Prion Protein Is a Key Determinant of Alcohol Sensitivity through the Modulation of N-Methyl-D-Aspartate Receptor (NMDAR) Activity

The prion protein (PrP) is absolutely required for the development of prion diseases; nevertheless, its physiological functions in the central nervous system remain elusive. Using a combination of behavioral, electrophysiological and biochemical approaches in transgenic mouse models, we provide strong evidence for a crucial role of PrP in alcohol sensitivity. Indeed, PrP knock out (PrP−/−) mice presented a greater sensitivity to the sedative effects of EtOH compared to wild-type (wt) control mice. Conversely, compared to wt mice, those over-expressing mouse, human or hamster PrP genes presented a relative insensitivity to ethanol-induced sedation. An acute tolerance (i.e. reversion) to ethanol inhibition of N-methyl-D-aspartate (NMDA) receptor-mediated excitatory post-synaptic potentials in hippocampal slices developed slower in PrP−/− mice than in wt mice. We show that PrP is required to induce acute tolerance to ethanol by activating a Src-protein tyrosine kinase-dependent intracellular signaling pathway. In an attempt to decipher the molecular mechanisms underlying PrP-dependent ethanol effect, we looked for changes in lipid raft features in hippocampus of ethanol-treated wt mice compared to PrP−/− mice. Ethanol induced rapid and transient changes of buoyancy of lipid raft-associated proteins in hippocampus of wt but not PrP−/− mice suggesting a possible mechanistic link for PrP-dependent signal transduction. Together, our results reveal a hitherto unknown physiological role of PrP on the regulation of NMDAR activity and highlight its crucial role in synaptic functions

Dielectric and pyroelectric properties of sintered discs of sodium meta vanadate

The dielectric and pyroelectric properties of poled and unpoled sintered discs of sodium meta vanadate were investigated in the temperature range from room temperature to 450°C. Dielectric constant and loss tangent anomalies were found around 375–390°C, while in pyroelectric coefficient, two anomalies were noticed at 250±25°C and 360±50°C respectively

GIS based Development of MCDM Model for Flood Risk Management across Godavari Lower Sub-Basin of India

&amp;lt;p&amp;gt;&amp;lt;strong&amp;gt;Abstract: &amp;lt;/strong&amp;gt;Because of the uncertainty and high cost involved, the Absolute Flood Protection has not been considered as a rational decision. Hence the trend is to replace Absolute Flood Protection strategy by Flood Risk Management Strategy. This Paper focus on the development of Multiple Criteria Decision Making (MCDM) model towards Flood Risk Management (FRM) across Godavari Lower Sub-Basin of India using GIS based methodologies for Flood Hazard Zonation in order to achieve global minimum of the Flood predicted Risk level.&amp;amp;#160; Flood Hazard Zone Map for the historical flood events obtained with the use of GIS based Digital Elevation Models across the study area have been presented and used for the estimation of Hazard Risk. Uncertainty (or Control) Risk levels of each Flood estimated using various Flood Forecasting methodologies have been compared for the selected locations of the study area. Effectiveness of Passive Flood Protection Measures in the form of Flood Levees has been quantitatively analyzed for the increase in the Opportunity Risk and corresponding reduction in the Flood Hazard Risk. Various types of Multi-Objective Evolutionary Algorithms (MOEAs) have been used&amp;amp;#160; to determine a Compromise solution with conflicting criteria between Hazard Risk and Opportunity (or Investment) Risk and the results were compared for each of the selected levels of Flood estimated with corresponding uncertainty. Traditional optimization method in the form of Pareto-Optimal Front have also been graphically depicted for the minimization of both Hazard Risk Objective function and Opportunity Risk Objective Function and compared with those obtained using MOEAs. Watershed wise distribution of optimized Flood Risk variation across the Sub-basin has been presented graphically for both the cases of with and without active Flood Routing Measures. &amp;lt;strong&amp;gt;Keywords:&amp;amp;#160; &amp;lt;/strong&amp;gt;Flood Risk Management; GIS based Flood Hazard Zonation; Multi-Criteria Decision Making; Multi-Objective Evolutionary Algorithms; Godavari Lower Sub-Basin of India;&amp;lt;/p&amp;gt; </jats:p

Computer modeling for the operation optimization of mula reservoir, upper Godavari Basin, India, using the Jaya Algorithm

In this paper, an application of the Jaya Algorithm (JA) is presented, to develop an operation optimization model for the Mula reservoir, located on the upper Godavari Basin, in India. The mentioned algorithm is a relatively new optimization technique, which is algorithm-specific and parameterless. In JA, there is no need for algorithm-specific parameter tuning, unlike with other heuristic techniques. To test its applicability, the model performance has been compared with that of other models for hypothetical four reservoir system studies available in the literature. Simulations for hypothetical four reservoir system have proven that JA is a better solution for a number of Function Evaluations when compared with the results obtained by means of other evolutionary methods such as Genetic Algorithms, Particle Swarm Optimization, Elitist Mutated Particle Swarm Optimization, and Weed Optimization Algorithm models reported in previous studies. Simulations have been carried out for real time operation of the Mula reservoir, and have revealed its superior performance when comparing the water releases proposed by it and the ones proposed by existing policy. Hence, from the two case studies presented, it can be concluded that the JA has potential in the field of reservoir operation and can be further explored to operation optimization of existing multi-reservoir system, with lower computations.Science and Engineering Research Board | Ref. ECR/2016/00140

Changes in valency state of ions in CuMn<SUB>2</SUB>O<SUB>4</SUB> at high temperatures

Thin films of copper manganite with three different molar ratios of CuratioMn viz 1:1, 1:2 and 1:3 have been deposited on quartz plates. The electrical conductivity of these thin films has been studied as a function of temperature. The energy of activation for electrical conduction in these compounds is found to increase from 0.20 eV to about 0.62 eV above 600&#176; K. Differential thermal analysis of bulk sample of copper manganite also shows a small endothermic change at 600&#176; K, while thermogravimetric analysis does not show any change in weight. It has been concluded from these results that the stable form of the ionic configuration of copper manganite at low temperatures, i.e. Cu1+[Mn3+Mn4+]O4 changes at high temperatures to Cu2+[Mn2 3+]O4

Proposition of New Metaphor-Less Algorithms for Reservoir Operation

Based on the current water crisis scenario, effective water resources management can play an essential role. Reservoir operation optimization is part of water resources management. Reservoir operation optimization is difficult as it involves a large number of variables and constraints to achieve this goal. The present study aims at exploring the performance of recently developed heuristic algorithms—Rao algorithms as applied to the reservoir operation studies for the first time. Rao algorithms are metaphor-less algorithms that require only basic parameters—population size and function evaluations. In the present study, Rao algorithms have been applied to two case studies: discrete four-reservoir operation system problem and continuous four-reservoir operation system problem (benchmark problems) for the assessment of their performance vis-à-vis other algorithms from the literature. The results showed that the Rao-1 algorithm provided the optimal solution with the least function evaluations when compared to Rao-2, Rao-3, and other algorithms applied in the past to the same benchmark problem. Consequently, the Rao-1 model is found to be superior to these approaches by taking less computational time. Hence, the Rao-1 algorithm can be considered suitable for application to reservoir operation optimization problems

Proposition of New Metaphor-Less Algorithms for Reservoir Operation

Based on the current water crisis scenario, effective water resources management can play an essential role. Reservoir operation optimization is part of water resources management. Reservoir operation optimization is difficult as it involves a large number of variables and constraints to achieve this goal. The present study aims at exploring the performance of recently developed heuristic algorithms—Rao algorithms as applied to the reservoir operation studies for the first time. Rao algorithms are metaphor-less algorithms that require only basic parameters—population size and function evaluations. In the present study, Rao algorithms have been applied to two case studies: discrete four-reservoir operation system problem and continuous four-reservoir operation system problem (benchmark problems) for the assessment of their performance vis-à-vis other algorithms from the literature. The results showed that the Rao-1 algorithm provided the optimal solution with the least function evaluations when compared to Rao-2, Rao-3, and other algorithms applied in the past to the same benchmark problem. Consequently, the Rao-1 model is found to be superior to these approaches by taking less computational time. Hence, the Rao-1 algorithm can be considered suitable for application to reservoir operation optimization problems.</jats:p