Performance Analysis of Disaster Management Using WSN Technology

AbstractIn this research paper we propose a model of Wireless Sensor Networksused for pre-detection of disasters. Here we have discussed the basic architecture of WSNs and how these can be used in disaster management. The major reasons for mass destruction are Earthquake and Tsunami. Millions of lives are lost owing to these. Disaster, be it natural or man-made has a catastrophic impact on lives, money and infrastructure. We do not have a sensitive system yet which provides pre detection of these calamities. Therefore we need to take serious measures to ensure our safety from these disasters. WSNs are a new technology which can be helpful in these situations. The paper also throws light on the future scope of the topic. The information derived can be stored and used for future reference to predict climate of the area at a particular time period

Multiresolution discrete finite difference masks for rapid solution approximation of the Poisson's equation

YesThe Poisson's equation is an essential entity of applied mathematics for modelling many phenomena of importance. They include the theory of gravitation, electromagnetism, fluid flows and geometric design. In this regard, finding efficient solution methods for the Poisson's equation is a significant problem that requires addressing. In this paper, we show how it is possible to generate approximate solutions of the Poisson's equation subject to various boundary conditions. We make use of the discrete finite difference operator, which, in many ways, is similar to the standard finite difference method for numerically solving partial differential equations. Our approach is based upon the Laplacian averaging operator which, as we show, can be elegantly applied over many folds in a computationally efficient manner to obtain a close approximation to the solution of the equation at hand. We compare our method by way of examples with the solutions arising from the analytic variants as well as the numerical variants of the Poisson's equation subject to a given set of boundary conditions. Thus, we show that our method, though simple to implement yet computationally very efficient, is powerful enough to generate approximate solutions of the Poisson's equation.Supported by the European Union’s Horizon 2020 Programme H2020-MSCA-RISE-2017, under the project PDE-GIR with grant number 778035

Characterization of doping levels in heteronuclear, gas-phase, van der Waals clusters and their energy absorption from an intense optical field

A simple mass spectrometric method has been developed to quantify dopant levels in heteronuclear clusters in the gas phase. The method is demonstrated with reference to quantification of the water content in supersonic beams of water-doped argon clusters. Such doped clusters have assumed much importance in the context of recently-reported doping-induced enhancement in the emission of energetic charged particles and photons upon their interaction with intense laser pulses. We have also measured the energy that a doped cluster absorbs from the optical field; we find that energy absorption increases with increasing level of doping. The oft-used linear model of energy absorption is found to be quantitatively inadequate.Comment: To appear in Chemical Physics Letter

A deep artificial neural network architecture for mesh free solutions of nonlinear boundary value problems

YesSeeking efficient solutions to nonlinear boundary value problems is a crucial challenge in the mathematical modelling of many physical phenomena. A well-known example of this is solving the Biharmonic equation relating to numerous problems in fluid and solid mechanics. One must note that, in general, it is challenging to solve such boundary value problems due to the higher-order partial derivatives in the differential operators. An artificial neural network is thought to be an intelligent system that learns by example. Therefore, a well-posed mathematical problem can be solved using such a system. This paper describes a mesh free method based on a suitably crafted deep neural network architecture to solve a class of well-posed nonlinear boundary value problems. We show how a suitable deep neural network architecture can be constructed and trained to satisfy the associated differential operators and the boundary conditions of the nonlinear problem. To show the accuracy of our method, we have tested the solutions arising from our method against known solutions of selected boundary value problems, e.g., comparison of the solution of Biharmonic equation arising from our convolutional neural network subject to the chosen boundary conditions with the corresponding analytical/numerical solutions. Furthermore, we demonstrate the accuracy, efficiency, and applicability of our method by solving the well known thin plate problem and the Navier-Stokes equation

A Comparison of Artificial Diet and Hybrid Sweet Corn for the Rearing of Helicoverpa armigera (Hubner) (Lepidoptera: Noctuidae) Based on Life Table Characteristics

The demographic characteristics of Helicoverpa armigera (Hubner) reared on hybrid sweet corn (Zea mays L. variety saccharata) (hybrid super sweet corn KY bright jean) and on an artificial diet were compared by using the age-stage, two-sex life table. Because the hatch rate of eggs varies with maternal age, age-specific fecundity was calculated based on the numbers of hatched eggs to reveal the biological characteristics of H. armigera accurately. The intrinsic rate of increase (r), finite rate (lambda) and mean generation time (T) of H. armigera were 0.0853 d(-1), 1.0890 d(-1) and 46.6 d, respectively, on Z. mays and 0.1015 d(-1), 1.1068d(-1), and 46.3 d, respectively, on the artificial diet. There were significant differences in the intrinsic rate of increase and finite rate between two treatments. The age-stage life expectancy and reproductive value also were calculated. The relationships among the net reproductive rate, the mean female fecundity, the number of emerged females, and the total number of individuals used in the life table study are consistent with theoretical expectations. We recommend the age-stage, two-sex life table for use in insect demographic studies to incorporate both sexes and the variation in developmental rate among individuals and to obtain accurate population parameters. The artificial diet is more suitable for the mass rearing of H. armigera

Differential physio-biochemical and metabolic responses of peanut (Arachis hypogaea L.) under multiple abiotic stress conditions

The frequency and severity of extreme climatic conditions such as drought, salinity, cold, and heat are increasing due to climate change. Moreover, in the field, plants are affected by multiple abiotic stresses simultaneously or sequentially. Thus, it is imperative to compare the effects of stress combinations on crop plants relative to individual stresses. This study investigated the differential regulation of physio-biochemical and metabolomics parameters in peanut (Arachis hypogaea L.) under individual (salt, drought, cold, and heat) and combined stress treatments using multivariate correlation analysis. The results showed that combined heat, salt, and drought stress compounds the stress effect of individual stresses. Combined stresses that included heat had the highest electrolyte leakage and lowest relative water content. Lipid peroxidation and chlorophyll contents did not significantly change under combined stresses. Biochemical parameters, such as free amino acids, polyphenol, starch, and sugars, significantly changed under combined stresses compared to individual stresses. Free amino acids increased under combined stresses that included heat; starch, sugars, and polyphenols increased under combined stresses that included drought; proline concentration increased under combined stresses that included salt. Metabolomics data that were obtained under different individual and combined stresses can be used to identify molecular phenotypes that are involved in the acclimation response of plants under changing abiotic stress conditions. Peanut metabolomics identified 160 metabolites, including amino acids, sugars, sugar alcohols, organic acids, fatty acids, sugar acids, and other organic compounds. Pathway enrichment analysis revealed that abiotic stresses significantly affected amino acid, amino sugar, and sugar metabolism. The stress treatments affected the metabolites that were associated with the tricarboxylic acid (TCA) and urea cycles and associated amino acid biosynthesis pathway intermediates. Principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and heatmap analysis identified potential marker metabolites (pinitol, malic acid, and xylopyranose) that were associated with abiotic stress combinations, which could be used in breeding efforts to develop peanut cultivars that are resilient to climate change. The study will also facilitate researchers to explore different stress indicators to identify resistant cultivars for future crop improvement programs

Polymorphisms of MTHFR and MTR genes are not related to susceptibility to childhood ALL in north India

Background:Acute lymphoblastic leukemia (ALL) is the most worldwide common type of childhood cancer. Methylenetetrahydrofolate reductase (MTHFR) and 5-methyltetrahydrofolate-homocysteine methyltransferase (MTR) participate in folate pathways and are known as critical factors for DNA integrity as well as DNA hypomethylation. The aim of this work is to investigate frequency of MTHFR (677C→T and 1298A→C) and MTR (2756A→G) polymorphisms and their interaction with respect to possible effect on risk of childhood ALL among North Indian population. Procedure: A case control study from has been conducted on bone marrow and peripheral blood samples from 125 ALL patients and 100 sex-age matched healthy controls using PCR-RFLP method. Results: No statistically significant differences were observed for different genotypes between patients and controls (p>0.05). Significant difference for the risk of ALL in individuals having genotype of MTHFR 677TT (OR=0.61, 95% CI=0.21–1.77) and MTHFR 1298CC (OR=0.56, 95% CI=0.18–1.68) was not observed. The correlation of SNP of MTR gene and risk of ALL was not observed, too. Conclusions: The differences in distribution of possible combined genotypes of MTHFR (677C→T, 1298A→C) and MTR (2756A→G) between ALL patients and controls were statistically insignificant

Global gene expression analysis of pigeonpea with male sterility conditioned by A 2 cytoplasm

Cytoplasmic male sterility(CMS), a maternally inherited trait, provides a promising means to harness yield gains associated with hybrid vigor. In pigeonpea [Cajanus cajan (L.) Huth], nine types of sterility-inducing cytoplasm have been reported, of which A2 and A4 have been successfully deployed in hybrid breeding. Unfortunately, molecular mechanism of the CMS trait is poorly understood because of limited research invested. More recently, an association between a mitochondrial gene (nad7) and A4-CMS has been demonstrated in pigeonpea; however, the mechanism underlying A2-CMS still remains obscure. The current investigation aimed to analyze the differences in A2-CMS line (ICPL 88039A) and its isogenic maintainer line (ICPL 88039B) at transcriptome level using next-generation sequencing. Gene expression profiling uncovered a set of 505 genes that showed altered expression in response to CMS, of which, 412 genes were upregulated while 93 were downregulated in the fertile maintainer line vs. the CMS line. Further, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein–protein interaction (PPI) network analyses revealed association of CMS in pigeonpea with four major pathways: glucose and lipid metabolism, ATP production, pollen development and pollen tube growth, and reactive oxygen species (ROS) scavenging. Patterns of digital gene expression were confirmed by quantitative real-time polymerase chain reaction (qRT-PCR) of six candidate genes. This study elucidates candidate genes and metabolic pathways having potential associations with pollen development and male sterility in pigeonpea A2-CMS. New insights on molecular mechanism of CMS trait in pigeonpea will be helpful to accelerate heterosis utilization for enhancing productivity gains in pigeonpea

Aberrant promoter hypermethylation of selected apoptotic genes in childhood acute lymphoblastic leukemia among north indian population

Promoter hypermethylation mediates gene silencing in many neoplasms. Acute leukemia has been reported to harbor multiple genes aberrantly silenced by hypermethylation. Aim: In present study, we investigated the prevalence of hypermethylation of caspase-8 (CASP8), TMS1 and DAPK genes in correlation with clinicopathological factors in childhood acute lymphoblastic leukemia (ALL). Materials and Methods: A case-control study has been conducted based on bone marrow and peripheral blood samples from 125 ALL patients and 100 sex-age matched healthy controls. Methylation specific polymerase chain reaction (PCR) and bisulfite sequencing PCR was performed to analyze the methylation status of these genes. Reverse transcription PCR and real time PCR was carried out to determine changes in the mRNA expression level of the genes due to hypermethylation. Results: Hypermethylation of the 5´CpG islands of the CASP8, TMS1 and DAPK gene promoters was found in 3.2, 6.4, and 13.6% of 125 childhood ALL samples from north Indian population, respectively. There were significant differences in pattern of hypermethylation of TMS1 (p = 0.045) and DAPK (p < 0.001) between patients and healthy controls. Down-regulation of mRNA expression was found in cases in which CASP8, TMS1 and DAPK were hypermethylated. Conclusions: The present study indicated the impact of hypermethylation-mediated inactivation of CASP8, TMS1 and DAPK genes, which is associated with risk of childhood ALL. This abnormality occurs in leukemogenesis and it may be used as a biomarker and for predicting the prognosis of ALL

Crack growth: Does microstructure play a role?

The experimental data presented in this paper reveals that even if the growth of long cracks in two materials, with different microstructures, have different da/dN versus ΔK curves the corresponding small crack curves can be similar. We also see that long cracks in a large range of steels with different microstructures, chemical compositions, and yield stresses can have similar crack growth rates. The materials science community is challenged to explain these observations. The experimental data also suggests that the threshold term ΔKthr in the Hartman-Schijve variant of the NASGRO crack growth equation appears to have the potential to quantify the way in which small cracks interact with the local microstructure. In this context it is also noted that the variability in the life of operational aircraft is controlled by the probability distribution associated with the size and nature of the material discontinuities in the airframe rather than the probability distribution associated with the scatter in the growth of small cracks with a fixed initial size