Cryogenic scintillation properties of n-type GaAs for the direct detection of MeV/c2 dark matter

This paper is the first report of n-type GaAs as a cryogenic scintillation radiation detector for the detection of electron recoils from interacting dark matter (DM) particles in the poorly explored MeV/c2 mass range. Seven GaAs samples from two commercial suppliers and with different silicon and boron concentrations were studied for their low temperature optical and scintillation properties. All samples are n-type even at low temperatures and exhibit emission between silicon donors and boron acceptors that peaks at 1.33 eV (930 nm). The lowest excitation band peaks at 1.44 eV (860 nm), and the overlap between the emission and excitation bands is small. The X-ray excited luminosities range from 7 to 43 photons/keV. Thermally stimulated luminescence measurements show that n-type GaAs does not accumulate metastable radiative states that could cause afterglow. Further development and use with cryogenic photodetectors promises a remarkable combination of large target size, ultra-low backgrounds, and a sensitivity to electron recoils of a few eV that would be produced by DM particles as light as a few MeV/c2

A powerful visualization technique for electricity supply and demand at industrial sites with combined heat and power and wind generation

The combination of wind generation and combined heat and power (CHP) on an industrial site brings significant design and operational challenges. The stochastic nature of wind power affects the flows of electricity imported and exported to and from the site. Economies of scale favor larger wind turbines, but at the same time it is also desirable to minimize the amount of electricity exported from the site to avoid incurring increased network infrastructure usage charges. Therefore the optimum situation is to maximize the proportion of the site load served by on-site generation. This paper looks at a visualization technique for power flows on an industrial site, which can be used to size on-site generators. The technique is applied to a test case, demonstrating how a simple combined heat and power control scheme can support the integration of on-site wind power. The addition of such CHP control has a small impact on the CHP unit but can greatly increase the proportion of wind generation consumed on-site. This visualization technique allows the comparison of different generation mixes and control schemes in order to arrive at the optimal mix from a technical and economic viewpoint

A Systems Approach to Healthcare: Agent-based Modeling, Community Mental Health, and Population Well-being

Purpose Explore whether agent-based modeling and simulation can help healthcare administrators discover interventions that increase population wellness and quality of care while, simultaneously, decreasing costs. Since important dynamics often lie in the social determinants outside the health facilities that provide services, this study thus models the problem at three levels (individuals, organizations, and society). Methods The study explores the utility of translating an existing (prize winning) software for modeling complex societal systems and agent\u27s daily life activities (like a Sim City style of software), into a desired decision support system. A case study tests if the 3 levels of system modeling approach is feasible, valid, and useful. The case study involves an urban population with serious mental health and Philadelphia\u27s Medicaid population (n = 527,056), in particular. Results Section 3 explains the models using data from the case study and thereby establishes feasibility of the approach for modeling a real system. The models were trained and tuned using national epidemiologic datasets and various domain expert inputs. To avoid co-mingling of training and testing data, the simulations were then run and compared (Section 4.1) to an analysis of 250,000 Philadelphia patient hospital admissions for the year 2010 in terms of re-hospitalization rate, number of doctor visits, and days in hospital. Based on the Student t-test, deviations between simulated vs. real world outcomes are not statistically significant. Validity is thus established for the 2008–2010 timeframe. We computed models of various types of interventions that were ineffective as well as 4 categories of interventions (e.g., reduced per-nurse caseload, increased check-ins and stays, etc.) that result in improvement in well-being and cost. Conclusions The 3 level approach appears to be useful to help health administrators sort through system complexities to find effective interventions at lower costs

Ankle complex musculature adaptations after Energy Drinks consumption in healthy young adult

Over the past few years, energy drink consumption has increased among students aged 18–34 years. Energy drinks alter the balance, reduce blood flow and interfere with neuromuscular activation in the lower extremities. We attempted to determine which specific additive of three different drinks (red bull, rockstar, and bang) could contribute to changes in muscle activation of the ankle complex. Twenty healthy young adults aged 22–28 years were included in this study and allocated among 3 groups, red bull, rockstar, and bang. Neuromuscular data were obtained from EMG sensors positioned on the anterior tibialis and gastrocnemius before completing the four balance tasks. Each participant completed all the tasks before and after the 16-ounce Edrink. ANOVA was performed to compare the data before and after the beverage. Statistical significance was set at P <0.05. A trend was observed in red bull and bang groups revealing a faster anterior tibial activity and prolong activation for gastrocnemius. The rockstar group also showed a more rapid activation trend and shorter response during all tasks for the gastrocnemius. It appears that the additives found in Redbull and Bang produce an increased posterior sway, indicated by the faster activity observed on the anterior tibial muscle. On the other hand, the elements encountered in rockstars provoke anterior movements, creating the need for a quicker response from the gastrocnemius muscle. Further research is required to explore certain energy drink ingredients' effects on dynamic activities such as walking

Decreased sex ratio following maternal exposure to polychlorinated biphenyls from contaminated Great Lakes sport-caught fish: a retrospective cohort study.

BACKGROUND: Fish from the Great Lakes are contaminated with polychlorinated biphenyls, which have been found to have several adverse reproductive effects. Several environmental contaminants have been found to alter the sex ratio of offspring at birth, but the evidence of such an effect of polychlorinated biphenyls has been inconsistent. METHODS: We examined parental serum polychlorinated biphenyl concentration in relation to the sex ratio of 173 children of mothers and 208 children of fathers from the Great Lakes region of the United States between 1970 and 1995. We calculated odds ratios for a male child using logistic regression and generalized estimating equations with adjustment for the year of birth of the child, maternal and paternal age, the mother's parity at the child's birth, and whether the child had an older brother. RESULTS: The adjusted odds ratio for having a male child among mothers in the highest quintile of serum polychlorinated biphenyl concentration was 0.18 (95% CI: 0.06–0.59) compared to mothers in the lowest quintile. Treating exposure as a continuous variable, the adjusted odds ratio for having a male child was 0.54 per unit increase in the natural log of maternal serum polychlorinated biphenyl concentration (95% CI: 0.33–0.89). There was little evidence of an association with paternal exposure. We found no association between either maternal or paternal serum dichlorodiphenyl-dichloroethene concentration and the sex ratio. CONCLUSIONS: These findings suggest that maternal exposure to polychlorinated biphenyls may decrease the sex ratio of offspring. These data add to the growing body of evidence that exposure to particular chemicals can alter the sex ratio at birth

Current and Future Advances in Surgical Therapy for Pituitary Adenoma

The vital physiological role of the pituitary gland, alongside its proximal critical neurovascular structures means pituitary adenomas cause significant morbidity or mortality. Whilst enormous advancements have been made in the surgical care of pituitary adenomas, treatment failure and recurrence remain challenges. To meet these clinical challenges, there has been an enormous expansion of novel medical technologies (e.g. endoscopy, advanced imaging, artificial intelligence). These innovations have the potential to benefit each step of the patient journey, and ultimately, drive improved outcomes. Earlier and more accurate diagnosis addresses this in part. Analysis of novel patient data sets, such as automated facial analysis or natural language processing of medical records holds potential in achieving an earlier diagnosis. After diagnosis, treatment decision-making and planning will benefit from radiomics and multimodal machine learning models. Surgical safety and effectiveness will be transformed by smart simulation methods for trainees. Next-generation imaging techniques and augmented reality will enhance surgical planning and intraoperative navigation. Similarly, the future armamentarium of pituitary surgeons, including advanced optical devices, smart instruments and surgical robotics, will augment the surgeon's abilities. Intraoperative support to team members will benefit from a surgical data science approach, utilising machine learning analysis of operative videos to improve patient safety and orientate team members to a common workflow. Postoperatively, early detection of individuals at risk of complications and prediction of treatment failure through neural networks of multimodal datasets will support earlier intervention, safer hospital discharge, guide follow-up and adjuvant treatment decisions. Whilst advancements in pituitary surgery hold promise to enhance the quality of care, clinicians must be the gatekeepers of technological translation, ensuring systematic assessment of risk and benefit. In doing so, the synergy between these innovations can be leveraged to drive improved outcomes for patients of the future

Testing of the Nursing Evidence‐Based Practice Survey

BackgroundClinicians’ knowledge and skills for evidence‐based practice (EBP) and organizational climate are important for science‐based care. There is scant literature regarding aligning organizational culture with EBP implementation and even less for unit and organizational culture. The Nursing EBP Survey examines individual, unit, and organizational factors to better understand registered nurses’ (RN) self‐reported EBP.AimsEstablish and confirm factor loading, reliability, and discriminant validity for the untested Nursing EBP Survey.MethodsThe study employed a descriptive cross‐sectional survey design and was targeted for RNs. The setting included 14 hospitals and 680 medical offices in Southern California. The 1999 instrument consisted of 22 items; 7 items were added in 2005 for 29 items. The questionnaire used a 5 point, Likert‐type scale. The survey website opened in November 2016 and closed after 23 weeks. Psychometric testing and factor determination used parallel analysis, exploratory factor analysis, confirmatory factor analysis (CFA), and ANOVA post hoc comparisons.ResultsOne thousand one hundred and eighty‐one RNs completed the survey. All factor loadings in the CFA model were positive and significant (p < .001). All standardized loadings ranged from .70 to .94. The covariance estimate between Factor 1 and Factor 2 was marginally significant (p = .07). All other covariances and error variances were significant (p < .001). Final factor names were Practice Climate (Factor 1), Data Collection (Factor 2), Evidence Appraisal (Factor 3), Implementation (Factor 4), and Access to Evidence (Factor 5). Four of 5 factors showed significant differences between education levels (p < .05 level). All factors showed significant differences (p < .05) between inpatient and ambulatory staff, with higher scores for inpatient settings.Linking Evidence to ActionNurses’ knowledge, attitudes, and skills for EBP vary. The 2019 Nursing EBP survey offers RNs direction to plan and support improvement in evidence‐based outcomes and tailors future EBP initiatives.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154968/1/wvn12432.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154968/2/wvn12432_am.pd

Opt: A Domain Specific Language for Non-linear Least Squares Optimization in Graphics and Imaging

Many graphics and vision problems are naturally expressed as optimizations with either linear or non-linear least squares objective functions over visual data, such as images and meshes. The mathematical descriptions of these functions are extremely concise, but their implementation in real code is tedious, especially when optimized for real-time performance in interactive applications. We propose a new language, Opt (available under http://optlang.org), in which a user simply writes energy functions over image- or graph-structured unknowns, and a compiler automatically generates state-of-the-art GPU optimization kernels. The end result is a system in which real-world energy functions in graphics and vision applications are expressible in tens of lines of code. They compile directly into highly-optimized GPU solver implementations with performance competitive with the best published hand-tuned, application-specific GPU solvers, and 1-2 orders of magnitude beyond a general-purpose auto-generated solver