text:
\section{CONCLUSION}

This paper presents a novel Feature Aggregation block that is used for anticipation of road accidents. The FA block refines each object's features by using the appearance relation between different objects in a given frame. We showed that using FA block along with an LSTM provides us with the complementary information related to both spatial and temporal domain of a video sequence. The quantitative and qualitative results on the challenging Street Accident (SA) dataset show that our method outperforms the state-of-the art methods in anticipating accidents earlier. As future work, we plan to incorporate other relation information between objects in a scene for accident anticipation.
\section{EXPERIMENTS}
We first describe the details of Street Accident (SA) \cite{chan2016anticipating-1} dataset that is used in the experiment. Then, we explain the implementation details and the evaluation metrics. Finally, we show that our method anticipates accidents earlier than state-of-the-art approaches on the SA dataset.
\subsection{Dataset}
The Street Accident (SA) \cite{chan2016anticipating-1} dataset contains videos captured across six cities in Taiwan. The videos have been recorded with a frame rate of 20 frames per second.  The frames extracted from these videos have a spatial resolution of 1280 x 720. Each video is 5 seconds long containing 100 frames where the accident videos contain an accident at the last 10 frames. Street Accident is a complex dataset captured with different lighting conditions and involves a wide variety of accidents. The SA dataset contains 620 positive videos (with an accident) and 1130 negative videos (without an accident). Following the experimental procedure in \cite{chan2016anticipating-1}, we use 1266 videos (455 positive and 829 negative) for training and 467 videos ( 165 positive and 301 negative)  at test time.

\subsection{Implementation Details}
We implemented our method in Tensorflow and performed experiments on a system with a single Nvidia Geforce 1080 GPU having 8GB of memory. We used the appearance features provided by \cite{chan2016anticipating-1} for SA dataset. The objects were extracted using Faster-RCNN \cite{ren2015faster}. VGG-16 \cite{zhang2015accelerating} was used to extract features from full frames and objects present in a frame which were first resized to a frame resolution of 224 x 224. The features were extracted from $fc6$ layer of VGG having a dimension of 4096. These features were passed through a linear embedding to reduce their dimensionality to 256 before giving them as an input to our network. We used LSTM with a hidden state size of 512 and a dropout of 0.5.  Considering the training time and memory limit, we limited the number of objects in a frame to 9. The parameters of the network were initialized randomly with a normal distribution having mean of 0 and a standard deviation of 0.01. The model was trained with a learning rate of 0.0001 using Adam optimizer and a batch size of 10. Training was performed for 40 epochs on the SA dataset.
\subsection{Evaluation Metrics}
For evaluation, we use mean Average Precision (mAP) and Average Time-to-Accident (ATTA) as our evaluation metrics.

\subsubsection{Average Precision}
For every frame, our network returns a softmax probability value showing the risk of accidents in the future. If the value is above a threshold $\beta$ and the video is an accident video, it is considered as a True Positive (TP) prediction, and, in case of a value below than a threshold, a False Negative (FN). Similarly, for a non-accident video, if the probability value is below a threshold, it is considered as a True Negative (TN) prediction, and in case of a value above than a threshold, it is a False Positives (FP). These values are obtained for all the frames in all the video sequences. Precision ($P$) and Recall ($R$) are computed as follows

\begin{equation}
P = \dfrac{TP}{TP+FP} \quad \textrm{and} \quad R =\dfrac{TP}{TP+FN}.\\
\end{equation}
\begin{table}[t]
    \vspace{5pt}
    \centering
    \renewcommand{\arraystretch}{1.3}
    \caption{Experimental results on SA dataset}
    \label{table:Comparison}
    \begin{tabular}{lcccc}
        \toprule
        Method  & mAP (\%) & ATTA (s) \\
        \midrule
        DSA \cite{chan2016anticipating-1} & 48.1  & 1.34 \\
        SP \cite{alahi2016social} & 47.3 & 1.66 \\
        L-R*CNN \cite{gkioxari2015contextual} & 37.4 & 3.13 \\
        L-RA \cite{zeng2017agent} & 49.1 & 3.04 \\
        L-RAI \cite{zeng2017agent} & 51.4 & 3.01 \\
        AdaLEA \cite{Suzuki_2018_CVPR} & 53.2 & 3.44 \\
        VGG + full frame feature  & 37.3  & 3.21 \\
        \midrule

        FA-1 & 47.7 & 3.29\\
        FA-2 & 48.6 & 3.21\\
        FA-3 & 47.2 & 3.23\\
        FA-4 & 41.3 & 3.56\\
        FA-final  & 49.8  & \textbf{3.76} \\

        \bottomrule
    \end{tabular}
    \vspace{-5pt}
\end{table}

\noindent After finding precision and recall at different values of threshold, we compute mean Average Precision. The general definition of mean Average Precision is area under the precision-recall curve.
\begin{equation}
    mAP = \int_{0}^{1} p(r) dr.
\end{equation}

\noindent where $p(r)$ is precision as a function of recall $r$.

\subsubsection{Average Time to Accident}
At every threshold $\beta$, we find the first value $\hat{t}$ in every positive video when the accident probability is above a threshold. If the accident starts at frame $\tau$, then $\tau$-$\hat{t}$ is Time-to-Accident (TTA). We average all TTAs for all the  positive videos to get a single TTA at a given threshold. After computing TTA at different thresholds, we average all TTAs to find Average Time-to-Accident (ATTA). A higher ATTA value means earlier anticipation of accidents.
\subsection{Quantitative Results}
\indent We first describe the following five variants of our FA block.
\subsubsection{FA-1}Fully connected layers with parameters $\mathbf{W}_{\theta}$ and $\mathbf{W}_{\phi}$ are removed from FA block.
\subsubsection{FA-2} Softmax function is replaced by multiplication with 1/$N$.
\subsubsection{FA-3} $Tanh$ activation function is replaced by ReLU.
\subsubsection{FA-4} Instead of using dot product similarity as relation fucntion, we use the relation network module proposed in \cite{santoro2017simple} to find attention weights. It is given as
\begin{equation}
    e_{t}^{ij} = ReLU(\mathbf{W}[\mathbf{A}^i;\mathbf{B}^j]+\mathbf{b}).
\end{equation}

where $;$ is a concatenation operation. $\mathbf{W}$ and $\mathbf{b}$ are learnable parameters of fully connected layer that project the concatenated vector to a scalar value.
\subsubsection{FA-final} This is our final network with fully connected layers $\mathbf{W}_{\theta}$ and $\mathbf{W}_{\phi}$, dot product similarity, softmax and $tanh$ activation function.\\\indent The quantitative results are given in Table~\ref{table:Comparison}. From the experimental results, it is seen that,
\begin{figure}[t]
     \centering
      \includegraphics[scale=0.32]{Figures/scatter_plot.pdf}
      \caption{Anticipation and accuracy comparison of different methods.}
      \label{fig:scatter_plot}
\end{figure}
our method outperforms numerous recent methods. L-RA and L-RAI are two variants of \cite{zeng2017agent} as stated in their work. It is interesting to note that our feature aggregation method performs better in predicting the accidents earlier than dynamic parameter prediction \cite{zeng2017agent} and adaptive loss based method \cite{Suzuki_2018_CVPR}, even though our mAP value is lower as compared to these methods. This is because our work primarily focuses on achieving a higher ATTA value for practical driving applications capable of predicting most of the accidents earlier, thus avoiding causalities. The adaptive loss strategy \cite{Suzuki_2018_CVPR} is aimed at early anticipation of accidents but we observe that our method anticipates accidents earlier than \cite{Suzuki_2018_CVPR} with a simple exponential cross entropy function. Results for \cite{chan2016anticipating-1}, \cite{alahi2016social} and \cite{gkioxari2015contextual} are taken from \cite{zeng2017agent} as the evaluation protocol is same. Fig.~\ref{fig:scatter_plot} shows the comparison between our method and different state-of-the art approaches. It can be seen that FA-final has the highest ATTA value with a reasonable mean average precision (mAP) that is comparable with other approaches.  \\
\indent Fig.~\ref{fig:figure_variants} shows Precision vs. Recall curves for different variants of FA block. The graph indicates that FA-final has the highest area under the curve whereas FA-4 gives the lowest. This shows that using dot product similarity in an embedding space as an appearance relation function gives better results than the concatenation operation \cite{santoro2017simple}. The other three variants have almost similar curves as FA-final with very little difference.
\subsection{Qualitative results}
We show qualitative results of accident anticipation in Fig.~\ref{fig:result_1_2}, ~\ref{fig:result_3} and~\ref{fig:result_4}. As seen from the results, it is evident that our method is able to differentiate between negative and positive videos. For a negative video, as seen in Fig.~\ref{fig:result_3}, the anticipation probability does not exceed the threshold indicating no accidents. Fig.~\ref{fig:result_4} shows a false alarm that was raised for a negative video. It can be attributed to the fact that objects were too close to each other in the video sequence.

\begin{figure*}
  \centering
  \begin{tabular}{@{}c@{}}
    \includegraphics[width=0.73\linewidth]{Figures/result1.jpg} \\[\abovecaptionskip]
  \end{tabular}

  \vspace{\floatsep}

  \begin{tabular}{@{}c@{}}
    \includegraphics[width=0.73\linewidth]{Figures/result2.jpg} \\[\abovecaptionskip]
  \end{tabular}

  \caption{Positive Examples. We keep the threshold at 0.8 for triggering accident anticipation. TTA is time to accident whereas the accident starts at 90$th$ frame.}\label{fig:result_1_2}
\end{figure*}

\begin{figure}[thbp]
     \centering
      \includegraphics[scale=0.32]{Figures/figure_variants.pdf}
      \caption{Precision vs. Recall curves for different variants of FA block.}
      \label{fig:figure_variants}
\end{figure}

\begin{figure*}[htb]
    \center
    \includegraphics[width=0.73\linewidth]{Figures/result3.jpg}
    \vspace{-2pt}
    \caption{
        A negative example. The network does not trigger accident anticipation because the probability value never exceeds the threshold.
    }
    \vspace{-10pt}
    \label{fig:result_3}
\end{figure*}

\begin{figure*}[htb]
    \center
    \includegraphics[width=0.73\linewidth]{Figures/result4.jpg}
    \vspace{-2pt}
    \caption{
         A false positive. The failure can be attributed to the fact that vehicles are too close to one another.
    }
    \vspace{-10pt}
    \label{fig:result_4}
\end{figure*}

\section{Introduction}
One of the biggest challenges faced by the autonomous vehicles is the accurate anticipation of accidents and taking necessary actions to avoid them. These accidents include vehicles colliding with one another, animals, pedestrians, and road signs. Accurate prediction of accidents ahead of time is imminent to avoid critical casualities.\\\indent Researchers have used computer vision and deep learning approaches to tackle the problem of accident detection \cite{herzig2019spatio} and anticipation \cite{zeng2017agent, chan2016anticipating-1, Suzuki_2018_CVPR}. The dataset includes videos from dashboard-mounted cameras fixed in vehicles. The normal samples comprise normal driving scenario whereas the abnormal samples comprise road accidents as seen from the camera. These videos capture the real-world traffic situation providing researchers with an efficient framework for evaluating their methods.\\\indent The task of anticipation and detection falls into two separate categories. Accident detection is related to action recognition where the network has a complete temporal context available at test time. Accident anticipation is a challenging task because it requires predicting a future event by making use of the limited temporal information as all practical systems are causal. The anticipation problem is evaluated by assessing how early the network predicts the event (in our case accident) ahead of time. Thus, accident anticipation should be tackled differently from detection/recognition problem.\\\indent Recognizing abnormal activity such as traffic accidents in a real life scenario poses a challenge for researchers because there exist a wide variety of vehicles that interact with one another to cause accidents. \begin{figure}[t]
     \centering
      \includegraphics[scale=0.18]{Figures/077.jpg}
      \caption{Dashcam footage showing an abnormal scenario}
      \label{figurelabel}
\end{figure} If a major portion of training data consists of accidents caused by only one kind of vehicle-to-vehicle interaction, the network might not generalize well on other kinds of accidents. For example, if the majority of accidents in the training data consist of cars colliding with motorbikes, the network will give poor performance for accidents caused by a car hitting another car. It is thus important to develop an anticipation neural network that models relationship between appearance features of different objects in a frame so that the network can generalize well on a wide variety of inter-object interactions.\\\indent Previous work \cite{chan2016anticipating-1} aims at anticipating accidents by giving attention to individual objects in a frame without taking into account their interactions with one another. In \cite{zeng2017agent}, the spatial and appearance-wise non-linear interaction between an agent and its environment is used to assess risk in the future.  In this work, we primarily aim at defining the relationship between appearance features of objects only that can be generally used.\\\indent We propose a novel method for accident anticipation that takes into account object-to-object interactions in a given frame of a video sequence. Our Feature Aggregation block strengthens every query object feature by adding a weighted sum of all other object features in a given video frame to the query object. The weighted sum represents global context specific to the query object whereas the attention weights are defined by appearance relationships between different objects in a single frame. Moreover, we use the sequence modelling power of Recurrent Neural Networks for accident anticipation. The refined object features along with the full frame features are input to a Long Short Term Memory (LSTM) network that returns an anticipation probability value corresponding to every frame. In this work, we focus on using the FA block for spatial domain only and use an LSTM to capture long-range temporal dependency between frames.\\\indent The rest of the paper is structured as follows. Research
related to our work is discussed in Section \rom{2}. In Section \rom{3}, we
describe the individual components of our method in detail. Implementation details and experimental results are given in Section \rom{4}. Finally, Section \rom{5} concludes the paper.
\section{ACCIDENT ANTICIPATION IN DASHCAM VIDEOS}
Accident Anticipation systems predict the occurrence of an accident as early as possible at testing. During training, the network is given a sequence of frames and labels defined as
\begin{equation}
(({\boldsymbol{\Omega}_1,{\boldsymbol{\Omega}_2},...,\boldsymbol{\Omega}_{S_{k}}}),y_{k}, \tau_{k})\quad  \text{for}\ k = 1,2,...,M.
\end{equation}
 Here, $\boldsymbol{\Omega}_i$ is the $i$-th frame in a video, $M$ is the total number of videos, $S_{k}$ denotes the number of frames in the $k$-th video, $y_{k}$ represents one-hot encoded video-level label indicating the presence of an accident, and $\tau_{k}$ is the frame index at which the accident started. For normal videos, $\tau$ is set to $\infty$. At test time, the network is given each frame one at a time to predict the occurrence of accidents as early as possible in the video sequence. Specifically, a network tries to anticipate an accident correctly at the $t$-th frame with $(\boldsymbol{\Omega}_1,\boldsymbol{\Omega}_2,...,\boldsymbol{\Omega}_t)$ such that $\tau$-$t$ is maximized. Note that in anticipation, unlike detection, partial observations till time $t<\tau$ are available to the network at test time.

We first describe the preliminaries of a recurrent neural network that is a constituent of our method. Afterwards, we describe our method in detail.
\subsection{Recurrent Neural Networks}
Recurrent Neural Networks are considered a powerful tool for sequence modelling. We use a Long-Short Term Memory network for accident anticipation in video sequences. LSTMs allow global aggregation of features over time
\begin{figure}[b]
     \centering
      \includegraphics[scale=0.5]{Figures/LSTM.jpg}
      \caption{An LSTM data flow}
      \label{fig: 2}
\end{figure}
by introducing memory into the system. In Fig.~\ref{fig: 2}, data flow of an LSTM is shown where $\mathbf{h}_{t}$ represents the hidden state generated at current time step $t$, $\mathbf{c}_{t}$ is the cell state that
\begin{figure}[t]
     \centering
      \includegraphics[width=8cm,height=7cm]{Figures/FA_Block.jpg}
      \caption{Our Feature Aggregation Block.}
      \label{fig: 3}
\end{figure}
captures long-range temporal dependency and $\mathbf{x}_{t}$ is the input to the LSTM. There are three different gates in an LSTM block: input gate $\mathbf{i}$, forget gate $\mathbf{f}$, and output gate $\mathbf{q}$. These gates filter the input in a way that the model learns useful information in the sequence by letting it pass through the LSTM and blocks the rest of the input using the forget gate. The data flow for LSTM is shown mathematically as
\begin{equation}
    \mathbf{i}_{t} = v_{1}(\mathbf{x}_{t}, \mathbf{h}_{t-1}) = \sigma(\mathbf{W}_{i}\mathbf{x}_{t} + \mathbf{U}_{i}\mathbf{h}_{t-1} + \mathbf{V}_{i}\mathbf{c}_{t-1} + \mathbf{b}_{i}),
\end{equation}
\begin{equation}
    \mathbf{f}_{t} = v_{2}(\mathbf{x}_{t}, \mathbf{h}_{t-1})= \sigma(\mathbf{W}_{f}\mathbf{x}_{t} + \mathbf{U}_{f}\mathbf{h}_{t-1} + \mathbf{V}_{f}\mathbf{c}_{t-1} + \mathbf{b}_{f}),
\end{equation}
\begin{equation}
    \mathbf{p}_{t} = v_{3}(\mathbf{x}_{t}, \mathbf{h}_{t-1})= \rho(\mathbf{W}_{c}\mathbf{x}_{t} + \mathbf{U}_{c}\mathbf{h}_{t-1}+ \mathbf{b}_{c}),
\end{equation}
\begin{equation}
    \mathbf{c}_{t} = \mathbf{f}_{t} \odot \mathbf{c}_{t-1} + \mathbf{i}_{t} \odot \mathbf{p}_{t},
\end{equation}
\begin{equation}
\mathbf{q}_{t} = v_{4}(\mathbf{x}_{t}, \mathbf{h}_{t-1}) = \sigma(\mathbf{W}_{q}\mathbf{x}_{t} + \mathbf{U}_{q}\mathbf{h}_{t-1} + \mathbf{V}_{q}\mathbf{c}_{t} + \mathbf{b}_{q}),
\end{equation}
\begin{equation}
    \mathbf{h}_{t} = \mathbf{q}_{t} \odot \rho(\mathbf{c}_{t}).
\end{equation}

\noindent In the equations above, $\odot$ is an element-wise product, and $\sigma$ and $\rho$ are sigmoid function and hyperbolic tangent function respectively. $\mathbf{W}$, $\mathbf{b}$, $\mathbf{U}$ and $\mathbf{V}$ are all learnable parameters of an LSTM.

\subsection{Feature Extraction}
\indent We begin our method by first detecting objects in individual frames of a video using Faster-RCNN \cite{ren2015faster}. The number of objects in a frame is limited to $N$. We then extract $d$-dimensional features for the objects present in the frames using a pre-trained VGG \cite{zhang2015accelerating}. Similar features are extracted for the whole frame as well. Thus, the object features $\mathbf{o}_{t}$ and full frame features $\mathbf{X}_{t}$ for the $t$-th frame are given as
\begin{align*}
\mathbf{o}_{t} &\in \mathbb{R} ^{N \times d}\\ \intertext{and}
\mathbf{X}_{t} &\in \mathbb{R} ^{d}.
\end{align*}

\subsection{Feature Aggregation Block}

In this subsection, we describe the FA Block to globally aggregate features over a frame. In order to detect accidents, it is important that the network understands the global context surrounding an object (a vehicle in our case) in a given frame. The main purpose of this block is to comprehend object interactions in the neural network. The FA block has further two components.
\begin{figure*}[thbp]
     \centering
      \includegraphics[scale=0.5]{Figures/Method.pdf}
      \caption{Overview of Accident Anticipation model.
      Full frame features $\mathbf{X}_{t}$ have size $B$ x $d$ whereas object features $\mathbf{o}_{t}$ are in the form of $B$ x $N$ x $d$. Here $B$ represents the Batch size, $S$ the total number of frames in a video sequence, $N$ the number of objects in a given frame and $d$ the feature dimension. These features are made input to FA block where they are refined. The full- frame feature $\mathbf{X}_{t}$ and averaged refined object features $\mathbf{m}_{t}$ are concatenated together and passed through an LSTM. $\hat{y}_{{t}}$ represents the anticipation probability at a given time instant $t$. }
      \label{fig: 4}
\end{figure*}

\subsubsection{Appearance Comparison}
This part of the FA block computes appearance relationship between objects in a given frame.  We use $i$ for the query object and $j$ to represent all possible objects in a given frame including the query object $i$. The object features $\mathbf{o}_{t}^{i}$ and $\mathbf{o}_{t}^{j}$ are passed through fully connected layers with parameters $\mathbf{W}_{\theta}$ and $\mathbf{W}_{\phi}$, respectively.
\begin{equation}
    \theta(\mathbf{W}_{\theta},\mathbf{b}_{\theta},\mathbf{o}_{t}) = \mathbf{W}_{\theta}\mathbf{o}_{t}^{i} + \mathbf{b}_{\theta},
\end{equation}
\begin{equation}
    \phi(\mathbf{W}_{\phi},\mathbf{b}_{\phi},\mathbf{o}_{t}) = \mathbf{W}_{\phi}\mathbf{o}_{t}^{j} + \mathbf{b}_{\phi},
\end{equation}
\noindent where $\mathbf{W}_{\theta}$, $\mathbf{W}_{\phi}$, $\mathbf{b}_{\theta}$ and $\mathbf{b}_{\phi}$ are all learnable parameters of fully connected layers. In order to show how object relations evolve over time, we add the hidden representation $\mathbf{h}_{t-1}$ into the output of fully connected layers.

\begin{equation}
    u(\mathbf{W}_{u},\mathbf{h}_{t-1}) = \mathbf{W}_{u}\mathbf{h}_{t-1},
\end{equation}
\begin{equation}
\mathbf{A}^{i} = \rho[u(\mathbf{W}_{u},\mathbf{h}_{t-1}) + \theta(\mathbf{W}_{\theta},\mathbf{b}_{\theta},\mathbf{o}_{t})],
\end{equation}
\begin{equation}
\mathbf{B}^{j} = \rho[u(\mathbf{W}_{u},\mathbf{h}_{t-1}) + \phi(\mathbf{W}_{\phi},\mathbf{b}_{\phi},\mathbf{o}_{t})].
\end{equation}

\noindent where $\mathbf{W}_{u}$ is a learnable parameter of fully connected layer, $\rho$ is the hyperbolic tangent function, and $\mathbf{A} \in \mathbb{R} ^{N \times d}$ and $\mathbf{B} \in \mathbb{R} ^{N \times d}$ show learnable transformations of object features $\mathbf{o}_{t}^{i}$ and $\mathbf{o}_{t}^{j}$, respectively. By transforming the objects' features, we can estimate the appearance comparison between objects effectively in a subspace.

We use dot product similarity as an appearance relation function between the transformation of objects' features in order to obtain the unnormalized attention weights $e^{ij}_{t}$.

\begin{equation}
    e^{ij}_{t} = \mathbf{A}^{i}(\mathbf{B}^{j})^{T},
\end{equation}
\noindent where $T$ represents a transpose function. The unnormalized attention weights $\{e^{ij}_{t}\}_{j=1}^{N}$ are normalized by using a softmax function so that the sum of all attention weights $\{\alpha^{ij}_{t}\}_{j=1}^{N}$ related to query object $i$ is 1, i.e.,

\begin{equation}
\alpha^{ij}_{t} = \dfrac{exp(e_{t}^{ij})}{\sum_{j}exp(e_{t}^{ij})}.
\end{equation}

\noindent $\alpha^{ij}_{t}$ is an attention weight showing the importance of object $j$'s feature with respect to object $i$. The attention weights are computed for all objects in a frame and packed together in a matrix $\boldsymbol{\alpha}_{t} \in \mathbb{R} ^{N \times N}$.

\subsubsection{Feature Refinement}
The FA block strengthens the feature of each query object by adding a weighted sum of all objects present in a frame to the query object. The weights indicate the appearance relation between the objects. First, a learnable transformation of object $\{o^{j}_{t}\}_{j=1}^{N}$ is obtained by passing it through a linear fully connected layer with parameters $\mathbf{W}_{g}$ and $\mathbf{b}_{g}$.
\begin{equation}
    g(\mathbf{W}_{g}, \mathbf{b}_{g}, \mathbf{o}_{t}) = \mathbf{W}_{g}\mathbf{o}_{t}^{j}+\mathbf{b}_{g},
\end{equation}
Afterwards, this representation is multiplied with the corresponding attention weights $\{\alpha^{ij}_{t}\}_{j=1}^{N}$ following the soft attention mechanism \cite{xu2015show}.

\begin{equation}
  \boldsymbol{\gamma}_{t}^{i} = \sum_{j=1}^{N} \alpha_{t}^{ij}g(\mathbf{W}_{g}, \mathbf{b}_{g}, \mathbf{o}_{t}),
\end{equation}
where $N$ is the total number of objects in a given frame.
The weighted summation of objects $\boldsymbol{\gamma}_{t}^{i}$ represents a global context for the query object $i$. The features of query object $i$ at time $t$ represented as $\mathbf{o}_{t}^{i}$ are refined by adding $\boldsymbol{\gamma}_{t}^{i}$ to produce $\mathbf{z}_{t}^{i}$.
\begin{equation}
\mathbf{z}_{t}^{i} = \mathbf{o}_{t}^{i} + \boldsymbol{\gamma}_{t}^{i}. \\
\end{equation}

\indent The Feature aggregation block is similar to the non-local block given in \cite{wang2018non} but is significantly altered for accident anticipation. Non-local blocks modify the features of each query position in a feature map by aggregating a weighted sum from all positions.
These positions refer to every location in a 2D feature map. In our method, we focus on strengthening object features instead of features of each individual pixel location. Moreover, we design our FA block such that in addition to capturing pairwise relationship between objects, it also learns the evolution of objects over time. This is done by adding an additional term including the hidden state of LSTM into our network.

\subsection{Traffic Accident Anticipation}

The overview of accident anticipation model is given in Fig.~\ref{fig: 4}. The refined object features $\mathbf{z}_{t} \in \mathbb{R} ^{N \times d}$ from a FA block are aggregated together to form per-frame descriptor $\mathbf{m}_{t}$ of size $d$.
\begin{equation}
\mathbf{m}_{t} = \dfrac{1}{N}\sum_{n=1}^{N}\mathbf{z}_{t}^{n}.
\end{equation}
This $d$-dimensional vector captures information of object interactions in a given frame. In order to have a better understanding of the scene, these features are combined with corresponding full frame features $\mathbf{X}_{t}$.
\begin{equation}
    \mathbf{x}_{t} = [\mathbf{X}_{t};\mathbf{m}_{t}],
\end{equation}
where ; indicates concatenation. The resulting features $\mathbf{x}_{t}$ are input to an LSTM, which outputs a hidden state $\mathbf{h}_{t}$. The hidden state is projected into probability values for the two classes, i.e., accident and non-accident by using a fully connected layer with parameters $\mathbf{W}_{o}$ and $\mathbf{b}_{o}$.
\begin{equation}
    f_{c}(\mathbf{W}_{o}, \mathbf{b}_{o}, \mathbf{h}_{t}) = \mathbf{W}_{o}\mathbf{h}_{t}+\mathbf{b}_{o},
\end{equation}
The output of the fully connected layer is normalized by a softmax activation fucntion.
\begin{equation}
    \hat{y}_{t} = softmax[f_{c}(\mathbf{W}_{o}, \mathbf{b}_{o}, \mathbf{h}_{t})].
\end{equation}
\begin{algorithm}
\caption{Training Procedure}
\label{algorithm1}
\textbf{Hyperparameters: } $S$ (Total number of frames in a video sequence), $N$ (Total number of objects in a frame), $y$ (video-level label), $\tau$ (accident label), and $d$ (Feature dimension).\\
\textbf{Input: }Video frames of size (224, 224, 3).\\
\textbf{Output: }A trained model.
\begin{algorithmic}[1]
\State Detect objects in the frames using Faster-rcnn.
\State Extract features from objects ($\mathbf{o}_{t} \in \mathbb{R} ^{N \times d}$) and full-frames ($\mathbf{X}_{t} \in \mathbb{R} ^{d}$)  using VGG.
\State Initialize $l$ = 0; $\mathbf{h}_{0}$ = zeros, $\mathbf{c}_{0}$ = zeros.
 \For{$t$ = 1,...., $S$}
 \State $\mathbf{A}$ = $\rho$($\mathbf{W}_{u}$$\mathbf{h}_{t-1}$ + $\mathbf{W}_{\theta}$$\mathbf{o}_{t}$ + $\mathbf{b}_{\theta})$
 \State $\mathbf{B}$ = $\rho$($\mathbf{W}_{u}$$\mathbf{h}_{t-1}$ + $\mathbf{W}_{\phi}$$\mathbf{o}_{t}$ + $\mathbf{b}_{\phi})$
 \State $\boldsymbol{\alpha}_{t}$ = $softmax$($\mathbf{A}$ $\otimes$ $\mathbf{B}^{T}$) ($\otimes$ is matrix multiplication)
 \State $\mathbf{z}_{t}$ = $\mathbf{o}_{t}$ + $\boldsymbol{\alpha}_{t}$ $\otimes$ ($\mathbf{W}_{g}\mathbf{o}_{t} + \mathbf{b}_{g})$
 \State $\mathbf{m}_{t}$ = $\dfrac{1}{N}\sum_{n=1}^{N}$ $\mathbf{z}_{t}^{n}$
 \State $\mathbf{x}_{t}$ = $concat(\mathbf{X}_{t},\mathbf{m}_{t})$
\State $\mathbf{h}_{t}$, $\mathbf{c}_{t}$ = LSTM($\mathbf{x}_{t}$, $\mathbf{c}_{t-1}$)
\State $\hat{y}_{t}$ = $softmax(\mathbf{W}_{o}\mathbf{h}_{t} + \mathbf{b}_{o})$
\State $l$ = $l$ + $\mathcal{L}(\hat{y}_{t}, y, \tau)$
\EndFor
\State Loss = mean($l$)
\State Backpropagate the Loss
\end{algorithmic}
\end{algorithm}
\indent During training, each frame is assigned a video-level label $y$ which is a one-hot encoded vector. For accident videos, the loss function is the exponential cross entropy, which gives more importance to frames that are closer to accident, hence, producing larger anticipation probability values for such frames. For non-accident videos, the loss function is the simple cross entropy. The loss for every frame is added for the entire video sequence, averaged and then back propagated.\\
The loss $\mathcal{L}(\hat{y}_{t})$ is given as
\begin{equation}
  \mathcal{L}(\hat{y}_{t}) =
  \begin{cases}
    \sum_{t}-exp(\tau-t)(ylog(\hat{y}_{t})) & \text{For pos. videos} \\
    \sum_{t}-(y log(\hat{y}_{t})) & \text{For neg. videos} \\
  \end{cases}
\end{equation}

\subsection{Architectural Details}
All fully connected layers with parameters $\mathbf{W}_{\theta}$, $\mathbf{b}_{\theta}$, $\mathbf{W}_{\phi}$,  $\mathbf{b}_{\phi}$, and  $\mathbf{W}_{u}$ compute non-linear transformations of their inputs where $\mathbf{W}_{\theta} \in \mathbb{R} ^{d \times d}$,
$\mathbf{b}_{\theta} \in \mathbb{R} ^{d}$, $\mathbf{W}_{\phi} \in \mathbb{R} ^{d \times d}$,
$\mathbf{b}_{\phi} \in \mathbb{R} ^{d}$,
 $\mathbf{W}_{u} \in \mathbb{R} ^{2d \times d}$, and the non-linearity is $tanh$. Fully connected layers with parameters $\mathbf{W}_{g}$, and $\mathbf{b}_{g}$ linearly transform the input where $\mathbf{W}_{g} \in \mathbb{R} ^{d \times d}$, and $\mathbf{b}_{g} \in \mathbb{R} ^{d}$. The number of layers in the recurrent neural network is fixed to 1. The final fully connected layer with parameters $\mathbf{W}_{o} \in \mathbb{R} ^{2d \times 2}$ and $\mathbf{b}_{o} \in \mathbb{R} ^{2}$ uses softmax activation function.

\section{Related Work}
\subsection{Video Classification}
Recurrent Neural Networks (RNN) have been used extensively in the past for Sequence/video classification. Yang \textit{et al.} \cite{yang2017tensor} model high dimensional sequential data with RNN architectures for video classification. Chen \textit{et al.} \cite{chen2017aggregating} explore video classification by aggregating the frame level feature representations to generate video-level predictions using variants of Recurrent Neural Networks and several fusion strategies. Hao \textit {et al.} \cite{ye2015evaluating} classify videos using a two-stream Convolutional Neural Network that uses both static frames and optical flows to classify sequences. For large-scale video classification, extracting optical flow features is computationally expensive. Tang \textit{et al.} \cite{tang2019hallucinating} propose a motion halluciantion network by which optical flow features are imagined using appearance features. Their method cuts down the computational cost by half for the two-stream video classification. Miech \textit {et al.} \cite{miech2017learnable} propose a two-stream architecture that models audio and visual features in a video sequence. In \cite{long2018attention}, the authors propose a local feature integration framework based on attention clusters for efficient video classification.

\subsection{Accident Detection and Anticipation}
Extensive research has been carried out in the domain of accident detection. Chan \textit{et al.} \cite{chan2016anticipating-1} use a RNN with dynamic attention to anticipate accidents in videos. Yao \textit{et al.} \cite{yao2019unsupervised} use an unsupervised approach involving future object localization and an RNN encoder-decoder network to detect accidents. The network is trained on normal training samples whereas the detection of accidents is carried out at test time. Herzig \textit{et al.} \cite{herzig2019spatio} classify input segments into accident or non-accident segments using a Spatio-Temporal Action Graph (STAG) network. Their supervised method involves refining the input features using non-local blocks \cite{wang2018non} to capture the spatial relation between objects and temporal relation between frames in a video sequence. Singh \textit {et al.} \cite{singh2018deep} use an unsupervised approach involving a denoising autoencoder to extract deep representation from normal CCTV videos at training time. Xu \textit{et al.} \cite{xu2019temporal} propose a Temporal Recurrent Network (TRN) that models temporal context over a long period which helps in anticipation of future actions in the video sequence. In \cite{zeng2017agent}, the authors adopt an agent-centric approach to measure the riskiness of each region with respect to the agent. In \cite{Suzuki_2018_CVPR}, the authors propose a novel adaptive loss for early anticipation of accidents.  \\
\section*{Acknowledgment}

\bibliographystyle{IEEEtran}

redpajama_set_name: RedPajamaArXiv


I have two great loves: nature and words. My pursuit of these passions has led me down two intertwining paths to become a scientist and a writer. While studying biology and English as an undergraduate at UC Davis, I got my first taste of travel writing as a "correspondent" for the university while studying abroad in Scotland. After deciding to pursue my love of the ocean, I received my master's degree in marine science at Moss Landing Marine Laboratories. I chose to study fish because I wanted to benefit both nature and people. Fish became that bridge. My research focused on California's newly established network of marine protected areas, and how the food web (as revealed by what fish were eating) could be affected by these protections. My interest in storytelling then led me to the Science Communication program at UC Santa Cruz where I learned many tools for communication, and emerged still wanting to keep a hand in both science and writing.
Fortunately, I have been able to merge both of these interests as the Communications Director and a Fisheries Biologist at the consulting company FISHBIO, where I have worked since 2012. In graduate school, I dreamed up a way to meld the professional with the personal: by studying fisheries in Southeast Asia. My personal interest is in Vietnam, where my mother's family is from. I was drawn to FISHBIO's fish research and conservation program in Southeast Asia, and have since worked in Laos, Cambodia, and Myanmar. Through this work, I have made the bridge from the ocean to freshwater, especially in the Mekong, the Mother River. The common thread is still fish. And I still often work with protected areas, though now they are in rivers.
Although my professional journey has brought me so close to my dream, my personal journey is the one leading me to Vietnam. I am currently working on a writing and research project that combines family, culture, and nature in an exploration of identity and place. The dragonfish is my talisman on this path – not a particular species but an idea, a blending of science and personal mythology. I'll be updating this website to share where the project takes me – follow along to see where the journey leads!


text:
Benjamin Britten: The Turn of the Screw at Wilton's Music Hall
This is not just live capture. This is a new hybrid form that honours the spirit of the original theatre production of Benjamin Britten's "The Turn of the Screw", but that also embraces the current constraints: the presence of the camera is declared…
Donizetti Queens in Concert
Compelling love duets, escalating conflicts and arias bursting with virtuosity and emotion. In his three Tudor Queens operas, bel canto master Gaetano Donizetti composed at the top of his game. In this concert, an international cast takes you on an…
Die ersten Menschen
In "Die ersten Menschen" (The first humans), the Bible story of the fratricide of Kajin (Cain) and Chabel (Abel) is presented from a different perspective. In the context of the first family on earth, Adahm (Adam) is concerned with cultivating the…
Offenbach: Les Contes d'Hoffmann (The Tales of Hoffmann)
The poet E. T. A. Hoffmann as the protagonist of his own fantastic tales: In his encounter with three women - Olympia, Antonia, and Giulietta - he searches in vain for love and for himself. Will he draw the strength for art from his failure in life…
Giuseppe Verdi: Falstaff
Sir John Falstaff is an anarchist who obeys only the reign of his own enjoyment, an egoist who feeds only his power-hunger and his own flesh, and who would prefer to raze the small-minded morals of his contemporaries like the walls of a fortress – by…
Wagner: Lohengrin from the Staatsoper Berlin
Bieitos interpretation of Wagner's Lohengrin deals with love, hate, jealousy and hope, but above all with man's imperative need to believe in something. To visualise these two contrasting worlds, Bieito creates two settings on stage: the world of…
George Frideric Handel: Semele
In Spring 2019, the Monteverdi Choir and English Baroque Soloists, led by John Eliot Gardiner, presented a critically-acclaimed European tour of Handel's opera Semele, including Alexandra Palace Theatre in London, where this live recording took place…
50. Jazzwoche Burghausen 2019: Al McKay's Earth Wind and Fire Experience
Burghausen has been a byword for jazz since 1970. For one week every March, the small town on the Salzach river turns into the German New Orleans. Ella Fitzgerald, Chris Barber, Roy Hargrove, Chick Corea and Dave Brubeck have all performed in…
Dmitri Hvorostovsky Festival: Sergei Rachmaninoff: The Miserly Knight & Aleko
Sergei Rachmaninoff's The Miserly Knight & Aleko from the Dmitri Hvorostovsky Festival 2019
Beethoven: Fidelio from St. Gallen
This opera film is based on Jan Schmidt-Garre's highly acclaimed stage production of Beethoven's Fidelio. The producers carefully filmed and edited several performances. By using additional footage of Jacquelyn Wagner as Leonore the stage production…

redpajama_set_name: RedPajamaCommonCrawl


Planning a wedding and choosing your wedding photographer can be a tremendous task. So, hopefully the information below will make at least one decision, a no-brainer.
You have a mile long to-do list to accomplish before your big day and The Beatific Lens is dedicated to making sure your planning goes as smoothly as possible, your photographs capture the true story of your love, and your memories stay eternally vivid.
The best wedding photographs take you back in time and give you the ability to relive your best day ever, in immense everlasting detail and evoke every wonderful emotion anew. This is exactly what I strive to do, present you with thoughtfully crafted imagery that leaves you in awe of yourself and your wedding day. Your gallery will provoke your senses, transcending the tale of your love into a timeless piece of art to be treasured by you and your loved ones for generations to come. My editing aesthetic embraces the whimsical side of photography; prominent deep rich colors and outstanding moody tones that truly captures your enchanting love story. Shooting in any circumstance and crafting beautifully composed photographs in the environment at hand is all part of my creative technique. During your wedding I zealously pursue each and every candid moment and minute detail making sure every memory is marvelously preserved and captured in a uniquely personalized way. My posing for portraiture is centered around natural movement and authentic reactions, personifying the love you share with one another and revealing the magic in the air. A big part of my process is getting to know my couples as I sincerely believe that the photographs from one of your biggest days ever, should not only make you feel incredible about yourself, but also genuinely embody who you are, perfectly encapsulating the love you share with one another. On your wedding day, I am a calming presence to combat the chaos and am there for you whenever you need me. I am an open book who loves to chat; I just adore listening to all of your stories and getting to know the real, raw you.
And with that, I enthusiastically await making your acquaintance and assisting you in designing the wedding of your dreams.
The truly custom package built by you, for you!
After the wedding, put on your wedding attire again and let's head off to a gorgeous location to capture even more spectacular photographs. This sessions allows us the time to craft truly unique and stunning images in epic locations.
In addition to creating dazzling photos, we spend our time goofing around and getting to know one another better. This allows me to determine your most flattering angles and leaves you feeling confident and ready for your wedding day.
Capturing all your cherished moments and the sweet little details during your dinner and toasts, The Beatific Lens has got you covered in all departments of merriment.
A second photographer chosen by The Beatific Lens will be present during the most meaningful parts of your day. They will work with and away from the me to capture different angles, ensuring there are no missed moments, and every reaction and detail is phenomenally captured and skillfully documented.
Exquisite albums thoughtfully crafted, wrapped in leather or velvet or with your favorite image printed on wood or metal and bound with linen. These albums are the final lasting physical piece of your wedding day, and it is for this reason that I work diligently to personalize each album to embody the couple's unique aesthetic.
Travel fees are required for weddings located outside of the state of Oregon or for any weddings that call for over night stays or flights. International travel is subject to higher prices to cover expenses.
We've met, gotten to know one another, and discussed the beautiful details of your special day. Now you've decided to book!
This is the time when I send over a contract for you to review and sign. Your wedding will be split up into two (or more) hassle free payments, the first of which is a 30% non-refundable reservation fee* that secures my services for your wedding date and is due within 14 days of signing the contract. The remaining amount will be due no later than 30 days before the date of your wedding.


FOUR months to the day before Lancashire will be playing County Championship cricket at Southport, Saj Mahmood and Stephen Parry turned up at Trafalgar Road last Saturday to help prepare the ground for the game against Nottinghamshire in July.
The Red Rose pair were helping spruce up Southport and Birkdale's facilities as part of the NatWest CricketForce initiative, and they were given a warm welcome by a large group of S&B members who were determined that their club should look its best for the return of first-class cricket.
Mahmood and Parry were quickly put to work painting the sightscreens at the Harrod Drive End and both players expressed their enthusiasm for outground cricket.
"Outgrounds are good for us," said Mahmood. "The opportunity's come for us to play at Liverpool and Southport and both venues have produced result wickets in the past. We know those strips better than any county in England and if we can use that knowledge to our advantage and get some good wins under our belts, we'll be up near the top of the table.
"Playing at Liverpool, Southport and Blackpool is a pretty good thing for Lancashire at the moment."


text:
San Miguel Topilejo est une communauté au sud de Mexico, dans la délégation Tlalpan, considérée comme un des 8 villages de Tlalpan.

La ville compte  et se trouve à  d'altitude.

.

Notes et références

Quartier de Mexico

redpajama_set_name: RedPajamaWikipedia


It's the eighth annual iFanboy All-Media Year End Round-Up! Conor Kilpatrick, Paul Montgomery, and special guest Mike Romo discuss everything they enjoyed in media in 2013. Movies, television, music, books, video games, and comics–it's all here!
00:52:19 – Marvel's Agents of S.H.I.E.L.D.
Can't wait to listen to this one! My favorite shows this year were Breaking BAD, Arrow, Orphan Black, Bates Motel, Hannibal, Orange is the New Black, Game of Thrones, The Returned, and more that I can't name right now.
As of approximately 3:30 p.m. Central Time, downloads via right-click and iTunes are only 25 minutes long?
Uh, guys, the podcast only comes in at 25 minutes – both on iTunes and direct download. You might want to check on that.
We are aware of the problem with the file. We are working on it now.
The file should be fixed now. If you downloaded a bad version on, say, iTunes, just delete that version and re-download the new file.
Cool. Thanks, Conor! Looking forward to the show. Let me be the first to say though – because you know someone was bound to – it would have been great if you had gotten Ron to join you guys for this show at least. Ah well, maybe next year.
Bioshock Infinite seems like a polarizing game but not for the obvious reasons. This video makes a lot of persuasive arguments about why it's not a well designed game. It's a long fascinating deconstruction narrated in a delightful Irish accent.
I haven't played it myself (not a big shooter fan) but I enjoy reading the various pros and cons about it. Does that seem weird? For me the best game of the year was DmC: Devil May Cry. Great fun that game.
Also just wanted to thank you guys for another great year. You guys consistently deliver my favorite podcast every week. Hope this show never goes away.
This is the only podcast I believe in. I've listened to many other popular comic podcasts and reviews and this is the only one I trust.iFanboy must never stop!
I am so glad to hear that you guys loved About Time as much as I did. A lot of people complained about it being overly sentimental but I couldn't disagree with them more. What a seriously beautiful and funny film.
I love shows like this, especially when Romo's in the house.
Totally agree with Paul about, "Bioshock Infinite." It was the first game that I really played since I was a kid, and that final battle took me a couple days, just because it was so frustrating. I feel like I saw God when I finally beat it.
With, "Orange is the New Black," I thought I would hate it because the trailers were really stupid and didn't really foreshadow what was to come accurately. I watched after hearing some of the hype and I loved it. I did hate Jason Biggs inclusion though; I wish he was leaving instead of Laura Prepon.
Vikings is one of my favorite shows. It feels so much like Sons of Anarchy set in the Norse universe. I know I'm not the only one to compare Ragnar to Jax.
Here's to a great '14!
BTW you guys should watch BLACK MIRROR and THE RETURNED. They both only have 6-7 episodes. You won't be disappointed, trust me.
The all media round up is one of my favourite podcasts of the year, I always start looking forward to it in November.
Thanks for all your hard work this year fellas!
first, i'd second the recommendation for a band called death. just watched that movie last night and it was phenomenal.
second, and i suppose this is mostly directed at paul, are there any plans to discuss the wrap-up of locke and key? i'm guessing the last issue came out after this was recorded, but i was looking forwarding to hearing the thoughts on whether it lived up to the series' as a whole and how well you thought hill and rodriguez did (or didn't) stick the landing.
I'm bending the rules and talking about it on the first show back. Special case.
Awesome Paul, but please, no spoilers!
And if you sneak Private Eye #5 in there, I certainly won't complain.
as a follow-up for my comment on a band called death, i picked up their album "for the whole world to see" today. it's good. you can tell they're young and still figuring out how to write, but definitely worth the money. glad i saw the movie, now.
I made the right call. I saw two of those movies.
Kon Tiki and Upstream Color.
Pacific Rim and About Time?
Frozen and A Band Called Death.
I have since seen American Hustle and Smaug.
Also, The Way Way Back, which might be my favorite subgenre of cinema.
Paul, Gone Home and Papers, Please are two of my favourites from this last year as well. Did you play The Stanley Parable? It completes my holy trilogy of indie games from the year. It'll be cheap in the Steam sale, I'd highly recommend it.
I haven't, but I shall check it out!
Still listening but through the movie portion and am enjoying the podcast very much. Conor, we are usually on the same page moviewise but mark me down as one of the ones who did not enjoy The Lone Ranger. Saw they were definitely trying for the Pirates vibe and it did not work for me. If you do like the character, I am currently reading The Lone Ranger Chronicles – an anthology of short stories by various authors including Chuck Dixon and Denny O'Neil. It's pretty good.
Also, did any of you see a movie this year called The Way Way Back? A really good coming of age movie with a great performance by Sam Rockwell.
Always enjoy the podcasts. Have a Merry Xmas and a Happy New Year.
I just watched The Way Way Back a couple nights ago. Nice heart to it. Jim Rash does good stuff.
I can't wait to listen to this. This is my fav episode all year. The only downside is no Ron this year for music. Speaking of Ron am I the only one thinking he was the guy behind Image hooking up with Dropbox for drm free comics disruption? Image just crushed it with that idea. If the other publishers are smart they will follow up quick.
That was extremely interesting, informative and entertaining. Thank you.
Just watched Man of Steel last night and enjoyed it more than expected. I enjoyed the updated modernizing of the look and feel of the mythos–also the John Byrne touches. The third act got maybe a little long winded, but Supes and Zod acted as I might have imagined two god-like aliens to be.
Hey guys, finally got around to listening good stuff! I skipped The Wolverine due to my dislike of X3 and Origins but I shall be redboxing it when it comes out. Looking forward to catching The Lone Ranger too! It looked like lots of fun but I couldn't convince anyone to go with me and that looked like a fun one to share with others. The big one that I loved this year was Derek Cianfrance's The Place Beyond The Pines. I really enjoyed Blue Valentine but this one was even better for me. I've seen it 3 or 4 time and cried each time. Best father/son/legacy movie I've seen in a long time.
For me the big tv surprise this year was Arrow. I skipped the first season cause the promos looked like they were targeting high school females but after a few episodes of Agents of S.H.I.E.L.D. (which I did not like) I went back and gave Arrow a try…absolutely blown away! The other sleeper show I found really interesting was Rectify, really good stuff.
Book-wise I haven't finished it but I picked up S. (http://www.amazon.com/S-J-Abrams/dp/0316201642/ref=sr_1_1?s=books&ie=UTF8&qid=1388162907&sr=1-1&keywords=s+jj+abrams) on a whim at Barnes and Noble and it is really interesting. I actually thought of Paul when I picked it up. I think you guys would at least get a kick out of the way the story unfolds. And that Difficult Men book sounds excellent, added on Amazon!
Also, I LOVED Frozen. It well deserves its superlative praise!
I finally watched THE WOLVERINE last night. It was really fun. The fight on top of the bullet train alone is worth checking it out. Everyone else is correct, though, the third act is a bit wonky. But a huge return to form after the last two Wolverine-centric films. Fantastic mid-credits sequence too!
Btw Brian is one of the nominees for induction into the Rock and Roll Hall of Fame for 2014.
These episodes are always a lot of fun.
I love Brooklyn99. Season 3 of Game of Thrones was excellent, too.
Gravity may have been my favorite film of the year.
I didn't read anything that really blew me away, unfortunately.
I'm really enjoying BROOKLYN 9-9 as well.
Great show as always guys. I too was really surprised by how much I liked Frozen, one of the better Disney movies in a really long time. Along with Frozen; American Hustle and Pacific Rim were probably my favorite movies of the year. Really glad you talked about and like The Americans, it was probably my favorite new show last year along with The Blacklist.


There are hundreds of cool things to make with loom bands, how do you choose? Snowflake Loom Bands are a seasonal choice.
I've been wanting to make these for a while. Fun Loom Bands can be full of creativity. They seemed the perfect medium to use for creating snowflake patterns and demonstrating the six fold symmetry.
Usual practice with loom bands is to work in rows. Here we work in the round securing the design at the six corners of a hexagon within a circle.
The simple repeated actions bring awareness of the geometry and numbers present in this little crystalized bit of nature.
Look again at Hexagonal Geometry in Snowflakes, remember that whatever pattern is created it has to be completed a total of 6 times around the hexagon.
Instructions for How to make Snowflake Loom Bands.
You'll need a password to access the page with the download.
Go to this access page , enter your NAME and EMAIL address and your password will be arrive in your inbox straight away with the page link.
If loom bands aren't your thing, why not have a look at how to make paper snowflakes.
Remember to leave pictures of your snowflake creations on the social pages. Can't wait to see them. Also if you had a minute to pop a couple of words in a review, would be great.
Have you found this interesting and would like to share it? if so, please encourage friends to input their own email to receive the download. Lets fill the world with loom band snowflakes and hexagon geometry.
Here's that link again to get access to 'How to make Loom Band Snowflakes'.


Just a few years ago, Catechesis of the Good Shepherd was a relative unknown in the Diocese of Rochester. Few local people had heard of this approach to children's religious formation, and there was not a single atrium — or classroom dedicated to this method of formation — anywhere within the diocese.
Fast forward to the present, however, and four diocesan parishes currently offer Catechesis of the Good Shepherd, with at least two more planning to join their ranks within the next few months.
"(This approach) is a way to kind of jump-start the faith relationship between children and God at a younger age," explained Anthony Klosterman, coordinator of faith formation and preschool at St. Patrick Parish in Victor, which opened an atrium and began offering Catechesis of the Good Shepherd last fall.
Most of the participants in this diocese are between the ages of 3 and 6, noted Michelle Kuhner, lead catechist for the program at the Victor parish and the woman responsible for bringing Catechesis of the Good Shepherd to the Diocese of Rochester. She'd been introduced to this method of catechesis, which has been around for more than 50 years, while she lived in Ave Maria, Fla.
Catechesis of the Good Shepherd follows the child-centered Montessori educational method that recognizes each child's need for independence. Each atrium contains a variety of materials that encourage prayer and contemplation, and the children choose which activities they would like to do.
Some of these activities are not overtly religious, such as arranging flowers or pouring water, yet they take on additional significance in the quiet environment of the atrium, according to Jennifer Brannin, one of the catechists at Church of the Holy Spirit in Webster. At the hand-washing area, for example, children carefully scrub and wash one finger at a time, and this exercise helps them build the focus and concentration they need to pray, she said.
"You're not teaching hand washing. You're teaching contemplation," Brannin explained.
Many of the materials found in an atrium encourage a deeper relationship with Jesus in a more obvious way. Each atrium, for example, includes miniature chalices, patens, cruets, candles and other items found at Mass, and the children may ask adults to show them how these items are used and then mimic those movements themselves.
"All the materials are designed so the children can work with the materials, actually touch the materials and use them to help them contemplate their relationship with God," said Lynn Foley, a Catechesis of the Good Shepherd volunteer at St. Patrick.
At some point during a session, the catechist will sit with each child and read the week's Scripture story, first from the Bible and then from a small Scripture booklet as the children use handmade figures to act out the story, Brannin said.
"When you just talk to them they're not going to remember it, but when they get to work with it, they remember it," Brannin said.
The atrium provides children with a place to explore things they already may be familiar with — Mass and stories of Jesus' life — in a way they can understand, Kuhner said.
It was the joy on the faces of the children involved in Catechesis of the Good Shepherd in Florida that first motivated Kuhner to go through the training necessary to become a certified catechist with the program. She later moved to Rochester and in 2017 formed an atrium at Sacred Heart Cathedral, where she was working as faith-formation coordinator.
Others in the Rochester Diocese soon expressed an interest in Catechesis of the Good Shepherd, and over the summer, more than two dozen people attended a 10-day training session at St. Bernard's School of Theology and Ministry with a formation leader from Florida. All of those people now are certified as level one catechists who can work with children between the ages of 3 and 6. This summer, another training session will be conducted in order to certify people as level two catechists, who will work with children between the ages of 6 and 9.
Kate Dominguez participated in last summer's training and now serves as assistant catechist for Catechesis of the Good Shepherd at St. John the Evangelist Parish in Spencerport. Her experiences thus far have deepened her own faith, she said.


It's time to get SCHWIFTY with this limited edition ZBOX containing a selection of merch from your favourite cartoon series, whether you're bit of a Pickle or seeking the Szechuan sauce, don't miss out and grab it now!
Contains a Rick and Morty Licensed T-shirt (exclusive), Rick and Morty Comic Book (exclusive), Rick and Morty Metallic Print (exclusive), a Rick and Morty Pop! Vinyl Figure, and Morty Action 5 inch Figure.
Worth it just for the comic!!
This box was just okay. It had a few good items in it that were decent. But contained a funko and morty figure that you can buy in any store. I understand not all the items can be exclusives but in my opinion instead of two figures that any Rick and Morty fan is already going to own they should of at least gone with items that perhaps were lesser known. This is just my opinion but still I would of much rather the funko been an exclusive.


Data mining service is the process of extracting a specific set of patterns from a wide dataset. It is considered to be a significant tool in the contemporary global scenario, to successfully transform the raw data into meaningful information. The concept of data mining service is used in different profiling techniques such as marketing, surveillance, detecting fraudulent activities, and scientific discovery.
NexGen Data Entry is the foremost offshore outsourcing service provider of the data mining solutions within a user-friendly designed budget.
Various other terms such as 'data fishing', 'data dredging', and 'data snooping' implies the utilization of data mining techniques to extract the portion of the larger dataset.
The dedicated team at NexGen Data Entry has the potential of mining the data from multiple secondary sources such as the professionally designed websites, white pages, or yellow pages. Let it be a small or a huge marketing campaign, the procedure won't be successful without the effective listing of the essential contacts, especially amidst this digital era. Hence, our team believes in offering the optimized, accurate, and consistent data mining services.
Primary function involves the process of extracting the data from the world of internet, as per the requirements of both the small and large scale business organizations. Collecting/extracting the significant data from the web is effective to execute the process of analysis.
Most of the firms are looking out for less time involving techniques to extract the contact information of clients or customers. We offer you with the cost-effective data mining measures, which will gather numerous details such as contact address, phone number, age/gender of client/customers, and much more.
Possessing the ability to develop a new Excel sheet or work on the existing one, and applying the necessary models or formulas. The data collected from the Excel sheets are the perfect choice for implementing error-free financial or business planning.
The concept of data mining isn't just limited to words. We will take you beyond the extraction of data from Word or Word-based documents. Our team ensures to fetch the small or large-scale based data from the multiple images and prepare them for significant analysis purposes.


Lawnmowers are among the essential home maintenance tools today. With them, gardening and landscaping became a lot bearable, as homeowners will never have to trim their lawns manually.
These tools are worth our trust. Nevertheless, there are some instances in where they go out of control. It is not a scary predicament, but it can cause nuisances and delay in your work. Fortunately, troubleshooting the lawn mower is doable.
You just have to know the issue and the corresponding resolution that should be implemented to solve it.
This is one of the most prevalent issues on every lawn mower suffer. I have seen and heard many people complaining about the problem. It is not an issue to bother. Still, immediate maintenance and repair should be conducted soon.
Usually, this problem occurs when you are running your lawnmower. The trouble starts when the lawn mower will suddenly puff a huge volume of white smoke.
Do not mistake it for gradual and continuous emission of white smoke. No. The smoke is almost spontaneous and huge that it can always catch your attention.
After the smoke was blown, the lawn mower will suddenly come to a halt. It will go in a state of suspension, in where it will not respond anymore to any starting mechanism that is built to the device.
Even if you rest the lawn mower for a day, things will not go back to normal easily. If you start the lawn mower again, it might show signs of life but it will just end up sputtering plumes of white smoke again.
Sooner or later, restarting the lawn mower will prove to be a difficult task.
A lawn mower that is stuttering can be caused by different factors. Before you start troubleshooting the lawn mower, you have to make sure that you can determine the most probable culprit to why your lawn mower died suddenly.
It is not good that there is water in the fuel line or fuel tank of the lawn mower. It can always result in engine problems.
That is a guarantee. Once the water has already penetrated the cylinder, ignition will become difficult. It also stops the gasoline from being ignited appropriately.
The water is usually derived from excessive condensation. You can blame the external elements for this. Sometimes, a wobbly gas cap that you have not check could also cause it.
To remove the water, you just need to empty the tank and use new and fresh fuel. Of course, do not forget to dispose of the oil and gas that you have previously removed in the tank.
Most of the time, a stuttering and smoking lawn mower is due to a damaged head gasket. Blown head gaskets are caused by either overheating or damaged parts due to over usage or old age.
Fortunately, this particular component of the lawn mower can be replaced. However, of course, it will always require money and professional services.
If the head gasket is fine, check the valves of the lawnmower. They might be broken or severed. However, for me, damaged valves are least likely the cause.
After all, valves do not induce compression. The mere fact that the lawn mower keeps on stuttering is a good proof that the perpetrator is the gasket.
Always check the spark plug of the engine if your lawn mower cannot run smoothly. Lawnmower spark plugs, just like the ones in your vehicle, are susceptible from getting worn and damaged.
Once this happens, the engine will experience irregularities in starting.
Try removing the spark plug so that you can examine it properly. Check the firing tip and see if the end has an accumulation of carbon. If yes, then clean it with the use of a wire brush. After this, restart the gap as specified by the manufacturer.
However, if the problem is due to a cracked porcelain housing or the deterioration in the metal bend, just replace the spark plug. Do not worry. It does not come expensive.
If the lawn mower releases white smoke then dies, those three factors that I have mentioned are the most possible reasons. You have to inspect any of these parts in the event that the SHTF situation takes place.
If you cannot fix the issue on your own, just refer the problem to a professional. It is better to let the pros handle the situation to prevent it from getting worse.
Did you learn from this guide? If you have some questions, feel free to ask me in the comment section below.
and hedge trimmer (I bought them after each and every from trugreen and agreenhand).
I love them. Quiet and clean. And I have thick St Augustine grass which it mows in the an hour on a single chargewith not a problem.
electric (corded or cordless) does not need power are a little dated in their assumptions.
It's a basic point that DC motors have more torque than gas magnetic generators.
use for lawn care type applications.


Many of our clients seek advice regarding the occupational health issues faced by organisations in business today.
Whether you are a large national company or a small family business, or indeed anything in between, you may need advice and help.
Oyster can provide specialists to advise and source an appropriate provider to help your company implement an occupational health programme to fit your cultural and business priorities.


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Corruption and Free Speech at Columbia
By Duane Thresher, Ph.D. October 10, 2022
These days, with Twitter and Facebook being hotbeds of censorship, IT and free speech are intimately related. I am an expert in both, although less willingly so for the latter, since I became so through denial of my free speech. My denial occurred at another hotbed of censorship these days, universities, and via a major method for censorship, email. This denial of free speech goes hand in hand with corruption at the universities, as it does for government.
This article, particularly its title, Corruption and Free Speech at Columbia (today is Columbus Day), is with acknowledgement to God and Man at Yale by William F. Buckley, who was essentially also writing about corruption and free speech (his book is subtitled The Superstitions of "Academic Freedom") at a university, Yale, while he was a student there, graduating in 1950. (Today Yale denies free speech to the point where some federal judges will no longer accept Yale Law School graduates as law clerks.)
I was a graduate student at Columbia University, doing climate modeling on supercomputers, and got my Ph.D. from there in 2004.
As has been widely reported recently, Columbia was caught, by one of its own math professors (Dr. Michael Thaddeus), outrageously lying (I read his proof; "outrageously" is justified) to dramatically increase its rank in the U.S. News & World Report college rankings. (Columbia subsequently withdrew from these rankings; expect numerous lawsuits against Columbia from Columbia students and their parents.)
As has also been widely reported recently, Columbia was successfully sued for a total of $236 million for sexual abuse by one of its medical doctors (Robert Hadden ) of a total of 226 patients. The large number of victims was because Columbia silenced the complaints of some of the first victims. (Ultimately, Columbia students and their parents will pay this judgment.)
Less widely reported is that Columbia was ranked as the worst college for free speech, 203 out of 203, by the Foundation for Individual Rights and Expression.
The first two reports are directly related to the third — corruption necessitates preventing free speech, i.e. silencing, censorship.
The main purpose of the First Amendment, all of its clauses (freedom of religion, speech, press, assembly, petitioning government for redress of grievances), is to prevent government corruption, particularly totalitarianism, by protecting freely speaking out about it, in various forums. Columbia's president, Lee Bollinger , a lawyer who claims to be an expert on the First Amendment and free speech, should know this and apply it to Columbia, but chooses not to. (Lee Bollinger is one of the highest-paid university presidents in the U.S., making $2.8 million in 2020, during the Coronavirus Scare, when Columbia's finances were in serious trouble; it's OK though, Bollinger bravely agreed to a pay freeze.)
As a Columbia alum I have suffered much denial of free speech over the years by Columbia — for which I am contemplating a lawsuit — particularly through their Orwellian control of Columbia email accounts.
University email accounts are important because their addresses provide the user with authentication, since only someone who attended the university could have a university.edu address; see Apscitu's Secure Contact page.
Columbia has a long history of censoring my email. Some examples:
I programmed significant parts of two major climate models and based on that in-depth knowledge, particularly of their fatal weaknesses, I became a skeptic of climate predictions; see Climate of Incompetence. In 2017 I tried to discuss this by emailing various climate research organizations, including government organizations, using my Columbia email account. Columbia blocked the sending of these emails, based on their content — i.e. Columbia read them — and bounced them back to me announcing this.
Like other universities, Columbia has a leftist bias in political email spam filtering; see also the computer science journal article A Peek into the Political Biases in Email Spam Filtering Algorithms During US Election 2020.
University alum directories are supposed to provide the email addresses of alum to other alum so they can stay in contact, particularly about what's happening at their "alma mater" (Latin for "nourishing mother"; see picture, with Big Brother , Lee Bollinger ). Columbia refuses to allow this. It only allows alum to contact other alum through Columbia's direct messaging system while logged into their Columbia "community" account, just like Facebook. However, most alum are almost never logged into their Columbia community account so never get these messages. Columbia, however, gets to read them, just like Facebook (possibly also reporting them to the government, just like Facebook).
When I complained about this censorship to Columbia several years ago, Columbia permanently hid my Columbia community account profile, on which I had posted this complaint. Searching for me in the Columbia community gives a message saying I hid my profile, which I certainly did not. I have tried numerous times to unhide it but Columbia will not allow me to.
Given Columbia's extreme denial of free speech, you can expect corruption beyond lying on college rankings and silencing complaints of sexual abuse by their medical doctors, like on the taxes they should have paid on their huge endowment under a new law they fought against — the same things they lied about to U.S. News & World Report affect how much tax they should have paid.
Freedom of speech may be lost forever at universities (e.g. see MIT Lawyers v. Dr. Thresher), a loss process that ironically started with the Free Speech Movement at the University of California Berkeley in the 1960's, but perhaps Elon Musk can at least return free speech to Twitter. Fittingly, since denial of free speech is very scary, we should know by Halloween.
[Update: After Columbia University withdrew from the U.S. News & World Report college rankings after cheating on them, Yale Law School and Harvard Law School also withdrew. The law schools say they withdrew because the rankings incentivize the wrong things in education. However, they've been saying this for decades, at least since the 1980's, but have continued to participate, and been profitably near the top of the rankings. No, as any court would agree prima facie, Yale Law School and Harvard Law School probably withdrew from the rankings because they too were cheating on them.]


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Fast Casual Greek
Little Greek Restaurant dishes true-blue specialties fast in Dallas proper
Mediterranean restaurants, we have. But Greek restaurants, not as much. Little Greek Restaurant to the rescue. This small chain from Florida will open two branches in North Texas, including one in Dallas, at the southwest corner of Walnut Hill and 75.
A branch will also open in Coppell, joining Little Greek's two other suburban branches in Richardson and Carrollton.
The Dallas location, which is slated to open in May, is going into a former bicycle shop, where it will be neighbors with Tupinamba, the Tex-Mex institution that just closed its Inwood location on January 31; Tupinamba intends to reopen at this new location in mid-February.
Little Greek was brought to Dallas by Jan and Barry Rosen, who discovered it on visits to Tampa.
"I loved the salad dressing. I had them ship it to me by the case," Jan says. "All my friends would buy it from me. I guess you could compare it to a creamy Italian. It has a lot of seasonings, and there's a little sweetness."
But you can't pin a restaurant's fortunes on salad dressing alone. "The reason I thought it would work is because we have Greek restaurants, but none that are fast casual," she says. "We cook to order in front of you. And we get our gyro meat and pita bread from Chicago."
They do quite a bit of catering for organizations like the Dallas Cowboys and hospitals, which Jan enjoys, because her mother was a caterer too. The location's proximity to Medical City Hospital was a deciding factor.
"We weren't even going to do another location, but when this property became available, it made sense," she says.
The menu includes familiar Mediterranean staples — hummus, of course, and baklava, and skewers of herbed chicken and beef served over rice — but also items unique to Greek cuisine such as moussaka and pastitsio.
"We want to differentiate ourselves from the Mediterranean places," she says. "Our Greek salad is unique because it's topped with a scoop of potato salad and a red beet," Jan says. "That's a Florida thing, but transformed into Dallas too."
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411 for renters
2 North Texas cities rank among best places to find new apartments in 2023
Photo by Flood Photography, courtesy of Greystar Properties
Renters seeking new apartments could have the best luck finding their new home in two Dallas suburbs, a new study says.
RentCafe has named Frisco and McKinney as the fourth and fifth best cities for finding new apartments in 2023, respectively. The apartment listing service ranked the top 50 U.S. cities for finding new apartments by analyzing the number of new apartments opened in the last 10 years, how large they are, the most recent occupancy rate, and the quality of neighborhoods where they are located.
The RentCafe report notes that apartment buildings are almost full in every metro area across the U.S., meaning renters have a higher chance of finding available apartments in newly built communities.
So, what made Frisco and McKinney stand out?
Over the last 10 years, Frisco has seen a 194.7% increase in new apartments, according to the study. The city also boasts a 92.9% share of new apartments in top locations and an occupancy rate of 95.1%. The average apartment size in Frisco is 933 square feet.
Frisco is also one of the fastest growing cities in the U.S., thanks to its "booming economy, amazing sports scene, countless entertainment options, proximity to the great outdoors and high safety rating," the study says.
As for McKinney, the city has increased its new apartments by 111% in the last 10 years and has 90.5% of its apartments in top locations. The average apartment size is 918 square feet, and 94.1% of McKinney apartments are occupied.
Much like Frisco, McKinney has "a thriving economy, great quality of life and high-paying job opportunities in various industries," the study says.
Texas cities dominated the ranking with 12 cities in the top 50, six of which made it into the top 10. In addition to Frisco and McKinney, the cities of Midland (No. 2), Humble (No. 3), Spring (No. 8), and Katy (No. 10) also made it to the top 10.
Boca Raton, Florida took the No. 1 spot in the survey.
No. 2-ranked Midland, which is part of the Permian Basin area, saw a 56.8% increase in new apartments. About 40.7% of the city's apartments are in top locations, and the average size of new apartments is 913 square feet. Meanwhile, about 81.8% of the apartments are occupied.
In the Houston suburb of Humble, which ranks No. 3, there has been a 45.2% increase in new apartments over the past decade. The occupancy rate is 91.1%, and the average size of new apartments is 925 square feet. About 78% of new apartments are in top locations.
Humble's suburban location and proximity to Houston could be what entices renters to move to the "hidden gem," the study says.
Also a Houston suburb, No. 8-ranking Spring boasts an occupancy rate of 94.5% and an average apartment size of 947 square feet. New apartments have increased 112.4%, and 48% of new apartments are in top locations.
Spring has seen substantial growth, mostly thanks to ExxonMobil's 2011 decision to build a campus there and expand its operations in Texas. While the campus was being built, many ExxonMobil employees relocated from Irving to Spring.
The tenth best city and another Houston suburb, Katy, has seen a 123.2% increase in new apartments. About 44.9% of those apartments are in top locations, and the average occupancy is 94.9%. The average size of new apartments is 951 square feet.
Katy offers "the best of both worlds" to many renters: small-town charm and big-city amenities. The city's highly rated schools and major employers contribute to its success. Also, Katy is a popular retirement spot because of its health care facilities and recreation centers.
Elsewhere in Texas, the top 50 included a mix of bigger cities, college towns, and suburbs:
Round Rock, No. 22
Increase in new apartments: 36%
Share of new apartments in top locations: 91%
Occupancy: 92.6%
Average size of new apartments: 895 square feet
Richardson, No. 25
Increase in new apartments: 79.5%
Share of new apartments in top locations: 96.5%
Average size of new apartments: 877
College Station, No. 31
Average size of new apartments: 1,039 square feet
Houston, No. 35
Conroe, No. 36
Plano, No. 42


Shuai Ming Wong of The Woodlands, Texas, will represent the West Team in his first Wyndham Cup appearance. The Southern Methodist University verbal commit has recorded 12 top-20 finishes in his five-year AJGA career. The AJGA's No. 6-ranked junior has competed in the U.S. Junior Amateur Championship on three occasions (2013, 2014, 2016) with his best finish coming in 2016 in the Round of 32. Wong started the 2017 season with runner-up finishes at the CB&I / Simplify Boys Championship at Carlton Woods and the Bishops Gate Golf Academy Junior at Horseshoe Bay, and a third-place finish at the Haas Family Invitational presented by BB&T.


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This is an exciting position available for a Registered Veterinary Nurse to join a friendly practice in the North West. They are a chain of 17 branches with an RCVS accredited hospital offering out of hours' care. Within the team they have 12 RVN'S, with SVN and ANA support. The role will be based at the main hospital based in Blackburn, which is well equipped with endoscopy and CT scanner etc. They also have an onsite rehabilitation and hydrotherapy unit.
The role involves approximately 37 hours per week with a maximum of four consecutive nights once a month on the night rota. A night shift will consist of, 8pm till 8am with the potential to sleep 12pm till 6am due to work load, support on nights will be provided with an ANA, Veterinary Surgeon on site and additional senior vet on call. Generous time off will be given for the night shifts equating to 17.6 weeks off a year including holiday allowance.
The team are proud to utilise our nurses to their full potential enabling them to use their schedule 3 work and nurse clinics. There may be some reception duties required occasionally. The ideal applicant will be confident and enthusiastic with a positive attitude. You must be able to work as a team as well as alone.
Our client requires an additional veterinary surgeon to join their 3 vet team. The practice have a busy and varied caseload and will support certificates in any small animal discipline.
Our client offer unrivaled career prospects and packages including accommodation if required.
Our client, a small animal practice in Lancashire, achieved the top tier Veterinary Hospital status from the RCVS and means they have the best equipment, team and processes in place to deliver outstanding pet care.
To that end you can expect to work in one of the UK's best equipped hospitals. You will be supported by a professional nursing team and will be supported and encouraged to work cases up to a high standard. You can expect a case volume that allows you to grow as a veterinarian, without breaking you mentally or physically.
Practice facilities include Ultrasound, rigid laparoscopy, digital x-ray, digital dental x-ray, endoscope, tonometer pen, capnograph, infusion pump, syringe drivers, ECG, Doppler, Radiosurgery, cryosurgery, Idexx blood analyser - Catalyst, Vetlyte, Procyte, Snap reader. Microscope, centrifuge, hydrotherapy treadmill.
The ideal candidate will a confident communicator and remain calm when under pressure. You will be able to work well with clients and staff to achieve good outcomes and also have the desire to grow and be the type of person who seeks out feedback and opportunities to develop.
The team will definitely be happy to support you with this as long as you share the same goals - for example one of their vets is currently studying for their Cert AVP and so the team provide time off and financial support to help them be successful. This a full time role working 35 hours on a 7 week rolling rota. Weekends will be a rota and will then be followed by a three day week. At the moment the roles has no out of hours, which may change. There may be occasions when in patients may need to be checked on during the night.
In addition to this the candidate will need to be flexible. So, occasionally, if a case needs a little more attention or a rota goes sideways, you will be happy to get the job done or help a colleague out. But the team will always make sure you get time back, or money and genuine gratitude when this happens.
*Deliver empathetic, trust-building consultations for wellness and ill/injured animals.
*Demonstrate critical thinking and decision making skills to create and implement diagnostic and therapeutic treatment plans.
*Surgical skills - neutering, lump removal wound repair are the core skills we need. If you can do more or want to learn more that's a bonus.
*Imaging skills - basic abdominal and thoracic radiograph interpretation. Ultrasonography is a bonus that would be highly regarded.
*Ability to build trusting relationships quickly and have high emotional intelligence.
*Good at "vet admin" (note keeping, client call backs and billing).
An independent 3 branch practice based in Lancashire is looking for a locum vet. Hours are 9am to 6pm with one late shift hours 2pm to 8pm. No OOH, sole charge, or weekend work. Accommodation is available. This clinic is a 24 hour hospital who offer home visits, ultrasound facilities, electrocardiography, modern operating sites, orthapedics and spinal surgery, key hole surgery full hospitalisation of patients and intensive care facilities.
Our client is looking for a full time small animal locum vet to cover the whole of August possibly longer.
This is a full time position which will include weekends on a rota basis but there are no out of hours with this position. Accommodation is available if required.


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CRT & EDU
Rona Madness
Violent Left
Vax Mandate
Biden Economy
By Frankie Stockes January 17, 2022
By Andrew White January 17, 2022
Chris Delmas/ AFP via Getty Images
By Jack Davis, The Western Journal January 16, 2022
By Gabriel Keane January 16, 2022
PA GOP Co-Chair Dick Stewart Blocked Teddy Daniels from Speaking at Candidate Event
By Cullen McCue January 16, 2022
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Free Speech News
ADL Adds 'Boogaloo' to Online Extremist Lexicon
By Lionel Du Cane January 10, 2020 at 11:42am
The ADL published an article on a term used to describe what people, referred to extremists, believe to be an upcoming civil war in America, which wasn't well-received by all, as left-anarchists took issue with some of the article's assertions.
The future civil war, or, the "Boogaloo," has been meme'd extensively to the point where it doesn't simply refer to an out-and-out civil war, but also small scale conflicts as a result of divisive policies and media outrage campaigns.
Memes concerning the so-called "Boogaloo" have mostly circulated dissident right-wing circles on social media.
In the article, the ADL starts by writing, "It's not often an old joke evolves into a catchphrase for mass violence, but that's just what's happened this past year when a variety of extremist and fringe movements and subcultures adopted the word "boogaloo" as shorthand for a future civil war."
"From militia groups to white supremacists, extremists on a range of online platforms talk about—and sometimes even anticipate—the "boogaloo." The rise of "boogaloo," and its casual acceptance of future mass violence, is disturbing. Among some extremists, it may even signify an increased willingness to engage in violence.
""Boogaloo" has its roots in decades of jokes about an old movie: the 1984 breakdancing film Breakin' 2: Electric Boogaloo. Almost from the moment of the movie's release, people exploited the format of the movie's title for humorous purposes, replacing "Breakin'" with some other film, event or person of their choice."
Extremists from militia groups to anarchists are posting online about the "boogaloo," their shorthand for a future civil war. White supremacists have also adopted the term to promote race war or white revolution. Our experts explain: https://t.co/2SytTVENkI
— ADL (@ADL) November 26, 2019
As previously mentioned, the article wasn't well-received by all.
The article says: "The boogaloo meme has spread to other movements with anti-government beliefs, primarily minarchists and anarcho-capitalists, which are essentially conservative alternatives to anarchism, as well as a few apparent anarchists. Use of the term by adherents of these philosophies often refers to violence against the state and its institutions, especially law enforcement."
For a change, those who took the most issue with the content wasn't the dissident right, but left-anarchists wishing to disassociate themselves from anarcho-capitalists–a form of right-wing anarchism.
"anarcho-capitalist" is a misnomer for people who equate property with freedom. They are known for sympathizing with fascists more than with radical egalitarians
— Millenarian Millennial Reloaded (@PraxisMaximus) November 26, 2019
https://twitter.com/koshersemite/status/1199452465952968709
The article makes a distinction between other factions vying for a meme'd boogaloo, stating:
White supremacists have also adopted the boogaloo concept. A particularly disturbing boogaloo t-shirt (currently available online) features the word boogaloo under a photograph of John Earnest, the white supremacist who opened fire at a synagogue in Poway, California, in April 2019, killing one person.
ADL Writes Letter Begging Fox News To Stop Tucker Carlson's January 6 Documentary Before It Airs
Whereas the militia movement, radical gun rights activists typically promote the boogaloo as a war against the government or liberals, white supremacists conceive of the boogaloo as a race war or a white revolution. Some promote boogaloo-related phrases alongside hashtags such as #dotr or #DayOfTheRope, both of which are references to neo-Nazi William Pierce's The Turner Diaries, a novelized blueprint for a white revolution.
Accelerationist white supremacists are particularly apt to use "boogaloo" – they seek the violent collapse of modern society in order to bring about a new, white-dominated world. Among them is Paul Nehlen, who gained notoriety by running for U.S. Congress in Wisconsin in 2016 and 2018. After the Poway synagogue shooting, Nehlen embraced both accelerationism and the term boogaloo and has even posted photos of himself wearing the John Earnest/boogaloo shirt.
The ADL has developed a reputation for adding other memes to their website for their altered meanings such as Pepe The Frog and the OK Sign–both starting out as supposedly innocuous apolitical symbols.
Other memes such as 'We Wuz Kangz' and '13/50′ were added to a hate list on the ADL website last year.
Submit a Correction →
ADL, Boogaloo
Lionel Du Cane
Summary Recent Posts Contact
He is the author of The Clowning of America: Woke Capital, Con Inc, & Meme Culture and A Matter of Time: How Time Preferences Make or Break Civilization - a book on how healthy societies view the concept of time .. If you enjoy his work, you can tip him on Kofi or support him on Patreon.
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Rani Khedira rejects Tunisia for the world cup in Russia
February 8, 2018 Anthony Craig No comments
Rani Khedira promised to make a decision on playing for Tunisia at the world cup in Russia soon. And the decision has been made.
Khedira has informed the Tunisian football association that he won't wear the colours of Tunisia at the world cup.
The reasons for rejecting Tunisia
Khedira said that he considered language barriers, time and fairness to the players that qualified for the world cup.
"I was born and raised in Germany, I only speak German, that was crucial," he explained.
"My game is about communication, instructions and tactics, time is too short, it's too difficult, I can not help the team with my best performance."
And finally, he wanted to be fair to other players on the team, "they have been performing for the past two years. I do not want to take the place from any of them."
Khedira emphasised It was not an easy decision for him, "It has been a long process with my surrounding, my dad is a proud Tunisian, I carry both countries in my heart and wish them the best, but in the end, it was the right decision."
I applaud Khedira for his fairness and objectivity. It takes courage to reject a chance to play at the world cup.
Given the circumstances he enumerated above, it is understandable why he rejected Tunisia.
TagsRani KhediraRussiaTunisia
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Tunisia seek Rani Khedira for the world cup in Russia.
November 21, 2017 Anthony Craig


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Seinfeld Back on NBC's Post-Leno Thursday Schedule, Sort Of
NBC has set its post-Leno 10 p.m. schedule and Jerry Seinfeld is coming back to Thursday nights–sort of, reports The Wrap.
The Seinfeld-produced comedy reality series "The Marriage Ref" will air Thursdays at 10 p.m. beginning March 4 (it will also get a post-Olympics closing ceremony preview on Feb. 28.)
Ron Howard's new drama "Parenthood" will take the Tuesday 10 p.m. slot, and "Law & Order" will go into the Monday slot while spin-off "Law & Order: SVU" takes over Wednesdays.
Newsmagazine "Dateline" gets the Friday slot, from 9-11 p.m. At 8 p.m. the network is putting a Lisa Kudrow-produced reality series "Who Do You Think You Are?"
–Elizabeth Jensen
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