text:
\section{Introduction}

With the increasing diversity of vehicular applications that require real-time information updates, such as   blind spot/lane change   and forward collision warnings, vehicular communications   over
the upcoming 6G mobile networks become time-critical, and thus,  fresh   updates are of   high importance \cite{9779322}. While the conventional communication latency and throughput are effective metrics to evaluate the performance  of the vehicular communication networks, these
metrics do not capture the information freshness which is critical to obtain the real-time knowledge about the location, orientation, and speed of the  vehicles. To this end, the age-of-information (AoI) is emerging as a useful metric to quantify the  freshness of the information while taking into account  the transmission latency, update generation time,  and inter-update time interval. Specifically, AoI is defined as the elapsed time between the  received information at the destination and the time when it was generated at the source \cite{6195689}. It should be noted that the inter-update time ---which is  a scheduling parameter--- is a crucial parameter in the AoI \cite{6195689}, and thus  optimizing AoI is totally different from optimizing other metrics such as the
 throughput and latency.

Moreover, the dramatic upsurge in the number of vehicles requires
the roadside infrastructures---such as roadside
units (RSUs)---to serve more vehicles
simultaneously and  support their time-critical update requirements. In this context, unicast and   multicast transmissions   are typically considered to transmit independent data messages  of interest for a user and    a group
of users, respectively. For instance, in \cite{8412246},   the authors considered maximizing the spectral efficiency by optimizing the downlink training and transmit power allocations. However, the unicast-multicast transmissions are predefined such that a user
 is either  a unicast  or belongs to a group of the multicast groups.   Another predefined unicast-multicast transmission scenario was considered in \cite{8417939}, in which     each   user receives a private
  message and a common message is broadcasted to all users. The authors maximized the desired effective channel gain by designing the unicast power allocation and multicast beamformers. In  \cite{8828094}, the energy efficiency was maximized while considering a predefined  unicast-multicast scenario with simultaneous wireless information and
power transfer.

None of the aforementioned research works considered \textit{optimizing a unicast, multicast, broadcast transmission scheduling}, while\textit{ minimizing AoI}. Note that the consideration of minimizing a time-dependent metric, such as  AoI necessitates a dynamic transmission scheduling  over the time horizon.
This paper develops a dynamic transmission scheduling and power allocation framework, in which at each time slot a vehicle  receives either unicast, multicast, or broadcast message from the RSU with optimized power allocations. The main contributions of this paper are summarized as follows:
\begin{itemize}
    \item We consider  minimizing both the AoI at the vehicles and the RSU's power expenditure, while optimizing the unicast-multicast scheduling decisions and their corresponding power allocations.    The two objectives are coupled in a conflicting manner, due to the transmit power allocations. Therefore, we formulate a multi-objective optimization problem for the two conflicting objectives.
    \item We develop a metaheuristic  solution based on the ant colony optimization (ACO)  to solve the  optimization problem, which provides a  near-optimal solution.
    \item A computationally efficient solution for the real-time implementation purposes is also developed using
     deep reinforcement learning (DRL)  model, which captures the vehicles' demands and the channel conditions in the state space and assigns processes to vehicles through dynamic unicast-multicast scheduling actions.
     \item Complexity analysis of the proposed algorithms is presented. Simulation results demonstrate interesting trade-offs between AoI  and power consumption as a function of system parameters.

\end{itemize}

The remainder of this paper is organized as follows.
Section~\ref{Sys} presents the  system model. The performance metrics and problem formulation are discussed in Section~\ref{Key}.      Section \ref{Sol} presents the ACO and DRL solutions. Section~\ref{SimSec}  illustrates
simulation results  and Section~\ref{Con} concludes the paper.

 \section{System Model and Assumptions}\label{Sys}
The considered system  consists of a  set $\mathcal{V} = \{v_i\}_{i=1}^{V}$ of  $ V $ vehicles supported by an   RSU  that   disseminates  timely
status updates  to  the vehicles.  The RSU is equipped with
a   uniform linear array  of $ N $ antennas. A multi-modal data dissemination scenario is considered, in which the RSU  is capable of providing timely
status updates  about a set $\mathcal{F} = \{f_l\}_{l=1}^{F}$ of $ F $ physical processes. The payload size of  an update     is   $L$ bits. Each vehicle is interested in   maintaining
freshness of its information
status about a subset of    processes $ \mathcal{R}_i \subseteq \mathcal{F} $. To represent the information demands of the   vehicles, we define $ \bm{R}=[r_{il}]_{\footnotesize{ V\times F}} $   such that \vspace{-.01cm}
\begin{equation}
	r_{il} = \begin{cases} 1, & \mbox{if vehicle } i  ~\mbox{is interested  in process}~ l,  \\
		0, & \mbox{otherwise}. \end{cases}
\end{equation}
The time is divided into $ T $ time slots each of duration $ \delta $. Let $ \psi_0=\{x_0,y_0\} $  be the coordinates of the RSU and $ \psi^{(t)}_i=\{x^{(t)}_i,y^{(t)}_i\} $ be the coordinates of vehicle $ i $ at time slot $ t $. The angle of vehicle $ i $ relative to the RSU at time slot $ t $ can be expressed as
	$\phi_i^{(t)}=\arccos \frac{x^{(t)}_i-x_0}{\ell_i^{(t)}}$,
where $ \ell_i^{(t)} = \lVert\psi^{(t)}_i-\psi_0\rVert $ is the distance between the   vehicle $ i $ and the RSU. Let us define the process-vehicle assignment decision variable $ \bm{\eta}^{(t)}=[\eta_{il}^{(t)} ]_{\footnotesize{ V\times F}} $,  such that
\begin{equation}
	\eta_{il}^{(t)} \!\!=\!\! \begin{cases} 1, & \!\!\!\mbox{if the update of } f_l  ~\mbox{is assigned to}~ v_i ~\mbox{at time slot}~t,  \\
		0, & \!\!\!\mbox{otherwise}. \end{cases} \nonumber
\end{equation}
It is worth noting that $ \sum_{i=1}^{V}\eta_{il}^{(t)}=1 $ implies that the update  of $ f_l $ is unicasted to  a single vehicle with $ \eta_{il}^{(t)}=1 $, $ \sum_{i=1}^{V}\eta_{il}^{(t)}=V'< V $ implies that the update of $ f_l $ is multicasted to   a group of vehicles with $ \eta_{il}^{(t)}=1 $.  Finally, $ \sum_{i=1}^{V}\eta_{il}^{(t)}= V $ implies that   the update message of $ f_l $ is broadcasted to  all  vehicles  and $ \sum_{i=1}^{V}\eta_{il}^{(t)}=0 $ implies that the information of process $ f_l $ is not transmitted to any vehicle at time slot $t$.
The communication channel between the RSU and vehicle $i$ at time slot $t$ is modeled as follows:
\begin{equation}
	\mbox{\textbf{h}}_i^{(t)} = \sqrt{\frac{c_0}{4\pi f_c\ell_i^{(t)^2}}}\mbox{\textbf{a}}^H(\phi_i^{(t)}) e^{j2\pi \varrho_i^{(t)}},
\end{equation}
where $ f_c $ is the carrier frequency,  $ c_0 $ is the speed of light, $H$ denotes the Hermitian transpose  of   $\mbox{\textbf{a}}$, and  $ \varrho_i^{(t)} $ is the
Doppler shift due to the movement of   vehicle $ i $ expressed as
$
	\varrho_i^{(t)}=\frac{c_i f_c\cos \phi_i^{(t)} }{c_0},
$
where $ c_i $ is the speed of vehicle $ i $ \cite{9557830}. Assuming a uniform linear antenna array at the RSU, the transmit array steering vector  $ \mbox{\textbf{a}}(\phi_i^{(t)} ) \in  \mathbb{C}^{N\times 1} $ (with  $ \phi_i^{(t)} $ as the   azimuth angle between the RSU and vehicle $i$ at time slot $t$) can be expressed as  follows:
 \begin{equation}
	\mbox{\textbf{a}}(\phi_i^{(t)})\! = \! [1,e^{j\pi \sin \phi_i^{(t)}}\!, e^{j 2\pi\sin \phi_i^{(t)} }\!,  \cdots\!, e^{j (N-1)\pi\sin \phi_i^{(t)} }],
\end{equation}
where $ j=\sqrt{-1} $ and the antenna spacing is $ \lambda/2 $ with $ \lambda $ as the carrier wavelength.

\section{Performance Metrics and Problem Statement}\label{Key}
\subsection{Decoding Error Probability}
To   guarantee the   vehicles' quality-of-service (QoS) requirements, the decoding error probability  of each message should be less than  a  tolerable decoding error.
The decoding error probability   can be expressed as \cite{9369424} follows:
\begin{equation}\label{error}
	\varepsilon_i(\gamma_i^{(t)}) = \Phi\left(\sqrt{\frac{\delta_2 \omega}{\Gamma^{(t)}_i}}\left[\ln\left(1+\gamma_i^{(t)}\right)-\frac{L\ln 2}{\delta_2 \omega}\right]\right),
\end{equation}
where $ \Phi\left(q\right)\triangleq\frac{1}{\sqrt{2\pi}}\int_{q}^{\infty}\exp(-\frac{u^2}{2})du $,  $ \Gamma^{(t)}_i\triangleq1-\frac{1}{(1+\gamma_i^{(t)})^2} $ is   the channel
dispersion, $ \gamma_i^{(t)} $ is the signal-to-interference plus-noise ratio (SINR) at vehicle $i$ at time slot $t$,   $ \omega $  is the bandwidth of the channel, and $ \delta_2\triangleq\delta-\delta_1 $ is the information transmission time,  with $ \delta_1 $ as the dedicated time to acquire the vehicles' angular parameters (i.e., location and speed).

\subsection{SINR Model with MRT Beamforming}
 The maximum ratio transmission (MRT)
	beamforming scheme is considered, in which the asymptotically optimal
	beamformer vector for the vehicles that assigned the same update message  is a linear
	combination of channels of these vehicles \cite{7417526},\cite{8412246}. Consequently, for a given  $ 	\bm{\eta}^{(t)} $, the linear combination of the channel vectors of vehicles that receive a message about $ f_l $  is expressed as    $\sum_{i=1}^{V}\eta_{il}\mbox{\textbf{h}}_i^{(t)}$.  Let $ \mbox{\textbf{p}}^{(t)} =$ $[p^{(t)}_1, \cdots, p^{(t)}_F] $ be the power allocation decision with     $p^{(t)}_l$ as the allocated power to transmit   message update of $f_l$. For    a given process-vehicle assignment    $ \bm{\eta}^{(t)} $ and power allocation decision $\mbox{\textbf{p}}^{(t)}$, the MRT beamforming vector  of message $ f_l $ (the beamforming vector of the group of vehicles that receive an update about $ f_l $) is expressed as  follows:

	\begin{equation}
		{\mbox{\textbf{{w}}}}_l(\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)})=	\sum_{i=1}^{V}\eta_{il}\frac{\sqrt{{p}_l^{(t)}}\mbox{\textbf{h}}_i^{(t)}}{\sqrt{N\chi^{(t)}_{i}\tilde{\xi}_{l}}},
	\end{equation}
	where $ \chi^{(t)}_{i}= {\frac{c_0}{4\pi f_c\ell_i^{(t)^2}}} e^{-j2\pi \varrho_i^{(t)}} $ is the   large-scale channel attenuation of vehicle $i$ and  $ \tilde{\xi}_{l} $ is a normalization factor \cite{8412246,8125756}.
The SINR at vehicle $i$ can thus be expressed as follows:

	\begin{equation}\label{SNR_SDMA_20}
		\gamma_i^{(t)}(\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)})= \frac{ |\mbox{\textbf{h}}_i^{(t)^H}\mbox{\textbf{w}}_l^{(t)}(\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)})|^2}{\sum\limits_{\substack{m=1\\m\neq l }}^{F} |\mbox{\textbf{h}}_i^{(t)^H}\mbox{\textbf{w}}_m^{(t)}(\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)})|^2+\sigma^2}.
	\end{equation}

\subsection{Age of Information}
The instantaneous AoI of the physical process  $f_l$ at vehicle $ i $  evolves according to
\begin{equation}\label{Ins_AoI}
	\Delta_{il}^{(t)}\!(\bm{\eta}^{(t)}\!,\!\mbox{\textbf{p}}^{(t)}\!)\!=\!\! \begin{cases} \delta,&\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\mbox{if}~ \eta_{il}^{(t)}\!\!\!=\!1 ~\mbox{and}~ \varepsilon_i(\gamma_i^{(t)}(\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)})\!)\!\leq\varepsilon^{\mbox{\scriptsize max}}_i\!,\\
		\Delta_{il}^{(t-1)}\!+\!\delta,& \mbox{otherwise}, \end{cases}
\end{equation}
where $ \varepsilon^{\mbox{\scriptsize max}}_i $ is the maximum allowed error probability at vehicle $i$. The time-average  AoI of $f_l$ at vehicle  $ i $ over $ T $ time slots is
	 $  \bar{\Delta}_{{il}}(\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)})\triangleq\mathbb{E}_{T}\!\!\left[\Delta_{il}^{(t)}(\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)})\right]=$ $ \frac{1}{T}\sum_{t=1}^{T}	\Delta_{il}^{(t)}(\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)}) $. Consequently, the total time-average  AoI    can be expressed as follows:
	 \begin{equation}\label{Avv_AoI}
	 	\begin{split}
	 	\bar{\Delta}(\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)})&=\sum_{i=1}^{V}\sum_{l=1}^{F} r_{il}\bar{\Delta}_{{il}}(\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)})\\
	 	&=\frac{1}{T}\sum_{i=1}^{V}\sum_{t=1}^{T}\sum_{l=1}^{F} r_{il}	\Delta_{il}^{(t)}(\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)}).
	 	\end{split}
	 \end{equation}
Note that the maximum value of $ \bar{\Delta}_{{il}} $ is $ \delta(T+1)/2 $, which corresponds the case of no update about $f_l$ is received at vehicle $ i $ over the $ T $ time slots. Thus, the maximum value (upper bound) of the total time-average  AoI $ \bar{\Delta}^{\mbox{\scriptsize max}} $ can be expressed as:
\begin{equation}\label{max_AoI}
	\bar{\Delta}^{\mbox{\scriptsize max}} = \frac{\delta (T+1)}{2}\sum_{i=1}^{V}\sum_{l=1}^{F}r_{il},
\end{equation}
which corresponds the case of no update is received by any vehicle during the $ T $ time slots. The minimum value (lower bound) of the total time-average  AoI $ \bar{\Delta}^{\mbox{\scriptsize min}} $ corresponds the case of updating each vehicle  in each time slot. Keeping in mind that a vehicle $ i $ is interested in $ |\mathcal{R}_i|=\sum_{l=1}^{F}r_{il} $ processes and the best option is to alternate the updates between the  $ |\mathcal{R}_i| $ processes, $ \bar{\Delta}^{\mbox{\scriptsize min}} $
  can be expressed as\footnote{The expression in \eqref{min_AoI}  is valid for $ T > |\mathcal{R}_i|+1  $; for the special case $ T < |\mathcal{R}_i| -1 $, we have $ \bar{\Delta}^{\mbox{\scriptsize min}} =\sum_{i=1}^{V} \frac{\delta}{T} \left[|\mathcal{R}_i| \frac{T(T+1)}{2} -\sum_{r=1}^{T}\frac{r(r+1)}{2}\right] $; both expressions are equivalent for $|\mathcal{R}_i|-1\leq T\leq|\mathcal{R}_i|+1$.}:
\begin{equation}\label{min_AoI}
	\bar{\Delta}^{\mbox{\scriptsize min}} =\sum_{i=1}^{V} \frac{\delta}{T}\left[ T\frac{|\mathcal{R}_i|(|\mathcal{R}_i|+1)}{2}- \sum_{r=1}^{|\mathcal{R}_i|-1}\frac{r(r+1)}{2}\right].
\end{equation}

  \begin{figure}[t]
  	\begin{center}
  		\includegraphics[width=.99\linewidth]{Mot}
  		\caption{Illustrative example with $V=5$ vehicles and  $F=4$   processes.}\label{Mot}
  	\end{center}
  \end{figure}

\subsection{Significance of Process-Vehicle Assignment and Power Allocation - A Toy Example}\label{Mot_example}
Let us consider $V=5$ vehicles, where each vehicle is interested in a subset of  $\mathcal{F} =\{f_1, f_2, f_3, f_4\}$ processes with demands as illustrated in Fig. \ref{Mot}. The associated information demand matrix $\mathbf{R}$   can be represented as follows:
\begin{equation}
	\mathbf{R}=[r_{il}]_{\footnotesize{ 5\times 4}}=\begin{blockarray}{ccccc}
		f_1 & f_2 & f_3 & f_4  \\
		\begin{block}{[cccc]c}
			1 & 0 & 0 & 1 & v_1\\
			1 & 0 & 1 & 0 &  v_2 \\
			1 & 0 & 0 & 1 &  v_3 \\
			1 & 1 & 1 & 0 & v_4 \\
			1 & 1 & 0 & 0 & v_5 \\
		\end{block}
	\end{blockarray}.
\end{equation}
Let us assume that the observation interval is $T=7$ time slots and  other parameters are as listed in Table \ref{TableResults}. According to \eqref{max_AoI} and \eqref{min_AoI}, the maximum and minimum time-average AoI at the vehicles can be computed  $\bar{\Delta}^{\mbox{\scriptsize max}} = 308/7= 44$s  and $ \bar{\Delta}^{\mbox{\scriptsize min}} = 108/7 \approx 15.4$s, respectively.
Let us assume that the RSU assigns the processes to vehicles and allocates the power at random, the time-average   AoI will  vary around $ 210/7 \approx 30$s and the power consumption will be around $0.5$W. By   examining    all   possible  process-vehicle assignment  and power allocation decisions  with objective of minimizing both AoI and power consumption,   the time-average   AoI can be reduced to  $ 124/7 \approx 17.7$s while the time-average consumed power   is $0.18$W if the following decisions are performed.
At $ t=1 $ no message is transmitted. At $t=2$, an update about $ f_1 $ is broadcasted to all vehicles. At $t=3$, an update about $ f_3 $ is unicasted to $v_2$ and updates about $ f_4 $ and $ f_2 $  are multicasted to $\{v_1, v_3\} $ and $\{v_4, v_5\} $, respectively,   and so on.
The question is how to select optimal  scheduling and power allocation decisions at each time slot for arbitrary number of physical processes and  vehicles with different demands. This motivates the problem formulation in the following.

\subsection{Problem Formulation}\label{Prob}
We consider minimizing the time-average AoI of each process at the vehicles   as well as the time-average   power consumption at RSU.  Keeping in mind   the trade-off between   these two objectives and the fact that   they  have different units, ranges, and orders of magnitude, they
should be normalized such that they have similar ranges \cite{marler2004survey}. Consequently,  we define    a    multi-objective weighted sum  utility function    as:
\begin{equation}\label{Obj}
	\begin{split}
		{O}(\bm{\eta}^{(t)}\!,\!\mbox{\textbf{p}}^{(t)})\!=& \zeta\frac{\bar{\Delta}(\bm{\eta}^{(t)}\!,\mbox{\textbf{p}}^{(t)}\!) \!-\!\bar{\Delta}^{\mbox{\scriptsize min}}}{\bar{\Delta}^{\mbox{\scriptsize max}}-\bar{\Delta}^{\mbox{\scriptsize min}}}\!+\!(1\!-\!\zeta)\frac{\bar{{p}}^{(t)}\!-\!P^{\mbox{\scriptsize min}}}{P^{\mbox{\scriptsize max}}\!-\!P^{\mbox{\scriptsize min}}},
	\end{split}
\end{equation}
 where  the time-average power consumption can be given as $ \bar{{p}}^{(t)} = \frac{1}{T}\sum_{t=1}^{T}\sum_{l=1}^{F}p^{(t)}_l $,  $ 0 < \zeta \leq 1$ is a relative weight to give preference to minimize the AoI or the power, $ \bar{\Delta}^{\mbox{\scriptsize max}} $ and $ \bar{\Delta}^{\mbox{\scriptsize min}} $ are the maximum and minimum total time-average AoI as expressed in \eqref{max_AoI} and \eqref{min_AoI}, respectively,   $ P^{\mbox{\scriptsize max}} $ is the maximum transmission power of the RSU, and $ P^{\mbox{\scriptsize min}}=0 $.   The   optimization problem is thus formulated  as follows:

\begin{subequations}\label{P1}
	\begin{alignat}{2}
		\mbox{\textbf{P1}}~	&\!\min_{\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)}}&& {O}(\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)}) \label{OPP1}\\
		&\mbox{s.t.}&& {\sum_{l=1}^{F}p_l^{(t)} \leq P^{\mbox{\scriptsize max}}},\label{con1}\\
		&&~~   & \sum_{l=1}^{F} \eta_{il}^{(t)} \leq 1, ~ \forall~ v_i \in \mathcal{V},\label{con3}\\
				&&~~   &   \eta_{il}^{(t)} r_{il} = \eta_{il}^{(t)}, ~ \forall~ 1\leq i\leq V, 1\leq l\leq F, \label{con4}\\
					&&~~   & {p_l^{(t)}\geq 0, ~ \forall~ f_l \in \mathcal{F}},\label{con2}\\
		&                  & ~~     & \eta_{il}^{(t)}\in \{0, 1\},  ~ \forall v_i  \in \mathcal{V}, f_l  \in \mathcal{F}. \label{con5}
	\end{alignat}
\end{subequations}
Constraint \eqref{con1}  guarantees that the allocated power is less than the maximum transmission power of the RSU. Constraint \eqref{con3}  guarantees that at most one process is assigned to each vehicle at each time slot.
Keeping in mind that $ \bm{R} $ and $  \bm{\eta}^{(t)} $ are binary variables, \eqref{con4} guarantees that if a vehicle $ i $ is not interested in process $l$ (i.e., $ r_{il}=0 $) then process $l$ will not be assigned to vehicle $i$ (i.e., $ \eta_{il}^{(t)}  $ should be $0$).

The optimization problem in \eqref{P1} is a mixed-integer non-linear programming (MINLP) problem, where the discontinuity in the objective function comes from (8), the non-linearity comes from (6),   and the integer constraint arises from (14f).

	\section{Proposed Age-Optimal Solutions}\label{Sol}
First, it is important to note that from \eqref{Ins_AoI},    the AoI of process $f_l$ at vehicle $i$ can be minimized if both $\eta_{il}^{(t)}=1$ and  $\varepsilon_i(\gamma_i^{(t)}(\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)})\!)\leq\varepsilon^{\mbox{\scriptsize max}}_i$. To ensure that $\varepsilon_i(\gamma_i^{(t)}(\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)})\!)\leq\varepsilon^{\mbox{\scriptsize max}}_i$, we denote
 $ \hat\gamma_i $ be the SINR at vehicle $v_i$ that ensures    $\varepsilon_i(\hat \gamma_i)=\varepsilon^{\mbox{\scriptsize max}}_i$ which can be found by solving \eqref{error} numerically. Then, from \eqref{error} and \eqref{SNR_SDMA_20}, the AoI of the process $f_l$ at vehicle $v_i$ can be minimized if both $\eta_{il}^{(t)}=1$ and the following inequality are satisfied, i.e., \vspace{-.31cm}
 \begin{equation}\label{Const}
 \frac{ {p}_l^{(t)}|\mbox{\textbf{h}}_i^{(t)^H}\mbox{\textbf{w}}_l^{(t)}(\bm{\eta}^{(t)})|^2}{\sum\limits_{\substack{m=1\\m\neq l }}^{F}{p}_m^{(t)} |\mbox{\textbf{h}}_i^{(t)^H}\mbox{\textbf{w}}_m^{(t)}(\bm{\eta}^{(t)})|^2 +\sigma^2}\geq \hat \gamma_i.
 \end{equation}
 \vspace{-.31cm}

 Consequently, a solution for
 the optimization problem in \eqref{P1} can be obtained by solving the following  optimization problem:
 \begin{subequations}\label{P3}
 	\begin{alignat}{2}
 		& \textbf{P2} \min_{\bm{\eta}^{(t)}{, \mbox{\textbf{p}}^{(t)}}}&&~ {O}(\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)}_{\bm{\eta}})  \nonumber\\
 		&\mbox{s.t.}&& \eqref{con3}, \eqref{con4}, ~\mbox{and}~\eqref{con5}, \nonumber\
 	\end{alignat}
 \end{subequations}
where $ \mbox{\textbf{p}}^{(t)}_{\bm{\eta}}\!=[{p}^{(t)}_{\bm{\eta}_1}, \cdots, {p}^{(t)}_{\bm{\eta}_F}] $ is the solution of the following linear programming problem:
\vspace{-.21cm}
 \begin{subequations}\label{PowerP1}
	\begin{alignat}{2}
	&\mbox{\textbf{p}}^{(t)}_{\bm{\eta}}\!=	\!\min_{\mbox{\textbf{p}}^{(t)}} \sum_{l=1}^{F}p_l^{(t)}  \nonumber\\
		&\mbox{s.t.}
		\frac{ \eta_{il}^{(t)}{p}_l^{(t)}|\mbox{\textbf{h}}_i^{(t)^H}\!\!\mbox{\textbf{w}}_l^{(t)}(\bm{\eta}^{(t)})|^2}{\sum\limits_{\substack{m=1\\m\neq l }}^{F}\!{p}_m^{(t)} |\mbox{\textbf{h}}_i^{(t)^H}\!\!\mbox{\textbf{w}}_m^{(t)}(\bm{\eta}^{(t)})|^2 \!+\!\sigma^2\!}\!\!\geq\! \eta_{il}^{(t)} \hat\gamma_i,
	                  ~~ \forall  f_l ,   v_i,\label{conPower1}
 \\
		& ~~ \eqref{con1} ~\mbox{and}~ \eqref{con2}	\nonumber	\end{alignat}
\end{subequations}
It is worth noting that for a given $  \bm{\eta}^{(t)} $,  constraint \eqref{conPower1} guarantees  that the allocated power minimizes the AoI. If \eqref{PowerP1} is infeasible for a given $  \bm{\eta}^{(t)} $, then  $  \bm{\eta}^{(t)} $ does not minimize the objective function and will be discarded.  The
 strategy of the following ACO and DRL solution approaches can be summarized as follows. Search for an optimized $  \bm{\eta}^{(t)} $ by exploring its search space and for each candidate  $  \bm{\eta}^{(t)} $ find the corresponding best power allocation by solving \eqref{PowerP1}. The fitness of a candidate  $  \bm{\eta}^{(t)} $ is reflected by its ability to minimize the objective function with a feasible power allocation.

\subsection{Ant Colony Optimization (ACO)
	 }
 The optimization problem in \eqref{P3}   can be solved
	 by enumerating all the feasible decisions. Such exhaustive search approach is computationally inefficient, which motivates  designing a metaheuristic solution based on the ACO        for rapid
	 discovery of good solutions and guarantee convergence \cite[Ch.4.3]{ACObook}.
	  In the proposed ACO algorithm, a colony of  $A$ ants  collaborate to solve $\textbf{ {P1}}$. Each ant   $ a \in A $   travels  a   tour of $T$ steps. In each step, it assigns a process for each vehicle.
The probability that     ant $ a $ assigns process $ f_l $ to vehicle $ v_i $     and the probability it does not  assign a process  to vehicle $ v_i $  at time  $t$  are    obtained as:
\begin{equation}\label{bid}
	\begin{split}
		\bar{\pi}_{il}^{\left(t\right)}=\frac{(\bar{\tau}^{(t)}_{il})^{\iota_1}(\bar{\varrho}^{(t)}_{il})^{\iota_2}}{1+\sum_{l=1}^{F}(\bar{\tau}^{(t)}_{il})^{\iota_1}(\bar{\varrho}^{(t)}_{il})^{\iota_2}},~
		\bar{\pi}_{i0}^{\left(t\right)}= 1-\sum_{l=1}^{F}\bar{\pi}_{il}^{\left(t\right)},
	\end{split}
\end{equation}
respectively, where  $ \bar{\tau}^{(t)}_{ir} $   is the trail pheromone and $ \bar{\varrho}^{(t)}_{il}$ is the   attractiveness   of assigning process $f_l$ to vehicle $v_i$. The latter is  set to be
\begin{equation}
    \bar{\varrho}^{(t)}_{il} =
		\frac{r_{il}\Delta_{il}^{(t)}}{t},
\end{equation}
to   give higher attractiveness to assigning the process with high AoI and of interest to  $v_i$.  { The parameters $\iota_1 $ and $\iota_2$   control the influence of the pheromone and attractiveness, respectively.}  At each step, ant $a$ obtains $  \bm{\eta}^{(t,a)} $ based on \eqref{bid} and obtain the power allocation $ \mbox{\textbf{p}}^{(t,a)} $  by  solving \eqref{PowerP1}. Only ants  that  obtain the highest and second-highest $O(\bm{\eta}^{(t,a)},\mbox{\textbf{p}}^{(t,a)}) $ $ \forall a \in A $   deposit their pheromone \cite{doerner2004pareto}.
The
pheromone is   updated as follows:
\begin{equation} \label{deposit}
		\bar{\tau}_{il}^{(t)}\leftarrow\left(1-\kappa\right)\bar{\tau}_{il}^{(t)}+ {\eta}_{il}^{(t,a)}\nabla{\tau}^{(a)},
\end{equation}
where $ \kappa $  is the pheromone evaporation coefficient and $ \Delta{\tau}^{(a)} $ is the deposit pheromone, which is expressed as
\begin{equation}
	 \nabla{\tau}^{(a)}\!\!=\!\begin{cases} \exp[-O(\bm{\eta}^{(t,a)},\mbox{\textbf{p}}^{(t,a)})], &\!\!\!\!\mbox{if}~  \sum\limits_{l=1}^{F}p_l^{(t,a)} \!\leq\! P^{\mbox{\scriptsize max}}\!,\\
		0, & \mbox{otherwise}. \end{cases}
\end{equation}
The ACO algorithm is illustrated in \textbf{Algorithm \ref{euclid1}} which  iterates until the improvement in the  best solution of the whole colony is less than a threshold $\epsilon_0$ or a maximum number of colonies $ I $  has been generated.

\begin{algorithm}
	\small
	\caption{\small ACO algorithm for age-optimum dynamic transmission.}\label{euclid1}
	\begin{algorithmic}[1]
 \small
 	\State  {\textbf{Input} $\bm{R}$,  $\mbox{\textbf{h}}_i^{(t)}$, $\kappa$, $I$, $A$, $\epsilon_0$;}
	\State  $ O^* \leftarrow  \infty $; {$ O_p \leftarrow  0 $;}
		\State    {\textbf{while} $ I \geq 1 $ and $ |O^* -O_p|\geq \epsilon_0 $  \textbf{do}}
		\State $ ~~ $ $O_1 \leftarrow  \infty $; $O_2 \leftarrow  \infty $; {$I=I-1$; $O_p=O^*$;}
		\State $ ~~ $ \textbf{for} $ a =1 $ to $ A $  \textbf{do}
		\State $ ~~~~~ $ \textbf{for} $ t =1 $ to $ T $  \textbf{do}
		\State $ ~~~~~~ $ Obtain  $\bm{\eta}^{(t,a)}$ using \eqref{bid}; Obtain  $\mbox{\textbf{p}}^{(t,a)}$ by solving \eqref{PowerP1};
		\State  $ ~~~~~ $  \textbf{end for}
		\State $~~$ Evaluate $O(\bm{\eta}^{(t,a)},\mbox{\textbf{p}}^{(t,a)})$ using \eqref{Obj};
		\State  $ ~~ $  \textbf{if} $ O^* >  O(\bm{\eta}^{(t,a)},\mbox{\textbf{p}}^{(t,a)})$,
	 $ O^* =  O(\bm{\eta}^{(t,a)},\mbox{\textbf{p}}^{(t,a)})$;
	     \textbf{end if};
		\State  $ ~~ $  \textbf{if} $ O_1 >  O(\bm{\eta}^{(t,a)},\mbox{\textbf{p}}^{(t,a)})$,  $ a_1=a$;
		\State  $ ~~ $  \textbf{else}  \textbf{if} $ O_2 > O(\bm{\eta}^{(t,a)},\mbox{\textbf{p}}^{(t,a)})$,  $ a_2 = a$;
	 \textbf{end if}
		\State  $ ~ $  \textbf{end for}
		\State  $ ~~~ $ Deposit pheromone of $ a_1 $ and $ a_2 $ using \eqref{deposit};
		\State   \textbf{end while}
		\State  \textbf{Return} $O^*$.

		\normalsize
	\end{algorithmic}
\end{algorithm}

{\subsection{DRL-Based Solution Approach}
In this section, we aim to design  a real-time solution approach for the optimization problem in \eqref{P1}.   In this context, we
develop a DRL model   that involves the definition of the environment state space
$ \bm{s}^{t}\in \bm{\mathcal{S}} $, the action space $ \bm{\mu}^{(t)}\in \bm{\mathcal{A}} $, and the    immediate reward function $ \rho^{(t)} $.

\begin{itemize}
	\item The state of the environment at time slot $ t $  is given by
	\begin{equation}
		\bm{s}^{t}\!=\!\!\left\{ \{\chi^{(t)}_i\},\{ r_{i1}\Delta_{i1}^{(t)},r_{i2}\Delta_{i2}^{(t)}, \cdots\!, r_{iF}\Delta_{iF}^{(t)}\}\right\}_{i=1}^V\!,
	\end{equation}
	which captures the   channel state and the AoI of the processes of interest for the $ V $ vehicles.
	\item The  action at time slot $ t $ is defined as $ \bm{\mu}^{(t)}=[\mu^{(t)}_i]_{\footnotesize{ V\times 1}} $, which is a  vector of integers   $ \mu^{(t)}_i \in \{0 \cup \mathcal{R}_i\} $, such that
	\begin{equation}
		\mu^{(t)}_i = \begin{cases} l,&  \mbox{implies }  f_l  ~\mbox{is assigned  to}~ v_i,  \\
			0, &  \mbox{implies}~v_i~\mbox{is not updated at}~t. \end{cases}
	\end{equation}
 It is worth noticing  that $\bm{\mu}^{(t)}$ is an equivalent representation to $\bm{\eta}^{(t)}$ with a dimension  of $V\times 1$ instead of $V\times F$.
	\item The immediate
	reward at time slot $ t $ is expressed as
\begin{equation}
		\rho^{(t)}\!\!=\!\zeta\frac{\bar{\Delta}_t(\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)}) \!-\!\bar{\Delta}_t^{\mbox{\scriptsize min}}}{\bar{\Delta}_t^{\mbox{\scriptsize max}}-\bar{\Delta}_t^{\mbox{\scriptsize min}}}\!+\!(1\!-\zeta)\frac{\hat{\mbox{\textbf{p}}}^{(t)}-P^{\mbox{\scriptsize min}}}{P^{\mbox{\scriptsize max}}-P^{\mbox{\scriptsize min}}},
\end{equation}
where $ \hat{\mbox{\textbf{p}}}^{(t)}=\frac{1}{t}\sum_{t'=1}^{t} {\mbox{\textbf{p}}}^{(t')} $, $\bar{\Delta}_t(\bm{\eta}^{(t)},\mbox{\textbf{p}}^{(t)})$,  $ \bar{\Delta}_t^{\mbox{\scriptsize max}} $,  and $\bar{\Delta}_t^{\mbox{\scriptsize min}}$ are obtained by replacing $T$ by $t$ in \eqref{Avv_AoI}, \eqref{max_AoI}, and \eqref{min_AoI}, respectively. {The reward is set to $ -\log(\rho^{(t)}+\nu) $, where $ \nu $ is a very small number that introduced to avoid infinite  reward.}
\end{itemize}
The DRL training algorithm is illustrated in \textbf{Algorithm~2}.  It is worth mentioning that the trained DRL agent estimates an action $\bm{\mu}^{(t)}$ for a given state, the corresponding $\bm{\eta}^{(t)}$    is utilized to find the power allocation in \eqref{PowerP1}   and evaluate the objective function in \eqref{OPP1}.

\begin{algorithm}[ht]
	\caption{\small DRL training algorithm   for age-optimum dynamic transmission.}\label{DeepLearning}
	\begin{algorithmic}[1]\small
		\State  Initialize the  weights of the deep   network $\theta $ and the replay buffer  \textbf{B};\label{l2}
		\State  \textbf{For $ episode=1 $ to} Max no. of episodes \textbf{do}\label{l3}
		\State  Initialize the
		environment and receive the initial state $ \bm{s}^{(1)} $; \label{l4}
		\State $~$\textbf{Repeat:}
		\State $ ~~$With probability $ \epsilon $, select a random action $\bm{\mu}^{(t)} \in \mathcal{A}$; Otherwise, select $ \bm{\mu}^{(t)}=\arg\max\limits_{\forall \bm{\mu}^{(t)}\in \bm{\mathcal{A}}}Q(\bm{s}^{(t)},\bm{\mu}^{(t)}\mid\bm{\theta}) $;
		\State $ ~~$ Obtain $\bm{\eta}^{(t)}$; Obtain $ \mbox{\textbf{p}}^{(t)^*}  $  by solving \eqref{PowerP1};
		\State $ ~~$  Observe the reward  $ \rho^{(t)} $ and    next state $\bm{s}^{({t+1})}  $;
		\State $ ~~$	Store the transition $ \{\bm{s}^{({t})},\bm{\mu}^{(t)}, \rho^{(t)},\bm{s}^{({t+1})}\}$ in \textbf{B};
	  $ t=t+1 $;
		\State	$~$\textbf{Until} terminal state $t=T$.
		\State $ ~~~$
		Sample a random mini-batch of $ M $ transitions from \textbf{B};
		\State $ ~~~$ For each transitions  in $ M $ obtain $y_m$ such that  \begin{equation*}
			y_m\!=\!\! \begin{cases}\rho^{(m)},&\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\!\mbox{if }\bm{s}^{(m+1)}  ~\mbox{is a terminal state},  \\
				\rho^{(m)}\!+\!\gamma\max\limits_{\forall \bm{\mu}^{(m)}\in \mathcal{A}}Q(\bm{s}^{{t}},\bm{\mu}^{(m)}\mid\bm{\theta}),&\!\!\!\!\mbox{otherwise}. \end{cases}
		\end{equation*}
		\State $ ~~~$  Update the weight of the DNN network by minimizing the loss $ L(\bm{\theta})=\frac{1}{M}\sum_{m=1}^{M}(y_{m}-Q(\bm{s}^{(m)},\bm{\mu}^{(m)}\mid\bm{\theta}))^2 $;
		\State \textbf{End for}
		\normalsize
	\end{algorithmic}
\end{algorithm}
}

\subsection{Complexity Analysis}
Keeping in mind that a process-vehicle assignment decision $  \bm{\eta}^{(t)} $ can be represented by a vector $ \bm{\mu}^{(t)}=[\mu_{i}^{(t)} ]_{\footnotesize{ 1\times V}} $, the
\begin{table}[ht]
	\caption{Simulation Parameters.}
	\begin{center}
		\begin{adjustbox}{width=.48\textwidth}			\begin{tabular}{|c|c||c|c||c|c|}
				\hline				\textbf{Parameter}&\textbf{Value} & \textbf{Parameter}&\textbf{Value}   & \textbf{Parameter}&\textbf{Value}    \\ \hline
				$ P^{\mbox{{\footnotesize max}}} $ 	&   $ 0 $ dB  &  $ c_i $ 	& $\sim U(10, 15)  $ m/s  \cite{9557830}  &   $ \omega $	&   $ 10 $ MHz \cite{9557830} \\ \hline
				$ f_c $ 	&   $ 3 $ GHz  \cite{9557830}&  $ N $ 	&   $ 64 $  \cite{9557830} &  $ L $ 	&   $128 $ byte  \\ \hline
				$  \varepsilon^{\mbox{{\footnotesize max}}} $ 	&   $ 10^-6 $ &  $ c_0 $ 	&   $ 2.99\times 10^8$ m/s & $ \sigma^2 $ 	&   $ 0.1  $   \\ \hline
				$ I $	&   $ 400 $ iteration &  $ A $ 	&   $ 100$ individuals  &   $ \delta $ 	&  $ 1   $ s  \\  \hline
				$ \kappa $	&   $ 0.1 $ &  $ \iota_1/\iota_2 $ 	&   $ 1$  &   $ {\epsilon_0 }$ 	&  {$0.01 $}    \\  \hline
				$ \textbf{B} $	&   $ 10^4 $ &   mini-batch 	&   $ 64$  &   learning rate	&  $ 0.001 $    \\  \hline
			\end{tabular}
		\end{adjustbox}
	\end{center}
	\label{TableResults}
\end{table}
 search space of \eqref{P3} over the $T$ time slots is $ \mathcal{O}((F+1)^{V}T) $. The  worst-case computational complexity of evaluating the objective function in \eqref{Obj} is  $ \mathcal{O}(VFT^2) $ operations and solving \eqref{PowerP1}  requires   $ \mathcal{O}((V+F)^{2.5}) $ operations. Consequently, the computational complexity of the exhaustive search is  $ \mathcal{O}(V^{3.5}T^3F^{V}) $. An ant agent performs $ \mathcal{O}(V F) $ operations to
  find a process-vehicle assignment decision,   $ \mathcal{O}((V+F)^{2.5}) $ operations to allocate the power, and  $ \mathcal{O}(VFT^2) $ operations to evaluate  \eqref{Obj}. Consequently, the  worst-case computational complexity of the ACO is  $ \mathcal{O}((VF)^{4.5}T^3AI) $, where $A$ is the number of ants in the colony and $I$ is the  maximum number of colonies. Considering a scenario of $V=5$ vehicles and $F=4$ processes, the   average execution time of the exhaustive search, ACO, and DRL  solution approaches is $ 1.8 $ s, $ 0.2 $ s, and $0.01$ s, respectively. \ {Average execution time using MATLAB on an Intel(R) Core(TM) i7-3770 CPU machine      working at a clock frequency of 3.4	GHz  and 16 GB of RAM.}

\section{Simulation Results and Discussions}\label{SimSec}
This section introduces simulation results to    evaluate  the proposed framework and compare its
performance with the random solution approach, in which the  process-vehicle assignment and power  allocations decisions  are selected at random.
   Unless
otherwise stated, the considered     numerical values of the system  parameters and solution approaches  are listed in Table
\ref{TableResults}.

\begin{figure*}
\vspace{-3mm}
\centering
\begin{minipage}{0.301\linewidth}
\includegraphics[width=1.\linewidth]{Figure_Zeta_0}
		\caption{Objective function in \eqref{Obj}    versus  the relative weight $\zeta$ with total number of   $F=4$   process and $\abs{\mathcal{R}_i}=2$.}\label{figRes1}

\end{minipage}\hfill
\begin{minipage}{0.301\linewidth}
\includegraphics[width=1.\linewidth]{Figure_Zeta_11}
		\caption{Average normalized  AoI and power expenditure    versus  the relative weight $\zeta$ with total number of processes $F=4$   process and $\abs{\mathcal{R}_i}=2$.}\label{figRes2}
\end{minipage}\hfill
\begin{minipage}{0.301\linewidth}
	\includegraphics[width=1.\linewidth]{Figure_RF}
		\caption{Average normalized  AoI and power expenditure    versus number of process of interest per vehicle $\abs{\mathcal{R}_i}$ with total number of processes $F=10$   process  and $\zeta=0.5$.}\label{figRes3}
\end{minipage}
\label{fig2}
\vspace{-5mm}
\end{figure*}

Figure \ref{figRes1} illustrates the objective function versus the relative weight $ \zeta $ for the proposed framework obtained using the exhaustive search, ACO, and DRL  solution approaches as well as the random approach.  It is seen that the      ACO and DRL approaches achieve performance close to that of the exhaustive search approach and the random approach provides the worst performance in comparison with the proposed framework with the three solution approaches.

To get more insight into this result,  Fig. \ref{figRes2} shows the average normalized AoI and power consumption versus the relative weight $ \zeta $ for the random solution and the   proposed framework using the ACO and DRL solutions. The curves of the exhaustive search   follow a similar trend to that of the ACO and are omitted to make Fig. \ref{figRes2} less crowded.
It is   noticed that the proposed framework  provides a good trade-off between  AoI and power expenditure as for low values of $ \zeta $ it minimizes the power expenditure and as
$ \zeta $ increases  it minimizes the AoI. That is not the case for the random solution, in which both the AoI and power expenditure are not function of the relative weight and the power consumption is higher than that of the proposed framework.

Figure \ref{figRes3} depicts the average normalized  AoI and power expenditure  of the  random solution  and the proposed framework using the ACO solution   versus the number of process of interest per vehicle $\abs{\mathcal{R}_i}$. It is clear that the AoI increases as the vehicles' demand increases in both random solution and proposed framework, with less AoI in the proposed framework. On the other hand, the  power expenditure in the proposed framework is decreased as  the vehicles' demand increases. This is attributed to   the fact that for a fixed set of processes, as the  number of process of interest per vehicle increases the demand of the vehicles becomes more similar which enables the proposed framework to transmit the same update to more vehicles, which reduces the interference, and thus reduces the  power expenditure.

\section{Conclusion}\label{Con}
	This paper has proposed a  dynamically unicast, multicast, and broadcast transmission framework to minimize both AoI and power consumption in vehicular networks. To solve the formulated mixed integer optimization problem, two solution approaches have been developed, namely a metaheuristic solution  based on ACO and  less computational complex in real-time evaluation solution based on DRL approach.
 Simulation results have illustrated that the proposed framework minimizes both the AoI and power consumption and provides a good trade-off between them. Results also have showed that ACO and DRL solution approaches provide  close to the optimal	solution, which is obtained through exhaustive search.

\section*{Acknowledgment}
This research was supported by two Discovery Grants funded by the Natural Sciences and Engineering Research Council of Canada.

\bibliographystyle{IEEEtran}

redpajama_set_name: RedPajamaArXiv


text:
Susano è una frazione del comune di Castel d'Ario, in provincia di Mantova.

Monumenti e luoghi d'interesse
 Ex chiesa dell'Assunzione ed ex convento domenicano, edificati nel XVII secolo.
 Corte di Susano, del XIV secolo, fu di proprietà dei Gonzaga

Note

Altri progetti

Collegamenti esterni

 Ecomuseo Mantova. Ex convento ed ex chiesa dell'Assunzione della Beata Vergine Maria.

Susano

redpajama_set_name: RedPajamaWikipedia


There is only one name generation rulepack ror tribals: "NamerPersonTribal".
It would be much better to have separate rulepacks for male and female colonists, just like how it works with animals: "NamerAnimalGenericFemale", "NamerAnimalGenericMale".
I must agree, the names for men and women are distinct in several languages, and it would be nice if we could differentiate better.


Congratulations to our ACFSC skaters who competed at the Winter Classic at the Igloo Ice Rink on Saturday.
Maneuver Team, which placed 3rd. Yes, you can continue to skate in College!
being named to the NJ Council of Figure Skating Clubs Academic Honors Team!
June 7 at the Mennan Ice Arena. We are so proud of Olivia!!


text:
Richard Hurley: We need your help: what will India's 2014 general elections mean for health?
In a couple of months India will hold parliamentary elections to determine its next central government. This administration, due to hold office from June, will also have responsibility for drafting India's 13th five year plan, which is key to its direction of development from 2017.
Prime Minister Manmohan Singh has said that he will not serve another term. Will his left-of-centre Indian National Congress, the ruling party since 2004, hang on to power? Or might the main opposition, the more socially conservative Bharatiya Janata Party, win, giving its leader, Narendra Modi, his chance in the hot seat?
Could one of these parties gain an outright majority or might some of the smaller parties gain a footing, if a coalition is the only way to form a government? And what about the new contender on the scene, the Aam Aadmi Party? Might it continue to gain popularity and sweep up a sizeable number of seats?
How might the next government's economic and health policies affect the future of Indian drug manufacturing, healthcare services, medical education, and clinical research, for example?
Current government spending on health ranks India at a lowly 171th place out of 175 countries, at just 1% of GDP in 2011. Indeed, health did not feature at all in the finance minister's agenda to make India the world's third largest economy, in the interim budget that he just announced.
But in a country where two thirds of citizens, some 800 million people, must meet all their healthcare expenses out of pocket, leading to widespread indebtedness, why is neither main party using universal health coverage to advance its campaign–that is, some form of insurance for all citizens (see this BMJ personal view article, How India can provide healthcare for all, and a feature, Protecting India's poorest from unaffordable medical bills, for more information)
And what about malnutrition, which affects as many as two in five Indian children under 3 years old? And the infectious diseases that continue to burden the Indian populace heavily, such as tuberculosis, dengue, rabies, and pneumonia. What about sanitation? And women's health?And rural health? And shortcomings in nursing?
In many countries health policy is a deal breaker come election time. For example, no UK political party can afford to ignore let alone threaten the NHS. And in the United States, consider the level of public debate surrounding "Obamacare" at the last election. The same does not seem to be true in India on anywhere near the same scale.
With your help, we'd like to start to try to change that. We'd like to know what you, as a healthcare professional, think about India's political parties, their health and other policies, their leaders, and the electoral process in general.
Who do you think will win, and what will it mean for health and healthcare in the country?
Who do you think should win and why?
Who would you appoint to lead India, if you could choose anyone?
What are the key health and other policy areas that the parties should focus on?
Why does health seem so far from the top of the parties' lists of priorities?
Must health policy always play second fiddle to economic policy?
And, finally, as we approach this defining moment in India's journey, how would you like to see us present these issues in The BMJ? Please do post a comment in response to this blog and let us know.
And please share this blog with your colleagues and friends.
I thank Anita Jain, The BMJ's India editor, for useful comments on an earlier draft.
Richard Hurley is India comment editor at The BMJ
Anita Jain, South Asia
Kailash Chand: Statins
Giridhara R Babu: Health for Indians—who cares about it anyway?

redpajama_set_name: RedPajamaCommonCrawl


whenever you call or write to us.
ANY ERRORS ON YOUR BILLING STATEMENT ?
and why you believe that Brickell Key Capital has made an error in the servicing of your mortgage loan.
SUFFERED ANY PROPERTY DAMAGE ?


text:
200+ NY Dealers Pull Out of Clunkers Program
Published Wed, Aug 19 20093:02 PM EDT Updated Fri, Sep 13 20134:33 PM EDT
Hundreds of auto dealers in the New York area have withdrawn from the government's Cash for Clunkers program, citing delays in getting reimbursed by the government, a dealership group said Wednesday.
Source: toyota.com
The Greater New York Automobile Dealers Association, which represents dealerships in the New York metro area, said about half its 425 members have left the program because they cannot afford to offer more rebates. They're also worried about getting repaid.
"(The government) needs to move the system forward and they need to start paying these dealers," said Mark Schienberg, the group's president. "This is a cash-dependent business."
The program offers up to $4,500 to shoppers who trade in vehicles getting 18 mpg or less for a more fuel-efficient car or truck. Dealers pay the rebates out of pocket, then must wait to be reimbursed by the government. But administrative snags and heavy paperwork have created a backlog of unpaid claims.
Schienberg said the group's dealers have been repaid for only about 2 percent of the clunkers deals they've made so far.
Many dealers have said they are worried they won't get repaid at all, while others have waited so long to get reimbursed they don't have the cash to fund any more rebates, Schienberg said.
"The program is a great program in the sense that it's creating a lot of floor traffic that a lot of dealers haven't seen in a long time," he said.
"But it's in the hands of this enormous bureaucracy and regulatory agency," he added. "If they don't get out of their own way, this program is going to be a huge failure."
The program is administered by the Department of Transportation. Transportation Secretary Ray LaHood said Wednesday that dealers will be repaid for the clunkers deals they have completed.
"I know dealers are frustrated. They're going to get their money," LaHood told reporters. He said the Obama administration would soon announce how much longer the $3 billion car incentive program will last.
Earlier Wednesday, AutoNation CEO Michael J. Jackson told CNBC in a live interview that the government owes his company about $45 million in rebates from the program, but that he still has faith in it.
"The program is succeeding on every level, except for this administrative log jam that we have at the moment, which I am very confident we will get get fixed," Jackson said.
Through early Wednesday, auto dealers have made clunkers deals worth $1.81 billion, resulting in 435,102 new car sales, according to the DOT.
CNBC Slideshow: Most Popular 'Clunker' Trade-Ins—and Purchases
—CNBC staff contributed to this report


text:
MMJ4mil
Loge 25
we have the worst sports radio people ever.
Scott always brought up that he was Jewish, i could care less about that and his man crush on drew brees.
Dan Patrick is a east coast biased chump who thinks he is a god
the guys on in the afternoon sharod and the giants fan, who are not even from san diego, i hate even more.
I love Hank Bauer.
the rest can die in a fire.
Future Moderator. Sign Me.
LLKoolKyle
Any sports talk show that has "The Bachelor" and "MC Hammer" as guests raises serious questions
Surprising how many posters are forsaking common sense for political correctness in the realm of entertainment. Especially since I see many of you quoting films like Blazing Saddles. I guess it takes all kinds....
FWIW Scott and BR did alot of charitable stuff and were pretty good for the community. They were also the only listenable show on 1090 in my opinion.
They can point to the incident where he made fun of that lady from the MTN. Network, because it's something tangible they can really point to as justification for his firing.
But just as bad, and perhaps more damning in his bosses' eyes, was the incident he had back in 2001, with some lady in a parking lot.
Kaplan previously was sued by a woman he called a "skank" on the air when he worked for XTRA Sports 690 in 2001. The woman sued him and the station's operator, Clear Channel Broadcasting, for slander, libel and invasion of privacy in 2003. The case was settled confidentially in 2004.
In that case, the woman had Kaplan's car towed because it was improperly parked. According to the suit, Kaplan approached her and said, "Do you know who I am? You've ruined my day, and I have 80,000 watts over which I can broadcast your name."
He then went on the air, said the woman's name and called her a skank, saying "I saw what she was wearing to work."
Yeah, that's pretty bad. I'm surprised he stuck around for so long, actually.
Karl Hungus
J. Norbert Klopp
What's so PC about not calling someone the things Kaplan called that woman? It's just being a decent god damned human being.
Just a bit of a difference between using funny lines from a movie in jest and maliciously humiliating someone on the air.
I guess when you paint it as black and white/cut and dry as this it makes sense.
I must say I think you're smarter than that.
Waterston Fan
Poor BR, he's now out of a job.
I'll respond by quoting the great Chris Rock: "What people have to ask is this: What if the person that he called a f*gg*t, was actually acting like a f*gg*t?"
Point being, I've seen posters from this thread crucifying others in previous threads for jumping to conclusions about character issues without knowing the full story/details. My advice is for them to take their own advice.
Originally posted by Karl Hungus View Post
It's just being a decent god damned human being.
And yet here you are posting in/and supporting the UT forums where people treat each other like sh*t on a daily basis. And you're going to preach decency? Have you been a decent human being for the entirety of your life?
Maybe you should take a look in the mirror before climbing onto that soapbox.
booman55
Just SayOW!
I think you're missing the real issue here. It's the fact that he's a man that's talking smack about a woman. That's not real classy.
If he was talking about another guy this situation gets resolved in a totally different manner.
Go Bolts!
The problem with the world is the intelligent people are full of doubts while the stupid ones are full of confidence.
I'll buy this argument much more than the previous.
I'm not as smart as I look ... or I should say I'm not as dumb as I look ...
Big Slimm
entitled to things
i don't understand the association between blazing saddles and scott kaplan.
So i listened this morning to see if i could get any news...not one word from the coach John...and his side kick...following the company line..wish someone had some juevos down there to tell it like it is or speak there mind on it.
Coach talked about the Aztec and as usual the Padres i think..sounded like a high school news show..jezus god. Boring.
Went to the website...every reference and photo removed! No information anywhere...just sad..management are always such cowards. Really bugs me..i need some closure.
So my proposal...BR and Vincie Glen...I think that would be tolerable to the company robots they have filling in now.
That station has about as much color as the old Friends TV show...I will say it..they need a black guy...and Vince is great. Tells it like it is..ooopps..I guess I just stated the reason it won't happen...
And another thing...all you guys posting and complaining that you don't like the guy...hey...CHANGE THE STATION...much preferable to forcing your world view on every one else. sasquatch scum-buzzards!.
Connie Madagain
Go to her facebook page and "like" her for taking out the garbage ...
https://www.facebook.com/pages/Andre...520523?sk=info
I am disappointed that Billy Ray Smith was let go too. Did not hear the rant, but I cannot imagine that BR piled on. He should have been retained.
Great suggestion about having Vencie Glenn and Billy Ray. I would add Lo Neal into the mix too. Dave and Jeff are dull and boring.
For all of Kaplan's stupid remarks, they put on a show with the best guests. When the Chargers made playoff runs, they had some real great Friday morning tail gate parties for all Charger fans and great friends. Kaplan alienated alot of people at Chargers Park with his negative comments about Turner and Smith.
Personally, I think Smith is real happy about this - do not be surprised if Smith is one the frequent guests on the new morning show now.
Vincie Glenn won't ever let anyone else talk so he isn't a good fit for radio.
BR will be fine, he played 9 years in the NFL and has worked for many years as a sportscaster and talk show host, and his wife has been a prominent news anchor for 20+ years. So I'm sure they are well off financially.


It is a vision with antonyms aplenty.
"High density" becomes high drama.
Even the developer's public relations firm—Love Communications—produces glitzy images that some loudly proclaim propaganda.
On March 13–14, residents of Herriman and South Jordan, respectively, had the opportunity to preview developer Doug Young's vision for Olympia Hills II.
Input from the meetings will be collected, considered and presented to Salt Lake County officials for next-step consideration in the developer's request for zoning changes to accommodate the project.
As Young sees it, Olympia Hills II would be a "live-work-play-shop modern community," anchored by a huge high-tech employer offering high-paying STEM (science, technology, engineering and math) careers. Instead of the original proposed density of nine units per acre, the Olympia Hills II number has slightly modified to 6.8.
The development would be buoyed by an unprecedented network of regional parks and trails, as well as a children's hospital and a Utah State Extension campus, all of which would reimagine around 900 acres of unincorporated Salt Lake County, running along the Bacchus Highway, or State Route 111.
"The concepts, on the surface, are worth exploring. They have a potential upside," observed Wasatch Front Regional Council (WFRC) Deputy Director and President of the Utah Chapter of the American Planning Association Ted Knowlton.
Olympia Hills II is a chiseled version of this past summer's highly contested, high-density Olympia Hills development plan for land located approximately from 6300–8500 West and 12400–13100 South.
The original proposal was broadly booed by Herriman residents who assembled a change.org petition with more than 16,000 signatures in opposition. In an action serving as the catalyst for the newly emerging Southwest Quadrant Mayors Council, mayors of Copperton Township, Herriman, Riverton and West Jordan banded together to dissuade the imposition of what they see as an infrastructure nightmare.
The tag-team pressure led then-Salt Lake County Mayor Ben McAdams to veto the Salt Lake County Council's near-unanimous, 7-1 support of the project, which would have sought approval to alter land use from an A-2 Agricultural Zone to a P-C or Planned Community Zone.
After going back to the drawing board to reimagine Olympia Hills, the developer is now, per the request of Salt Lake County, hosting public open houses for comment, prior to making a formal application for a rebooted project.
It is a project forecast with what the developer calls "patient money," meaning that there is time to await approvals and funding to wait out the securing of anchor tenants.
Olympia Hills II is a re-spliced project looking to gain traction necessary to begin what developer Young says is ultimately a 30- to 40-year process.
The developer would look to transform the unincorporated area to a bustling, mixed-use, high-tech community, a modern-day corporate town beholden to a tech behemoth such as Amazon, Facebook or Google. Young traced Utah's history with mining towns as evidence of communities historically growing around work. The demise of "big-box" retail and other disruptive changes in business, he observed, will reinvent the way communities operate.
To visually depict today's high-tech town concept, the developer even included pictures of Facebook founder and CEO Mark Zuckerberg and Facebook's "Willow Campus" corporate town. There is no affiliation of any sort with Zuckerberg or Facebook. The project's far-west location and lack of breezy transportation with I-15 make it a seeming non sequitur with its goal of building synergy with Lehi's Silicon Slopes high-tech community.
City Journals reporters attended both open houses March 13–14 at Herriman's Bastian Elementary and South Jordan's Golden Fields Elementary—listening to and interviewing multiple residents of both Herriman and South Jordan. At press time, a tally of citizen comments was unavailable – in terms of either content or quantity.
Critiques of Olympia Hills II's creating a "commuter community" sting in the present sense, being a spot-on critique of existing community Herriman. The city has had the dubious distinction of having the state's lowest jobs-to-housing ratio, rendering it a sprawling bedroom community without economic development to support it, requiring commuters to drive elsewhere to work opportunities.
In some cases, resident concerns morphed to conspiracies, with elected officials and others charging the developer with purposefully staging the open houses without proper public notification.
Numerous residents used the term "propaganda" to refer to visuals depicting aspects of Olympia Hills II.
Misinformed residents critiqued the developer for poor development projects in Herriman, which he legitimately had no part of.
Some residents came to the sessions anticipating a "town hall" format and felt ill-at-ease navigating a room full of posters on easels, visually depicting everything from storm-drain management to traffic patterns.
Multiple residents asked developer Young for "guarantees" — as to which tech company would become the anchor tenant, which children's hospital would co-anchor, what types of housing products would dominate the acreage and what the density distribution would look like.
"I tell my children that wanting something is not a plan," remarked Herriman City Councilman and Mayor Pro Tempore Jared Henderson, who also included the concept in a lengthy Facebook post which was widely distributed to residents across the Southwest Valley.
"Guarantees" are never givens in planning such a visionary community, according to Knowlton.
"We're not opposed to growth, but we want it done responsibly," said Herriman Resident Lisa Brown, who is part of the resident coalition who assembled the 16,000-signature opposition to the initial Olympia Hills project.
"I'm really sad," said Kristie Miller, a Herriman resident who attended the meeting in South Jordan. "A case of less information, more propaganda. It is disappointing to not see any impact reports or resources that are backing up claims.


Wired has just published an amazing article detailing a gory report on how Google and other unlisted major companies were hacked.
I just finished an audiobook called The Scarecrow via Audible and it was a good fiction.
But, this Wired article is so much more real and in some ways insane if you think about the silent under the radar attacks that's going on against corporations around the world.
I highly recommend you read the whole article at Wired. But this what I came away with after reading it.
Advanced Persistent Threat (APT) – A new form of attack that can lay dormant in a corporate network for months even a year before coming alive and avoid detection.
They use very hard to detect ways of sending data home – gather data in a staging server, slice the data into small rare packets, sometimes even using customized packers, packets with spoofed headers or even use the SSL port with a custom protocol.
After reading this article, I came away with a sobering feeling of the always connected to the Internet we live in now.
Google came out and openly said that they were hacked but many of the major corporations didn't.
I rarely wear a tin foil hat but sometimes stuff like this makes you wonder.
It certainly makes us wonder about safety of our information on the Internet.


I think there is something to settings that makes you write. It's not enough to write, you should go where the muse calls you. Maybe VS Naipaul would not have been able to compile his award-winning novels if he was told to sit in the middle of MG Road or Sarjapur Road, right near the Silk Board Junction and write! So, while I can look out at the sea, I can write. But push me to the end of a working day and ask your mind to settle a while, allow the words to flow, and it simply does not. One of my friends, Karen, was telling me in a chat message how she needs to write down all her travel memories, so that she can indeed look back and see that she has led a remarkable life. And how true is that. We all lead such remarkable lives. It's hidden away within the junkyard of moments we fill our lives with. But there is no such life as a life ordinarily lived. What stories we make of our lives!
And what memories we build. While I was waiting to board the bus in Kempegowda Bus Station in Bangalore on Friday night, I was reminded of one journey nearly five years ago now, perhaps. Karen was there with her husband, Dave. Along with two other Indian friends, Birdy and Mahesh, we were going to take the bus to Banavasi. It was the beginning of a very long weekend. We had dinner in Koramangala and then took separate rickshaws to reach the bus station in the heart of the city. Or rather, Karen, Mahesh, and I reached. Birdy and Dave didn't. Traffic was piled up on all sides leading to the bus station. There were throngs of people it seemed headed just about to anywhere. The bus we were taking was the state road transportation bus. It wasn't meant for comfort. It was meant to help you reach your destination. Rickety seats. Open air windows. But it was already packed. And much to our chagrin, the bus was going to leave on time. We jumped on to the bus, appealing to the driver and the conductor, telling him to wait for our friends to catch up. In vain. He was going to leave. He had to be on time. I shook my head in disbelief. Late? It was just a minute past 8PM! The bus starts to pull away.
I frantically message Birdy and if SMSes could scream, it was a scream. She screams back, saying that they left the rickshaw because it wasn't moving in the traffic and are now walking their way to the bus. Running their way. Karen and I look at each other, the same thought running through our heads. Should we wait for them? Should we jump off the bus? Mahesh is hanging on the foot board, looking for one white head and one dark head to emerge from the thronging masses. We didn't want to take a decision. We want the decision to be forced on us. Ah, much like life. We wait. I call Birdy and I am shouting. Passengers are staring. Almost teasingly, the bus moves out. Slowly. Excruciatingly. But it's moving. But the traffic saves us. Just as it also pushes us to the limit. The bus just crawls along behind what seems like hundreds of other buses, all headed in 4 different directions, it looks like. And then, Mahesh yells. "They are here." On cue, they arrive. Breathless. Clambering on to the bus. We smile. Dave says 'hah.' Just like that the 'hah' becomes a memory. I would not know then that this would be a memory. But that's the thing about memories. They never tell you. They sneak on to you and weave something special out of that moment. A memory is that moment you realize what constitutes the memorable in your life. Now, each time I visit the central bus station, I think of that one night. The tension and the stress dissolving into one magical pause when you know everything is going to be all right. I feel at the end of my life that's what I am going to think. All this tension and stress and hullabaloo. But in the end, it was just all right. What memories we weave. What memories.


Play for the youngest pupils about a pan and a pancake. The storyteller came in and found a box and began to play with all the things in the box. As the pancake didn't want to be eaten, jumped out of the pan and ran away!
Play based on the myths of King Midas and Medusa.
Play based on Edgar Allan Poe's poems.
Play based on the book The Canterbury Tales by the English writer Geoffrey Chaucer. A group of pilgrims meet in the Tabard Inn and entertain each other by telling stories on their pilgrimage.
The three stories chosen are The Miller's Tale, The Wife of Bath's Tale and The Pardoner's Tale.


This entry was posted on Friday, July 8th, 2011 at 23:43	and is filed under Nøbel, Tijdstrijd. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.
Wat was het een succesvol tijdritje voor ons allen :)! Gefeliciteerd. Op naar het CK!


text:
namespace ui {

namespace test {
class InputHandlerProxyTest;
}

class InputHandlerProxyClient;
class InputScrollElasticityController;
class SynchronousInputHandler;
class SynchronousInputHandlerProxy;

// This class is a proxy between the blink web input events for a WebWidget and
// the compositor's input handling logic. InputHandlerProxy instances live
// entirely on the compositor thread. Each InputHandler instance handles input
// events intended for a specific WebWidget.
class InputHandlerProxy
    : public cc::InputHandlerClient,
      public SynchronousInputHandlerProxy,
      public NON_EXPORTED_BASE(blink::WebGestureCurveTarget) {
 public:

  InputHandlerProxy(cc::InputHandler* input_handler,
                    InputHandlerProxyClient* client);
  ~InputHandlerProxy() override;

  InputScrollElasticityController* scroll_elasticity_controller() {
    return scroll_elasticity_controller_.get();
  }

  void set_smooth_scroll_enabled(bool value) { smooth_scroll_enabled_ = value; }

  enum EventDisposition {
    DID_HANDLE,
    DID_NOT_HANDLE,
    DROP_EVENT
  };
  EventDisposition HandleInputEventWithLatencyInfo(
      const blink::WebInputEvent& event,
      ui::LatencyInfo* latency_info);
  EventDisposition HandleInputEvent(const blink::WebInputEvent& event);

  // cc::InputHandlerClient implementation.
  void WillShutdown() override;
  void Animate(base::TimeTicks time) override;
  void MainThreadHasStoppedFlinging() override;
  void ReconcileElasticOverscrollAndRootScroll() override;
  void UpdateRootLayerStateForSynchronousInputHandler(
      const gfx::ScrollOffset& total_scroll_offset,
      const gfx::ScrollOffset& max_scroll_offset,
      const gfx::SizeF& scrollable_size,
      float page_scale_factor,
      float min_page_scale_factor,
      float max_page_scale_factor) override;

  // SynchronousInputHandlerProxy implementation.
  void SetOnlySynchronouslyAnimateRootFlings(
      SynchronousInputHandler* synchronous_input_handler) override;
  void SynchronouslyAnimate(base::TimeTicks time) override;
  void SynchronouslySetRootScrollOffset(
      const gfx::ScrollOffset& root_offset) override;

  // blink::WebGestureCurveTarget implementation.
  bool scrollBy(const blink::WebFloatSize& offset,
                const blink::WebFloatSize& velocity) override;

  bool gesture_scroll_on_impl_thread_for_testing() const {
    return gesture_scroll_on_impl_thread_;
  }

 private:
  friend class test::InputHandlerProxyTest;

  // Helper functions for handling more complicated input events.
  EventDisposition HandleMouseWheel(
      const blink::WebMouseWheelEvent& event);
  EventDisposition HandleGestureScrollBegin(
      const blink::WebGestureEvent& event);
  EventDisposition HandleGestureScrollUpdate(
      const blink::WebGestureEvent& event);
  EventDisposition HandleGestureScrollEnd(
      const blink::WebGestureEvent& event);
  EventDisposition HandleGestureFlingStart(
      const blink::WebGestureEvent& event);
  EventDisposition HandleTouchStart(
      const blink::WebTouchEvent& event);

  // Returns true if the event should be suppressed due to to an active,
  // boost-enabled fling, in which case further processing should cease.
  bool FilterInputEventForFlingBoosting(const blink::WebInputEvent& event);

  // Schedule a time in the future after which a boost-enabled fling will
  // terminate without further momentum from the user (see |Animate()|).
  void ExtendBoostedFlingTimeout(const blink::WebGestureEvent& event);

  // Returns true if we scrolled by the increment.
  bool TouchpadFlingScroll(const blink::WebFloatSize& increment);

  // Returns true if we actually had an active fling to cancel, also notifying
  // the client that the fling has ended. Note that if a boosted fling is active
  // and suppressing an active scroll sequence, a synthetic GestureScrollBegin
  // will be injected to resume scrolling.
  bool CancelCurrentFling();

  // Returns true if we actually had an active fling to cancel.
  bool CancelCurrentFlingWithoutNotifyingClient();

  // Request a frame of animation from the InputHandler or
  // SynchronousInputHandler. They can provide that by calling Animate().
  void RequestAnimation();

  // Used to send overscroll messages to the browser.
  void HandleOverscroll(
      const gfx::Point& causal_event_viewport_point,
      const cc::InputHandlerScrollResult& scroll_result);

  scoped_ptr<blink::WebGestureCurve> fling_curve_;
  // Parameters for the active fling animation, stored in case we need to
  // transfer it out later.
  blink::WebActiveWheelFlingParameters fling_parameters_;

  InputHandlerProxyClient* client_;
  cc::InputHandler* input_handler_;

  // Time at which an active fling should expire due to a deferred cancellation
  // event. A call to |Animate()| after this time will end the fling.
  double deferred_fling_cancel_time_seconds_;

  // The last event that extended the lifetime of the boosted fling. If the
  // event was a scroll gesture, a GestureScrollBegin will be inserted if the
  // fling terminates (via |CancelCurrentFling()|).
  blink::WebGestureEvent last_fling_boost_event_;

  // When present, Animates are not requested to the InputHandler, but to this
  // SynchronousInputHandler instead. And all Animate() calls are expected to
  // happen via the SynchronouslyAnimate() call instead of coming directly from
  // the InputHandler.
  SynchronousInputHandler* synchronous_input_handler_;
  bool allow_root_animate_;

#ifndef NDEBUG
  bool expect_scroll_update_end_;
#endif
  bool gesture_scroll_on_impl_thread_;
  bool gesture_pinch_on_impl_thread_;
  // This is always false when there are no flings on the main thread, but
  // conservative in the sense that we might not be actually flinging when it is
  // true.
  bool fling_may_be_active_on_main_thread_;
  // The axes on which the current fling is allowed to scroll.  If a given fling
  // has overscrolled on a particular axis, further fling scrolls on that axis
  // will be disabled.
  bool disallow_horizontal_fling_scroll_;
  bool disallow_vertical_fling_scroll_;

  // Whether an active fling has seen an |Animate()| call. This is useful for
  // determining if the fling start time should be re-initialized.
  bool has_fling_animation_started_;

  // Non-zero only within the scope of |scrollBy|.
  gfx::Vector2dF current_fling_velocity_;

  // Used to animate rubber-band over-scroll effect on Mac.
  scoped_ptr<InputScrollElasticityController> scroll_elasticity_controller_;

  bool smooth_scroll_enabled_;

  bool uma_latency_reporting_enabled_;

  base::TimeTicks last_fling_animate_time_;

  DISALLOW_COPY_AND_ASSIGN(InputHandlerProxy);
};

}  // namespace ui

#endif  // UI_EVENTS_BLINK_INPUT_HANDLER_PROXY_H_

redpajama_set_name: RedPajamaGithub


This was one of my earliest purchases, (an auction in 1975), and the cheapest ($1). It was in use every day for quite a while until the last year when the filters started to go bad. It's in need of a complete overhaul now, the switches are noisy and the hum is unbearable.


Temple Beth El | The Puget Sound Photo Booth Co.
Thank you to everyone at Temple Beth El for hosting our photo booth at their Ner Tamid dinner and recognition in Tacoma tonight. It was an awesome two hours snapping your photos; you all look great! It was a ton of fun!
Enjoy your online gallery; both the photos and 4×6 prints have been uploaded there!


The Cheesecakes are multiple award-winners who have dazzled and delighted audiences in Las Vegas, New York, New Orleans, San Francisco, Seattle, Helsinki, Paris, Stockholm, Rome, and Berlin, as well as all across Canada!
With influences from cult classics like Priscilla Queen of the Desert to Broadway favourites like Guys and Dolls, to imaginative roller coasters like their original Cheesecakes in Space, these girls know how to put on a modern day show-stopper!
The Cheesecakes are known for their high-energy acts, standout performers, and comedic timing.
This evening is open to both CVWBN members and non-members alike and would be enjoyed by all genders.
Get your tickets online, HERE or in person at the Sid Williams Theatre Box Office.
Proceeds will go to this year's B.O.O.S.T. recipient:Soroptomist International of Courtenay. Thank you to the sponsors of this amazing event: Old House Hotel & Spa and proud Soroptimist and CVWBN member Home SOULutions Remediation.


text:
Sundre Airport  is located  southwest of Sundre, Alberta, Canada.

See also
Sundre/Goodwins Farm Airport

References

External links
Place to Fly on COPA's Places to Fly airport directory

Registered aerodromes in Alberta
Mountain View County


text:
A human chain demands transparency in the deployment of 5G in Segovia
5G, EHS, EMF, EMFIS, Environment, Spain
International experts at a scientific conference held in the city warn about the risks of exposure to electromagnetic fields for people and the environment.
By GONZALO AYUSO HIJOSA – 16th June 2018
The participants in the human chain passed through the arches of the Aqueduct in a protest act that ended in the Plaza Mayor. / KAMARERO
A human chain formed by dozens of people carrying posters and a scarf of 300 meters of virgin wool dyed with natural dyes, yesterday in Segovia requested transparency in the implementation process of 5G in the city, which has been chosen by Telefónica, next to Talavera de la Reina, to pioneer services with this new communications technology.
The participants started in the Plaza de Día Sanz, next to the Aqueduct, and they went in and out through the arches of the monument, demanding clarity from both Telefónica and the City Council in the deployment of the 5G. Then they marched to the Plaza Mayor where the protesters deposited shoes as a symbol of all those who are suffering due to exposure to electromagnetic fields and who have not been able to participate in this act of protest.
In fact, sources of the organization explained that, in the events organized by the Platform Stop 5G in Segovia only around 170 people attended, two thirds could not participate in the human chain when traveling the center of the city due to exposure from electromagnetic waves.
The scarf used in the demonstration has been woven in different places by groups of women in workshops led by the craftswoman Fátima Carrasco. With this garment the platform wants to symbolize that it is not against new technologies but it is committed to a secure technology such as cable.
The virgin wool dyed with natural dyes is a call of attention to the need to return to a model of development in contact with nature, based on the organic, respect for life, what is clean, healthy, healthy.
In addition, the fact that it has been woven by women highlights that precisely the diseases of central sensitization, among which are electrohypersensitivity and multiple chemical sensitivity, affect mainly women (between 70% and 90% of the total of affected).
Scientific day/Day of Science
During the morning, the auditorium of the Vicerrector Santiago Hidalgo de la UVa building was the scene of a series of presentations by international scientists who agreed on the effects on health, and also on the natural environment, of electromagnetic waves.
In this sense, Ceferino Maestu, from the Center for Biomedical Technology of the Polytechnic University of Madrid, explained that while legislation emphasizes thermal effects there is evidence of biological effects related to diseases.
On the implementation of 5G it was reported that an antenna will be installed for every ten blocks of housing and legislation protects companies in terms of the disclosure of their location. On the other hand, until its generalization it will coexist with other systems such as 2G, 3G, 4G and WiFi.
Among the main conclusions: EU legislation allows limits of up to 450 microwatts per square centimeter when the scientific recommendation and resolution 1815 of the Council of Europe is 0.1 microwatts.
This expert said that there are studies that indicate that this new technology is approaching levels with thermal effects that generate pathologies of central sensitization: fibromyalgia, chronic fatigue syndrome, electrosensitivity and are even related to brain tumors or leukemia, a risk also indicated by Annie J. Sasco, an expert from international cancer research organizations and David Carpenter, director of a health institute in Albany (USA).
White areas/zones
Several of the speakers expressed the need to demand the establishment of white areas in the city; for example, schools, public squares, libraries, etc., but the EU is opposed because it clashes with its policy of universal access to the internet, which it co-finances.
This article was translated from Spanish by EMFSA. Original article below.
Una cadena humana reclama transparencia en el despliegue del 5G en Segovia
Human chain across Segovia, Spain to Stop 5G


Chappaqua is a "hamlet" that is part of the town of New Castle, which dates to the year 1791 when it split from the neighboring city of North Castle. The entire community, which also includes the hamlet of Millwood, has a population of approximately 16,500 residents and is located in Westchester County in the beautiful Hudson Valley region of the state. Chappaqua is primarily a residential, family-oriented community that contains a lot of open space and gives the feeling of living in the country. It is home to the Horace Greeley House, which contains the New Castle Historical Society with period furnishings, a period garden, gift shop and rotating exhibits on the local history. The Hudson River Valley is full of historical landmarks, legends and lore. You'll find luxurious accommodations, fine restaurants, and breathtaking scenery and picnic spots along the Hudson River, entertaining attractions and antique shopping. The Hudson Valley is also home to the "Legend of Sleepy Hollow," the historic Kykuit Rockefeller Estate, Washington Irving's Sunnyside and Philipsburg Manor, which is an 18th century farm and mill. The Rockefeller State Park Preserve near Chappaqua offers a variety of habitats, including a lake, wetlands, woodlands and fields. The park is a great place for hiking, picnicking, horseback riding, cross-country skiing, birdwatching, fishing and photography.
The closest airports in the area are the La Guardia airport (LGA) located about 26 miles south of Chappaqua in New York, New York, the Teterboro airport (TEB) located approximately 26 miles southwest of Chappaqua in Teterboro, New Jersey, the Stewart International airport (SWF) located roughly 29 miles northwest of Chappaqua in Newburgh, New York, the John F Kennedy International airport (JFK) located around 35 miles south of Chappaqua in New York, New York, and finally the Newark Liberty International airport (EWR) located about 38 miles southwest of Chappaqua in Newark, New Jersey.
Jeepers West Nyack NY 11.7 mi.
Playland Park Rye NY 13.0 mi.
Glen Island Park New Rochelle NY 17.1 mi.
Bayville Amusements Bayville NY 20.1 mi.
Adventureland Farmingdale NY 33.8 mi.
Astroland Brooklyn NY 36.3 mi.
Coney Island Boardwalk Brooklyn NY 36.3 mi.
Coney Island - Kenny Kaufman Brooklyn NY 36.3 mi.
Deno's Wonder Wheel Amusement Park Brooklyn NY 36.3 mi.
Nellie Bly Park Brooklyn NY 36.3 mi.
Quassy Amusement Park Middlebury CT 41.8 mi.
Boomers Family Fun Center Medford NY 46.3 mi.
Country Fair Entertainment Park Medford NY 46.3 mi.
Kid's Kingdom Medford NY 46.3 mi.
Bowcraft Amusement Park Scotch Plains NJ 47.7 mi.
Keansburg Amusement Park Keansburg NJ 53.1 mi.
Lake Compounce Bristol CT 55.2 mi.
Land Of Make Believe Hope NJ 65.0 mi.
Jenkinson's Boardwalk Point Pleasant Beach NJ 75.2 mi.
Splash Down Park Fishkill NY 27.0 mi.
Splish Splash Water Park Riverhead NY 59.9 mi.
Carousel Water & Fun Park Beach Lake PA 78.1 mi.
Zoom Flume Water Park Durham NY 88.3 mi.
Sesame Place Langhorne PA 91.1 mi.
Dorney Park & Whitewater Kingdom Allentown PA 97.8 mi.
Maple Breeze Park Pawcatuck CT 101.4 mi.
Water Wizz Westerly RI 101.8 mi.
Mountain Creek Vernon NJ 109.7 mi.
Thundering Surf Water Slide Beach Haven NJ 113.3 mi.
Water World Phoenixville PA 116.0 mi.
Yawgoo Valley Ski Area and Waterpark Exeter RI 119.1 mi.
Mohansic Golf Course Yorktown Heights NY 7.7 mi.
Sanctuary Country Club Yorktown Heights NY 7.7 mi.
Rockland Lake State Park Congers NY 8.3 mi.
Maple Moor Golf Course White Plains NY 8.9 mi.
Pound Ridge Golf Club Pound Ridge NY 10.6 mi.
Saxon Woods Golf Course Scarsdale NY 11.0 mi.
Shallow Creek Golf Course Shrub Oak NY 11.5 mi.
Rainbow Country Club Greenville NY 12.0 mi.
Broadacres Golf Club Orangeburg NY 12.6 mi.
Phillip J Rotella Municipal Golf Course Thiells NY 13.2 mi.
Rockleigh Golf Course Rockleigh NJ 13.9 mi.
E Gaynor Brennan Golf Course Stamford CT 14.4 mi.
Sterling Farms Golf Course Stamford CT 14.4 mi.
Chemung Golf Course Waverly NY 14.6 mi.
DJs Golf Center Par 3 Waverly NY 14.6 mi.
Shepard Hills Country Club Waverly NY 14.6 mi.
Country Club At Lake MacGregor Mahopac NY 14.7 mi.
Blue Hill Golf Course Pearl River NY 15.2 mi.
Pehquenakonck Country Club North Salem NY 15.6 mi.
Garrison Golf Club Garrison NY 16.2 mi.
Holland Hills Country Club Glenwood NY 16.4 mi.
Tamcrest Country Club Alpine NJ 16.8 mi.
Oak Hills Park Golf Course Norwalk CT 16.9 mi.
Dunwoodie Golf Course Yonkers NY 17.1 mi.
Sprain Lake Golf Course Yonkers NY 17.1 mi.
Bergen Hills Country Club River Vale NJ 17.3 mi.
Valley Brook Golf Club River Vale NJ 17.3 mi.
Highlands Country Club Garrison NY 17.6 mi.
Vails Grove Golf Course Brewster NY 17.9 mi.
Ridgefield Golf Course Ridgefield CT 18.1 mi.
Big Birch Patterson NY 25.9 mi.
Thunder Ridge Patterson NY 25.9 mi.
Mount Peter Warwick NY 31.6 mi.
Craigmeur Newfoundland NJ 35.7 mi.
Woodbury Woodbury CT 39.3 mi.
Mohawk Mountain Cornwall CT 52.4 mi.
Mount Southington Southington CT 55.1 mi.
Holiday Mountain Monticello NY 58.9 mi.
Shawnee Mountain Delaware PA 59.5 mi.
Catamount Hillsdale NY 71.6 mi.
Butternut Ski Area Great Barrington MA 74.6 mi.
Tanglewood Tafton PA 75.6 mi.
Alpine Mountain Analomink PA 76.1 mi.
Hunter Mountain Hunter NY 76.6 mi.
Belleayre Moutain Highmount NY 77.7 mi.
Otis Ridge Otis MA 79.5 mi.
Camelback Tannersville PA 80.6 mi.
Ski Windham Windham NY 83.3 mi.
Ski Plattekill Roxbury NY 88.0 mi.
Hook Mountain State Park NY 7.6 mi.
Rockland Lake State Park NY 8.3 mi.
Mohansic State Park NY 8.7 mi.
Blauvelt State Park NY 10.5 mi.
Mianus River State Park CT 11.1 mi.
High Tor State Park NY 11.4 mi.
Stony Point State Park NY 12.0 mi.
Tallman Mountain State Park NY 12.2 mi.
Palisades State Park NY 13.0 mi.
Bear Mountain State Park NY 14.8 mi.
Bear Mountain State Park NY 15.2 mi.
Palisades State Park NJ 16.5 mi.
Palisades Interstate Park NY 17.9 mi.
Seth Pierrepont State Park CT 18.1 mi.
Wooster Mountain State Park CT 20.3 mi.
Clarence Fahnestock Memorial State Park NY 20.3 mi.
Hudson Highlands State Park NY 21.9 mi.
Storm King State Park NY 22.4 mi.
Caumsett State Park NY 22.9 mi.
Putnam Memorial State Park CT 23.3 mi.
Bergen County Zoological Park Paramus NJ 21.9 mi.
Bronx Zoo/Wildlife Conservation Park Bronx NY 22.0 mi.
Queens Wildlife Center Flushing NY 27.3 mi.
Beardsley Zoological Gardens Bridgeport CT 29.1 mi.
Central Park Wildlife Center New York NY 33.2 mi.
New York Aquarium Brooklyn NY 36.3 mi.
Prospect Park Wildlife Center Brooklyn NY 36.3 mi.
Trevor Zoo Millbrook NY 43.4 mi.
Staten Island Zoo Staten Island NY 45.6 mi.
Mystic Aquarium Mystic CT 94.4 mi.
New Jersey State Aquarium at Camden Camden NJ 111.0 mi.
Philadelphia Zoological Garden Philadelphia PA 111.1 mi.


"The hair is short. The makeup-free face is pretty by some angles but also handsome by others. You notice the small breasts, of course, but also the broad, low-slung pelvis. And the movement this long, rangy instrument produces is flowing and gentle, yet strong.
To watch Sean Dorsey in the studio is to surrender your urge to categorize.
So Dorsey doesn't use mere language. The 33-year-old choreographer, who was born female but now prefers the pronoun "he," uses movement and story, and the combination speaks more poignantly than any label.
In "Second Kiss," a duet with Mair Culbreth, the dancers tumble over one another as Dorsey's voice-over tells of a fourth-grader's flirtations with the class' most popular girl. In "Six Hours," the same duo's dynamic grows testy and tense as Dorsey's tale describes the lovers' visit home.
Dorsey's first full evening of choreography runs Friday and Saturday at ODC Theater. Click here for full story.


Thank you for letting me be part of your creative projects! Show me pictures! I thank my Heavenly Father for the courage & provision to be true to my design, and pray that if you have not already, you will discover the beauty & wonder of yours!


This is the letter every missionary dreads writing.
Me: I am really stressed about money. We have had so many unexpected expenses this month and I do not know what we are going to do.
Her: That really surprises me, you always make everything sound like it is going so well.
Me: I mean, things are going well. Really well. The ministry is growing. We are healthy and happy. We still believe we are in the right place at the right time. The girls are doing well. Everything is good. It is just, money.
Her: Well, I think people would be supportive if you let them know.
Me: *Whining* But it is just so hard to ask for money.
Her: People want to help. They cannot live there, so they want to support the work and workers they believe in.
It is true. I frequently emphasize the things that are going well. In most blogs I want you to know how much we are doing and how well it is going. This is mostly because I want you to see value in our project and to increase the excitement about what is happening in our small corner of the world. It is also true that I do not often say when we need help. This part of being a missionary living on the generosity of others is H.A.R.D. It is humbling in a good way that increases your faith in both God and the community of believers that He has called to do His work. It is also humbling in a way that makes you look at the ground, shuffle your feet, and impulsively give a list of all the worthy things you have done this week. I am extremely grateful that we have not had to raise personal support in the four years that we have been here. Our family and friends have been INCREDIBLY generous and consistent in their encouragement and financial support. We know they believe in us and in the work we are doing. In a way, that makes it harder, because here I am, asking for more.
So I am going to pad 'the ask' with an exciting announcement.
That's right, we are coming back and we need your help to get there. We need to raise $6000 for our trip back. This will cover our travel cost both to and from the States, and also while we are there. America is expensive!! We are going to be doing a lot of traveling to speak with different churches and groups and all of that travel expense adds up. Would you consider helping us in this way?
We are also praying for a few more people to join on as monthly supporters. Our cost of living has gone up recently. Tanzania is not immune to inflation. We are hoping to raise $400 more in monthly support to cover our basic needs. If this is an area you feel like you could support us, we would be incredibly grateful. We might even bring you a cool gift from Tanzania when we see you in the Fall. 🙂 All donations are tax deductible. All of our personal funds are processed through our sending church, The Vine, in Temple, Texas.
Step 2: Enter in your recurring payment information selecting Missions: Administration as your "Giving Type". It is VERY important that you select Missions: Administration in order for your donation to get to our ministry. You can select to use either a credit/debit card or set up bank account withdrawals. Your payment will be deducted as you select.
On your checks 'Memo Line' please write: Missions Administration. Again, it is VERY important to indicate Missions Administration so that your donation goes to the correct ministry.
We cannot thank you enough for choosing to support our work through financial donations. This is a very real way for you to be involved in the efforts made in Arusha, Tanzania. You are a blessing to our family and we look forward working with you.
I will leave you with a fun video of singing at the Market Center.


There are a number of different types of Diabetes (or Diabetes mellitus as it is sometimes called). The most common form is Type 2 Diabetes – of the total number of people with Diabetes, approximately 90% have Type 2.
Type 2 Diabetes tends to be diagnosed in older people − with those between the ages of 60 and 79 being most affected – and is typically associated with an unbalanced diet, being overweight and a lack of exercise.
Type 1 Diabetes, on the other hand, is an auto-immune disease. The body's immune system destroys the insulin-producing cells so that the body itself is no longer able to keep the blood glucose levels constant.
Controlling the blood glucose levels is routine for most people with Diabetes.
30 to 70% of all diabetic patients experience changes to their skin as a result of the disease.2 The symptoms are many and varied: about 40% of patients suffer from dry skin3 some of whom also experience severe itching. Scaly skin, an increased susceptibility to infections and wounds that don't heal easily are frequently caused by Diabetes.
One of the reasons for this is that, in patients with Diabetes, the body is no longer able to effectively regulate the blood glucose levels. A high blood sugar count damages blood vessels and nerves in the long term and has numerous effects on the various organs of the body – including the skin.
Diabetics can experience dry, cracked skin – especially on their feet.
A lack of lipids and moisture-binding substances.
Urea and other NMFs attract and bind in moisture. Ceramide strengthens the natural skin barrier and reduces moisture loss.
Diabetes can cause damage to nerve fibres and blood vessels and, as a result, the skin's natural barrier function is compromised. Skin is less able to attract and retain the moisture it needs and so it dries out, becomes sensitive and the body's immune defense system is weakened.
Thorough and regular body and foot care, using products proven to be suitable for – and effective on – diabetic skin is particularly important for diabetics.
Eucerin UreaRepair PLUS Lotion 10% Urea contains an active formula that instantly soothes skin and gives it the long-lasting moisturisation it needs.
Appropriate skin care with Urea improves the condition of diabetic skin.
Urea: a Natural Moisturising Factor (NMF) that occurs naturally in skin. It binds water in to the outermost layers of skin, thereby ensuring that the surface of skin remains smooth.
Ceramide: part of the skin's natural barrier, Ceramide prevents too much moisture from being lost due to evaporation. A healthy and strengthened skin barrier also defends against the irritants that can cause inflammation and itching.
Other NMFs: Lactate, Pyrrolidinecarboxylic Acid (PCA), Amino Acids, salts and Glucose. These substances also occur naturally in skin and bind water in to the outermost layers.
With the RepairPLUS complex, Eucerin UreaRepair PLUS Lotion 10% Urea works effectively in both the upper and lower layers of the epidermis relieving the symptoms of dry skin and strengthening the skin barrier.
Clinical and dermatological studies have proven the lotion's effectiveness with diabetic skin.
Eucerin UreaRepair PLUS Lotion 10% Urea is just one of the products in the Eucerin UreaRepair range proven to be effective with diabetic skin. The range also includes body creams, ointments and hand and foot creams.To find out more go to Eucerin UreaRepair PLUS range.
In order to demonstrate the efficacy of Eucerin UreaRepair PLUS Lotion 10% Urea, especially on diabetic skin, it was tested in a clinical study with 64 diabetic patients (Type 1 & 2) between the ages of 20 and 70 (the mean age was 56.7) years old. The sample suffered from dry to very dry skin and applied the lotion on their arms, legs and feet – twice daily and for two weeks.
The doctors and participating diabetics confirmed the effectiveness of the product.
Skin condition showed a significant improvement after two weeks of application - both in terms of dryness and flakiness.
After two weeks the diabetics themselves noticed a significant improvement in skin condition. Dryness, feelings of tightness, tingling, itchiness and burning significantly decreased. And, as a result of the l improvement in skin condition the sample said they would recommend the product to others. Most of the sample were positive about the experience of using the lotion.
Eucerin UreaRepair PLUS Lotion 10% Urea is scientifically proven to be effective in treating diabetic skin.


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