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Vulture populations are in severe decline across Africa and prioritization of geographic areas for their conservation is urgently needed. To do so, we compiled three independent datasets on vulture occurrence from road-surveys, GPS-tracking, and citizen science (eBird), and used maximum entropy to build ensemble species distribution models (SDMs). We then identified spatial vulture conservation priorities in Ethiopia, a stronghold for vultures in Africa, while accounting for uncertainty in our predictions. We were able to build robust distribution models for five vulture species across the entirety of Ethiopia, including three Critically Endangered, one Endangered, and one Near Threatened species. We show that priorities occur in the highlands of Ethiopia, which provide particularly important habitat for Bearded Gypaetus barbatus, Hooded Necrosyrtes monachus, Rüppell’s Gyps rüppelli and White-backed Gyps africanus Vultures, as well as the lowlands of north-eastern Ethiopia, which are particularly valuable for the Egyptian Vulture Neophron percnopterus. One-third of the core distribution of the Egyptian Vulture was protected, followed by the White-backed Vulture at one-sixth, and all other species at one-tenth. Overall, only about one-fifth of vulture priority areas were protected. Given that there is limited protection of priority areas and that vultures range widely, we argue that measures of broad spatial and legislative scope will be necessary to address drivers of vulture declines, including poisoning, energy infrastructure, and climate change, while considering the local social context and aiding sustainable development.
This article examines shoplifting from department stores and variety chain stores in interwar America and Britain. Patterns of shoplifting show strong similarities—with stores facing a predominantly female, and disproportionately affluent, army of amateur shoplifters, together with a much smaller corps of professional thieves. The incidence and characteristics of shoplifting are explored, together with the stores’ legal and other strategies to deter shoplifters. The article also examines why apparently prosperous women had the highest propensity to shoplift. Britain and the United States had strong commonalities in terms of open display retail formats, the methods used to deter shoplifters, and typical legal penalties. However, America had one critical difference—the much higher incidence of a type of store criminal who specialized in deliberately getting apprehended in order to sue the store for false arrest and, often, false imprisonment, slander, and a range of related charges. This reflected the higher damages typically awarded by U.S. courts compared with their British counterparts, inflated by local antagonism to retail corporations, together with a system—at least in some U.S. cities—whereby corrupt lawyers and judges connived in shoplifting acquittals that paved the way for lawsuits.
Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full two-dimensional (2D) image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields, and other sample-dependent properties. However, extracting this information requires complex analysis pipelines that include data wrangling, calibration, analysis, and visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open-source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail and present results from several experimental datasets. We also implement a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open-source HDF5 standard. We hope this tool will benefit the research community and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project.
ABSTRACT IMPACT: Indiana CTSI Team Science to maximize rapid collection, analyses and dissemination of biosamples collected from patients with Covid-19 to provide preliminary data for grant applications on the pathogenesis and outcomes of patients with Covid-19. OBJECTIVES/GOALS: When Covid-19 hit Indiana in April, there was an immediate need to respond rapidly to coordinate research across our healthcare systems. The CTSI became a point of contact for coordinating research endeavors including activation of clinical trials and use of precious samples from patients with Covid-19 to maximize preliminary data for grants. METHODS/STUDY POPULATION: The Indiana CTSI coordinated collection of biospecimens at multiple hospitals using in person and remote consenting via telephone or on a smartphone utilizing a QR code. We also retrieved existing samples from the Indiana Biobank previously collected for future research and from subject positive for Covid-19 by search of the linked electronic health record (EHR). A total of 224 subject samples (7 children, 36 previously collected, and 6 with both acute and recovered specimens) were obtained over a four month period. Our CTSI cores ran varied analyses collated to a single database, linked to the EMR for use as preliminary data for grant applications to avoid redundancy of measures on limited samples. RESULTS/ANTICIPATED RESULTS: The 224 subject samples were used for whole exome DNA sequencing, RNA seq, analyses of 48 plasma cytokine/chemokines by multiplex analyses, and PBMC isolated for culture and assessment of secreted cytokines. The clinical data were linked and included demographics, hospitalization length of stay and need for mechanical ventilation, max and min oxygen levels, liver function tests, IL-6, D-dimer, CRP, LDH, and ferritin, need for dialysis, and echocardiography. Additional clinical data were available upon request. A survey was sent to our CTSI email to query for potential interest in the data with 87 inquiries, and to date 46 investigators have requested data and/or additional samples. DISCUSSION/SIGNIFICANCE OF FINDINGS: During the first surge of Covid-19, the CTSI coordinated analyses for the dissemination of results for use by CTSI investigators to minimize duplication of assays and increase availability. The collaboration of research coordinators, biobank, research cores, and informatics demonstrates the power and agility of team science in the Indiana CTSI.
Introduction to Education provides pre-service teachers with an overview of the context, craft and practice of teaching in Australian schools as they commence the journey from learner to classroom teacher. Each chapter poses questions about the nature of teaching students, and guides readers though the Australian Professional Standards for Teachers. Incorporating recent research and theoretical literature, Introduction to Education presents a critical consideration of the professional, policy and curriculum contexts of teaching in Australia. The book covers theoretical topics in chapters addressing assessment, planning, safe learning environments, and working with colleagues, families, carers and communities. More practical chapters discuss professional experience and building a career after graduation. Rigorous in conception and practical in scope, Introduction to Education welcomes new educators to the theory and practical elements of teaching, learning, and professional practice.
We explore marine reservoir effects (MREs) in seal bones from the northern Bering and Chukchi Seas regions. Ringed and bearded seals have served as dietary staples in human populations along the coasts of Arctic northeast Asia and North America for several millennia. Radiocarbon (14C) dates on seal bones and terrestrial materials (caribou, plants seeds, wood, and wood charcoal) were compared from archaeological sites in the Bering Strait region of northwestern Alaska to assess MREs in these sea mammals over time. We also compared these results to 14C dates on modern seal specimens collected in AD 1932 and 1946 from the Bering Sea region. Our paired archaeological samples were recovered from late Holocene archaeological features, including floors from dwellings and cache pits, that date between 1600 and 130 cal BP. 14C dates on seal bones from the northern Bering and Chukchi Seas show differences [R(t)] of 800 ± 140 years from to their terrestrial counterparts, and deviations of 404 ± 112 years (ΔR) from the marine calibration curve.
The Victorian City of London’s financial center expanded and renewed its building infrastructure virtually unimpeded by considerations of urban preservation, conservation, or public opinion. The next phase of massive rebuilding, during the long post-1945 boom, appeared likely to follow the same pattern. However, by the mid-1960s, the freedom of City office owner-occupiers and developers to do as they wished with their buildings had become substantially constrained by rising conservationist sentiment. This paper explores this process through the history of the design, building, and eventual aborted demolition of Gibson Hall, the Bishopsgate headquarters of National Provincial Bank for over a century. This paper charts the life of Gibson Hall, in particular its conception, design, and, ultimately, its attempted redevelopment. We also consider the long-term consequences of the rebalancing between economic and conservation objectives for the nature of British urban redevelopment and the adoption of a “throwaway” business headquarters style—to remove any risk of popular support for preservation.
Depressive and anxiety disorders are highly comorbid, which has been theorized to be due to an underlying internalizing vulnerability. We aimed to identify groups of participants with differing vulnerabilities by examining the course of internalizing psychopathology up to age 45.
We used data from 24158 participants (aged 45+) in 23 population-based cross-sectional World Mental Health Surveys. Internalizing disorders were assessed with the Composite International Diagnostic Interview (CIDI). We applied latent class growth analysis (LCGA) and investigated the characteristics of identified classes using logistic or linear regression.
The best-fitting LCGA solution identified eight classes: a healthy class (81.9%), three childhood-onset classes with mild (3.7%), moderate (2.0%), or severe (1.1%) internalizing comorbidity, two puberty-onset classes with mild (4.0%) or moderate (1.4%) comorbidity, and two adult-onset classes with mild comorbidity (2.7% and 3.2%). The childhood-onset severe class had particularly unfavorable sociodemographic outcomes compared to the healthy class, with increased risks of being never or previously married (OR = 2.2 and 2.0, p < 0.001), not being employed (OR = 3.5, p < 0.001), and having a low/low-average income (OR = 2.2, p < 0.001). Moderate or severe (v. mild) comorbidity was associated with 12-month internalizing disorders (OR = 1.9 and 4.8, p < 0.001), disability (B = 1.1–2.3, p < 0.001), and suicidal ideation (OR = 4.2, p < 0.001 for severe comorbidity only). Adult (v. childhood) onset was associated with lower rates of 12-month internalizing disorders (OR = 0.2, p < 0.001).
We identified eight transdiagnostic trajectories of internalizing psychopathology. Unfavorable outcomes were concentrated in the 1% of participants with childhood onset and severe comorbidity. Early identification of this group may offer opportunities for preventive interventions.
Background: Hospital-acquired Clostridioides difficile infection (HA-CDI) rates are highly variable over time, posing problems for research assessing interventions that might improve rates. By understanding seasonality in HA-CDI rates and the impacts that other factors such as influenza admissions might have on these rates, we can account for them when establishing the relationship between interventions and infection rates. We assessed whether there were seasonal trends in HA-CDI and whether they could be accounted for by influenza rates. Methods: We assessed HA-CDI rates per 10,000 patient days, and the rate of hospitalized patients with influenza per 1,000 admissions in 4 acute-care facilities (n = 2,490 beds) in Calgary, Alberta, from January 2016 to December 2018. We used 4 statistical approaches in R (version 3.5.1 software): (1) autoregressive integrated moving average (ARIMA) to assess dependencies and trends in each of the monthly HA-CDI and influenza series; (2) cross correlation to assess dependencies between the HA-CDI and influenza series lagged over time; (3) Poisson harmonic regression models (with sine and cosine components) to assess the seasonality of the rates; and (4) Poisson regression to determine whether influenza rates accounted for seasonality in the HA-CDI rates. Results: Conventional ARIMA approaches did not detect seasonality in the HA-CDI rates, but we found strong seasonality in the influenza rates. A cross-correlation analysis revealed evidence of correlation between the series at a lag of zero (R = 0.41; 95% CI, 0.10–0.65) and provided an indication of a seasonal relationship between the series (Fig. 1). Poisson regression suggested that influenza rates predicted CDI rates (P < .01). Using harmonic regression, there was evidence of seasonality in HA-CDI rates (2 [2 df] = 6.62; P < .05) and influenza rates (2 [2 df] = 1,796.6; P < .001). In a Poisson model of HA-CDI rates with both the harmonic components and influenza admission rates, the harmonic components were no longer predictive of HA-CDI rates. Conclusions: Harmonic regression provided a sensitive means of identifying seasonality in HA-CDI rates, but the seasonality effect was accounted for by influenza admission rates. The relationship between HA-CDI and influenza rates is likely mediated by antibiotic prescriptions, which needs to be assessed. To improve precision and reduce bias, research on interventions to reduce HA-CDI rates should assess historic seasonality in HA-CDI rates and should account for influenza admissions.