Averaging Transformations of Synaptic Potentials on Networks

The problem of the transformation of microscopic information to the macroscopic level is an intriguing challenge in computational neuroscience, but also of general mathematical importance. Here, a phenomenological mathematical model is introduced that simulates the internal information processing of brain compartments. Synaptic potentials are integrated over small number of realistically coupled neurons to obtain macroscopic quantities. The striatal complex, an important part of the basal ganglia circuit in the brain for regulating motor activity, has been investigated as an example for the validation of the model

The Predominance of Electric Transport in Synaptic Transmission

The quantitative description of the motion of neurotransmitters in the synaptic cleft appears to be one of the most difficult problems in the modeling of synapses. Here we show in contradiction to the common view, that this process is merely governed by electric transport than diffusion forces

On the Achievable Rates of Pairwise Multiway Relay Channels

In this paper, we study the effect of users' transmission ordering on the common rate and sum rate of pairwise multiway relay channels (MWRCs) with functional-decode-forward strategy. To this end, we first develop a graphical model for the data transmission in a pairwise MWRC. Using this model, we then find the optimal orderings that achieve the maximum common rate and sum rate of the system. The achieved maximum common and sum rate are also found. Moreover, we show that the performance gap between optimal orderings and a random ordering vanishes when SNR increases. Computer simulations are presented for better illustration of the results.Comment: Extended version of "On the Achievable Rates of Pairwise Multiway Relay Channels" accepted for ISIT 201

ATP Hysteresis in Tripartite Synapses

Recent experimental studies strongly suggest the influence of glial purinergic transmission in the modulation of synaptic dynamics. By releasing adenosine triphosphate (ATP), which accumulates as adenosine, astrocytes tonically suppressed synaptic transmission. The delayed multi-step feedback of the glial adenosine with the neuron suggest the existence of hysteresis phenomena, which are investigated in the present study from the theoretical point of view. The model suggests that a memory operator, tripartite synaptic plasticity, governs the mysterious delayed feedback inhibition caused by the action of adenosine on neuronal $A_1$ receptors and provides a powerful tool for further dynamical modeling tasks on tripartite synapses

Internet addiction and its relationship with anxiety, stress, depression and insomnia in nursing and midwifery

Background & Objectives: Internet addiction is one of the problems associated with the advancement of technology that affects people's mental health. The purpose of this study was to investigate the relationship between addiction to the Internet and insomnia, anxiety, depression and stress in nursing and midwifery students of Bojnourd Islamic Azad University in 2017. Methods: This descriptive-analytical study was conducted on 250 nursing and midwifery students of Bojnourd Islamic Azad University which were selected by stratified random sampling method. Data collection was done using demographic information, Young's Internet addiction, Insomnia (ISI), and Anxiety, Depression and Stress Questionnaire (DASS21). Data were analyzed by statistical test of one-way ANOVA and analyzed using SPSS-16 software. Results: 76% of female students were female and 53.2% were nursing students. The mean of Internet addiction score in students was 31.14 and 6.7% of them had Internet addiction. Also, the mean score of anxiety, stress, depression and insomnia was 12.54, 23.37, 17.12 and 14.56. There was a significant relationship between addiction to the Internet with anxiety, stress, depression and insomnia (P˂0.001). Conclusion: Considering the prevalence of Internet addiction among students, and its significant relationship with depression, anxiety, stress and insomnia in them, plans must be made to prevent this health problem. Key¬words: Internet addiction, depression, insomnia, anxiety, stress

Signal detection in extracellular neural ensemble recordings using higher criticism

Information processing in the brain is conducted by a concerted action of multiple neural populations. Gaining insights in the organization and dynamics of such populations can best be studied with broadband intracranial recordings of so-called extracellular field potential, reflecting neuronal spiking as well as mesoscopic activities, such as waves, oscillations, intrinsic large deflections, and multiunit spiking activity. Such signals are critical for our understanding of how neuronal ensembles encode sensory information and how such information is integrated in the large networks underlying cognition. The aforementioned principles are now well accepted, yet the efficacy of extracting information out of the complex neural data, and their employment for improving our understanding of neural networks, critically depends on the mathematical processing steps ranging from simple detection of action potentials in noisy traces - to fitting advanced mathematical models to distinct patterns of the neural signal potentially underlying intra-processing of information, e.g. interneuronal interactions. Here, we present a robust strategy for detecting signals in broadband and noisy time series such as spikes, sharp waves and multi-unit activity data that is solely based on the intrinsic statistical distribution of the recorded data. By using so-called higher criticism - a second-level significance testing procedure comparing the fraction of observed significances to an expected fraction under the global null - we are able to detect small signals in correlated noisy time-series without prior filtering, denoising or data regression. Results demonstrate the efficiency and reliability of the method and versatility over a wide range of experimental conditions and suggest the appropriateness of higher criticism to characterize neuronal dynamics without prior manipulation of the data

Minimizing the total tardiness and makespan in an open shop scheduling problem with sequence-dependent setup times

We consider an open shop scheduling problem with setup and processing times separately such that not only the setup times are dependent on the machines, but also they are dependent on the sequence of jobs that should be processed on a machine. A novel bi-objective mathematical programming is designed in order to minimize the total tardiness and the makespan. Among several multi-objective decision making (MODM) methods, an interactive one, called the TH method is applied for solving small-sized instances optimally and obtaining Pareto-optimal solutions by the Lingo software. To achieve Pareto-optimal sets for medium to large-sized problems, an improved non-dominated sorting genetic algorithm II (NSGA-II) is presented that consists of a heuristic method for obtaining a good initial population. In addition, by using the design of experiments (DOE), the efficiency of the proposed improved NSGA-II is compared with the efficiency of a well-known multi-objective genetic algorithm, namely SPEA-II. Finally, the performance of the improved NSGA-II is examined in a comparison with the performance of the traditional NSGA-II

Optimizing the co-feeding strategy of Persian sturgeon (Acipenser persicus) larvae using Artemia nauplii and formulated diet

High mortality and labor costs are associated with first-feeding sturgeon culture, particularly during the period of dietary transition from live to formulated feed. Therefore we investigated the effects of various feeding treatments on the survival and growth of the Persian sturgeon (Acipenser persicus) larvae during a 20-day culture period. Three replicate groups (250 fish/replicate) of first-feeding larvae were fed according to four main feeding regimes: (1) live food (live nauplii of brine shrimp Artemia urmiana); (2) indirect transition (5 days live food followed by gradual transition to formulated diet); (3) direct transition (using different combinations of live and formulated diet from the start feeding onwards); (4) formulated feed (FD) from the start feeding. Results indicated that growth and survival were higher in the indirect transition feeding regime than in other regimes. Based on our study, co-feeding of A. persicus should start five days after prior feeding with live food

Mathematical Modelling of the Neurochemical Processes in Schizophrenia

Schizophrenia is an endogenous psychosis with a 1 \% prevalence in world population. Several pharmacological studies suggest that alterations in the function of different neurotransmitter systems such as dopamine or glutamate are related to schizophrenic symptoms. This thesis represents mathematical models that are constructed to investigate the dynamical behaviour of the neurochemical systems in the human brain. These models formulate the anatomical properties and physiological processes of synapses, single brain compartments and large neurochemical pathways involved in the regulation of behaviour such as the basal ganglia and the limbic system. The interaction between the neurochemical systems and the electrophysiological activities are considered by modelling in different scales. In the synaptic scale, it has been shown that the transport of neurotransmitters in the synaptic cleft is merely governed by electrical forces than diffusion. The intra-synaptic concentration of neurotransmitters is modelled using partial differential equations and is coupled to the Hodgkin-Huxley equation (neurochemical modification) to model the effect of neurotransmitter-receptor binding in the generation of post-synaptic potentials. Considering the morphological and ultra-morphological studies of brain compartments, the averaged electrophysiological activity is modelled by integral equations respecting these internal structures. A system comprised by nonlinear delay differential equations is constructed to simulate the dynamical behaviour of neurochemical concentrations, coupled to the local electrophysiological activity of the compartments, on the brain pathways. By parameter sensitivity analysis, we have also investigated qualitatively the influence of certain anti-psychotic agents. Synchronized oscillations are experienced in electrophysiological systems. The neurotransmitter concentrations also demonstrate an oscillatory behaviour. The resulting oscillatory dynamics of these processes reveals a profound view on the relation between the dynamical behaviour of the neurochemical systems and the occurrence of psychotic states. These facts led us to establish a hypothesis on this relation, called the oscillation hypothesis of psychosis. Because of the general formulation of the models, these are not only useful for schizophrenia, but also for the investigations of other neurological diseases

Effective Factors on Project Management Performance in Small and Medium Enterprises

The purpose of this paper is to focus on project management performance through absorptive capacity and dynamic capabilities. Project management (PM) considers as an attempt of a particular team of professional members working together to combine proper techniques through appropriate managerial procedures to accomplish a project with perseverance on delivering at the right time. Since firm capabilities including absorptive capacity and dynamic capabilities are believed to be a behavioral orientation toward integration and recreation of the resources which could be associates with the performance of projects in companies, according to such great significances, it is worth to investigate how to manage them and support their impact on the businesses. This study presents a conceptual framework for the importance of effective factors to enhance project management performance. Key words: Absorptive Capacity, Dynamic Capabilities, Project Managemen