A comparison of activation functions in multilayer neural network for predicting the production and consumption of electricity power

Predicting electricity power is an important task, which helps power utilities in improving their systems’ performance in terms of effectiveness, productivity, management and control. Several researches had introduced this task using three main models: engineering, statistical and artificial intelligence. Based on the experiments, which used artificial intelligence models, multilayer neural networks model has proven its success in predicting many evaluation datasets. However, the performance of this model depends mainly on the type of activation function. Therefore, this paper introduces an experimental study for investigating the performance of the multilayer neural networks model with respect to different activation functions and different depths of hidden layers. The experiments in this paper cover the comparison among eleven activation functions using four benchmark electricity datasets. The activation functions under examination are sigmoid, hyperbolic tangent, SoftSign, SoftPlus, ReLU, Leak ReLU, Gaussian, ELU, SELU, Swish and Adjust-Swish. Experimental results show that ReLU and Leak ReLU activation functions outperform their counterparts in all datasets

Analyse de quelques algorithmes probabilistes à délais aléatoires

Dans la première partie de cette étude, nous proposons et analysons des algorithmes probabilistes d’élection uniforme dans des graphes de types arbres, les k-arbres et les polyominoïdes. Ces algorithmes utilisent des durées de vie aléatoires associées aux sommets découverts (sommets feuilles ou simpliciaux). Ces durées sont des variables aléatoires indépendantes et sont localement engendrées au fur et à mesure que les sommets sont découverts. Dans la seconde partie, nous analysons un algorithme probabiliste de synchronisation pour le problème de rendez-vous avec agendas dynamiques. L’objectif est de trouver un couplage maximal dans un graphe donné. Ensuite, nous proposons et étudions un modèle de diffusion à délai aléatoire pour la transmission d’un message dans un réseau. Finalement, dans la dernière partie, nous exposons les outils utilisés pour implémenter la simulation des algorithmes distribués.In the first part of this study, we propose and analyze a probabilistic algorithms of uniform election in graphs of structures of the trees type, k-trees and polyominoids. These algorithms use random delay associated to discovered vertices (leaf vertices or simplicial vertices). These delays are independent random variables and are locally generated as and when the vertices are discovered. In the second part, we analyze a probabilistic algorithm of synchronization for the problem of rendezvous with dynamic agendas. The goal is to find a maximal matching in a given graph. Then, we propose and study a model of diffusion with random delay for the transmission of a message in a network. Finally, in the last part, we expose the tools used to implement the simulation of the distributed algorithms

Stochastic Analysis of Mobile Ad-hoc Networks

Abstract The MANET networks (Mobile Ad-hoc Networks) are known by their dynamicity of nodes and they are without pre-existing infrastructure. To study this kind of networks, we modelled them by a Random Geometric Graphs (RGG). We show that this type of graph is the best adapted to represent such networks, and this shows that the RGG are able to catch the dynamicity properties. We study then the evolution of the network by a continuous-time birth-death Markov process

Quantitative evaluation of the beneficial effects in the mdx mouse of epigallocatechin gallate, an antioxidant polyphenol from green tea

In two separate previous studies, we reported that subcutaneous (sc) or oral administration of (−)-epigallocatechin-3-gallate (EGCG) limited the development of muscle degeneration of mdx mice, a mild phenotype model for Duchenne muscular dystrophy (DMD). However, it was not possible to conclude which was the more efficient route of EGCG administration because different strains of mdx mice, periods of treatment and methods of assessment were used. In this study, we investigated which administration routes and dosages of EGCG are the most effective for limiting the onset of dystrophic lesions in the same strain of mdx mice and applying the same methods of assessment. Three-week-old mdx mice were injected sc for 5 weeks with either saline or a daily average of 3 or 6 mg/kg EGCG. For comparison, age-matched mdx mice were fed for 5 weeks with either a diet containing 0.1% EGCG or a control diet. The effects of EGCG were assessed quantitatively by determining the activities of serum muscle-derived creatine kinase, isometric contractions of triceps surae muscles, integrated spontaneous locomotor activities, and oxidative stress and fibrosis in selected muscles. Oral administration of 180 mg/kg/day EGCG in the diet was found the most effective for significantly improving several parameters associated with muscular dystrophy. However, the improvements were slightly less than those observed previously for sc injection started immediately after birth. The efficacy of EGCG for limiting the development of dystrophic muscle lesions in mice suggests that EGCG may be of benefit for DMD patients

Down syndrome is an oxidative phosphorylation disorder

Down syndrome is the most common genomic disorder of intellectual disability and is caused by trisomy of chromosome 21. Several genes in this chromosome repress mitochondrial biogenesis. The goal of this study was to evaluate whether early overexpression of these genes may cause a prenatal impairment of oxidative phosphorylation negatively affecting neurogenesis. Reduction in the mitochondrial energy production and a lower mitochondrial function have been reported in diverse tissues or cell types, and also at any age, including early fetuses, suggesting that a defect in oxidative phosphorylation is an early and general event in Down syndrome individuals. Moreover, many of the medical conditions associated with Down syndrome are also frequently found in patients with oxidative phosphorylation disease. Several drugs that enhance mitochondrial biogenesis are nowadays available and some of them have been already tested in mouse models of Down syndrome restoring neurogenesis and cognitive defects. Because neurogenesis relies on a correct mitochondrial function and critical periods of brain development occur mainly in the prenatal and early neonatal stages, therapeutic approaches intended to improve oxidative phosphorylation should be provided in these periods.Funding sources: This work was supported by grants from Instituto de Salud Carlos III [FIS-PI17/00021, FIS-PI17/00166]; Fundación Mutua Madrileña [MMA17/01]; Precipita-FECYT crowdfunding program [PR194]; Gobierno de Aragón [LMP135_18, Grupos Consolidados B33_17R] and FEDER 2014–2020 “Construyendo Europa desde Aragón”. CIBERER is an initiative of the ISCIII

A genetic cause of Alzheimer disease: mechanistic insights from Down syndrome

Down syndrome, caused by an extra copy of chromosome 21, is associated with a greatly increased risk of early onset Alzheimer disease. It is thought that this risk is conferred by the presence of three copies of the gene encoding amyloid precursor protein (APP), an Alzheimer risk factor, although the possession of extra copies of other chromosome 21 genes may also play a role. Further study of the mechanisms underlying the development of Alzheimer disease in Down syndrome could provide insights into the mechanisms that cause dementia in the general population

DYRK1A Protein, A Promising Therapeutic Target to Improve Cognitive Deficits in Down Syndrome

Down syndrome (DS) caused by a trisomy of chromosome 21 (HSA21), is the most common genetic developmental disorder, with an incidence of 1 in 800 live births. Its phenotypic characteristics include intellectual impairment, early onset of Alzheimer’s disease, congenital heart disease, hypotonia, muscle weakness and several other developmental abnormalities, for the majority of which the pathogenetic mechanisms remain unknown. Among the numerous protein coding genes of HSA21, dual-specificity tyrosine-(Y)-phosphorylation-regulated kinase 1A (DYRK1A) encodes a proline-directed serine/threonine and tyrosine kinase that plays pleiotropic roles in neurodevelopment in both physiological and pathological conditions. Numerous studies point to a crucial role of DYRK1A protein for brain defects in patients with DS. Thus, DYRK1A inhibition has shown benefits in several mouse models of DS, including improvement of cognitive behaviour. Lastly, a recent clinical trial has shown that epigallocatechine gallate (EGCG), a DYRK1A inhibitor, given to young patients with DS improved visual recognition memory, working memory performance and adaptive behaviour