230 research outputs found

    Hybrid JAYA algorithm for workflow scheduling in cloud

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    Workflow scheduling and resource provisioning are two of the most critical issues in cloud computing. Developing an optimal workflow scheduling strategy in the heterogeneous cloud environment is extremely difficult due to its NP-complete nature. Various optimization algorithms have been used to schedule the workflow so that users can receive Quality of Service (QoS) from cloud service providers as well as service providers can achieve maximum gain but there is no such model that can simultaneously minimize execution time and cost while balancing the load among virtual machines in a heterogeneous environment using JAYA approach. In this article, we employed the hybrid JAYA algorithm to minimize the computation cost and completion time during workflow scheduling. We considered the heterogeneous cloud computing environment and made an effort to evenly distribute the load among the virtual machines. To achieve our goals, we used the Task Duplication Heterogeneous Earliest Finish Time (HEFT-TD) and Predict Earliest Finish Time (PEFT). The makespan is greatly shortened by HEFT-TD which is based on the Optimistic Cost Table. We used a greedy technique to distribute the workload among Virtual Machines (VMs) in a heterogeneous environment. Greedy approach assigns the upcoming task to a VM which have lowest load. In addition, we also considered performance variation, termination delay, and booting time of virtual machines to achieve our objectives in our proposed model. We used Montage, LIGO, Cybershake, and Epigenomics datasets to experimentally analyze the suggested model in order to validate the concept. Our meticulous experiments show that our hybrid approach outperforms other recent algorithms in minimizing the execution cost and makespan, such as the Cost Effective Genetic Algorithm (CEGA), Cost-effective Load-balanced Genetic Algorithm (CLGA), Cost effective Hybrid Genetic Algorithm (CHGA), and Artificial Bee Colony Algorithm (ABC)

    Initial Filling of Tehri Reservoir — Analysis of Seepage Data

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    Initial Filling of reservoirs in dams, particularly the embankment type, is a very important phase as unusual behaviour / accidents of many dams have been reported during this period. A regular observation / analysis of quantum of seepage vis-Ă -vis the reservoir level is a significant activity so that any serious development inside the body of dam and foundation / abutments rocks are revealed in advance and remedial measures are taken up timely to prevent catastrophic failures. At Tehri, a 260.5m high earth & rockfill dam has been constructed across river Bhagirathi, a tributary of mighty river Ganga in India. Seepage discharge data of first two years of Initial Filling of Tehri reservoir has been analysed, which has led to a few important conclusions. The Analysis of Seepage data for the Initial Filling of Tehri reservoir is presented in the paper

    Initial Filling of Tehri Reservoir — Analysis of Seepage Data

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    Initial Filling of reservoirs in dams, particularly the embankment type, is a very important phase as unusual behaviour / accidents of many dams have been reported during this period. A regular observation / analysis of quantum of seepage vis-Ă -vis the reservoir level is a significant activity so that any serious development inside the body of dam and foundation / abutments rocks are revealed in advance and remedial measures are taken up timely to prevent catastrophic failures. At Tehri, a 260.5m high earth & rockfill dam has been constructed across river Bhagirathi, a tributary of mighty river Ganga in India. Seepage discharge data of first two years of Initial Filling of Tehri reservoir has been analysed, which has led to a few important conclusions. The Analysis of Seepage data for the Initial Filling of Tehri reservoir is presented in the paper

    Regulation of homocysteine metabolism by Mycobacterium tuberculosis S-adenosylhomocysteine hydrolase

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    Mycobacterium tuberculosis modulates expression of various metabolism-related genes to adapt in the adverse host environment. The gene coding for M. tuberculosis S-adenosylhomocysteine hydrolase (Mtb-SahH) is essential for optimal growth and the protein product is involved in intermediary metabolism. However, the relevance of SahH in mycobacterial physiology is unknown. In this study, we analyze the role of Mtb-SahH in regulating homocysteine concentration in surrogate host Mycobacterium smegmatis. Mtb-SahH catalyzes reversible hydrolysis of S-adenosylhomocysteine to homocysteine and adenosine and we demonstrate that the conserved His363 residue is critical for bi-directional catalysis. Mtb-SahH is regulated by serine/threonine phosphorylation of multiple residues by M. tuberculosis PknB. Major phosphorylation events occur at contiguous residues Thr219, Thr220 and Thr221, which make pivotal contacts with cofactor NAD+. Consequently, phosphorylation negatively modulates affinity of enzyme towards NAD+ as well as SAH-synthesis. Thr219, Thr220 and Thr221 are essential for enzyme activity, and therefore, responsible for SahH-mediated regulation of homocysteine

    Racial Differences in the Association Between Luminal Master Regulator Gene Expression Levels and Breast Cancer Survival

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    Compared with their European American (EA) counterparts, African American (AA) women are more likely to die from breast cancer in the United States. This disparity is greatest in hormone receptor-positive subtypes. Here we uncover biological factors underlying this disparity by comparing functional expression and prognostic significance of master transcriptional regulators of luminal differentiation.Fil: Byun, Jung S.. National Institutes of Health; Estados UnidosFil: Singhal, Sandeep K.. Columbia University; Estados UnidosFil: Park, Samson. National Institutes of Health; Estados UnidosFil: Yi, Dae Ik. National Institutes of Health; Estados UnidosFil: Yan, Tingfen. National Institutes of Health; Estados UnidosFil: Caban, Ambar. Columbia University Medical Center; Estados UnidosFil: Jones, Alana. National Institutes of Health; Estados UnidosFil: Mukhopadhyay, Partha. Columbia University Medical Center; Estados UnidosFil: Gille, Sarah. National Institutes of Health; Estados UnidosFil: Hewitt, Stephen M.. No especifíca;Fil: Newman, Lisa. No especifíca;Fil: Davis, Melissa B.. Henry Ford Health System; Estados UnidosFil: Jenkins, Brittany D.. Henry Ford Health System; Estados UnidosFil: Sepulveda, Jorge L.. Columbia University Medical Center; Estados UnidosFil: de Siervi, Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Nápoles, Anna María. National Institute On Minority Health And Health Disparities; Estados UnidosFil: Vohra, Nasreen A.. East Carolina University; Estados UnidosFil: Gardner, Kevin. Columbia University Medical Center; Estados Unido

    Kaiso (ZBTB33) subcellular partitioning functionally links LC3A/B, the tumor microenvironment, and breast cancer survival

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    The use of digital pathology for the histomorphologic profiling of pathological specimens is expanding the precision and specificity of quantitative tissue analysis at an unprecedented scale; thus, enabling the discovery of new and functionally relevant histological features of both predictive and prognostic significance. In this study, we apply quantitative automated image processing and computational methods to profile the subcellular distribution of the multi-functional transcriptional regulator, Kaiso (ZBTB33), in the tumors of a large racially diverse breast cancer cohort from a designated health disparities region in the United States. Multiplex multivariate analysis of the association of Kaiso’s subcellular distribution with other breast cancer biomarkers reveals novel functional and predictive linkages between Kaiso and the autophagy-related proteins, LC3A/B, that are associated with features of the tumor immune microenvironment, survival, and race. These findings identify effective modalities of Kaiso biomarker assessment and uncover unanticipated insights into Kaiso’s role in breast cancer progression.Fil: Singhal, Sandeep K.. North Dakota State University; Estados UnidosFil: Byun, Jung S.. National Institutes of Health; Estados UnidosFil: Park, Samson. National Institutes of Health; Estados UnidosFil: Yan, Tingfen. National Institutes of Health; Estados UnidosFil: Yancey, Ryan. Columbia University; Estados UnidosFil: Caban, Ambar. Columbia University; Estados UnidosFil: Hernandez, Sara Gil. National Institutes of Health; Estados UnidosFil: Hewitt, Stephen M.. U.S. Department of Health & Human Services. National Institute of Health. National Cancer Institute; Estados UnidosFil: Boisvert, Heike. Ultivue, Inc; Reino UnidoFil: Hennek, Stephanie. Ultivue Inc.; Reino UnidoFil: Bobrow, Mark. Ultivue Inc.; Reino UnidoFil: Ahmed, Md Shakir Uddin. Tuskegee University; Estados UnidosFil: White, Jason. Tuskegee University; Estados UnidosFil: Yates, Clayton. Tuskegee University; Estados UnidosFil: Aukerman, Andrew. Columbia University; Estados UnidosFil: Vanguri, Rami. Columbia University; Estados UnidosFil: Bareja, Rohan. Columbia University; Estados UnidosFil: Lenci, Romina. Columbia University; Estados UnidosFil: Farré, Paula Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: de Siervi, Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Nápoles, Anna María. National Institutes of Health; Estados UnidosFil: Vohra, Nasreen. East Carolina University; Estados UnidosFil: Gardner, Kevin. Columbia University; Estados Unido

    Protein expression of the gp78 E3 ligase predicts poor breast cancer outcome based on race

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    Women of African ancestry suffer higher rates of breast cancer mortality compared with all other groups in the United States. Though the precise reasons for these disparities remain unclear, many recent studies have implicated a role for differences in tumor biology. Using an epitope-validated antibody against the endoplasmic reticulum-associated E3 ligase, gp78, we show that elevated levels of gp78 in patient breast cancer cells predict poor survival. Moreover, high levels of gp78 are associated with poor outcomes in both ER+ and ER- tumors, and breast cancers expressing elevated amounts of gp78 protein are enriched in gene expression pathways that influence cell cycle, metabolism, receptor-mediated signaling, and cell stress response pathways. In multivariate analysis adjusted for subtype and grade, gp78 protein is an independent predictor of poor outcomes in women of African ancestry. Furthermore, gene expression signatures, derived from patients stratified by gp78 protein expression, are strong predictors of recurrence and pathological complete response in retrospective clinical trial data and share many common features with gene sets previously identified to be overrepresented in breast cancers based on race. These findings implicate a prominent role for gp78 in tumor progression and offer insights into our understanding of racial differences in breast cancer outcomes.Fil: Singhal, Sandeep K.. No especifíca;Fil: Byun, Jung S.. National Institutes of Health; Estados UnidosFil: Yan, Tingfen. National Institutes of Health; Estados UnidosFil: Yancey, Ryan. Columbia University; Estados UnidosFil: Caban, Ambar. Columbia University; Estados UnidosFil: Hernandez, Sara Gil. National Institutes of Health; Estados UnidosFil: Bufford, Sediqua. No especifíca;Fil: Hewitt, Stephen M.. No especifíca;Fil: Winfield, Joy. Columbia University; Estados UnidosFil: Pradhan, Jaya. Columbia University; Estados UnidosFil: Mustkov, Vesco. Columbia University; Estados UnidosFil: McDonald, Jasmine A.. No especifíca;Fil: Pérez Stable, Eliseo J.. National Institutes of Health; Estados UnidosFil: Nápoles, Anna María. National Institutes of Health; Estados UnidosFil: Vohra, Nasreen. No especifíca;Fil: de Siervi, Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Yates, Clayton. No especifíca;Fil: Davis, Melissa B.. No especifíca;Fil: Yang, Mei. No especifíca;Fil: Tsai, Yien Che. No especifíca;Fil: Weissman, Allan M.. No especifíca;Fil: Gardner, Kevin. Columbia University; Estados Unido

    Daksha: On Alert for High Energy Transients

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    We present Daksha, a proposed high energy transients mission for the study of electromagnetic counterparts of gravitational wave sources, and gamma ray bursts. Daksha will comprise of two satellites in low earth equatorial orbits, on opposite sides of earth. Each satellite will carry three types of detectors to cover the entire sky in an energy range from 1 keV to >1 MeV. Any transients detected on-board will be announced publicly within minutes of discovery. All photon data will be downloaded in ground station passes to obtain source positions, spectra, and light curves. In addition, Daksha will address a wide range of science cases including monitoring X-ray pulsars, studies of magnetars, solar flares, searches for fast radio burst counterparts, routine monitoring of bright persistent high energy sources, terrestrial gamma-ray flashes, and probing primordial black hole abundances through lensing. In this paper, we discuss the technical capabilities of Daksha, while the detailed science case is discussed in a separate paper.Comment: 9 pages, 3 figures, 1 table. Additional information about the mission is available at https://www.dakshasat.in

    Science with the Daksha High Energy Transients Mission

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    We present the science case for the proposed Daksha high energy transients mission. Daksha will comprise of two satellites covering the entire sky from 1~keV to >1>1~MeV. The primary objectives of the mission are to discover and characterize electromagnetic counterparts to gravitational wave source; and to study Gamma Ray Bursts (GRBs). Daksha is a versatile all-sky monitor that can address a wide variety of science cases. With its broadband spectral response, high sensitivity, and continuous all-sky coverage, it will discover fainter and rarer sources than any other existing or proposed mission. Daksha can make key strides in GRB research with polarization studies, prompt soft spectroscopy, and fine time-resolved spectral studies. Daksha will provide continuous monitoring of X-ray pulsars. It will detect magnetar outbursts and high energy counterparts to Fast Radio Bursts. Using Earth occultation to measure source fluxes, the two satellites together will obtain daily flux measurements of bright hard X-ray sources including active galactic nuclei, X-ray binaries, and slow transients like Novae. Correlation studies between the two satellites can be used to probe primordial black holes through lensing. Daksha will have a set of detectors continuously pointing towards the Sun, providing excellent hard X-ray monitoring data. Closer to home, the high sensitivity and time resolution of Daksha can be leveraged for the characterization of Terrestrial Gamma-ray Flashes.Comment: 19 pages, 7 figures. Submitted to ApJ. More details about the mission at https://www.dakshasat.in

    Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

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    Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Peer reviewe
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