text:
\section{Introduction}
The image quality in low-light or under-exposure conditions is often unsatisfactory, so image/video enhancement in low light has been an active research topic in computer vision.
However, it is challenging due to strong noise, detail loss, non-uniform exposure, \textit{etc}.
These problems become even more serious in videos taken from dynamic scenes. In this paper, in contrast to low-light, we loosely call bright-light and day-light images/videos/events \textit{normal-light} images/videos/events.

Most of fully-supervised deep-learning based low-light video enhancement (LLVE) methods~\cite{FeifanLv2018MBLLENLI,HaiyangJiang2019LearningTS,RuixingWang2021SeeingDS} or video reconstruction methods~\cite{TianfanXue2019VideoEW,XintaoWang2019EDVRVR,TakashiIsobe2020VideoSW,PengDai2022VideoDW} are based on the multi-frame alignment-and-enhancement framework.
This pipeline firstly utilizes some techniques, \textit{e.g.}, 3D convolution~\cite{FeifanLv2018MBLLENLI,HaiyangJiang2019LearningTS}, deformable convolution~\cite{TakashiIsobe2020VideoSW,PengDai2022VideoDW}, or flow-based alignment~\cite{TianfanXue2019VideoEW}, to align the temporal information from adjacent frames to the reference frame, and then uses an enhancement network for noise removal and illumination correction (see Fig.~\ref{fig:index}(a)).
However, when facing extreme low light or significant motion in videos, these algorithms may produce multi-frame fusion artifacts in the predicted images (see the results of SDSDNet in Fig.~\ref{fig:index}(c)).

Existing methods face some potential difficulties. First, sensor noise is not negligible in low signal-to-noise low-light scenarios.
This noise hinders the network from learning the alignment of temporal features.
Second, the interference between strong noise and image details causes the enhancement network to remove some image details inevitably.

In this paper, inspired by the low latency and high dynamic range of events, we use synthetic
events to guide the enhancement and restoration of low-light videos.
In general, events are captured by event cameras (e.g., DAVIS240C~\cite{EliasMueggler2017TheED}), which contain sparse and asynchronous intensity changes of the scene, instead of the color and intensity as in normal images.
Recently, Gehrig \textit{et al.}~\cite{Gehrig_2020_CVPR} present a method that can convert videos recorded with conventional cameras into synthetic realistic
events.
The pioneering work applying event information to low-light enhancement is SIDE ~\cite{SongZhang2020LearningTS}.
However, their work studies the transformation from real events to single images, and due to the difficulty of collecting real event-image pairs, it is an unpaired learning method.
Differently, we focus on the fusion between synthetic enhanced events and video frames, where the synthetic events and frames are paired.

Unlike the conventional two-stage video reconstruction/enhancement pipeline, we propose a three-stage LLVE pipeline with the guidance of synthetic events: 1) event synthesis and restoration; 2) event-image fusion; 3) low-light enhancement (see Fig.~\ref{fig:index}(b)).
The first stage is event-to-event, aiming to obtain normal-light events from low-light events.
Due to the sparsity of events and the interpolation of fast motion by an event synthesis algorithm, our network can restore normal-light events well and solve the problems of noise, color shift, and detail loss based on the enhanced events (see Fig.~\ref{fig:challengs}).

\begin{figure}[!t]
		\centering
		\includegraphics[
		 width=0.48\textwidth]{challenges.pdf}
		\caption{Challenges of low-light image/video enhancement. When comparing the events of normal-light images and low-light images, we find that low-light enhancement faces challenges of strong noise, color shift, and detail loss. These
       problems are hard to notice in normal-light images, but are apparent in the event voxels.}
		\label{fig:challengs}
\end{figure}

Different from most event-image fusion methods~\cite{StefanoPini2018LearnTS,StefanoPini2019VideoSF,JinHan2020NeuromorphicCG,GenadyPaikin2021EFINetVF,he2022timereplayer}, which combine event and image features by simply concatenating them, we design a novel Event and Image Fusion Transform (EIFT) module for better fusing the sparse event features and image features in the second stage of our pipeline.
And in the last stage, we design an Event-Guided Dual Branch (EGDB) module
for low-light enhancement.
Using the mask generated by the enhanced events, the image can be divided into areas with little change and areas with sharp change during a period of time.
Moreover, the proposed global branch and local branch in EGDB can deal with these two kinds of areas, respectively.
A transformer network is used in the global branch to capture global illumination information.

In summary, we make the following contributions:
\begin{itemize}
  \item A novel three-stage pipeline with the guidance of synthetic events for low-light video enhancement is proposed. It consists of event synthesis and restoration, event image fusion, and low-light enhancement.

  \item We design a novel Event and Image Fusion Transform (EIFT) module for event-image fusion and an Event-Guided Dual Branch (EGDB) module for low-light enhancement.

  \item Extensive experiments on both synthetic and real LLVE datasets show that our method outperforms both the state-of-the-art (SOTA) low-light video and single image enhancement approaches.

\end{itemize}

\section{Related Work}

This section discusses the most related methods, including low-light video enhancement, event-image fusion, and low-level vision Transformers.

\noindent
\textbf{Low-Light Video Enhancement (LLVE).}
This line of work focuses on how to utilize temporal information from adjacent frames. They can be divided into paired learning and unpaired learning.
In the former, most methods use the alignment-and-enhance framework for LLVE.
Lv \textit{et al.}~\cite{FeifanLv2018MBLLENLI} and Chen \textit{et al.}~\cite{ChenChen2019SeeingMI} use 3D convolution and their networks can combine temporal information from image sequences.
Wang \textit{et al.} use a mechatronic system to collect a dataset named SDSD, where the normal-light and low-light image pairs are well aligned~\cite{RuixingWang2021SeeingDS}.
They also use deformable convolutions in the multi-frame alignment stage.
Some approaches try to solve the LLVE problem by combining an image-based model with temporal consistency loss~\cite{ChenChen2019SeeingMI,SongZhang2020LearningTS}.
However, most of the temporal consistency losses in LLVE~\cite{FanZhang2022LearningTC} or other video restoration tasks~\cite{MingHsuanYang2018LearningBV,HengyuanZhao2021TemporallyCV} are optical-flow based, which may be limited by the error in optical flow estimation.
As for unpaired learning methods, to solve the lack of data problem, Triantafyllidou \textit{et al.}~\cite{triantafyllidou2020low} convert normal-light videos to low-light videos using two CycleGAN~\cite{JunYanZhu2017UnpairedIT} networks.
In this framework, normal-light videos are first converted into long exposure videos and then into low-light videos.

\noindent
\textbf{Event-Based Image/Video Reconstruction.}
The event camera can handle high-speed motion and high-dynamic scenes because of its dynamic vision sensor.
Therefore, events can be applied to image or video reconstruction tasks including video deblurring~\cite{jiang2020learning}, super-resolution~\cite{han2021evintsr,jing2021turning}, joint filtering~\cite{wang2020joint}, and tone mapping~\cite{simon2016event,JinHan2020NeuromorphicCG}.
Our work is the first to explore the application of synthetic events in the low-light video enhancement task.

\noindent
\textbf{Event-Image Fusion.}
Event features and image features are of different modals, with different characteristics.
Event features reflect motion changes, so most values in the scene at a certain moment are zero.
Image features in low light contain both strong noise and scene structure.
Most works simply concatenate or multiply event features and image features~\cite{StefanoPini2018LearnTS,StefanoPini2019VideoSF,JinHan2020NeuromorphicCG,GenadyPaikin2021EFINetVF,he2022timereplayer,Tomy2022fusingevent}.
Han \textit{et al.}~\cite{JinHan2020NeuromorphicCG} fuse the low-dynamic-range image features and the event features for high-dynamic-range image reconstruction.
He \textit{et al}.~\cite{he2022timereplayer} concatenate the optical flow, event, and image together for video interpolation.
Tomy \textit{et al.}~\cite{Tomy2022fusingevent} multiply the multi-scale image and event features for robust object detection.
Very recently, Cho \textit{et al.}~\cite{cho2022Eif} design an event image fusion module for depth estimation.
The differences between these methods and our work are: 1) we deal with the LLVE task; 2) they mainly use image features to densify sparse event features, while in our work, event and image features enhance each other for restoration.

\noindent
\textbf{Low-Level Vision Transformers.}
In recent years, Transformers have been applied in many low-level visual tasks, and they can be divided into multi-task and task-specific Transformers.
For multi-task Transformers, Chen \textit{et al.}~\cite{chen2020pre} and Li \textit{et al.}~\cite{li2021efficient} propose IPT and EDT, respectively, which are pre-trained on several low-level vision tasks.
Wang \textit{et al.}~\cite{ZhendongWang2021UformerAG} and Zamir~\cite{Zamir2021Restormer} design U-Net-like Transformer architectures for denoising, deblurring, deraining, \textit{etc}.
Task-specific Transformers also obtain state-of-the-art performances in many applications including super-resolution~\cite{FuzhiYang2020LearningTT,chen2022activating}, deraining~\cite{Jie2022idt,Liang_2022_CVPRw}, and inpainting~\cite{yan2020sttn}.
In our paper, we use Transformer in the enhancement stage to deal with the areas in the videos without fast motion.

\section{Method}
In this section, we first describe our overall pipeline and then present the three stages of our method, including event synthesis and restoration, event-image fusion, and low-light enhancement.

\begin{figure}[!t]
		\centering
		\includegraphics[
		 width=0.47\textwidth]{overallnetwork.pdf}
		\caption{Architecture of our overall network. The original event voxels pass the event restoration network and generate the restored event voxels. And the low-light image and the restored event voxels are combined to obtain the final enhanced normal-light results.}
		\label{fig:overallnet}
\end{figure}

As shown in Fig.~\ref{fig:overallnet}, firstly, the original event voxels are obtained by synthesizing light sequences (Sec. 3.1). And the restored event voxels are generated from a U-Net (Sec. 3.1).
The image and the restored event voxels are encoded to deep features, fused by the EIFT module (Sec. 3.2) and enhanced by the EGDB module (Sec. 3.3).
Finally, the decoder outputs the enhanced images.

\subsection{Events Synthesis and Restoration}
\textbf{Event Synthesis.} To synthesize original event voxels, we have the following three steps: frame upsampling, event generation, and event voxel generation.
In the \textbf{first} step, we use an off-the-shelf up-sampling algorithm~\cite{xiang2020zooming} to get $N'$ up-sampled frames (with $N'$ adaptively chosen) from $N$ frames ($N' > N$).
In the \textbf{second} step, two adjacent frames (from $N'$ frames) are subtracted to obtain $d_{x,y,t}$, and whether an event $e_{i}$ is generated is determined by the difference.
If $d_{x_{i}, y_{i}, t_{i}}$ exceeds a threshold, we generate an event $e_{i} = \left(x_{i}, y_{i}, t_{i}, p_{i}\right)$, where $(x_{i}, y_{i})$ and $t_{i}$ are the location and time of the event and $p_{i} = \pm 1$ $(p_{i}  d_{x_{i}, y_{i}, t_{i}} > 0)$.
We use one threshold for low-light events (set to 2) and another for normal-light events (set to 5).
This is because setting a higher threshold when generating low-light events will lose some useful events.
In the \textbf{third} step, in order to make the events processed by neural networks better, it is necessary to convert the discrete event values $\{0,+1,-1\}$ into floating-point event voxels.
Following ~\cite{zhu2019unsupervised,weng2021event}, we generate the voxels $E \in \mathbb{R}^{B \times H \times W}$ as:
\begin{small}
\begin{equation}
E_{k}\! =\! \sum^{n}_{i=0} p_{i} \max \left( \! 0,1 \! - \!\left|k \! - \! \frac{t_{i}\! - \! t_{0}}{t_{n}\! -\! t_{0}}(B \! - \! 1)\right|\right), \ k\in \{1,...,B\},
\label{eq:evvoxel}
\end{equation}
\end{small}%
where $t_{0}$ and $t_{n}$ denote the start and end moments of the events, respectively. $B$ equals to $2N \times 3$, where $N$ is the input frame number, 2 corresponds to the positive and negative event voxels, and 3 corresponds to the r-g-b color channels.
This equation shows that we use temporal bilinear interpolation to obtain $B$ voxels of the event temporal information.

\textbf{Event Restoration.} In the event restoration, we aim to generate restored events from the original events using an CNN.
To the best of our knowledge, there is no available neural network to transfer low-light events to normal-light event voxels.
We design a network (see the supplementary materials) that is able to predict an event probability map $ P \in \mathbb{R}^{B \times H \times W}$ and an event voxel map $V\in \mathbb{R}^{B \times H \times W} $ simultaneously.
Finally, the restored event voxels are calculated as:
\begin{equation}
E^{r}=M(P) V ,
\end{equation}
where the element $M_{i}(P_{i})$ of $M(P)$ is 1 when $P_{i} \ge 0.5$ and 0 otherwise.
The loss functions that constrain $M$ and $V$ will be described in Sec. 3.4.

\begin{figure*}[!t]
		\centering

		\includegraphics[ width=0.88\textwidth]{fusionv2.pdf}
		\caption{Architecture of the EIFT module. All the ReLU layers are omitted for clarity.}
		\label{fig:fusionblock}
\end{figure*}

\subsection{Event-Image Fusion}
Different from most event-image fusion methods~\cite{StefanoPini2018LearnTS,StefanoPini2019VideoSF,JinHan2020NeuromorphicCG,GenadyPaikin2021EFINetVF,he2022timereplayer}, which combine event and image features by concatenating them simply, we design a novel Event and Image Fusion Transform (EIFT) module for better fusing the sparse event features and dense image features.
Our EIFT is based on the mutual attention mechanism, where the event features and the image features modulate each other.
Specifically, the event feature modulates the image feature by hinting where fast motion happens and distinguishing between strong noise and image details; the image feature modulates the event feature by introducing the color or semantic information.
In our EIFT, such modulation is achieved by generating the channel transform map and the spatial attention map from the modulated features. The maps have values between 0 and 1 indicating the importance of every element.

Fig.~\ref{fig:fusionblock} is the designed network structure of EIFT. Each EIFT module contains two EIFT blocks.
In the first block, $F^{0}_{E}$ and $F^{0}_{I}$ serve as the main feature and the modulation feature, respectively.
Inspired by~\cite{Zamir2021Restormer}, to reduce computational complexity, our modulation is divided into cross-channel transform (CCT) and element-wise product (EWP).
In CCT, the modulation feature passes two parallel convolution blocks and generates $
{Q} \in \mathbb{R}^{H W \times C}$ and $ {K} \in \mathbb{R}^{C \times H W}$.
The dot product of $K$ and $Q$ is performed, and the Softmax function is applied to generate a $C \times C$ channel transform map. Then it is multiplied by the main feature. The whole CCT can be formulated as:
\begin{equation}
{X} = f_{1}(F_{E}) \cdot \operatorname{Softmax}\{f_{3}(f_{2}(F_{I})) \cdot f_{4}(f_{2}(F_{I}))\}.
\label{eq:s1}
\end{equation}

In EWP, the modulation feature first passes through some convolution blocks to generate a spatial attention map. And the element-wise multiplication product between the spatial attention map and the main feature is carried out, which can be formulated as:
\begin{equation}
F=\sigma\left(f_{5}(X)\right) \odot f_{6}(f_{2}(F_{I})).
\label{eq:s2}
\end{equation}
$f_{i}$ in Eqn.~\ref{eq:s1} and Eqn.~\ref{eq:s2} are the convolution blocks indicated in Fig.~\ref{fig:fusionblock}. $\sigma$ and $\odot$ denote the Sigmoid function and the element-wise production, respectively.

In the second EIFT block, the inputs (outputs of the first EIFT block) are swapped, where $\tilde{F}^{n}_{E}$ is the modulation feature and $\tilde{F}^{n}_{I}$ is the main feature. The final outputs of the EIFT module are $F^{n}_{E}$ and $F^{n}_{I}$ for the $n$-th EIFT module. In this paper, $n$ is set to $2$.

\subsection{Low-Light Enhancement}

In low-light image/video enhancement, illumination estimation/enhancement is important.
The previous LLVE methods often process the whole image using convolution networks.
However, the difficulties for illumination enhancement in areas with little motion and in areas with fast motion are quite different.
Especially when there is fast motion, where the illumination will change, the estimated illumination is often inaccurate.
We make two improvements: 1) we use two branches to deal with these two kinds of areas (with fast motion, and without fast motion) respectively for illumination enhancement; 2) we use a Transformer to enhance the brightness.

\textbf{Mask Generation.} Given the restored event voxels, $E^{r} \in \mathbb{R}^{(2N \times 3) \times H\times W}$, generated from the first stage (Sec. 3.1), we use the positive voxels $E^{r,+} \in \mathbb{R}^{(N \times 3) \times H\times W}$ for generating the mask $M'$, which is computed by:
\begin{equation}
\begin{aligned}
M_{c} = \operatorname{max}\{ E^{r,+}_{c,1},E^{r,+}_{c,2},...,E^{r,+}_{c,N}\}, \ c \in \{r,g, b\},
\end{aligned}
\end{equation}
\begin{equation}
M' = \operatorname{max}\{M_{r},M_{g},M_{b}\} \in \mathbb{R}^{H \times W},
\end{equation}
where $M'$ is then resized to the same resolution as the input of EGDB.
Finally, $M'$ is changed to a binary 0-1 mask with a threshold 0.9.

\textbf{Network Details.} In Fig.~\ref{fig:enhancementnet}, EGDB consists of a global branch and a local branch.
In the global branch, we first concatenate the $F^{n}_{E}$ and the masked image feature $(1-M')F^{n}_{I}$ from the event-image fusion stage and perform the adaptive average pooling to get the feature $F \in \mathbb{R}^{32 \times 32 \times 2C}$.
Because of the color uniformity and texture sparsity of these kinds of areas, down-sampling can reduce network parameters without loss of performance.
The feature $F$ is then reshaped, splited into $m$ feature patches $F_{i} \in \mathbb{R}^{ p ^{2} \times 2C}, i=\{1, \ldots, m\}$, where $p$ is the patch size and $m=\frac{H}{p} \times \frac{W}{p}$, and passes a self-attention layer and a feed-forward layer of the conventional Transformer~\footnote{See the supplementary materials for more network details.}.
The global branch outputs $F_{g}$ with the same size of $F^{n}_{E}$.
The local branch with two residual blocks receives $M'F^{n}_{I}$ and outputs the feature $F_{l}$.
Finally, the EGDB module outputs $F_{c}$, which is the concatenation of $F_{g}$ and $F_{l}$.

\subsection{Training and Loss Functions}
The training contains two stages.
In the first stage, with the low-light event voxels and the normal-light event voxels, we train the event restoration network using
\begin{equation}
L_{s1}=L_{m}+\lambda_{1} L_{v},
\end{equation}
where the first term is the binary cross-entropy loss between the predicted event probability map $P$ and the binary normal-light voxel mask $M^{G}$ (generated by the normal-light event voxel ground truth $G$ with a threshold 0.1):
\begin{equation}
L_{m}\!=\!-\frac{1}{H W}\! \sum_{i=1}^{H W} M^{G}_{i} \! \log \left(P_{i}\right)+\left(1 \! -\! M^{G}_{i}\right) \! \log \left(1\! -\! P_{i}\right),
\end{equation}
where $P_{i} \in P$ and $M^{G}_{i} \in M^{G}$. The second term $L_{v}$ is the $L_{1}$ loss between $E^{r}$ and $G$.

After the first stage, the parameters of the event restoration network are fixed, and the other networks are trained. The loss function is defined as:
\begin{equation}
L_{s2}=L_{1}+\lambda_{2} L_{vgg},
\end{equation}
where $L_{1}$ and $L_{vgg}$ are respectively the $L1$ loss and the perceptual loss~\cite{johnson2016perceptual} between the predicted normal-light image and its ground truth.

\label{sec:basicnetwork}

\begin{figure}[!t]
		\centering

		\includegraphics[ width=0.47\textwidth]{enhancementv4.pdf}
		\caption{Architecture of the EGDB module with the global branch (upper part) and the local branch (bottom part). All the ReLU layers are omitted for clarity.}
		\label{fig:enhancementnet}
\end{figure}

\section{Experiments and Analysis}
\label{sec:exp}
In this section, we conduct an ablation study and compare with state-of-the-art methods.

\subsection{Datasets and Implementation Details}
\textbf{Datasets.} For a real low-light video dataset, we adopt SDSD~\cite{RuixingWang2021SeeingDS} which contains 37,500 low- and normal-light image pairs with dynamic scenes.
SDSD has an indoor subset and an outdoor subset.
For a fair comparison, we use the same training/test split as in~\cite{RuixingWang2021SeeingDS}.
We do not consider the real LLVE datasets which are not released~\cite{HaiyangJiang2019LearningTS,WangWei2019EnhancingLL} or only contain static scenes~\cite{ChenChen2019SeeingMI}.
In order to have experiments on more scenes and data, following the work~\cite{triantafyllidou2020low}, we also perform experiments on Vimeo90k~\cite{TianfanXue2019VideoEW}.
We select video clips whose average brightness is greater than 0.3 (the highest brightness is 1) as normal-light videos, and then use the method in ~\cite{lv2021attention} to synthesize low-light video sequences~\footnote{More details are shown in the supplementary materials.}.
We finally get 9,477 training and 1,063 testing sequences, each with 7 frames, from Vimeo90k.

\textbf{Implementation Details.} We implement our method in the PyTorch~\cite{AdamPaszke2019PyTorchAI} framework, and train and test it on two 3090Ti GPUs.
The network parameters are randomly
initialized with the Gaussian distribution.
In the training stage, the patch size and batch size are 256 and 4, respectively.
We adopt the Adam~\cite{DiederikPKingma2014AdamAM} optimizer with momentum set to 0.9.
The input number of frames $N$ is set to 5.

\begin{table}[t]
\centering\small
  \vspace{-2mm}
\resizebox{8.6cm}{!}{
\begin{tabular}{clcccc}
\toprule
\multicolumn{1}{l}{}                                                           &         & PSNR$\uparrow$  & SSIM$\uparrow$ & LPIPS$\downarrow$ & Network Size \\ \midrule
\multirow{8}{*}{\begin{tabular}[c]{c}Image-based\\ method\end{tabular}}  & DeepUPE & 21.82 & 0.68 & --      &     0.59M   \\
                                                                               & ZeroDCE & 20.06 & 0.61 &  --     &   0.08M     \\
                                                                               & DeepLPF & 22.48 & 0.66 &  --     &   1.77M    \\
                                                                               & DRBN    & 22.31 & 0.65 &   --    &  1.12M \\
                                                                               & Uformer* & 23.46 & 0.72 &  0.202     &  20.4M        \\
                                                                               & STAR*    &  23.39     &   0.70   & 0.283  &  0.03M            \\
                                                                               & SCI*      &  19.67     &   0.69  &  0.298    &  0.01M            \\
                            & LLFlow*      &  24.90     &   0.78  &   0.182   &  5.43M         \\
                                                                               \midrule
\multirow{5}{*}{\begin{tabular}[c]{c}Video-based \\ method\end{tabular}} & MBLLVEN & 21.79 & 0.65 &  0.190     &   1.02M           \\
                                                                               & SMID    & 24.09 & 0.69 &   0.213    &   6.22M     \\
                                                                               & SMOID   & 23.45 & 0.69 & 0.187   &  3.64M            \\
                                                                               & SDSDNet & 24.92 & 0.73 & 0.138  &          4.43M    \\
                                                                               & SGZSL*   &  23.89 &  0.70    & 0.308   &   28.1M     \\
                         \midrule
\multicolumn{1}{l}{}                                                           & Ours    & \bf{25.81} & \bf{0.80} &  \bf{0.126}  & 3.51M  \\
\bottomrule
\end{tabular}}
  \caption{Quantitative frame-based low-light enhancement comparison on SDSD~\cite{RuixingWang2021SeeingDS}. The best results are in \textbf{bold}. * denotes methods implemented by us using their official models and other results are cited from~\cite{RuixingWang2021SeeingDS}.}
\end{table}

\begin{table}[t]
  \centering\small
  \resizebox{7.9cm}{!} {
  \begin{tabular}{c|cccc}
    \toprule
      Model&PSNR$\uparrow$ & SSIM $\uparrow$ & LPIPS $\downarrow$ & Network size\\
    \midrule
      ZeroDCE&24.56 & 0.7533& 0.202 & 0.08M\\
      STAR& 24.72 & 0.7595 & 0.195 & 0.03M \\
      Uformer& 30.29 & 0.9203 &  0.058 & 20.4M\\
      MBLLVEN&27.06 & 0.8706 &0.083 & 1.02M \\
      SMOID& 29.74 & 0.9239 & 0.059& 3.64M \\
      SDSDNet&29.06& 0.9233&  0.064& 4.43M\\
      Ours& \textbf{30.53} & \textbf{0.9254} & \textbf{0.038}   & 3.51M \\
    \bottomrule
  \end{tabular}}
  \label{tab:vimeo90k}
\caption{Quantitative frame-based low-light enhancement comparison on the Vimeo90K dataset.}
\end{table}

\begin{table}[t]
  \centering\small

  \resizebox{5.2cm}{!} {
  \begin{tabular}{c|ccc}
    \toprule
      Model&FID$\downarrow$&Warping Error$\downarrow$\\%&MABD$\downarrow$\\
      \midrule
      MBLLVEN&0.533& 2.98 \\%& 0.0133 \\
      SMID & 0.552 & 2.85 \\%& 0.0170 \\
      SMOID& 0.521& \underline{2.62}\\
      SDSDNet&\textbf{0.368}&4.36\\
      SGZSL&0.722&6.13 \\
      Ours& \underline{0.370}& \textbf{2.61}\\
    \bottomrule

  \end{tabular}}
    \caption{Quantitative video-based low-light enhancement
comparison on the SDSD dataset. The best results are in \textbf{bold} and the second best are \underline{underlined}.}
  \label{tab:videosdsd}
\end{table}

 \begin{figure*}[!t]
		\centering

		\includegraphics[ width=0.91\textwidth]{comparisonresultv2.pdf}
		\caption{Visual comparison between other SOTA methods and ours on two patches of one example from SDSD. The numbers are PSNR values on the whole image.}
		\label{fig:resultsdsd}
\end{figure*}

\subsection{Comparison with State-of-the-Arts.}\textbf{State-of-the-Art Methods.}
We compare our work with seven low-light single image enhancement methods (DeepUPE~\cite{RuixingWang2019UnderexposedPE}, ZeroDCE~\cite{ChunleGuo2020ZeroReferenceDC}, DeepLPF~\cite{SeanMoran2020DeepLPFDL}, DRBN~\cite{WenhanYang2020FromFT}, STAR~\cite{ZhaoyangZhang2021STARAS}, SCI~\cite{LongMa2022TowardFF} and LLFlow~\cite{YufeiWang2022LowLightIE}, one SOTA transformer-based general image restoration method (Uformer~\cite{ZhendongWang2021UformerAG}), and five low-light video enhancement methods (MBLLVEN~\cite{FeifanLv2018MBLLENLI}, SMID~\cite{ChenChen2019SeeingMI}, SMOID~\cite{HaiyangJiang2019LearningTS}, SDSDNet~\cite{RuixingWang2021SeeingDS} and SGZSL~\cite{ShenZheng2022SemanticGuidedZL}).
In these methods, SCI and Zero-DCE are un-supervised, and the models marked by $*$ in Table 1 and all the models in Table 2 are implemented using their official models on the corresponding datasets.

\textbf{Quantitative Results.}
For frame-based comparison, we use PSNR and SSIM~\cite{ZhouWang2004ImageQA}, and Learned Perceptual Image
Patch Similar (LPIPS)~\cite{zhang2018perceptual} to compare the restored images.
For video-based comparison, we adopt FID and Warping Error for video-based methods. These two metrics can well reflect the quality and stability of the predicted videos.
As shown in Table 1 and Table 2, our method obtains the best performances on both SDSD and Vimeo90K for frame-based comparisons.
For video-based comparison, our method gets the 2nd on FID (only 0.002 lower than the best method) and the 1st on Warping Error without using any stability loss like SMID.

\textbf{Qualitative Results.} In Fig.~\ref{fig:resultsdsd}, we show visual comparisions on SDSD. Most single-image enhancement methods either produce some noise (DeepLPF, ZeroDCE, Uformer and STAR) or have color shift (DeepUPE and SCI).
As for the video-based methods, SMID does not restore the color well, SMOID blurs the details. The deviation of noise map estimation by SDSDNet results in a certain degree of noise in the prediction.
With the help of events, our method restores the color and removes the noise simultaneously.
We show other visual results on Vimeo90K in the supplementary materials, where ours also outperforms the others.

\begin{table}[t]
  \centering\small

  \vspace{-2mm}

  \resizebox{6.9cm}{!} {
  \begin{tabular}{c|ccc}
    \toprule
      Model&PSNR $\uparrow$&SSIM$\uparrow$&LPIPS$\downarrow$\\
      \midrule
      EIFT $\rightarrow$ UNet & 25.54 & 0.79& 0.135\\
      W/o CCT&25.46 & 0.78 & 0.141\\
      W/o EWP &25.52 &0.79 &0.138\\
      \midrule
      W/o Event Guidance &25.49 & 0.78 & 0.143\\
      W/o Global Branch &25.34 & 0.77 & 0.167\\
      W/o Local Branch &25.42 & 0.78 & 0.162 \\
      \midrule
      PCD+EGDB (W/o EG) & 24.27 & 0.73 & 0.185\\
       \midrule
      Full Model & \bf{25.81} & \bf{0.80} & \bf{0.126}\\

    \bottomrule

  \end{tabular}}
  \vspace{-2mm}
  \caption{Ablation study on SDSD. EG: event guidance.}
  \label{tab:abstudy}
\end{table}

\subsection{Ablation Study}
In this section, we do an ablation study based on the SDSD dataset and show the results in Table~\ref{tab:abstudy}.

\subsubsection{Network Architecture.}
First, we analyze the effectiveness of the network architecture.

\textbf{EIFT}. We construct three models: 1) EIFT $\rightarrow$ UNet. We replace the EIFT module with
the UNet~\cite{OlafRonneberger2015UNetCN} which has a similar
model size with EIFT in the event-image fusion. The two feature maps, $F^{i}_{E}$ and $F^{i}_{I}$, $i = 0,1$, are concatenated and used as the input to the UNet.
2) W/o CCT. We remove the cross-channel transform operation in EIFT.
3) W/o EWP. We remove the element-wise product operation in EIFT.
The PSNR value of these models drops 0.27dB, 0.35dB and 0.29dB respectively.
This result shows the effectiveness of our EIFT module.

\textbf{EGDB}. In the low-light enhancement stage, we also build three modified models for ablation study.
1) W/o Event Guidance, which means that the map generation block is removed and the input image features are not masked.
2) W/o Global Branch, which removes the global branch in EGDB. Note that we increase the number of the residual blocks in `W/o Global Branch' to make the network parameter amount equal to the full model.
3) W/o Local Branch, which removes the local branch in this model.
The PSNR value of these models drop 0.32dB, 0.47dB, and 0.39dB respectively.
The result shows the effectiveness of our EGDB module.

\subsubsection{Effectiveness of the Event Guidance.}
To show the effectiveness of the event guidance, we build a model named `PCD+EGDB (W/o EG)'  in Table~\ref{tab:abstudy}.
The input of this model is five consecutive frames, and the network size is similar to the full model.
The first part of `PCD+EGDB (W/o EG)' is the PCD module in~\cite{RuixingWang2021SeeingDS} and the EGDB module of the second part is without the events (the same as W/o Event Guidance).
We can see that the PSNR decreases sharply by 1.54dB, which shows the effectiveness of the event guidance and our pipeline.

\begin{figure}[!t]
\centering
    \includegraphics[width=0.46\textwidth]{eventillust.pdf}
   \caption{Illustration of how the synthetic events help the restoration of low-light videos. EG: event guidance.}
     \label{fig:eventsillust}
\end{figure}

\subsection{Visualization of the Restored Event Voxels.}
In Fig.~\ref{fig:eventsillust}, we give some results of restored event voxels to show how the restored events help to enhance the low-light videos.
On the low-light voxels in the top row, we can see that the events contain noise and color shift.
Our event restoration network successfully removes these artifacts.
Our result has much fewer artifacts compared with the prediction of `PCD+EGDB (w/o EG)'.
The bottom row example demonstrates that with less noise in the restored events, our result is sharper and keeps better details.

\subsection{Generalization to Other Real Videos}
 \begin{figure}[!t]
		\centering
		\includegraphics[ width=0.46\textwidth]{llveloli.png}
		\caption{Visual comparison between some SOTA methods and ours on the Loli-Phone dataset.}
		\label{fig:resultloli}
\end{figure}

To verify the generalization ability of our method on other real low-light videos, we also test it and some SOTA low-light enhancement methods (including MBLLVEN, SMOID, KinD++~\cite{YonghuaZhang2021BeyondBL}, RetinexNet~\cite{ChenWei2018DeepRD}, and RRDNet~\cite{AnqiZhu2020ZeroShotRO}) on the Loli-Phone dataset (without ground truth)~\cite{LoLi}.
Two examples are shown in Fig.~\ref{fig:resultloli}. From the images, we can see that the enhancement of low-light videos by MBLLVEN and RRDNet is limited.
KinD++ and RetinexNet produce some color artifacts.
The results of SMOID contain multi-frame fusion artifacts (zooming in to see the upper left part of the first result by SMOID).
The prediction by our method does not have the issues of those methods.
Another advantage of our method is that with the help of events, it better deals with the white balance problem in low light.
Under natural light, the floor and wall should appear white or gray. However, the results predicted by other methods are yellowish, while our results are gray.

\section{Conclusions}
We propose to use synthetic events as the guidance for low-light video enhancement.
We design a novel Event and Image Fusion Transform (EIFT) module for event-image fusion and an Event-Guided Dual Branch (EGDB) module for low-light enhancement.
Our method outperforms both the state-of-the-art low-light video and single image enhancement approaches.
It takes extra time to synthesize the events (about 20$\%$ of the total inference time).
Future work includes exploring better ways to restore the events in low-light conditions and fusing events and images.

redpajama_set_name: RedPajamaArXiv


As a mom my heart melts when I think about first days of school. So many apron strings to cut, so many mama hearts breaking as they see their babies walk away and into the world.
Apron Strings: In past centuries, toddlers wore aprons or pinafores to keep their clothes clean. These aprons had a pair ribbons or tapes ("strings") sewn to the shoulders or back, which the mother would hold onto, rather like a leash. When the child was old enough to be allowed some independence, the tapes would be cut off. So, "cutting the apron strings" means becoming independent from one's mother or other protector/authority figure and going out on one's own.
Kindergarten: It's the first. That first time you let them walk on by themselves for a whole day or half a day can be tough for a mom. I can't describe it, but the feels well up and you just cry. All I could think about was "my baby","There goes my baby".
Elementary school:Each year in elementary school is tough because you are watching them grow older and older and more independent. Those personalities are meeting up with other personalities and daily making impacts on your little child. They are facing things that you have been protecting them from all these years. It's the real world for them and you.
Middle School: The middle school years or even tougher. You have to drop your child off in that hormonal, uncertain, verbal pool called Middle School. In middle school every year is different every outlook changes as fast a New York minute. Each day they are a different person, but it's all normal.
High School: Those years as freshmen, sophomores, and juniors when you let go of so much because they are ready. They are ready to put into practice what they've learned from all of those years in school. To use the knowledge, the wisdom, the decision-making skills that you have instilled in them from day one. This is the time for it all to show up, or so we hope it does. A time where they will contribute to society with those lessons learned from you, like wash your hands, be nice, no name calling, speak clearly, show respect, love your neighbor and be courteous. They are becoming men, we are seeing it right before our eyes. Our momma tear-filled eyes.
Senior Year: That senior year is another hard one, it's a lot like kindergarten because it's a last. Last drop offs, counting down the days of having daily interactions and preparing them for the "real world". It's a great year to develop and set boundaries. A time to speak of expectations and test the waters. Last days of connecting to the community, your community.
The world is filled with so many opportunities to grow and develop. Fortunately we had these children of ours to love them and let them go. To become great people and to be appreciated by others. It is time to let them go and shine.


text:
Uncertainty in Current Climate Outlook
Climate outlooks for the remainder of the fall season turned less certain this week, as the likelihood of La Nina has been reduced, explained Laura Edwards, Acting State Climatologist and SDSU Extension Climate Field Specialist.
"As of September 8, 2016 NOAA's (National Oceanic Atmospheric Administration's) Climate Prediction Center removed their La Nina Watch status, and are now favoring Neutral conditions," Edwards said.
She explained that El Nino and La Nina are generally the best long-term forecast indicators for the late fall and winter season. "For the last several months, computer models and forecasters had been projecting a weak La Nina to affect our climate in North America this winter, following the strong El Nino from earlier this year. With the status removed, it makes climate predicting a little less certain," Edwards said.
Neutral conditions means sea surface temperatures in the equatorial region of the Pacific Ocean, and other atmosphere and ocean indicators, are near the long-term average.
La Nina is when ocean waters are cooler than average in the eastern equatorial Pacific Ocean, with sustained temperatures of just under 1 degree Fahrenheit cooler than average for three consecutive months.
The climate outlook for October and the season ahead was issued by NOAA's Climate Prediction Center on September 15, 2016.
Edwards said this update continues to show warmer than average temperatures favored in South Dakota for the month ahead. "This outlook is given with a little less certainty than we had seen in previous outlooks," she said.
The precipitation outlook for October is also less clear for the state, as it is in a region that has equal probability of being wetter, drier or near average for the month.
"This could be good news for eastern region farmers who are looking for some warm and dry, or even near average rainfall, conditions to help dry down corn and soybeans for harvest," Edwards said.
She added that the outlook could be less ideal news for western and central region growers, who are looking for some rainfall to help start winter wheat this fall.
"Despite some much-needed rainfall in August, many areas could still benefit from additional moisture to recover from the significant drought that took hold this summer," she said. "Fall moisture could also help with pasture and forage conditions, and set the stage for the early spring."
Looking further ahead, Edwards said according to the Climate Prediction Center, the rest of the year could continue to be warmer than average.
"This has been a consistent feature of 2016, as the year so far has been warmer than average for South Dakota," she said.
Precipitation for the rest of the year has become more uncertain, partly due to the reduced probability of La Nina that generally affects the Northern Rockies and can spill over into the western Dakotas.
"South Dakota now sits just east of an area that is still favored to be wetter than average, with no clear signals for precipitation in our area," she said.
Since La Nina has become less likely than neutral conditions, Edwards explained that for the rest of the fall and winter season ahead, climatologists will be looking at a handful of other atmospheric and oceanic patterns.
"There are other patterns that can affect us, both from the Pacific and Atlantic Oceans, and how they drive the jet stream in the winter season," she said.
This winter, climate forecasters will likely be looking closer at some shorter term changes in the climate, on the timescales of three to four weeks to a couple of months.

redpajama_set_name: RedPajamaCommonCrawl


Why buy a used car or truck? When you choose a pre-owned car, truck, suv or van from McMinnville Honda you can be assured that our reputation and expertise stand behind our transactions. We'll always give you the lowest price possible and help find you the best finance options and packages available through our large network of banks, credit unions and other lending institutions.
Many customers have different goals like finding a quality used car for zero down or low down payment. Others want to purchase a reliable truck for their business or for towing. Perhaps you're a college student who needs a dependable preowned car that gets great gas mileage. No matter what you're looking for in price range, or style or manufacturer from Acuras, BMW, Buick, Chevrolet, Dodge, Ford, Toyota, Nissan, Mercedes Benz, Subaru...it's all here. Our online search capability and hundreds of photos make car shopping online fun and enjoyable. Our website is quick and easy to navigate, delivering you the information and specs on every preowned vehicle in stock. Our preowned used inventory is always changing so check back frequently or, even easier, give us a call and let us know what you are looking for. Chances are good that the used car or truck you're looking for could be in our detail shop awaiting it's final presentation or at another dealer who wants to trade it to us. It's no wonder that new customers and their friends and family are finding McMinnville Honda and our great selection of preowned cars. We promise we're worth the drive from Beaverton, Hillsboro, Portland and, of course, right here in McMinnville. You can also visit our preowned dealership, minutes away or online at www.hondausedcarcenter.com. With our volume of preowned vehicles and large selection it made sense to have more space and a team of Used Car buyers. Our used car managers have spent countless hours researching car values, watching demand trends at used car auctions all over Oregon and pore over the statistics and values from sources like Kelly Blue Book and other industry resources. Have a trade-in that want us to subtract from your "trade-up" vehicle? You can do it here! All this experience and willingness to earn your business equates to a smart and enjoyable preowned buying transaction.
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CARFAX One-Owner. Clean CARFAX. Crystal Black Pearl 2016 Honda Accord EX-L w/Navigation and Honda Sensing FWD CVT 2.4L I4 DOHC i-VTEC 16V One Owner Carfax, Low Mileage, Leather, 4-Wheel Disc Brakes, 7 Speakers, ABS brakes, Air Conditioning, Alloy wheels, AM/FM radio: SiriusXM, Automatic temperature control, CD player, Exterior Parking Camera Rear, Four wheel independent suspension, Front dual zone A/C, Memory seat, Navigation System, Panic alarm, Power driver seat, Power moonroof, Power steering, Power windows, Rear window defroster, Remote keyless entry, Security system, Speed control, Speed-sensing steering, Steering wheel mounted audio controls, Traction control. Recent Arrival! Odometer is 4656 miles below market average! 27/37 City/Highway MPG Awards: * ALG Residual Value Awards * 2016 KBB.com Brand Image Awards 2016 Kelley Blue Book Brand Image Awards are based on the Brand Watch(tm) study from Kelley Blue Book Market Intelligence. Award calculated among non-luxury shoppers. For more information, visit www.kbb.com. Kelley Blue Book is a registered trademark of Kelley Blue Book Co., Inc. Advertised prices exclude taxes, license, registration costs, deq fees and $115 dealer title/registration document preparation service fee. All vehicles subject to prior sale.


Sending a RFP to the Convention & Visitors Bureau is the first step in securing valuable support and services for your meeting in Asheville. Involving our staff will help you save time and make the best host property decision.
Amenity gifts for VIPs - Gifts for 2 or 4 VIPs are provided depending on your contracted room total. Gifts include locally made products.
Attraction Value Cards for all attendees - Value cards offer discounts to area attractions and businesses.
Staff member can travel prior year to promote destination to your attendees - We can help you begin promoting Asheville to your meeting attendees and help you build the highest attendance.
Gift Card to incentivize early registration - One gift card to a local business will be provided. The planner can offer the chance to win the card if attendees register for the conference by a certain date.
Qualifying meetings are eligible for CVB's Meetings Incentive Funds - If a meeting meets specific criteria, incentive funds may be available to help offset some meeting costs.
Delivery of visitor information to meeting site - CVB staff will deliver Asheville Travel Guides and maps to the meeting site.
Staffed information table (based on availability) - Staffing of a visitor information table can be provided based on availability of staff or Visitor Center volunteers.
Mention of your event in CVB partner newsletter with information on opportunities to participate - Need volunteers, local support or want to spread the word to our tourism partners? A blurb can be included in our partner newsletter.


text:
Sustainable Forest Management News
Paper giant APP failing its own sustainability goals, report alleges
by Hans Nicholas Jong 11 January 2021
JAKARTA — Activists have called on financiers and clients of Asia Pulp & Paper (APP), one of the world's biggest paper producers, to stop doing business with the company, citing…
Companies must account for quality, not just quantity, when it comes to forests (commentary)
by Julie Nash and Jamison Ervin 31 December 2020
The launch of the New York Declaration on Forests (NYDF) in 2014, with the support of nearly 200 corporate, government, NGO and Indigenous peoples and local community endorsers, put forests…
Poor governance fuels 'horrible dynamic' of deforestation in DRC
by Victoria Schneider 21 December 2020
There's a saying in the Democratic Republic of Congo (DRC) that refers to "Article 15," a nonexistent paragraph of the country's constitution during the Mobutu Sese Seko dictatorship in the…
As minister and activists trade barbs, Madagascar's forests burn
by Malavika Vyawahare 17 December 2020
A long and intense fire season is exacting a grim toll across Madagascar. At its onset in May, a wave of fires ate into the dry forests that line the…
France's tropical forest conservation efforts: an interview with AFD's Gilles Kleitz
by Rhett A. Butler 16 December 2020
Since hosting the United Nations Climate Change Conference in 2015 which resulted in the Paris Climate Agreement, France has become a leading proponent for tropical forest conservation. This effort has…
Mexico: Four decades of community lessons from the forests of Durango
by Marco A. Hernández T. 13 October 2020
As July begins, the rains become an integral part of the landscape of Santiago Papasquiaro, in the northern Mexican state of Durango. For the residents of the region, this indicates…
Madagascar minister calls protected areas a 'failure,' seeks people-centric approach
by Rivonala Razafison and Malavika Vyawahare 20 August 2020
ANTANANARIVO, Madagascar — Madagascar's protected area network has failed to improve the lives of people, the country's environment minister observed at a recent meeting, setting the stage for an overhaul of how…
Life among the turtles: Traditional people struggle inside an Amazon reserve
by Thais Borges and Sue Branford 10 August 2020
While MRN, a mining firm makes big profits working within, and harming, a Brazilian conservation unit, traditional people can be fined for collecting Brazil nuts and fishing sustainably in a nearby protected area.
Guardians of Mexico's community forests confront climate change
by Pablo Hernández Mares 31 July 2020
In some Indigenous languages, two words are just not enough to convey everything encompassed by the phrase "climate change." Alejo López, who speaks one of the varieties of Chinantec that…
New report asks, do land titles help poor farmers?
by John C. Cannon 22 July 2020
Companies and governments are pushing for the privatization of land around the world as a way to get at economically valuable resources, according to a recent report from the Oakland…
Forest restoration, not just halting deforestation, vital to Amazon
by Sarah Sax 22 July 2020
Brazil is well positioned to benefit from forest restoration and agroforestry, but policies in states like Maranhão fail to address that potential and could contribute to further deforestation.
In Mexico, groups push for reforms to law promoting sustainable forest use
by Thelma Gómez Durán 15 July 2020
Mexico's General Law on Sustainable Forest Development is once again in the spotlight. Despite being a recent law, approved on June 5, 2018, and applauded at the time for its…
Conservation insights from an enormous aspen clone: Q&A with ecologist Paul Rogers
by James Dinneen 5 June 2020
With its groves of pockmarked white bark and trembling green medallion leaves, Pando looks like any other aspen forest. But the approximately 47,000 stems that form its giant body share…
Community forest enterprises provide win for forests and people: Study
by Thelma Gómez Durán 21 May 2020
What do countries like Mexico, Guatemala, Nepal and Namibia have in common? All four are home to rich repositories of biodiversity. But each country has also developed models for community…
Ecuador's Kichwa implement innovative approach to rainforest conservation
by Matthew Wilburn King 20 May 2020
The need to conserve and protect global forests is clear and urgent. Indigenous populations like the Amazonian Kichwa have recognized the need for action to prevent the worst effects of…
Aiming for conservation and development in a corner of Mexico's Mayan jungle
by Thelma Gómez Durán 6 May 2020
José Ramírez Talango is a retired teacher and beekeeper. When he was a child he used to walk through the jungle to reach Laguna Chakanbakán in the southeastern Mexican state…
Healing the world through 'radical listening': Q&A with Dr. Kinari Webb
by Justin Catanoso 30 April 2020
Dr. Kinari Webb believes this because she has witnessed it — up close: Amid this global pandemic, the health of the planet is intricately connected to public health around the…
Through biomimicry, Brazil seeks tech innovations inspired by nature
by Sibélia Zanon 28 April 2020
From spiderweb-inspired shampoo to a hotel whose architecture is based on the thermal properties of toucan beaks, scientists and companies in Brazil are betting on nature's intelligence to create innovative solutions that reduce impacts on the planet.
Watchdogs lament palm oil giant Wilmar's exit from forest conservation alliance
by Hans Nicholas Jong 8 April 2020
JAKARTA — Environmental watchdogs say the exit of the world's largest refiner and trader of palm oil from a committee that helps identify forest areas for protection could hurt efforts…
Indonesia risks timber trade with EU after scrapping license rules
by Hans Nicholas Jong 30 March 2020
JAKARTA — The European Union is seeking an explanation for Indonesia's decision to scrap a highly regarded timber legality verification system, which the bloc uses to ensure it imports only…
Indonesia ends timber legality rule, stoking fears of illegal logging boom
JAKARTA — Environmental experts have warned of a resurgence in illegal logging in Indonesia after the government declared that wood exports would no longer have to comply with a stringent…
The commons, community and conservation: Q&A with anthropologist Leticia Merino
by Thelma Gómez Durán 6 March 2020
Leticia Merino graduated from college with a degree in social psychology. But her plans to continue her studies in that field were thrown into doubt after she encountered a community…
For Mexico's forgotten cloud forests, sustainability and protection are key
In 2009, scientists estimated that Mexico's tropical montane cloud forests — hillside woodlands blanketed in fog and rain — were down to 28% of their original extent. Fifty-three percent of…
'Unless impunity is fought, we will not get anywhere': Q&A with community forestry expert Lucía Madrid
by Thelma Gómez Durán 28 February 2020
Lucía Madrid spent her childhood in a land of trees and a time of flux. It was the 1980s in Mexico's Sierra Norte de Oaxaca region, and communities were organizing…
Video: Abraham Khouw, the professor who joined the Save Aru movement
by The Gecko Project and Mongabay 18 February 2020
This article was co-published with The Gecko Project. Additional support was provided by Earthsight. In late 2013, during a hearing convened by the local legislature of Indonesia's Maluku province, a…
Video: Mika Ganobal, the civil servant who risked his job to save his homeland
by The Gecko Project and Mongabay 7 February 2020
This article was co-published with The Gecko Project. Additional support was provided by Earthsight. When the politician in charge of Indonesia's Aru Islands signed permits for a vast sugar plantation,…
Mexico: Community forestry boosts conservation, jobs, and social benefits
by Thelma Gómez Durán 22 January 2020
Laura Jiménez, Manuel Herrera and Elías Santiago grew up in a land where elders proudly related how they managed to recover their forests, hearing them recount how the Mexican government…
Deforestation for potential rubber plantation raises concerns in Papua New Guinea
by John C. Cannon 19 December 2019
PORT MORESBY, Papua New Guinea — The upstart deforestation over the past year and a half that's sidling up to Pochon Lili's land has him worried. "As a landowner, I'm…
Madagascar's bold reforestation goal lacks a coherent plan, experts say
by Malavika Vyawahare 22 November 2019
RANOMAFANA and ANTANANARIVO, Madagascar — While many U.S. travelers dream of the fabled forests of Madagascar, for Malagasy conservationist Mahandry Hugues Andrianarisoa, 28, it was the verdant landscape of upstate…
10 takeaways from Indonesia's grassroots #SaveAru success
by The Gecko Project and Mongabay 28 October 2019
This article was co-published with The Gecko Project. This month Mongabay and The Gecko Project published "Saving Aru," an article chronicling how the people of Indonesia's Aru Islands thwarted a…


text:
package org.robolectric.shadows;

import android.content.ContentUris;
import android.net.Uri;
import org.junit.Before;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.robolectric.TestRunners;

import static org.assertj.core.api.Assertions.assertThat;

@RunWith(TestRunners.WithDefaults.class)
public class ShadowContentUrisTest {
  Uri URI;

  @Before
  public void setUp() throws Exception {
    URI = Uri.parse("content://foo.com");
  }

  @Test public void canAppendId() {
    assertThat(ContentUris.withAppendedId(URI, 1)).isEqualTo(Uri.parse("content://foo.com/1"));
  }

  @Test(expected = NullPointerException.class)
  public void appendIdThrowsNullPointerException() {
    ContentUris.withAppendedId(null, 1);
  }

  @Test public void canParseId() {
    assertThat(ContentUris.parseId(Uri.withAppendedPath(URI, "1"))).isEqualTo(1L);
    assertThat(ContentUris.parseId(URI)).isEqualTo(-1L);
  }

  @Test(expected = NumberFormatException.class)
  public void parseIdThrowsNumberFormatException() {
    ContentUris.parseId(Uri.withAppendedPath(URI, "bar"));
  }

  @Test(expected = UnsupportedOperationException.class)
  public void parseIdThrowsUnsupportedException() {
    ContentUris.parseId(Uri.parse("mailto:bar@foo.com"));
  }

}

redpajama_set_name: RedPajamaGithub


text:
Q: making a list into dictionary suppose you have a list
A = ["A: 1", "B: 2", "C: 3"]

can you make this into a dictionary of
dict_A = {"A" : 1, "B": 2, "C": 3}

I got stuck at making the list into a dictionary

A: In [1]: A = ["A: 1", "B: 2", "C: 3"]

In [2]: {k:int(v.strip()) for k,v in (i.split(":") for i in A)}
Out[2]: {'A': 1, 'B': 2, 'C': 3}

This can effectively be unpacked as follows:
d = {}
for item in A:  # the first time around, item = "A: 1"
    key, value = item.split(":")  # key = "A", value = " 1"
    value = value.strip()  # value = "1"
    value = int(value)  # value = 1
    d[key] = value

A: A = ["A: 1", "B: 2", "C: 3"]
B={}
for i in A:
    B[i[0]]=int(i[3])
print(B)

{'A': 1, 'B': 2, 'C': 3}

the length of every string here is 4. the i[0] is the key like 'A' and the i[3] is the value like '1'. converting it to int would give you the exact value you want, and then you just assign it to the dictionary for each key values.

A: One nice way of doing this:
A = ["A: 1", "B: 2", "C: 3"]

A = [item.split(':') for item in A]
dict_A = dict([[key, int(val)] for key, val in A])

print(dict_A)
>>  {'A': 1, 'B': 2, 'C': 3}

to break down each line and what it returns:
A = [item.split(':') for item in A]
>> [['A', ' 1'], ['B', ' 2'], ['C', ' 3']]

After first splitting on :, each index in A now holds a list of two items. and each index of A can be unpacked. For example: first, second = A[1] is the same as first, second = A[1][0], A[1][1] ; in both cases  'B' would be assigned to first and '2' to second
Considering that all the numbers are still strings they need to be converted to int, but we only want to convert the second item in each of our nested lists; this is where unpacking can be useful, as we would only apply the int conversion to the second item.
This can be done nicely in a single list comprehension
[[key, int(val)] for key, val in A]
>> [['A', 1], ['B', 2], ['C', 3]]

but, considering that you want a dictionary, we can just call dict() to convert into dictionary
dict([['A', 1], ['B', 2], ['C', 3]])
>> {'A': 1, 'B': 2, 'C': 3}

redpajama_set_name: RedPajamaStackExchange


Hi Everyone. For some years DH has been receiving hundreds of healing requests on various social networking sites. A couple of years back, DH received a vision/message in meditation that she should further develop her healing more in a social direction and was half-jokingly told and shown to become the "MySpace Healer". Just recently DH discovered Face Book and its strength in providing the perfect, efficient viral networking platform for freely sharing a profound healing gift with humanity in an vastly expanded and almost revolutionary manner.
Obviously, DH is not the first healer to clue into Facebook's potential as an evolutionary & revolutionary platform to provide mass healing. In looking around FaceBook DH discovered similar offerings from various groups and individuals providing healing services – (in person and long distance, one on one, or mass healings). As a result, DH was more inspired than ever to share healing gifts in this forum as well. After decades of solid healing experience in every conceivable circumstance, Facebook healings are a natural progression. By serendipity of happenstance and mutual enlistment, a charitable service organization is being created to support this beautiful and large scale healing effort.
At least one other very popular healer on Facebook offers free group healing events. By all the comments submitted by participants, this distance energy work is clearly amazing and he has amassed 7000 fans in only 2 months. His current intention is to provide only one Free event every seven weeks or so. If participants feel they need more continuous healing support, they are encouraged to visit his website and invest in themselves by purchasing a monthly healing subscription for $99 / month with a family and pet upgrade available for an additional $39 per month.
We feel this is a wonderful model. We seek seek only to improve upon this approach by focusing on Frequency & Affordability while reducing or eliminating any aspect which could be perceived by the public to tarnish the purity of the offer. Basically, we wish to increase the frequency of the free events and lower the price of the pay subscriptions.
We are certain that some of his fans will find the other healer's pay subscription offerings quite affordable and worthwhile. Considering that many other healers charge $99 and up for a single (one on one) long distance session and his customers are receiving one weekly one hour scheduled group session and an undefined number of additional unscheduled adjustments per week they may consider their investment a good deal (assuming they are happy with the results for the investment). Yet, for most people, an investment of $1200 to $1656 a year will be perceived as too steep for price of admission and they will settle for the cyclical 7 week freebie. Once again, we have concerns that healing becomes the province of the rich and indulgent, rather than for everyone (except, of course, once every 7 weeks).
While most of his fans have viewed this Free offering as overwhelmingly generous, it has been pointed out that he currently schedules his Free sessions at the same time he schedules his Pay subscription sessions – so there is no real cost to him in devoting extra time or energy for the Free event participants. We certainly do not fault him for this approach and are making an observation and not a criticism. However, we will schedule our FEE & FREE offerings separately as not to invite suspicion, doubt or criticism from our paying customers who will naturally feel that as they are paying – they should have separate time scheduled for them.
Of course, effective healing is a measure of results – not a measure of time or measure of money. Cost-effective healing, however, factors in the time & money. Many healings can occur in a "holy instant" whereas, some conditions resolve over much longer periods of time, or defy apparent healing altogether. Some marginally effective healing work can costs thousands; yet miracles can be available elsewhere for free. So time and money are not the determining factors in the power of a healing. Yet, unless we are visibly and instantly healed we are likely to feel more taken care of by someone who gives us an hour of their time than someone who gives us 5 minutes for the same money. Likewise, it is also a human tendency to place increasing value on those products and services which cost us more-but this is a rule of thumb and not spiritual law . Historically, most sacred traditions offer such healing and sacred gifts for free. Masters such as Jesus, Buddha, and numerous saints, mystics, gurus never charged for dispensations of Grace, but by all accounts their healings were truly miraculous- beyond most powerful energy work readily available today. Of course, the exchange of money for services is the customary & fair energy exchange in the modern world. Although determining "fair exchange" is clearly the rub. Modern day "prosperity pimps" and abundance gurus charge thousands of dollars for a weekend seminar and many of us routinely engage the services (sometimes for years on end) of therapists, counselors, life coaches, etc. who charge hundreds of dollars an hour for their services-so why not healers. A gifted healer is certainly as entitled to a richly blessed life of abundance. The thing is not to place money, fame, or ego above service to to others.
Consistent with our philosophy and concerns we have expressed above, we at FDH will structure our offerings – Free or Fee – consistent with our mission of service, research and education. Yes, we will offer monthly and yearly healing subscriptions for those who feel this course of personal commitment and level of energy exchange are appropriate for them. However, our subscription pricing will be significantly less than similar online offerings. Moreover, early subscription sign ups are half off during the promotional start up period and are available for $30 per month and less ($1 per day).
click this link for further details on our healing subscriptions.
Next, we feel divinely compelled that we should offer Free Healing events at least once a month (and much more frequently for the first two to three months) without concern that our subscription service offerings will suffer by everyone simply taking advantage of the frequent freebies. We trust the Golden Rule will guide the actions of all participants-including ourselves. Our focus is Service, Research, Education- in that order. Money is somewhere down the line after these-but we are just just as happy to freely receive as to freely give. Spacing our free event offerings farther apart in time certainly makes better business sense, (but we are not in the BIZ of healing- we are in the service of healing). In our opinion, the only reason to space Free Events so far apart is to manipulate people into signing up for paying subscriptions, thus undermining the true underlying charity and integrity of our mission. If not in reality, then in perception. We feel we must take all steps necessary to build trust with the public – even the most jaded and skeptical – and to reduce or eliminate all avenues of criticism and cynicism.
To insure fairness and a sense of added value to our FEE or PAY participants, those who sign up for subscriptions will have their FEE healing events scheduled on a separate night of the week from the FREE event but are welcome to sign up for the FREE events as well. As a further bonus, early pay subscribers will have their subscriptions extended by the time equal to the "Frequent Freebie " overlap Distance Healing Project enrollment period. For instance, if you sign up for a Pay subscription during the first week but our overlapping membership drive runs for two months with Free events scheduled as frequently as two weeks apart, you will receive an extra two months of weekly scheduled healings. If you sign up as a pay subscriber at the beginning of the second month, you receive one free extra month on your subscription period to insure that you do not feel cheated or short changed in any way.
If any of our healing events overlap with another healing/activation offering we highly recommend that you take advantage of every free offering available. The best things in Life are Free – you might as well load up. The work of others will not impede the Love and Energy flowed by our master healer. Of course, you may not be able to tell whose efforts may have had the desired effect-which may or may not be important to you. We care more for your well being than in receiving credit or in taking your money. If the sound bytes "all healing is self-healing" or "Spirit is the only healer" echoed by virtually every healer alive are anything beyond lip service, then there should be no attachment to credit, money or even specific results. To further insure non-attachment, our resident healer has insisted we keep their identity a secret for the duration of the project. DH has also agreed to donate their share of all profits for the first year of the project back to the research and educational efforts of the project. In fact, all profits will be used to further support the charitable service, research, educational activities of this and similar organizations.
We recommend you make your choice of mixing healing energies based on your own intuition. If others dissuade you from our offering because they plant fear or concern over mixing disparate energies, this is simply their EGO trying to convince you to let them keep you (and your money) all to themselves. Additionally, be particularly mindful of being spiritually manipulated if money is involved. We will never turn anyone in need away-regardless of their ability to pay. Furthermore, we suggest that the highest vibration always entrains lower frequencies towards itself, thus uplifting and upgrading any lower frequencies.
We just wish to conclude by thanking everyone for this opporunity to serve so many on such a high level.


Mansarovar Park plot is offering Residential plot in NH-24 Ghaziabad. It is one of best residential project and offering best plot in varying size and affordable price in your budget. This Residential Project is well connected to Delhi/NCR with roads, railway and metro. This township have based modern amenities like wide Tar road, Boundary Wall, water Supply, Electricity, Entry & Exit Gate, Schools, Hospitals, malls with multiplexes, Temple, Park, 24X7 Security System. Location Advantage are Upcoming Metro Station.
Mansarovar Park plot NH-24, Ghaziabad is a most affordable residential project in Ghaziabad, which main purpose is to offer you affordable residential plot with plentiful of facilities.


Zeehan Pool will be open this summer following upgrades by West Coast Council.
The council closed the pool during the 2017/18 swimming season to undertake infrastructure improvements designed to cut operational costs.
West Coast mayor Phil Vickers said the pools at Zeehan, Queenstown and Rosebery "have all received significant maintenance and upgrades for the coming season".
The pools will be open until February 28 and operate under the council's cold weather policy.
Queenstown and Zeehan pool won't open if the weather forecast is under 16 degrees Celsius while Rosebery won't open if it's under 18 degrees Celsius.
The council has also reduced the opening hours for Rosebery Pool due to low patronage in the 2017/18 season.


BioAscent will be attending the 30th Symposium on Medicinal Chemistry which is set to take place on the 2 May 2019 in Hatfield, UK.
The "Hatfield MedChem" meeting is a highly successful, long-standing, one-day annual meeting. To commemorate 30 years, this year's programme will focus on 'Celebrating UK Drug Discovery', highlighting success stories from large pharma, biotech and academia; and exciting scientific prospects for the future.
Presentations will showcase medicinal chemistry from tools to candidates, across a range of modalities, therapeutic areas and target classes with an emphasis on key learnings and knowledge developed during the course of effective discovery efforts.


Macy Gray is an American R&B and soul singer-songwriter, musician, record producer and actress. She is known for her distinctive raspy voice and a singing style heavily influenced by Billie Holiday. Gray has released six studio albums, and received five Grammy Award nominations, winning one. Gray is best known for her international hit single "I Try", taken from her multi-platinum debut album On How Life Is.
Macy Gray is a pretty unknown artist to me aside from her only hit I Try and her 2018 singles, so this will be a nice change to skim her discography. I will use 24 songs (singles/music videos), and won't include the covers from her cover album because I want to keep the number easily splittable (that's not a word I think) into four groups of 6.
Sweet Baby is SO good.
I'm not too familiar with her discography so I'll be kicking in later.


If you're paranoid about papers or cantaloupes popping out of the top of your Metro, the Metro Hood was made for you. Tailored of 400 denier pack cloth, the Hood secures to the rear cross bar with hook and loop tabs. The front edge is attached with a side release buckle and short tension strap. When not in use leave the hook and loop tabs attached and tuck the Hood into the Metro and out of the way.
Note: Fits Metro Basket Pannier only.


text:
How can potentially negative effects on local populations of large-scale land acquisitions be mitigated and what could institutions do to protect human rights of the affected population ?
The project deals with the issue of the socio-political, economic and environmental potentials and problems characterizing transnational, large-scale land acquisitions (LSLA). Over the last years, forceful eruption of cross-border land acquisitions took place. There is, however, only limited academic knowledge of the circumstances in which these land deals take place – in terms of processes and contexts – as well as in respect to their impacts on local populations. LSLA may have significant and uneven impacts on the livelihood systems of local populations. Yet, it is acknowledged that the promises are not fulfilled and that land acquisitions are in some cases detrimental to large number of populations.
The project's preliminary findings from field research indicate that the on-going agrarian transformation associated with rubber-tree plantation in Cambodia and Laos increases the vulnerability of the less well-off segments of the population. Based on comprehensive case studies in both countries, the project aims at producing generalised insights for evidence based decision and policy making. The research will be structured around three core questions : What are the processes among various actors and institutions across different administrative scales determining the negotiation and implementation of land acquisition ? What are the impacts of land deals on local populations in terms of livelihood system and vulnerability ? What role do existing policies, institutions and mechanisms play (and what role could they play) in mitigating the tensions related to LSLA and protecting the human rights of local popula-tions ?
Beyond its contribution to the academic debates related to "land grabbing", the project will provide material for policy dialogue with authorities, UN agencies, international financial institutions and non-governmental organizations in their effort to accompany the implementation of large-scale land deals and to mitigate their possible negative impacts.
Agrarian change
Transnational land acquisitions
Land governance
International Organisations:
UN Special Rapporteur on the Right to Food
International Land Coalition
NGOs, States or other Institutions:
Rubber Research Institute of Cambodia, Ministry of Agriculture, Forestry and Fisheries
Water Resource and Environment Administration (WREA), Prime Minister's Office, Government of Laos
National Land Management Authority, Prime Ministers Office, Government of Laos
Movie Website
Working Paper – Large-Scale Land Acquisitions in Southeast Asia
Master dissertation – Cecilie Friis
Master dissertation – Patricia Paramita
Policy Brief: Large-Scale Land Acquisitions and Livelihoods in Cambodia and Laos: Increasing Vulnerability
Policy Brief: Beyond Anecdotal Evidence of Large Scale Land Acquisitions
Policy Brief: Large-Scale Land Acquisitions, Human Rights and State Accountability
Large-Scale Land Acquisitions – International Development Policy – Issue 6/2015
Christophe Gironde
Graduate Institute Geneva
Christophe Golay
Ioana Cismas
Olivier De Schutter
UN United Nations
Cecilie Friis
Andreas Heinimann
Vong Nanhthavong
Peter Messerli
Irene Biglino
Amaury Peeters
Oliver Schoenweger
Patricia Paramita
Suon Seng
Center for Development Oriented Research in Agriculture and Livelihood Systems
Gilda Senties Portilla


Experimenting with a new format. WUF! The idea is to have a mix of content here, some weird, some useful, and a bit of fun at the end. This site is, after all, HAPPY wisdom. So let's get to it!
Okay, the weirdest story I saw online this week has to go to the guy who almost died when a fish swam down his throat.
There is a lot of great resources out on the Web to encourage you, to make you better, or to make you feel worse by comparing yourself to some artificial standard.
It turns out that we're not all so different, and as humans, we need to address eight different areas of our life. If we can find time to visit each of these dimensions you will likely uncover where that issue is.
Emotional – do you understand your feelings and express them to people you trust?
Environmental – is your home calming and pleasant?
Financial – are you in a place where money isn't a constant worry? Worry about this can affect your health so do you what you can lifestyle-wise to make this less of an issue.
Intellectual – are you a life-long learner? Foster curiosity in your life and it'll become more interesting.
Occupational – is your job or your volunteer work satisfying? If not, you're not a tree – move!
Physical – fitness is a well-proven component of mental health. Even 2-3 ten-minute walks a day would suffice!
Social – do you have the right support network of family and friends?
Spiritual – what connection do you have to the Big Picture? Tie into the deep mystery of our world with mindfulness.
There it is, in short. There's a nice little video on it, below, and I'll likely aim some future HappyWisdoms at this list.
Like many trends, I initially disparaged the Fidget Spinner as a useless device that isn't that satisfying. However, after playing with some of the higher-end models, I have to say its fairly entertaining. It's not only me – apparently, the guys floating around in space found the time and space on their spaceship to make room for a Fidget Spinner.
What's super interesting is it looks like the angular momentum from the fidget spinner can be transferred from it to the astronaut. The raw power of physics is made even more interesting in zero-G environments.


Science Fair. The words strike terror into the hearts of students, parents, and staff. As if the holidays were not stress enough!
It used to be that science fair was pretty low key and just a chance for students to have fun while learning to do experiments of their choice, or show off their model of a scientific principal, or to display their rock collections. That's surely not the way it is now.
Today, high school students can win thousands, or even tens of thousands of dollars in scholarship money and research grants. In the 2015 INTEL International Science and Engineering Fair, a sixteen year old, a seventeen year old, and an eighteen year old each won $50,000!
OK - no pressure there! These days, science fair is not for wimps. Districts expect that science teachers will make sure that students from their district have a chance of competing at state, regional, and international science fairs and bringing home the credit to their school and school district.
Students as young as fifth grade begin competing in state or regional science fairs. Not many parents have the background in science to help their children with that kind of project. And not many teachers have the time to help each individual child to plan and carry out a unique and scientifically valid project.
As the result of having been the district science fair coordinator for my school district, I learned first hand that without some help, a lot of kids just can't do it. And it's pretty obvious which kids had massive amounts of help from a parent who just happens to be an engineer or biomedical researcher. We want kids who don't have that kind of parent help to have a fair shot at learning to do a good science experiment - and maybe even going on to win some scholarship money.
Last spring, after seeing the 7,000th model volcano of my career, a homemade 3-D printer, and a fully functioning electricity-generating bicycle desk for teachers, I decided to write a Science Fair Guide for students entering their first competitive science fair, (and for the parents who want to help them plan a good project and have an encouraging experience in science).
"If the result confirms the hypothesis, you've made a discovery.
If the result is contrary to the hypothesis, you've made a discovery."
That's what we science teachers want for students to understand. It's about finding out things we didn't know, even if - or especially if - it didn't go the way we expected it to.
With this year's science fair season upon us, I've made a set of Editable Science Fair Planning Calendars for anyone who needs them. They're free. I hope they'll reduce the planning stress a little bit and make it easier to keep everything moving smoothly.


Congratulations to the 3 millionth trader!
The client who was so lucky to become the trader # 3 000 000 is Rudianto from Indonesia! Congratulations! Follow the news at our site not to miss the video report of our Indonesian team, who will bring Rudianto these perfect news. Stay tuned!


Model No. YPW.2694G by: Heritage Brass.
List price £30.35 You save £10.62!
This is a Heritage Brass Primed White screwless Euro plate, ideal for fitting four Euro modules. This wiring device is part of the Heritage Brass Primed Metal screwless range - a flat metal plate, primed, suitable and ready for painting; also, this range is screwless - no visible screws on the plate!
Note: picture is schematic, for informative purposes. Please check the finish of the plate and the type of the plate for this Euro Plate.


First on the ground photos of phrase three of Kingdom of Poseidon - the marine park! No new details have been revealed except that this expansion will be opening next year.
BREAKING: Kingdom of Poseidon's first of many expansions, an outdoor waterpark named "Sea Monster Island" is opening July 20, 2018! Sea Monster Island is located adjacent to the park's existing indoor waterpark. The new waterpark will feature at least two large waterslides and a huge wave pool. No images of Sea Monster Island have been released yet but check back soon for photos of the expected soft opening in the coming days.


Hawleywood's Barber Shop & Shaving Parlor located in Huntington Beach. Nobody provides a cleaner cut, because no one is more thorough. No matter what your style is-classic businessman, high taper, flat-top, low and clean, psychobilly quiff or classic Mohawk-we'll get it perfectly right, like we have for discerning gentlemen since 1999. All haircuts are finished with a hot towel, straight-razor shave around the neckline and ears; and a scalp and neck massage. You'll walk out the door with your choice of styling-and lookin' sharp!


text:
New Pups on the Block
Shocking changes to the Westminster Dog Show have tongues, not tails, wagging
Steven Devadanam
The Westminster Dog Show is on.
Photo by Henny Ray Arbams/AP
Where does the wolf puppy stand?
Icelandic Sheepdog
Of-the-moment indicators of changing trends aren't limited to Mercedes Benz Fashion Week. Travel about 30 blocks south, and you'll see signs of the times inside Madison Square Garden, where the Westminster Kennel Club Dog Show runs though Tuesday night.
What makes this year unique is a new diversity among the competing breeds. In all, six new breeds are making their debut: Icelandic sheepdogs, redbone coonhounds, Leonbergers, Boykin spaniels, cane corso and bluetick coonhounds. Also new this year is the Xoloitzcuintli, which was compared in the Sunday Styles section of the New York Times to a "hot water bottle with pig eyes, bat ears and a rat tail." The Xolo is the most recent member of the 170 recognized purebreds appearing on the roster of the American Kennel Club.
Recognize a few of your favorites in that list? Probably not, as none of them have made it to the final round. Bloomberg reports that in the final circle is a "regal" three-year-old Pekingese, a Scottish deerhound, a Chinese Shar-Pei and bearded collie with an affinity for standing on its hind legs and doling out hugs. These four champion purebreds will compete with the winners of the sporting group, which counts Golden Retrievers, working dogs such as Akitas, and terriers among its ranks.
Yet the lingering question remains: In this maze of rare breeds, cutthroat competition and utter cuteness, where does the wolf puppy stand?
In its first day, the show was a magnet for B-list celebrities, such as Austin's own seven-time Tour de France winner Lance Armstrong with his twin 9-year-old daughters and Jane Hammett-Bright, who almost reached the final episode of last season's Survivor: Nicaragua. At 10 p.m. Tuesday evening, the Best in Show will be announced by top judge Paolo Dondina.
We wait with bated doggy breath.
news/entertainment
get ready for cook-off
Houston Livestock Show and Rodeo fires up dates for 2023 World's Championship Bar-B-Que Contest
Photo courtesy of Houston Livestock Show and Rodeo
It's Cook-off time, y'all.
Now that fans know the entertainers who'll take the NRG Stadium stage or the 2023 Houston Livestock Show and Rodeo, it's time to turn attention to the unofficial kickoff of the rodeo run.
The 2023 World's Championship Bar-B-Que Contestwill run Thursday, February 23 through Saturday, February 25 on the NRG Stadium grounds. The wildly popular event sees more than 250 teams from around the world will compete for best in show in sections like brisket, ribs, chicken, Go Texan, Dutch Oven dessert, and the Open Contest category.
Cook teams show up and show out in pits disguised as fire engines and covered wagons, to airplanes and armadillos. The more than 700 entries compete for best overall barbecue and other categories on Saturday, February 25, with results announced at The Garden Stage at 7 pm.
As always, team tents are invitation-only. But rodeo visitors can enjoy several public venues, including The Garden, Rockin' Bar-B-Que Saloon, and the Chuckwagon. More fun and wild rides can be found at the carnival. The private tents are a see-be seen affair with presenting sponsor Cotton Holdings sure to unveil yet another over-the-top tent that's as big as Texas.
Young grillers and smokers can compete in the Jr. Cook-off contest on Friday, February 24. Kids between the ages of 8-14 will be given a single steak to prepare that will be judged on appearance/presentation, tenderness, and taste. Awards will be presented to the top three contestants.
The party continues at The Garden Stage, where Texas Country acts strum their stuff, while the Rockin' Bar-B-Que Saloon also features live, a DJ spinning tunes, and a large patio.
Visitors should consider ride sharing or look for parking at these lots:
Yellow Lot
Location: 610 to Main St., enter Gate 16 off Main St.
610 Lot
Location: West Bellfort and Kirby.
Hours: 10 am to 10 pm
Tickets can be purchased online or at the contest gates and start at $20 for adults, $5 for children, and free for kids aged 2 and under. Admission to the World's Championship Bar-B-Que Contest includes a complimentary sliced barbecue brisket and sausage plate, access to live music areas, and admission to the carnival. (Importantly, admission does not include access to private cook-off tents.)
Fans can also score a Grounds Season Pass allowing access to all Cook-off events for $50.
Event times are Thursday, February 23, 5 pm to 11 pm; Friday, February 24, noon to 11 pm; and Saturday, February 25, 9 am to 11 pm. More information can be found at rodeohouston.com or on the official RodeoHouston app.
Houston Livestock Show and RodeoWorld's Championship Bar-B-Que Contestrodeorodeohouston


text:
Changchun Wuhuan Gymnasium is een arena in de stad Changchun in China.

De arena wordt voornamelijk gebruikt voor sporten die binnen beoefend worden. Er is plaats voor 11.428 mensen en werd geopend in 1994.

Tijdens de Aziatische Winterspelen 2007 vonden hier de openings- en sluitingsceremonie plaats. Tevens werden hier de wedstrijden van het kunstschaatsen en het shorttrack verreden.

IJsbaan in China
Sportaccommodatie in China
Aziatische Winterspelen 2007
Gym
Bouwwerk in Jilin
Sport in Jilin

redpajama_set_name: RedPajamaWikipedia


text:
Flintshire War Memorials
Card Form
Prestatyn Memorial
Prestatyn Soldiers WW1
« Back to Prestatyn Soldiers WW1
Owen, Robert
Name of Researcher / Enw'r ymchwylydd: Rene Owens
Name of Memorial / Enw'r gofeb: Prestatyn (Christ Church) Churchyard
Regiment/Catrawd: Cheshire regiment, 1st/6th battalion.
Service Rank and Number / Rheng gwasanaeth a rhif: Private 66133
Military Cemetery/Memorial / Fynwent milwrol: Fins New British Cemetery, Sorel-le-Grand, Somme.
Ref No Grave or Memorial / Rhif cyfeirnod bedd: IV. B. 19
Country of Cemetery or Memorial / Gwlad y fynwent neu gofeb: France/Flanders
Medals Awarded / Medalau a ddyfarnwyd: British War Medal, Victory medal.
Date of Death / Dyddiad Marwolaeth: 16 February 1918
Circumstances of Death / Dyddiad ac amgylchiadau marwolaeth:
Killed in action, 16th Feb 1918, age 19.
Commonwealth War Grave Certificate / Tystysgrif Bedd Rhyfel y GymanwladView certificate
Robert Owen was the son of Roger and Elizabeth Owen, and was born at Mold on 13th February 1899.
We first encounter his family on the 1901 Census for Wales, provided by Ancestry. They were living at Ty Draw, a prosperous farm in the Gwysaney area of Mold. Head of the family was Robert Owen aged 77, who was described as a farmer, a Methodist preacher, and an employer, who had been born at Llanllyfni, Caernarvonshire. His wife Mary was 70, and had been born in Penmorfa, Caernarvonshire. Their son Roger, Robert's father, was 32, and had been born at Dolbenmaen, while Robert's mother Elizabeth, also 32, had been born in Denbighshire. Their children were Blodwen A. aged 3, Robert aged 2, and Mary, aged 1, all born in Mold. There was also a general domestic servant Catherine Roberts, aged 18, and five male farm servants. Roger and his wife spoke Welsh and English, while all the others spoke only Welsh.
Ancestry records show that Roger and Elizabeth had married in Ruthin in 1896, and also that sadly, Roger had died in 1903, aged 34.
In the 1911 Census for Wales, we find Elizabeth now living at Dyffryn, Well Street, Ruthin. She is described as a widow, aged 39, born Llanynys, and living by private means. She had four children, these were Blodwen Ann aged 13, Robert aged 12, Mary aged 11, and Elizabeth, aged 7, who had been born since the last census. All were at school, and everyone spoke both languages. There was one servant, still Catherine Roberts, now aged 28.
The website Soldiers who Died in the Great War confirms the known details for Robert.
Sometime after the Census Robert moved to Prestatyn in order to work in a bank, we know this from his Army Records which have survived. These records show that he took the oath at Chester on 23rd September 1916, and was approved at Wrexham on March 6th, 1917. He was enlisted into the 65th Training Reserve. He gave his address as Roseberry House, Nant Hall Road, Prestatyn, and his occupation as a bank clerk. His age was 17 years and 7 months, and his height was 5 feet 6 inches. His chest measurement was 35 inches, 38 inches when expanded. His next of kin was his mother Elizabeth Owen of Clovelly, Ruthin, and his religion was Wesleyan.
Robert's Service Records give further details.
He was attested on 23rd September 1916.
He joined the Reserve on 24th September 1916.
He was mobilised on 5th March 1917.
He was posted on 7th March 1917.
Also from these records we find that at Curragh Barracks on 6th December 1917 he was charged with improper conduct in the ranks, and was sentenced to two days confined to barracks. Still at Curragh he was deprived of 21 days' pay for "overstaying his pass from tattoo 3/1/18 till 11pm 8/1/18. 121 hours."
After enlistment in the 65th Reserve Battery, he was transferred to 213th Infantry Battalion, the 21st Grad Btn Cheshire Regiment.
The records inform that he embarked on 18/1/18
He disembarked on 19/1/18
He joined and was posted to the 11th Cheshires on 21/1/18 at Rouen, and joined the battalion in the field on 5/2/18. On 16/2/18 he was killed in action in the field. He had been with his battalion for 11 days.
There is a card for Robert in the Roll of Honour in the Hawarden Archives. His period of service is given as one year. In the space for his address is the stamp of the National and Provincial and Union Bank of England Ltd, and the card is signed by the manager. The signature is not legible.
In the declaration of all living relatives, in addition to his mother, his three sisters were named. They were Blodwen 22, Mary 20, and Betty 17.
On February 21st 1922, Mrs Elizabeth Owen signed for the receipt of his medals and scroll.
From the website listing Soldiers Effects we know that on 8th May 1918 Mrs Owen was awarded £2 15s 10d, money owing to Robert, and on 8th December 1919, a further £3 war gratuity.
Robert was killed three days after his 19th birthday.
He is also commemorated on the Ruthin memorial.
Learn more about the other soldiers on the Prestatyn Memorial
Anderson, Thomas
Ash, John Buckley
Barnett, William John
Batters, Frank Gilderoy
Batters, George William
Bowes, Roy
Bray, George Llewellyn
Cook, Walter Quest
Cooke, Charles William
Cooper, Charles
Darbey, John Edward
Davies, Peter James
Dobbins, Francis
Duplock, Charles Leslie
Duplock, Montague (served as Marten Cave Duplock)
Ellis, William
Evans, Robert Parry
Gibbons, Wilfred
Griffiths, Arthur
Hardman, Frederick Roland
Hawkins, Stuart A S
Higgins, Thomas
Hughes, Ceiriog
Hughes, James Tudor
Hughes, John E
Hughes, Joseph L
Hughes, Matthew H
Hughes, Thomas E
Jones, Alfred
Jones, Arthur Rowland
Jones, Arthur S
Jones, Gwilym
Jones, Herbert
Jones, Ivor D
Jones, John Ivor
Jones, Joseph Francis Maldwyn
Jones, Roger A
Jones, Roland Arthur
Jones, Samuel
Lawton, Eric R
Lewis, Bernard
Livesey, James Trevor
MacDonald, William P
Madden, Alfred
McClaren, Francis Walter Stafford
Mocatta, Robert Menzies
Owen, Joseph Heber
Owen, Thomas H
Parry, William
Pritchard, Sidney
Pulford, Samuel
Quinney, Harold
Randles, Harry
Riley, Angus
Roberts, John T
Roberts, Robert John
Roberts, Thomas E
Seymour, Charles
Staffin, Matthew
Thornton, James Percy
Turner, Thomas Norman Leslie
Williams, Charles
Williams, Owen John
Williams, Samuel
Williams, Walter E
Wright, Edward
Honorary Patron: Colonel P J Knox OBE
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text:
clara ritger
filmmaker. journalist.
Clara Ritger grew up in the small town of Huntington Beach, California, population 200,000, where she learned what real Mexican food tastes like and how to cut the line at Disneyland. At the ripe old age of two she ran as far ahead of her parents as her child leash would take her on the Yosemite trails to ask random strangers questions about why they were hiking and if they would be her friend. Since then, she has continued to ask why but usually refrains from asking subjects during interviews if they want to be her friend.
By high school she learned what a real small town is, after moving to Genoa, Nevada, population 500. She was a very nerdy speech and debater, but collected more trophies in that than she did in soccer and tennis, so she made a point of doing all of them, to, you know, run with the cool crowd too, breaking social barriers and everything you would see in a John Hughes film. She graduated from Douglas High School in 2009 and shipped off to the University of Notre Dame, where she graduated cum laude with a B.A. in Political Science and Film, Television and Theatre in May 2013. She also has a minor in Journalism, Ethics, and Democracy, because why do college if you can't do it all?
Currently, Clara is a freelance video director and producer based in New York, NY. She works across mediums in digital, TV and film, and has recently worked with NBC News, the Wall Street Journal and PBS. Her curiosity about the world has led her to tell stories across industries, including finance, health, food, travel, fashion, and the environment. She partners with media companies, brands, and nonprofits to create emotional, shareable stories.
Prior to moving to NYC, Clara was based in the Washington, D.C. area as a Producer at Green Buzz Agency, where she created documentary style videos for major brands and nonprofits, including Upworthy and Make-A-Wish. She has also written and/or done multimedia work for National Journal, The Indianapolis Star, USA Today, The Philadelphia Inquirer, Pittsburgh Post-Gazette, Pittsburgh Tribune-Review, Patriot-News, Morning Call, Capitolwire, Northern Virginia Magazine, 88.1 WVPE NPR, the Reno Gazette-Journal, NDtv News and the oldest collegiate publication in the United States, Scholastic magazine.
Clara really likes coffee, and once bought everything on the menu at Starbucks because she had extra monopoly money at school and wanted to find out what her favorite drink actually was. It cost her $134.80. She also enjoys cooking and a good book. She is not one of those freak people who enjoys running, but she does it anyway, because it is good for you, or something like that. Her middle name is Lucille, which invariably comes up in conversation, so now you know.
Clara does not feel that autobiographies – especially at her age – should be taken seriously.
The Great American Cooking Story
Staff Me Up


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