text:
\section{Introduction}
\label{sec:1}
In recent years, with the rapid growth of different types of data on the Internet, Approximate Nearest Neighbor (ANN) search plays an increasingly important role in many application fields, such as information retrieval, data mining and computer vision \cite{zhu2017exploring,cao2017collective,DBLP:journals/tmm/ZhuHLHSZ17}. Due to the high computational efficiency and low storage cost, hashing has become one of the most popular technologies in ANN search \cite{xie2017dynamic,survey,DBLP:journals/tkde/ZhuSXC17,DBLP:journals/tnn/ZhuHLXS18}.

The basic idea of hashing is to learn the hash function for mapping high-dimensional data into the binary Hamming space while preserving the similarity structure of the original space \cite{survey,zhu2016learning,DBLP:conf/mm/LuZCLNZ19,DBLP:conf/sigir/Lu0CNZ19}. Many hashing-based methods are developed for uni-modal retrieval. Nevertheless, in the real world, data with the same semantic often appears with multiple modalities, such as image, text and video. To take advantage of the relationship between heterogeneous data, it is necessary to develop the Cross-Modal Hashing (CMH) \cite{CMFH,DCH,SCM,SePH,LSSH,xie2016online} in the ANN search. Specifically, in the cross-modal retrieval, the modality of the query is different from that of the retrieved data. In this paper, we mainly focus on two typical cross-modal retrieval tasks: image retrieves text (I2T) and text retrieves image (T2I) tasks.

Most existing CMH methods are based on hand-crafted features. The feature extraction and hash code learning are performed independently. This may limit the representation capability of the samples and thereby undermine the accuracy of the learned hash codes. Recently, the deep learning based hashing methods have developed the end-to-end deep learning architecture to learn feature representation and hash coding simultaneously. Deep Cross-modal Hashing (DCMH) \cite{DCMH} extends the traditional deep models to cross-modal retrieval. It performs the end-to-end learning framework with deep neural networks for each modality. Pairwise Relationship Guided Deep Hashing (PRDH) \cite{PRDH} integrates different pair-wise constraints to learn the similarities of hash codes from inter-modality and intra-modality. With deep learning, deep cross-modal hashing methods can capture the correlation across different modalities more effectively than the shallow learning methods.

In existing deep hashing frameworks, the hash codes from two different modalities of paired samples are compulsively set to be the same. Generally, they first learn the feature representation separately through the deep neural network for different modalities, and then minimize the loss between different modality features to establish the modality relations. The shortcoming of these deep CMH methods is that the complex relationship among multi-modal data cannot be fully captured by simply imposing constraints on the last layer of the neural network with multiple modalities.

In this paper, we propose a novel \emph{Fusion-supervised Deep Cross-modal Hashing} (FDCH) method.
Firstly, the outputs of the deep neural networks for all modalities are imported into the fusion network in pairs. The last layer of the fusion network with pair-wise embedding constraint directly outputs the unified hash codes. By this way, the complex correlation between multi-modal data can be captured more effectively, and the learned unified hash codes enhance the similarity between instances with the same semantic. Furthermore, in order to reduce the quantization error, FDCH directly learns the discrete unified hash codes without relaxing during the optimization. Secondly, we use the unified hash codes as the supervision to train modality-specific hash networks for encoding the out-of-sample data queries. Meanwhile, both pair-wise similarity information and classification information are exploited to train the discriminative hash networks under one stream framework. It enables the learned hash networks to preserve cross-modal similarity and keep semantic consistency simultaneously.

The main contributions of our work are summarized as:
\begin{itemize}
\item FDCH captures the complex correlation between  multi-modal data by inputting the feature representations of paired training samples into a fusion network. Two streams of heterogeneous modalities can be fused deeply. The learned unified hash codes could enhance the similarity between instances with the same semantic, and further supervise the training of the modality-specific hash networks for encoding the queries.
\item We train the modality-specific hash networks under one stream framework with the supervision of both pair-wise similarity information and classification information. Further, FDCH keeps the discrete nature of hash codes without relaxation in the optimization to reduce quantization errors. To the best of our knowledge, there is no similar work in the previous deep cross-modal hashing methods.
\end{itemize}

\section{Related Work}
\label{sec:2}
Cross-modal hashing has become an active research topic in literatures due to its high efficiency and low storage cost in cross-modal retrieval \cite{CMDVH,Shen2015Learning,DBLP:conf/mm/LiuNZCZY18,DBLP:journals/sigpro/LuZCSZ19}. Various techniques have been proposed for CMH. They can be roughly divided into two categories: unsupervised methods and supervised methods

Unsupervised hashing methods learn the hash codes and functions with only the paired unlabeled training samples. Inter-Media Hashing (IMH) \cite{IMH} finds a common Hamming space for learning hash functions, where inter-modality and intra-modality consistency are explored to produce hash codes. Linear Cross-Modal Hashing (LCMH) \cite{LCMH} learns the common space and hash functions by representing training samples from all modalities with lower dimensional approximations. It preserves the similarity of multimedia documents and reduces the time and space complexity. Collective Matrix Factorization Hashing (CMFH) \cite{CMFH} learns hash codes with collective matrix factorization during the offline phase. Latent Semantic Sparse Hashing (LSSH) \cite{LSSH} learns the latent semantic features through sparse coding and matrix factorization, and then maps them to a joint abstraction space to obtain the binary hash codes.

Supervised hashing methods achieve better results by exploiting semantic information to enhance correlation across different modalities.
Semantic Correlation Maximization (SCM) \cite{SCM} maximizes the correlation between different modalities by seamlessly integrating semantic label into the hashing learning for large-scale data. Semantics-Preserving Hashing (SePH) \cite{SePH} learns the semantics-preserving hash codes by minimizing the KL-divergence of derived probability distribution in the hamming space from that in semantic space. Discriminant Cross-modal Hashing (DCH) \cite{DCH} is proposed to jointly learn the binary codes, the linear classifiers and the hash functions.

The methods mentioned above are all shallow CMH methods based on hand-crafted features. Since the feature extraction and hash code learning processes are performed separately, they may not interact to further exploit the relationships among different modalities.
Recently, several works on deep CMH have been developed to perform cross-modal retrieval through the end-to-end learning architecture with deep neural networks \cite{DCMH,PRDH}.
Nevertheless, these methods are not able to fully capture the nonlinear correlation across different modalities to learn discriminative hash codes.

\section{The proposed approach}
\label{sec:3}
\subsection{Deep Framework Overview}
\label{sec:3.1}
 The basic deep framework of FDCH model is illustrated in  Figure \ref{fig:Figure1}. It consists of two components:

\textbf{\emph{Unified hash codes learning}}: There are three networks involved in this component: image network, text network and fusion network. For the design of the image network, we use the CNN-F network in \cite{Chatfield2014Return}. The original CNN-F model consists of eight layers: five convolutional layers $(conv1-conv5)$ and three fully-connected layers $(fc6-fc8)$.
For the text modality, we first represent each text sample as a vector with Bag-of-Word (BOW) representation, and then input the BOW vector into the text network with two fully-connected layers. In particular, the number of hidden nodes in the last fully-connected layer of the image and text network should be consistent.
For fusion network combines the outputs of image and text networks in pairs, it consists of two fully-connected layers. To obtain the unified hash codes, the second layer is designed as a hash layer $fch$ (with $k$ hidden nodes), and the activation function is an identity function.

\textbf{\emph{Modality-specific hash networks training}}: In order to learn the hash functions for encoding out-of-sample queries, we redesign the image and text networks for training modality-specific hash networks. In this component, the last fully-connected layers of the image and text networks are replaced with the hash layer $fch$ (with $k$ hidden nodes), the identity function is used as the activation function, the rest of the settings are the same as the above step

\subsection{Notations and Problem Formulation}
\label{sec:3.2}
Assume cross-modal dataset is $O = \left\{ {\left. {{o_i}} \right\}} \right._{i = 1}^n$ containing $n$ training sample pairs, where ${o_i} = \left( {{v_i},{t_i},{y_i}} \right)$. Correspondingly, $V = \left[ {{v_1},...,{v_n}} \right] \in {\mathbb{R}^{{d_v} \times n}}$ and $T = \left[ {{t_1},...,{t_n}} \right] \in {\mathbb{R}^{{d_t} \times n}}$ are image and text features, respectively. Let $Y = \left [{{y_1},...,{y_n}} \right] \in {\mathbb{R}^{{c} \times n}}$ denote label matrix for all training samples, and if $o_i $ belongs to the $j$-th class ${y_{ji}} = 1$, otherwise ${y_{ji}} = 0$. Given the label information, the pair-wise similarity matrix is defined as $S = \left\{ {\left. {{s_{ij}}} \right\}} \right.$, where ${s_{ij}} = 1$ when ${o_i}$ is semantically similar to ${o_j}$, otherwise ${s_{ij}}=0$. For multi-label datasets, we define ${s_{ij}} = 1$ if ${o_i}$ and ${o_j}$ have at least one same label, otherwise ${s_{ij}}=0$.

FDCH aims to learn compact $k$-bit binary code for each instance, and $B \in {\left\{ { - 1,1} \right\}^{k \times n}}$ is unified hash code matrix with the $i$-th column ${b_i} \in {\left\{ { - 1,1} \right\}^k}$. For two binary codes ${b_i}$ and ${b_j}$, the relationship between their Hamming distances $di{s_H}\left( {{b_i},{b_j}} \right)$ for evaluating similarity and their inner product $\left\langle {{b_i},{b_j}} \right\rangle $ is formulated as follows: $di{s_H}\left( {{b_i},{b_j}} \right) = \frac{1}{2}\left( {k - \left\langle {{b_i},{b_j}} \right\rangle } \right)$. Obviously, two binary codes with larger inner products have smaller Hamming distances. Therefore, we can use the inner product of different binary codes to quantify their similarity.
Given pair-wise similarity matrix $S = \left\{ {\left. {{s_{ij}}} \right\}} \right.$, the probability of ${s_{ij}}$ under the condition $B$ is defined as:
\begin{equation}
\small
\label{eq:1}
\begin{split}
p\left( {{s_{ij}}|B} \right) = \left\{ \begin{array}{l}
\sigma \left( {{\Psi _{ij}}} \right),{s_{ij}} = 1\\
1 - \sigma \left( {{\Psi _{ij}}} \right),{s_{ij}} = 0
\end{array} \right.
\end{split}
\end{equation}
where $\sigma \left( {{\Psi _{ij}}} \right) = \frac{1}{{1 + {e^{ - {\Psi _{ij}}}}}}$ is a sigmoid function, and ${\Psi _{ij}} = \frac{1}{2}\left\langle {{b_i},{b_j}} \right\rangle  = \frac{1}{2}b_i^T{b_j}$. Eq.(\ref{eq:1}) shows that samples with larger inner products should have higher probability of being similar, so it can measure the similarity of hash codes

\subsection{Unified Hash Codes Learning}
\label{sec:3.3}
Let $\mathop f\limits^ \sim  \left( {V;{\theta _v}} \right)$ denote the learned feature representation corresponding to the output of the image network, $\mathop g\limits^ \sim  \left( {T;{\theta _t}} \right)$ denote the learned text feature corresponding to the output of the text network. Given the output of the image and text networks, we can combine them with the nonlinear activation (tanh) function $t\left(  \cdot  \right)$ to get the input $Z = t\left( {} \right.\mathop f\limits^ \sim  \left( {V;{\theta _v}} \right) + \mathop g\limits^ \sim  \left( {T;{\theta _t}} \right)\left. {} \right)$ of the fusion network. Further, we define the output of the fusion network for all training as $H = h\left( {Z;{\theta _z}} \right) \in {\mathbb{R}^{K \times n}}$.
By jointly training the image network, text network and fusion network, our method nonlinearly transforms the paired training samples into powerful unified hash codes in this step.

Combining with the above analysis of similarity measure, the objective function for learning the unified hash codes can be defined as follows
\begin{equation}
\small
\label{eq:2}
\begin{split}
\begin{array}{l}
\mathop {\min }\limits_{B,{\theta _v},{\theta _t},{\theta _z}} L =  - \sum\limits_{i,j = 1}^n {\log p\left( {{s_{ij}}|B} \right)} \\
\qquad \qquad \qquad + \lambda \left\| {B - H} \right\|_F^2 + \eta \left\| {H\textbf{1}} \right\|_F^2\\
\qquad \qquad \qquad s.t.B \in {\left\{ { - 1,1} \right\}^{k \times n}},
\end{array}
\end{split}
\end{equation}
where the first term is a negative log likelihood function $-\sum\limits_{{s_{ij}} \in S} {\log p\left( {{s_{ij}}|B} \right)}  =  - \sum\limits_{{s_{ij}} \in S} {\left( {{s_{ij}}{\Phi _{ij}} - \log \left( {1 + {e^{{\Phi _{ij}}}}} \right)} \right)} $, and ${\Phi _{ij}} = \frac{1}{2}H_{ * i}^T{H_{ * j}}$. Besides, $\lambda $ and $\eta$ are hyper-parameters.
The first term is a pair-wise embedding constraint to preserve the semantic similarities in $S$. By minimizing the negative log likelihood function, it makes the similarity (inner product) between two similar samples as large as possible, and the similarity between dissimilar samples as small as possible. The second term minimizes the loss between outputs of the fusion network and binary hash codes, so that the learned unified hash codes can preserve the nonlinear correlations among training samples. The third term is a balance constraint to maximize the information of each hash bit. It requires each bit to have an equal opportunity to be coded to 1 or -1 for all training samples.

The optimization problem in Eq.(\ref{eq:2}) can be solved by using the iterative update strategy. Specifically, we can learn one variable while fix other variables alternatively. We learn unified hash codes $B$ and network parameters $\theta=\left\{ {{\theta _v},{\theta _t},{\theta _z}} \right\}$ as follows.

\textbf{\emph{Update $\theta $, with $B$ fixed}}: we adopt the mini-batch Stochastic Gradient Descent (SGD) to learn $\theta  = \left\{ {{\theta _v},{\theta _t},{\theta _z}} \right\}$. We first compute the gradient of the loss function in Eq.(\ref{eq:2})
\begin{equation}
\small
\label{eq:3}
\begin{split}
\begin{array}{l}
\frac{{\partial L}}{{\partial {H_{ * i}}}} = \frac{1}{2}\sum\limits_{j = 1}^n {\left( {\sigma \left( {{\Phi _{ij}}} \right){H_{ * j}} - {s_{ij}}{H_{ * j}}} \right)} \\
\qquad \quad + \frac{1}{2}\sum\limits_{j = 1}^n {\left( {\sigma \left( {{\Phi _{ji}}} \right){H_{ * j}} - {s_{ji}}{H_{ * j}}} \right)} \\
\qquad \quad + 2\lambda \left( {{H_{ * i}} - {B_{ * i}}} \right) + 2\eta H\textbf{1}
\end{array}
\end{split}
\end{equation}

Then we can obtain the gradients of each layer through the chain rule and update the parameters $\theta$ by Back Propagation (BP) \cite{hinton2006reducing} algorithm.

\textbf{\emph{Update $B$, with $\theta $ fixed}}: In the optimization process, we keep the discrete nature of unified hash codes $B$. When $\theta $ is fixed, we can obtain the following formulation
\begin{equation}
\small
\label{eq:4}
\begin{split}
\begin{array}{l}
\mathop {\max }\limits_B tr\left( {\lambda {B^T}H} \right) \ s.t. \ B \in {\left\{ { - 1,1} \right\}^{k \times n}}
\end{array}
\end{split}
\end{equation}

The hash codes ${B_{ij}}$ can be solved as
\begin{equation}
\small
\label{eq:5}
\begin{split}
B = \texttt{sign}\left( {\lambda H} \right)
\end{split}
\end{equation}
\subsection{Modality-specific Hash Networks Training}
\label{sec:3.4}
We have learned powerful unified hash codes for all training sample pairs through above steps. In this section, we train the image network $f\left( {V;{\theta _v}} \right)$ and text network $g\left( {T;{\theta _t}} \right)$ to obtain corresponding hash functions ${h^v}\left(  \cdot  \right)$ and ${h^t}\left(  \cdot  \right)$ for encoding out-of-sample queries.

Firstly, we adopt the inter-modal pair-wise embedding constraint preserve the cross-modal similarity between the outputs from image network hash and text hash network.
\begin{equation}
\small
\label{eq:6}
\begin{split}
{J_1} =  - \sum\limits_{i,j = 1}^n {\left( {{s_{ij}}{\Theta _{ij}} - \log \left( {1 + {e^{{\Theta _{ij}}}}} \right)} \right)}
\end{split}
\end{equation}
where ${\Theta _{ij}} = F_{ * i}^T{G_{ * j}}$.

Obviously, by optimizing the negative log likelihood of the pair-wise similarity $S$, the Hamming distance between two semantically similar samples can be reduced, while increasing the Hamming distance between semantically dissimilar samples.

Then, we use the high-quality hash codes learned before to supervise the training of modality-specific hash networks. By minimizing the loss function below, the nonlinear correlations embedded in $B$ are transmitted to hash networks $f\left( {V;{\theta _v}} \right)$ and $g\left( {T;{\theta _t}} \right)$. At the same time, the outputs of the last fully connected layer for two hash networks are forced to be close to the binary code.
\begin{equation}
\small
\label{eq:7}
\begin{split}
{J_2} = \left\| {B - F} \right\|_F^2 + \left\| {B - G} \right\|_F^2
\end{split}
\end{equation}

Although the pair-wise similarity information in Eq.(\ref{eq:6}) and the unified hash codes containing the nonlinear correlation in Eq.(\ref{eq:7}) have been used to learn the hash functions, the semantic label information is not fully exploited.

Next, we model the relationship between the hash networks and the label information. The trained hash networks of image and text are expected to be optimal for classification. We use the label information directly by linearly mapping it into modality-specific networks as follows
\begin{equation}
\small
\label{eq:8}
\begin{split}
\begin{array}{l}
{J_3} = \left\| {F - W_1^TY} \right\|_F^2 + \left\| {G - W_2^TY} \right\|_F^2 + \left\| {W_1^T} \right\|_F^2 + \left\| {W_2^\texttt{T}} \right\|_F^2
\end{array}
\end{split}
\end{equation}
where $W_1^\texttt{T} \in {\mathbb{R}^{k \times c}}$ and $W_2^\texttt{T} \in {\mathbb{R}^{k \times c}}$ are mapping matrices corresponding to image and text modalities, respectively.

Finally, we add the following balance constraints to maximize the information of each bit.
\begin{equation}
\small
\label{eq:9}
\begin{split}
\begin{array}{l}
{J_4} = \left\| {F\textbf{1}} \right\|_F^2 + \left\| {G\textbf{1}} \right\|_F^2
\end{array}
\end{split}
\end{equation}

Based on the analysis of the above four terms, the overall objective function is rewritten as follows
\begin{equation}
\small
\label{eq:10}
\begin{split}
\mathop {\min }\limits_{{\theta _v},{\theta _t}} J = {J_1} + \gamma {J_2} + \beta {J_3} + \alpha {J_4}
\end{split}
\end{equation}
where $\gamma $, $\beta $ and $\alpha $ are hyper-parameters to balance the importance of each terms.
\begin{table*}[]
\small
\caption{mAP comparison on MIRFLICKR-25K and NUS-WIDE. The best result is shown in boldface.}
\vspace{-3mm}
\centering
\resizebox{1.5\columnwidth}{!}{
\begin{tabular}{|p{25mm}<{\centering}|p{14mm}<{}|p{12mm}<{\centering}|p{12mm}<{\centering}|p{12mm}<{\centering}|p{12mm}<{\centering}|p{12mm}<{\centering}|p{12mm}<{\centering}|}
\hline
\multirow{2}{*}{Task}  &\multicolumn{1}{c|}{\multirow{2}{*}{Methods}}  &\multicolumn{3}{c|}{\textbf{MIRFLICKR-25K}}   &\multicolumn{3}{c|}{\textbf{NUS-WIDE}} \\ \cline{3-8}
& \multicolumn{1}{c|}{}                         & 16 bit     & 32 bit     & 64 bit     & 16 bit     & 32 bit     & 64 bit     \\ \hline \hline
\multirow{3}{*}{\begin{tabular}[c]{@{}c@{}} \\ \\  Image Query\\ v.s\\ Text Database\end{tabular}}
 & CMFH               & 0.5644       & 0.5648          & 0.5666          & 0.3384       & 0.3407          & 0.3452         \\ \cline{2-8}
 & LSSH               & 0.5950       & 0.6043          & 0.6117          & 0.4616       & 0.4606          & 0.4800          \\ \cline{2-8}
 & DCH                & 0.5991       & 0.6025          & 0.6009          & 0.4275       & 0.4402          & 0.4526          \\ \cline{2-8}
 & SCM                & 0.5821       & 0.5726          & 0.5672          & 0.3858       & 0.3744          & 0.3666          \\ \cline{2-8}
 & SePH$_{km}$        & 0.6534       & 0.6665          & 0.7277          & 0.6056       & 0.6223          & 0.6674          \\ \cline{2-8}
 & DCMH               & 0.7050       & 0.7194          & 0.7366          & 0.6195       & 0.6472          & 0.6721          \\ \cline{2-8}

 & FDCH              & \textbf{0.7762}       & \textbf{0.7877}         & \textbf{0.7897}     & \textbf{0.6861}       & \textbf{0.7003}         & \textbf{0.7139 }  \\ \hline \hline
\multirow{3}{*}{\begin{tabular}[c]{@{}c@{}}\\ \\ Text Query\\ v.s\\ Image Database\end{tabular}}
 & CMFH               & 0.5632       & 0.5631          & 0.5639          & 0.3377       & 0.3401          & 0.3424          \\ \cline{2-8}
 & LSSH               & 0.5893       & 0.5988          & 0.5950          & 0.4481       & 0.4464          & 0.4568          \\ \cline{2-8}
 & DCH                & 0.5804       & 0.5981          & 0.5968          & 0.4003       & 0.4179          & 0.4428          \\ \cline{2-8}
 & SCM                & 0.5976       & 0.5826          & 0.5724          & 0.3858       & 0.3708          & 0.3576          \\ \cline{2-8}
 & SePH$_{km}$        & 0.6135       & 0.6238          & 0.6768          & 0.5876       & 0.5747          & 0.6314          \\ \cline{2-8}
 & DCMH               & 0.7038       & 0.7048          & 0.7291          & 0.6147       & 0.6432          & 0.6651          \\ \cline{2-8}

 & FDCH              & \textbf{0.7504 }      &\textbf{0.7555 }       & \textbf{0.7552}     & \textbf{0.6518 }      & \textbf{0.6712}         & \textbf{0.6834 }     \\ \hline
\end{tabular}
}
\label{table2}
\vspace{-3mm}
\end{table*}

Similarly, for the optimization problem of Eq.(\ref{eq:10}), we can also solve it through the alternate learning strategy, which learns one parameter by fixing others. The process of alternately learning parameters $\theta _v$, $\theta _t$, $W_1$ and $W_2$ is as follows.

\textbf{\emph{Update $\theta_v $, with $\theta _t$, $W_1$ and $W_2$ fixed}}: The mini-batch SGD with BP algorithm is used to learn parameter $\theta _v$. For each instance ${{v_i}}$, we first derive the gradient of the loss function as follow
\begin{equation}
\small
\label{eq:11}
\begin{split}
\begin{array}{l}
\frac{{\partial J}}{{\partial {F_{ * i}}}} = \frac{1}{2}\sum\limits_{j = 1}^n {\left( {\sigma \left( {{\Theta _{ij}}} \right){G_{ * j}} - {s_{ij}}{G_{ * j}}} \right)}+ 2\gamma \left( {{F_{ * i}} - {B_{ * i}}} \right) \\
\qquad \quad+ 2\beta \left( {W_1^\texttt{T}{Y_{ * i}} - {F_{ * i}}} \right) + 2\alpha F\textbf{1}
\end{array}
\end{split}
\end{equation}

Then we can obtain the gradients of each layer through the chain rule and update the parameters $\theta_v $ by BP algorithm.

\textbf{\emph{Update $\theta_t $, with $\theta _v$, $W_1$ and $W_2$ fixed}}: Similarly, we learn parameter $\theta _t$ through the mini-batch SGD with BP algorithm. For each instance ${{v_t}}$, we compute the gradient of the loss function as follow
\begin{equation}
\small
\label{eq:12}
\begin{split}
\begin{array}{l}
\frac{{\partial J}}{{\partial {G_{ * j}}}} = \frac{1}{2}\sum\limits_{i = 1}^n {\left( {\sigma \left( {{\Theta _{ij}}} \right){F_{ * i}} - {s_{ij}}{F_{ * i}}} \right)}+ 2\gamma \left( {{G_{ * j}} - {B_{ * i}}} \right) \\
\qquad \quad + 2\beta \left( {W_2^\texttt{T}{Y_{ * j}} - {G_{ * j}}} \right) + 2\alpha G\textbf{1}
\end{array}
\end{split}
\end{equation}

Then we can obtain the gradients of each layer through the chain rule and update the parameters $\theta_t $ by BP algorithm.

\textbf{\emph{Update $W_1$, with $\theta _v$, $\theta_t $ and $W_2$ fixed}}: It is easy to solve parameter $W_1$ by the regularized least squares problem. We can get the following closed-form solution
\begin{equation}
\small
\label{eq:13}
\begin{split}
W_1 = \beta {\left( {Y{Y^\texttt{T}} + I} \right)^{ - 1}}Y{F^\texttt{T}}
\end{split}
\end{equation}

\textbf{\emph{Update $W_2$, with $\theta _v$, $\theta_t $ and $W_1$ fixed}}: The parameter $W_2$ can also be solved by the regularized least squares problem. It has a closed-form solution as follow:
\begin{equation}
\small
\label{eq:14}
\begin{split}
W_2 = \beta {\left( {Y{Y^\texttt{T}} + I} \right)^{ - 1}}Y{G^\texttt{T}}
\end{split}
\end{equation}

\subsection{Online Cross-modal Retrieval}
For a new query that is out of the retrieval database, we can easily obtain its hash code as long as one of its modalities is available. Specifically, given a query instance ${v_q}$ from the image modality, we use forward propagation of the image network to generate the hash code as follows
\begin{equation}
\small
\label{eq:15}
\begin{split}
b_q^v = {h^v}\left( {{v_q}} \right) = \texttt{sign}\left( {f\left( {{v_q};{\theta _v}} \right)} \right)
\end{split}
\end{equation}

Similarly, if a instance only has the text modality ${t_q}$, we can also use the text network to generate its hash code as:
\begin{equation}
\small
\label{eq:16}
\begin{split}
b_q^t = {h^t}\left( {{t_q}} \right) = \texttt{sign}\left( {g\left( {{t_q};{\theta _t}} \right)} \right)
\end{split}
\end{equation}

\section{Experiments}
\label{sec:4}

\subsection{Experimental Datasets}
\label{sec:4.1}
\textbf{MIRFLICKR-25K} \cite{Huiskes2008The} consists of 25,000 instances collected from Flickr website. In experiments, we select instances with at least 20 labels, which has 20,015 image-text pairs. Here, each textual modality is represented as a 1386-dimensional BoW vector. For image modality, we directly use raw pixels as input.

\textbf{NUS-WIDE} \cite{Chua2009NUS} is a real-world web image dataset containing 269,648 instances. In the experiment, we select the 10 most frequent concepts to construct a subset with 186,577 image-text pairs. For each image-text pair, the textual modality is represented by 1000-dimensional BoW vector, and the image modality directly uses the raw pixels as input.

In experiments, we randomly sample 2,000 instances as query and the rest as database (retrieval set). To reduce computational cost, similar to \cite{PRDH}, we randomly sample 5,000 instances from the database for training. After completing the training, we binarize the database samples into the hash codes and perform cross-modal retrieval.
\vspace{-4mm}
\begin{figure*}
\centering
\mbox{
\subfigure{\includegraphics[width=70mm]{flick_i2t32.pdf}
}\hspace{-4mm}\mbox{
\subfigure{\includegraphics[width=70mm]{flick_t2i32.pdf}
}
\mbox{
\subfigure{\includegraphics[width=70mm]{1flick_i2t64.pdf}
}\hspace{-4mm}\mbox{
\subfigure{\includegraphics[width=70mm]{1flick_t2i64.pdf}
}
\caption{\emph{Precision-Recall} curves on MIRFLICKR-25K.}
\label{fig:Figure2}
\vspace{-3mm}
\end{figure*}

\subsection{Experimental Settings}
\label{sec:4.2}
\textbf{Baselines}: In experiments, we compare our FDCH with six state-of-the-art cross-modal hashing methods.
They can be divided into two categories: LSSH \cite{LSSH}, CMFH \cite{CMFH} and DCH \cite{DCH} are supervised methods; SCM \cite{SCM}, SePH$_{km}$ \cite{SePH} and DCMH \cite{DCMH} are unsupervised methods. For fair comparison, at the $fc7$ from the initial CNN-F network used by our method, we extracted the CNN feature for the shallowed baselines.

\textbf{Implemental Details}: Our FDCH is implemented under the MatConvNet framework. For image network, we initialize the first seven layers using the CNN-F network pre-trained on the ImageNet dataset. All parameters for other deep neural networks in the FDCH model are randomly initialized.
For the text network with two fully-connected layers, we set the dimension as $[8192 \rightarrow 2500]$ on the MIRFLICKR-25K, and on the NUS-WIDE we set the dimension as $[8192 \rightarrow 1000]$ for 16 bits, and set to $[8192 \rightarrow 600]$ for 32 and 64 bits.
For the fusion network which combines the outputs of image and text networks in pairs, we set the dimension of its fully-connected layers as $[4096 \rightarrow k]$ on all datasets.\vspace{-4mm}
\subsection{Performance Comparisons}
\label{sec:4.3}
\begin{table}[]
\small
\caption{mAP scores of different variants of FDCH on MIRFLICKR-25K with 16-bit code length.}
\vspace{-1mm}
\centering
\resizebox{0.6\columnwidth}{!}{
\begin{tabular}{|c|l|l|l|l|}
\hline
\multicolumn{4}{|c|}{\emph{\textbf{MIRFLICKR-25K}}} \\ \hline
 \multirow{1}{*}{Task}         & FDCH      & FDCH-I         & FDCH-II   \\
 \hline\multirow{1}{*}{\begin{tabular}[c]{@{}c@{}}I $\rightarrow$ T\end{tabular}}
         & \textbf{0.7762}       & 0.7666         & 0.7379          \\
 \hline\multirow{1}{*}{\begin{tabular}[c]{@{}c@{}} T $\rightarrow$ I\end{tabular}}
         & \textbf{0.7504}       & 0.7310          & 0.6834          \\ \hline
\end{tabular}
}
\label{table1}
\vspace{-6mm}
\end{table}
\textbf{Hamming Ranking} \cite{DCMH}: Table \ref{table2} shows the mAP scores of our FDCH and the compared methods with CNN-F features on MIRFLICKR-25K and NUS-WIDE, respectively.
In the cross-modal retrieval task, LSSH, CMFH, SePH$_{km}$ and our FDCH both learn the unified hash codes. As can be seen from Table \ref{table2}, our method achieves the best performance for two different retrieval tasks on MIRFLICKR-25K. This is because our approach can effectively capture the correlation of multi-modal data through the nonlinear transformation from the fusion network. On the NUS-WIDE with complex semantic content, our FDCH also obtains superior performance compared to other methods, as shown in Table \ref{table2}. The results demonstrate that FDCH can fully exploit the label information to learn more discriminative hash code.

\textbf{Hash Lookup} \cite{DCMH}: Figure \ref{fig:Figure2} and \ref{fig:Figure3} show the precision-recall curves by Hash Lookup. We plot the precision-recall curve by varying the Hamming radius from 0 to $k$ with a step size of 1. Figure \ref{fig:Figure2} presents the precision-recall curves with 32 and 64 code lengths for different retrieval tasks on MIRFLICKR-25K. The precision-recall curves on NUS-WIDE are shown in Figure \ref{fig:Figure3}. It can be seen that the performance of our FDCH is significantly better than baselines.

Further, we design two variants of our method to evaluate the performance. FDCH-I ignores the classification information embedded in the modality-specific network. FDCH-II removes the pair-wise similarity constraint when training modality-specific hash network. Table \ref{table1} shows that the mAP scores of these variants are degraded. The results verify that it is effective to simultaneously embed pair-wise similarity and classification information in modality-specific network under one stream framework.\vspace{-4mm
\begin{figure*}
\centering
\mbox{
\subfigure{\includegraphics[width=70mm]{nus_i2t32.pdf}
}\hspace{-4mm}\mbox{
\subfigure{\includegraphics[width=70mm]{nus_t2i32.pdf}
}\hspace{-4mm}\mbox{
\subfigure{\includegraphics[width=70mm]{nus_i2t64.pdf}
}\hspace{-4mm}\mbox{
\subfigure{\includegraphics[width=70mm]{nus_t2i64.pdf}
}
\caption{\emph{Precision-Recall} curves on NUS-WIDE.}
\label{fig:Figure3}
\end{figure*}

\section{Conclusion}
\label{sec:5}
In this paper, we propose a novel Fusion-supervised Deep Cross-modal Hashing (FDCH) approach. Through a fusion network with paired samples as input, FDCH effectively explores the complex correlation between multi-modal data. The learned unified hash codes enhance the similarity between instances with the same semantic. Besides, both pair-wise similarity information and classification information are embedded in modality-specific hash networks under one stream framework, which simultaneously preserves cross-modal similarity and semantic consistency. Experiments demonstrate the superiority of FDCH compared with several state-of-the-art approaches.

\textbf{Acknowledgements.} The work is partially supported by the National Natural Science Foundation of China (Nos. 61772322, 61572298, 61802236, U1836216) and the Key Research and Development Foundation of Shandong Province (Nos. 2017GGX10117, 2017CXGC0703)

\footnotesize
\bibliographystyle{IEEEbib}

redpajama_set_name: RedPajamaArXiv


Morgan Bate is a English teacher in the American Language Center system of schools. Her love of travel has taken her to many places, most recently Morocco. Her professional life has wandered as much as her feet, and after finishing a degree in philosophy and literature she worked in project management and marketing strategy before becoming the country director in Morocco for the special internship program, Pro World Inc.


text:
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info@girvin.com
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mack@girvin.com
GIRVIN | Strategic Branding & Design | Seattle
GIRVIN | Strategic Branding & Design | New York
Brand Japan
by Tim Girvin | Brands, Concepts, General | Apr 17, 2010
Exploring brand dissolution in Japan: heritage, brand storytelling and emotional resonance in community
Working as a designer in Japan in the 80s, then the 90s, lead me to some extraordinary explorations, from the height of Japanese corporate design and the supremely modernistic sense of visualization and strategy, to the wabi sabi of centuries old Buddhist compounds and monasteries, to sharing stories with Japanese businessmen, at all hours of the late night and early morning bar hopping, to sitting and chatting with old fishermen and farmers in the future outreaches of the Japanese countryside.
The concept of story, cultural values, spirit principles and brand is deeply embedded in the heritage of Japanese strategy — and this sensitivity oftentimes informed the most serious of corporate business tactics. Still, Japan has inherently and consistently molded the brand development programs of the West with its own practices of cultural sensitivity. In working with top designers and brand strategists, for the highest ranked kabushiki gaisha I found ideas of development that were both comprehensible and relevant, to senses of design planning that were distinctly flavored with nihon character. This shift in stylistic legacy relates in part to the principle of heritage and family, since many of the most powerful brands of Japan are in fact ancient family associations — even samurai and commerce class legacies for hundreds of years. In Japan the use of crests (mon) is not, however, a privilege confined to persons of quality and distinction alone – anyone many have one. Unique, beautiful graphic symbols are the traditional Japanese "family crests" that are deeply rooted in the life of the Japanese people. Many families have their own crests handed down from generation to generation of the female members of a family, even after marriage, a woman was privileged to use her mother's crest — for decoration, equipage or their own distinct storytelling in memory.
This idea of identity is no "dead" cultural heritage. Family crests continue to play an important role in the complex Japanese society of today in many varied ways. The patterned principles of application are based on centuries-old family crests are often — in the explication of their heritage — are used as company symbols, trademarks, or as central themes for commerical posters and promotional productions.
To gather a sense of the length of application, it's worthy to note that Japanese crests and their development goes back to the 11th century when warriors started affixing flags and symbolic signs to their banners on the battlefield. Given their bloody, hard fought expression, after the battle and the warrior classes return home, they continued to use the signs as distinguishing marks of their families.
In later, peaceful times, the crest was worn as it still is, on the Japanese outer garment or kimono, in five places at the back of the neck, on each sleeves and each breast. Alternatively, sometimes only in three places – on the back and sleeves. The patterning application, the material for the kimono is dyed, a stencil of the crest is pasted on it and appears in white on the finished kimono. The implications of brand — and the family crest — marked many of the family possessions, such as their lacquerware, their traveling cases, rickshas, personal accouterments. Products followed — and similarly marked, to expand on provenance and family story in history.
There are about 200 basic crests and nearly 4,000 variations — and these are in many cases naturalistic in origin, based mostly on the designs of flowers, birds and animals. Other "product" expressions, like saké, textiles, metalwork, tools came to become "family brands." The highest level of "brand mark", in Japan — the most famous among the myriad of family crests still in use is the one having a 16-petalled chrysanthemum as its design — reserved as the emblem of the Imperial Family.
Still, even with this fascinating history, the idea of Japan Brands, Inc. has undergone serious challenges of late — particularly in the difficulties of Toyota. It's been pointed out that there is a discrepancy, over the course of the last decade, that has emphasized production and quota over the sensitivity of brand in story for consumer relationships.
According to the Financial Times, "faced with low growth at home, Japanese companies have viewed overseas sales as the route to improved profitability, which in turn has meant increasing capital expenditure to increase capacity. However, the focus on exports has caused the currency to appreciate, with the result that margins have narrowed, which in turn demands more sales to grow profits, which in turn demands more capex, with a vicious circle ensuing.
The drive to produce more — and more — has drawn resources away from other areas of corporate activity, with brand management one of the more significant areas of inattention. With all the classic Japanese household names, brand value in Japan is surprisingly low. Only seven Japanese brands appear in the Interbrand Global 100. An ironic component of recent events is that Toyota, which accounts for two of those seven brands (Toyota and Lexus), is one of the few Japanese companies to have had a strong brand. Empowered brand value is shown in both earnings growth and share price performance, with "Toyota one of only a handful of Japanese shares to hit all-time highs in the past five years. However, recent events have suggested that Toyota's brand is not as robust as management believed. Interbrand puts Toyota's brand value to sales at 16 per cent, half that of BMW's and below either Honda or Daimler, and roughly where it has been for a decade."
What I find interesting is the nature of the Japanese love of "other brands" — gaijin brando — and the challenges, now, for their own brand culture. In working on western brands, converted to eastern brands — the interest and acceptance of remote brand propositions, from Seattle's Best Coffee, to Louis Vuitton, the fascination with buying westernized objects — from the commonplace to the luxurious are compelling case studies in international marketing.
Still, in every instance, from Starbucks coffee culture to brand leaping and class jumping in the acquisition of branded luxury items, there is a necessity to build a special character that gestures to the inherent character of Japanese sensibilities. That works one way, but can the Japanese build that selfsame strategy for application to their own products and branded expressions? Kyocera, which found itself unable to translate a reputation for quality products in one area into sales in another, built their "One Company" campaign, which has engendered change. The brand is moving up the rankings. According to the Financial Times, "Kyocera has been able to allocate resources to branding, having slashed capex – from Y90bn in 2005 to about Y40bn this year."
It is going to take more than single strategic shifts to holistically alter the Japanese marketplace, which is why the bellwether company for study is Sony. For the last 10 years, its challenges have come to symbolize Japan's decline to "also-ran" status. The global financial crisis, which brought the company to its knees, "appears to have kickstarted a revolution in the group. Capex is being slashed, production is being outsourced to Taiwanese firms such as Compal, and a refocus on branding is taking place. It is a little too early to judge whether the rebranding is a success, but investors are going with it. Since the start of the year, Sony's share price is up 15 per cent." (Pelham Smithers) "Japanese companies are taking note. If they follow suit and execute successfully, corporate Japan may finally break out of its low-margin malaise and with it trigger sustainable interest in the equity market."
The nature of that return will be a renewal of the love of the brand — which, in a way, relates to the heritage of what brand storytelling, even familial alignment, can bring in building the legacy of brand, emotional resonance and market relevance to renewed heights of authentic connectivity.
Yes, noted — long sentence, but truth lies there, the Rising Sun.
tsg | decatur island
the reels: http://www.youtube.com/user/GIRVIN888
girvin blogs:
http://blog.girvin.com/
http://tim.girvin.com/Entries/index.php
girvin profiles and communities:
TED: http://www.ted.com/index.php/profiles/view/id/825
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WANDER. WONDER. WISDOM.
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The Symbolism of the X
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THE PRESENTATION AT FUTURE IN REVIEW | THE CONFERENCE: FIRE2018
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DESIGN AS A PORTAL | THE SYMBOLISM OF MAGICAL INTENT
Mary, Queen of Scots Movie Titling: It's No Hatchet Job
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BRAND MYSTICISM
Brands, Concepts, General | Apr 16, 2010
Drawing brand energy | the calligraphic stroke
Exploring the signature, brand story, the drawn line and den röda tråden I was working in Sweden, last week, with the CEO of a remarkable company, Hästens, and our discussions ranged around the nature of human experience -- from the spirit of sleep, rest and recovery, deep solace and quietude in the brand sentience of…
Finding Brand Soul | Seeking the heart of the brand experience
Brand core: what lies within? The idea of finding the soul of the brand is something that many might immediately chafe against, or laugh out loud -- the sheer presumption: brand = soul. But I'm finding that this is increasingly the place in which Girvin works, as well as the special exploration that I consider,…
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redpajama_set_name: RedPajamaCommonCrawl


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Subject: Doesn't anyone have it?!
our out of a commercial break, when the quarters start and end, during 'out of town scoreboard' clips, etc.
The song of which the theme has came from since '05 is 'Rise To Glory' by ES Posthumus. The song that that the theme came from from '03-'04 was 'Posthumus Zone' by ES Posthumus.
I would get Rise to Glory because I don't mind it, but I'd SO much prefer having the Rise to Glory instrumental.
BUT what i'm looking for isn't the direct instrumental from that rap song, because it isn't really what the NFL on CBS theme is. It isn't exactly that instrumental.
I've scoured through the 'Theme Music from NFL Primetime Highlights' thread over and over again and I still couldn't find it.
Now if someone could post the link from some sharing website or somethin, that would be awesome.


A must-read in formal and semi-formal verification!
This book is a result of my teaching mathematical programming to graduate students of the University of Delhi for over thirty years. In preparing this book, a special care has been made to see that it is self-contained and that it is suitable both as a text and as a reference.
In development scenarios where things can't be run in a debugger, or when you run the risk of masking the problem, logs are the greatest source of information about running a program. Pro Apache Log4j, Second Edition</i> provides best practices guidelines and comprehensive coverage of the most recent release.


To avail of the student rate you must provide proof of your student status at registration. ie Student card showing institution/student number/end date of student card. If proof is not provided then full fee will apply.


text:
by Jeff Eckert
Wings Over Mars
Artist's concept of the ARES marsplane. Courtesy of NASA.
ARES instrument layout. Courtesy of NASA.
A fascinating UAV-based concept is NASA's Aerial Regional-scale Environmental Survey of Mars (ARES) — a proposed Mars Scout mission. It is intended to extend the Mars exploration program by making measurements in three areas: crustal magnetism; atmospheric boundary layer composition, chemistry, and dynamics; and near-surface water. In operation, the autonomous powered airplane will be delivered in a protective "aeroshell," then released after entering the red planet's atmosphere. After separation, the wings and tail will unfold, and the aircraft will pull up and begin its mission.
The fun part is that NASA has made available a detailed flight simulator that allows the operator to program a mission and watch it progress. Available for both Windows and Mac OS X, you can download it at http://education.grc.nasa. gov/MarsFlight/ index.htm. But be patient. It takes up about 750 MB, so
both download and installation are slow. You can also get a pdf or jpg file that allows you to print, cut out, and fold your own scale model. Just visit http://marsairplane.larc. nasa.gov/platform.html.
Bot With An Appetite
Basic configuration of the EATR bot. Courtesy of Robot Technology, Inc.
While most bot designers agonize over how to provide enough power to keep the machinery running for extended periods, the Energetically Autonomous Tactical Robot (EATR), an ongoing program at Robotic Technology, Inc. (www. robotictechnologyinc.com), circumvents the problem by creating a biologically inspired bot that actually forages for its own food.
Much like a great white shark cruising the beach for tasty tourists, EATR "can find, ingest, and extract energy from biomass in the environment (and other organically-based energy sources), as well as use conventional and alternative fuels (such as gasoline, heavy fuel, kerosene, diesel, propane, coal, cooking oil, and solar) when suitable." According to the developer, it can travel about 100 miles on a meal of 150 lb of vegetation.
The system has four basic subsystems: an autonomous control system with sensors; a manipulator system (robot arm and end effectors); a hybrid engine system (external combustion engine that charges a battery); and a mobility platform
(either fully robotic or a modified standard automotive vehicle).
EATR is entering the proof-of-concept phase, which will focus on its ability to recognize edible biomass sources, ingest them, and generate electrical power. Phase 3 will lead to commercialization in several military and civilian areas. If you see one coming down the street, try not to look too delectable.
UAV Employs Fuel Cells
The Ion Tiger fuel cell powered UAV. Courtesy of the Office of Naval Research.
Beating the battery dilemma in a different way is the Ion Tiger UAV, under development at the Naval Research Lab ( www.nrl.navy.mil) in Washington, DC, for various surveillance missions. It tests a 500W hydrogen-powered polymer fuel cell design that allows it to carry heavier payloads over longer distances than earlier battery-powered designs. It also provides better stealth characteristics because of its small size, reduced noise, low heat signature, and total lack of emissions. The Tiger, which is slated for a trial flight soon, is expected to provide a 24 hour flight endurance with a 5 lb (2.7 kg) payload.
BMI Achieves Mind Over Matter
At the end of March, Honda
8 SERVO 06.2009


Sudsy Dough™ is an interactive bath toy that doubles as a moldable scented dough and a cleansing soap. Kids can squeeze and squish Sudsy Dough in the bath, rub it on as body wash, or take it outside the tub and make custom-shaped soaps that will dry when left out in open air. Sudsy Dough is scented and infused with moisturizing ingredients such as Shea Butter and beeswax. Each ball also has a surprise bath toy hidden inside! Available fragrances include Merry Mango, Sassy Strawberry, Awesome Apple, Bubbly Blueberry, and Blissful Blackberry.


Comes to life as impactful stories, products, experiences and engagement. Digital and IRL.
Enhances meaningful connection while helping brands be brave in trying different things. To get different results.
Draws on unique multidisciplinary synthesis from travel, fashion, retail and tech. To explore thinking and doing in creative ways.
Builds on cross disciplinary ideas and processes to resonate and engage users. Such as lifestyle storytelling and editorial ecommerce which fashion excels at applied to a tech product.
Big picture thinking connects the dots cohesively between visual storytelling, product design, brand and innovation strategy. My experience engaging in multifunctional roles creating, strategising and managing, from global companies to early stage startup and entrepreneurship, set the benchmark for multidisciplinary holistic approach. Nothing exists in silos.


text:
Winter classes set
The East Berlin Area Community Center, 405 North Ave., has announced some of its winter classes.
Creative Tots, a preschool class for ages 3-5, 9-11 a.m. Mondays, Jan. 4-Feb. 15. Cost: $50 per session.
Hatha Yoga, 6-7:30 p.m. Tuesdays and 9:30-11 a.m. Thursdays, Jan. 7-March 10. Cost: $55-$100 for sessions, $8 drop-in fee per class.
Kinder Ready Class for ages 3-5, 9 a.m.-noon or 9 a.m.-1 p.m. Mondays, Wednesdays and Fridays, Jan. 4-May 25. Cost: $110-$125 per week.
Tai Chi Chih classes, 6-7:30 p.m. Mondays, Jan. 11-Feb. 29. Cost: $80 for eight weeks. Registration: Jack Weaver, 676-0768.
For more information, call 259-8848, email info@ebacc.org or visit www.ebacc.org.


text:
Q: How to track event in Audit.Net with SqlDataProvider I'm trying to audit db actions using SqlDataProvider .
Global.asax.cs
                Audit.Core.Configuration.DataProvider = new SqlDataProvider()
        {
            ConnectionString =  "...",
            Schema = "dbo",
            TableName = "Event",
            IdColumnName = "EventId",
            JsonColumnName = "JsonData",
            LastUpdatedDateColumnName = "LastUpdatedDate",

            CustomColumns = new List<CustomColumn>()
        {

            new CustomColumn("EventType", ev => ev.EventType),
            new CustomColumn("ModuleName", ev => "AuditTrail")
        }
        };

if I add custom column like following
    new CustomColumn("StartDate", ev=>ev.StartDate),
    new CustomColumn("EndDate", ev=>ev.EndDate),
    new CustomColumn("Duration", ev=>ev.Duration),
    new CustomColumn("Target", ev=>ev.Target),
    new CustomColumn("Comments", ev=>ev.Comments),
    new CustomColumn("Environment", ev=> ev.Environment),

it throws an exception "No mapping exists from object type Audit.Core.AuditEventEnvironment to a known managed provider native type"
How can I track the event here.
Basically I want to insert jasonData field value into several fields.
Context Changes
    public override int SaveChanges()
    {
        return _helper.SaveChanges(_auditContext, () => base.SaveChanges());
    }

    public override async Task<int> SaveChangesAsync(CancellationToken cancellationToken = default(CancellationToken))
    {
        return await _helper.SaveChangesAsync(_auditContext, () => base.SaveChangesAsync(cancellationToken));
    }

A: It was an issue in data types.
The correct code should be
     Audit.Core.Configuration.DataProvider = new SqlDataProvider()
    {
        ConnectionString =  "...",
        Schema = "dbo",
        TableName = "Event",
        IdColumnName = "EventId",
        JsonColumnName = "JsonData",
        LastUpdatedDateColumnName = "LastUpdatedDate",

        CustomColumns = new List<CustomColumn>()
    {

        new CustomColumn("EventType", ev => ev.EventType),
        new CustomColumn("ModuleName", ev => "AuditTrail"),
        new CustomColumn("StartDate", ev=>Convert.ToDateTime(ev.StartDate)),
        new CustomColumn("EndDate", ev=>Convert.ToDateTime(ev.EndDate)),
        new CustomColumn("Duration", ev=>Convert.ToInt32(ev.Duration)),
    }
    };

We can add the following custom fields for some of the other details of the json data field.
    new CustomColumn("UserName", ev=> ev.Environment.UserName.ToString()),
    new CustomColumn("MachineName", ev=> ev.Environment.MachineName.ToString()),
    new CustomColumn("DomainName", ev=> ev.Environment.DomainName.ToString()),
    new CustomColumn("CallingMethod", ev=> ev.Environment.CallingMethodName.ToString()),
    new CustomColumn("DatabaseName", ev=> ev.GetEntityFrameworkEvent().Database.ToString()),

Since the entries of the json content is little bit different in insert and update, I'm still trying to separate data by the action.

redpajama_set_name: RedPajamaStackExchange


The employee wrote another memo earlier in the year which described Facebook as an "intolerant" "political monoculture," writing that "we claim to welcome all perspectives, but are quick to attack – often in mobs – anyone who presents a view that appears to be in opposition to left-leaning ideology." This drew comparisons to the equally controversial memo by Google employee James Damore, who was fired for writing a detailed and well-researched criticism of his company's internal intolerance and culture of unquestioning acceptance of leftist socio-biological narratives.
Amerige was previously at the center of a Facebook group called "FB'ers for Political Diversity," composed of some of the few conservative employees who were concerned with their company's unambiguous leftist bias.
Facebook was also part of a swathe of social media and tech companies, including Apple, Google, and Spotify, which coordinated about two months ago to de-person free speech advocate, conservative commentator, and patriot Alex Jones. The site also landed in hot water when it conducted a survey asking its audience if men should be allowed to ask children for pornographic content, fitting a larger pattern of a correlation between far-left bias and a disturbing acceptance of pedophilia.
With the recent leak of an internal Google memo "The Good Censor," embracing Orwellian censorship, rejection of free speech, and thought control, the time is running out for the political right to stand up to social media and tech giants such as Facebook. Amerige's conscientious departure is the latest in a frightening trend which, if not reversed immediately, threatens to have the result of right-wing voices and their supporters being excluded from the online public space and forum of ideas entirely.


Author and entrepreneur Jason Boreyko knows firsthand the challenges of starting a business. And more than anything, he knows how scary it can be; being your own boss and being responsible for the business and everyone in the organization can make anyone feel scared and uncertain. But with all the challenges and difficulties that all entrepreneurs will have to deal with, the rewards, both personal and professional, are incomparable.
Let's face it; you're the number one person standing in the way of your success. If you've been thinking about starting a business for years and you haven't done so yet, why? Fear, as mentioned, could be the main culprit. List down all your "fear factors." Make a list of what you think could go wrong and list down probable solutions for each one. If you can get past this hurdle, you'll be fired up to get down to business.
The problem with starting a business is that most aspiring entrepreneurs want to capture a big market right away. This might not be the best way to go about it. The way to get your business off the ground is to offer something special that either no one else has or is something far better and superior to what's already out there, says Jason Boreyko.
To put it in an analogy, don't offer an entire wardrobe if your specialty is sports apparel. Start small so you can catch the attention of the right market.
You may have already heard this numerous times, but it bears repeating: don't quit your day job. When you're still in the process of establishing your business, you will need a steady source of income and that means your job. When your business grows, gain more clients or customers, and as your finances become more stable, you can then decide on leaving your job to put all your attention on your growing business, advises Jason Boreyko.
One of the things that entrepreneurs will have to overcome is their shyness. You've got to be your business' best salesperson if you want your team and your customers to believe in what you're offering. There's simply no convincing others of how exceptional your product is if they don't hear it from you first.
In the end, your success in business all boils down to one unifying factor: you.
Stay tuned for more business tips from Jason Boreyko.


The introduction by Etihad Airways of a daily Abu Dhabi – Washington Dulles flight gave the opportunity for the airline's President and Chief Executive Officer, James Hogan, to address the International Aviation Club in its home city. COMMENT this week is a report on what he had to say.
Mr Hogan (57) is an Australian and prior to his present position (appointed September 2006) held a similar post at Gulf Air in nearby Bahrain.
James Hogan began his career in 1975 at Ansett Airlines, and subsequently held senior positions with the then British Midland Airways, Hertz and Forte Hotels.
Mr Hogan said that Etihad Airways' unique business model, which is a combination of organic growth, code-shares and minority equity investments, was proving very effective in building passenger numbers, revenue and profit for all its partners.
"The traditional airline alliances have evolved into slow-to-respond, bureaucratic organisations which struggle to deliver added value to their member airlines, many of which are no longer compatible with each other.
If we look at the consolidation currently occurring throughout the airline industry, we are also seeing more fragmentation within the alliances. This is going to continue as members seek ways to operate profitably in a very competitive environment with high fuel costs and generally slower global economic growth.
This month we will report our strongest ever first quarter results. Our codeshare and equity partners have made a major contribution to that financial success", Mr Hogan said.
Etihad Airways owns 29% of airberlin, 40% of Air Seychelles, 9%of Virgin Australia and just under three per cent of Aer Lingus. It has 42 code-share relationships around the world.
The airline posted a profit of US$42m in 2012 and saw two of its equity partners – airberlin and Air Seychelles – return to profitability, meaning that all five airlines are now in the black.
Mr Hogan said that Etihad Airways' equity alliance of minority shareholdings enabled the airline to enter markets within local foreign investment limits and, therefore, without the complexities, approvals or expense attached to mergers or larger investments.
"It is easier, faster and far more cost effective to grow through one-on-one partnerships with established, respected carriers than it is to rely totally on our own resources, and to start from scratch in every market we serve.
We have hand-picked like-minded partners with whom we can work collaboratively to build revenue across a broader network and reduce operating costs.
We focus on our partners' profitability as much as our own, because we are not dealing with competing interests. When the five CEOs sit down to make decisions, we have a shared commitment to make things happen", he said.
Mr Hogan said that because Etihad Airways had skin in the game it could go so much further than legacy alliances in thinking innovatively and building relationships that delivered ongoing value.
"An example of innovation is the way we are now working with our equity alliance partners to develop 'centres of excellence' in which operational and commercial expertise is pooled to deliver best practice across the group.
Cooperation includes fleet and engine acquisition, maintenance, recruitment and training. This is real value-add for our equity alliance and I am confident it is the way forward", Mr Hogan said.


20/04/2012�� You can use free office suite to view and edit Excel files on Android phone. Calculate and filter data, viewing chart in your Excel files. Calculate and filter data, viewing chart in your Excel files.
3/01/2019�� The only thing Excel on WP shares with Excel on the desktop is a common file format and some basic functionality. Other than that, totally different. The mobile version is missing pivot tables, tables, advanced graphing, drawing layer, conditional formatting, macros, a few dozen functions, etc.
If you prefer to export contacts from iPhone to CSV or Excel, go to the article about how to save iPhone contacts to CSV/Excel for the details. Step 1 : On your iPhone, go to Settings > [your name] > iCloud and toggle on the Contacts option.
You can easily edit your iPhone contacts in Excel using CopyTrans Contacts. This article demonstrates how to export your iPhone contacts to an Excel list, edit your contact list within Excel and then re-import the newly-edited contact list to your iPhone via CopyTrans Contacts.


For the first time since adopting our cat 18 months ago, we needed to go out of town. We placed our two dogs in a crate-free kennel and flew away, leaving Waldo in the care of a pet sitter. I realized not long before we left that Waldo had not been left alone–with neither dogs nor people–for any longer than four hours since coming to us from the Virginia Beach SPCA.
Therefore, because Waldo sleeps in our bed at night, I wanted to have someone stay at the house to sleep with him, to lessen the trauma I just knew he would suffer by our being gone. I gratefully received my daily text messages from Judy, with her notes and pictures of Waldo doing his normal things. I was still concerned about him, but did feel better.
Once home, though, I learned Judy had needed to go hunting for Waldo in the middle of the night. He had retreated to his own bed in our closet and was sound asleep–all by himself.
This entry was posted in Cats, Pet Care and tagged anthropomorphic, cat, dogs. cats, pet care, vacation, Virginia Beach SPCA by Cindy. Bookmark the permalink.


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Livecast
Alisha Peru
Muse Meets Pink Floyd - Android Superstation's Masterpiece Album: This Side of Nowhere
Wow; All I can say is, "Wow."
I have many submissions come across my desk here at Live and Amplified, but I rarely find an album that genuinely blows me away. Within the first few seconds of listening to Android Superstation's This Side of Nowhere, I knew that I was in for some kind of ethereal, galactic treat. Composed by members Danny Day Church (vocals, guitar), Heather Moore (keyboards, vocals), James Yan (bass guitar), and Marc Voss (drums), this Orange County progressive rock group is truly a diamond in the rough. I am so blessed to have become acquainted with their music and will most definitely follow them in the years to come. These are prodigy-level musicians who work in fluid flow with one another. Boasting emotional lyrics and vocals, beautifully moving bass lines, epic drums, wail-y Pink Floyd-like guitar solos, and Muse-level piano and keyboard runs, Android Superstation has it all.
This Side of Nowhere was produced by the members of Android Superstation and was recorded, mixed, and mastered at Hear No Evil studios in Orange County, California. Though the band has only been together since 2017, their talents boast otherwise. This Side of Nowhere took roughly two-and-a-half years to complete, and even includes a graphic novel as an extra element to listening (https://www.androidsuperstation.com/universe).
I got such an eerie, post-apocalyptic feeling while reading the graphic novel's Prologue and listening to the album at the same time. I highly recommend looking at this incredible piece of art; it has a lot to say.
Right off the bat, I hear so many subtle musical intricacies and ethereal vocal effects in This Side of Nowhere. I would genuinely love to see this band live (and would pay a fair amount of money to do so - even in a small local venue). This type of progressive genre beckons for fog machines and epic laser and mood lighting effects. Android Superstation boasts so much raw emotion. Please, please, do yourself a favor, and listen to this album.
Photo by Erin Elmassian
The first track on this project, "This Side of Nowhere," oscillates between quiet, smooth sections and more intense rock portions. I especially dig the breakdown at four minutes in. It's a killer way to add some diversity to the track, and I love the simplistic hits from the bass and synth, which perfectly line up with Voss' drum accents. As a bassist myself, I got particularly excited when I heard Yan switch back to a moving bass line (with octaves) at around 4:17. The backing vocals on "This Side of Nowhere" add the perfect touch to the piece, and I think that this is one hell of an opening tune.
"Alive" begins with a space-like transition section at the beginning of the track. Moore's piano work really reminds me of Muse in this piece. I love the drums early on in this song (Voss has a nice tom tone and a stellar cymbal sound, along with a sharp, crisp snare). Yan has the perfect, round bass tone, and the overall panning and vocal mixing is excellent (Hats off to you, Hear No Evil Studio!). This is some fantastic production work. It definitely makes me feel alive.
"After You" makes me feel like I am about to embark on Disney's Space Mountain. Moore does some BEAUTIFUL piano work here, and there is an extraordinary buildup as the song moves forward. "After You" would make a great concert starter, and I definitely said "wow" out loud while being swept up in this song. Moore is truly an incredible synth/piano player, and her classical piano training really shines through in this band. (Heather, please tell me that you own a keytar. You would rock it on stage.) I love Yan's especially low bass work in this song, and I don't even have words for the end of this track. Chills.
"Fractured" boasts some rad dirty tones in the bass and guitar. This track got my adrenaline going and heart beating a little faster. This was the song that I listened to while looking into Android Superstation's graphic novel. What a crazy feeling.
For all of you piano-lovers out there, "All There Is" contains a beautiful, emotional keyboard part. It is genuinely moving and pulls at the heart-strings (especially when Church's beautiful vocals come back in). This track makes me want to cry.
"Through The Darkness" is a nice touch to This Side of Nowhere. I really applaud Android Superstation's choice to break up the male vocals with some lovely female flair. I like the traditional organ sound and appreciate the fact that "Through The Darkness" is more simplistic than some of the other tracks that we have heard thus far. This simplicity gives listeners' ears a break. I love the ever-ascending synthesizer, and the crazy, descending piano scales. The out-of-the-ordinary astral sounds and unique choice of bass notes are a nice touch, too. This song is very progressive, yet the interesting choice of notes somehow still fit together in a way that works. The ending of this piece is epic and would make for a great addition to any movie soundtrack.
"Victorious" has some really hard-hitting drums starting at 0:56. This is my favorite drum track on the album. Nice work on the double bass pedal, Voss.
I love the synth parts that ascend and descend in "The Absence of Light." The way that we hear the top end coming through is really quite lovely. Church and Yan both chose complimentary guitar and bass tones that blend well together in this song. (I would love to know what pedals they are using.) Church's vocal "ooo's" are very Muse-like, and the cool "dripping" sound effects are a fun addition to the track.
"Faith" contains some drum hits early on that sound just like a heartbeat. I am infatuated with Church's acoustic guitar in this song because it is different and breaks up the "rock" feel that we have heard so much of. Moore's piano notes are tasteful and simple, and there is such a subtle build in this track (especially in drums). The left/right panning with the vocals (starting at around 4:00) is really great. I particularly like Moore's extra vocal part that comes through in only one ear.
I applaud the fact that the opening of "Collide" is only instrumental. Some stellar upper piano scales are going on, along with interesting clock-ticking and whisperings (creepy!). "Collide" is, in my opinion, the darkest track on This Side of Nowhere. I most definitely found myself looking over my shoulder while listening to this track with headphones on, and physically jumped when someone walked into my office. The section of "Collide" beginning at around 6:00 contains some awesome fuzz tones; this must have been a blast to record. There is such a good fade at the end of this track, and I love the cricket sounds and "pitter-patters" panned between the left and right headphones. Just a word of advice about this song, though: don't listen to it alone in the dark!
Finally, we come to "The Other Side." Even though I am typically a very hard rock type of listener, I was caught off guard by the fact that this closing piece ended up being my favorite track on the album. Church's simple acoustic guitar and vocals grabbed my attention, and at first, I was actually wondering if I was even listening to the same band! This entire song is relatively different from the rest of the songs on This Side of Nowhere. I absolutely love the lyrics, and they hit me right in the middle of my heart. This is precisely what good lyrics do. The clean guitar and bass tones are a nice break from the "fuzz" tones that we heard earlier on in the album, and the hi-hat sounds very clean in this track. Voss' drums have a nice balance between the highs, mids, and lows. I really get Pink Floyd vibes here, especially in the emotional, raw, and wailing guitar solo. "The Other Side" is an anthem and a ballad containing beautiful chord progressions. The more simplistic instrumental work allows listeners to really focus on what is being said, and the ending left me emotional, feeling as though Android Superstation was on a rocket ship, flying through space.
All in all, Android Superstation does not disappoint. Where the heck did this group come from? Their musicality is off the charts, and their unique sound effects are not cheesy or overdone (which is very difficult to do). There is so much good in this album; I can't possibly articulate all of it.
All I can say now is, "Wow."
Follow Android Superstation:
Website: www.androidsuperstation.com
Facebook: @androidsuperstation
Twitter: @a_superstation
Instagram: @androidsuperstation
YouTube: https://www.youtube.com/channel/UCEZLYIj05bYtx2HzooMMrEw
Spotify: https://open.spotify.com/artist/5ZYStEtmJ70t1HgLSfWoII?si=Go7dyvNDRxy8ZOj1nps6dg
www.alishaperu.com
Cover Photo: Erin Elmassian
liveandamplified
superstation
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8 Southern Arizona Musicians to Look Out For


Effective in 2013, the Health Care and Education Reconciliation Act of 20101 will subject some individuals to a 3.8% Medicare contribution tax on unearned income. This new tax will apply to single taxpayers with a modified adjusted gross income (MAGI) in excess of $200,000 and married taxpayers with a MAGI in excess of $250,000 if filing a joint return, or $125,000 if filing a separate return. The provision is contained in new Sec. 1411, Unearned Income Medicare Contribution. Congress added the provision as a means of raising revenue to pay for health care reform. It targets wealthier taxpayers, as can be seen by the thresholds at which the tax applies.
For most individuals, MAGI will be their adjusted gross income unless they are U.S. citizens or residents living abroad and have foreign earned income. The tax is equal to 3.8% of the lesser of net investment income or the amount by which MAGI exceeds the threshold.3 Continue reading article……………….


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Centurions stretching their way to shape this summer
By: Jeff Dubrof
KRIS file photo
St. John Paul II's football is utilizing yoga to prepare for the upcoming season.
For many teams, the summer is a time for off-season training, a time to hit the field for conditioning or head to the weight room to build up strength.
Football players at St. John Paul II High School are doing both but have added something unique to their regiment: yoga.
"Yoga is beneficial, 100%," Instructor Dyamond Brown said.
Head coach Andrew Leon is using their time on the mats as a change of pace.
"A lot of stuff you do in yoga is core strength, stretching and flexibility," Leon said. "We do a lot of banging around in the weight room so it is good to give the kids a chance to relax."
A football player's schedule is by no means light either. Starting with weights in the morning, class during the day and practice after school, yoga is providing a break from that grind.
"You go eight hours a week all year long," senior Lance Zuniga said, "Coming out here is nice to relax and reset your mind."
The yoga routine might be a break from the grueling stretch of weights and conditioning, but it is by no means easy for these players. Even six weeks into their program, they still find themselves struggling.
"There's a lot of different yoga positions that a lot of us are still working on," senior Dylan Olivarez said. "It is a lot more difficult than people think."
The team won't stop the yoga workouts once the season starts, Leon told me. They'll continue these workouts as a form of mental vacation.


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Lifting Lifestyle Content to the Next Level
Published: Thursday, April 16, 2020
At Family Features, we produce content on a wide variety of topics. From business and finance to health and education, lifestyle content comes in many shapes and forms. Now we have a new method of distributing it to editors and readers.
Our new Lifestyle Video Production & Distribution projects are easy, stress-free and provide visually appealing information for editors that put your brand's message out there for the world to see.
Put Readers at Ease with Helpful Content
Published: Thursday, March 26, 2020
Weeks into the COVID-19 pandemic, a great deal of uncertainty remains. In fact, it may seem that the only thing certain is how significantly COVID-19 has altered our way of life. These unprecedented times call for a new way of thinking about content, but savvy brands are adapting their strategies to connect with consumers in ways they never have before.
Play Hard, Work Harder in the Entertainment Capital of the World
Published: Friday, February 14, 2020
The NAHB International Builders' Show (IBS) attracts more than 1,400 exhibitors to Las Vegas as the largest annual light construction show in the world, which is why Family Features sent two staff members to this year's event.
Nancy Hanks and Lindsey Horstmann, two members of our sales team, took to the skies to connect with past, present and (hopefully) future clients in the city of lights and see their latest, in-demand products.
"Our goal at the show was to help the organizations connect with consumers," Hanks said. "We really wanted to seek out the consumer-facing brands and make them aware of our strategies and abilities. We wanted to show how we can support their brand awareness methods."


Play Ghostbusters Games on Emulator Online. All the best Ghostbusters games online for different retro emulators including GBA, Game Boy, SNES, Nintendo and Sega. There are many online Ghostbusters games in the collection. All of the games that you see here are without download, pick any and start playing right away. If you enjoy the game, be sure to vote for it and leave a comment. Ghostbusters games that started it all back in the day are now playable within your browser! Start by playing some popular Ghostbusters online games like New Ghostbusters 2, GhostBusters, Ghostbusters and Extreme Ghostbusters.


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PCOM Library / Archive for "Uncategorized"
Jackie Werner August 21, 2019 Alternative and Complementary Medicine, Hot Topics in Research, Uncategorized
Characteristics and Components of Medical Group Visits for Chronic Health Conditions: A Systematic Scoping Review
Parikh M, Rajendran I, D'Amico S, Luo M, Gardiner P. Characteristics and components of medical group visits for chronic health conditions: A systematic scoping review. The Journal of Alternative and Complementary Medicine. 2019;25(7):683-698. https://doi.org/10.1089/acm.2018.0524.
Objectives: Chronic health conditions are a major challenge to the health care system. Medical Group Visits (MGVs) are a valuable health care delivery model used in a variety of medical settings and patient populations. We conducted a systematic scoping review of MGV research literature for chronic health conditions to summarize the characteristics and individual components of MGVs in the United States of America and Canada.
Design: We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses scoping review methodology and searched five databases using nine widely used MGV-related terms.
Subjects: We included studies conducted in the United States and Canada, whose participants were >18 years old and attended an MGV conducted in a medical setting by a billable health care provider. We excluded groups related to diabetes, pregnancy, and cancer.
Results: Of 3777 studies identified, we found 55 eligible studies of which 9 are randomized controlled trials and 46 are observational studies. The majority of studies were conducted in academic medical centers, were observational in design, and recruited patients using physician referrals. The three most frequently studied groups include a combination of several chronic conditions (n = 12), chronic pain conditions (n = 10), and cardiovascular disease (n = 9). Curriculum components included didactics (n = 55), experiential activities (n = 27), and socializing components (n = 12). Didactic areas include (1) medical topics such as symptoms management (n = 27) of which 14 included pain management, and (2) lifestyle/educational component (n = 33) that comprised of talks on nutrition (n = 29), exercise (n = 20), stress (n = 16), and sleep (n = 10). The top integrative medicine (IM) modalities (n = 13) included: mindfulness techniques (n = 8), meditation (n = 6), and yoga (n = 5). Substantial heterogeneity was observed in the recruitment, implementation, curriculum components, and outcomes reported.
Conclusion: The MGV is a model of patient-centered care that has captured the attention of researchers. IM modalities are well represented in the curriculum components of MGVs. Further investigation into the components identified by this study, may help in better targeting of group interventions to patients and contexts, where it is most likely to be effective.
Hot Topics: Spinal Surgery "Enhanced Recovery" Cuts Opioid Use
Jackie Werner February 20, 2019 Hot Topics in Research, Neurosurgery, Substance Use Disorders, Surgery, Uncategorized
Enhanced recovery after elective spinal and peripheral nerve surgery: pilot study from a single institution
Ali ZS, Flanders TM, Ozturk AK, et al. Enhanced recovery after elective spinal and peripheral nerve surgery: Pilot study from a single institution. Journal of Neurosurgery: Spine SPI. 2019:1-9. https://dx.doi.org/10.3171/2018.9.SPINE18681.
Enhanced recovery after surgery (ERAS) protocols address pre-, peri-, and postoperative factors of a patient's surgical journey. The authors sought to assess the effects of a novel ERAS protocol on clinical outcomes for patients undergoing elective spine or peripheral nerve surgery.
The authors conducted a prospective cohort analysis comparing clinical outcomes of patients undergoing elective spine or peripheral nerve surgery after implementation of the ERAS protocol compared to a historical control cohort in a tertiary care academic medical center. Patients in the historical cohort (September–December 2016) underwent traditional surgical care. Patients in the intervention group (April–June 2017) were enrolled in a unique ERAS protocol created by the Department of Neurosurgery at the University of Pennsylvania. Primary objectives were as follows: opioid and nonopioid pain medication consumption, need for opioid use at 1 month postoperatively, and patient-reported pain scores. Secondary objectives were as follows: mobilization and ambulation status, Foley catheter use, need for straight catheterization, length of stay, need for ICU admission, discharge status, and readmission within 30 days.
A total of 201 patients underwent surgical care via an ERAS protocol and were compared to a total of 74 patients undergoing traditional perioperative care (control group). The 2 groups were similar in baseline demographics. Intravenous opioid medications postoperatively via patient-controlled analgesia was nearly eliminated in the ERAS group (0.5% vs 54.1%, p < 0.001). This change was not associated with an increase in the average or daily pain scores in the ERAS group. At 1 month following surgery, a smaller proportion of patients in the ERAS group were using opioids (38.8% vs 52.7%, p = 0.041). The ERAS group demonstrated greater mobilization on postoperative day 0 (53.4% vs 17.1%, p < 0.001) and postoperative day 1 (84.1% vs 45.7%, p < 0.001) compared to the control group. Postoperative Foley use was decreased in the ERAS group (20.4% vs 47.3%, p < 0.001) without an increase in the rate of straight catheterization (8.1% vs 11.9%, p = 0.51).
Implementation of this novel ERAS pathway safely reduces patients' postoperative opioid requirements during hospitalization and 1 month postoperatively. ERAS results in improved postoperative mobilization and ambulation.
Hot Topics: Current Patient Engagement Measures Fall Short
Jackie Werner November 28, 2018 Family Medicine, Hot Topics in Research, Uncategorized
How do healthcare professionals working in accountable care organisations understand patient activation and engagement? Qualitative interviews across two time points
Mishra MK, Saunders CH, Rodriguez HP, Shortell SM, Fisher E, Elwyn G. How do healthcare professionals working in accountable care organisations understand patient activation and engagement? Qualitative interviews across two time points. BMJ Open. 2018;8(10). http://dx.doi.org/10.1136/bmjopen-2018-023068
Objective If patient engagement is the new 'blockbuster drug' why are we not seeing spectacular effects? Studies have shown that activated patients have improved health outcomes, and patient engagement has become an integral component of value-based payment and delivery models, including accountable care organisations (ACO). Yet the extent to which clinicians and managers at ACOs understand and reliably execute patient engagement in clinical encounters remains unknown. We assessed the use and understanding of patient engagement approaches among frontline clinicians and managers at ACO-affiliated practices.
Design Qualitative study; 103 in-depth, semi-structured interviews.
Participants Sixty clinicians and eight managers were interviewed at two established ACOs.
Approach We interviewed healthcare professionals about their awareness, attitudes, understanding and experiences of implementing three key approaches to patient engagement and activation: 1) goal-setting, 2) motivational interviewing and 3) shared decision making. Of the 60 clinicians, 33 were interviewed twice leading to 93 clinician interviews. Of the 8 managers, 2 were interviewed twice leading to 10 manager interviews. We used a thematic analysis approach to the data.
Key results Interviewees recognised the term 'patient activation and engagement' and had favourable attitudes about the utility of the associated skills. However, in-depth probing revealed that although interviewees reported that they used these patient activation and engagement approaches, they have limited understanding of these approaches.
Conclusions Without understanding the concept of patient activation and the associated approaches of shared decision making and motivational interviewing, effective implementation in routine care seems like a distant goal. Clinical teams in the ACO model would benefit from specificity defining key terms pertaining to the principles of patient activation and engagement. Measuring the degree of understanding with reward that are better-aligned for behaviour change will minimise the notion that these techniques are already being used and help fulfil the potential of patient-centred care.
Hot Topics: Mass Spectroscopy "Cancer Pen" Could Quickly Detect Tumors
Jackie Werner October 4, 2017 Hot Topics in Research, Oncology, Uncategorized
Nondestructive tissue analysis for ex vivo and in vivo cancer diagnosis using a handheld mass spectrometry system
Zhang J, Rector J, Lin JQ, et al. Nondestructive tissue analysis for ex vivo and in vivo cancer diagnosis using a handheld mass spectrometry system. Science Translational Medicine. 2017;9(406). http://dx.doi.org/10.1126/scitranslmed.aan3968
Conventional methods for histopathologic tissue diagnosis are labor- and time-intensive and can delay decision-making during diagnostic and therapeutic procedures. We report the development of an automated and biocompatible handheld mass spectrometry device for rapid and nondestructive diagnosis of human cancer tissues. The device, named MasSpec Pen, enables controlled and automated delivery of a discrete water droplet to a tissue surface for efficient extraction of biomolecules. We used the MasSpec Pen for ex vivo molecular analysis of 20 human cancer thin tissue sections and 253 human patient tissue samples including normal and cancerous tissues from breast, lung, thyroid, and ovary. The mass spectra obtained presented rich molecular profiles characterized by a variety of potential cancer biomarkers identified as metabolites, lipids, and proteins. Statistical classifiers built from the histologically validated molecular database allowed cancer prediction with high sensitivity (96.4%), specificity (96.2%), and overall accuracy (96.3%), as well as prediction of benign and malignant thyroid tumors and different histologic subtypes of lung cancer. Notably, our classifier allowed accurate diagnosis of cancer in marginal tumor regions presenting mixed histologic composition. Last, we demonstrate that the MasSpec Pen is suited for in vivo cancer diagnosis during surgery performed in tumor-bearing mouse models, without causing any observable tissue harm or stress to the animal. Our results provide evidence that the MasSpec Pen could potentially be used as a clinical and intraoperative technology for ex vivo and in vivo cancer diagnosis.
Hot Topics: Peer-Reviewed Blog Introduces New Medical Researchers to Publishing
Jackie Werner February 22, 2017 Hot Topics in Research, Research Commentary, Uncategorized
Coached Peer Review: Developing the Next Generation of Authors
Sidalak D, Purdy E, Luckett-Gatopoulos S, Murray H, Thoma B, Chan TM. Coached peer review: Developing the next generation of authors. Academic Medicine. 2017;92(2):201-204. http://dx.doi.org/10.1097/ACM.0000000000001224.
Publishing in academic journals is challenging for learners. Those who pass the initial stages of internal review by an editor often find the anonymous peer review process harsh. Academic blogs offer alternate avenues for publishing medical education material. Many blogs, however, lack a peer review process, which some consumers argue compromises the quality of materials published.
CanadiEM (formerly BoringEM) is an academic educational emergency medicine blog dedicated to publishing high-quality materials produced by learners (i.e., residents and medical students). The editorial team has designed and implemented a collaborative "coached peer review" process that comprises an open exchange among the learner–author, editors, and reviewers. The goal of this process is to facilitate the publication of high-quality academic materials by learner–authors while providing focused feedback to help them develop academic writing skills.
The authors of this Innovation Report surveyed (February–June 2015) their blog's learner–authors and external expert "staff" reviewers who had participated in coached peer review for their reactions to the process. The survey results revealed that participants viewed the process positively compared with both traditional journal peer review and academic blog publication processes. Participants found the process friendly, easy, efficient, and transparent. Learner–authors also reported increased confidence in their published material. These outcomes met the goals of coached peer review.
CanadiEM aims to inspire continued participation in, exposure to, and high quality production of academic writing by promoting the adoption of coached peer review for online educational resources produced by learners.
Prostate cancer discovery may make it easier to kill cancer cells
PJ Grier January 5, 2016 Hot Topics in Research, Oncology, Prostate, Uncategorized
Checkpoint Kinase 2 Negatively Regulates Androgen Sensitivity and Prostate Cancer Cell Growth
Prostate cancer is the second leading cause of cancer death in American men, and curing metastatic disease remains a significant challenge. Nearly all patients with disseminated prostate cancer initially respond to androgen deprivation therapy (ADT), but virtually all patients will relapse and develop incurable castrationresistant prostate cancer (CRPC). A high-throughput RNAi screen to identify signaling pathways regulating prostate cancer cell growth led to our discovery that checkpoint kinase 2 (CHK2) knockdown dramatically increased prostate cancer growth and hypersensitized cells to low androgen levels. Mechanistic investigations revealed that the effects of CHK2 were dependent on the downstream signaling proteins CDC25C and CDK1. Moreover, CHK2depletion increased androgen receptor (AR) transcriptional activity on androgen-regulated genes, substantiating the finding that CHK2 affects prostate cancer proliferation, partly, through the AR. Remarkably, we further show that CHK2 is a novel ARrepressed gene, suggestive of a negative feedback loop between CHK2 and AR. In addition, we provide evidence that CHK2 physically associates with the AR and that cell-cycle inhibition increased this association. Finally, IHC analysis of CHK2 in prostate cancer patient samples demonstrated a decrease in CHK2 expression in high-grade tumors. In conclusion, we propose that CHK2 is a negative regulator of androgen sensitivity and prostate cancer growth, and that CHK2 signaling is lost during prostate cancer progression to castration resistance. Thus, perturbing CHK2 signaling may offer a new therapeutic approach for sensitizing CRPC to ADT and radiation.
Cancer Research. 12/1/2015, Vol. 75 Issue 23, p5093-5105. 13p.
Non-lethal Inhibition of Gut Microbial Trimethylamine Production for the Treatment of Atherosclerosis
PJ Grier Cardiology, Hot Topics in Research, Uncategorized
Non-lethal Inhibition of Gut
Trimethylamine (TMA) N-oxide (TMAO), a gut-microbiota-dependent metabolite, both enhances atherosclerosis in animal models and is associated with cardiovascular risks in clinical studies. Here, we investigate the impact of targeted inhibition of the first step in TMAO generation, commensal microbial TMA production, on diet-induced atherosclerosis. A structural analog of choline, 3,3-dimethyl-1-butanol (DMB), is shown to non-lethally inhibit TMA formation from cultured microbes, to inhibit distinct microbial TMA lyases, and to both inhibit TMA production from physiologic polymicrobial cultures (e.g., intestinal contents, human feces) and reduce TMAO levels in mice fed a high-choline or L-carnitine diet. DMB inhibited choline diet-enhanced endogenous macrophage foam cell formation and atherosclerotic lesion development in apolipoprotein e−/− mice without alterations in circulating cholesterol levels. The present studies suggest that targeting gut microbial production of TMA specifically and non-lethal microbial inhibitors in general may serve as a potential therapeutic approach for the treatment of cardiometabolic diseases. •Gut microbial trimethylamine lyases are a therapeutic target for atherosclerosis•3,3-dimethyl-1-butanol inhibits microbial trimethylamine formation•3,3-dimethyl-1-butanol attenuates choline diet-enhanced atherosclerosis•Non-lethal gut microbial enzyme inhibition can impact host cardiometabolic phenotypes Drugging the gut microbiota with a non-lethal inhibitor that blocks production of the metabolite trimethylamine reduces the formation of atherosclerotic lesions and represents the first step toward treatment of cardiometabolic diseases by targeting the microbiome.
Cell 17 December 2015 163(7):1585-1595