FIELD INVESTIGATIONS INTO HARMONICS POLLUTION AFFECTING TRANSFORMERS

Field investigations on harmonics caused by loads are essential to have a quantitative visualization and formation of premise of research. Field investigations have been carried out covering spectrum of loads and voltage levels right from generation to consumers, as at present. Investigations have revealed that low tension consumers form cluster of non-linear loads and are major contributors of current harmonics. Traction loads are another major category of harmonic pollutant. Industrial consumers do provide reactive compensation which helps to filter out current harmonics partially. However, in absence of any regulatory measure consumers keep polluting current harmonics into the system and also bear with the consequential disturbances. Voltage harmonics are significant only at leaf ends of distribution distribution system, where source impedance, seen by the harmonics generated by the load, is high. Tranasformer is the first major equipment in power system to intercept the harmonics. These harmonics caused accelerated ageing of transformers and even objectionable rise of temperature of cover-plate and turets

FIELD INVESTIGATIONS INTO HARMONICS POLLUTION AFFECTING TRANSFORMERS

Field investigations on harmonics caused by loads are essential to have a quantitative visualization and formation of premise of research. Field investigations have been carried out covering spectrum of loads and voltage levels right from generation to consumers, as at present. Investigations have revealed that low tension consumers form cluster of non-linear loads and are major contributors of current harmonics. Traction loads are another major category of harmonic pollutant. Industrial consumers do provide reactive compensation which helps to filter out current harmonics partially. However, in absence of any regulatory measure consumers keep polluting current harmonics into the system and also bear with the consequential disturbances. Voltage harmonics are significant only at leaf ends of distribution distribution system, where source impedance, seen by the harmonics generated by the load, is high. Tranasformer is the first major equipment in power system to intercept the harmonics. These harmonics caused accelerated ageing of transformers and even objectionable rise of temperature of cover-plate and turets

A calcium-based plasticity model for predicting long-term potentiation and depression in the neocortex

Pyramidal cells (PCs) form the backbone of the layered structure of the neocortex, and plasticity of their synapses is thought to underlie learning in the brain. However, such long-term synaptic changes have been experimentally characterized between only a few types of PCs, posing a significant barrier for studying neocortical learning mechanisms. Here we introduce a model of synaptic plasticity based on data-constrained postsynaptic calcium dynamics, and show in a neocortical microcircuit model that a single parameter set is sufficient to unify the available experimental findings on long-term potentiation (LTP) and long-term depression (LTD) of PC connections. In particular, we find that the diverse plasticity outcomes across the different PC types can be explained by cell-type-specific synaptic physiology, cell morphology and innervation patterns, without requiring type-specific plasticity. Generalizing the model to in vivo extracellular calcium concentrations, we predict qualitatively different plasticity dynamics from those observed in vitro. This work provides a first comprehensive null model for LTP/LTD between neocortical PC types in vivo, and an open framework for further developing models of cortical synaptic plasticity.We thank Michael Hines for helping with synapse model implementation in NEURON; Mariana Vargas-Caballero for sharing NMDAR data; Veronica Egger for sharing in vitro data and for clarifications on the analysis methods; Jesper Sjöström for sharing in vitro data, helpful discussions, and feedback on the manuscript; Ralf Schneggenburger for helpful discussions and clarifications on the NMDAR calcium current model; Fabien Delalondre for helpful discussions; Francesco Casalegno and Taylor Newton for helpful discussion on model fitting; Daniel Keller for helpful discussions on the biophysics of synaptic plasticity; Natali Barros-Zulaica for helpful discussions on MVR modeling and generalization; Srikanth Ramaswamy, Michael Reimann and Max Nolte for feedback on the manuscript; Wulfram Gerstner and Guillaume Bellec for helpful discussions on synaptic plasticity modeling. This study was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne, from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology. E.B.M. received additional support from the CHU Sainte-Justine Research Center (CHUSJRC), the Institute for Data Valorization (IVADO), Fonds de Recherche du Québec–Santé (FRQS), the Canada CIFAR AI Chairs Program, the Quebec Institute for Artificial Intelligence (Mila), and Google. R.B.P. and J.DF. received support from the Spanish “Ministerio de Ciencia e Innovación” (grant PGC2018-094307-B-I00). M.D. and I.S. were supported by a grant from the ETH domain for the Blue Brain Project, the Gatsby Charitable Foundation, and the Drahi Family Foundation

STEPS 4.0: Fast and memory-efficient molecular simulations of neurons at the nanoscale

Recent advances in computational neuroscience have demonstrated the usefulness and importance of stochastic, spatial reaction-diffusion simulations. However, ever increasing model complexity renders traditional serial solvers, as well as naive parallel implementations, inadequate. This paper introduces a new generation of the STochastic Engine for Pathway Simulation (STEPS) project (http://steps.sourceforge.net/), denominated STEPS 4.0, and its core components which have been designed for improved scalability, performance, and memory efficiency. STEPS 4.0 aims to enable novel scientific studies of macroscopic systems such as whole cells while capturing their nanoscale details. This class of models is out of reach for serial solvers due to the vast quantity of computation in such detailed models, and also out of reach for naive parallel solvers due to the large memory footprint. Based on a distributed mesh solution, we introduce a new parallel stochastic reaction-diffusion solver and a deterministic membrane potential solver in STEPS 4.0. The distributed mesh, together with improved data layout and algorithm designs, significantly reduces the memory footprint of parallel simulations in STEPS 4.0. This enables massively parallel simulations on modern HPC clusters and overcomes the limitations of the previous parallel STEPS implementation. Current and future improvements to the solver are not sustainable without following proper software engineering principles. For this reason, we also give an overview of how the STEPS codebase and the development environment have been updated to follow modern software development practices. We benchmark performance improvement and memory footprint on three published models with different complexities, from a simple spatial stochastic reaction-diffusion model, to a more complex one that is coupled to a deterministic membrane potential solver to simulate the calcium burst activity of a Purkinje neuron. Simulation results of these models suggest that the new solution dramatically reduces the per-core memory consumption by more than a factor of 30, while maintaining similar or better performance and scalability

Reconstruction and simulation of neocortical microcircuitry

We present a first-draft digital reconstruction of the microcircuitry of somatosensory cortex of juvenile rat. The reconstruction uses cellular and synaptic organizing principles to algorithmically reconstruct detailed anatomy and physiology from sparse experimental data. An objective anatomical method defines a neocortical volume of 0.29 ± 0.01 mm3 containing ∼31,000 neurons, and patch-clamp studies identify 55 layer-specific morphological and 207 morpho-electrical neuron subtypes. When digitally reconstructed neurons are positioned in the volume and synapse formation is restricted to biological bouton densities and numbers of synapses per connection, their overlapping arbors form ∼8 million connections with ∼37 million synapses. Simulations reproduce an array of in vitro and in vivo experiments without parameter tuning. Additionally, we find a spectrum of network states with a sharp transition from synchronous to asynchronous activity, modulated by physiological mechanisms. The spectrum of network states, dynamically reconfigured around this transition, supports diverse information processing strategies

Methanol and DME Economy in India

19-23Opportunities and challenges of converting biogas feedstocks to biomethanol

Eco-friendly Pest Management Using Monoterpenoids. I. Antifungal Efficacy of Thymol Derivatives

645-648Ether and ester derivatives of thymol, 5-methyl-2-(1-methyl ethyl) phenol, a natural monoterpenoid, were synthesized and antifungal potency against Aspergillus niger, Aspergillus oryzae, Fusarium oxysporum and Alternaria alternata was evaluated to study structure-activity relationships. Thymyl ethers showed better antifungal potency than esters in overall studies. The data suggested that in eight simple ethers and three esters, the addition of a methylene group or a carbon, an olefinic bond or an aromatic moiety in side chain led to compounds with improved potency over the parent compound, thymol. In case of the two dimer ethers and four esters, increasing the number of methylene groups had little effect on the antifungal potency with the exception of higher activities for dithymyl ethylene ether and dithymyl malonate