Fundamental Strings, Holography, and Nonlinear Superconformal Algebras

We discuss aspects of holography in the AdS_3 \times S^p near string geometry of a collection of straight fundamental heterotic strings. We use anomalies and symmetries to determine general features of the dual CFT. The symmetries suggest the appearance of nonlinear superconformal algebras, and we show how these arise in the framework of holographic renormalization methods. The nonlinear algebras imply intricate formulas for the central charge, and we show that in the bulk these correspond to an infinite series of quantum gravity corrections. We also makes some comments on the worldsheet sigma-model for strings on AdS_3\times S^2, which is the holographic dual geometry of parallel heterotic strings in five dimensions.Comment: 25 page

Gravity Dual of a Quantum Hall Plateau Transition

We show how to model the transition between distinct quantum Hall plateaus in terms of D-branes in string theory. A low energy theory of 2+1 dimensional fermions is obtained by considering the D3-D7 system, and the plateau transition corresponds to moving the branes through one another. We study the transition at strong coupling using gauge/gravity duality and the probe approximation. Strong coupling leads to a novel kind of plateau transition: at low temperatures the transition remains discontinuous due to the effects of dynamical symmetry breaking and mass generation, and at high temperatures is only partially smoothed out.Comment: 27 pages, 6 figures, harvmac; v2, references and minor comments added, version to be submitted to JHEP; v3, corrections to section

Sensor tasking utilizing deep reinforcement learning in a random finite set framework

There is a growing need to increase the capabilities of existing sensor arrays to monitor a large amount of space objects orbiting the Earth with a limited number of opportunities to observe these objects. Due to geopolitical considerations and financial cost, it is infeasible to create an array of sensors that can monitor each space object and accurately describe its state. Instead of brute force techniques by increasing the number of sensors worldwide, the current advancements in computational capability along with new algorithms for multi-target filtering and reinforcement learning has allowed a pathway to begin solving the non-myopic, heterogenous sensor tasking problem. This work employs the labeled multi-Bernoulli filter in conjunction with advanced, deep reinforcement learning techniques such as the policy gradient Q-learning algorithm and deep Q-networks. The filter and reinforcement learning techniqures are used together to track ten targets in geosynchronous orbit, while a linear Kalman filter and the reinforcement learning techniques are used to evaluate their effectiveness in multi-agent learning scenarios. The future deployment of these algorithms and their specific logistical considerations are also discussed with potential solutions.Aerospace Engineerin

A study to determine the knowledge of pharmacovigilance among pharmacy students from Mumbai university

Background: Pharmacovigilance (PV); also known as drug safety surveillance, is the science of enhancing patient care and patient safety regarding the use of medicines by collecting, monitoring, assessing, and evaluating information from healthcare providers and patients. Pharmacists are pivotal players in adverse drug event (ADE) monitoring and reporting. However, most pharmacists are unaware or not knowledgeable about the guidelines used by their respective countries’ drug regulatory bodies. It is the need of the hour to train pharmacy students on the concept of pharmacovigilance.Methods: A cross-sectional study was carried out among pharmacy students from Mumbai University, India during May-June 2017. On the basis of the eligibility criterion 352 students were selected for the present study. Four hundred students were approached to participate in the study of which 201 agreed to participate (males: 179; females: 173). Pretested questionnaire was distributed and collected data was analyzed using IBM SPSS version 23.Results: Overall pharmacovigilance knowledge (44%) and perception (58%) was low among the participants of the present study. Seventy four percent of the participants felt that adverse drug reaction (ADR) reporting should be made compulsory for healthcare professionals. And only 21% agreed that the topic of Pharmacovigilance is well covered in pharmacy curriculum.Conclusions: Pharmacy council of India, pharmacy teacher’s association and respective pharmacy college should take necessary steps to increase the knowledge and create awareness regarding pharmacovigilance and adverse drug reaction reporting among pharmacy students.

Outcomes and care practices for preterm infants born at less than 33 weeks’ gestation: A quality-improvement study

BACKGROUND: Preterm birth is the leading cause of morbidity and mortality in children younger than 5 years. We report the changes in neonatal outcomes and care practices among very preterm infants in Canada over 14 years within a national, collaborative, continuous quality-improvement program. METHODS: We retrospectively studied infants born at 23–32 weeks’ gestation who were admitted to tertiary neonatal intensive care units that participated in the Evidence-based Practice for Improving Quality program in the Canadian Neonatal Network from 2004 to 2017. The primary outcome was survival without major morbidity during the initial hospital admission. We quantified changes using process-control charts in 6-month intervals to identify special-cause variations, adjusted regression models for yearly changes, and interrupted time series analyses. RESULTS: The final study population included 50 831 infants. As a result of practice changes, survival without major morbidity increased significantly (56.6% [669/1183] to 70.9% [1424/2009]; adjusted odds ratio [OR] 1.08, 95% confidence interval [CI] 1.06–1.10, per year) across all gestational ages. Survival of infants born at 23–25 weeks’ gestation increased (70.8% [97/137] to 74.5% [219/294]; adjusted OR 1.03, 95% CI 1.02–1.05, per year). Changes in care practices included increased use of antenatal steroids (83.6% [904/1081] to 88.1% [1747/1983]), increased rates of normothermia at admission (44.8% [520/1160] to 67.5% [1316/1951]) and reduced use of pulmonary surfactant (52.8% [625/1183] to 42.7% [857/2009]). INTERPRETATION: Network-wide quality-improvement activities that include better implementation of optimal care practices can yield sustained improvement in survival without morbidity in very preterm infants

Gendering Farmer Producer companies at the Agricultural Frontier of India: Empowerment or Burden?

Farmer Producer Companies (FPCs) are driving agricultural frontier expansions in India. Their main objectives are to mobilize small-scale farmers to collectivize and organize in order to gain collective bargaining power, in the process empowering farmers and eliminating middlemen. However, they have not established any demonstrable success in achieving these goals. This chapter seeks firstly, to draw transnational connections between agro-ecological transformations in India and larger market/capital expansions through FPCs, contextualized amidst national development goals for farmer empowerment, changing labor patterns, and ecological degradation. In doing so, it will, secondly, explore the gendered dimension of FPCs in India by analyzing how the process of establishing women-only FPCs by using mandatory inclusion as a participation tool can serve to disempower and further burden women. While mandatory involvement of women farmers on their Board of Directors as an empowerment strategy can prove crucial to enhancing women’s decision-making roles, this chapter asks whether such an inclusionary approach remains meaningful to achieve FPC success in a context where external support for women’s empowerment is not provided

Association between admission temperature and mortality and major morbidity in preterm infants born at fewer than 33weeks\u27 gestation

Importance: Neonatal hypothermia has been associated with higher mortality and morbidity; therefore, thermal control following delivery is an essential part of neonatal care. Identifying the ideal body temperature in preterm neonates in the first few hours of lifemay be helpful to reduce the risk for adverse outcomes. Objectives: To examine the association between admission temperature and neonatal outcomes and estimate the admission temperature associated with lowest rates of adverse outcomes in preterm infants born at fewer than 33 weeks\u27 gestation.. Design, Setting, And Participants: Retrospective observational study at 29 neonatal intensive care units in the Canadian Neonatal Network. Participants included 9833 inborn infants born at fewer than 33 weeks\u27 gestation who were admitted between January 1, 2010, and December 31, 2012.. Exposure: Axillary or rectal body temperature recorded at admission.. Main Outcomes And Measures: The primary outcomewas a composite adverse outcome defined as mortality or any of the following: severe neurological injury, severe retinopathy of prematurity, necrotizing enterocolitis, bronchopulmonary dysplasia, or nosocomial infection. The relationships between admission temperature and the composite outcome as well as between admission temperature and the components of the composite outcome were evaluated using multivariable analyses.. Results: Admission temperatures of the 9833 neonates were distributed as follows: lower than 34.5°C (1%); 34.5°C to 34.9°C (1%); 35.0°C to 35.4°C (3%); 35.5°C to 35.9°C (7%); 36.0°C to 36.4°C (24%); 36.5°C to 36.9°C (38%); 37.0°C to 37.4°C (19%); 37.5°C to 37.9°C (5%); and 38.0°C or higher (2%). After adjustment for maternal and infant characteristics, the rates of the composite outcome, severe neurological injury, severe retinopathy of prematurity, necrotizing enterocolitis, bronchopulmonary dysplasia, and nosocomial infection had a U-shaped relationship with admission temperature (a \u3e 0 [P \u3c .05]). The admission temperature at which the rate of the composite outcome was lowest was 36.8°C (95%CI, 36.7°C-37.0°C). Rates of severe neurological injury, severe retinopathy of prematurity, necrotizing enterocolitis (95%CI, 36.3°C-36.7°C), bronchopulmonary dysplasia, and nosocomial infection (95%CI, 36.9°C-37.3°C) were lowest at admission temperatures ranging from 36.5°C to 37.2°C.. Conclusions And Relevance: The relationship between admission temperature and adverse neonatal outcomes was U-shaped. The lowest rates of adverse outcomes were associated with admission temperatures between 36.5°C and 37.2°C.

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages