A Method for Determining Asymptotes of Home-Range Area Curves

Home-range area curves are used to estimate the number of locations needed to accurately estimate home range size based on the asymptote of the curve. However, the current methodology used to identify asymptotes for home-range area curves is largely subjective and varies between studies. Our objective was to evaluate the use of exponential, Gompertz, logistic, and reciprocal function models as a means for identifying asymptotes of home-range area curves. We radio monitored northern bobwhite (Colinus virginianus) coveys during mid-September through November 2001-2002 in Jim Hogg County, Texas. We calculated home-range size of radiomarked coveys using the 95% fixed kernel with least squares cross validation and minimum convex polygon estimators. We fitted area observations and coefficient of variation to the number of locations using exponential, Gompertz, logistic, and reciprocal function models to estimate the minimum number of locations necessary to obtain a representative home range size for each home range estimator. The various function models consistently provided a relatively good fit for home range area curves and coefficient of variation curves (0.58 ≤ R2 0.99; P \u3c 0.05) for both home range estimators. We used an information-theoretic framework (AICC) to select the best model to estimate area-curve asymptotes. The use of function models appears to provide a structured and useful approach for calculating area-curve asymptotes. We propose that researchers consider the use of such models when determining asymptotes for home-range area curves and that more research be conducted to validate the strength of this method

The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure

'A foundation-hatched black elite’: Obama, the US establishment and foreign policy

US foreign policy has a largely unacknowledged racial dimension due to the racial characteristics of the US foreign policy establishment, and in shared mindsets in a soon-to-be ‘majority-minority’ nation. White Anglo-Saxon Protestant (WASP) racial-ethnic and class factors produce managed change through socialisation in an attenuated meritocratic order, adapting to challenges to elite dominance by incorporating rising talent, without altering broader patterns of power. The greatest success of such a system would be the assimilation of the most elite minority individuals, even as the bulk of those groups’ members continue to experience discrimination. Such success would be compounded by election to the highest office of a minority US president extolling the virtues of post-racial politics. President Barack Obama represents a ‘Wasp-ified’ black elite, assimilated into the extant structures of power that remain wedded to a more secular, non-biologically-racial, version of Anglo-Saxonism or, more broadly, liberal internationalism. Hence, it should occasion little surprise that there has been so little change in US foreign policies during Obama’s two-term presidency

Accounting for nature: assessing habitats in the UK countryside.

Countryside Survey 2000 (CS2000) and the Northern Ireland Countryside Survey 2000 (NICS2000) have been designed to provide detailed information about the habitats and landscape features that are important elements of our countryside. They can tell us about the ‘stock’ of these resources, that is how much of them we have and where they are to be found, and they can give us an insight into their condition based on the variety and abundance of the plant species associated with them. Using information from previous surveys, we can also gain an understanding of how the stock and condition of these habitats and landscape features are changing over time. We can build up a sort of balance sheet or an account of natural assets in the UK countryside. In this report we look in particular at the period between the last two surveys, 1990 and 1998

Internet of Things for Environmental Sustainability and Climate Change

Our world is vulnerable to climate change risks such as glacier retreat, rising temperatures, more variable and intense weather events (e.g., floods, droughts, and frosts), deteriorating mountain ecosystems, soil degradation, and increasing water scarcity. However, there are big gaps in our understanding of changes in regional climate and how these changes will impact human and natural systems, making it difficult to anticipate, plan, and adapt to the coming changes. The IoT paradigm in this area can enhance our understanding of regional climate by using technology solutions, while providing the dynamic climate elements based on integrated environmental sensing and communications that is necessary to support climate change impacts assessments in each of the related areas (e.g., environmental quality and monitoring, sustainable energy, agricultural systems, cultural preservation, and sustainable mining). In the IoT in Environmental Sustainability and Climate Change chapter, a framework for informed creation, interpretation and use of climate change projections and for continued innovations in climate and environmental science driven by key societal and economic stakeholders is presented. In addition, the IoT cyberinfrastructure to support the development of continued innovations in climate and environmental science is discussed

The Mount Sinai Prebiopsy Risk Calculator for Predicting any Prostate Cancer and Clinically Significant Prostate Cancer: Development of a Risk Predictive Tool and Validation with Advanced Neural Networking, Prostate Magnetic Resonance Imaging Outcome Database, and European Randomized Study of Screening for Prostate Cancer Risk Calculator

Background: The European Association of Urology guidelines recommend the use of imaging, biomarkers, and risk calculators in men at risk of prostate cancer. Risk predictive calculators that combine multiparametric magnetic resonance imaging with prebiopsy variables aid as an individualized decision-making tool for patients at risk of prostate cancer, and advanced neural networking increases reliability of these tools.Objective: To develop a comprehensive risk predictive online web-based tool using magnetic resonance imaging (MRI) and clinical data, to predict the risk of any prostate cancer (PCa) and clinically significant PCa (csPCa) applicable to biopsy-naive men, men with a prior negative biopsy, men with prior positive low-grade cancer, and men with negative MRI.Design, setting, and participants: Institutional review board-approved prospective data of 1902 men undergoing biopsy from October 2013 to September 2021 at Mount Sinai were collected.Outcome measurements and statistical analysis: Univariable and multivariable analyses were used to evaluate clinical variables such as age, race, digital rectal examination, family history, prostate-specific antigen (PSA), biopsy status, Prostate Imaging Reporting and Data System score, and prostate volume, which emerged as predictors for any PCa and csPCa. Binary logistic regression was performed to study the probability. Validation was performed with advanced neural networking (ANN), multi-institutional European cohort (Prostate MRI Outcome Database [PROMOD]), and European Randomized Study of Screening for Prostate Cancer Risk Calculator (ERSPC RC) 3/4.Results and limitations: Overall, 2363 biopsies had complete clinical information, with 57.98% any cancer and 31.40% csPCa. The prediction model was significantly associated with both any PCa and csPCa having an area under the curve (AUC) of 81.9% including clinical data. The AUC for external validation was calculated in PROMOD, ERSPC RC, and ANN for any PCa (0.82 vs 0.70 vs 0.90) and csPCa (0.82 vs 0.78 vs 0.92), respectively. This study is limited by its retrospective design and over-estimation of csPCa in the PROMOD cohort.Conclusions: The Mount Sinai Prebiopsy Risk Calculator combines PSA, imaging and clinical data to predict the risk of any PCa and csPCa for all patient settings. With accurate validation results in a large European cohort, ERSPC RC, and ANN, it exhibits its efficiency and applicability in a more generalized population. This calculator is available online in the form of a free web-based tool that can aid clinicians in better patients counseling and treatment decision-making.Patient summary: We developed the Mount Sinai Prebiopsy Risk Calculator (MSP-RC) to assess the likelihood of any prostate cancer and clinically significant disease based on a combination of clinical and imaging characteristics. MSP-RC is applicable to all patient settings and accessible online. Crown Copyright (C) 2022 Published by Elsevier B.V. on behalf of European Association of Urology.</p

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Lawson criterion for ignition exceeded in an inertial fusion experiment

For more than half a century, researchers around the world have been engaged in attempts to achieve fusion ignition as a proof of principle of various fusion concepts. Following the Lawson criterion, an ignited plasma is one where the fusion heating power is high enough to overcome all the physical processes that cool the fusion plasma, creating a positive thermodynamic feedback loop with rapidly increasing temperature. In inertially confined fusion, ignition is a state where the fusion plasma can begin "burn propagation" into surrounding cold fuel, enabling the possibility of high energy gain. While "scientific breakeven" (i.e., unity target gain) has not yet been achieved (here target gain is 0.72, 1.37 MJ of fusion for 1.92 MJ of laser energy), this Letter reports the first controlled fusion experiment, using laser indirect drive, on the National Ignition Facility to produce capsule gain (here 5.8) and reach ignition by nine different formulations of the Lawson criterion