158 research outputs found

    3E: Energy-Efficient Elastic Scheduling for Independent Tasks in Heterogeneous Computing Systems

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    Reducing energy consumption is a major design constraint for modern heterogeneous computing systems to minimize electricity cost, improve system reliability and protect environment. Conventional energy-efficient scheduling strategies developed on these systems do not sufficiently exploit the system elasticity and adaptability for maximum energy savings, and do not simultaneously take account of user expected finish time. In this paper, we develop a novel scheduling strategy named energy-efficient elastic (3E) scheduling for aperiodic, independent and non-real-time tasks with user expected finish times on DVFS-enabled heterogeneous computing systems. The 3E strategy adjusts processors’ supply voltages and frequencies according to the system workload, and makes trade-offs between energy consumption and user expected finish times. Compared with other energy-efficient strategies, 3E significantly improves the scheduling quality and effectively enhances the system elasticity

    Electrochemical determination of chemical oxygen demand using Ti/TiO2 electrode.

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    To overcome the shortcomings of the conventional potassium dichromate method (PDM) for monitoring chemical oxygen demand (COD) of waters, many efforts have been made on developing quick and environment-friendly techniques. Among all alternatives, electrochemical (EC) techniques are very competitive due to their relatively simple devices and quickness. A number of electrodes have been fabricated to investigate electrochemical determination of COD. However, little work has been reported on Ti/TiO2 based electrode for this purpose. In the present work, Ti/Ti/TiO2 electrode was simply prepared by anodic oxidation of pure titanium. Aqueous solutions of potassium hydrogen phthalate and phenol were electrolyzed by chronocoulometry in a three-electrode system with Ti/Ti/TiO2 as working electrode (anode). Organic compounds were electrochemically oxidized on Ti/Ti/TiO2 electrode by hydroxyl radicals and the released electrons were recorded and transferred to currents. The electric currents were proportional to the COD values of the water samples being investigated. Based on data of COD values and corresponding currents, a linear regression equation was obtained for a certain kind of waste water. With the regression equation, current of an unknown water sample was transferred to its COD value. Conditions for the presented EC method were set up as cell voltage 2.0V v.s. SCE and pH 7.0. The linear range of COD was of about 25~530 mg/L. COD values of real waste water samples were measured by Ti/Ti/TiO2 electrode and the relative errors were all in the range of ±8% compared with data determined by conventional PDM. The electrochemicalmethodology was successfully applied to evaluate COD in waste water

    Deep Learning for Automated Contouring of Gross Tumor Volumes in Esophageal Cancer

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    PurposeThe aim of this study was to propose and evaluate a novel three-dimensional (3D) V-Net and two-dimensional (2D) U-Net mixed (VUMix-Net) architecture for a fully automatic and accurate gross tumor volume (GTV) in esophageal cancer (EC)–delineated contours.MethodsWe collected the computed tomography (CT) scans of 215 EC patients. 3D V-Net, 2D U-Net, and VUMix-Net were developed and further applied simultaneously to delineate GTVs. The Dice similarity coefficient (DSC) and 95th-percentile Hausdorff distance (95HD) were used as quantitative metrics to evaluate the performance of the three models in ECs from different segments. The CT data of 20 patients were randomly selected as the ground truth (GT) masks, and the corresponding delineation results were generated by artificial intelligence (AI). Score differences between the two groups (GT versus AI) and the evaluation consistency were compared.ResultsIn all patients, there was a significant difference in the 2D DSCs from U-Net, V-Net, and VUMix-Net (p=0.01). In addition, VUMix-Net showed achieved better 3D-DSC and 95HD values. There was a significant difference among the 3D-DSC (mean ± STD) and 95HD values for upper-, middle-, and lower-segment EC (p<0.001), and the middle EC values were the best. In middle-segment EC, VUMix-Net achieved the highest 2D-DSC values (p<0.001) and lowest 95HD values (p=0.044).ConclusionThe new model (VUMix-Net) showed certain advantages in delineating the GTVs of EC. Additionally, it can generate the GTVs of EC that meet clinical requirements and have the same quality as human-generated contours. The system demonstrated the best performance for the ECs of the middle segment

    Characteristics of SARS-CoV-2 Omicron BA.5 variants in Shanghai after ending the zero-COVID policy in December 2022: a clinical and genomic analysis

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    IntroductionAn unprecedented surge of Omicron infections appeared nationwide in China in December 2022 after the adjustment of the COVID-19 response policy. Here, we report the clinical and genomic characteristics of SARS-CoV-2 infections among children in Shanghai during this outbreak.MethodsA total of 64 children with symptomatic COVID-19 were enrolled. SARS-CoV-2 whole genome sequences were obtained using next-generation sequencing (NGS) technology. Patient demographics and clinical characteristics were compared between variants. Phylogenetic tree, mutation spectrum, and the impact of unique mutations on SARS-CoV-2 proteins were analysed in silico.ResultsThe genomic monitoring revealed that the emerging BA.5.2.48 and BF.7.14 were the dominant variants. The BA.5.2.48 infections were more frequently observed to experience vomiting/diarrhea and less frequently present cough compared to the BF.7.14 infections among patients without comorbidities in the study. The high-frequency unique non-synonymous mutations were present in BA.5.2.48 (N:Q241K) and BF.7.14 (nsp2:V94L, nsp12:L247F, S:C1243F, ORF7a:H47Y) with respect to their parental lineages. Of these mutations, S:C1243F, nsp12:L247F, and ORF7a:H47Y protein were predicted to have a deleterious effect on the protein function. Besides, nsp2:V94L and nsp12:L247F were predicted to destabilize the proteins.DiscussionFurther in vitro to in vivo studies are needed to verify the role of these specific mutations in viral fitness. In addition, continuous genomic monitoring and clinical manifestation assessments of the emerging variants will still be crucial for the effective responses to the ongoing COVID-19 pandemic

    Establishment of porcine and human expanded potential stem cells.

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    We recently derived mouse expanded potential stem cells (EPSCs) from individual blastomeres by inhibiting the critical molecular pathways that predispose their differentiation. EPSCs had enriched molecular signatures of blastomeres and possessed developmental potency for all embryonic and extra-embryonic cell lineages. Here, we report the derivation of porcine EPSCs, which express key pluripotency genes, are genetically stable, permit genome editing, differentiate to derivatives of the three germ layers in chimeras and produce primordial germ cell-like cells in vitro. Under similar conditions, human embryonic stem cells and induced pluripotent stem cells can be converted, or somatic cells directly reprogrammed, to EPSCs that display the molecular and functional attributes reminiscent of porcine EPSCs. Importantly, trophoblast stem-cell-like cells can be generated from both human and porcine EPSCs. Our pathway-inhibition paradigm thus opens an avenue for generating mammalian pluripotent stem cells, and EPSCs present a unique cellular platform for translational research in biotechnology and regenerative medicine

    Creación y Simulación de Metodologías de Análisis, Clasificación e Integración de Nuevos Requerimientos a Software Propietario

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    La priorización de nuevos requerimientos a implementar en un software propietario es un punto fundamental para su mantenimiento, la conservación de la calidad, observación de las reglas de negocio y los estándares de la empresa. Aunque existen herramientas de priorización basadas en técnicas probadas y reconocidas, las mismas requieren una calificación previa de cada requerimiento. Si la empresa cuenta con solicitudes provenientes de varios clientes de un mismo producto, aumentan los factores que afectan a la empresa, las herramientas disponibles no contemplan estos aspectos y hacen mucho más compleja la tarea de calificación. Este trabajo de investigación abarca la realización de un relevamiento de los métodos de priorización y selección de nuevos requerimientos utilizados por empresas de la zona de Rosario, y la definición de una metodología para la selección un nuevo requerimiento, que implica el análisis y evaluación de todas las implicaciones sobre el producto de software y la empresa, respetando sus reglas de negocio. La metodología creada conduce a la definición de los procesos para la construcción de una herramienta de calificación y priorización de nuevos requerimientos en software propietario que tiene solicitudes de varios clientes al mismo tiempo, con instrumentos de calificación que consideran todos los aspectos relacionados, proveerá técnicas de priorización actuales y emitirá informes personalizados según diferentes perspectivas de la empresa.Eje: Ingeniería de SoftwareRed de Universidades con Carreras en Informática (RedUNCI
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