this study was designed to compare the effectiveness of different activation treatments for activation of in vitro matured oocytes and their developmental potency in mcr2aa medium so as to obtain maximum number of embryos. a total of 1090 cumulus oocyte complexes (coc’s) were collected from 480 ovaries. in vitro matured oocytes were randomly divided into four groups. group 1 in vitro matured oo...

the goal of this study was to determine the effects of the l-type calcium channel blockers verapamil and diltiazem on the currents of voltage-gated potassium channel (fkv1.4δn), an n-terminal-deleted mutant of the ferret kv1.4 potassium channel. measurements were made using a two electrode voltage clamp technique with channels expressed stably in xenopus oocytes. the fkv1.4δn currents displayed...

A method to convert real number partitioned activation function into complex number one is provided. The method has 4em variations; 1 has potential to get holomorphic activation, 2 has potential to conserve complex angle, and the last 1 guarantees interaction between real and imaginary parts. The method has been applied to LReLU and SELU as examples. The complex number activation function is an...

We analyze in detail the performance of a Hamming network classifying inputs that are distorted versions of one of its m stored memory patterns. The activation function of the memory neurons in the original Hamming network is replaced by a simple threshold function. The resulting Threshold Hamming Network (THN) correctly classifies the input pattern, with probability approaching 1, using only O...

A number of studies have questioned the validity of the Quickprop algorithm and the activation function derivative offset as appropriate methods of speeding backpropagation style training. This paper follows on from those results with a practical study using generated data sets. The generation method is briefly presented, along with the results of comparisons which indicate, at least on these d...

Most existing graph-based parsing models rely on millions of hand-crafted features, which limits their generalization ability and slows down the parsing speed. In this paper, we propose a general and effective Neural Network model for graph-based dependency parsing. Our model can automatically learn high-order feature combinations using only atomic features by exploiting a novel activation func...

We compare activation functions in terms of the approximation power of their feedforward nets We consider the case of analog as well as boolean input

Any single-hidden-layer feedforward network based on Gaussian or asymptotically constant odd or even rational non-polynomial activation functions has the same property as such networks based on hyperbolic tangent: input-output function determines weights and biases up to a permutation of the hidden units and sign-flips.

This paper presents a new model of an artificial immune network which is strongly based on the repertoire completeness assumption. The model is different from previous approaches in that it eliminates the genetic search achieved by most of the current immune network models. Instead on focusing on developing new B cells which better fit the data, the new model focuses on regulating the size of e...