---
abstract: 'Neural network pruning is an important technique for creating efficient machine learning models that can run on edge devices. We propose a new, highly flexible approach to neural network pruning based on Gibbs distributions. We apply it with Hamiltonians that are based on weight magnitude, using the annealing capabilities of Gibbs distributions to smoothly move from regularization to adaptive pruning during an ordinary neural network training schedule. This method can be used for either unstructured or structured pruning, and we provide explicit formulations for both. We compare our proposed method to several established pruning methods on ResNet variants and find that it outperforms them for unstructured, kernel-wise, and filter-wise pruning.'
author:
-
-
bibliography:
- 'mybibfile.bib'
title: 'A Framework for Neural Network Pruning Using Gibbs Distributions\'
---

neural networks, neural network pruning, edge intelligence, machine learning

Introduction {#sec:introduction}
============

While machine learning research has recently focused on massive deep neural networks, practical deployment of these powerful models on edge devices remains a challenge. One approach to making machine learning for edge intelligence more feasible is neural network pruning, where connections in a neural network are removed to produce a smaller final model. Pruning can be used on its own to improve inference performance and compress models, or it can be combined with other techniques like quantization to produce even more efficient neural networks [@han2016deep].

Neural network pruning methods can be divided into structured and unstructured pruning. In unstructured pruning, any set of connections can be removed. Structured pruning instead requires that the pruned connections follow some structure, such as removing entire rows from weight matrices or entire filters from convolutional layers. Structured pruning can usually improve performance metrics like inference speed at lower sparsity levels than unstructured pruning, since the structure can be taken advantage of in optimization [@wen2016learning]. On the other hand, unstructured pruning can generally remove more connections without significantly decreasing accuracy, even finding architectures that outperform the original model [@frankle2019lottery].

We introduce a novel pruning method that can be used for both unstructured and structured pruning. Taking inspiration from statistical physics, we propose inducing a Gibbs distribution over the weights of a neural network and sampling from it during training to determine pruning masks. This procedure induces a learned network structure that is resilient to high degrees of pruning. Gibbs distributions are highly flexible in terms of network properties that they can express, and quadratic energy functions, such as Ising models, can capture parameter interactions and induce desired structure in pruning masks. They also naturally allow a temperature parameter to be used for annealing, gradually converging to a final pruning mask during training and improving network resilience to pruning.

Many existing pruning methods start with a trained network and use an iterative procedure that alternates between removing some connections and training for additional epochs to fine-tune the network [@han2016deep; @li2017pruning; @luo2017thinet]. We believe that it is preferable to prune the network during the original training phase, since this allows the network and the pruning mask to adapt to each other, in particular encouraging the network to take on a representation that is robust to pruning. We show that our method can take advantage of additional training epochs by stretching the annealing and learning rate schedules rather than adding a separate fine-tuning phase. We compare our proposed method to a number of structured and unstructured pruning methods from the literature, including methods that fine-tune trained networks and methods that prune while training [@han2016deep; @frankle2019lottery; @gomez2019learning; @li2017pruning; @luo2017thinet]. We generally find that our method outperforms them.

Sample code for our proposed method is available at <https://github.com/j201/gibbs-pruning>.

Proposed Method {#sec:method}
===============

A Gibbs distribution over a vector $\x$ has a density function $$p(\x) = \frac{1}{Z(\beta)}e^{-\beta H(\x)},
    \label{eq:gibbs}$$ where $H(\x)$ is the Hamiltonian function, or [*energy*]{}, $\beta$ is an inverse temperature parameter, and $Z(\beta)$ is a partition function that normalizes the distribution. Gibbs distributions are a very general family of probability distributions, giving considerable flexibility in defining pruning methods. For instance, every Markov random field corresponds to a Gibbs distribution, and vice versa. They also naturally permit annealing, by changing $\beta$ over the course of training.

In our proposed method, $\x$ represents a pruning mask for a single neural network layer, with $x_i \in \{-1,1\}$. Given the weights of the layer as a flattened vector $\w$, a weight $w_i$ is masked (treated as zero) during training if the corresponding $x_i$ is -1. $\x$ is sampled from $p(\x)$ at every training step and once again after training to determine the final mask. Note that weight values are not permanently modified during training, allowing a connection to be masked out in some iterations and active in others.

The goal of our method is to have both the neural network weights and pruning mask converge together from random initial states to a final effective representation over the course of training. Gibbs distributions enable this, since they can be annealed from more random behaviour at high temperatures and converge to a final steady state [@kirkpatrick1983optimization]. The most likely result of sampling — and the result we expect to converge to — corresponds to the state that minimizes the Hamiltonian. We select a Hamiltonian and annealing schedule that will converge to an effective pruned network.

Defining a pruning method within this framework requires:

-   A Hamiltonian where the minimum energy corresponds to a desired pruned structure, based on the network parameters;

-   A method for sampling from the distribution;

-   An approach for annealing $\beta$ during training.

The following sections discuss these elements in more detail.

Unstructured Pruning
--------------------

A widely used heuristic for pruning neural networks is pruning weights with low magnitudes [@han2016deep; @li2017pruning; @gale2019state]. We follow this approach in designing a Hamiltonian for unstructured pruning: we want the energy to be minimized when weights with low magnitude are pruned away.

Let $N$ be the number of weights in the layer and let $\v$ represent a vector with the elements of $\w$ sorted such that $v_i^2 \leq v_{i+1}^2$. Given a pruning rate $p$ between 0 and 1, select $Q(p) = v_i^2$, where $i = p(N-1)+1$. If $i$ is not an integer for the given value of $p$, we linearly interpolate between $Q(p^-)$ and $Q(p^+)$, where $p^-$ and $p^+$ are the nearest values below and above $p$ respectively for which $i$ is an integer: $$Q(p) = Q(p^-) + \frac{p - p^-}{p^+ - p^-}\left(Q(p^+) - Q(p^-)\right).$$ In effect, $Q(p)$ is the empirical $p$th quantile of the squared weight magnitudes.

We define the Hamiltonian for unstructured pruning as $$H(\x) = \sum_{i=1}^N \Big(Q(p) - w_i^2\Big)x_i.
    \label{eq:ham-unstruct}$$ The value of the Hamiltonian is minimized when the fraction $p$ of weights with lowest magnitude are masked, making that the state that annealing will converge towards.

In general, sampling from the Gibbs distribution is difficult because the partition function cannot be feasibly computed for large vectors. In the following proposition, we show that our proposed Hamiltonian for unstructured pruning factors in terms of elements of $x$. The elements are therefore independent and can easily be sampled individually.

The Gibbs distribution corresponding to the proposed Hamiltonian (\[eq:ham-unstruct\]) has a product form. \[prop:unstruct-factor\]

The partition function $Z(\beta)$ normalizes the distribution. With the proposed Hamiltonian, it has the form: $$\begin{aligned}
    Z(\beta) &= \sum_{\x\in\{-1,1\}^N} e^{-\beta \sum_{i=1}^N \left(Q(p) - w_i^2\right)x_i} \\
    &= \sum_{x_1\in\{-1,1\}} \sum_{x_2\in\{-1,1\}} ... \prod_{i=1}^N e^{-\beta \left(Q(p) - w_i^2\right)x_i} \\
    &= \prod_{i=1}^N \left(e^{-\beta \left(Q(p) - w_i^2\right)} + e^{\beta \left(Q(p) - w_i^2\right)} \right) \\
    &= \prod_{i=1}^N 2 \mbox{cosh} \Big(\beta\left(Q(p) - w_i^2\right)\Big).\end{aligned}$$ The Gibbs distribution therefore factors as: $$\begin{aligned}
p(\x) &= \frac{1}{\prod_{i=1}^N 2 \mbox{cosh} \Big(\beta\left(Q(p) - w_i^2\right)\Big)} e^{-\beta \sum_{i=1}^N \left(Q(p) - w_i^2\right)x_i} \\
    &= \prod_{i=1}^N \frac{1}{2 \mbox{cosh} \Big(\beta\left(Q(p) - w_i^2\right)\Big)} e^{-\beta \left(Q(p) - w_i^2\right)x_i}.\end{aligned}$$

Structured Pruning {#sec:structured}
------------------

For structured pruning, we prune blocks of weights together in a way that is advantageous for inference performance. We enforce this by adding a quadratic term to the Hamiltonian that encourages all elements of the pruning mask within given neighbourhoods to take the same value, where the neighbourhoods are chosen to correspond to the blocks of weights that are pruned together. For instance, to do filter-wise pruning on a convolutional network, we would define the neighbourhoods to correspond to the filters of the layer.

We define a neighbourhood as a set of indices corresponding to a subset of weights in the neural network layer. Let $\N_k$ represent the $k$th neighbourhood. Neighbourhoods are disjoint and the union of all neighbourhoods is the set of all weight indices, that is $\N_i \cap \N_j = \emptyset$ and $\bigcup_{k=1}^{M} \N_k = \{1,...,N\}$, where $M$ is the number of neighbourhoods. Let us also define a vector $\bar{\w}$ such that $$\bar{w}_k^2 = \frac{1}{|\N_k|}
\sum_{i\in \N_k}w_i^2.$$ We propose the Hamiltonian $$H(\x) = -c\sum_{k=1}^M\,\sum_{\substack{i,j \in \N_k\\i \neq j}}x_ix_j + \sum_{i=1}^N
    \Big( \bar{Q}(p) - w_i^2\Big)x_i,
    \label{eq:ham-struct}$$ where $c$ is a hyperparameter controlling the relative influence of the structure term on the Hamiltonian, and $\bar{Q}(p)$ is an empirical quantile function over squared weight magnitudes as described previously, but calculated over the values in $\bar{\w}$ instead of $\w$. The state that minimizes the Hamiltonian when $c$ is large enough to enforce the mask structure therefore corresponds to pruning the fraction $p$ of neighbourhoods with lowest average weight magnitude. When $|\N_k| = 1\,\forall\,k$, the inner summation in the quadratic term does not sum over anything, so the quadratic term does not apply. Hence the unstructured pruning Hamiltonian (\[eq:ham-unstruct\]) is a special case of the Hamiltonian (\[eq:ham-struct\]).

The following proposition shows that the probability distribution still factors in terms of neighbourhoods, so we can sample each neighbourhood separately.

The Gibbs distribution corresponding to the Hamiltonian (\[eq:ham-struct\]) has a block product form.

Since the first term of the Hamiltonian (\[eq:ham-struct\]) is zero for elements from different neighbourhoods, the Hamiltonian can be expressed as: $$\begin{aligned}
    H(\x) &= \sum_{k=1}^M H_k(\x_k),\end{aligned}$$ where $H_k(\x_k)$ is the Hamiltonian (\[eq:ham-struct\]) only computed over the elements of the neighbourhood $\N_k$. Following the same approach as for Proposition \[prop:unstruct-factor\], the partition function can then be shown to factor as: $$\begin{aligned}
    Z(\beta) &= \prod_{k=1}^M\,\sum_{\x_k \in \{-1,1\}^{|\N_k|}} e^{-\beta H_k(\x_k)} \\
    &= \prod_{k=1}^M Z_k(\beta),\end{aligned}$$ and the overall distribution factors as: $$\begin{aligned}
p(\x) &= \prod_{k=1}^M\frac{1}{Z_k(\beta)} e^{-\beta H_k(\x_k)}.\end{aligned}$$

Sampling from the above distribution is more challenging than in the unstructured case. If neighbourhoods are small enough, the partition function for each can be computed and the distribution can be sampled from directly. But for large neighbourhoods, this is computationally infeasible, and so we use a Markov chain Monte Carlo (MCMC) method to generate samples. A sampling method that parallelizes well and is simple to implement on a GPU is preferable for neural network training to highly iterative methods like standard Gibbs sampling or the Wolff algorithm [@wolff1989collective]. We therefore propose using Chromatic Gibbs sampling [@gonzalez2011parallel].

Chromatic Gibbs sampling involves making a colouring over the elements in $\x$ such that any interacting elements $x_i$ and $x_j$ in the Hamiltonian have different colours. For our Hamiltonians, $x_i$ and $x_j$ interact if there is a term $\alpha x_ix_j$ with $\alpha \neq 0$. An iteration of the Markov chain then consists of sampling all elements of one colour simultaneously given the current values of all other elements.

To create a colouring, we arbitrarily divide each neighbourhood into two sets of elements and modify the Hamiltonian to remove all quadratic terms containing elements in the same set. In graphical terms, this transforms the Markov random field for each neighbourhood from a complete graph to a complete bipartite graph that can be coloured with two colours, as shown in Figure \[fig:chromatic\]. This modification still preserves a high degree of connectivity within each neighbourhood and so is still effective at encouraging elements in neighbourhoods to take the same value. For instance, to perform filter-wise pruning of a convolutional network, we can divide all connections into two groups based on their input channel. Pseudocode for this algorithm is shown in Algorithm \[fig:chromatic-algo\].

[latex@errorgobble]{}

$\X_0 \gets \X_{\text{init}\,:,:,0:C/2,:}$ $\X_1 \gets \X_{\text{init}\,:,:,C/2+1:C,:}$ $\X \gets \text{concatenate}(\X_0, \X_1)$

\[fig:chromatic-algo\]

Our Hamiltonians are designed so that we know which $\x$ value minimizes them and is therefore the mode of the distribution. To minimize burn-in time, we use this value to initialize the Markov chain, as recommended in [@brooks2011handbook].

Annealing
---------

We perform annealing by increasing $\beta$ from a low value to a high value while training. At high temperatures (low $\beta$), differences in the Hamiltonian do not affect sampling much, and so roughly 50% of weights are pruned randomly. This phase acts similarly to stochastic methods for regularizing neural networks [@labach2019survey], in particular dropconnect [@wan2013regularization], regularizing the network and conditioning it to be robust under weight pruning. Once annealed to a low temperature (high $\beta$), the Gibbs distribution converges towards the value of $\x$ that minimizes the Hamiltonian, which is our desired final pruning mask. A significant amount of later training time is therefore spent adapting to the particular structure of the pruning mask. The balance between time spent on adapting to random masks and time spent on adapting to the final mask can be controlled by the particular annealing schedule for $\beta$ used in training.

Experiments {#sec:experiments}
===========

We compare Gibbs pruning, our proposed method, to several pruning methods that are either well-established or have recently shown exceptional results. We evaluate performance on ResNet neural networks [@he2016deep]. Nearly all of the parameters of these networks are in convolutional layers, which already are much more sparse than dense layers of similar dimensions, and additionally employ weight sharing, making them more difficult to prune than dense layers. Pruning methods that are effective on networks like AlexNet [@krizhevsky2012imagenet] with large dense layers often do not show the same performance on networks like ResNet, making them a more challenging test.

In particular, we train ResNet-20 and ResNet-56 with linear projection [@he2016deep] on the CIFAR-10 [@krizhevsky2012cifar] dataset. The networks are trained for 200 epochs using the Adam optimizer [@kingma2014adam], with a learning rate initially set to $10^{-3}$ and reduced by a factor of 10 at epoch 80 and every 40 epochs thereafter. We use data augmentation during training, randomly shifting images horizontally and vertically by up to 10% and flipping images horizontally with 50% probability. This achieves baseline top-1 accuracies of 90.7% for ResNet-20 and 92.2% for ResNet-56. For all methods, we prune all convolutional layers except for the first one, following the recommendation in [@gale2019state].

For pruning methods that use additional epochs for fine-tuning, we use a training rate of $10^{-5}$ after the initial training phase. We also test changing the lengths of fine-tuning schedules, to evaluate tradeoffs between the number of additional training epochs and the final accuracy.

Unstructured Pruning
--------------------

[.45]{} ![Comparison of our proposed method to other unstructured pruning methods. All methods prune 90% of weights. Dotted lines are shown for comparison on methods that do not require additional training epochs. []{data-label="fig:resnetscatter"}](resnet20-scatter.pdf "fig:"){width="\textwidth"} \[fig:resnet20scatter\]

[.45]{} ![Comparison of our proposed method to other unstructured pruning methods. All methods prune 90% of weights. Dotted lines are shown for comparison on methods that do not require additional training epochs. []{data-label="fig:resnetscatter"}](resnet56-scatter.pdf "fig:"){width="\textwidth"} \[fig:resnet56scatter\]

We compare Gibbs pruning to four established unstructured pruning methods. The first is using $l_1$ regularization with a tuned penalty of 0.001 to induce sparsity during training before masking the fraction $p$ of weights in each layer with the lowest magnitude. The other pruning methods are more advanced approaches from the literature. We evaluate the method proposed in [@han2016deep] by Han et al. Once training is complete, a certain percentage of the weights with lowest magnitude are pruned and the network is fine-tuned. This procedure is then repeated several times. We test different training schedules, using pruning percentages of 10%, 20%, 30%, etc. up to 90%, fine-tuning for $n$ epochs after each step, leading to a total of $200+9n$ epochs. We also compare to iterative magnitude pruning (IMP), proposed by Frankle et al. [@frankle2019lottery] with rewinding [@frankle2019stabilizing]. This method trains the network several times, pruning gradually more each time and then rewinding the network weights to the values they had after the first 500 training steps. To test different training times, we vary the number of times that the network is trained with intermediate pruning rates between the initial rate of 0% and the final rate of 90%. Finally, we test targeted dropout, a method recently proposed by Gomez et al.[@gomez2019learning]. We use their most successful hyperparameter settings: $\alpha=0.75,\gamma=0.9$.

When using Gibbs pruning, we anneal $\beta$ according to a logarithmic schedule from 0.7 to 10000. With the baseline training schedule of 200 epochs, we anneal over the first 128 epochs. These values were chosen empirically to cover a range from an effective pruning rate of 50% to $p$.

To compare our proposed method to those that use additional training epochs, we also evaluate ’stretching’ the training and pruning procedure to take place over a longer training schedule. To do this, we run training for some multiple of 200 epochs, and stretch out the learning rate and $\beta$ annealing schedules by the same multiple. This follows our general approach of training and pruning at the same time, but gives the network longer to both converge to the final pruning mask and to fully adapt to it. In some highly stretched configurations, the pruning mask requires a higher final $\beta$ to converge—in these cases we increase the final beta to $10^6$.

We evaluate pruning 90% of weights in each pruned layer, which is a high degree of compression for the given networks that effectively shows performance differences between different methods. Results are shown in Figure \[fig:resnetscatter\]. Our proposed method outperforms the other evaluated methods for any number of training epochs. While it is effective at 200 epochs, stretching the learning and annealing schedules provides even better performance.

We evaluate Gibbs pruning using different pruning rates in Figure \[fig:p-acc\]. When additional training epochs are used, the resulting accuracy can come close to or exceed the baseline accuracy even with very high pruning rates. For instance, removing 95% of weights in pruned layers decreases accuracy by only 0.90% for ResNet-20 and 0.45% for ResNet-50. To the best of our knowledge, these are the best results reported for such a high compression rate on CIFAR-10 [@blalock2020state].

![Loss in accuracy compared to the baseline versus pruning rate using our proposed unstructured pruning method.[]{data-label="fig:p-acc"}](p-acc-plot.pdf){width="45.00000%"}

[0.4]{}

[width=]{}

       Method
  ----------------- ------ ------ ------ ------
                     50%    75%    90%    95%
     Random mask     89.3   87.2   83.2   79.8
   Random re-init.   88.6   86.3   83.4   79.4
    Gibbs pruning    89.9   89.0   87.5   85.2

  : ResNet-56

[0.4]{}

[width=]{}

       Method
  ----------------- ------ ------ ------ ------
                     50%    75%    90%    95%
     Random mask     91.2   90.0   87.3   84.6
   Random re-init.   90.3   89.1   86.7   84.5
    Gibbs pruning    91.2   90.8   89.8   88.5

  : ResNet-56

\[t:random\]

Random Masks and Re-initialization
----------------------------------

In [@liu2019rethinking], the authors show that results with many pruning methods can be replicated by training a network with the same structure as the pruned network, but with newly initialized weights. This calls into question the utility of training large networks and then pruning, as well as the relevance of weight values in pruning networks. To assess this phenomenon with our proposed method, we evaluate retraining pruned networks with randomly re-initialized weights. For comparison, we also test training networks from scratch using random pruning masks with the chosen sparsity.

Results are shown in Table \[t:random\]. We find that random re-initialization does not meet the performance of our proposed method, and is more similar to training with a random mask. These results suggests that Gibbs pruning acts less as a search over possible network architectures, and instead adapts more dynamically along with weight values throughout training, resulting in a final representation that is more tuned to particular weights than other methods are.

[.45]{} ![Comparison of our proposed method to other kernel-wise structured pruning methods. All methods prune 90% of weights. Dotted lines are shown for comparison on methods that do not require additional training epochs. []{data-label="fig:resnetkernelscatter"}](resnet20-kernel-scatter.pdf "fig:"){width="\textwidth"} \[fig:resnet20kernelscatter\]

[.45]{} ![Comparison of our proposed method to other kernel-wise structured pruning methods. All methods prune 90% of weights. Dotted lines are shown for comparison on methods that do not require additional training epochs. []{data-label="fig:resnetkernelscatter"}](resnet56-kernel-scatter.pdf "fig:"){width="\textwidth"} \[fig:resnet56kernelscatter\]

Structured Pruning {#structured-pruning}
------------------

We also evaluate performance for structured convolutional neural network pruning. We consider pruning individual kernels as well as entire filters of size $N\times N\times C$, where $C$ is the number of output channels for the layer being pruned. Generally speaking, kernel-wise pruning can achieve higher accuracies for the same number of parameters, but might be harder to optimize performance for compared to filter-wise pruning. In practice, the desired structure depends on the optimization capabilities of the hardware and software the neural network is implemented on.

We compare Gibbs pruning to three established structured pruning methods. One is targeted dropout [@gomez2019learning], implemented as previously described, but dropping entire kernels or filters. For filter-wise pruning, we set its hyperparameters to the most effective values described for unit dropout: $\alpha=0.9, \gamma=0.75$. We also evaluate iteratively pruning filters or kernels based on their $l_1$-norm and retraining, as proposed by Li et al. in [@li2017pruning]. Finally, we evaluate ThiNet pruning, as proposed by Luo et al. [@luo2017thinet]. This method greedily prunes channels to minimize changes in activations over an evaluation dataset. Pruning a channel is equivalent to pruning a filter in the previous layer, making channel-wise and filter-wise pruning comparable. This method does not prune $1\times1$ convolution layers, which we also omit for filter-wise pruning with our proposed method.

For kernel-wise Gibbs pruning, each neighbourhood is small enough that the partition function is practically computable, so we sample directly from the Gibbs distribution. For filter-wise pruning, we use chromatic Gibbs sampling as described in Section \[sec:structured\]. We run the Markov chain for 50 iterations, as further iterations did not improve performance in practice. For kernel-wise pruning, we set $c$ to 0.01 and anneal $\beta$ logarithmically from 0.7 to 10000. For filter-wise pruning, we set $c$ to 1 and anneal $\beta$ logarithmically from 0.003 to 1. As with unstructured pruning, these values were chosen empirically to cover a range from an effective pruning rate of 50% to $p$, while also converging to a mask that has the desired structure. To test different training lengths, we stretch the learning rate and annealing schedules as previously described.

Kernel-wise pruning results are shown in Figure \[fig:resnetkernelscatter\] and filter-wise pruning results are shown in Figure \[fig:resnetfilterscatter\]. Note that a lower pruning rate of 75% is used in evaluating filter-wise pruning methods, since filter-wise pruning at high rates results in much lower accuracy. In both types of structured pruning, Gibbs pruning outperforms other methods, and stretching the learning rate and annealing schedules proves to be effective in additionally improving accuracy.

[.45]{} ![Comparison of our proposed method to other filter-wise structured pruning methods. All methods prune 75% of weights. Dotted lines are shown for comparison on methods that do not require additional training epochs. []{data-label="fig:resnetfilterscatter"}](resnet20-filter-scatter.pdf "fig:"){width="\textwidth"} \[fig:resnet20filterscatter\]

[.45]{} ![Comparison of our proposed method to other filter-wise structured pruning methods. All methods prune 75% of weights. Dotted lines are shown for comparison on methods that do not require additional training epochs. []{data-label="fig:resnetfilterscatter"}](resnet56-filter-scatter.pdf "fig:"){width="\textwidth"} \[fig:resnet56filterscatter\]

Conclusion
==========

We introduce a novel method for neural network pruning based on Gibbs distributions that achieves high pruning rates with little reduction in accuracy. It can be used for either unstructured or structured pruning, and the general framework can be adapted to a wide range of pruning structures. Our results show the efficacy of simultaneously training and pruning a network rather than training and pruning as distinct steps at different times. Future work could explore other structures that can be expressed within this framework, such as limiting the number of non-zero values in convolutional kernels or structured pruning of recurrent neural network layers.

Acknowledgement
===============

The authors would like to thank Fujitsu Laboratories Ltd. and Fujitsu Consulting (Canada) Inc. for providing financial support for this project at the University of Toronto.


Wastage of ova in young Merino ewes.
Eight sub-flocks each of 48 to 51 Merino ewes were mated for 18 days with 1 ram to each subflock. Four of the sub-flocks were of non-parous 1.5-year-old ewes and the other 4 were of parous 2.5-year-old ewes. Fertilisation rates for the subflocks of 1.5-year-old ewes varied from 83 to 94%, and the sub-flocks of 2.5-year-old ewes ranged from 81 to 94%. By day 29 post coitum 42% and 56% of 1.5-year-old ewes in sub-flocks 1 and 2 respectively were no longer pregnant. Embryonic mortality was low in other sub-flocks of 1.5- and 2.5-year-old ewes. Virtually all embryonic death occurred after day 12 post coitum. The sporadic occurrence of high ova wastage in maiden 1.5-year-old ewes in this experiment and in others is discussed in relation to the short duration of oestrus in young ewes and the great variation in service activity of rams.


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Q:

Why does "e.preventDefault()" and "return false" disable the post?

I have encountered a problem today. I have solved it. I solved it heuristically, however I want scientific explanation (We should not be a programmer, a scientific person also :) )
Here is my initial View code of my MVC project:
    //shortened for brevity

@using (Html.BeginForm())
{
    @Html.ValidationSummary(true)

    <fieldset>

            @Html.LabelFor(model => model.UserName)

            @Html.TextBoxFor(model => model.UserName, new { onkeyup = "InputToLower(this);" })
            @Html.ValidationMessageFor(model => model.UserName)

            @Html.LabelFor(model => model.UserPassword)

            <input type="password" name="password1" id="password1" />

            Lütfen şifrenizi tekrar giriniz:

            <input type="password" name="password2" id="password2" />

            @Html.LabelFor(model => model.UserEmail)

            @Html.EditorFor(model => model.UserEmail)
            @Html.ValidationMessageFor(model => model.UserEmail)

                <input type="submit" id="registerButton" value="Kayıt Ol" />

    </fieldset>
     }

Code is shortened for brevity. When I disable e.preventDefault() and return false, posting has been done.  How and why e.preventDefault() and return false prevent posting? Do you recommend any book that mentions that kind of issue? Thanks in advance.

A:

registerButton is submit button and behavior of submit is to post form's data to the action that is mentioned in form tag. If you have not mentioned any action attribute in form tag then it will hit post action of same get action.
event.preventDefault() and return false stops your post back or further events.


* Stephen Colbertdropped by his soon-to-be-predecessor David Letterman’s show on Tuesday night. The two joked heartily, about, among other things, Stephen’s salary for the gig – he revealed he’d once turned down an opportunity to intern at the Late Show because he wasn’t going to be paid. Come 2015, that should be a fond memory for Colbert.

* We’ve loved him as Barney, and before that Doogie Howser, and now Neil Patrick Harris is earning high praise for his role as Hedwig in John Cameron Mitchell’s Hedwig and the Angry Inch. The new version of the production opened on Tuesday night, with The New York Times’ Ben Brantley declaring that Harris now joins “an elite club of musical-comedy male supernovas that has exactly one other member these days, Hugh Jackman.” High praise, indeed.

* Robert Downey Jr is new to Twitter but it looks like he’s got the hang of it quite well – giving us his first pic from the set of The Avengers: Age of Ultron, which is of him andexecutive producer Jeremy Latcham in safety vests. Keep ’em comin’, Mr Stark.

* If you’re a Pixies fan, you’ll already know you can stream the band’s first album in over 20 years, right now. Indie Cindy recorded without co-founder Kim Deal, is the 6th album from the Boston group, and no doubt a polarizing one for many.

* Oscar winner Lupita Nyong’o has topped People Magazine’s Most Beautiful list. Of course, she’s to be commended for much more than her looks, but it’s still pretty great to see her on the cover.


The relationship between arterial compliance, age, blood pressure and serum lipid levels.
To investigate the association of serum lipids with non-invasively assessed systemic arterial compliance in a group of newly diagnosed coronary artery disease patients and their matched controls. Systemic arterial compliance is important in maintaining diastolic blood pressure and coronary perfusion, with decreased diastolic blood pressure in the presence of significant coronary artery disease suggested as contributing to increased morbidity. Decreased systemic arterial compliance is also associated with increased morbidity through its contribution to systolic hypertension. Despite the importance of arterial compliance, its association with biochemical factors is not certain. Twenty newly diagnosed coronary artery disease patients and disease-free controls were matched for age, sex, smoking status and total serum cholesterol level. Systemic arterial compliance was measured using applanation tonometry and Doppler velocimetry before instigation of treatment. There was no difference in group low-density lipoprotein or high-density lipoprotein cholesterol levels. Systemic arterial compliance was significantly less in the coronary artery disease group. For the groups combined, a significant negative correlation was demonstrated between systemic arterial compliance and low-density lipoprotein; however, on separate group analysis the correlation was confined to the coronary artery disease group. A significant difference was found in the association between systemic arterial compliance and diastolic blood pressure for the two groups. Increasing low-density lipoprotein cholesterol levels are associated with decreasing systemic arterial compliance; however, the identified intergroup differences suggest that, presumably because of differences in lipid-vessel wall interactions, disease-free subjects exhibit relatively less alteration in aortic mechanical properties than those who develop coronary artery disease.


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Article on Malaysia’s Election in Islamic Monthly

…BN’s victory means that it will hold 60% of the seats in Parliament, despite receiving less than half of the national vote. That is the result of the gerrymandering of electoral districts and also the gross imbalance in the size of those districts, which can range from less than 25,000 to over 100,000 voters. That tends to benefit rural districts, where the BN is strong, at the expense of urban voters, who favor the opposition.

In every election there are reports of voter fraud, “phantom voters,” and vote buying. The general consensus among political experts is that in past years it did not affect the ultimate outcome. This year, however, the picture is more confused. There are numerous and well-documented reports of vote buying and illegal voting. The indelible ink that the Election Commission used turned out to be easily removable.


The present invention relates to an aerodynamic vehicle mirror head which combines an aerodynamically shaped housing for the mirror head with an upstream vane on the side of the mirror head adjacent the vehicle for causing air scrubbing of the mirror surface and a downstream vane on the opposite side of the mirror head for closing down and reducing the size of the downstream wake of the mirror flow field. The mirror head is especially suited for use on a large vehicle such as a truck or bus.


Geheimnisverrat, Behinderung der Justiz: Immer neue Enthüllungen setzen Amerikas Präsidenten unter Druck. Dass er Medienberichte dementieren lässt, beeindruckt viele Amerikaner schon lange nicht mehr. Das liegt vor allem an Donald Trump selbst.

Als Donald Trump vor wenigen Wochen seine ersten hundert Tage im Amt komplettierte, präsentierten viele amerikanische Tageszeitungen und Faktencheck-Portale erstaunliche Zahlen. In der so wichtigen Anfangsphase seiner Präsidentschaft habe der Republikaner sage und schreibe 492 Mal falsche oder irreführende Aussagen gemacht, rechnete etwa die Zeitung „Washington Post“ vor.

Natürlich haben auch Präsidenten vor Trump immer mal wieder Lügen verbreitet, doch die meisten Beobachter sind sich einig: Kaum ein Vorgänger habe ein derart gespaltenes Verhältnis zu Wahrheit gehabt wie der aktuelle Amtsinhaber. Nur an zehn von hundert Tagen habe Trump keine falschen oder irreführenden Aussagen von sich gegeben. An sechs dieser zehn Tage soll er übrigens Golf spielen gewesen sein.

Mehr zum Thema 1/ Trump verrät dem russischen Außenminister Lawrow vertrauliche Informationen eines befreundeten Nachrichtendienstes. Damit brüskiert er seine Partner, beschädigt sein Amt – und setzt die Sicherheit Amerikas aufs Spiel.

Man muss diese Vorgeschichte im Hinterkopf haben, wenn man die aktuelle Debatte über angeblich von Trump an Russland ausgeplauderte Top-Secret-Informationen eines befreundeten Geheimdiensts oder die mögliche Behinderung von FBI-Ermittlungen analysiert. Viele Amerikaner, unter ihnen auch Republikaner, sind zunehmend skeptisch, wenn sie mit Aussagen der Trump-Regierung konfrontiert werden. Zu oft wurde ihr Präsident beim Lügen erwischt.

Video starten Washington : Trump soll Russland Geheimdienstinformationen verraten haben Trump soll sensible Geheimdienstinformationen an Lawrow weitergegeben haben To view this video please enable JavaScript, and consider upgrading to a web browser that supports HTML5 video Video: reuters, Bild: MINISTRY HAN/REX/Shutterstock

Da hilft es offenbar auch nicht viel, dass Trump in dieser Woche mit seinem Nationalen Sicherheitsberater H.R. McMaster einen Mitarbeiter vorschickte, dessen Glaubwürdigkeit – bisher zumindest – über nahezu jeden Zweifel erhaben war. Dass der frühere General die entsprechenden Berichte vieler Medien als „falsch“ und die Vorgehensweise des Präsidenten als „völlig angemessen“ bezeichnete, heißt nicht, dass der Großteil der Öffentlichkeit das auch glaubt.

Spicers Absturz

Es wäre schließlich nicht das erste Mal, dass ein enger Mitarbeiter Trumps beim Versuch, den eigenen Chef zu verteidigen, eine peinliche Bauchlandung erlitte. Präsidentensprecher Sean Spicer, bis zu Trumps Amtsantritt im Januar eigentlich auch eine parteiübergreifend respektierte Person in Washington, zerstörte gleich an seinem ersten Arbeitstag viel Glaubwürdigkeit, als er in aggressivem Ton verkünden musste, dass die Zuschauermenge bei Trumps Amtseinführung größer war, als Fotos belegten.

Seitdem vergeht kaum eine Woche, in der Spicer sich bei seinen Pressekonferenzen nicht im Gestrüpp von Fehlinformationen, Halbwahrheiten und Trump-Deutungen verstrickt. Spicers Stellvertreterin Sarah Huckabee-Sanders ereilte vergangene Woche ein ähnliches Schicksal, als sie den von Trump veranlassten Rauswurf von FBI-Direktor James Comey mit einer Erklärung zu begründen versuchte, der der Präsident kurz danach selbst widersprach. Sogar Vizepräsident Mike Pence fand sich bereits des Öfteren blamiert und frustriert in solchen Situationen wieder.

Trump attackiert Mitarbeiter

„Menschen, die ein Leben lang im öffentlichen Dienst für Integrität standen, riskieren in dieser Regierung, ihren Ruf zu verspielen“, sagt der Republikaner-Berater Steve Schmidt. Der demokratische Senator Brian Schatz sagt im Magazin „Politico“, Trump und sein Team hätten bereits „am Inaugurationstag damit begonnen, ihre Glaubwürdigkeit zu verspielen“.

Derweil versucht Trump offenbar, die Schuld für die schlechten Schlagzeilen auf seine Mitarbeiter abzuwälzen. So soll der Präsident bereits zu Beginn dieser Woche das PR-Team um Spicer, Huckabee-Sanders und Kommunikationsdirektor Michael Dubke regelrecht angepfiffen haben, sich „endlich auf einer gemeinsamen Wellenlänge“ einzufinden, wie die Zeitung „New York Times“ unter Berufung auf eine gut informierte Quelle berichtet.

Gut möglich, dass Spicer der erste Mitarbeiter ist, der bei einem „Shake-up“ im Weißen Haus gehen müsste. Andere Beobachter glauben, dass Stabschef Reince Priebus ganz oben auf der Entlassungsliste steht.

Affäre um FBI-Chef Comey

Am Dienstagabend bricht dann die nächste Eilmeldung über Washington herein. Demnach soll Trump bei einem Treffen im Februar den damaligen FBI-Chef Comey darum gebeten haben, die Ermittlungen gegen seinen früheren Sicherheitsberater Michael Flynn einzustellen. Das berichtet die Zeitung „New York Times“ unter Berufung auf ein Memo, das Comey kurz nach dem Treffen mit Trump geschrieben haben soll. Flynn steht derzeit wegen seiner Russland-Kontakte im Wahlkampf im Visier von Sicherheitsbehörden und Kongressausschüssen.

Der Sturm der Empörung lässt nicht lange auf sich warten. „An einem Tag, an dem wir dachten, dass die Dinge nicht mehr schlimmer werden können, sind sie es doch geworden“, sagt der demokratische Senator Chuck Schumer am Abend im Kapitol mit düsterer Miene. Die Vereinigten Staaten würden „auf eine Probe gestellt“. Wenn ein Präsident einem FBI-Direktor rate, die laufende Untersuchung eines führenden Wahlkampfberaters zu beenden, dann sei das nur mit den Worten „Behinderung der Justiz“ zu beschreiben, empört sich der renommierte Jurist und CNN-Kommentator Jeffrey Toobin.

Und was macht Trump? Er lässt die Skandalmeldungen dementieren – bereits zum zweiten Mal in dieser Woche. Sagt er die Wahrheit? Blickt man auf seine Bilanz der ersten hundert Regierungstage, sind Zweifel angebracht.


Monday, December 9, 2013

A Bizarre Hit and Run Happened Saturday Morning

Shamanique R. Bryant is being charged in a bizarre hit and run that occurred early Saturday morning near the intersection of Euclid Avenue and Coltman Road.

Bryant was driving a 2001 Oldsmobile Alero when she rear-ended another car, Cleveland.com reports. Ok, that's pretty reckless, but nothing too out of the ordinary.

But, Bryant was driving fast enough that the impact threw the woman sitting in the passenger seat, Mattie J. Quellen Stubbs, out of the car.

Did Bryant stop and get out of the car to see if Stubbs was ok? No. Did she instead flee the scene? Yes.

While the actions mentioned above point to some sort of diminished capacity for reasoning and general good decision making, Bryant did later stop to perform CPR on a man in the backseat of the car. By the way, the man had been shot earlier in the night.

Presumably the man who had been shot showed some sign of improvement, because Bryant returned to the scene of the accident, where she then proceeded to run over Stubbs.

So, to recap, Bryant is speeding, crashes into another car, causing her passenger to be thrown out of her car, while a man is likely bleeding profusely from a gunshot wound in the backseat. Bryant flees sans Stubbs, comes back and runs over Stubbs, who died from her injuries.

Bryant is being charged with aggravated vehicular homicide, and leaving the scene of an accident. According to Fox 8, OVI charges may also be added.


Q:

The "CreateRiaClientFilesTask" task failed unexpectedly

I've VS 2010 and recently installed WCF RIA Services V1.0. For testing I have created a new Silverligh Business project but now every now and then when I rebuild the solution I receive the following error:
Does anybody know why I get this?
Thanks
Error   1   The "CreateRiaClientFilesTask" task failed unexpectedly.
System.IO.FileNotFoundException: Could not load file or assembly 'Microsoft.ServiceModel.DomainServices.Tools, Version=4.0.0.0, Culture=neutral, PublicKeyToken=31bf3856ad364e35' or one of its dependencies. The system cannot find the file specified.
File name: 'Microsoft.ServiceModel.DomainServices.Tools, Version=4.0.0.0, Culture=neutral, PublicKeyToken=31bf3856ad364e35'
   at System.RuntimeTypeHandle.GetTypeByName(String name, Boolean throwOnError, Boolean ignoreCase, Boolean reflectionOnly, StackCrawlMarkHandle stackMark, Boolean loadTypeFromPartialName, ObjectHandleOnStack type)
   at System.RuntimeTypeHandle.GetTypeByName(String name, Boolean throwOnError, Boolean ignoreCase, Boolean reflectionOnly, StackCrawlMark& stackMark, Boolean loadTypeFromPartialName)
   at System.RuntimeType.GetType(String typeName, Boolean throwOnError, Boolean ignoreCase, Boolean reflectionOnly, StackCrawlMark& stackMark)
   at System.Type.GetType(String typeName, Boolean throwOnError)
   at System.Web.Hosting.HostingEnvironment.CreateWellKnownObjectInstance(String assemblyQualifiedName, Boolean failIfExists)
   at System.Web.Hosting.HostingEnvironment.CreateWellKnownObjectInstance(String assemblyQualifiedName, Boolean failIfExists)
   at System.Web.Hosting.ApplicationManager.CreateObjectInternal(String appId, Type type, IApplicationHost appHost, Boolean failIfExists, HostingEnvironmentParameters hostingParameters)
   at System.Web.Hosting.ApplicationManager.CreateObjectInternal(String appId, Type type, IApplicationHost appHost, Boolean failIfExists)
   at System.Web.Compilation.ClientBuildManager.CreateObject(Type type, Boolean failIfExists)
   at Microsoft.ServiceModel.DomainServices.Tools.CreateRiaClientFilesTask.CreateSharedTypeService(ClientBuildManager clientBuildManager, IEnumerable`1 serverAssemblies, ILogger logger)
   at Microsoft.ServiceModel.DomainServices.Tools.CreateRiaClientFilesTask.GenerateClientProxies()
   at Microsoft.ServiceModel.DomainServices.Tools.CreateRiaClientFilesTask.ExecuteInternal()
   at Microsoft.ServiceModel.DomainServices.Tools.RiaClientFilesTask.Execute()
   at Microsoft.Build.BackEnd.TaskExecutionHost.Microsoft.Build.BackEnd.ITaskExecutionHost.Execute()
   at Microsoft.Build.BackEnd.TaskBuilder.ExecuteInstantiatedTask(ITaskExecutionHost taskExecutionHost, TaskLoggingContext taskLoggingContext, TaskHost taskHost, ItemBucket bucket, TaskExecutionMode howToExecuteTask, Boolean& taskResult)

WRN: Assembly binding logging is turned OFF.
To enable assembly bind failure logging, set the registry value [HKLM\Software\Microsoft\Fusion!EnableLog] (DWORD) to 1.
Note: There is some performance penalty associated with assembly bind failure logging.
To turn this feature off, remove the registry value [HKLM\Software\Microsoft\Fusion!EnableLog].
    BusinessApplication2

A:

Close VS, delete files in c:\Windows\Microsoft.NET\Framework\v4.0.30319\Temporary ASP.NET Files\.
Restart VS, Build solution.
By the way; I got the problem after a bluescreen.

A:

I found restarting VS in Administrator mode was all that was required.


About Us

Yashraj Biotechnology Limited (YBL) is a part of the “YASHRAJ GROUP” having diversified interests in finance, construction, agriculture, chemicals and biotechnology. YBL was established in 1999 with a mission to achieve excellence in biotechnology and utilize its power for the good of humanity.

Top Products

D-Dimer

Human Placental Ferritin

HE4

PSA-ACT complex

FABP-3

Anti-PSA Monoclonal Antibody

New Products

sTfR

Click here for full detailsThe uptake of iron by cells is mediated by a cell surface transferrin receptor (TfR). The level of TfR expression is proportional to the need for iron in the cells. A proteolytic product of transferrin receptor soluble transferrin receptor (sTfR) appears in plasma during the cellular deficiency of iron. sTfR is used as a biomarker for the evaluation of suspected iron deficiency in patients.
Route of Production: Native

rGalectin-3

Click here for full detailsGalectin-3 is a member of lectin family. Galectin-3 binds to a wide range of extracellular matrix proteins such as fibronectin, and laminin domains. Expression of Galectin-3 is seen in neutrophils, macrophages, mast cells, fibroblasts, and osteoclasts Plasma. Galectin-3 is a novel prognostic marker in patients with chronic heart failure.
Route of Production: Recombinant

NGAL (Neutrophil Gelatinase Associated Lipocalin)

Click here for full detailsAlso known as Lipocalin-2. It is an early and reliable indicator of acute kidney injury (AKI). In the recent past NGAL has emerged as an excellent prognostic marker for the AKI. During kidney injury level of NGAL goes high in both plasma as well as urine. Since NGAL is resistant to protease, it is stable in the blood and serum. Wild type: consists of 178 amino acids (AA 21-198). Mutant NGAL: consists of 178 amino acids (AA 21- 198) with replacement of free Cysteine to Serine at 107th position. Route of Production: Native, Recombinant

rSLO (Recombinant Streptolysin)

Click here for full detailsStreptolysin o is a hemolytic endotoxin secreted from streptococcal. It is a thiol activated membrane damaging protein of Molecular weight 69 Kda. It is binds to cholesterol-containing target membranes.
Route of Production: Recombinant

rSAA-I (Recombinant Serum amyloid A)

Click here for full detailsSerum amyloid A (SAA) proteins comprise a family of apolipoproteins. These proteins play an important role in HDL metabolism and cholesterol homeostasis. Human SAA1 is a major acute phase protein that is highly expressed in response to inflammation and tissue injury. SAA1 is considered to be a biomarker for inflammation.
Route of Production: Recombinant

Monoclonal Antibody against CA15-3 like antigen

Click here for full details15-3 is a glycosylated protein of molecular weight of around 400 KDa. It is secreted by the surface epithelia of cancer tissues and released into the blood stream. The mouse monoclonal antibody has been generated against native CA 15-3 like antigen.


3 Sexy Summer Hair Ideas – Oklahoma City Hairdresser

Summer is a time when you want to go to the beach, hang out at the pool and enjoy the outdoors. Sexy summer hair is simple and you don’t have to spend a lot of time and effort to look you best while you’re enjoying the sun. First start with a great cut. With a great cut your hair will look good no matter how you wear it. Next protect your hair from the sun by using products which contain sunscreen. Your scalp can sunburn just like your face and body so if you’re going to be out and about in heavy sun, wear a hat or scarf. The easiest summer hairstyle is a short pixie or bob, but it you have longer hair you’ll need some styling options.

Cosmopolitan.com

Big Ponytail

Instead of just opting for a boring ponytail why not add some volume for a different look? The secret to this look is a sleek front and a pumped up back. Use volumizing mousse on towel dried hair and gather it up into a ponytail about eye level. Use a paddle brush to back comb the ponytail. Make it as big and messy as you want. This is a great look if you’re spending the day at the beach or pool.

Braids

A long braid down your back is sexy. It sways as you walk and you can have this look in just a few minutes. Either gather your hair up into a low ponytail and then braid it, or French braid your hair into a long ponytail. This style works best on long thick hair, but you can still have this look with almost any texture or length. Simply French braid your hair into a back braid and you’ve got a sexy no fuss style.

Low Slung Bun

If you need a polished look for special night out a low slung bun is the perfect answer. Gather your hair up into a ponytail at the nape of your neck, wrap the hair around the ponytail and secure it with hairpins. Use some extra hold spray to keep it all together and don’t worry about getting each hair in place. A bit of a messy look is very sexy this season.

These are just a few of the great sexy styles you can try out this summer. Ask your stylist to recommend professional products to protect your hair from sun, chlorine and keep it looking great all summer long.

Call now to book an appointment. Anastasia is a salon hair stylist in Oklahoma City, OK. Out of town appointments welcome.


Lymphocyte vaccination protects prediabetic non-obese diabetic mice from developing diabetes mellitus.
In the therapeutic manoeuvre termed "lymphocyte vaccination", activated lymphocytes capable of transferring an autoimmune disease are instead attenuated and given in vaccine form. We have previously shown that such a therapy administered to non-obese diabetic (NOD) mice at 6 weeks of age prevents diabetes mellitus. To assess whether this therapy has potential clinical relevance, in the present study lymphocyte vaccination was applied in NOD mice in 3 weekly doses commencing in the immediate prediabetic period (age 12 weeks), when insulitis is advanced and diabetes incipient. Of 30 NOD mice receiving active vaccine (composed of attenuated lymphocytes from diabetic NOD mice) 13 (43.3%) remained non-diabetic to the age of 30 weeks, in comparison with 2 of 30 (6.7%; p < 0.01) mice receiving a control vaccine (composed of attenuated lymphocytes from non-diabetic NOD/B10 mice) and 5 of 26 (19.2%; p < 0.01) mice receiving saline carrier alone. Moreover, in an additional group of 10 NOD mice receiving active vaccine weekly between 12 and 30 weeks, 8 remained diabetes free at the end of the treatment. The most notable effect of the vaccine was that the delay in diabetes onset was accompanied by a reduction in insulitis and in some cases a complete absence of infiltrating lymphocytes at 30 weeks of age. Immunocytochemistry indicated that when present, islet infiltrating lymphocytes in non-diabetic mice that received active vaccine showed significantly reduced staining for interferon-gamma, compared with the infiltrate seen in diabetic mice receiving the control vaccine or saline. This study demonstrates that the rapid progression to diabetes typically seen in 12-week-old NOD mice can be delayed by lymphocyte vaccination, supporting the possibility that a vaccine composed of attenuated autologous peripheral blood lymphocytes could be effective in high risk first degree relatives of patients with insulin dependent diabetes mellitus.


Exclusive: After the Persian Gulf War in 1991, America’s neocons thought no country could stand up to the high-tech U.S. military, and they realized the Soviet Union was no longer around to limit U.S. actions. So, the “regime change” strategy was born and many have died, writes ex-CIA analyst Ray McGovern.

By Ray McGovern

Former Washington insider and four-star General Wesley Clark spilled the beans several years ago on how Paul Wolfowitz and his neoconservative co-conspirators implemented their sweeping plan to destabilize key Middle Eastern countries once it became clear that post-Soviet Russia “won’t stop us.”

As I recently reviewed a YouTube eight-minute clip of General Clark’s October 2007 speech, what leaped out at me was that the neocons had been enabled by their assessment that after the collapse of the Soviet Union Russia had become neutralized and posed no deterrent to U.S. military action in the Middle East.

While Clark’s public exposÃ© largely escaped attention in the neocon-friendly “mainstream media” (surprise, surprise!), he recounted being told by a senior general at the Pentagon shortly after the 9/11 attacks in 2001 about the Donald Rumsfeld/Paul Wolfowitz-led plan for “regime change” in Iraq, Syria, Lebanon, Libya, Somalia, Sudan and Iran.

This was startling enough, I grant you, since officially the United States presents itself as a nation that respects international law, frowns upon other powerful nations overthrowing the governments of weaker states, and in the aftermath of World War II condemned past aggressions by Nazi Germany and decried Soviet “subversion” of pro-U.S. nations.

But what caught my eye this time was the significance of Clark’s depiction of Wolfowitz in 1992 gloating over what he judged to be a major lesson learned from the Desert Storm attack on Iraq in 1991; namely, “the Soviets won’t stop us.”

That remark directly addresses a question that has troubled me since March 2003 when George W. Bush attacked Iraq. Would the neocons widely known as “the crazies” at least among the remaining sane people of Washington have been crazy enough to opt for war to re-arrange the Middle East if the Soviet Union had not fallen apart in 1991?

The question is not an idle one. Despite the debacle in Iraq and elsewhere, the neocon “crazies” still exercise huge influence in Establishment Washington. Thus, the question now becomes whether, with Russia far more stable and much stronger, the “crazies” are prepared to risk military escalation with Russia over Ukraine, what retired U.S. diplomat William R. Polk deemed a potentially dangerous nuclear confrontation, a “Cuban Missile Crisis in reverse.”

Putin’s Comment

The geopolitical vacuum that enabled the neocons to try out their “regime change” scheme in the Middle East may have been what Russian President Vladimir Putin was referring to in his state-of-the-nation address on April 25, 2005, when he called the collapse of the Soviet Union “the greatest geopolitical catastrophe of the [past] century.” Putin’s comment has been a favorite meme of those who seek to demonize Putin by portraying him as lusting to re-establish a powerful USSR through aggression in Europe.

But, commenting two years after the Iraq invasion, Putin seemed correct at least in how the neocons exploited the absence of the Russian counterweight to over-extend American power in ways that were harmful to the world, devastating to the people at the receiving end of the neocon interventions, and even detrimental to the United States.

If one takes a step back and attempts an unbiased look at the spread of violence in the Middle East over the past quarter-century, it is difficult to avoid the conclusion that Putin’s comment was on the mark. With Russia a much-weakened military power in the 1990s and early 2000s, there was nothing to deter U.S. policymakers from the kind of adventurism at Russia’s soft underbelly that, in earlier years, would have carried considerable risk of armed U.S.-USSR confrontation.

I lived in the USSR during the 1970s and would not wish that kind of restrictive regime on anyone. Until it fell apart, though, it was militarily strong enough to deter Wolfowitz-style adventurism. And I will say that for the millions of people now dead, injured or displaced by U.S. military action in the Middle East over the past dozen years the collapse of the Soviet Union as a deterrent to U.S. war-making was not only a “geopolitical catastrophe” but an unmitigated disaster.

Visiting Wolfowitz

In his 2007 speech, General Clark related how in early 1991 he dropped in on Paul Wolfowitz, then Under Secretary of Defense for Policy (and later, from 2001 to 2005, Deputy Secretary of Defense). It was just after a major Shia uprising in Iraq in March 1991. President George H.W. Bush’s administration had provoked it, but then did nothing to rescue the Shia from brutal retaliation by Saddam Hussein, who had just survived his Persian Gulf defeat.

According to Clark, Wolfowitz said: “We should have gotten rid of Saddam Hussein. The truth is, one thing we did learn is that we can use our military in the Middle East and the Soviets won’t stop us. We’ve got about five or 10 years to clean up those old Soviet client regimes Syria, Iran (sic), Iraq before the next great superpower comes on to challenge us.”

It’s now been more than 10 years, of course. But do not be deceived into thinking Wolfowitz and his neocon colleagues believe they have failed in any major way. The unrest they initiated keeps mounting in Iraq, Syria, Libya, Somalia, Lebanon not to mention fresh violence now in full swing in Yemen and the crisis in Ukraine. Yet, the Teflon coating painted on the neocons continues to cover and protect them in the “mainstream media.”

True, one neocon disappointment is Iran. It is more stable and less isolated than before; it is playing a sophisticated role in Iraq; and it is on the verge of concluding a major nuclear agreement with the West barring the throwing of a neocon/Israeli monkey wrench into the works to thwart it, as has been done in the past.

An earlier setback for the neocons came at the end of August 2013 when President Barack Obama decided not to let himself be mouse-trapped by the neocons into ordering U.S. forces to attack Syria. Wolfowitz et al. were on the threshold of having the U.S. formally join the war against Bashar al-Assad’s government of Syria when there was the proverbial slip between cup and lip. With the aid of the neocons’ new devil-incarnate Vladimir Putin, Obama faced them down and avoided war.

A week after it became clear that the neocons were not going to get their war in Syria, I found myself at the main CNN studio in Washington together with Paul Wolfowitz and former Sen. Joe Lieberman, another important neocon. As I reported in “How War on Syria Lost Its Way,” the scene was surreal funereal, even, with both Wolfowitz and Lieberman very much down-in-the-mouth, behaving as though they had just watched their favorite team lose the Super Bowl.

Israeli/Neocon Preferences

But the neocons are nothing if not resilient. Despite their grotesque disasters, like the Iraq War, and their disappointments, like not getting their war on Syria, they neither learn lessons nor change goals. They just readjust their aim, shooting now at Putin over Ukraine as a way to clear the path again for “regime change” in Syria and Iran. [See Consortiumnews.com’s “Why Neocons Seek to Destabilize Russia.”]

The neocons also can take some solace from their “success” at enflaming the Middle East with Shia and Sunni now at each other’s throats — a bad thing for many people of the world and certainly for the many innocent victims in the region, but not so bad for the neocons. After all, it is the view of Israeli leaders and their neocon bedfellows (and women) that the internecine wars among Muslims provide at least some short-term advantages for Israel as it consolidates control over the Palestinian West Bank.

In a Veteran Intelligence Professionals for Sanity memorandum for President Obama on Sept. 6, 2013, we called attention to an uncommonly candid report about Israeli/neocon motivation, written by none other than the Israel-friendly New York Times Bureau Chief in Jerusalem Jodi Rudoren on Sept. 2, 2013, just two days after Obama took advantage of Putin’s success in persuading the Syrians to allow their chemical weapons to be destroyed and called off the planned attack on Syria, causing consternation among neocons in Washington.

Rudoren can perhaps be excused for her naive lack of “political correctness.” She had been barely a year on the job, had very little prior experience with reporting on the Middle East, and in the excitement about the almost-attack on Syria she apparently forgot the strictures normally imposed on the Times’ reporting from Jerusalem. In any case, Israel’s priorities became crystal clear in what Rudoren wrote.

In her article, entitled “Israel Backs Limited Strike Against Syria,” Rudoren noted that the Israelis were arguing, quietly, that the best outcome for Syria’s (then) 2 ½-year-old civil war, at least for the moment, was no outcome:

“For Jerusalem, the status quo, horrific as it may be from a humanitarian perspective, seems preferable to either a victory by Mr. Assad’s government and his Iranian backers or a strengthening of rebel groups, increasingly dominated by Sunni jihadis.

“‘This is a playoff situation in which you need both teams to lose, but at least you don’t want one to win, we’ll settle for a tie,’ said Alon Pinkas, a former Israeli consul general in New York. ‘Let them both bleed, hemorrhage to death: that’s the strategic thinking here. As long as this lingers, there’s no real threat from Syria.’”

Clear enough? If this is the way Israel’s leaders continue to regard the situation in Syria, then they look on deeper U.S. involvement overt or covert as likely to ensure that there is no early resolution of the conflict there. The longer Sunni and Shia are killing each other, not only in Syria but also across the region as a whole, the safer Tel Aviv’s leaders calculate Israel is.

Favoring Jihadis

But Israeli leaders have also made clear that if one side must win, they would prefer the Sunni side, despite its bloody extremists from Al-Qaeda and the Islamic State. In September 2013, shortly after Rudoren’s article, Israeli Ambassador to the United States Michael Oren, then a close adviser to Israeli Prime Minister Benjamin Netanyahu, told the Jerusalem Post that Israel favored the Sunni extremists over Assad.

“The greatest danger to Israel is by the strategic arc that extends from Tehran, to Damascus to Beirut. And we saw the Assad regime as the keystone in that arc,” Oren said in an interview. “We always wanted Bashar Assad to go, we always preferred the bad guys who weren’t backed by Iran to the bad guys who were backed by Iran.” He said this was the case even if the “bad guys” were affiliated with Al-Qaeda.

In June 2014, Oren then speaking as a former ambassador said Israel would even prefer a victory by the Islamic State, which was massacring captured Iraqi soldiers and beheading Westerners, than the continuation of the Iranian-backed Assad in Syria. “From Israel’s perspective, if there’s got to be an evil that’s got to prevail, let the Sunni evil prevail,” Oren said.

Netanyahu sounded a similar theme in his March 3, 2015 speech to the U.S. Congress in which he trivialized the threat from the Islamic State with its “butcher knives, captured weapons and YouTube” when compared to Iran, which he accused of “gobbling up the nations” of the Middle East.

That Syria’s main ally is Iran with which it has a mutual defense treaty plays a role in Israeli calculations. Accordingly, while some Western leaders would like to achieve a realistic if imperfect settlement of the Syrian civil war, others who enjoy considerable influence in Washington would just as soon see the Assad government and the entire region bleed out.

As cynical and cruel as this strategy is, it isn’t all that hard to understand. Yet, it seems to be one of those complicated, politically charged situations well above the pay-grade of the sophomores advising President Obama who, sad to say, are no match for the neocons in the Washington Establishment. Not to mention the Netanyahu-mesmerized Congress.

Corker Uncorked

Speaking of Congress, a year after Rudoren’s report, Sen. Bob Corker, R-Tennessee, who now chairs the Senate Foreign Relations Committee, divulged some details about the military attack that had been planned against Syria, while lamenting that it was canceled.

In doing so, Corker called Obama’s abrupt change on Aug. 31, 2013, in opting for negotiations over open war on Syria, “the worst moment in U.S. foreign policy since I’ve been here.” Following the neocon script, Corker blasted the deal (since fully implemented) with Putin and the Syrians to rid Syria of its chemical weapons.

Corker complained, “In essence I’m sorry to be slightly rhetorical we jumped into Putin’s lap.” A big No-No, of course especially in Congress to “jump into Putin’s lap” even though Obama was able to achieve the destruction of Syria’s chemical weapons without the United States jumping into another Middle East war.

It would have been nice, of course, if General Clark had thought to share his inside-Pentagon information earlier with the rest of us. In no way should he be seen as a whistleblower.

At the time of his September 2007 speech, he was deep into his quixotic attempt to win the Democratic nomination for president in 2008. In other words, Clark broke the omerta code of silence observed by virtually all U.S. generals, even post-retirement, merely to put some distance between himself and the debacle in Iraq and win some favor among anti-war Democrats. It didn’t work, so he endorsed Hillary Clinton; that didn’t work, so he endorsed Barack Obama.

Wolfowitz, typically, has landed on his feet. He is now presidential hopeful Jeb Bush’s foreign policy/defense adviser, no doubt outlining his preferred approach to the Middle East chessboard to his new boss. Does anyone know the plural of “bedlam?”

Ray McGovern works for Tell the Word, a publishing arm of the ecumenical Church of the Saviour in inner-city Washington. He served for a total of 30 years as an Army infantry/intelligence officer and CIA analyst and is a member of the Steering Group of Veteran Intelligence Professionals for Sanity (VIPS).


ThreadRacer

ThreadRacer is a simple CPU benchmark utility designed to test the relative performance of CPU cores. Simultaneous Multi-Threading (SMT) for AMD, and Hyper-Threading (HT) on Intel, accelerates processing by sharing select CPU units between two logical cores, or threads. This means that every pair of CPU cores has shared computational units and cache(s). This can impact performance. Threads should be loaded on distinct CPU core sets before their pairs are utilized, something all modern OSes are aware of. In some cases, it is still preferable to manually disable SMT/HT so that threads are forced to execute on more optimal CPU cores. Process Lasso can disable SMT/HT on a per-process basis by using staggered CPU affinities.


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Twenty-fourth Sunday in Ordinary Time, 16th September

Mark
8:27–35

Jesus
went on with his disciples to the villages of Caesarea Philippi; and on the way
he asked his disciples, “Who do people say that I am?” And they answered him, “John
the Baptist; and others, Elijah; and still others, one of the prophets.” He
asked them, “But who do you say that I am?” Peter answered him, “You are the
Messiah.” And he sternly ordered them not to tell anyone about him. Then he
began to teach them that the Son of Man must undergo great suffering, and be
rejected by the elders, the chief priests, and the scribes, and be killed, and
after three days rise again. He said all this quite openly. And Peter took him
aside and began to rebuke him. But turning and looking at his disciples, he
rebuked Peter and said, “Get behind me, Satan! For you are setting your mind
not on divine things but on human things.” He called the crowd with his
disciples, and said to them, “If any want to become my followers, let them deny
themselves and take up their cross and follow me. For those who want to save
their life will lose it, and those who lose their life for my sake, and for the
sake of the gospel, will save it.”

Commentary

St. Mark recorded two incidents in
Jesus’ public life. They both took place in Caesarea Philippi, which is a town
in the north-eastern corner of Palestine close to the border. It was rebuilt by
the Tetrarch Philip who added his name to the original town that had already
called after Caesar so as to distinguish it from another Caesarea on the west
coast of Palestine.

The first incident happened about a year
or more after Jesus’ public ministry. During the period, Jesus performed many
miracles in additional to preaching. There were a large crowd followed him,
apart from his apostles. Jesus knew that the crowd were forming some ideas
about him as to who he was, though such ideas might vary from one end of the
spectrum to another end.

For those people who had heard but not
met John the Baptist, it would be natural that they mistook him as John the
Baptist. However, one person might think Jesus being John the Baptist risen
from the dead was Herod because his conscience bore the guilt of John the
Baptist’s murder.

Some said Jesus was Elijah, the great
prophet of Israel. According to legend, he had been taken up to heaven and
would return again to prepare the way for the Messiah. Still some thought he
was one of the prophets who had taught their ancestors before. Up to this very
moment, no one knew Jesus is, except the demons. But they were ordered by Jesus
to keep silent about his identity.

Then Jesus asked his apostles: “But who
do you say that I am?” Through their leader, Peter, they proclaimed their
belief in him as the promised Messiah. It was interesting at this point because
Jesus ordered them to remind silent about who he was. Such an order was
necessary because the apostles though knew who he was they had no idea what
this title meant. This would soon be shown in the second incident. Jesus would
like them to learn the real meaning of Messiah until they witnessed his
crucifixion and resurrection.

But first, he corrected their idea of
Messiah by saying that he was not to reign on earth as a glorious and
triumphant king, rather he was to suffer many things and finally be put to
death. In fact, he was the suffering servant foretold by prophet Isaiah.
Nevertheless, Jesus concluded that eventually he would triumph because death
would not hold him and he would rise again after three days.

Although Jesus made it plain about his suffering,
death and resurrection, his apostles did not understand much. How could this
man who performed miracles right in front their own eyes be so powerless? How
could dead man rise again? All these questions puzzled them. Peter would not
accept this and told Jesus he should not admit the prediction he had made.

Jesus told Peter to back down because
his idea was opponent to God’s plan, which was laid down in the prophecies of
the second-Isaiah that is the first reading of today’s liturgy of Word. Peter
and his companions took a very human outlook on God’s purpose in sending the
Messiah. Today, we may still hold this very human outlook on God’s purpose of
his salvation.

Jesus’ suffering, death and resurrection
set us an example that true Christian life demands that one is ever ready to
sacrifice one’s own convenience and pleasure if the gospel so demands. From the
very beginning, the Christian Church saw the cross, from being a scandal the
cross became the emblem and the proud standard of God’s love for mankind, as
the symbol of Christ’s redemptive action – something every Christian should be
ready to imitate. Amen.


Scare up a wickedly good time with these macabre potions (no cauldron required).

By Kelly A. Magyarics

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Nothing quite says “Halloween” like the color black. Even cocktails are looking spooky this month, with bartenders adding crushed black sesame seeds, squirts of squid ink and sprinkles of activated charcoal to feed into the holiday’s eerie vibe. This Halloween scare up a wickedly good time with these macabre potions (no cauldron required).

Ursula, the half-human, half-octopus villainess from Disney’s The Little Mermaid, was the inspiration for this ocean potion. A swirl of squid ink evokes the opaque ink that Ursula emits when she’s angry, and the glass’s shape mirrors the hurricane of destruction that the dark witch of the sea causes in her final battle.

“For Halloween, we wanted to have a little fun and dip into our darker side,” says Renee Reardon, manager of Food Wine & Co. “Black cocktails are anything but ordinary, and represent the Halloween spirit.”

Rub the outside of a chilled cocktail glass with a lemon wedge, and then rim it with the brown sugar. Add the remaining ingredients, except the squid ink, to a cocktail shaker. Add ice, and shake vigorously until chilled. Strain into the prepared glass, add a few drops of squid ink and swirl it with a toothpick. Garnish with the squid tentacle.

This ominous-looking variation of the Hemingway Daiquiri is fitting for Halloween, “considering Hemingway’s jilted outlook on the world, not to mention the more obvious foreboding image that ‘Death Before Dinner’ evokes,” says Matt Allred, Zentan’s lead bartender. He alters the classic crowd-pleasing recipe by adding orgeat syrup to round out the sweetness. Citrus juice infused with activated charcoal gives it a dark, gunmetal grey color.

An interpretation of a sesame-driven Japanese dessert in liquid form, Zentan’s drink gets depth (and color) from syrup made from black sesame seeds.

“Charcoal reinforces the black color of the sesame seeds and makes for a pretty aesthetic, especially as a canvas for the garnish,” says former bar manager Jon Harris, who created the drink. Though strawberry adds an accent, the sip is more foreboding and savory than fruity or sweet, making it both a trick and a treat.

Add all ingredients to a cocktail glass. Add ice, and shake vigorously until chilled. Strain into a chilled cocktail glass. Garnish with edible flowers sprinkled on top.

For the sesame-strawberry syrup:
Bring ¼ cup chopped strawberries and 1 cup water to a boil in a medium saucepan. Reduce the heat to medium, and add 2 cups of sugar. Simmer until the syrup clarifies and the sugar is dissolved. Remove from heat and let cool. Strain out the strawberries, and pour the syrup into a blender. Add 4 teaspoons of toasted black sesame seeds and blend the mixture on high until the seeds are pulverized. Let the syrup cool, and strain out the sesame seeds. Store in the refrigerator until needed.

The somber tones of artist Joseph Beuy’s images stirred fellow artist and mixologist Ektoras Binikos to recreate them in a cocktail. Activated charcoal is purely for aesthetics, but the best-selling drink gets floral and herbal undertones from muddled shiso leaves and Bergamot bitters.

“As a mixologist and visual artist, I have this idea that my cocktails are components of a large social sculpture,” says Binikos. The drink’s drab and gloomy appearance belies its fitting festivity at a Halloween soirée.

Wet the outside rim of a cocktail glass and roll it in the smoked sea salt to rim it.

In a cocktail shaker, muddle the lime wedges, 1 shiso leaf, the simple syrup and the mastiha water. Add the vodka, Becherovka, juices, citrus bitters, zest and activated charcoal powder to the shaker. Add ice and shake vigorously until chilled. Strain the drink into the prepared highball glass, and top with 2 shiso leaves and 2–3 drops of the Bergamot bitters.

Todd Thrasher, a partner at PX and its beverage director, was tired of guests requesting dirty martinis with stuffed blue-cheese olives, so he came up with this version that’s anything but clichéd and murky. He infuses Dolin Blanc Vermouth with a tablespoon of squid ink.

“It’s dark and dramatic, and perfect to serve up at a Halloween party when a regular martini needs to be a little more spooky and festive,” says Thrasher.

Everything on the menu at this South American restaurant is smoked or touches the flame. Smoked tomato juice and a charred chili pepper give mouthwatering savory notes to the brunch eye-opener whose name translates to “panther.” It gets a facelift with a briny mixture of fish stock and a dash of squid ink.

For the applewood-smoked tomato juice:
Pour applewood chips into a smoker box, set on a grill and preheat to medium. Pour tomato juice into a shallow bowl or pan, set it on the grill and smoke for 20 minutes, or until desired flavor is achieved. (A stovetop smoker can also be used.)


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TODAY´S NEWS

STAR Plus completes fourth year of leadership

Since the last four years STAR Plus has been playing a good innings of 200 weeks of continuous lead, and surging ahead with shows that cater to three generations, making TV viewing a family phenomenon. STAR Plus shows have also been high on the rating cards for four consecutive years, dominating the top slot.

In these four years, some of the shows on the channel have earned phenomenal success across the country, pushing competition to a far second with high TVRs and increasing eyeballs. STAR shows like ‘Kyunki Saas Bhi Kabhi Bahu Thi’, ‘Kahaani Ghar Ghar Kii’ and ‘Kasautii Zindagii Kay’ are continuing to command strong loyalty among Indian audience.

Delivering constant ratings around the 15 TVR mark, these shows generate channel shares of around 50 per cent. While these shows consolidate evening primetime for STAR, the channel has also worked in evolving other dayparts for Indian Television. Considering the immense popularity of the shows, STAR Plus first extended the primetime stretching to 11.30pm and now to midnight.

The channel has also brought in existence afternoon viewership, which too generates high TVRs of almost as much as 12 to 13. While the channel continues to bring in substantial female viewers, it has also proved to be a deliverer for male target as well. Kids programming too came in its present form with STAR initiatives like ‘Sonpari’, ‘Shaka Laka Boom Boom’, ‘Shararat’, ‘Sssshhh…Koi…Hai’ and ‘Hatim’.

The four years that STAR has witnessed post the launch of ‘Kaun Banega Crorepati’ has seen the channel evolve in various ways. What is perhaps the most important aspect of STAR’s growth is that this growth has signified newer heights for the general entertainment and created new benchmarks on Indian television.


786 F.2d 1163
Unpublished DispositionNOTICE: Sixth Circuit Rule 24(c) states that citation of unpublished dispositions is disfavored except for establishing res judicata, estoppel, or the law of the case and requires service of copies of cited unpublished dispositions of the Sixth Circuit.ESTA M. ADAMS, Plaintiff-Appellant,v.J.C. PENNEY COMPANY, INC., Defendant-Appellee.
85-3810
United States Court of Appeals, Sixth Circuit.
2/13/86

N.D.Ohio
APPEAL DISMISSED
ORDER
BEFORE:  MARTIN, KRUPANSKY and GUY, Circuit Judges.

1
This matter is before the Court on the motion to dismiss the appeal filed by the J.C. Penney Company, Inc., on November 20, 1985.  The appellant filed a response in opposition on January 13, 1986.  The appellant's response is untimely.  Rule 8(a), Rules of the Sixth Circuit, allows ten days from service of the motion to respond.

2
The appellant is appealing the district court order granting summary judgment in favor of the appellee.  The case was brought pursuant to the Age Discrimination in Employment Act, 29 U.S.C. Sec. 623(A) and the Rehabilitation Act, 29 U.S.C. Secs. 793-94.

3
The motion to dismiss is based on appellee's contention that the notice of appeal was filed late.  The judgment from which appellant seeks to appeal was filed on August 27, 1985; the notice of appeal was not filed until September 27, 1985.  The notice of appeal was one day late.  Pursuant to Rule 4(a)(1), Federal Rules of Appellate Procedure, appellant is required to have filed her notice of appeal within 30 days from entry of judgment.  This Court does not have jurisdiction to grant an extension of time.  Peake v. First National Bank and Trust Co. of Marquette, 717 F2d 1016 (6th Cir. 1983).

4
A motion for an extension of time must be filed in the district court.  Rule 4(a)(5), Federal Rules of Appellate Procedure.  The language of Federal Rule of Appellate Procedure 4(a)(5) 'requires that a motion for an extension of time to file a notice of appeal be filed not later than thirty days after the expiration of the original appeal time prescribed by the Rule.'  Pryor v. Marshall, 711 F.2d 63, 64 (6th Cir. 1983).

5
For the foregoing reasons, it is ORDERED that the appeal be and hereby is dismissed.