Corrections.
Ontology highlight
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PROVIDER: S-EPMC6880299 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionWhile smoking rates are 3-4 times higher among criminal justice populations than in the general population, no studies have previously examined smoking characteristics in a community corrections population.MethodsThe current study involved descriptive analyses of self-reported survey data from 217 criminal justice supervisees reporting for urine drug screens during a 5-day period at a community corrections facility in the southeastern United States.ResultsMost participants were current smokers (72.3%), males (65.9%), and Black (50.2%) who reported smoking three fourths of a pack of cigarettes per day and had been smoking for about 15 years. More than half of smokers reported that they would be interested in receiving cessation assistance if free help were available and of these, 60% were interested in pharmacotherapy. White smokers used more cigarettes per day, were more likely to have already tried medication to help them quit smoking, and were also more interested in pharmacotherapies and less interested in behavioral therapies compared with Black smokers. Female smokers did not differ from male smokers on key smoking characteristics, but male smokers were more likely to have tried or regularly used other tobacco products, such as cigars. Female smokers were significantly more likely to report interest in using a pharmacotherapy agent for future cessation, while male smokers reported more interest in nonpharmacotherapy approaches to quit smoking.DiscussionResults from this study highlight important differences among smoking groups and may indicate the need to test tailored smoking interventions.
| S-EPMC2902910 | biostudies-literature
Project description:Theoretical models capture very precisely the behaviour of magnetic materials at the microscopic level. This makes computer simulations of magnetic materials, such as spin dynamics simulations, accurately mimic experimental results. New approaches to efficient spin dynamics simulations are limited by integration time step barrier to solving the equations-of-motions of many-body problems. Using a short time step leads to an accurate but inefficient simulation regime whereas using a large time step leads to accumulation of numerical errors that render the whole simulation useless. In this paper, we use a Deep Learning method to compute the numerical errors of each large time step and use these computed errors to make corrections to achieve higher accuracy in our spin dynamics. We validate our method on the 3D Ferromagnetic Heisenberg cubic lattice over a range of temperatures. Here we show that the Deep Learning method can accelerate the simulation speed by 10 times while maintaining simulation accuracy and overcome the limitations of requiring small time steps in spin dynamic simulations.
| S-EPMC7426868 | biostudies-literature
Project description:Carceral settings in the United States have been the source of many single site COVID-19 outbreaks. Quarantine is a strategy used to mitigate the spread of COVID-19 in correctional settings, and specific quarantine practices differ state to state. To better understand how states are using quarantine in prisons, we reviewed each state's definition of quarantine and compared each state's definition to the Centers for Disease Control's (CDC) definition and recommendations for quarantine in jails and prisons. Most prison systems, 45 of 53, define quarantine, but definitions vary widely. No state published definitions of quarantine that align with all CDC recommendations, and only 9 states provide quarantine data. In these states, the highest recorded quarantine rate occurred in Ohio in May 2020 at 843 per 1,000. It is necessary for prison systems to standardize their definitions of quarantine and to utilize quarantine practices in accordance with CDC recommendations. In addition, data transparency is needed to better understand the use of quarantine and its effectiveness at mitigating COVID-19 outbreaks in carceral settings.
| S-EPMC8491943 | biostudies-literature
Project description:Revelation of emerging exotic states of topological insulators (TIs) for future quantum computing applications relies on breaking time-reversal symmetry and opening a surface energy gap. Here, we report on the transport response of Bi2Te3 TI thin films in the presence of varying Cr dopants. By tracking the magnetoconductance (MC) in a low doping regime we observed a progressive crossover from weak antilocalization (WAL) to weak localization (WL) as the Cr concentration increases. In a high doping regime, however, increasing Cr concentration yields a monotonically enhanced anomalous Hall effect (AHE) accompanied by an increasing carrier density. Our results demonstrate a possibility of manipulating bulk ferromagnetism and quantum transport in magnetic TI, thus providing an alternative way for experimentally realizing exotic quantum states required by spintronic applications.
| S-EPMC3739003 | biostudies-literature
Project description:We present two new semiempirical quantum-chemical methods with orthogonalization and dispersion corrections: ODM2 and ODM3 (ODM x). They employ the same electronic structure model as the OM2 and OM3 (OM x) methods, respectively. In addition, they include Grimme's dispersion correction D3 with Becke-Johnson damping and three-body corrections E ABC for Axilrod-Teller-Muto dispersion interactions as integral parts. Heats of formation are determined by adding explicitly computed zero-point vibrational energy and thermal corrections, in contrast to standard MNDO-type and OM x methods. We report ODM x parameters for hydrogen, carbon, nitrogen, oxygen, and fluorine that are optimized with regard to a wide range of carefully chosen state-of-the-art reference data. Extensive benchmarks show that the ODM x methods generally perform better than the available MNDO-type and OM x methods for ground-state and excited-state properties, while they describe noncovalent interactions with similar accuracy as OM x methods with a posteriori dispersion corrections.
| S-EPMC6416713 | biostudies-literature