Spike patterns are among the most common electrophysiological descriptors of neuron types. Surprisingly, it is not clear how the diversity in firing patterns of the neurons in a network affects its activity dynamics. Here, we introduce the state-dependent stochastic bursting neuron model allowing for a change in its firing patterns independent of changes in its input-output firing rate relation...

The impact of financial challenges on the profit of a supply chain, have caused the researcher to model the supply chain network by considering the operational and financial dimensions. Also, the establishment of a closed loop supply chain (CLSC) network has a high effect on economic profit. So, the purpose of this study is to design a stochastic closed loop supply chain network by considering ...

Signal transduction within biological cells is governed by networks of interacting proteins. Communication between these proteins is mediated by signaling molecules which bind to receptors and induce stochastic transitions between different conformational states. Signaling is typically a cooperative process which requires the occurrence of multiple binding events so that reaction rates have a n...

The development of optimization and mathematical models for closed loop supply chain (CLSC) design has attracted considerable interest over the past decades. However, the uncertainties that are inherent in the network design and the complex interactions among various uncertain parameters are challenging the capabilities of the developed tools. The aim of this paper, therefore, is to propose a n...

abstract the aim of this study was to selecting the suitable model for forecast land, production and price of sugar beet in iran. for this purpose, models applied to forecast are arima, single and double exponential smoothing, harmonic, artificial neural network and arch for period 1993-2008. results of durbin-watson tests, land, production and price of sugar beet series were found non stochast...

the paper discusses the current state of research concerning railway network timetabling and traffic management. timetable effectiveness is governed by frequency, regularity, accurate running, recovery and layover times, as well as minimal headway, buffer times and waiting times. analytic (queuing) models and stochastic microsimulation are predominantly used for estimation of waiting times and ...

in this study, a robust controller is designed for fuzzy network control systems (ncss) using the static output feedback. delay and data packet dropout affect on the stability of network control systems, and therefore, the asymptotic stability condition is established considering delay and data packet dropout. delay is time-varying while the lower and upper bounds for delay is defined, and the ...

Many cellular processes involve a small number of molecules and undergo stochastic fluctuations in their levels of activity. Cerebellar long-term depression (LTD) is a form of synaptic plasticity expressed as a reduction in the number of synaptic AMPA receptors (AMPARs) in Purkinje cells. We developed a stochastic model of the LTD signaling network, including a PKC-ERK-cPLA(2) positive feedback...

We study a stochastic synchronization of spiking activity in feedforward networks of integrate-and-fire model neurons. A stochastic mean field analysis shows that synchronization occurs only when the network size is sufficiently small. This gives evidence that the dynamics, and hence processing, of finite size populations can be drastically different from that observed in the infinite size limi...

The expected value model and the chance-constrained programming model for unbalanced bidding problem are established on the condition that quantities of each activity are stochastic variables and the total project is finished smoothly in this paper. These models can make the unbalanced bidding price more reasonable and applicable. In order to solve these models, stochastic simulation, neural ne...