trading route from Africa to America and the Caribbean.
The island's leather-bound archives reveal horrendous details of events nearly 180 years ago.
One ship, intercepted on December 2, 1840, carried 245 slaves. Another, seized on January 17, 1841, was from Angola heading to Brazil with 308 slaves "in good health" and 108 "sick" slaves.
Between 1840 and 1865, around 25,000 slaves were freed and released on St. Helena, according to historians.
Many died from dysentery and smallpox.
An estimated 8,000 are buried in Rupert's Valley in the north of the island, said archaeologist Andrew Pearson.
"Because you have the mid-Atlantic stopping point, it is unique and hugely important," he said. "Nowhere else could have this -- people straight off slave ships."
It is in Rupert's Valley that a road was built several years ago to bring in imported construction equipment for the island's first airport.
As bulldozers tore through the earth, they stumbled on human bones -- the remains of 325 people, most of them in mass graves, mainly children with an average age of 12.
"Rupert is littered with remains from that period," said airport manager Janet Lawrence. There were only two known graveyards and the rest were unmarked.
Previously other bones had been unearthed during the construction of a power station in the 1980s.
"My father told me stories about chains and slaves," recalls Alonzo Henry, 36.
"We used to get a lot of power cuts and people used to say it was because the power station had been built on the graves".
Island's dark past
His aunt Deborah Fowler, 53, remembers finding bones when they were looking for food for goats.
"As kids, we thought it was animal bones," she said.
From her window, she can see a low stone building that was once the slaves' hospital, and is now used for fish processing.
The remains have forced St. Helena's residents to confront the island's dark past and to wrestle with a dilemma of how to balance development with giving due respect to the burial sites.
"When we were growing up, we were told about Napoleon (who died in exile on the island), the Boers (war prisoners), but there was barely any information about the slaves," said jeweller Giselle Richards, 32.
In contrast to the slaves' fate, Napoleon was honoured with a tomb -- though his body was taken back to France -- while the Boer prisoners lie in neat plots in a hillside graveyard.
The decision to temporarily hold the remains of the liberated slaves in a storeroom at Jamestown jail has disconcerted some.
Rediscovering our past
Jeremy Harris, director of the local National Trust conservation group, admits he forced open a lock and broke in after being repeatedly denied permission to inspect the building.
He is now supporting a campaign for the bones to be moved and ceremonially reinterred.
"The symbolic fact that these people are kept in an extension of the prison is inappropriate," he said.
Island officials argue that the thick walls of the old prison keep the bones at a constant temperature.
And last month a group of local experts was commissioned to make recommendations within six months on the reburial of the remains.
For Alonzo Henry, who believes he may be a descendant of the slaves, the discovery of the bodies during the airport's construction was deeply ironic.
"With the airport, we are thinking about our future and yet we are rediscovering our past," he said.
St. Helena,
Bones of freed slaves
16 dead as army clashes with rebels in DR Congo
FBI told Dutch about terror brothers before Brussels blasts...
AFCON: Morocco qualify, Egypt close, Nigeria out
Over 5 million seek to vote in controversial Burundi poll: election chief
Lynch mob drags alleged child-killers from India police station


Professor Jane den Hollander AO has been Vice-Chancellor of Deakin University Australia since July 2010. At Deakin, Professor den Hollander introduced LIVE the future, an aspiration for Deakin to drive the digital frontier in higher education, harnessing the power, opportunity and reach of new and emerging technologies in all that it does.
Professor den Hollander is a Director of UniSuper Limited and Trustee, a member of the Premier's Jobs and Investment Panel and a member of the VERNet Board (Victorian Education and Research Network) Prior to taking up her appointment as Vice-Chancellor of Deakin University, Professor den Hollander was Deputy Vice-Chancellor (Academic) at Curtin University in Western Australia. Professor den Hollander received an Order of Australia for her distinguished service to tertiary education in the 2017 Australia Day Honours awards.


text:
New Dada
The term neo-dada applied to the work of artists working in America in the 1950s and 1960s which was reminiscent of the art of the early twentieth century dada movement but having more interest in the object than Dada claimed to have.
Robert Rauschenberg, Monogram, 1955
Image source: https://www.flickr.com/photos/rocor/38414055976/in/photostream/ Author: rocor
Neo-Dada was a movement with audio, visual and literary manifestations that had similarities in method or intent with earlier Dada artwork. It sought to close the gap between art and daily life, and was a combination of playfulness, iconoclasm, and appropriation. There was also an international dimension to the movement, particularly in Japan and in Europe, serving as the foundation of Fluxus, Pop Art and Nouveau réalisme.
What's the Neo Dada?
Jim Dine, Drag – Johnson and Mao, 1967
Image source: https://www.wikiart.org/en/jim-dine/drag-johnson-and-mao-1967 Author:Jim Dine
The term Neo-Dada was applied to the works of artists such as Jasper Johns, Robert Rauschenberg, and Allan Kaprow who initiated a radical shift in the focus of modern art during the 1950s. Neo-Dada artists are known for their usage of mass media and found objects, as well as a penchant for performance. These artists rebelled against the emotionally charged paintings of the Abstract Expressionists that dominated the art world in the 1950s. By introducing mundane subject and emphasizing performance, the Neo-Dada artists ushered in the radical changes modern art underwent during the 1960s and paved the way for Pop art, Minimalism, and Conceptualism.
How it originated
While many individual works and moments contributed to the definition of the Neo-Dada aesthetic, Cage's "The Event," or Theatre Piece No. 1 (1952), performed at Black Mountain College, summarized the movement's interests in the emphasis on chance, individuality, interaction with the audience, and multiple media all combined into a singular work. After moving to New York City, Rauschenberg and Johns were neighbors and often discussed their ideas about artistic practice in their studios, further refining the aesthetic, particularly the idea that the artist's intent should not be legible or present in the final work.
John Cage in 1988
Image source: https://en.wikipedia.org/wiki/John_Cage
The label Neo-Dada was first used in 1957 by art critic Robert Rosenblum and then the following year by Thomas B. Hess, director of ARTnews magazine. The critic and art historian Barbara Rose defined Neo-Dada as a broader movement in 1962, by which time the East Coast branch of the movement was largely considered to be over and Pop art began to captivate New York.
Consumer culture
Nam June Paik, TV Cello, 1971. Three cathode-ray tubes (15-inch, 9-inch and 20-inch), acrylic boxes, three television casings, electronics, wiring, wood base, fan and stool
Image source: https://www.flickr.com/photos/11561957@N06/50026976476/ Author:B
Unlike the militant declarations of Dada artists, Neo-Dada artists provoked through covert strategies more suitable to the cold war climate. Neo-Dada simultaneously mocked and celebrated consumer culture, united opposing conventions of abstraction and realism, and disregarded boundaries between media through experimentation with assemblage, performance, and other hybrid fusions.
From the viewer perspective
Takashi Murakami, 727, 2018
Image source: https://www.flickr.com/photos/129231073@N06/42558220430 Author:Fred Romero
Neo-Dada artists adhered to Marcel Duchamp's premise that works of art are intermediaries in a process that the artist begins and the viewer completes. In the historical context, Neo-Dada revived this long dormant theoretical framework and provided the foundation for many of the contemporary art movements that followed.
Encouraging the shift toward the viewer as part of the artwork, many Neo-Dada artists adhered to a notion that the viewer's interpretation of a work – not the artist's intent – determined its meaning. This was emphasized through the use of chance, found objects, and mass media, which helped eliminate the artist's predetermined significance and instead placed the focus on the viewer's reading of the piece.
Info sources: https://www.theartstory.org/movement/neo-dada/
https://www.tate.org.uk/art/art-terms/n/neo-dada
https://en.wikipedia.org/wiki/Neo-Dada
Author JBDAdminPosted on April 1, 2020 September 29, 2021 Categories Art & Design, UncategorizedTags 1900, 1950, 1960, 20th century, america, at, ballet, collage, consumism, dada, duchamp, europe, exhibition, japan, john cage, minimalism, music, neo dada, painting, pop art, pop culture
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text:
Academy of the Fine Arts, 1029 Chestnut Street
Historical Images of Philadelphia Looney Old Philadelphia in Early Photographs
Item No: pdcl00132
Title: Academy of the Fine Arts, 1029 Chestnut Street
Additional Title: Pennsylvania Academy of the Fine Arts
Historic Street Address: Washington Square West
Media Type: Albumen Prints
Source: Print and Picture Collection
Notes: "When the Academy was first built in 1806, it was surrounded by a garden and the site had a frontage of one hundred feet on Chestnut Street. By 1869, however, most of this property had been sold and business establishments had almost hidden the Academy from view. The photograph was made just before the building was sold to Robert Fox, who opened Fox's New American Theatre (later the Chestnut Street Opera House) on this site in 1870."--OPEP, p. 137.
Notes: The Academy set back in a court-yard. Entrance with gate and sign above: "Academy of the Fine Arts," with walkway between two retail stores. Group of men with top hats posing on the steps of the Academy. Two street lamps on sidewalk; two horses pulling a carriage. Both stores have doors open with people looking out; store on left has man looking out window on top floor. Store on left: "Ladies hair dresser..." on one window and on other: "Selling out below cost..." To the left of this: "[?]rden"; below and attached to the awning: "...Jewelry"; and free-standing letters at top of building: "[?]arden." Store to the right of Academy entrance: "Children's..." and "Boots & shoes." Printed on building above the sidewalk: "1023, J. Parsons & Co. men's boy's boots shoes [?]." on both sides of the door. To the right of this store are numerous signs: "Hitchcock's half dime music," "Woods [?]," "Turner Hamilton book binding, stationery, and periodicals, 106 So. 10th St.," and "Hitchcock's Dime Music." The next store: "Wines [...]."
Bibliography: Reprinted in: Old Philadelphia in early photographs, 1839-1914/edited by Robert F. Looney. New York: Dover Publications, c1976.
Creation Year: 1869
Geocode Latitude: Geocode Latitude:39.9501
Geocode Longitude:-75.1581
Stationery trade
Chestnut Street
J. Parsons & Co.
Hitchcock's Dime Music
Turner Hamilton Book Binding, Stationery, and Periodicals
Newspaper vendors
Pan and Zoom
Go to Hip Map
(1869). Academy of the Fine Arts, 1029 Chestnut Street. [Albumen Prints]. Retrieved from https://libwww.freelibrary.org/digital/item/2657
Academy of the Fine Arts, 1029 Chestnut Street. 1869. Albumen Prints. Free Library of Philadelphia: Philadelphia, PA. https://libwww.freelibrary.org/digital/item/2657. (accessed Jan 21, 2021)


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text:
Senate approves, Obama will sign, Blumenthal's veterans bill
Washington – A bill designed to prevent suicide by veterans is expected to be signed into law by President Obama after its approval Tuesday by the U.S. Senate, 99-0. The measure was sponsored by Sens. Richard Blumenthal, D-Conn., and John McCain, R-Ariz.
The Clay Hunt Suicide Prevention for American Veterans legislation will provide more mental health resources to the Department of Veterans Affairs and demand more accountability from the agency. The VA's reputation was tarnished by last year's revelations about the poor delivery of health care at some of its facilities.
"This breakthrough bipartisan step will help countless veterans overcome invisible wounds of war that lead to 22 tragic suicides every day," Blumenthal said. "We owe these wounded warriors more effective mental health care, so they can win the war against inner demons that come home from service."
The bill was approved unanimously by voice vote in the House last month. It now goes to the White House, where President Obama is expected to sign it.
The legislation would require an annual, third-party evaluation of mental health care and suicide prevention programs at the VA and establish a pilot program that would repay up to $30,000 per year of the college loans of psychiatrists who commit to at least two years of service in the VA.
The bill would also establish another pilot program in five communities with high numbers of veterans. That program would establish peer support groups to help in the transition from active duty to civilian life and improve access to mental health services.
The bill is named after Clay Hunt, the decorated U.S. Marine sniper who took his own life in 2011 after returning from Iraq.
"Clay is only one example of veterans who are trying to make their way in our country today, but who suffer – more so than they have to – because of the Department of Defense's and Department of Veterans Affairs' mismanagement of resources for suicide prevention and mental health treatment," said McCain in a speech on the Senate floor before the vote.
Ana Radelat Ana has written about politics and policy in Washington, D.C.. for Gannett, Thompson Reuters and UPI. She was a special correspondent for the Miami Herald, and a regular contributor to The New York TImes, Advertising Age and several other publications. She has also worked in broadcast journalism, for CNN and several local NPR stations. She is a graduate of the University of Maryland School of Journalism.


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