in recent years transdifferentiation technology has enabled direct conversion of human fibroblasts to become a valuable, abundant and accessible cell source for patient-specific induced cell generation in biomedical research. the majority of transdifferentiation approaches rely upon viral gene delivery which due to random integration with the host genome can cause genome instability and tumorig...

the aim followed in this study was to compare the performance of multiple regression vs neural network models to predict the activity of antioxidant enzymes super oxide dismutase (sod), cat alase (cat), ascorbate pero xidase (apx) and peroxidase (pox) in the shoots of wheat (triticum aestivum), alvand cultivar in a soil polluted with cadmium. the treatments consisted of four levels of cadmium (...

objective(s): nowadays much effort is being invested in order to diagnose the mechanisms involved in neural differentiation. by clarifying this, making desired neural cells in vitro and applying them into diverse neurological disorders suffered from neural cell malfunctions could be a feasible choice. thus, the present study assessed the capability of fetal brain extract (fbe) to induce rat bon...

fluoxetine is a common antidepressant which selectively inhibits serotonin reuptake at synaptic level. some research findings have proposed the effect this drug on neurogenesis, neuronal survival as well as proliferation of the neural progenitor cells. endometrium is a part of uterus which harbors mesenchymal stem cells. this source of stem cells can be differentiated into neural cells which ma...

background: in vitro simulation of developmental processes is an invaluable tool to shed light on the intrinsic mechanism of developmental biosystems such as central nervous system in mammals. chick somites have been used to simulate the neural differentiation of human neural progenitor cells. in the present study, we aimed to indicate whether somites have the ability to express required neural...

The paper deals with Data Envelopment Analysis (DEA) and Artificial Neural Network (ANN). We believe that solving for the DEA efficiency measure, simultaneously with neural network model, provides a promising rich approach to optimal solution. In this paper, a new neural network model is used to estimate the inefficiency of DMUs in large datasets.

the hybrid fuzzy differential equations have a wide range of applications in science and engineering. we consider the problem of nding their numerical solutions by using a novel hybrid method based on fuzzy neural network. here neural network is considered as a part of large eld called neural computing or soft computing. the proposed algorithm is illustrated by numerical examples and the resu...

in this paper, we introduce a hybrid approach based on neural network and optimization teqnique to solve ordinary differential equation. in proposed model we use heyperbolic secont transformation function in hiden layer of neural network part and bfgs teqnique in optimization part. in comparison with existing similar neural networks proposed model provides solutions with high accuracy. numerica...

The main contribution of the present paper is to train efficient neural networks for seismic design of double layer grids subject to multiple-earthquake loading. As the seismic analysis and design of such large scale structures require high computational efforts, employing neural network techniques substantially decreases the computational burden. Square-on-square double layer grids with the va...

Routing is one of the basic parts of a message passing multiprocessor system. The routing procedure has a great impact on the efficiency of a system. Neural algorithms that are currently in use for computer networks require a large number of neurons. If a specific topology of a multiprocessor network is considered, the number of neurons can be reduced. In this paper a new recurrent neural ne...