text:
\section{Introduction}

Automatic speech recognition (ASR) has largely improved using recurrent
neural network (RNN) acoustic models due to the networks ability to
learn long-term information. Unfortunately, RNNs becomes difficult
to train when extended to deeper structure. This is  because the deeper
models is essential to learn more abstract information for improving
the prediction of unseen data \cite{sak2014long}. Several attempts
have been made to train deep RNN such as using non-recurrent structures
to increase the number of layers and model complexity \cite{pascanu2013construct},
including transform gates for smoother gradient flow \cite{zhang2016highway}.
But training deep recurrent structures is complex as the gradient
has to travel multiple hidden states and lack of better optimization
algorithms \cite{pascanu2013construct}. Meanwhile, deep neural networks
(DNN) can run much deeper, lead to better generalization to unseen
data and are less prone to overfitting. Also, feed-forward training
is relatively simple and faster when compared to recurrent structures.
Besides these advantages, DNN fail to perform better for tasks which
require long-term information. Thus to overcome this constraint, the
authors in \cite{zhang2015feedforward} represented the temporal context
as a fixed size representation and train them jointly. In another
work by \cite{raffel2015feed,vesel2016sequence}, the unweighted average
of input context is used in modeling temporal information. The limitation
with these approaches are that they fail to model the temporal order
which is important for speech tasks as shown in \cite{hochreiter1997long}.
Analogous to these networks is time delay neural network (TDNN), where
each layer is fed with multi spliced input \cite{peddinti2015time}.
Even though TDNN has the ability to model long-term contexts, RNN
still shows better performance over TDNN \cite{peddinti2015time}.
A possible reason for this is the fact that the performance gain of
RNN is devoted to their stepwise learning of time frames and not by
the size of context as found in \cite{mohamed2015deep}.

A straight forward approach to allow DNN to learn a single time step
at each layer is by denoting the time context length based on the
number of layers. A practical challenge in this approach is that DNN
having more than few layers starts to degrade due to gradient vanishing
problem. Recent works by \cite{he2015deep} showed that deeper convolutional
networks can be trained in a much simpler way using residual connections.
This approach showed significant gains in image recognition tasks.
Additionally, \cite{ghahremani2016linearly} suggested to use shortcut
connections and singular value decomposition for deeper fully connected
networks and got better performance in ASR tasks. This paper makes
an attempt to use residual structure with time delayed connections
to harness the power of both temporal and hierarchical structures
at each layer as explained in section \ref{sec:Residual-memory-networks}.
Figure \ref{fig:residual}, illustrates an basic form of residual
network structure where the input $x$ is summed to next layers output
using a shortcut connection with identity mapping $I$.\vspace{-0.4cm}
\begin{figure}[H]
\begin{centering}
\includegraphics[scale=0.4]{Figures/residual2ct}
\par\end{centering}

\caption{\label{fig:residual}Structure of residual component }
\end{figure}
\vspace{-0.4cm}
In this work, we propose Residual memory network (RMN), a variant
of DNN where the number of layers denotes both the length of temporal
information learnt and the structural depth. The key contributions
of RMN are:
\begin{itemize}
\item The use of residual connections after every few layers to increase
the network depth makes training faster with increase in performance.
During backpropagation, the residual lines allows unimpeded flow of
gradients.
\item A memory component is present in each layer in a serial manner where
the first layer sees $t-T$ time instant and the last layer sees $t-1$
frame. The component weights are shared across all layers to enable
them to learn longer-context.
\end{itemize}
A combination of these two components allows RMN to learn long-term
dependencies and higher level abstracts simultaneously in a much simpler
and efficient way. Bi-directional RMN (BRMN) is also formulated in
this work, which is a simple extension to RMN by adding an extra connection
with shared weights for learning future information. Computational
complexity is relatively less for BRMN over BLSTM or bi-directional
RNNs which is detailed in section \ref{sub:Bi-directional-residual-memory}.

In section \ref{sec:Experimental-setup}, we explain about AMI corpus
and the baseline model configurations used in our experiments. A detailed
explanation to build proposed RMN and BRMN model is in section \ref{sub:RMN-configuration-and}
and \ref{sub:BRMN-configuration-and}. Empirical evaluation is conducted
in section \ref{sec:Validation-experiments} to validate the structure
of RMN for speech recognition tasks. Comparison of the RMN with the
best LVCSR systems in literature in listed in section \ref{sub:Summary-of-results},
which is followed by conclusion and future work.

\section{Residual memory networks\label{sec:Residual-memory-networks}}

RMN is composed of memory layers and residual connections as shown
in figure \ref{fig:Architecture-of-residual}. The residual connection
connects the previous output to the current input by skipping few
layers. Each memory layer contains two weight transforms: The first
affine transform $W_{l}$ learns current time step and is different
for each layer $l=1,2,..L$ as in standard DNNs. The second weight
transform $W_{s}$ is shared across all layers and learns past information
by varying delay in decreasing order. For example in figure \ref{fig:Architecture-of-residual},
$W_{s}$ receives $t-T^{th}$ frame in first layer, second layer receives
$t-(T-1)^{th}$ frame and the delay keep decreasing as we proceed
to higher layers. In RMN $T$ is fixed based on the number of layers.
For instance 18 layered network captures 18 time steps. In this network,
relu activation is used after each memory layer as it is efficient
for training deeper networks \cite{ghahremani2016linearly,he2015deep}.
Thus, RMN can be represented as a variant of deep feed-forward neural
network which harnesses the important characteristics of unfolded-RNN
and residual networks.

\subsubsection{Forward propagation}

Figure \ref{fig:Architecture-of-residual} shows the series of computations
done in RMN architecture, where input $x(t),\,\{t=1,2,..T\}$ at time
instant $t$ is processed using $W_{l}$ matrix in the layer $l$
to get $h_{l}(t)$. The shared weight $W_{s}$ receives $h_{l}(t-m)$
by delaying $h_{l}(t)$ by $m$ time steps. The feed-forward output
after each memory layer is\vspace{-0.3cm}

\begin{equation}
y_{l}(t)=\phi\,(x(t)W_{l}+h_{l}(t-m)W_{s}),\,l=1,2,..L
\end{equation}

where $h_{l}(t)=x(t)W_{l}$ and $\phi$ is the relu activation output.

\subsubsection{Backward propagation}

Backpropagation for computing the parameter $W_{l}$ is done in the
same way as in standard DNNs. The shared parameter $W_{s}$ is computed
by taking into account error gradients from all $T$ time instants
which is exactly equal to $L$ memory layers. The error derivative
w.r.t to $W_{s}$ is\vspace{-0.3cm}

\begin{equation}
\frac{\partial E(t)}{\partial W_{s}}=\sideset{}{_{k=1}^{T}}\sum\left[\frac{\partial E(t)}{\partial\hat{z}(t)}\frac{\partial\hat{z}(t)}{\partial h_{l}(t)}\right]\frac{\partial h_{l}(t)}{\partial h_{k}(k)}\frac{\partial h_{k}(k)}{\partial W_{s}}
\end{equation}

where $\hat{z}(t)$ is the softmax output,$z(t)$ is target label
and $E_{t}(.)$ denotes cross-entropy loss function.

\subsection{Bi-directional residual memory network\label{sub:Bi-directional-residual-memory}}

In this section, the structure of bi-directional RMN (BRMN) is discussed.
The BRMN is an extension of RMN with one additional shared weight
transform which receives future frames as input. The forward propagation
output is given as\vspace{-0.3cm}

\begin{equation}
y_{l}(t)=\phi\,(x(t).W_{l}+h_{l}(t-m).W_{s}+h_{l}(t+m).W_{b})
\end{equation}
\vspace{-0.4cm}

where $t-m$ is the time instant delayed by m steps and $W_{b}$ is
the shared weight across layers. Unlike bi-directional RNN described
in \cite{schuster1997bidirectional}, BRMN does not require two separate
recurrent units for training future and past frames. The past and
future frames are not treated as independent entities and merged after
each layer. A possible explanation for bi-directional RNN to have
two separate layers is because RNN is tend to look over all frames
during prediction which leads to performance drop\cite{schuster1997bidirectional}.
In case of BRMN the network is constrained to pre-defined context
size based on the the number of memory layers and thus connecting
the forward states and backward states after each memory layer shows
improvement in performance. Also, BRMN requires only one extra weight
transform over RMN and hence the number of parameters is significantly
less when compared to bi-directional RNN and BLSTM \cite{graves2014towards,schuster1997bidirectional}.
\begin{figure}[H]
\begin{centering}
\includegraphics[width=8.5cm,height=3.5cm]{Figures/rmn_arc_3s_18lmem_comp_dark2ct}
\par\end{centering}

\caption{\label{fig:Architecture-of-residual}Architecture of residual memory
network (RMN) with number of memory layers $L=18.$ The memory layers
can model temporal context size of 18. }
\end{figure}
\vspace{-0.5cm}

\section{Experimental setup\label{sec:Experimental-setup}}

The experiments were conducted on the AMI meeting conversation corpus
\footnote{http:corpus.amiproject.org/}, using the independent headset
microphone (IHM) recordings. The database is composed of 77 hours
- train data and 9 hours of each dev and eval data. 16KHz sampled
waveform was used to extract 13-dimensional MFCC features. These features
were mean normalized, spliced over 7 frames and projected down to
40 dimensions using linear discriminant analysis (LDA) obtained from
LDA+MLLT model. The LDA features were fed to speaker adaptive training
(SAT) using speaker based feature-space maximum likelihood linear
regression (fMLLR) transforms to obtain fMLLR features. 80 dimensional
log Mel-filterbank (fbank) features were also used for comparison.
The standard GMM-HMM and DNN is trained by following the Kaldi toolkit
\cite{povey2011kaldi}. The LSTM and RMN is trained using the CNTK
toolkit \cite{yu2014introduction}. SAT alignments using 4006 tied-states
were used as targets for neural network training. Testing was done
using eval set with trigram language model.

\subsection{Baseline DNN and LSTM models}

The DNN configuration includes 440 (40 x 11 splice) dimensional fMLLR
features at input and 4006 senones at softmax output. DNN containing
6 hidden layers, 2048 neurons were initialized using RBM pretraining
and fine-tuned with minibatch SGD frame-classification training. The
LSTM training is performed by following the CNTK recipe \cite{tan2016speaker}.
The LSTM is composed of 3 projected LSTM layers, each having 1024
memory cells and 512 projection units. The LSTM is trained using truncated
backpropagation through time (BPTT) with a minibatch size of 20. Forward
propagation is done with 40 parallel utterances for faster training
and better generalization \cite{yu2014introduction}. Highway LSTM
is also built by following the procedure in \cite{zhang2016highway}
to analyze the effect of increase in LSTM depth. 3 layered Highway
LSTM works better as increasing it to 8 degrades the performance as
in table \ref{tab:Baseline-recognition-performance}. Further experiments
in this paper is done with 3 layered Highway LSTM and will be denoted
as LSTM for simplicity. The BLSTM architecture is also used which
include 3 bi-directional layers each with 512 memory cells and 300
projection units. BLSTM is trained using latency control technique
with 22 past frames and 21 future frames as mentioned in \cite{zhang2016highway}.
The LSTM based models receives 40 dimensional fMLLR directly as splicing
does not help for training LSTMs \cite{miao2015speaker}. The speech
recognition results of all these models are stated in table \ref{tab:Baseline-recognition-performance}.

\subsection{Ivector extractor\label{sub:Ivector-extractor}}

BUT standardization initiative tool \footnote{http://voicebiometry.org/}
is used an ivector extractor. This extractor is trained on 9000 hours
of Fisher English (part 1 and 2), NIST SRE 2004-2008, Switchboard
(phase 2, phase 3, cellular part 1, and cellular part 2). An 100 dimensional
mean- and length-normalized ivector is extracted for each speaker,
after applying multi-lingual neural network based VAD tuned to detect
confident speech. Ivectors are appended to input features for training
LSTM based systems as suggested in \cite{tan2016speaker}.

\subsection{RMN configuration and training\label{sub:RMN-configuration-and}}

The memory layers in the RMN architecture contains 512 hidden units
followed by the relu activation function. The memory layer is preceded
and followed by a higher dimensional layer of 1024 units as it was
found to be crucial for better learning. Thus the network configuration
is represented as 440-1024- {[}512 x N layers{]}-1024-4006. The separate
weights of RMN $W_{l}$ as mentioned in section \ref{sec:Residual-memory-networks}
are Gaussian initialized with mean $0$ and standard deviation of
$0.2/\sqrt{layer\,dim}$. The shared weight matrix $W_{s}$ is initialized
as $0$ to ensure the model learns feature representation during the
first epoch followed by learning of temporal information. This is
done to disable the transfer of delayed inputs at the beginning of
training. Also, empirically we found that we can restrict the matrix
$W_{s}$ to be diagonal without loss in performance and it was used
throughout this work. In RMN, the residual connection shown is created
after every 3 layers as we found it to be optimum as in table \ref{tab:skips}.
Thus RMN requires smaller number of parameters compared to standard
DNN and LSTM as mentioned in table \ref{tab:param/wer-ami}. The
RMN is trained using truncated BPTT with a minibatch size of 256 as
suggested in \cite{saon2014unfolded} and a maximum of 10 utterances
in each minibatch. The initial learning rate is set to 0.2 and increased
to 1 in the next 4 epochs. Further training is done by automatically
reducing the learning rate for the next epoch by a factor of 0.5 if
cross-entropy loss degrades. L2 regularization weight is fixed to
0.00001 and momentum is set to 0.9. The scripts for running the RMN
and BRMN experiments are available in github repository \footnote{https://github.com/creatorscan/AMI\_CNTK\_scripts}

\subsection{BRMN configuration and training\label{sub:BRMN-configuration-and}}

The bi-directional RMN (BRMN) is trained by following the same procedure
as RMN with the following modifications: First, the initial learning
rate is fixed as 0.000095 and then allowed to auto adjust \cite{yu2014introduction}
based on validation loss as in RMN. Second, latency control technique
is used to capture 21 future frames. Empirically, we found that BRMN
works better for non-spliced input i.e., 40 dimensional fMLLR features
were directly sent to input of BRMN. Table \ref{tab:splice} shows
the performance BRMN with and without splicing. Thus the network configuration
of BRMN is 40-1024-{[}512 x 18 layers{]}-1024-4006. \vspace{-0.5cm}
\begin{table}[H]
\begin{minipage}[t]{1\columnwidth}%
\caption{\label{tab:Baseline-recognition-performance}Baseline recognition
performance (\% WER) of DNN, DNN+residual, LSTM, highway LSTM and
BLSTM for eval set of AMI corpus using fMLLR features}

\begin{center}
\vspace{-0.5cm}
\begin{tabular}{|c|c|c|c|c|c|}
\hline
\multirow{2}{*}{DNN} & DNN+ & LSTM \cite{tan2016speaker} & \multicolumn{2}{c|}{Highway LSTM} & BLSTM\tabularnewline
\cline{4-6}
 & residual & 3 layers & 3 layers & 8 layers & 3 layers\tabularnewline
\hline
\hline
27.1 & 26.7 & 26.0 & 25.8 & 26.0 & 24.9\tabularnewline
\hline
\end{tabular}
\par\end{center}%
\end{minipage}\hfill{}%
\begin{minipage}[t]{1\columnwidth}%
\caption{\label{tab:skips}\% WER of RMN model with number of layers skipped
by the residual connection. This experiment is done by with 15 memory
layers of RMN}

\begin{center}
\vspace{-1cm}

\par\end{center}

\begin{center}
\begin{tabular}{|c|c|c|c|}
\hline
\multicolumn{4}{|c|}{\# layers skipped by residue}\tabularnewline
\hline
1 & 2 & 3 & 4\tabularnewline
\hline
\hline
26.6 & 26.0 & 25.9 & 25.9\tabularnewline
\hline
\end{tabular}
\par\end{center}%
\end{minipage}\hfill{}%
\begin{minipage}[t]{1\columnwidth}%
\caption{\label{tab:splice}\% WER of RMN and BRMN for spliced and non-spliced
input with different width using eval set of AMI corpus}

\begin{center}
\vspace{-1cm}

\par\end{center}

\begin{center}
\begin{tabular}{|c|c|c|c|}
\hline
\% WER & \multicolumn{3}{c|}{Splice width}\tabularnewline
\cline{2-4}
Model & 1 (no splice) & 15 (+/-7) & 21 (+/-10)\tabularnewline
\hline
\hline
RMN & 26.6 & 25.6 & 25.6\tabularnewline
\hline
BRMN & 24.3 & 24.8 & 25.4\tabularnewline
\hline
\end{tabular}
\par\end{center}%
\end{minipage}
\end{table}
\vspace{-0.7cm}

\section{Validation experiments\label{sec:Validation-experiments}}

This section provides a detailed analysis to understand the behavior
of RMN.

\subsection{Effect on layer size and feature type}

Initial experiment is done to find the optimum number of layers for
RMN using 40 dimensional fMLLR features. Figure \ref{fig:res_rmn_dnn_layer_size}
compares the performance of DNN + residual networks with and without
delay connections. The baseline performance of DNN+residual without
delay is shown in table \ref{tab:Baseline-recognition-performance}
Two notable observations can be made from this figure. 1) The importance
of delay connections is clearly visible from this figure as it shows
more than 1\% absolute gain over DNN+residual models. 2) The increase
in number of layers has positive influence over both DNN+residual
and RMN systems. The performance of both systems reaches threshold
after 18 layers. Based on these observations, the number of optimum
RMN layers is chosen to 18.

Table \ref{tab:features-fbank/fmllr} shows the effect of fMLLR features
and fbank features using RMN. This table shows that RMN shows comparable
performance to LSTM using fbank features. The performance of RMN is
clearly better for fMLLR features when compared to fbank features.
The LSTM models seems to perform slightly better over RMN systems
for fbank features. It is also visible that both RMN and LSTM suffers
with fbank due to the existence of strong correlations in time and
frequency. Thus, further experiments in this paper will be conducted
based on fMLLR features.

\subsection{Effect of bi-directional RMN and parameters}

Table \ref{tab:param/wer-ami} shows that the BRMN model gains absolute
1.3 \% improvement over RMN. Next, it is observed that RMN shows slight
improvement over LSTM and a similar pattern is noted in bi-directional
models. A striking difference between RMN and LSTM models is the number
of computational parameters. Even though the RMN has deeper structure
the number of parameters is greatly reduced. From table, it is visible
that RMN requires 28.9 \% lesser parameters than LSTM while BRMN needs
38.5 \% lesser parameters than BLSTM. The reason behind this parameter
difference in BRMN is due to its simple addition of one extra weight
transform for future frames over RMN model, while BLSTM requires two
separate LSTM layers for both directions.\vspace{-0.3cm}

\begin{figure}[H]
\includegraphics[scale=0.35]{Figures/pyplots/res_vs_mem}

\caption{\label{fig:res_rmn_dnn_layer_size}Performance comparison between
RMN and (DNN+residual) networks for different layer sizes}
\end{figure}
\vspace{-0.5cm}

To verify the importance of deeper architecture in reducing data mismatch,
the training and validation error is plotted in figure \ref{fig:loss}.
Convergence of RMN model indicates that RMN is learning in a similar
fashion as LSTM. The training loss of RMN models is more than when
compared to LSTM models, substantiating that RMN is less prone to
overfitting. In case of validation loss, RMN models shows less error
over LSTM based systems.\vspace{-0.3cm}
\begin{figure}[H]
\includegraphics[scale=0.35]{Figures/pyplots/trainval_ccmbloss2}

\caption{\label{fig:loss}Training and validation err on RMN, BRMN, LSTM and
BLSTM using AMI corpus}
\end{figure}
 \vspace{-0.7cm}

\subsection{Speaker adaptation using ivectors}

The RMN is fed with ivectors by augmenting it with input features.
The experiments in table \ref{tab:param/wer-ami} shows that RMN with
fMLLR+ivector features gives 6.25 \% relative improvement over RMN
with fMLLR. A relative improvement of 7.4 \% is obtained by BRMN model
using fMLLR+ivector over fMLLR features. A minimal improvement of
absolute 0.3 \% is obtained for RMN over LSTM network. The BRMN system
with ivectors provides 1.75 \% relative improvement over BLSTM with
ivectors. Augmenting ivectors in BLSTM increases the parameters by
2 million whereas BRMN parameters are increased by 0.1 million. This
signifies that BRMN shows significant gains over BLSTM without increasing
the parameters drastically.\vspace{-0.7cm}
\begin{table}[H]
\caption{Comparison of LSTM and RMN with uni- and bi-directional layers and
different types of features. Performance of speaker adaptation using
ivectors is noted here. The number of parameters (\# params) computed
is also listed. \label{tab:param/wer-ami}\label{tab:features-fbank/fmllr}}

\centering{}{\footnotesize{}}%
\begin{tabular}{|c|c|c|c|c|c|}
\hline
\multirow{2}{*}{{\footnotesize{}Input}} & \multirow{2}{*}{{\footnotesize{}Model}} & \multicolumn{2}{c|}{{\footnotesize{}Uni-directional}} & \multicolumn{2}{c|}{{\footnotesize{}Bi-directional}}\tabularnewline
\cline{3-6}
 &  & {\footnotesize{}\% WER} & {\footnotesize{}\# params} & {\footnotesize{}\% WER} & {\footnotesize{}\# params}\tabularnewline
\hline
\hline
\multirow{2}{*}{{\footnotesize{}Fbank}} & {\footnotesize{}LSTM } & {\footnotesize{}27.8} & {\footnotesize{}14.5 M} & {\footnotesize{}26.3} & {\footnotesize{}17.1 M}\tabularnewline
\cline{2-6}
 & {\footnotesize{}RMN} & {\footnotesize{}28.1} & {\footnotesize{}10.7 M} & {\footnotesize{}26.4} & {\footnotesize{}9.9 M}\tabularnewline
\hline
\multirow{2}{*}{{\footnotesize{}fMLLR}} & {\footnotesize{}LSTM } & {\footnotesize{}25.8} & {\footnotesize{}14.5 M} & {\footnotesize{}24.5} & {\footnotesize{}16.1 M}\tabularnewline
\cline{2-6}
 & {\footnotesize{}RMN} & \textbf{\footnotesize{}25.6} & {\footnotesize{}10.3 M} & \textbf{\footnotesize{}24.3} & {\footnotesize{}9.9 M}\tabularnewline
\hline
{\footnotesize{}fMLLR+} & {\footnotesize{}LSTM } & {\footnotesize{}24.3 } & {\footnotesize{}16.5 M} & {\footnotesize{}22.9} & {\footnotesize{}18.1 M}\tabularnewline
\cline{2-6}
{\footnotesize{}ivec} & {\footnotesize{}RMN } & \textbf{\footnotesize{}24.0} & {\footnotesize{}10.4 M} & \textbf{\footnotesize{}22.5} & {\footnotesize{}10.0 M}\tabularnewline
\hline
\end{tabular}{\footnotesize \par}
\end{table}
\vspace{-0.7cm}
\begin{table}[H]
\caption{\label{tab:stateoftheart}Comparison of RMN with existing methods
in literature trained using 300 hours of Switchboard corpus and tested
with Hub5-00 eval set. In this table 3g is trigram, 4g is meant as
4-gram, bn-fMLLR is bottleneck features with fMLLR and ivec represents
100 dimensional ivectors built using section \ref{sub:Ivector-extractor}.}

\centering{}{\footnotesize{}}%
\begin{tabular}{|c|c|c|c|c|}
\hline
\multirow{2}{*}{\% WER} & \multirow{2}{*}{Model Type} & \multicolumn{3}{c|}{{\footnotesize{}SWB (\% CE WER)}}\tabularnewline
\cline{3-5}
 &  & {\footnotesize{}3g} & {\footnotesize{}4g} & {\footnotesize{}4g+ivec}\tabularnewline
\hline
\hline
{\footnotesize{}Proposed } & {\footnotesize{}\hspace{-0.7cm}RMN} & {\footnotesize{}13.0} & {\footnotesize{}12.0} & \textbf{\footnotesize{}10.9}\tabularnewline
\cline{2-5}
{\footnotesize{}Models} & {\footnotesize{}\hspace{-0.6cm}BRMN} & {\footnotesize{}11.8} & {\footnotesize{}10.8} & \textbf{\footnotesize{}9.9}\tabularnewline
\hline
{\footnotesize{}State-of-the-art} & \multicolumn{3}{c|}{{\footnotesize{}\hspace{-2cm}TDNN \cite{povey2016purely}}} & {\footnotesize{}12.5}\tabularnewline
\cline{2-5}
{\footnotesize{}results } & \multicolumn{3}{c|}{{\footnotesize{}Unfolded RNN + fMLLR \cite{saon2014unfolded}}} & {\footnotesize{}12.7}\tabularnewline
\cline{2-5}
{\footnotesize{}in } & \multicolumn{3}{c|}{{\footnotesize{}\hspace{-0.5cm}LSTM + bn-fMLLR \cite{saon2016ibm}}} & {\footnotesize{}10.8}\tabularnewline
\cline{2-5}
{\footnotesize{}literature} & \multicolumn{3}{c|}{{\footnotesize{}\hspace{-2.1cm}LSTM \cite{povey2016purely}}} & {\footnotesize{}11.6}\tabularnewline
\cline{2-5}
 & \multicolumn{3}{c|}{{\footnotesize{}\hspace{-2cm}BLSTM \cite{povey2016purely}}} & {\footnotesize{}10.3}\tabularnewline
\hline
\end{tabular}{\footnotesize \par}
\end{table}
\vspace{-0.5cm}

\subsection{Results of various LVCSR systems\label{sub:Summary-of-results}}

This section brings the state-of-the-results of LSTM, BLSTM, unfolded
RNN and TDNN models using 300 hours of switchboard data tested with
hub5-2000 evaluation set. These results are obtained by using ivectors
and 4-gram language model. To present a fair comparison, RMN model
is also trained with 300 hours data followed by testing with a trigram
language model built with Fisher and switchboard corpus, and later
rescored with 4-gram language model. The RMN and BRMN is trained in
a similar configuration as mentioned in section \ref{sub:RMN-configuration-and}
and \ref{sub:BRMN-configuration-and}. The table \ref{tab:stateoftheart}
shows the \% WER of switchboard (SWB) subset obtained after cross-entropy
(CE) training. The effectiveness of RMN in modeling long-term dependencies
for large vocabulary data is clearly visible in table \ref{tab:stateoftheart}.

\section{Conclusion}

In this paper we proposed residual memory network (RMN) structure,
a variant of feed-forward network to capture temporal context. We
have also introduced a bi-directional RMN which capture forward and
backward states with less computational complexity. The reasonable
effectiveness of RMN in capturing both temporal and higher-order information
was shown in AMI and switchboard tasks. BRMN showed 3.8 \% relative
improvement over BLSTM and RMN gained 6 \% relative improvement over
LSTM. In the future, we will develop a way to further increase the
depth of RMN for capturing longer context. A interesting direction
is to validate the ability of RMN in language modeling tasks. To increase
the efficiency of RMN with fbank features, we would like to use convolutional
layers before RMN to learn spatial representations.

\bibliographystyle{IEEEbib}

redpajama_set_name: RedPajamaArXiv


Team Sky debuted what looked like a new Castelli skinsuit at the Giro d'Italia's first time trial on Tuesday, a skinsuit that could be the specially designed kit Chris Froome will wear at the Tour de France this summer.
The new suit, which was worn by Mikel Landa and Geraint Thomas was noticeably different from the Castelli Body Paint 3.3 suit being worn by the rest of Team Sky.
Team Sky and their clothing partner Castelli have been working with researchers at the Norwegian University of Science and Technology for the last year to develop a new skinsuit for this season, ahead of Froome's attempt to win a fourth Tour title this July. Castelli replaced Rapha as the team's clothing sponsor for 2017.
The skinsuits worn by Landa and Thomas on the Giro's stage 10 time trial on Tuesday featured visibly different fabrics and construction to the existing Castelli Body Paint 3.3 suit, as well as featured an integrated number pocket.
>>> Is it necessary to buy an expensive skinsuit, or will a cheap one do?
While unable to confirm whether this exact suit will be worn by Froome this July as it could evolve further and change before then, it is evidence of new technologies being tested by the team and Castelli in the run up to the Tour.
Sky started working with researchers at the Norwegian University of Science and Technology at the start of 2016, a collaboration that came about after staff at Sky read the thesis of one of the researchers in the department of physics, Luca Oggiano who has a PhD in sports aerodynamics, and got in touch.
Although details of the technology used in the suit are being kept closely under wraps, speaking to Cycling Weekly earlier this spring, Oggiano said the team had tried to take a "completely new approach" to what has been done before; rethinking the fabric and way the suit is put together.
>>> Which aero bike is actually the fastest?
The researchers also have a replica model of Froome in his time trial position for round the clock testing, and have been testing prototypes in indoor velodromes.
"We've been doing almost a year of intensive testing, we test different technologies and different ideas that we have and that we are either going to implement in the prototype," Oggiano said. "It's about one year of intensive testing through the university and some students and researchers.
This year's Tour features two time trials at both end of the race; a 14 kilometre test on stage one, then a crucial 23 kilometre TT on the penultimate stage in Marseille after which the race winner will be all but crowned. Though there are significantly fewer time trialling kilometres this year than in recent editions of the race, the time trials remain as important to the general classification.
Simon Jones, speaking as Sky's head of performance support and innovation before he took over as performance director at Cycling Australia in April, said they were hoping to see "continuous improvements" rather than a "step change" in performance with the suit.
"It will always boil down to seconds, we're not going to suddenly take a minute off a 40km time trial but you can win or lose a Tour on a matter of seconds," Jones said.
Froome however, is hoping he won't even get to wear the suit by the time the second time trial comes around in France, as if he's in the yellow jersey by that point he will be required to wear the official, race issue yellow skinsuit provided by the organisers.
"[We're trying to] make sure things we can control we're absolutely all over," Froome told Cycling Weekly of the suit. "If everything goes according to plan hopefully I'll be in a yellow skinsuit by that point, so I probably wont even get to use it.


I love it. I'm grateful for it. But I certainly didn't deserve it.
Mother's Day isn't a fun day for many people. There are lots of reasons why they feel pain instead of joy on that expectly happy day. But God sees, and He understands. He meets us where we are.
How Do You Respond To The Prostitute?
How do you respond to someone else's sin? Some of us think "I would never throw the stone!". Question for you: Do you go and gossip about someone caught in sin? Do you tell everyone else and air that persons dirty laundry all in the name of "prayer request"? That is throwing the stone.


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The Philippine National Police - Special Action Force (PNP-SAF), through its BAC, will undertake a Small Value Procurement for the Food Supplies Expenses amounting to PhP 462.733.34, in accordance with Section 53.9 of the Implementing Rules and Regulations of Republic Act No. 9184.
The Philippine National Police - Special Action Force (PNP-SAF), through its BAC, will undertake a Shopping for the Office Supplies Expenses amounting to Php 376,833.34. in accordance with Section 52.1 of the Implementing Rules and Regulations of Republic Act No. 9184.
The Philippine National Police - Special Action Force (PNP-SAF) through ts BAC will undertake a Small Value Procurement for the Training Expenses amounting to PhP 56,400.00 in accordance with Section 53.9 of the Implementing Rules and Regulations of Republic Act No. 9184.
The Philippine National Police - Special Action Force (PNP-SAF), through its BAC, will undertake a Srnall Value Procurement for the Other Supplies and Materials Expenses amounting to PhP 13,400.00, in accordance with Section 53.9 of the Implementing Rules and Regulations of Republic Act No. 9184.
The Philippine National Police - Special Action Force (PNP-SAF) through its BAC will undertake a Small Value Procurement for the Repair and Maintenance of Motor Vehicles amounting to PhP 300,00000. in accordance with Section 53.9 of the Implementing Rules and Regulations of Republic Act No. 9184.

redpajama_set_name: RedPajamaCommonCrawl


text:
Q: Convert pcap file to LAS python I am tasked with converting pcap files to LAS files in python. I know this is a possible task because veloview uses a python shell and this command -- vv.saveLASFrames('c:/path/to/output.las', 10, 20, 0)
in this example, 10 is the starting frame, 20 is the ending frame, and 0 is the raw transformation mode.
I essentially want to know of there are any libraries that perform the similar function of transforming a pcap file to an LAS file. I don't even need it to be as advanced as extracting the point data. I already have code that does that. I just need the LAS file.
I have tried using these resources -- https://github.com/ArashJavan/veloparser
and -- https://pypi.org/project/velodyne-decoder/
and neither of them works. Any help would be greatly appreciated!

redpajama_set_name: RedPajamaStackExchange


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Danish People's Party spokesperson convicted on racism charge
Jesper Langballe, church spokesperson for the Danish People's Party (DF), was on Friday convicted of making defamatory statements about Muslims. Langballe pleaded guilty to the charge of defamation under the anti-racism section of the penal code.
In January, Langballe wrote a letter to Berlingske Tidende newspaper in which he commented on claims made by the chairman of the Free Press Society, Lars Hedegaard, that Muslim fathers rape their daughters.
In his letter, Langballe supported Hedegaard's views, saying that Hedegaard should not have written that "Muslim fathers rape their daughters, when the truth seems to be that they only kill them (the so-called honour killings) – and turn a blind eye when uncles rape them."
Langballe lashed out at the laws banning racist speech, and for allowing courts to convict people based on whether the defendant felt violated or defamed, and "not whether the statements made are actually true or false," he said. "Given this section and its position within the penal code, I have to believe that I'm being convicted in advance of the trial. I have no intention of participating in such a charade. That's why I confess."
Langballe was sentenced to pay 5,000 kroner.
Copenhagen Post, 6 December 2010
This entry was posted in Denmark, Far right racists by Bob Pitt. Bookmark the permalink.


"Miles Herndon, dashing soldier of fortune, delivers the rightful prince.
Warners are indeed fortunate in having Errol Flynn in the family to play Herndon.
the Pauper, which is climaxed by an elaborate coronation sequence.
It is Errol Flynn, playing a good natured soldier of fortune, who takes the young prince under his wing – not the least believing his story – and finally clears the way for a nick-of-time restoration of the royal youth, just as the unwilling beggar boy is about to be crowned king of England. In the role, Flynn is a dashing figure.
Warners have made the coronation ceremony one of the year's spectacular screen episodes.
The Prince and the Pauper is an excitingly narrated, handsomely prodeuced, finely acted picture – an artistic achievement for producer Hal B. Wallis and all concerned – and a box-office natural.
Heading the supporting bill is a color short, A Day at Santa Anita.
Just in time for the Coronation!
Published on May 1, 1937 – Perfect because of the May Day connections to the legend of Robin Hood.
Movie Released in May of 1938.
How do you like the idea of the dashing young Errol Flynn as the adventurous Robin Hood?
of the most popular of the Fairbanks' roles.
partner with Patric Knowles in a featured role.
In the opinion of Errol Flynn, cooking is best in the great open spaces.
Flynn, the Irish actor, author, world-traveler and soldier-of-fortune now starring in the Cosmopolitan production of Green Light, which closes tonight at Warners' Hollywood and Downtown, is a great admirer of culinary delicacies.
Flynn learned the art of cookery beside roaring bonfires. His tutors were natives of New Guinea, Australia, and the uncharted islands in the South Seas.
He discovered that they know more about cooking and seasoning than most of the civilized races of the earth.
Rory & Sean in Coronado!
Rory & Sean have been a Very Big Hit in Coronado this Weekend, at all the VIP Ceremonies, Rory's sensational Show about Errol, Dive Bomber, introduced by Sean, and a "The Baron of Mulholland" Meet & Greet/Book Signing.
Chris Lemmon and Leonard Maltin were around. Legendary Flynn-Fan Richard Dreyfuss met with Rory & Sean before the show.
Several festival guests had great stories about Errol. One was a little girl at her aunt's home in Holmby Hills when Errol came by and read all the kids Peter and the Wolf. One fellow's father used to watch Errol play tennis at the Hotel Del and said he was incredible, one day nearly beating the top ranked player in California/one of best players in the world. Also heard about Errol socializing with Naval officers at North Island Officers Club, at the Hotel Del bar, and at their homes on Coronado.
P.S. Dive Bomber is extraordinary on the big screen.


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Tag Archives: John McPherson
Trailer of the Day: Tainted Getaway
What was meant to be a once-in-a-lifetime job opportunity for Allison Haven becomes a nightmare when she's abducted by escape convict Brock Bremmer, who vows to retrieve his lost money from a tragic past. Little does he know an old nemesis, Mason, is hot on his trail to retrieve it as well, including the authorities…
July 25, 2019 in Trailers.
Interview: John V. Soto
Director John V. Soto discusses his new Perth-shot Sci Fi thriller, The Gateway. John's previous directing credits include The Reckoning starring Luke Hemsworth, Viva Bianca and Jonathan LaPaglia and Needle with Ben Mendelsohn. Interview by Matthew Eeles Tell us a about 'The many interacting worlds hypothesis' and your research into it? Early on in the development process for…
May 2, 2018 in Interviews.
Trailer of the Day: Wrong Night Stand
Wrong Night Stand Directed by Mark Huxley Written by Mark Huxley and Neal Huxley Starring Neal Huxley, John McPherson and Tanya Jade Wrong Night Stand tells the story of Eddie and Eve. Shortly after the two start dating, Eve's crazed ex boyfriend is released from prison, and begins to hunt down Eve. Trouble ensues as Eddie is stalked and…
February 26, 2018 in News, Trailers.
Myles Pollard is back from the dead in the first teaser trailer for John V. Soto's The Gateway
The Gateway Directed by John V. Soto Written by John V. Soto and Michael White Produced by John V. Soto Starring Jacqueline McKenzie, Hayley McElhinney, Myles Pollard, Shannon Berry, Troy Coward, Ben Mortley, Adam T Perkins, John McPherson, Ryan Panizza, Shirley Toohey, Jag Pannu and Steve Burridge A particle physicist grieving over the loss of her husband in…
June 28, 2017 in Trailers.


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CD8+ T Cells Are Required For Glatiramer Acetate Therapy in Autoimmune Demyelinating Disease
Andrew F. Tyler, Jason P. Mendoza, Mihail Firan, Nitin J. Karandikar
The exact mechanism of glatiramer acetate (GA, Copaxone®), an FDA-approved immunomodulatory therapy for multiple sclerosis (MS), remains unclear after decades of research. Previously, we have shown that GA therapy of MS induces CD8+ T cell responses that can potentially suppress pathogenic CD4+ T cell responses. Using a murine model of MS, experimental autoimmune encephalomyelitis (EAE), we now demonstrate that CD8+ T cells are necessary in mediating the therapeutic effects of GA. Further, adoptive transfer of GA-induced CD8+ T cells resulted in amelioration of EAE, establishing a role as a viable immunotherapy in demyelinating disease. Generation of these cells required indoleamine-2,3-dioxygenase (IDO), while suppressive function depended on non-classical MHC class I, IFN-γ, and perforin expression. GA-induced regulatory myeloid cells, previously shown to activate CD4+ regulatory T cells in an antigen-independent manner, required CD8+ T cells for disease suppression in vivo. These studies demonstrate an essential role for CD8+ T cells in GA therapy and identify their potential as an adoptive immunotherapeutic agent.
Demyelinating Diseases
T-lymphocytes
Autoimmune Experimental Encephalomyelitis
Indoleamine-Pyrrole 2,3,-Dioxygenase
Perforin
Adoptive Transfer
Myeloid Cells
Tyler, A. F., Mendoza, J. P., Firan, M., & Karandikar, N. J. (2013). CD8+ T Cells Are Required For Glatiramer Acetate Therapy in Autoimmune Demyelinating Disease. PLoS One, 8(6), [e66772]. https://doi.org/10.1371/journal.pone.0066772
CD8+ T Cells Are Required For Glatiramer Acetate Therapy in Autoimmune Demyelinating Disease. / Tyler, Andrew F.; Mendoza, Jason P.; Firan, Mihail; Karandikar, Nitin J.
Tyler, AF, Mendoza, JP, Firan, M & Karandikar, NJ 2013, 'CD8+ T Cells Are Required For Glatiramer Acetate Therapy in Autoimmune Demyelinating Disease', PLoS One, vol. 8, no. 6, e66772. https://doi.org/10.1371/journal.pone.0066772
Tyler AF, Mendoza JP, Firan M, Karandikar NJ. CD8+ T Cells Are Required For Glatiramer Acetate Therapy in Autoimmune Demyelinating Disease. PLoS One. 2013 Jun 21;8(6). e66772. https://doi.org/10.1371/journal.pone.0066772
Tyler, Andrew F. ; Mendoza, Jason P. ; Firan, Mihail ; Karandikar, Nitin J. / CD8+ T Cells Are Required For Glatiramer Acetate Therapy in Autoimmune Demyelinating Disease. In: PLoS One. 2013 ; Vol. 8, No. 6.
@article{c1c1324b597f4254b27cf3b26cd4803b,
title = "CD8+ T Cells Are Required For Glatiramer Acetate Therapy in Autoimmune Demyelinating Disease",
abstract = "The exact mechanism of glatiramer acetate (GA, Copaxone{\circledR}), an FDA-approved immunomodulatory therapy for multiple sclerosis (MS), remains unclear after decades of research. Previously, we have shown that GA therapy of MS induces CD8+ T cell responses that can potentially suppress pathogenic CD4+ T cell responses. Using a murine model of MS, experimental autoimmune encephalomyelitis (EAE), we now demonstrate that CD8+ T cells are necessary in mediating the therapeutic effects of GA. Further, adoptive transfer of GA-induced CD8+ T cells resulted in amelioration of EAE, establishing a role as a viable immunotherapy in demyelinating disease. Generation of these cells required indoleamine-2,3-dioxygenase (IDO), while suppressive function depended on non-classical MHC class I, IFN-γ, and perforin expression. GA-induced regulatory myeloid cells, previously shown to activate CD4+ regulatory T cells in an antigen-independent manner, required CD8+ T cells for disease suppression in vivo. These studies demonstrate an essential role for CD8+ T cells in GA therapy and identify their potential as an adoptive immunotherapeutic agent.",
author = "Tyler, {Andrew F.} and Mendoza, {Jason P.} and Mihail Firan and Karandikar, {Nitin J.}",
T1 - CD8+ T Cells Are Required For Glatiramer Acetate Therapy in Autoimmune Demyelinating Disease
AU - Tyler, Andrew F.
AU - Mendoza, Jason P.
AU - Firan, Mihail
AU - Karandikar, Nitin J.
N2 - The exact mechanism of glatiramer acetate (GA, Copaxone®), an FDA-approved immunomodulatory therapy for multiple sclerosis (MS), remains unclear after decades of research. Previously, we have shown that GA therapy of MS induces CD8+ T cell responses that can potentially suppress pathogenic CD4+ T cell responses. Using a murine model of MS, experimental autoimmune encephalomyelitis (EAE), we now demonstrate that CD8+ T cells are necessary in mediating the therapeutic effects of GA. Further, adoptive transfer of GA-induced CD8+ T cells resulted in amelioration of EAE, establishing a role as a viable immunotherapy in demyelinating disease. Generation of these cells required indoleamine-2,3-dioxygenase (IDO), while suppressive function depended on non-classical MHC class I, IFN-γ, and perforin expression. GA-induced regulatory myeloid cells, previously shown to activate CD4+ regulatory T cells in an antigen-independent manner, required CD8+ T cells for disease suppression in vivo. These studies demonstrate an essential role for CD8+ T cells in GA therapy and identify their potential as an adoptive immunotherapeutic agent.
AB - The exact mechanism of glatiramer acetate (GA, Copaxone®), an FDA-approved immunomodulatory therapy for multiple sclerosis (MS), remains unclear after decades of research. Previously, we have shown that GA therapy of MS induces CD8+ T cell responses that can potentially suppress pathogenic CD4+ T cell responses. Using a murine model of MS, experimental autoimmune encephalomyelitis (EAE), we now demonstrate that CD8+ T cells are necessary in mediating the therapeutic effects of GA. Further, adoptive transfer of GA-induced CD8+ T cells resulted in amelioration of EAE, establishing a role as a viable immunotherapy in demyelinating disease. Generation of these cells required indoleamine-2,3-dioxygenase (IDO), while suppressive function depended on non-classical MHC class I, IFN-γ, and perforin expression. GA-induced regulatory myeloid cells, previously shown to activate CD4+ regulatory T cells in an antigen-independent manner, required CD8+ T cells for disease suppression in vivo. These studies demonstrate an essential role for CD8+ T cells in GA therapy and identify their potential as an adoptive immunotherapeutic agent.


text:
Q: How can I join/merge 2 DataFrames, keeping values from the second? I have two DataFrames with user details and scores. Some users have a second score and will be present in the second DataFrame. What I want to do is to join or merge them together (don't really mind which) to get their final score i.e. if they exist in the second DataFrame then take it from there, otherwise from the first.
DataFrame one:
    first_name  last_name              email  score               feedback
0         Bill      First  user1@example.com   57.0  Needs to try again
1         Anna     Second  user2@example.com   10.0  Not enough to proceed
2         Fred      Third  user3@example.com  100.0  Excellent!

DataFrame two:
    first_name  last_name              email  score      feedback
0         Bill      First  user1@example.com  100.0  Much better!

Desired result:
    first_name  last_name              email  score               feedback
0         Bill      First  user1@example.com  100.0  Much better!
1         Anna     Second  user2@example.com   10.0  Not enough to proceed
2         Fred      Third  user3@example.com  100.0  Excellent!

The closest I've got is df1.merge(df2, on=['email', 'first_name', 'last_name', ], how='left') but that gives me columns: first_name last_name email score_x feedback_x score_y feedback_y

A: Use pd.concat and drop_duplicates:
out = pd.concat([df2, df1]).drop_duplicates(['first_name', 'last_name', 'email'])
print(out)

# Output
  first_name last_name              email  score               feedback
0       Bill     First  user1@example.com  100.0           Much better!
1       Anna    Second  user2@example.com   10.0  Not enough to proceed
2       Fred     Third  user3@example.com  100.0             Excellent!

Assuming first_name, last_name and email fields are the primary key to identify records like your merge.
Just before drop_duplicates, your dataframe looks like:
>>> pd.concat([df2, df1])
  first_name last_name              email  score               feedback
0       Bill     First  user1@example.com  100.0           Much better!
0       Bill     First  user1@example.com   57.0     Needs to try again  # dupe
1       Anna    Second  user2@example.com   10.0  Not enough to proceed
2       Fred     Third  user3@example.com  100.0             Excellent!

A: Alternative using combine_first:
cols = ['email', 'first_name', 'last_name']
out = df2.set_index(cols).combine_first(df1.set_index(cols)).reset_index()

output:
               email first_name last_name  score               feedback
0  user1@example.com       Bill     First  100.0           Much better!
1  user2@example.com       Anna    Second   10.0  Not enough to proceed
2  user3@example.com       Fred     Third  100.0             Excellent!


text:
NN Life Sciences
Extremities Market is Still Maturing
Zimmer Biomet looking to dominate the shoulder sector.
Zimmer Biomet Strengthens Spine Offering with PrimaGen Advanced Allograft
Zimmer Biomet Appoints President of Americas
Minimally Invasive Spine Market to Surpass $842 Million by 2023
Zimmer Biomet Internationally Launches Subchondroplasty Procedure
Zimmer Biomet Recalls Comprehensive Reverse Shoulder Due to High Fracture Rate
Michael Barbella, Managing Editor06.05.17
Consider it a natural evolution, of sorts.
The planet's extremities market, long ignored by major orthopedic device manufacturers, is finally commanding respect as companies attempt to counterbalance sluggish growth in the saturated, maturing hip and knee replacement sectors. Fueled by an aging world population, more youth-related sports injuries, and rising rates of obesity, osteoarthritis, and osteoporosis, the global extremities market is projected to be worth $15.9 billion by 2024, according to Research and Markets data. Internal fixation devices such as plates and screws have dominated the sector in recent years due to the early functionality, abbreviated hospital stays, minimal scarring, and reduced non-union risk associated with these products. Acumed LLC has particularly benefited from the high demand for internal fixation, having sold 500,000 wrist fixation implants (Acu-Loc and Acu-Loc 2) in just two years.
Such promise, of course, is garnering interest among major orthopedic companies that traditional have overlooked the sector in favor of the more lucrative large-joint sector. ODT's May/June feature story "Going to Extremes" examines the trends and challenges driving the extremities market as well as some of the latest technologies available to patients. Steve Vankoski, senior director of global marketing, Extremities, for Zimmer Biomet Inc., was among the experts interviewed for the feature; his full input is provided in the following Q&A.
Michael Barbella: Please discuss the trends in the extremities market. What trends have you noticed this year and how do they differ (if at all) from past trends?
Steve Vankoski: One of the biggest trends in the extremities market is the increased use of reverse shoulder arthroplasty, which was approved by the U.S. Food and Drug Administration (FDA) in 2003.1 Currently, in the United States, approximately one half of shoulder surgeries are reverse shoulder arthroplasty and the balance are total shoulder arthroplasty or hemi-arthroplasty.2 In Europe, the number is higher with reverse shoulder arthroplasty accounting for approximately 70 percent of shoulder surgeries.3 Reverse shoulder surgeries are on the rise due to: increasing utilization to treat shoulder fracture patients; expanding application to patients, both elderly and more active, with impaired rotator cuff; and surgeons becoming more comfortable with the procedure and its successful outcomes.
We also expect to see advanced imaging with 3-D planning and patient specific instrumentation (PSI) to accelerate over the next decade. Zimmer Biomet was the first company in the market to introduce PSI for shoulder replacement. The Zimmer Biomet PSI Shoulder and Signature Shoulder solutions are 3D virtual surgery planning software, coupled with a complete set of PSI guides and a patient-specific glenoid bone model, providing a surgeon the ability to develop a personalized plan to accommodate each patient's unique anatomy and then execute that plan with precision. The combination of the Zimmer Biomet PSI Shoulder planning software and instrument guides is designed to provide a surgeon with tools to optimize positioning and fixation outcomes and to help maximize implant performance.
Today, approximately 10 percent of surgeons are using PSI, and that number will continue to grow. Because shoulder surgery is complex with varying glenoid morphology of an arthritic shoulder joint, surgeons increasingly rely on advanced imaging and three dimensional planning to better understand how to place an implant. The planning is also convenient, enabling surgeons to review scans right from their own PCs or laptops.
Another trend is implants are becoming more nuanced. While implant base plates have historically been simply flat, recently introduced solutions come in a variety of shapes, including wedges and curvatures, giving surgeons more options to match the patient's anatomy and preserve bone. We can anticipate these implant options to garner increased adoption in the future, particularly in combination with PSI solutions which will allow the surgeon to plan and select the optimal implant design for the patient and then place it in the ideal position in surgery.
Barbella: What challenges face companies in the small joint (extremities) sector, and how are these challenges different than those faced by companies manufacturing large joints - i.e., hips and knees? How can companies in the extremities sector overcome these challenges?
Vankoski: Many surgeons operate on hips, knees, and shoulders so large orthopaedic manufacturers, such as Zimmer Biomet, have an advantage because the company owns significant market share in all those segments and can offer streamlined access to a full product line, making it more challenging for smaller companies. Nevertheless, the advantage for companies that focus on the small joint sector is they are highly specialized, and their sales force is well equipped to market specifically to shoulder specialists who are devoted to shoulder surgery.
Barbella: What new technologies are on the horizon? What kinds of implants hold the most potential for patients and for market growth?
Vankoski: The Zimmer Biomet Comprehensive Vault Reconstruction System (VRS), the first patient-matched glenoid implant cleared to specifically treat patients with a severely deficient rotator cuff and extensive bone loss which precludes the use of a standard glenoid baseplate, is one technology that holds the most potential for patients. The VRS uses CT imaging and advanced 3D reconstruction techniques to allow surgeons to personalize each patient's implant. With the VRS, we can develop any shape glenoid as long as the implant falls within a certain volumetric space and utilizes a specific number of screws, ensuring the implant fits like a glove. Additionally, there is no need to remove any more bone than the patient has already lost.
More than 60 VRS cases have been performed since September [2016]. While the volume is not tremendously high, the technology is valuable because it offers customization, helping patients who may not have any other solution.
Other technologies on the horizon include stemless implants, range of motion analysis and vitamin E solutions. We have seen humeral implants become progressively shorter over the past decade and we should expect the utilization of shorter stems to contunie to increase. Some designs are so short that they have been defined as stemless. Zimmer Biomet introduced the first stemless shoulder in Europe in 2004. The clinical outcomes have been promising and we should expect clearance of multiple stemless implants in the United States in the near future. Range of motion analysis will be an enhancement of the aforementioned PSI technology that will enable surgeons to simulate on a computer the range of motion for a specific patient and shoulder implant prior to surgery so the surgeon can detect impingment, evaluate range of motion and optimize implant placement of both the glenoid and humeral implants with the goal of improved patient outcomes. vitamin E solutions, already used in hip and knee implants, are expected to enhance the durability and strength of the shoulder reconstruction.
Barbella: Where does innovation come from in the extremities market? How does Zimmer Biomet stay innovative?
Vankoski: To stay innovative, Zimmer Biomet believes it's important to focus on unmet needs, for the patient, for the surgeon and for the hospital. We believe that it is imperative to consider each of these important stakeholders when contemplating new solution strategies. Zimmer Biomet also contends that it must continue to focus on those underserved patients who may benefit from orthpaedic innovation that is simply not available to them yet. And lastly, to not pigeonhole one's thinking and look for assets and opportunities outside of the extremities market that may serve as solutions in the extremities space. Innovation can be achieved through organic growth or acquisitions.
Barbella: Aside from the implants, how does the extremities market differ from large joints, or spine? What makes extremities implants a design challenge?
Vankoski: The extremities market differs from the large joints or spine markets because it is still maturing. The exact design optimization and mechanics for the shoulder market are a work in progress while the hip and knee markets are very mature. Also, patients are less aware of their options in the extremities space, specifically hand and ankle, compared to large joints.
Another important difference is there are two ways to reconstruct the shoulder—total shoulder and reverse shoulder arthroplasty. Reverse shoulder arthroplasty is one of the most meaningful innovations in the shoulder market in the last 15 years.
Other than these differences, the extremities market does not differ greatly from the large joints or spine markets. All markets engage surgeons in a similar manner, and the surgery complications, infection rates and success rates are similar across the markets.
Barbella: How do the technological/physiological demands of small joints differ from other orthopedic markets?
Vankoski: The technological and physiological demands of small joints differ from other orthopaedic markets in a few ways. The shoulder is the most flexible joint in the body and, generally, the loads are less than large joints.
The American Society for Testing and Materials (ASTM) standards for physical testing are not as established and mature for shoulder implants as they are for knee and hip implants.
While survivorship is similar for knee, hip and shoulder surgeries at five years, total shoulder replacement surgery may immobilize patients for a longer period because surgeons typically cut into the muscle.
Barbella: Where do the extremities and trauma markets overlap? How do they differ?
Vankoski: When thinking about the extremities and trauma markets, the age of the patient and the condition of the joint matter. Depending on these factors, surgeons will decide to replace or repair the joint. With a young patient, the surgeon may use trauma products to plate and repair the existing joint. With an older patient, the surgeon may use extremity arthroplasty products to completely replace the joint. Nevertheless, there is no clear age distinction on when a surgeon will opt for trauma or shoulder arthoplasty treatment as the patient's activity level and surgeon's personal treatment preferences are important variables.
Barbella: Where do you see the extremities market five years from now?
Vankoski: Five years from now we will likely see greater penetration of reverse shoulder arthroplasty, more stemless implants for total shoulder procedures, increased utilization of advanced bearing materials like vitamin E, and greater adoption and innovation in 3D personalized planning, instrumentation, and implants.
1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4762794/
2. Orthopedic Network News, Volume 28, Number 1, January 2017
3. http://www.internationalshoulderjournal.org/article.asp?issn=0973-6042;year=2007;volume=1;issue=4;spage=108;epage=113;aulast=Katz
More of a Niche Market
Innovation With Speed
Big Trend Towards Small Bone Plating
The Intricacy of Extremity Anatomy
North American Elbow Replacement Market to Hit $29.5 Million by 2023
Going to Extremes
Revised ASTM Standard Will Help Test, Improve Elbow Prostheses
Zimmer Biomet's First-Quarter Sales Rise 3.8 Percent
Spine Wave Hires Executive VP of Research and Development
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text:
Q: Visual Studio 2008 profiler analysis - missing time I ran the Visual Studio 2008 profiler against my ASP.NET application and came up with the following result set.
CURRENT FUNCTION                                      TIME (msec)
---------------------------------------------------|--------------
Data.GetItem(params)                               |   10,158.12
---------------------------------------------------|--------------

Functions that were called by Data.GetItem(params)    TIME (msec)
---------------------------------------------------|--------------
Model.GetSubItem(params)                           |     0.83
Model.GetSubItem2(params)                          |     0.77
Model.GetSubItem3(params)                          |     0.76
etc.

The issue I'm facing is that the sum of the Functions called by Data.GetItem(params) do not sum up to the 10,158.12 msec total. This would lead me to believe that the bulk of the time is actually spent executing the code within that method.
My question is ... does Visual Studio provide a way to analyze the method itself so I can see which sections of code are taking the longest? if it does not are there any recommended tools to do this? or should I start writing my own timing scripts?
Thank you

A: The VS 2008 profiler does not support block level profiling, but I believe that Red Gate's profiler does.

A: Don't concentrate on timing the code. That's the top-down approach.
Bottom-up is way more effective.
This method works just fine in Visual Studio.

A: An another approach would be to break up your GetItem method into a number of smaller methods (perhaps doing a binary chop) to narrow down where the time is being spent. Probably easier than writing some timing scripts.


text:
Title: An investigation of the cellular functions of LEDGF/p75
Author: Hughes, Siobhan Marie
Awarding Body: Imperial College London
Current Institution: Imperial College London
Lens epithelium-derived growth factor (LEDGF) is a critical co-factor of lentiviral integration that accounts for the characteristic bias of the retroviral genus towards integration within active transcription units of the host genome. It's well-characterised role in viral replication notwithstanding, cellular functions of LEDGF are poorly understood. In this study gene expression profiling and proteomic analysis have been used to elucidate cellular functions of LEDGF. Gene expression profiling of mouse embryonic fibroblasts (MEFs) derived from Psip1-/- (LEDGF-null) embryos revealed that less than 200 genes were significantly up- or down-regulated compared to wild type (WT) MEFs. The changes in gene expression of a subset of affected genes were confirmed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assays. However, these changes could not be reversed by re-introduction of LEDGF into knockout MEFs. Furthermore, in vitro knockout of Psip1 did not reproduce the effects of in utero knockout, suggesting that LEDGF ablation per se does not account for the observed perturbations in gene expression. Collectively, these data strongly indicate that in spite of its apparent ubiquitous association with active transcription units, LEDGF does not play an essential nor direct role in the regulation of gene expression. Tandem affinity purification (TAP) of a cTAP-tagged truncation mutant of LEDGF (residues 326-530) identified the heterodimeric S-phase kinase, termed cell division cycle 7 (Cdc7):activator of S-phase kinase (ASK), as a novel interactor of LEDGF. Both kinase subunits co-immunoprecipitated with LEDGF from human cells, and endogenous Cdc7 and LEDGF proteins displayed nuclear co-localisation in G1 and S phases of the cell cycle. Moreover, Cdc7:ASK was enriched on chromatin when ectopically co-expressed with LEDGF in human cells, suggesting that LEDGF may affect chromatin binding of the kinase. Truncation analyses identified the integrase-binding domain (IBD) of LEDGF as essential and minimally sufficient for the interaction with Cdc7:ASK. Reciprocally, the interaction required auto-phosphorylation of the kinase and the presence of fifty C-terminal residues of ASK. LEDGF potently stimulated the kinase activity of Cdc7:ASK, increasing phosphorylation of one of its substrates, mini-chromosome maintenance 2 (MCM2), in vitro by more than 10-fold. The effect strictly depended on the interaction, as LEDGF mutants unable to bind Cdc7:ASK also failed to promote its kinase activity. Intriguingly, removing the C-terminal region of ASK, involved in the interaction with LEDGF, resulted in a hyper-active kinase. These results indicate that the interaction with LEDGF relieves autoinhibition of Cdc7:ASK kinase activity, imposed by the C-terminus of ASK. While more work is required to fully elucidate the natural cellular functions of LEDGF, this study has provided some insight into its role in cell biology. In particular, understanding the role of LEDGF in Cdc7:ASK kinase regulation and the implications of this interaction during S phase of the cell cycle are promising avenues of investigation highlighted in this study.
Supervisor: Cherepanov, Peter ; Weber, Jonathan Sponsor: Not available
10.25560/6091


text:
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http://www.discovernikkei.org/es/journal/2019/6/18/mutual-aid-society-1/
Por Takako Day / 18 Jun 2019
Pre-World War II Chicago had no segregated residential enclaves for Japanese residents like the Japantowns and Little Tokyos on the West Coast, but this did not mean there wasn't a Japanese community. Actually, there was a Japanese community, but it was more of an invisible mental space in the Japanese residents' minds than a physical community.
Although Japanesehad livedscattered throughout Chicago since the 19th century, they certainly had formed various community groups and organizations. Becoming members of those groups and attending their meetings helped these people maintain their identity as Japanese. In fact, a sense of community was needed by the Japanese immigrants, because "even in such a cosmopolitan city as Chicago, where, because of the comparatively small number of Japanese, prejudice against them was at a minimum, the Japanese residents…were made to feel that they were not an integral part of the social life of the city. They were not welcomed to the social functions of Americans who were their equals in income and business position."1 As such, they needed a sense of belonging, so forming groups with their fellow countrymen who shared the same language and culture was a natural survival strategy and it continues for Shin Issei even today.
The first Japanese group, called "The Japanese Club", was formed in Chicago in 1892 with about twenty Japanese residents, to prepare for the 1893 Columbian Exhibition. Dr. Masuo Ikuta, assistant in the Chemistry Department at the University of Chicago2 was chosen as president, George Sasaki, a student of literature and Christianity, was chosen as secretary, and K. Nakayama, who would later to open the gift store "The Nippon" at 48 Adams between State and Wabash Streets for the Exhibition, was chosen as treasurer.3
Over the next 50 years, many groups and organizations were formed for the mutual benefit and welfare of Japanese Chicagoans, and some of them had a close relationship with the Japanese Consulate of Chicago, which was established in December 1897.
Japanese Christians formed the Japanese YMCA (Young Men's Christian Association) in 1908, the Japanese Mutual Aid Society of Chicago was established in 1910 under the guidance of the Japanese Consulate, and various Japanese business groups sprouted in the 1910s and 1920s, although many were short-lived. The Japanese Society of Chicago was formed in 1927 and a subcommittee helped with the Japan exhibit at the 1933 Chicago Fair, "A Century of Progress." The Chicago Business Club started in 1934, and finally, a new Japanese Mutual Aid Society was formed in 1935. All of these groups were interconnected, as their membership rosters overlapped over the years.
Charles Yasuma Yamazaki (Photo from Beikoku Nikkei-jin Hyakunen-Shi, page 1318).
Immediately after the Pearl Harbor attack in December 1941, the only surviving organization, the Japanese Mutual Aid Society, was ordered to cease all activities, not to collect dues, and not to congregate in groups of any more than three persons.4 In addition, the houses of several members of the Society, including Hidefumi Mukoyama and Masuto Kono, were searched by the FBI.5 However, actual arrests were made to only to three key members who were deeply involved with the Japanese Mutual Aid Society from the beginning: Charles Yasuma Yamazaki, president, Masuto Kono, one of the board members, and Shoji Osato, an agent of the Japan Travel Bureau, a subsidiary of the Japanese government.
Although their arrests could be seen as a natural consequence of the government's suspicious eyes on organizations with strong ties to Japan through the Japanese consulate (similar to what happened on the West Coast), what is peculiar about the Chicago Japanese was that they were arrested not once, but twice: in 1941 and 1943. Osato was arrested in December 1941, and Yamazaki and Kono were arrested in December 1943, after Osato was paroled in May 1943.
The difference in the timing of the arrests of these Chicago Japanese was possibly a result of their contact with the African American community, as seen in case of Eizo Yanagi, who was arrested twice and transferred every year from 1942-1946 to camps and detention centers under the Department of Justice. Did the Japanese Mutual Aid Society have suspicious contacts with African Americans in Chicago? If so, what kinds of contacts were made, and how were Yamazaki and Kono involved in those contacts? We must also remember that in 1943, race riots also occurred in June in Detroit, Michigan.
The Japanese Mutual Aid Society
The Japanese Mutual Aid Society was formed in January 1935, with Kenji Nakauchi, the Japanese consul, as honorary president. The Society had three main purposes: 1) to purchase centrally located cemetery lots; 2) to help pay final expenses of anyone who died without family or funds; and 3) to provide any necessary social services to the Japanese community in Chicago.6 The first office was located at 816 North Clark Street;6 these premises were occupied by a restaurant owned by Frank Yasunori Maruyama, treasurer of the Society. This restaurant had once been known as "Chicago Lunch," owned by Charles Yasuma Yamazaki.7 Yamazaki subsequently sold it to Maruyama in 1930, who was an employee at the restaurant.8
The Japanese Mutual Aid Society started out with more than 100 members, and the membership fee was 50 cents.9 Their first act was to start a fund drive for a Japanese cemetery; the Society purchased a lot at Montrose Cemetery in March 1935, completed the mausoleum, and had an unveiling ceremony on Memorial Day in 1938.10 With several Hawaiian-born Nisei members, including Isamu Tashiro, a dentist, and Paul Yoshio Kirimura, a pearl salesman,11 the Society incorporated under the laws of the State of Illinois in 1939.12
Japanese Mausoleum at Montrose Cemetery
The society's funds were left in the trust of the Japanese Consulate, and the signature of the consulate secretary was requiredat the time of any withdrawals, in order to protect the members of the Society.13 Accordingly, the Society maintained close working relations with the Japanese Consulate during the ensuing years.14
In fact, the Consulate became more politically influential over the Chicago Japanese and their associated groups after the Mukden incident in September 1931. The Japanese Society of Chicago started a fundraising drive to provide relief supply bags to Japanese soldiers in Manchuria, collected $669.62 with cooperation of various Japanese groups and sent it to the Japanese Army through the Consulate.15
After the Second Sino-Japanese War broke out in July 1937, activities of the Japanese Mutual Aid Society were more inclined to shadow the patriotism and nationalism seen during these times in Japan. The Society organized an emergency committee in August 1937 to help with home front responsibility from overseas. The committee had 25 members, including Yamazaki, Kono, Osato and Consul Masutani.16 According to Mayumi Hoshino,"While some Japanese Chicagoans seemed to unconditionally support their native land, some did not, disagreeing with much being done by the Japanese government, especially its military operations in Asia." 17 For example, it was reported to the consulate that a book titled Resistance and Founding of a State, a collection of lectures by Chiang Kai-shek and a pamphlet titled King (a collection of anti-war short essays, both of which were written in Japanese) were circulating among Japanese in Chicago.18 However, according to Hoshino, "Overall, the organization enthusiastically promoted strong external ties with the motherland and internal ties within the Japanese community of Chicago."19
What follows are just a few examples of fundraising drives by the committee: $964.25 in total from nearly 200 Japanese residents to send "relief funds" for Japanese soldiers in China in September 1937,20 $597.50 for an Asahi newspaper company campaign to help the Japanese government purchase a military aircraft in October 1937,21 and donations for Japanese soldiers' families in October 1938.22 In October 1939, Yamazaki, a life member of the Japanese Red Cross, announced a drive to recruit new members for the Japanese Red Cross, and more than sixty Japanese joined the organization.23
Japanese women also participated in patriotic fundraising drives. In February 1938, the Japanese Women's Club of Chicago, a Japanese language school, and a Japanese Christian Church all housed at 214 W. Oak St., started a drive to make and send "relief supply bags" to Japanese soldiers in China. With the money they collected, they made 350 bags and sent them to Japan.24 The bags were filled with necessities such as bath tissues, towels, soap, clothes, food, medications, photos, pictures and security blankets for fighting soldiers.25
In February 1940, another "relief supply bag" drive took place with the sponsorship of the Women's Club and support of the Japanese Mutual Aid Society.26 With Mrs. Ashino, wife of Consul General Ashino chairing the campaign,27 the Japanese wives of the Club and the Society collected $438.28, from which 539 bags were made. Other individuals made an additional 225 bags, and in total, 764 bags were sent to Japan through the Japanese Consulate.28 In return, a personal letter of appreciation, written by a soldier in South China and addressed to the Japanese Women's Club and the Japanese Mutual Aid Society, was received in September 1940.29
During the war, the Society also returned to one of their original purposes: to provide social services to the Japanese community in Chicago. Although they were forced to stop all regular activities, in June 1943, the Japanese Mutual Aid Society was able to organize the Mutual Service Center at 537 North Wells Street, a hostel for Japanese and Japanese Americans who were resettling in the Midwest from the various American concentration camps.30 Elmer Sherrill, Midwest Director of the War Relocation Authority, gave his hearty approval of the Society's efforts31 and the Police Department made no objection to the project.32 According to Yamazaki, the Society made a donation of $200, Frank Maruyama made a loan of $300 and Frank Fukuda, owner of a restaurant on North Clark Street, also made a loan of $350 to get the Center up and running.33
Although there were no actual officers at the Center, its policies and decisions were made by a committee consisting of Yamazaki, Kono, Mukoyama, Maruyama and Fukuda. A Japanese couple, Togawa and his wife, were the actual managers of the Center.34 The center had approximately thirty rooms and other accommodations for twenty more people. Sliding scale rates were charged in accordance with the person's ability to pay. Most of the hostellers stayed for a short period of time before finding permanent quarters and no profit was realized in the operation of the hostel.35 Despite the Japanese Mutual Aid Society's"pro-Japan" activities between 1937 and 1941, and the good-willed hostel program in summer 1943, Charles Yasuma Yamazaki was arrested on December 3, 1943.
Part 2 >>
1. Steiner, Jesse F, The Japanese Invasion: A Study in the Psychology of inter-Racial Contacts, Dissertation, University of Chicago, 1917, page 109.
2. Annual Register, 1892-1893, University of Chicago.
3.Chicago Tribune, Dec 11, 1892.
4. Bulletin of the Japanese Mutual Aid of Chicago 1934-1977, page 3, JASC Legacy Center Collection.
5. Ito, Shikago ni Moyu, page 215.
6. Bulletin of Japanese Mutual Aid of Chicago 1934-1977, page 2, JASC Legacy Center Collection.
7. 1923 Chicago City Directory.
8. Charles Yasuma Yamazaki file, WW II Alien Enemy Internment Case Files, 1941-1954, General Records of the Department of Justice, RG 60 Box 266, Case File # 100-7471, National Archives and Records Administration, College Park, Maryland.
9. Nichibei Jiho, February 9, 1935.
10. Bulletin of the Japanese Mutual Aid of Chicago 1934-1977, page 3, JASC Legacy Center Collection.
11. 1940 Census.
12. Nichibei Jiho, January 28,1939.
13. Nichibei Jiho, February 9, 1935; Yamazaki FBI File No 100-7471, RG 60, Box 266.
15. Nichibei Jiho, May 14, 1932.
16. Nichibei Jiho, October 2, 1937.
17. Hoshino, Mayumi, Strangers in the Heartland: Cultural Identity in Flux, Japanese Americans in Chicago, 1892-1942, Dissertation, Indiana University, 2012, page 244.
18. Report from Consul Ashino in Chicago to Nomura, January 12, 1940, Diplomatic Archives of the Ministry of Foreign Affairs of Japan, A-1-1-0-30_2_4_001.
19. Hoshino, page 235.
20. Nichibei Jiho, September 4 and October 2, 1937.
21.Nichibei Jiho, November 6, 1937.
22. Nichibei Jiho, November 5, 1938.
23. Nichibei Jiho, November 11, 1939.
24. Nichibei Jiho, April 16, 1938.
25. Nichibei Jiho, February 10, 1939.
28. Nichibei Jiho, March 30, 1940.
29. Nichibei Jiho, September 7, 1940.
31. Yamazaki FBI file No100-7471, RG 60, Box 266.
33. Yamazaki FBI File No 100-7471, RG 60, Box 266.
© 2019 Takako Day
charles yasuma yamazaki chicago japanese mutual aid society Pre-World War II
Takako Day
Takako Day, originally from Kobe, Japan, is an award-winning freelance writer and independent researcher who has published seven books and hundreds of articles in the Japanese and English languages. Her latest book, SHOW ME THE WAY TO GO HOME: The Moral Dilemma of Kibei No No Boys in World War Two Incarceration Camps is her first book in English.
Relocating from Japan to Berkeley in 1986 and working as a reporter at the Nichibei Times in San Francisco first opened Day's eyes to social and cultural issues in multicultural America. Since then, she has written from the perspective of a cultural minority for more than 30 years on such subjects as Japanese and Asian American issues in San Francisco, Native American issues in South Dakota (where she lived for seven years) and most recently (since 1999), the history of little known Japanese Americans in pre-war Chicago. Her piece on Michitaro Ongawa is born of her love of Chicago.
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Facebook shares cratered 18.4 per cent in early trading on Thursday after the social network reported a slight miss in its earnings call on Wednesday and warned of slower growth going forward as scrutiny over privacy affects both costs and revenue.
The share decline could wipe out over US$100 billion for Facebook investors, with Mark Zuckerberg's fortune set to plunge by around US$15 billion, according to media reports. Zuckerberg's net worth had tumbled from US$82.4 billion to US$63.6 billion on Wednesday evening, when Facebook shares were down 16 per cent, Forbes reported.
That caused Zuckerberg's rankings among the world's richest people to drop from fourth to eighth place in a matter of hours, a "record drop," according to Forbes.
Facebook shares started to dip after the company revealed it had narrowly missed its second quarter revenue target, but the plunge began after executives said that profit margins would plummet for several years due to the costs of improving privacy safeguards and slowing usage in the biggest advertising markets.
The second-quarter results were the first sign that a new European privacy law and a succession of privacy scandals involving Cambridge Analytica and other app developers have bit into Facebook's business. The company further warned that the toll would not be offset by revenue growth from emerging markets and Facebook's Instagram app, which has been more immune from privacy concerns.
If the share drop holds on Thursday, it would be Facebook's largest single-day decline, topping a 12 per cent decrease in July 2012.
Facebook had cautioned investors to expect a big jump in second-quarter costs because of efforts to address concerns about poor handling of users' privacy and to better monitor what users post. Total expenses in the second quarter surged to US$7.4 billion, up 50 per cent compared with a year ago.
The General Data Protection Regulation (GDPR) in the European Union also will cause a revenue drop. The new privacy law forced several changes to Facebook's privacy terms and sign-up process, leading a minority of users to opt for non-personalized ads, which tend to generate less revenue.
Facebook's daily active users in Europe declined by 3 million amid the new regulation. Worldwide daily user growth for Facebook's namesake service slid for its sixth straight quarter, bringing it to nearly 1.5 billion users in the second quarter.