text:
\section{Introduction}
Prompt learning aims to design or learn appropriate prompts which can induce the capacity from pre-trained language models (PLMs) to perform specific tasks, and it becomes a new paradigm to use PLMs due to its flexibility and fewer extra parameters. There are typically two kinds of prompts, namely discrete prompt and continuous prompt. Discrete prompt such as GPT-3 \cite{Brown2020LanguageMA} uses the task instructions and task-related instances as prompt for zero-shot and few-shot learning respectively. PET/iPET \cite{schick-schutze-2021-exploiting,schick-schutze-2021-just} utilizes the manually-designed prompts to reformulate many tasks as cloze questions (e.g., by appending phrases such as ``Similar sense of two sentences?") and performs gradient-based fine-tuning with smaller PLMs. To simplify PET/iPET, ADAPET \cite{tam-etal-2021-improving} decouples the losses for the label tokens and a label-conditioned masked language modeling objective over the full original input. Considering that manually designing the discrete prompts is time-consuming and labor-intensive, several efforts focus on searching proper discrete prompts automatically \cite{shin-etal-2020-autoprompt,gao2020making,zhong-etal-2021-factual}.\par
\begin{figure}[t]
    \centering
    \includegraphics[width=8.5cm]{case.pdf}
    \caption{The example is chosen from WiC dataset in SuperGLUE. The color words indicate the manually-designed patterns which are used to formalize the instance into close-style questions.}
    \label{fig1:prompt-tuning}
\end{figure}
Although discrete prompts can reflect rationality from the perspective of humans, it may not be necessarily suitable for PLMs. To tackle this problem, a lot of studies begin to focus on continuous prompts. Continuous prompts can be thought of as special tokens. \cite{lester2021power} proposes prompt tuning and concatenates the continuous prompts with the embedding layer of PLMs. When using small PLMs, the performance of prompt tuning has a clear gap with fine-tuning. \cite{li-liang-2021-prefix} proposes prefix tuning and shows comparable results with fine-tuning on generation tasks. Prefix tuning concatenates continuous prompts with each layer in the decoder and only optimizes $0.1\% $ of the model parameters. However, the current usage of discrete and continuous prompts assumes that all samples in one task share the same prompt, and does not consider
the diversity of the instances in which some are easy and others are difficult. Therefore, it is desirable to learn a special prompt for each instance.\par
In this paper, we propose an \textbf{I}nstance-aware \textbf{P}rompt \textbf{L}earning method (abbreviated as IPL) which learns a unique prompt for each instance. As shown in Figure \ref{fig1:prompt-tuning}, we use two different manually-designed patterns to formalize the instances into cloze-style questions and feed them into the pre-trained language model (PLM). As we can see, for each instance, using different prompts can get different answers. Pattern 1 is suitable for instance 1, while pattern 2 fits instance 2, which means that every instance needs a specific prompt for itself. However, it is difficult to dynamically find an appropriately discrete prompt for each instance. Therefore, we consider to utilize a look-up module and obtain a dynamic continuous prompt for each instance. Specifically, we take each learnable prompt token as a query and calculate its contribution to each instance through the look-up module. After doing this, each learnable prompt token has a different contribution to the instance and the contribution weighted continuous prompts are then utilized to guide the PLMs to perform the downstream task more instance-aware.\par
We evaluate our approach on natural language understanding (NLU) and generation (NLG) tasks. For NLU tasks, we conduct experiments on SuperGLUE \cite{Wang2019SuperGLUEAS} with both GPT2 \cite{radford2019language} and RoBERTa \cite{Delobelle2020RobBERTAD}. For NLG tasks, we conduct experiments on table-to-text generation and summarization using GPT2. Experimental results on various tasks demonstrate that our method obtains considerable improvements compared to strong baselines. Especially, our method achieves the new state-of-the-art on the SuperGLUE few-shot learning benchmark. In summary, our key contributions can be listed as follows: \par
\begin{itemize}
\item {We propose an instance-aware prompt learning method that can learn a unique prompt for each instance.} \par
\item {Extensive experiments on both language understanding and generation tasks under both unidirectional and bidirectional PLMs verify the effectiveness of our method.}\par
\item {Detailed analyses verify that IPL can indeed dynamically learn appropriate continuous prompts for each instance.} \par
\end{itemize}

\begin{table*}[t]
\centering
\tiny
\resizebox{\textwidth}{!}{%
\renewcommand{\arraystretch}{1.0}
\tiny
\begin{tabular}{@{}lcccccccc|c@{}}
\toprule
{Method} &
  {\begin{tabular}[c]{@{}c@{}}{BoolQ}\\ Acc.\end{tabular}} &
  {\begin{tabular}[c]{@{}c@{}}CB\\ Acc./F1\end{tabular}} &
  {\begin{tabular}[c]{@{}c@{}}MultiRC\\ EM/F1a\end{tabular}} &
  {\begin{tabular}[c]{@{}c@{}}RTE\\ Acc.\end{tabular}} &
  {\begin{tabular}[c]{@{}c@{}}WiC\\ Acc.\end{tabular}} &
  {\begin{tabular}[c]{@{}c@{}}COPA\\ Acc.\end{tabular}} &
  {\begin{tabular}[c]{@{}c@{}}WSC\\ Acc.\end{tabular}} &
  {\begin{tabular}[c]{@{}c@{}}ReCoRD\\ Acc./F1\end{tabular}} &
  \multicolumn{1}{l}{Avg} \\ \midrule
GPT-3{\tiny $^{\dagger}$}  & 77.5          & 82.1/57.2          & 32.5/74.8          & 72.9          & 55.3           & 92.0          & 75.0             & \textbf{89.0}/90.1 & 73.2          \\
PET{\tiny $^{\dagger}$}    & 79.4          & 85.1/59.4          & 37.9/77.3          & 69.8          & 52.4           & \textbf{95.0} & 80.1           & 86.0/86.5          & 74.1          \\
iPET{\tiny $^{\dagger}$}   & \textbf{80.6} & \textbf{92.9}/92.4          & 33.0/74.0          & 74.0            & 52.2           & \textbf{95.0} & 80.1           & 86.0/86.5          & 76.8          \\
ADAPET{\tiny $^{\ddagger}$} & 80.3          & 89.3/86.8          & \textbf{39.2/80.1} & \textbf{76.5} & 54.4           & 89.0          & 81.7           & 85.4/92.1          & 77.3          \\
\hline
IPL   & 79.2          & \textbf{92.9/94.8} & 38.5/76.8        & 76.2          & \textbf{64.6} & 91.0          & \textbf{84.8} & 83.6/\textbf{91.1}        & \textbf{79.3} \\ \hline
\end{tabular}%
}
\caption{Few-shot learning (32 examples) on SuperGLUE validation set with ALBERT-xxlarge-v2. $\dagger$ indicates the results reported in \protect\cite{schick-schutze-2021-just}, and $\ddagger$ indicates the results reported in \protect\cite{tam-etal-2021-improving}. }
\label{table1}
\end{table*}

\begin{table*}[]
\centering
\resizebox{\textwidth}{!}{%
\renewcommand{\arraystretch}{1.0}
\tiny
\begin{tabular}{@{}lcccccccc|c@{}}
\toprule
{Method} &
  {\begin{tabular}[c]{@{}c@{}}BoolQ\\ Acc.\end{tabular}} &
  {\begin{tabular}[c]{@{}c@{}}CB\\ Acc./F1\end{tabular}} &
  {\begin{tabular}[c]{@{}c@{}}MultiRC\\ EM/F1a\end{tabular}} &
  {\begin{tabular}[c]{@{}c@{}}RTE\\ Acc.\end{tabular}} &
  {\begin{tabular}[c]{@{}c@{}}WiC\\ Acc.\end{tabular}} &
  {\begin{tabular}[c]{@{}c@{}}COPA\\ Acc.\end{tabular}} &
  {\begin{tabular}[c]{@{}c@{}}WSC\\ Acc.\end{tabular}} &
  {\begin{tabular}[c]{@{}c@{}}ReCoRD\\ Acc./F1\end{tabular}} &
  \multicolumn{1}{l}{Avg} \\ \midrule
GPT-3$^{\dagger}$ &
  76.4 &
  75.6/52.0 &
  30.5/75.4 &
  69.0 &
  49.4 &
  \textbf{92.0} &
  80.1 &
  \textbf{90.2/90.1} &
  71.8 \\
PET$^{\dagger}$ &
  79.1 &
  87.2 / 60.2 &
  \textbf{36.4 / 76.6} &
  67.2 &
  50.7 &
  90.8 &
  \textbf{88.4} &
  85.4 / 85.9 &
  74.0 \\
iPET$^{\dagger}$ &
  \textbf{81.2} &
  88.8/79.9 &
  31.7/74.1 &
  70.8 &
  49.3 &
  90.8 &
  \textbf{88.4} &
  85.4 / 85.9 &
  75.4 \\
ADAPET$^{\ddagger}$ &
  80.0 &
  \textbf{92.0}/82.3 &
  35.7 / 76.2 &
  \textbf{75.0} &
  53.5 &
  85.4 &
  85.6 &
  85.5 / 86.1 &
  76.0 \\
\hline
IPL &
  78.4 &
  \textbf{92.0/85.9} &
  {\color[HTML]{212121} 35.1/75.9} &
  74.9 &
  \cellcolor[HTML]{FFFFFF}\textbf{60.9} &
  85.6 &
  84.9 &
  83.5/84.3 &
  \textbf{76.6} \\ \hline
\end{tabular}
}
\caption{Few-shot learning (32 examples) on SuperGLUE test set with ALBERT-xxlarge-v2. $\dagger$ indicates the results reported in \protect\cite{schick-schutze-2021-just}, and $\ddagger$ indicates the results reported in \protect\cite{tam-etal-2021-improving}}
\label{table2}
\end{table*}
\section{Approach}
In this section, we present the details of our model IPL.
\begin{figure}[t]
    \centering
    \includegraphics[width=8cm]{Figure1.pdf}
    \caption{Illustration of our approach. $[P_1,P_2,P_3,\cdot\cdot\cdot,P_l]$ represents the prompt tokens. $[T_1,T_2,T_3,\cdot\cdot\cdot,T_n]$ represents the input tokens. $\{\bm{e_1},\bm{e_2},\bm{\cdot\cdot\cdot},\bm{e_n}\}$ represents the embeddings of input tokens. $\{\bm{p_1},\bm{p_2},\bm{\cdot\cdot\cdot},\bm{p_n}\}$ is the learnable prompt, and $[\bm{\hat {p_1}},\bm{\hat {p_2}},\bm{\cdot\cdot\cdot},\bm{\hat {p_l}}]$ refers to the weighted representation for the input instance.}
    \label{fig:Instance-aware prompt tuning}
\end{figure}
Previous studies demonstrate that prompt learning is promising for downstream tasks. However, using fixed prompts (e.g., discrete prompts like "convert the table into a sentence" or continuous prompts after optimization) for diverse instances in one task ignores the peculiarity of different instances. To address this problem, our instance-aware prompt learning method IPL can learn a special prompt for each specific instance. Next, we introduce prompt learning first and then present our IPL model.
\subsection{Prompt Learning}
For the standard paradigm of pre-training and fine-tuning, there is a gap (e.g., inconsistent objective function) between the pre-training stage and the fine-tuning stage. Fortunately, prompt learning bridges this gap by formalizing the downstream tasks into the form of a conditional language model or masked language model. Discrete prompt is an important method in prompt learning, for instance, given a masked language model $\mathcal{M}$, we first use the prompt to formulate a question and answer instance $x$ (e.g., [passage]. Can you have too much oxygen in your body ? ) as:
\begin{equation}\nonumber
\begin{aligned}
\hat{x} = x\ \text{the answer is [MASK]}.
\end{aligned}
\end{equation}
Then $\hat{x}$ is fed into $\mathcal{M}$, and let $\mathcal{M}$ determine whether "Yes" or "No" is more appropriate to replace [MASK] \cite{gao2020making}.\par
Continuous prompt is an alternative approach in prompt learning. Suppose we get the embedding sequence $\{\bm{e_1},\bm{e_2},\bm{\cdot\cdot\cdot},\bm{e_n}\}$ of the instance $x$, and we concatenate the continuous prompt (e.g., as shown in the red dotted box in Figure \ref{fig:Instance-aware prompt tuning}) $\{\bm{p_1},\bm{p_2},\bm{\cdot\cdot\cdot},\bm{p_l}\}$ with the embedding sequence, which can be formalized as follows:
\begin{equation}\nonumber
\begin{aligned}
\quad\quad\ \ \bm{\hat{x}} = \{\bm{p_1},\bm{p_2},\bm{\cdot\cdot\cdot},\bm{p_l};\bm{e_1},\bm{e_2},\bm{\cdot\cdot\cdot},\bm{e_n}\}
\end{aligned}
\end{equation}
Then, $\bm{\hat{x}}$ is fed into $\mathcal{M}$ to generate the target labels.\par
In this paper, we combine the advantages of continuous prompts with discrete prompts and propose an instance-aware prompt learning method which learns a unique prompt for each instance. Next, we detail our proposed IPL mdoel.
\subsection{Instance-aware Prompt Learning}\label{instance-aware}
We denote $\mathcal{T}$ as an instance in a form of a sequence consisting of n tokens $\mathcal{T}=\{T_1,T_2,\cdot\cdot\cdot,T_n\}$. We follow  \cite{li-liang-2021-prefix,lester2021power}, and use learnable prompts of special tokens $\mathcal{P} = \{P_1,P_2,\cdot\cdot\cdot,P_l\}$ and update the embeddings of these prompt tokens during prompt learning. As shown in Figure \ref{fig:Instance-aware prompt tuning}, we first use the pre-trained language model to obtain the embedding sequence $\{\bm{e_1},\bm{e_2},\bm{\cdot\cdot\cdot},\bm{e_n}\}$ of $\mathcal{T}$, and get a matrix $\bm{X}\in\mathbb{R}^{n\times d_e}$, where $n$ is the length of instance $\mathcal{T}$, $d_e$ is the dimension of the embedding space. Then we create a learnable matrix $\bm{P}=\{\bm{p_1},\bm{p_2},\bm{\cdot\cdot\cdot},\bm{p_l}\}$ of $\mathcal{P}$, where $l$ is the length of the prompt, and  $\bm{P}\in\mathbb{R}^{l\times d_e}$. After we get the prompt matrix $\bm{P}$ and embedding matrix $\bm{X}$, we use the projection matrices $\bm{W^M}\in\mathbb{R}^{d_e\times d_h}$ and $\bm{W^N}\in\mathbb{R}^{d_e\times d_h}$ to map $\bm{P}$ and $\bm{X}$ into matrix $\bm{M}\in\mathbb{R}^{l\times d_h}$ and $\bm{N}\in\mathbb{R}^{n\times d_h}$ respectively, where $d_h$ is the dimension of projection space.
\begin{equation}
\begin{split}
    \bm{M} &= \bm{P W^M} \\
    \bm{N} &= \bm{X W^N}
\end{split}
\end{equation}
\par
We suppose that each learnable prompt token has a different contribution to different instances and we learn the contribution scores by calculating the relevance score between matrix $\bm{M}=\{\bm{p_1^\prime},\bm{p_2^\prime},\bm{\cdot\cdot\cdot},\bm{p_l^\prime}\}$ and $\bm{N}=\{\bm{e_1^\prime},\bm{e_2^\prime},\bm{\cdot\cdot\cdot},\bm{e_n^\prime}\}$. After we get the relevance score, we pass the score to the look-up module. In the look-up module, we adopt a method of mean operation and apply a sigmoid function $\sigma$ to obtain how much does each learnable prompt token contributes to the instance $\mathcal{T}$. The detailed calculation is as follows:
\begin{gather}
    s_j = \sigma(\frac{1}{n}\sum_{i=1}^{n}\bm{p_j^\prime}\cdot\bm{{e_n^\prime}^T}) \\
    \bm{\hat p_j} = s_j\cdot \bm{p_j}
\end{gather}
where $\bm{{e_n^\prime} ^T}$ is the transpose of $\bm{e_n}$. $\bm{ p_j^{\prime}}$ is the contribution of the \emph{j}-th prompt token to the instance $\mathcal{T}$. $s_j$ is the contribution score of the \emph{j}-th prompt token after applying a sigmoid funtion $\sigma$, and $\bm{\hat {p_j}}$ is the \emph{j}-th weighted representation for the instance. After doing such a calculation for all prompt tokens, we get the weighted prompt as $\bm{\hat{P}}=\{\bm{\hat {p_1}},\bm{\hat {p_2}},\bm{\cdot\cdot\cdot},\bm{\hat {p_l}}\}$. Then we concatenate weighted continuous prompt with the embedded instance as a new matrix $[\bm{\hat{P}};\bm{X}]\in\mathbb{R}^{(l+n)\times d_e}$, and feed it into the pre-trained language model.\par
During training, we optimize the parameters of prompt module and PLMs. We do not freeze the model parameters as \cite{lester2021power} does, because their results demonstrates that the gap between prompt tuning and fine-tuning disappear only when the model size increases to 10 billion parameters.
\begin{table*}[]
\centering
\resizebox{\textwidth}{!}{%
\tiny
\renewcommand{\arraystretch}{1.2}
\begin{tabular}{@{}ccccccl|lccccc@{}}
\toprule
\textbf{Method} &
  \begin{tabular}[c]{@{}c@{}}BoolQ\\ Acc.\end{tabular} &
  \begin{tabular}[c]{@{}c@{}}CB\\ Acc./F1\end{tabular} &
  \begin{tabular}[c]{@{}c@{}}MultiRC\\ F1a/EM\end{tabular} &
  \begin{tabular}[c]{@{}c@{}}RTE\\ Acc.\end{tabular} &
  \begin{tabular}[c]{@{}c@{}}WiC\\ Acc.\end{tabular} &
   &
   &
  \begin{tabular}[c]{@{}c@{}}BoolQ\\ Acc.\end{tabular} &
  \begin{tabular}[c]{@{}c@{}}CB\\ Acc./F1\end{tabular} &
  \begin{tabular}[c]{@{}c@{}}MultiRC\\ F1a/EM\end{tabular} &
  \begin{tabular}[c]{@{}c@{}}RTE\\ Acc.\end{tabular} &
  \begin{tabular}[c]{@{}c@{}}WiC\\ Acc.\end{tabular} \\ \hline \hline
\multicolumn{1}{c}{} &
  \multicolumn{1}{c}{} &
  \multicolumn{1}{c}{} &
  \texttt{GPT2-base} &
  \multicolumn{1}{c}{} &
  \multicolumn{1}{c}{} &
   &
   &
  \multicolumn{1}{c}{} &
  \multicolumn{1}{c}{} &
  \texttt{GPT2-large} &
  \multicolumn{1}{c}{} &
  \multicolumn{1}{c}{} \\
\hline
\hline
PET &
  74.55 &
  94.05/95.58 &
  {70.36/\textbf{22.87}} &
  67.14 &
  65.67 &
   &
   &
  80.43 &
  92.86/94.75 &
  75.81/32.42 &
  78.70 &
  \textbf{70.22} \\
PT &
  74.16 &
  92.86/94.70 &
  69.84/21.16 &
  67.03 &
  64.16 &
   &
   &
  79.66 &
  96.43/97.37 &
  75.81/\textbf{34.10} &
  75.45 &
  69.12 \\
\hline
IPL &
  \textbf{74.89} &
  \textbf{94.64/96.03} &
  \textbf{70.54}/22.35 &
  \textbf{69.68} &
  \textbf{66.72} &
   &
   &
  \textbf{80.80} &
  \textbf{98.21/98.67} &
  \textbf{76.00}/33.26 &
  \textbf{80.14} &
  69.59 \\ \hline
\end{tabular}%
}
\caption{Fully-supervised learning on SuperGLUE validation set with unidirectional pre-trained language models. PET means PET fine-tuning with a single pattern, and PT refers to prompt-tuning. For a fair comparison, we use the same pattern for all models.}
\label{table3}
\end{table*}
\begin{table*}[]
\centering
\resizebox{\textwidth}{!}{%
\tiny
\renewcommand{\arraystretch}{1.2}
\begin{tabular}{@{}ccccccl|lccccc@{}}
\toprule
\textbf{Method} &
  \begin{tabular}[c]{@{}c@{}}BoolQ\\ Acc.\end{tabular} &
  \begin{tabular}[c]{@{}c@{}}CB\\ Acc./F1\end{tabular} &
  \begin{tabular}[c]{@{}c@{}}MultiRC\\ F1a/EM\end{tabular} &
  \begin{tabular}[c]{@{}c@{}}RTE\\ Acc.\end{tabular} &
  \begin{tabular}[c]{@{}c@{}}WiC\\ Acc.\end{tabular} &
   &
   &
  \begin{tabular}[c]{@{}c@{}}BoolQ\\ Acc.\end{tabular} &
  \begin{tabular}[c]{@{}c@{}}CB\\ Acc./F1\end{tabular} &
  \begin{tabular}[c]{@{}c@{}}MultiRC\\ F1a/EM\end{tabular} &
  \begin{tabular}[c]{@{}c@{}}RTE\\ Acc.\end{tabular} &
  \begin{tabular}[c]{@{}c@{}}WiC\\ Acc.\end{tabular} \\ \hline\hline
\multicolumn{1}{c}{} &
  \multicolumn{1}{c}{} &
  \multicolumn{1}{c}{} &
  \texttt{RoBERTa-base} &
  \multicolumn{1}{c}{} &
  \multicolumn{1}{c}{} &
   &
   &
  \multicolumn{1}{c}{} &
  \multicolumn{1}{c}{} &
  \texttt{RoBERTa-large} &
  \multicolumn{1}{c}{} &
  \multicolumn{1}{c}{} \\
\hline
\hline
PET &
  80.03 &
  \textbf{96.43/95.56} &
  76.05/\textbf{35.12} &
  82.67 &
  69.28 &
   &
   &
  85.47 &
  98.81/99.12 &
  83.36/\textbf{51.07} &
  87.12 &
  70.85 \\
PT &
  80.32 &
  96.43/94.76 &
  76.05/33.44 &
  80.14 &
  68.86 &
   &
   &
  85.44 &
  98.81/99.12 &
  83.23/50.75 &
  87.01 &
  72.14 \\
\hline
IPL &
  \textbf{80.63} &
  \textbf{96.43/95.56} &
  \textbf{76.19}/34.59 &
  \textbf{82.91} &
  \textbf{70.85} &
   &
   &
  \textbf{85.66} &
  \textbf{99.40/99.56} &
  {\textbf{83.40}/50.89}&
  \textbf{87.48} &
  \textbf{73.51} \\ \hline
\end{tabular}%
}
\caption{Fully-supervised learning on SuperGLUE validation set with bidirectional pre-trained language models. PET means PET fine-tuning with a single pattern, and PT refers to prompt tuning. For a fair comparison, we use the same pattern for all the models.}
\label{table4}
\end{table*}
\section{Experiments}
To evaluate our method IPL, we conduct experiments on both NLU tasks and NLG tasks. For NLU tasks, we evaluate IPL on SuperGLUE$\footnote{\url{https://supergluebenchmark.com/}}$ \cite{Wang2019SuperGLUEAS}. And we evaluate IPL for few-shot learning by using 32 labeled examples per task from FewGLUE\footnote{\url{https://github.com/timoschick/fewglue}} \cite{schick-schutze-2021-just}). For NLG tasks, we select 3 standard table-to-text generation tasks: E2E \cite{Novikova2017TheED}, WebNLG \cite{Gardent2017TheWC}, DART \cite{Radev2021DARTOS} and a dialogue summarization task: SamSum \cite{Gliwa2019SAMSumCA}.
 \subsection{Experiments on NLU Tasks}
 Our code is implemented based on PET$\footnote{\url{https://github.com/timoschick/pet}}$ using HuggingFace \cite{Wolf2020TransformersSN}.
The experiment results include the few-shot learning results and fully-supervised learning results.
\subsubsection{Few-shot Learning Results}
 For a fair comparison, we choose ALBERT-xxlarge-v2 \cite{Lan2020ALBERTAL} for experiments and use the same data split as \cite{schick-schutze-2021-just}, which consists of 32 labeled examples for each task. We use a default setting training for 20 epochs, using a learning rate of 1e-5, a batch size of 8, and a prompt length of 16.\par
Our main results on the validation and test sets on SuperGLUE are shown in Table \ref{table1} and Table \ref{table2}. We compare against GPT-3, PET/iPET and ADAPET. Initially, ADAPET does not use the unlabeled data and achieves the state-of-the-art on SuperGLUE few-shot learning tasks compared to PET/iPET which uses the unlabeled data. And for IPL, we train IPL with a single pattern and do not use the unlabeled data.\par
As can be seen from Table \ref{table1}, on average, IPL outperforms GPT-3 by 6 points; outperforms PET's iterative variant, iPET, by 2.5 points, and even outperforms the previous state-of-the-art model ADAPET by 2 points on the dev set. Specifically, compared with iPET and GPT-3, IPL achieves improvements on 5 out of the 8 tasks and 6 out of the 8 tasks respectively, demonstrating the effectiveness of our method in few-shot NLU tasks. We will conduct detailed analysis in \ref{Visualization of Instance Aware Prompt}.\par
We also report the test set on SuperGLUE in Table \ref{table2}, IPL outperforms all other models including ADAPET, which is the previous state-of-the-art model, and obtains the new state-of-the-art for few-shot learning on SuperGLUE.\par
\subsubsection{Fully-supervised Learning Results}
To verify IPL on various PLMs, we perform experiments on 5 out of the 8 tasks of SuperGLUE benchmark including BoolQ, MultiRC, RTE, CB, and WiC, where we choose both unidirectional PLMs GPT-2 and bidirectional PLMs RoBERTa. We report the performance of fine-tuning with PET \cite{schick-schutze-2021-exploiting}, prompt tuning \cite{lester2021power}, and our method IPL. We use a default setting training for 20 epochs, using a learning rate of 2e-5, a batch size of 32, and a prompt length of 16.\par
Table \ref{table3} and Table \ref{table4} show our main results on GPT-2 and RoBERTa. On unidirectional PLMs like GPT2-base and GPT2-large, IPL outperforms PET fine-tuning and prompt tuning on all 5 tasks with GPT2-base and 4 out of 5 tasks on GPT2-large. On bidirectional PLMs like RoBERTa-base and RoBERTa-large, IPL outperforms all other RoBERTa-based models on all 5 tasks. Based on the experiment results, we demonstrate that IPL can achieve great results on both GPT-2 and RoBERTa models.
\subsection{Experiment on NLG Tasks}
For NLG tasks, we compare IPL on GPT2-base and GPT2-large with two baseline methods: the standard fine-tuning, and prompt tuning, where we do not freeze the model parameters as IPL does. The experiment results are illustrated in Table \ref{table5} and Table \ref{table6}. We choose three table-to-text tasks and a summarization task. For table-to-text tasks, on E2E, we use the official evaluation script, which reports BLUE \cite{Papineni2002BleuAM}, NIST \cite{Belz2006ComparingAA}, ROUGE-L \cite{Lin2004ROUGEAP}, and CIDEr \cite{Vedantam2015CIDErCI}. On WebNLG, we use the official evaluation script, which reports BLEU, METEOR \cite{Lavie2007METEORAA}, and TER \cite{snover-etal-2006-study}. On DART, we use the official evaluation script and report BLEU, METEOR, TER, and BERTScore \cite{Zhang*2020BERTScore:}. As for the summarization task: SamSum, we report ROUGE-1, ROUGE-2, and ROUGE-L. The hyperparameters we tune include the number of epochs, batch size, learning rate, and prefix length. For table-to-text tasks, we set batch size as 32, prefix length as 10, the number of epochs as 10 for both GPT2-base and GPT2-large, in addition to the learning rate as 5e-5 for GPT-base, 5e-6 for GPT-large. For the summarization task, we set the prefix length as 100 and other hyperparameters keep consistent with table-to-text tasks.
\begin{table*}[]
\centering
\resizebox{\textwidth}{!}{%
\small
\renewcommand{\arraystretch}{1.4}
\begin{tabular}{@{}ccccc|ccc|ccc|ccc|cccc@{}}
\toprule
 &
  \multicolumn{4}{c}{E2E} &
  \multicolumn{9}{c}{WebNLG} &
  \multicolumn{4}{c}{DART} \\
\multicolumn{1}{l}{} &
  \multicolumn{1}{l}{BLUE} &
  \multicolumn{1}{l}{NIST} &
  \multicolumn{1}{l}{R\_L} &
  \multicolumn{1}{l}{CIDEr} &
  \multicolumn{3}{c}{BLUE} &
  \multicolumn{3}{c}{MET} &
  \multicolumn{3}{c}{TER $\downarrow$} &
  \multicolumn{1}{l}{BLUE} &
  \multicolumn{1}{l}{MET} &
  \multicolumn{1}{l}{TER $\downarrow$} &
  \multicolumn{1}{l}{BERT} \\ \hline
 &
   &
   &
   &
   &
  Seen &
  Unseen &
  All &
  Seen &
  Unseen &
  All &
  Seen &
  Unseen &
  All &
   &
   &
   &
  \multicolumn{1}{l}{} \\
\midrule\midrule
\multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{\texttt{GPT2-base}} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} \\
\midrule\midrule
FT &
  69.55 &
  8.79 &
  71.52 &
  \textbf{2.49} &
  56.01 &
  26.46 &
  41.70 &
  39.33 &
  25.04 &
  32.46 &
  46.40 &
  81.80 &
  62.63 &
  42.08 &
  35.17 &
  52.58 &
  94.12 \\
PT &
  69.78 &
  8.81 &
  71.55 &
  \textbf{2.49} &
  60.55 &
  28.03 &
  45.51 &
  43.25 &
  28.82 &
  36.30 &
  38.03 &
  74.17 &
  54.60 &
  \textbf{45.27} &
  \textbf{37.62} &
  49.83 &
  94.76 \\
\hline
IPL &
  \textbf{69.82} &
  \textbf{8.82} &
  \textbf{71.65} &
  \textbf{2.49} &
  \textbf{60.93} &
  \textbf{29.94} &
  \textbf{46.46} &
  \textbf{43.27} &
  \textbf{29.15} &
  \textbf{36.50} &
  \textbf{37.76} &
  \textbf{72.23} &
  \textbf{53.56} &
  42.98 &
  35.62 &
  \textbf{48.50} &
  \textbf{95.43} \\
\midrule\midrule
\multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{\texttt{GPT2-large}} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} &
  \multicolumn{1}{l}{} \\
\midrule\midrule
FT &
  68.32 &
  \textbf{8.76} &
  \textbf{71.25} &
  2.48 &
  62.11 &
  43.52 &
  53.61 &
  44.56 &
  37.39 &
  41.21 &
  37.06 &
  53.62 &
  44.65 &
  47.16 &
  38.24 &
  47.35 &
  94.43 \\
PT &
  68.32 &
  8.65 &
  71.04 &
  2.49 &
  \textbf{64.18} &
  46.04 &
  55.85 &
  \textbf{45.30} &
  38.62 &
  \textbf{42.17} &
  \textbf{34.81} &
  50.92 &
  \textbf{42.19} &
  \textbf{48.57} &
  39.04 &
  \textbf{46.12} &
  94.90 \\
\hline
IPL &
  \textbf{68.53} &
  8.68 &
  71.2 &
  \textbf{2.51} &
  64.06 &
  \textbf{46.12} &
  \textbf{55.90} &
  45.24 &
  \textbf{38.64} &
  42.12 &
  35.28 &
  \textbf{50.55} &
  42.28 &
  48.38 &
  \textbf{39.15} &
  46.17 &
  \textbf{95.47} \\ \hline
\end{tabular}%
}
\caption{The best score is in bold for both GPT2-base and GPT2-large. The FT refers to fine-tuning. PT refers to prompt tuning. For the metrics, the higher the better except for TER.}
\label{table5}
\end{table*}
\subsubsection{Results on NLG Tasks}
As shown in Table \ref{table5}, on GPT2-base, IPL performs better than fine-tuning and prompt tuning on E2E and WebNLG, while on DART, which is an open domain table-to-text dataset, IPL slightly underperforms prompt tuning. On GPT2-large, IPL outperforms fine-tuning and can be comparable or better than prompt tuning. Additionally, IPL obtains better performance on WebNLG unseen domains suggesting that IPL can generalize to other domains better. For the summarization task, the results in Table \ref{table6} show IPL performs better than fine-tuning and prompt tuning on both GPT2-base and GPT2-large models, suggesting it has the potential to scale to even larger models. Above all, the results demonstrate that IPL can achieve great results on NLG tasks with GPT-2 model. \par
\begin{figure}[t]
\centering
\subfigure[Prompt length (Few-shot)]{
\begin{minipage}[t]{0.5\linewidth}
\centering
\includegraphics[width=4cm]{prompt_length.pdf}
\label{3a}
\end{minipage}%
}%
\subfigure[Prompt length (SamSum)]{
\begin{minipage}[t]{0.5\linewidth}
\centering
\includegraphics[width=4cm]{samsum.pdf}
\label{3b}
\end{minipage}%
}%
\caption{(a) Performance on validation set in the few-shot of SuperGLUE including WiC, WSC, and CB, while the prompt length varies in \{0,4,8,16,20,30,40\}. (b) Performance on SamSum while the prompt length varies in \{0,5,10,20,50,100\}.}
\end{figure}

\begin{figure}[t]
    \centering
    \includegraphics[width=8.8cm]{case_study.pdf}
    \caption{Attention visualization of different instances. (a) and (b) are similar instances, (a) and (c) or (b) and (c) are dissimilar instances. X-axis represents the input sequence without prompt, and Y-axis represents the prompt sequence.}
    \label{case_attention}

\end{figure}

\section{Analysis}\label{Analysis}
We conduct detailed analyses on IPL. Section \ref{prompt length} studies the effect of the prompt length on the performance of few-shot learning on SuperGLUE. Section \ref{Visualization of Instance Aware Prompt} visualizes the attention matrix of similar instances and dissimilar instances to verify the effectiveness of our approach. Section \ref{case_study} shows the results of different methods on different instances.
\subsection{Prompt Length}\label{prompt length}
We visualize the relationship between the performance and different prompt lengths (other settings are fixed). For NLU tasks, we conduct experiments on three tasks of SuperGLUE including CB, WSC, WiC using ALBERT-xxlarge-v2. Figure \ref{3a} shows that performance increases as the prompt length increases up to a threshold (16 for CB and WiC, 20 for WSC), and then the performance slightly drops. Figure \ref{3b} shows the effect of prompt length on the performance of different model sizes on SamSum. We can see that the performance consistently increases until the prompt length is up to 50. Continuing to increase the prompt length cannot yield significant improvements.

\subsection{Visualization of Instance-aware Prompt}\label{Visualization of Instance Aware Prompt}
We choose similar instances and dissimilar instances from WSC \cite{Levesque2011TheWS} for analysis. Figure \ref{case_attention} shows the analysis results for IPL on similar instances and dissimilar instances. We visualize the attention matrix of the instance and prompt. As shown in \ref{case_attention}(a) and \ref{case_attention}(b), the attention matrices between \ref{case_attention}(a) and \ref{case_attention}(b) are similar, which means IPL can produce similar prompts for similar instances. Comparing \ref{case_attention}(a) and \ref{case_attention}(c) or \ref{case_attention}(b) and \ref{case_attention}(c), we find that the attention matrices are not similar, suggesting that IPL can produce different prompts for dissimilar instances. Consequently, our approach learns a special prompt for each instance and can be aware of the important information of the instance.\par
\subsection{Case study}\label{case_study}
As shown in Figure \ref{figure5}, for indistinguishable instances, PET utilizes a fixed discrete prompt and makes a wrong judgment on the meaning of the word `put' and `department'. Prompt tuning prepends the fixed continuous prompt with the two instances based on the pattern of PET and also gives wrong answers. In contrast, our method IPL learns a unique prompt for each instance and contains much information of the instance yielding the correct answer.
\begin{table}[]
\centering
\small
\begin{tabular}{@{}cccc|ccc@{}}
\toprule
Method & R-1  & R-2  & R-L  & R-1  & R-2  & R-L  \\ \midrule\midrule
\multicolumn{1}{l}{} & \multicolumn{3}{c}{\texttt{GPT2-base}}                 & \multicolumn{3}{c}{\texttt{GPT2-large}}                \\ \midrule\midrule
FT     & 42.6 & 18.9 & 38.5 & 47.2 & 22.2 & 42.8 \\
PT     & 46.5 & 21.4 & 41.8 & 49.3 & 24.5 & 44.8 \\ \midrule
IPL                 & \textbf{46.6} & \textbf{21.7} & \textbf{42.0} & \textbf{49.7} & \textbf{24.8} & \textbf{45.0} \\ \midrule
\end{tabular}
\caption{Results for summarization on SamSum using GPT2 models. The FT refers to fine-tuning. PT refers to prompt tuning, and the best score is in bold.}
\label{table6}
\end{table}
\begin{figure}[t]
    \centering
    \includegraphics[width=8.8cm]{example.pdf}
    \caption{The instances are chosen from WiC dataset in SuperGLUE, which is shown on the top. We use the manually-designed pattern from PET. PT refers to prompt tuning. Our method is shown on the bottom, and the color words mean our approach can be aware of the important words in the instance.
}
    \label{figure5}
\end{figure}
\section{Related Work}
GPT-3 \cite{Brown2020LanguageMA}, which uses the task description and several typical examples as prompt to guide the generation, indicates the language models are few-shot learners and leads to the waves of prompt learning. Recently, PET/iPET \cite{schick-schutze-2021-just} utilizes the manually-designed prompts to reformulate natural language understanding tasks as cloze-style questions with gradient-based fine-tuning.
There are also a lot of studies that utilize the manually-designed prompt to mine the knowledge from the PLMs \cite{jiang-etal-2020-know,Trinh2018ASM}.
Since manual-designed prompt is time-consuming and the search space is huge, researches focus on automatic prompt search \cite{gao2020making,shin-etal-2020-autoprompt,zhong-etal-2021-factual}.

However, the handcrafted prompt can only reflect rationality from the perspective of humans, which midwifery the exploration in continuous prompts. \cite{li-liang-2021-prefix} proposes prefix tuning and concatenates learnable prompt at each layer of transformer while only optimizing the prefix parameters. In contrast, prompt tuning \cite{lester2021power} concatenates learnable prompt only in the embedding layer and only optimizes the prompt parameters in the embedding layer. Although \cite{lester2021power} demonstrates the effectiveness of light-weight prompt-tuning, the gap with full parameter fine-tuning still exists especially when the PLM is small.

There are also a lot of works that interleave the prompt throughout the input layer. \cite{hambardzumyan-etal-2021-warp} proposes WARP, initializing the prompt parameters either with word embeddings of [MASK] or similar to the vectors from the word embedding layer. Their work is based on a series of masked language models \cite{Delobelle2020RobBERTAD,Lan2020ALBERTAL} and uses a learnable output layer to project the mask to class logits, which restricts the model and only produces a single output. \cite{Liu2021GPTUT} proposes P-tuning, using the patterns based on human design and putting the continuous prompts interleave throughout the embedded input. When optimizing the model, P-tuning jointly updates both the prompt and model parameters to perform on SuperGLUE. Similarly, we borrow the idea of human designed patterns to convert different tasks into the form of conditional language model or masked language model, and also apply our method on GPT-2 and RoBERTa.

However, the above usage of the discrete and continuous prompts assumes that the prompt is fixed for a specific task and all samples in the task share the same prompt. Different from the above methods, our proposed IPL dynamically learns a special prompt for each instance and obtains considerable improvements compared to strong baselines.

Very recently, a contemporaneous work also presents another instance dependent prompt generation approach \cite{IDPG}, which studies only masked language model on only NLU tasks. In contrast, our IPL model is simple and effective for both unidirectional and bidirectional PLMs on both NLU and NLG tasks.\par

\section{Conclusion and Future Work}
In this paper, we propose an instance-aware prompt learning method named IPL, which learns a unique prompt for each instance. We find that IPL has the potential to be applied to both unidirectional and bidirectional PLMs on both language understanding and generation tasks. In the few-shot learning SuperGLUE benchmark, IPL outperforms all other models and obtains the new state-of-the-art. Detailed analysis demonstrates that our IPL model can indeed dynamically learn appropriate prompts for various instances.\par
In the future, we would explore how to generate better instance-aware prompts, and apply the instance-aware method to parameter-efficient tuning for more natural language processing tasks.
\bibliographystyle{named}

redpajama_set_name: RedPajamaArXiv


text:
Home QITO Quarterly International Trade Outlook (QITO) for Q3 2018
Quarterly International Trade Outlook (QITO) for Q3 2018
The British Chambers of Commerce (BCC), in partnership with DHL, has produced its Quarterly International Trade Outlook (QITO) for Q3 – July to September – 2018
The QITO report is based on survey and documentation data from more than 2,600 UK exporters and is designed to give British businesses a better understanding of international opportunities, with a focus on dynamic new markets. It also features a Trade Confidence Index, which measures the UK's exporting health by analysing trends in the volume of trade documentation issued by accredited Chambers of Commerce.
The findings of the Q3 2018 Outlook indicate that exporters continue to hold steady performance. Many exporters are performing well but economic and political factors are having an impact on their operations. Firms remain confident that export sales and turnover will increase over the next twelve months, with 38 per cent of exporting manufacturers enjoying an increase in export orders over the last three months.
Labour shortage continues to be the top concern. Exporters in manufacturing and service firms are reporting difficulties finding the right staff. In Q3 69 per cent of exporting manufacturers and 54 per cent of exporting service firms attempted to recruit; 76 per cent and 69 per cent of exporting manufacturers and exporting service firms said they faced challenges recruiting the right staff.
The BCC/DHL Trade Confidence Index, a measure of the volume of trade documentation issued nationally, fell by 3.9 per cent on the quarter. The Index now stands at 120.42.
Commenting on the findings, Ian Wilson, DHL Express UK & Ireland CEO, said the QITO report does show how uncertainty around the world can have an impact on businesses: "Resolution of the Brexit negotiations is critical to allow businesses to move forward; the facilitation of continued smooth and simple trade with the EU is paramount."
Claire Walker and Hannah Essex, Co-Executive Directors of Policy and Campaigns for British Chambers of Commerce, said: "the uncertainty of Brexit continues to weigh on many, as does currency fluctuations and global trade turmoil […] that said, UK businesses are resilient, and many exporters continue to perform strongly in the current circumstances"
"Our latest research shows that half of businesses would advise the government to prioritise future trade with the EU, compared to a third who would prioritise trade outside the EU. Given the importance of Europe as a trading partner the BCC believes the UK government's focus should be securing significant levels of market access British business currently have before undertaking new agreements around the world."
Trade and Economic Outlook
The International Monetary Fund (IMF) downgraded its outlook for the global economy for 2018 and 2019 to 3.7 per cent from its previous 3.9 per cent forecast.
The British Chambers of Commerce currently expect that the UK economy will grow by 1.1 per cent in 2018, by 1.3 per cent in 2019 and by 1.6 per cent in 2020.
The World Trad Organisation (WTO) forecasts global growth of 3.9 per cent this year and 3.7 in 2019, in line with the IMF.
Destination profiles
The Q3 2018 QITO report includes fact sheets for the USA, Canada, and South Mexico. Each fact sheet includes an economic snapshot, opportunities for UK businesses, market strengths, cultural tips, and Customs tips.
Read the full Q3 2018 QITO here

redpajama_set_name: RedPajamaCommonCrawl


text:
ContactParker
Parker United Kingdom
Most Reliable Fitting for Rail: EO-2 Soft-Sealing Fitting for Leak-Tightness
Posted by Parker United Kingdom Team on 2018, 11 09
The reliability of every component is significant for the design engineer of modern railway vehicles if they are to function smoothly in the long term.
The EO-2 fitting has been extremely reliable for application use in the rail industry. The soft-sealing fitting does not need to be re-tightened even after years of continual usage, and the seal is designed for long-term cost savings.
Furthermore, it is always an advantage for the assembler when components are simple, safe and quick to install - easily carried out with commercial tools. But there are other benefits.
Advantages of EO-2
1. Ermeto design
The main advantage lies in the design detail. The EO-2 was developed on the foundation of the Ermeto Cutting Ring System - a well-known concept. It features a special characteristic - a large-volume elastomeric seal. Invisible from the outside, the seal assures sustained function and leak-tightness even in extreme application conditions.
The profile of the EO-2 elastomeric seal shows a particularly large cross-section which seals safely even in unfavourable tolerance ranges of tubing and fittings. So the sealing effect is supported by the system pressure. This means that EO-2 fittings are well suited for high-pressure applications. Due to the high preload of the seal, the EO-2 design has formidable gas leak-tightness. This prevents the penetration of air in vacuum conditions.
In comparison with other fitting types, the EO-2 Series has an advantage because of optimal installation room without gaps and dead volume. For the user typical sealing damage such as spiral extrusion or wear caused by "pumping" are prevented.
2. The "assembly to dead-stop" advantage
An ever-recurring problem is under- and over-assembly. EO-2 eliminates this because before assembly of the fitting, a gap is located between the end faces of the sealing and retaining ring. This gap closes as soon as the retaining ring has reached its final cut depth into the tube. Assembly completion by this dead-stop is very clearly indicated. An equally good assembly outcome is achieved with manual assembly too. So completed assembly can be checked by an operator's quick visual inspection.
3. Greater safety through clearly perceptible assembly stop
As soon as the gap between both rings is closed, the EO-2 connection is ready for assembly-inspection and installation. If the functional nut is then tightened to spanner tightness, it is sufficient to tighten the connection with 1/4 to 1/6 of a turn. This clearly noticeable stop point increases the user's feeling of safety and prevents effectively dangerous under-assembly. And always remember this: "after fixed comes off". This will certainly be avoided with EO-2.
4. Meeting the standards
EO-2 Fittings meet DIN 2353 and ISO 8434. They are available for tube sizes from 6 -42 mm O.D. – which covers most situations. For warm temperatures, it can be used with no problems up to +200 °C. Conversely, arctic temperatures pose no problems. EO-2 fittings are available in steel and stainless steel depending on your application.
All EO-2 fittings are certified in accordance with EN45545-2 and EN61363 and also have the IRIS certification. For the designer, this means a universally deployable fitting which meets the current certification standards. This significantly simplifies designs.
5. Wide application range and ease of assembly
A big application range means wider design possibilities. EO-2 covers hydraulic and pneumatic applications. For the user, there are clearly reduced costs and assembly work. In addition, this fittings series is also well suited to restricted access situations.
EO-2 are well-greased and easily assembled. The threads of the standard smooth-coated retaining nuts are additionally treated with EO-LUB from sizes 25S/28L. The torques of EO-2 fittings are thereby reduced by about 25 percent and make their contribution to preventing dangerous under-assemblies.
6. Save procurement and warehousing costs with the EO-2 functional nut
In the EO-2 functional nut the sealing and retaining rings are assembled so that these three parts cannot be lost and form one design element. Because of this, individual parts such as seals and cutting rings cannot be forgotten, mixed up or fitted the wrong way round. All these kinds of mistakes that might be made must be avoided at all costs because they affect the safety of both passengers and railway personnel.
Individual parts do not have to be laboriously collected together during assembly. The user can shorten assembly times, reduce warehousing costs and into the bargain increase the security of his/her systems free of charge.
Viewed on the whole, the EO-2 Series, represents an attractive, safe and reliable alternative to comparable fittings systems. EO-2 is available worldwide and in the case of replacement, makes the procurement of the required components easier. EO-2 also meets the "Buy America Act." Click here to earn more about on EO-2 Fittings.
Article contributed to by Georg Kälble, manager marketing-service, High Pressure Connectors Europe, Parker Hannifin.
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Note to Most Reliable Fitting for Rail: EO-2 Soft-Sealing Fitting for Leak-Tightness
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The London Philharmonic Orchestra wishes to mark the eightieth birthday of British composer Harrison Birtwistle by commissioning and performing a new Piano Concerto specially created for virtuosic French pianist Pierre-Laurent Aimard. The Piano Concerto, supported by the Ernst von Siemens Music Foundation, will receive its UK premiere as part of the LPO's season at Southbank Centre's Royal Festival Hall and will be conducted by the Orchestra's Principal Conductor, Vladimir Jurowski, who is a major champion of new music and inventive, adventurous programming. The other pieces in the concert will be Stravinsky's works 'Orpheus' and 'Symphonies of Wind Instruments' as well as Messiaen's 'Oiseaux Exotiques'. Harrison Birtwistle is a grandee of European contemporary music. His works combine modernist aesthetic with mythic power and emotional impact, often taking inspiration from contemporary art and the rituals of classical mythology. Orchestral works include BBC Proms commission, 'Panic' and 'The Minotaur' for The Royal Opera. He won the Ernst von Siemens Music Prize in 1995.
In order to to offer maximum legacy and global exposure for the new work in a variety of territories, the LPO has put together a consortium of co-commissioning partners. This guarantees four performances of the work across two continents in the space of just four months and offers the possibility that it will be taken up quickly by other orchestras, promoters and venues. The co-commissioners are Bayerischer Rundfunk Musica Viva (Munich), Casa da Musica (Porto) and the Boston Symphony Orchestra.


The PSC ruled during a hearing with representatives from Drew this week that the city is in violation of Miss. Code Ann. 77-3-35 and 77-3-37, "having failed to seek Commission approval of rates for customers beyond one-mile of the corporate limits and failing to file schedules with the Commission showing those rates and charges.
Municipalities typically have jurisdiction over water rates inside their boundaries and one mile outside the city limits, but PSC has jurisdiction over areas beyond that one-mile radius.
During the 2013 Legislative session, Drew obtained enabling legislation through Senate Bill 2932 to construct, expand, operate and maintain a water distribution system in a certain area more than five miles from Drew's corporate limits, PSC said.
The Commission said it granted Drew a municipally-owned utility, a certificate of public convenience and necessity to provide water service.
This was conditional upon Drew filing a tariff with the Commission and seeking approval of initial rates, charges and a service extension policy, prior to assessing its customers for water service, PSC said in its ruling this week.
Drew now has until May 20 to file with the Commission a formal notice of intent to change rates in accordance with Rule 9 of the Public Utilities Rules of Practice & Procedure.
If they fail to do so, without obtaining an extension from the Commission, it may result in civil penalties in the amount up to and including $5,000 per day and/or result in a Commission-initiated service adequacy hearing, possibly resulting in certificate cancellation, the ruling said.


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What engine is in 318i?
BMW M42 engine
The 318i models were powered by the BMW M42 engine, which was used in the 318is model sold in other countries.
What engine does a BMW E30 1991 have?
The BMW E30 3 Series 318is (US) has a Inline 4, Petrol engine with 1796 cm3 / 109.6 cu-in capacity. How many horsepower (hp) does a 1991 BMW E30 3 Series 318is (US) have? The 1991 BMW E30 3 Series 318is (US) has 134 PS / 132 bhp / 99 kW.
What is a BMW M42 engine?
The BMW M42 is a DOHC four-cylinder petrol engine which was produced from 1989-1996. It is BMW's first mass-production DOHC engine and was produced alongside the BMW M40 SOHC four-cylinder engine as the higher performance engine. Later versions of the M42 also feature a dual length intake manifold ("DISA").
Is a BMW 318i a 3 cylinder?
BMW has brought back the 318i badge for the entry-level petrol 3 Series, and as is the norm these days, the numbers don't hint at what's under the bonnet. BMW has slotted in the same small petrol engine it uses in the 2 Series Active Tourer and MINI Cooper – a tiny 1.5-litre turbo with just three cylinders.
Is the BMW m42 engine reliable?
As a BMW tech I rarely see any major/costly problems on the M42. It's gutless(comparitively) and sounds like ass, but it's reliable.
How can you tell the difference between m44 and m42?
The difference in the intake manifold besides all the plastic pieces on the m44 is that the m42 has DISA and the m44 does not. The throttle bodies are different, the m44 has the ICV mounted on the TB and the m42 has it under the upper intake manifold. 4. The m42 has a vane type air meter and the m44 has a MAF.
Is BMW 318i a good car?
Is the BMW 318i a good & reliable car? So long as it is serviced on time and looked after well, the BMW 318i can be a great, reliable and enjoyable mode of transport. Although it is no tar-burning supercar the 318i has been known for 30 years as a well-made, pleasant way to get around town.
Are 3 cylinder engines good?
A 3 cylinder engine is much more fuel efficient compared to a 4 cylinder engine of the same size. This is because of two primary factors, reduced frictional losses and lighter weight. Both of these factors combined give 3 cylinder engines an upper hand in terms of fuel efficiency.
What kind of engine does a BMW 318i have?
My thoughts on the 1991 BMW 318i with the 1.8L Inline 4 cylinder engine and 5 speed manual transmission: I've always loved the E30. The boxy shape, the peppy… My thoughts on the 1991 BMW 318i with the 1.8L Inline 4 cylinder engine and 5 speed manual transmission: I've always loved the E30.
How many horsepower does a BMW 325i have?
By comparison, peak torque for the 325i engine was 215 N⋅m (159 lb⋅ft) at 4000 rpm. The 1987 Series 2 update boosted the 320i to 95 kW (127 hp) and the 325i to 125 kW (168 hp), and improved fuel economy.
What kind of engine does the BMW E30 have?
At the launch of the E30 range, the six-cylinder models consisted of the 320i, which had a 2.0 L (122 cu in) version of the M20 producing 92 kW (123 bhp), and the 323i, with a 2.3 L (140 cu in) M20 producing 102 kW (137 bhp), both using Bosch L-Jetronic fuel injection. These models were not sold in North America, presumably for emissions reasons.
What was the first BMW 3 series with all wheel drive?
The E30 325iX model was the first 3 Series to have all-wheel drive. The first BMW M3 model was built on the E30 platform and was powered by the high-revving BMW S14 four-cylinder petrol engine, which produced 175 kW (235 bhp) in its final European-only iteration. The BMW Z1 roadster was also based on the E30 platform.
Is a Ruger 10/22 an assault weapon?
Can I play chess online with a friend?


text:
Поверхностные волны:

 Поверхностные акустические волны

redpajama_set_name: RedPajamaWikipedia


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Home Food Riverside Food Lab
Riverside Food Lab
Food Lab..
Most of the school districts support and participate in the city's business operations, including television stations, public libraries, kitchens, medical clinics, school bus yard, school laundries, warehouses and police departments. There are also recreational areas available in a school district. Oftentimes, school districts become a contributing factor to the success or the recession of the city's economic and political status Riverside Food Lab.
The performance of a school district can be equated to the performance of the schools itself. Schools are not just for students. Schools are community centers. They cater to a number of different people and different businesses. Therefore, a good school should include a good learning environment. Discover why these unified district schools are making a reputable name.
Flagstaff Unified School District
The success of Flagstaff in Arizona is through the collaboration and commitment of parents, educators and its community. They have qualified teachers, wherein, most of them have a master's degree, are certified counselors, librarians and administrators. A number of their teachers are also recipients of citations and awards.
In 2002, the National Principal of the Year came from their district. Flagstaff Middle School received the Golden Bell award, the highest commendation for innovative instruction in Arizona. This district, founded in a log cabin, has now 6 elementary schools, 3 high schools, 4 middle schools and 1 alternative combination of high school and middle school. It also has a number of school buildings, libraries and recreational areas. Magnet schools were also opened to concentrate on academics, especially in Science, Arts and Citizenship and Character Education and Technology Riverside Food Lab.
Flagstaff has a rich mix culture, excellent tourist destinations along with a scientific but family-oriented community that knows how to established good schools and a good quality of life. The community supports the districts' entire program by opening opportunities for both faculty and students alike. Some companies that provide it include a Lowell Observatory, W.L. Gore & Associates, a number of museums and symphony orchestras.
For the schools comfortable and safe environment, the community provides bus fleets, food services, health services and basic social services. In return, the students consistently score above national average on achievement exams, in which, drop out rates are lower than the state average. They garner gold medals in state and national competitions. They are also well prepared for careers in technology, trade and business. Graduates have been accepted at prestige universities including Princeton, Stanford and Yale.
Lake Elsinore Unified School District
Lake Elsinore in California is fast growing when it comes to commerce, retails, residential and light industry. The city provides excellent public service programs that include fire and police protection, public and commercial transportation and job opportunities in industries like tourism, computer animation, telecommunication, machining, aero sports and construction products. This school division provides students opportunities for academic excellence, extra curricular and athletic programs along with scholarship and employment opportunities Riverside Food Lab.
This district consists of 15 elementary schools, 5 middle schools, 3 high schools, and 4 alternative education schools. For the last two years, this school district is making a name in academic achievement and was even placed in the top 10 in riverside County ranking. Schools in this area are also known for its community involvement doing charitable works.
This school district has implemented a magnet program called Visual and Performing Arts and is now proving to be a success specifically in Butterfield Elementary School. It is making a name for arts and theaters in its 14 yrs of successful performances. They have received a number of honors and awards including Golden Bell, Los Angeles Music Center "BRAVO" award, healthy Start Grant and as a Treatment School for Reading and Arts Integrated for Student Excellence Riverside Food Lab.
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The Masters: Joshua Beaty
A conversation between art and fashion, and the monstrosity of overinterpretation.
Words Celia Fernández
Images Courtesy of Joshua Beaty
Joshua Beaty is a synonym of art and creativity. He is not looking to challenge the definition of fashion, nor does he dictate his own. He is only interested in creating, and his designs welcome any interpretation from the audience. Like a performance that some people hate, and some people love. There is no right or wrong for Joshua because in his words: "the real monstrosity is the excess in interpretations. It's more about what people see in my work than what I'm trying to say."
Words have always had a special place in Joshua's live. Born and raised in Nottingham, the British designer learned French from an early age, at school and from his mother. A career in Languages was the path that Joshua would most likely end up in, and fashion design was never part of the plan. However, after he took the foundation course at CSM, his destiny changed drastically.
Although he was aware of the reputation that Central Saint Martins had, Joshua Beaty never felt intimidated to pursue his newfound dream. That is not Joshua; he doesn´t think too much about what other people say or suggest. With no high expectations of getting in, he decided to at least try, and applied for the BA Fashion with Knitwear. Now, seven years later he has graduated from the MA Fashion, where the best part for Joshua "are the tutors and the students and having the opportunity to establish that kind of dialogue."
A conversation between art and fashion can be read in Joshua Beaty's signature, and is the reason why he is here today. "I did fashion because I like art, not because I like buying clothes or something like that. What I like about fashion is that it gives a purpose, and you can use it, and you can wear it. Fashion is something that gives a life almost."
During his time on the BA, like any other young fashion student, Joshua was trying to find his voice. It wasn't that easy and, therefore, he struggled separating his multidisciplinary artistic projects from what it was meant to be purely fashion. It was during the MA that he understood when the two have to be separated, and when they can cross over. He admits: "Sometimes that outcome can cross over and has to be aligned somewhere, so you have to differentiate what functions respond to purely fashion. You have to be super creative with what you are doing to get these ideas because fashion also has a function; it is not just to look at a photo. You have to be able to sit down and think about the human needs and how to implement them into your work."
Joshua is more focused on looking for the best way to expand his art, but he does see the purpose of fashion and its potential as a language. "People have to be able to use it, and as a designer, it has to be more product-based, but personally, I try to discuss beauty through my work," he confesses.
In his graduation collection that he showcased last February at London Fashion Week, the theatricality was served. A surrealistic touch came with accessories and decorations suggesting intestinal tubes and orifices, creating a visual metaphor of consumption, which, as he said recently to 1Granary, "was kind of what's going on politically at the moment and uncertainty for young designers."
With the normal stress that comes from presenting a collection during fashion week, Joshua felt equally relieved as deflated after the show: "It's a bit anti-climax because you've been waiting for something to happen for such a long time. It's always quite depressing the day after because you've spent all your time in something that suddenly is done."
However, unlike other young designers, the pressure of potential critics doesn't affect Joshua much. He believes that everyone will always say something different, or at least something. For Joshua Beaty, that is part of the game and, even more so, the primary purpose of what he does. "I think it's hilarious that everyone, especially in fashion, likes to say 'this is this, and this is that.' I think everyone would say something different, which was also the point of this collection. I wanted people to think it's about something else."
The day after the show Joshua went straight to the library to start researching his next project. Just like his ideas, his creative process never stops. It always starts with drawings, sometimes unrelated to clothes or fashion. Drawing helps him to be constantly looking and allows him to see properly, with perspective. Textile manipulation and experimenting with different techniques are also part of this continuous creative process. Joshua never hits 'pause' because his work lives in him and his art is the language that he is most fluent in.
When thinking of his future, Joshua Beaty admits that he would like to work on his own projects that mix fashion with other aspects that he is interested in, like art and film. He also considers moving back to Paris where he has done a few performance and art projects before.
Regardless of what's next for Joshua, fashion, art, and performance will inevitably feed off each other in his work. They are all in his DNA. Sometimes we will love the outcome and sometimes we will hate it. In any of those cases, Joshua would have succeeded. He never meant to please the audience anyway. "Even if people hated it, I rather them hated it than forgot it. As long as it provoked some reaction that is what is important to me."
Shanti Bell: Representing the Weight of Masculinity
The graduate's BA collection, featuring woodwork sculptures and tailored menswear, was inspired by conversations with her brother
Karolina Widecka and design by conspiracy theory
Her MA collection, 'Where's the Curve?', focuses on conspiracy theories and the paranoia they provoke
Julia Ballardt: The poetry of punk
The German designer Julia Ballardt is inspired in her collection by the subculture's signature emblems of belonging.
Shanghai-based designer Zheng Lu believes the future is mechanical
A collection about rebelling against industry norms, Zheng Lu's search for a well-oiled fashion system led him to create workwear with his own spin on anti–fashion
Masha Popova flies solo
The recent fashion design graduate found success online and rejected the post-grad job route
Shuxuan Li's womenswear speaks its own language
Based in New York, Chinese knitwear designer Shuxuan Li creates fitted yet loose womenswear that explores contrasts and tensions between artistic heritage and superficial modernity.


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Fishing: News
Pioneering Angler Gary Klein Continues to Take Aim at Bass Fishing Perfection
Lynn Burkhead, WorldFishingNetwork.com
Texas bass angler Gary Klein has been chasing tournament fishing perfection since the 1970s; as co-founder of a new professional bass angler circuit, this pioneering fisherman continues to take aim at the top rung of the sport
Spend some time with bass fishing pro Gary Klein on his sprawling ranch in North Texas and it doesn't take long to understand he is a man of great passion who rarely, if ever, does anything in life in a half-hearted fashion.
That much seems apparent as you watch – and listen – to Klein go about one of his favorite off-the-water pursuits, long-range rifle shooting at extreme distances of 1,000-yards or more.
From the custom-built precision rifles Klein and his shooting buddies bring to the range to the intricate hand loads constructed at the reloading bench to the detailed notes concerning each shot made downrange, being half-hearted just isn't in the 50-something-year-old angler's DNA.
This might help explain Klein's continued pursuit of bass fishing perfection, something that began in earnest in 1979 when the then California resident pushed youthful fears aside and followed his dream of becoming a professional tournament angler on the budding B.A.S.S. tournament trail founded by the legendary Ray Scott.
Due to his drive and work ethic, when Klein qualified for the 1979 Bassmaster Classic in his very first season – something he has gone on to do an amazing 30 times – it wasn't surprising. Nor is the fact he used his budding prowess with a lengthy flipping stick to earn a fourth-place finish in the Classic when it visited Lake Texoma not far from Denison, Texas.
In the nearly 40 years following Klein's professional debut, the desire to compete and win still burns brightly for the longtime Bassmaster Elite Series pro and the co-founder of Major League Fishing.
"Nothing is the same today as it was in 1979 since the sport has continued to evolve over time," said Klein, a longtime resident of Weatherford, Texas. "Back then, we fished with reels that had pearl white handles and 6-foot-long rods that had metal reel seats.
"But the one thing that continues to be the same is the passion that I have for fishing, the passion that others who fished in that Texoma Classic still have. If you look at some of the anglers who were there, from Roland Martin to Rick Clunn to Bill Dance, they still love fishing and continue to be active in the sport to this very day."
That list continues to include Klein, who along with his fellow competitor and good friend, Boyd Duckett, founded the wildly successful Major League Fishing circuit and TV show five years ago.
"For me, it hasn't changed all of these years later," said Klein. "I still have a great passion for fishing and that has never changed. In fact, the more I get to fish, the more that I enjoy fishing."
Since that 1979 Classic, Klein has gone on to carve out one of the most legendary careers the sport has ever seen, capturing two B.A.S.S. Angler-of-the-Year titles (1989 and 1993), winning eight B.A.S.S. events, finishing second in nine others and garnering 79 top-10 finishes along the way.
Klein also has done well on the FLW Tour, winning two events and qualifying for six Forrest Wood Cup FLW Championship tournaments.
Add in a near miss at the Major League Fishing 2014 Challenge Cup on Texas' Ray Roberts Lake – Klein lost an 8-pound-class bass at the boat with minutes to go that would have catapulted him ahead of eventual winner Kelly Jordon – and there isn't much the Gary Klein career resume doesn't list.
Add all of his accolades up and that's 10 professional tournament wins, two Angler-of-the-Year titles, qualifying for 36 major championship-level events and pocketing nearly $3 million in career earnings along the way.
Not bad for an angler who says he used to have trouble sleeping at night during his high school years because he couldn't stop thinking about competitive bass fishing.
"I just can't explain to people the passion that I have had all of these years for competitive angling," said Klein. "The fire that I have inside, it burns hotter now than it did in 1979 on many different levels.
"I have accomplished a lot in my career, but there's a lot that I haven't accomplished too and that still drives me. I still want to go out there, compete against the best, catch more fish than they do and have a good time."
Bassmaster Elite Series and MLF pro angler Gary Klein has played a key pioneering role in helping take some bass fishing techniques mainstream. One of his favorite techniques is pitching. (Jeff Phillips photo)
While Klein shows no interest in slowing down and retiring to his wildlife-rich ranch in the Rolling Plains of Texas, he has reached the place in his life where he is concerned about giving back to a sport he says has given so much to himself, his wife, Jana, and his two daughters, Lakota and Kanyon.
"I want to help take competitive fishing to an even higher level," said Klein. "In my 30-plus-something years as a tournament pro, the sport is still not where I hope to see it eventually get. What we're doing with Major League Fishing, I think that's heading down the right road, but I'm still not satisfied with where we are after five years. We've got a lot more left to do."
Specifically, Klein hopes to take tournament angling to a more mainstream audience in the years to come, the same crowd that will sit down and watch a professional football, baseball, basketball or hockey game, even if they have never personally played the sport.
"I want to have competitive angling truly recognized as a sport," said Klein. "And I want to see more people – kids, youth and adults – continue to get involved in this sport. This sport has made me what I am and I want to see the sport keep growing."
To that end, Klein has become increasingly involved in causes like the growing high school fishing movement and in passing along his knowledge and passion for fishing to young people who might one day follow in his footsteps.
In recent years, doing that has taken place through Klein's involvement with the Texas Bass Brigade program, an annual camp that has a stated mission of empowering and educating young people with leadership skills and knowledge in wildlife and fisheries management coupled with sound land stewardship practices.
"I hope like crazy that we continue to pass all of this on and that's why I want to continue to be involved with young kids and to help introduce them to the outdoors," said Klein. "I want them to want to be involved in fishing like I have been because what better way to grow up is there? There are so many distractions for our young people today with negative world events (happening) and challenges (their parents face).
"It's sad to me that so many kids never get a chance to get involved in the outdoors. Especially since one of the truest things I know about fishing is that some of the fondest memories that kids can have is fishing with their mom or dad. Those are memories that you'll carry with you to the grave versus something that you bought, watched or listened to and quickly forgot."
At the end of the day, as Klein continues along the passionate path of tournament bass fishing he has traveled since his youth, the Texas angling pro has a firm grasp on how he wants to be remembered as a fishing pioneer.
"That Gary Klein was an individual who wasn't afraid to follow his dream," smiles Klein. "It all started for me at age 15, way back in 1972, the very first time I ever heard of tournament fishing. I knew right then that this was for me.
"That same desire still exists today," he added. "To me, failure in life is never having tried. Whatever the rest of my career holds, at least I tried to live my dreams out. It's been a fun ride and I've thoroughly enjoyed it, but I'm not done yet. I still have some dreams left inside that I want to make sure turn into reality."
Fueled by the continuing passion to drive Gary Klein nearly four decades after he began his career, don't bet against him.
Get Your Fish On.
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State Records Reported in Maryland, Michigan
G&F Online Staff - May 23, 2019
It must be time for summer fishing because records are falling everywhere.
Your Guide for the Best Catfish Baits
G&F Staff
If you've been catching catfish with the same method for years, it's time to change it up and...
Game & Fish Magazine Names New Editorial Director
Adam Heggenstaller takes over after 14 years with NRA Publications.
Mustad's Inkvader Octopus Live Jig
From big fish to small, just about any saltwater game fish out there will love the new Mustad Inkvader Octopus Live Jig that Mustad's Russ Whisler shows to OSG's Lynn Burkhead.
As KVD tells OSG's Lynn Burkhead, innovative Humminbird products and cutting-edge technology like that found in the new Mega 360 Imaging sonar are major reasons contributing to his unparalleled success.
MLF Pros: What's Your Go-To Lure?
When all else fails, here's what these pros tie on.
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We reviewed these new boats that stand out for value, reliability and made-for-fishing action.
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The 2019 Bassmaster Elite Series schedule will feature three new fishing destinations.
© 2019 Outdoor Sportsman Group. All Rights Reserved.
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Knot Theory and Its Applications
Kunio Murasugi
Part of the Modern Birkhäuser Classics book series (MBC)
Fundamental Concepts of Knot Theory
Knot Tables
Fundamental Problems of Knot Theory
Classical Knot Invariants
Seifert Matrices
Invariants from the Seifert Matrix
Torus Knots
Creating Manifolds from Knots
Tangles and 2-Bridge Knots
The Theory of Braids
The Jones Revolution
Knots via Statistical Mechanics
Knot Theory in Molecular Biology
Graph Theory Applied to Chemistry
Vassiliev Invariants
Knot theory is a concept in algebraic topology that has found applications to a variety of mathematical problems as well as to problems in computer science, biological and medical research, and mathematical physics. This book is directed to a broad audience of researchers, beginning graduate students, and senior undergraduate students in these fields.
The book contains most of the fundamental classical facts about the theory, such as knot diagrams, braid representations, Seifert surfaces, tangles, and Alexander polynomials; also included are key newer developments and special topics such as chord diagrams and covering spaces. The work introduces the fascinating study of knots and provides insight into applications to such studies as DNA research and graph theory. In addition, each chapter includes a supplement that consists of interesting historical as well as mathematical comments.
The author clearly outlines what is known and what is not known about knots. He has been careful to avoid advanced mathematical terminology or intricate techniques in algebraic topology or group theory. There are numerous diagrams and exercises relating the material. The study of Jones polynomials and the Vassiliev invariants are closely examined.
"The book ...develops knot theory from an intuitive geometric-combinatorial point of view, avoiding completely more advanced concepts and techniques from algebraic topology...Thus the emphasis is on a lucid and intuitive exposition accessible to a broader audience... The book, written in a stimulating and original style, will serve as a first approach to this interesting field for readers with various backgrounds in mathematics, physics, etc. It is the first text developing recent topics as the Jones polynomial and Vassiliev invariants on a level accessible also for non-specialists in the field." -Zentralblatt Math
Algebraic topology Knot invariant Knot theory computer computer science group theory mathematical physics
1.Department of MathematicsUniversity of TorontoTorontoCanada
DOI https://doi.org/10.1007/978-0-8176-4719-3
Copyright Information Springer Science+Business Media New York 1996
Publisher Name Birkhäuser, Boston, MA


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These memories tell a unique story of M&S through the eyes of our customers and employees
My mum looks great in the 50s inspired 125 dress - now I know what she looked like when she was young!
My earliest memory of Marks & Sparks is going shopping with my mum and younger sister to buy new pants, socks and an outfit for Whitsuntide. On Whit Sunday we would dress in our new clothes and parade amongst family.
Lynne Barrett
We treasure the stories we receive and we'd love to hear your M&S memories.
Browse memories by...
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M&S Food
M&S Home
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I worked in M&S in 1964 when Aberdeen had 500 residents quarantined in hospital with the typhoid outbreak. I married & moved to M&S office in Edinburgh under Mrs Whitehill. Now 50 years later I am working as a Christmas temp in Dundee store in the Lingerie Dept exactly where I started 50 years ago.
Edith Christie 'nee Reid
I remember when I started work at M&S Durham Store in 1964 everyone had to address you by your full name... Mrs Smith or Miss Jones.. no first names were allowed to be used at all. It seems so silly now when I think about it, but it was like this for a great many years.
I worked in Manchester aged 16 and was paid £5.10s. I remember Young Junior Teens, tights, towels, men's coloured shirts and chilled food. It was so busy we couldn't re-stock quick enough; managers used to say "if it's too tidy it's not busy"! In the miners' strike we used torches, and decimalization was a challenge.
Hazel Broughton
I wore blue nylon overalls when I first stared at M&S in 1964 - I was the first 15 year old to be taken on, as you had to be 18 before then. I retired last year, June 2012
When I used to go shopping with my Mum we would go to various shops and although I never thought of my Mum as a snob, she always told me to keep the Marks and Spencer bag on the outside (so everyone could see). Mum was a great advocate for the store I wish I could go shopping with her once more :-)
I was brought up in a children's home in Aberdeen and M&S would donate Christmas presents to us. They also helped me get my paints, brushes and easel so I could go to Grays School of Art for a year. That was 1967. I now work in M&S and have been for 27years. I feel like they are part of my family.
I was employed at Marks & Spencer in 1969 in the Menswear Department in Manchester. I had great fun when I entered Miss Marks & Spencer, the store's hairdresser won and I would love to see that photo again. I now live in Australia and would love to show it to my family. I wore an M&S swim suit.
Mrs Anne Lunn maiden name Entwistle
Going to the stall in the Grainger Market in Newcastle, the first of M&S if I remember right, it was called a penny stall.
susan henderson
My first visit to Marks & Spencer was the best!
Pink coconut cake - was hoping it would be brought back for Jubilee year as well as chocolate crinkle crunch biscuits!!!
Helen Holt


The postings for seasonal park ranger and student ranger positions are now closed.
For employment opportunities in our vehicle accessible campgrounds and day-use areas, please contact the Park Operator directly. Contact information is listed on individual park webpages (Find a Park).
If you are interested in being a park operator/contractor that provides campground and day-use area recreation services, all contracts are awarded through an extensive request for proposal process. If any other contract opportunities become available, they will be posted on our main page.


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OHSU
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Oregon Institute of Occupational Health Sciences Featured Resources provide the latest information on workplace safety, health and well-being. Additional information can be filtered by topic in the supporting navigation to the left of the article content.
NIOSH Safety and Health Topic: Body Art
http://www.cdc.gov/niosh/topics/body_art/
The body art industry is unique because its artists express themselves through living art, but in doing so, artists may also come in contact with their client's blood. Because of this, tattoo artists and body piercers may also be exposed to a bloodborne pathogen such as hepatitis B virus, hepatitis C virus, or human immunodeficiency virus (HIV).
Source: NIOSH
OSHA Woodworking eTool Health hazards
https://www.osha.gov/SLTC/etools/woodworking/health_wooddust.html
Exposure to wood dust has long been associated with a variety of adverse health effects, including dermatitis, allergic respiratory effects, mucosal and nonallergic respiratory effects, and cancer.
Source: OSHA
Environmental Health News: Inkling of concern - Chemicals in tattoo inks face scrutiny
http://www.environmentalhealthnews.org/ehs/news/2011/tattoo-inks-face-scrutiny
New research has turned up troubling details about chemicals in tattoo inks, including some endocrine disruptors and toxic metals, and a compound that has been called one of the most potent skin carcinogens. The FDA has launched an investigation into concerns about ink safety.
Source: Environmental Health News
NIOSH Science Blog: Safety and Health for Tattooists and Piercers
http://blogs.cdc.gov/niosh-science-blog/2009/10/27/tattoo/
Tattooists and piercers work in an industry that is unique in opportunities and challenges. The National Institute for Occupational Safety and Health (NIOSH) began visiting tattooing and piercing studios in the 1990s in response to workplace safety and health concerns raised by artists in the industry. Based on these visits and interviews with artists, we found many had concerns about exposures to blood and bloodborne diseases.
Health Hazard Evaluation: Exposures at a Pottery Shop (PDF)
http://www.cdc.gov/niosh/hhe/reports/pdfs/2007-0127-3068.pdf
The HHE Program responded to a request at a pottery shop which concerned potential exposures to silica, volatile organic compounds, and dry materials mixed there. HHE Program investigators collected personal breathing zone and area air samples, surface wipe samples, measured carbon monoxide (CO) during forklift use, and performed an ergonomic assessment of work practices.
Photographic Materials: Safety Issues and Disposal Procedures
http://www.ehs.ufl.edu/HMM/photo.htm
This University of Florida Division of Environmental Health and Safety Manual is not intended to replace the Material Safety Data Sheets (MSDS) as the source of information on photographic chemicals. It is critical that the MSDS for each chemical be consulted to determine the specific hazard associated with that chemical.
Source: University of Florida Environmental Health and Safety
Traditional Sculpture Hazards
http://www.trueart.info/?s=Sculpture
Source: True Art
Woodworking Hazards
http://www.trueart.info/?s=Woodworking
Wood sculpture and furniture-making use a large number of different types of hard and soft woods, including many exotic tropical woods. Many of these woods are hazardous themselves. Sometimes woods are treated with hazardous preservatives or pesticides.
Source: True Art Information
Safer Alternatives
http://www.silversmithing.com/1altern.htm
Source: Society of American Silversmiths
Safety for Glass Studios
http://www.dodgestudio.com/safety.htm
Source: Dodge Studio Designs
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Today, data breaches and cyber-theft are at an all-time high, with new and evolving technologies being used to instigate as well as prevent attacks. As a result, organizations are being compelled to take both defensive and offensive measures to protect the privacy and integrity of their information assets. The trend from both a regulatory as well as an operational point of view is toward more stringent, more comprehensive and more transparent, unified information governance policies and procedures.
How can you take charge? One way is to automate your information governance workflow, practices and procedures. The act of streamlining information governance helps organizations form more comprehensive strategies. Before any automation can be applied, every organization must conduct a comprehensive assessment of information assets across the enterprise and grapple with retention and disposition policies and practice. Best practices focus on applying frameworks and rules that encompass records classification, a set of retention rules, and a procedure to lock down records so that they cannot be deleted unless in accordance with retention rules. Also important is implementing a process to help ensure that systems can export records and all of their metadata in a format that can be imported to successor applications.
Another best practice for advancing your current information management program to an enterprise-wide, integrated and mature set of procedures is by conducting what Canon terms a business process assessment. This is an objective in-depth analysis of the current state of an organization's records management program including strengths and weaknesses and what must be done to build upon positives and address the negatives. The ingestion and egress of information is mapped; repositories are identified (including "rogue" repositories that are created by employees without notifying the IT department); current taxonomies are identified including how they were implemented; concerns expressed by employees about how they access information are gathered; bad recordkeeping habits are documented; and how the current overall program may negatively impact the organization's ability to meet regulatory requirements is clarified.
While leveraging the business process assessment for guiding future direction, the next step is to craft the information governance framework that will support program planning, monitoring and enforcing compliance. This, in turn, drives the company's ability to define, approve and communicate the information management program (policy, retention schedule and procedures) while implementing it with new standards, architecture and analytics reporting functions. Figure 1 below highlights many of the key elements of an information governance framework.
This is a time-intensive and expensive undertaking, consisting of five phases: the business process assessment, the resulting report that will be referenced for all initiatives, planning for change, implementation and analytics. Within the table, each phase is summarized at a high level to provide an orientation on how to get started.
What are some additional steps you should take to automate and improve your information governance and compliance efforts? Consider these four essential practices.
Digitize core compliance and governance processes. This includes identifying processes that will be best suited to automation. Look to reduce or eliminate paper-based and manual activities that slow the process and expose the organization to additional risk. Then apply business rules and technology to automate the identification and classification of information, access controls, and keyword and full-text search.
Utilize data capture functionality. When it comes to information governance, it is important that organizations look further than simply a scan-and-store approach. For many, "digitization" tends to imply scanning a piece of paper and filing away an image file instead. However, you could be entirely paperless but still miss the broader opportunity to leverage information in a way that is increasingly more beneficial to the performance of your organization. Work to utilize inbound data capture for more than just indexing data for the image. This is at the heart of business intelligence and more expansive information governance.
Consider data remediation. Data remediation is a critical element of any sound information governance program. Employees are using shared and personal hard drives, cloud services and other devices for data storage. This makes it extremely difficult to manage the massive amount of information being created and stored. Under these conditions, there is no elimination of what is commonly referred to as ROT (redundant, obsolete and trivial data). There is also no consistency in storage syntax and naming conventions, and no data cleansing. Service providers such as Canon can provide the analytics to identify what you have, classify that information and cleanse it to eliminate the ROT.
Information governance and compliance are pressing concerns for C-suite leaders in all industries. With evolving compliance demands, quickly changing technologies and ever-more-pressing threats in cybersecurity, it's easy to lose sleep at night. One way to rest better is to automate information governance and compliance. The technologies and approaches work to solidify your information governance strategy, while ensuring that policies and procedures are performed and adhered to automatically, every day.


Agape concentrates our efforts locally in Dallas/Fort Worth and North Texas as well as throughout the United States. By focusing on the local markets we are able to bring the highest level of service to all our clients. Our goal is to not simply sell our doctors an insurance policy, but to address and provide solutions to the various risks facing a practice. We do this through visual inspection, practice policy and procedures review and contract review and an assessment of current insurance contracts.
We strive to have local contacts that will help our clients solve their practice problems and we do this by being active in the local medical community. Agapé Healthcare Partners is a preferred medical malpractice vendor for Jefferson Physician Group, Genesis Physician Group, Patient Physicians Network and IPA of Denton County. In addition to this, we hold leadership rolls in the Alliance for Healthcare Excellence, Doctors Referral Network, DFW Medical Connections and Healthcare Executive Networking Group.
Jim has helped physicians negotiate and place their Medical Malpractice insurance in the Dallas, Fort Worth and North Texas area for over 13 years.
As the founder of Agapé Healthcare Partners, L.P., Jim built the practice from a start up in 2004, to being the driving force in the North Texas Medical Malpractice market today. He has developed several medical malpractice programs which have helped to make this market one of the most competitive in the country.
Specialties: Negotiation and placement of Medical Malpractice Insurance for individual and group medical practices, Facility Medical Professional Liability for Hospitals, Surgery Centers, Urgent Care Clinic, Medi-Clinics, Nursing Homes & Long Term Care Facilities, Skilled Nursing Facilities, Medical Spa's and Aesthetic Facilities.
Reneé joined Agape in June 2007. She attended University of Texas at Austin and majored in Business. Reneé handles all the accounting issues for the firm. She would be happy to answer any question regarding billing.
Laurie started her career at Sullivan Kelly Insurance Agency over 15 years ago. She is licensed in Texas and has also worked on the carrier side as well. Laurie is takes a personally interest in her clients and does everything she can to provide them with the information the need. Contact Laurie with any questions or concerns.


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Man charged with flying drone near police copter
A 20-year-old man was arrested for allegedly flying a drone within feet of a Philadelphia police helicopter Wednesday evening in Center City.
Joseph Roselli is facing charges of aggravated assault, causing catastrophe, simple assault and recklessly endangering another person, police said Thursday.
The drone was first seen around 6 p.m. over the area of 18th and Walnut Streets where an anti-Trump protest was engaged in a faceoff with police, said Chief Inspector Scott Small. The drone "came within feet" of the helicopter, which was monitoring the protest below.
That close contact between the drone and helicopter led to the assault charges, said Officer Christine O'Brien, a police spokeswoman. The drone nearly hit the helicopter's windshield, she said.
Police tracked the drone to a building at 19th and Chestnut Streets and arrested the operator, Small said. - Robert Moran