FABRIC: A National-Scale Programmable Experimental Network Infrastructure

FABRIC is a unique national research infrastructure to enable cutting-edge and exploratory research at-scale in networking, cybersecurity, distributed computing and storage systems, machine learning, and science applications. It is an everywhere-programmable nationwide instrument comprised of novel extensible network elements equipped with large amounts of compute and storage, interconnected by high speed, dedicated optical links. It will connect a number of specialized testbeds for cloud research (NSF Cloud testbeds CloudLab and Chameleon), for research beyond 5G technologies (Platforms for Advanced Wireless Research or PAWR), as well as production high-performance computing facilities and science instruments to create a rich fabric for a wide variety of experimental activities

On Economic Policy Uncertainty and Sovereign Credit Rating Decisions: Panel Quantile Evidence for the Eurozone

We employ a panel quantile framework that quantifies the relative importance of quantitative and qualitative factors across the conditional distribution of sovereign credit ratings in the Eurozone area. We find that regulatory quality and competitiveness have a stronger impact for low rated countries whereas GDP per capita is a major driver of high rated countries. A reduction in the current account deficit leads to a rating or outlook upgrade for low rated countries. Economic policy uncertainty impacts negatively on credit ratings across the conditional distribution; however, the impact is stronger for the lower rated countries. In other words, the creditworthiness of low rated countries takes a much bigger ‘hit’ than that of high rated countries when European policy uncertainty is on the rise

Investigation on semi-active control of vehicle suspension using adaptive inerter

The analysis of passive control with inerter in suspension system has been well studied in previous work by employing different configurations and optimizing the spring stiffness, damping coefficient and inertance simultaneously. In this paper, we study the suspension performance with semi-active control under the assumption that the inertance may be adjusted in real-time. The suspension system is designed to attenuate the vertical acceleration of the sprung mass. A quarter-car model is considered, and the inerter is installed parallel to the spring and damper. First, an analysis is provided on the influence of a fixed inerter to a given suspension system. Then, a state-feedback H2 controller for active suspension system is designed. The active force is approximated by an inerter with adaptive inertance. Simulation results show that comparing with the passive suspension with a fixed inerter, the designedH2 controller realized by adaptive inerter can achieve good improvement of ride comfort at the sprung mass natural frequency at the expense of a relatively small deterioration at the unsprung mass natural frequency. Copyright © (2014) by the International Institute of Acoustics & Vibration All rights reserved.postprin

Structural empowerment is a strong predictor of organizational commitment in nurses: A systematic review and meta-analysis

AIMS: The aim of this systematic review and meta-analysis is to explore the relationship between structural empowerment and organizational commitment and to examine a theoretical model under which empowerment could potentially affect organizational performance. DESIGN: PRISMA guidelines for systematic reviews and meta-analyses were used and quality assessment of articles was performed. DATA SOURCES: Electronic database searches were conducted in Google Scholar, PubMed/Medline, CINAHL, Scopus, and EMBASE from January 1950–1 January 2019, which resulted in 204 retrieved studies, published between 1994–2018. REVIEW METHODS: A random effects model was used to produce a pooled estimate of effect sizes (correlation coefficient, Cronbach's alpha), with analysis of heterogeneity and publication bias. A meta-analytic structural equation model of the constructs analysed was also performed. RESULTS: The final review included 22 studies. The meta-analytic means of structural empowerment, organizational commitment, job satisfaction, and psychological empowerment alpha reliabilities were 0.87, 0.84, 0.85, and 0.87, respectively. Heterogeneity but no publication bias was present in these outcomes. Structural empowerment was strongly correlated with organizational commitment (r = 0.43). The meta-analytic correlation coefficients of organizational commitment with psychological empowerment and job satisfaction were 0.53 and 0.47, respectively. Structural empowerment was correlated with job satisfaction and psychological empowerment with correlation coefficients of 0.57 and 0.44, respectively. Finally, job satisfaction was correlated with psychological empowerment with a correlation coefficient of 0.53. A meta-analytic structural equation model was tested with good fit which predicted performance (commitment and job satisfaction) from empowerment (structural and psychological). CONCLUSION: Structural empowerment is strongly correlated to organizational commitment and with psychological empowerment, they increase organizational performance. Organizations should attempt to make structural empowerment as widespread as possible to create an effective workplace culture. IMPACT: Structural empowerment in nurses is important to help deliver an effective workplace culture where nurses can be committed and have reduced intention-to-leave. Structural empowerment was strongly correlated with organizational commitment. Organizational commitment was significantly correlated with psychological empowerment and job satisfaction. Structural empowerment was correlated with job satisfaction and psychological empowerment as well. A meta-analytic structural equation model with good fit predicted performance. These results will affect nursing researchers and practitioners. Results indicate a need for organizational restructuring that promotes empowerment and formation of theoretical models that connect empowerment to performance

Predicting Anatomical Therapeutic Chemical (ATC) Classification of Drugs by Integrating Chemical-Chemical Interactions and Similarities

The Anatomical Therapeutic Chemical (ATC) classification system, recommended by the World Health Organization, categories drugs into different classes according to their therapeutic and chemical characteristics. For a set of query compounds, how can we identify which ATC-class (or classes) they belong to? It is an important and challenging problem because the information thus obtained would be quite useful for drug development and utilization. By hybridizing the informations of chemical-chemical interactions and chemical-chemical similarities, a novel method was developed for such purpose. It was observed by the jackknife test on a benchmark dataset of 3,883 drug compounds that the overall success rate achieved by the prediction method was about 73% in identifying the drugs among the following 14 main ATC-classes: (1) alimentary tract and metabolism; (2) blood and blood forming organs; (3) cardiovascular system; (4) dermatologicals; (5) genitourinary system and sex hormones; (6) systemic hormonal preparations, excluding sex hormones and insulins; (7) anti-infectives for systemic use; (8) antineoplastic and immunomodulating agents; (9) musculoskeletal system; (10) nervous system; (11) antiparasitic products, insecticides and repellents; (12) respiratory system; (13) sensory organs; (14) various. Such a success rate is substantially higher than 7% by the random guess. It has not escaped our notice that the current method can be straightforwardly extended to identify the drugs for their 2nd-level, 3rd-level, 4th-level, and 5th-level ATC-classifications once the statistically significant benchmark data are available for these lower levels

Time Consistent Portfolio Selection Under Short-Selling Prohibition: from Discrete to Continuous Setting

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Agrobiodiversity and Its Conservation in Nepal

Nepal is a part of the world\u27s biodiversity hotspot and ranks the 49th in the world for biodiversity. Agrobiodiversity and its conservation status were studied through literature review, field survey, key informant survey and focus group discussion. Results of field implementation of some good practices and action research were also documented. Among 24,300 total species in the country, 28% are agricultural genetic resources (AGRs), termed as agrobiodiversity. Agrobiodiversity has six components (crops, forages, livestock, aquatic, insects and microorganisms) and four sub-components (domesticated, semi-domesticated, wild relatives and wild edible) in Nepal. Agrobiodiversity on each component exists at agroecosystem, species, variety/breed/biotype/race/strain, genotype and allele levels, within an altitude range from 60 to 5,000 masl. There are 12 agroecosystems supporting 1026 species under crop component, 510 under forage, 35 under livestock, 250 under the aquatic animal, 17 under aquatic plant, 3,500 under insect and 800 under microorganism. An estimated loss of agrobiodiversity is 40%, however, farmers have reported up to 100% loss of AGRs in some areas for a particular species. Conservation of agrobiodiversity has been initiated since 1986. Four strategies namely ex-situ, on-farm, in-situ and breeding have been adopted for conservation and sustainable utilization of AGRs. Eighty good practices including process, methods and actions for managing agrobiodiversity have been in practice and these practices come under five conservation components (sensitization, method and approach, accelerator, value and enabling environment). Within the country, 18,765 accessions of AGRs have been conserved in different kinds of banks. A total of 24,683 accessions of Nepalese crops, forages and microbes have been conserved in different International and foreign genebanks. Some collections are conserved as safety duplication and safety backup in different CGIARs\u27 banks and World Seed Vault, Korea. Two global databases (GENESYS and EURISCO) have maintained 19,200 Nepalese accessions. Geographical Information System, Climate Analog Tool and biotechnological tools have been applied for better managing AGRs. Many stakeholders need to further concentrate on the conservation and utilization of AGRs. Global marketing of some native AGRs is necessary for sustaining agriculture and attracting young generations as well as conserving them through use