THE ECONOMICS OF CONTROLLING INFECTIOUS DISEASES ON DAIRY FARMS

Cost effective disease control on the dairy farm can enhance productivity and subsequently profitability. Previous economic studies on animal disease have focused on production losses and evaluation of disease eradication programs and provided little guidance as to the optimal prevention action. This paper presents a theoretical model on the economics of livestock disease and develops an empirical model to determine the optimal set of control strategies for four production limiting cattle diseases: bovine viral diarrhea (BVD), enzootic bovine leukosis (EBL), Johne's Disease (JD) and neosporosis. Control functions indicating the prevalence of infection with each of the four diseases for each of the ten strategies are estimated. The optimal strategies that minimize total disease cost (direct production losses and control expenditures) are provided for each disease on the basis of farm survey results from the Maritime provinces. The results emphasize the importance of introduction checks before new animals enter the herd and adequate vaccination protection as cost-effective control strategies.Farm Management, Livestock Production/Industries,

Teen Distracted Reality an Interactive Virtual Education (D.R.I.V.E.): Experience and Impact on Teenage Drivers

Introduction: In 2013, 2,163 teens in the United States ages 16–19 were killed and 243,243 were treated in emergency departments for injuries from motor vehicle crashes. distracted driving (i.e. texting, loud music, or phone conversations) and impaired driving (driving under the influence) play a role in these motor vehicle crashes. Prevention efforts aimed at high-risk teenager driving behavior may encourage safe driving habits. Methods: The Teen D.R.I.V.E. program is a mobile driving simulator that provides teenagers with distracted and impaired driving scenarios. We administered anonymous surveys from April 2015-April 2016 to obtain demographic data and evaluate the program’s impact on their driving behavior. We retrospectively analyzed survey responses using univariate and multivariate statistical analysis. Results: A total of 1374 participants in the survey, however, 50 did not respond to the driving experience portion of the survey. Most participants (70%) were between 16-17 years of age years old and 51% were males. A majority (76%) of respondents had driving experience (26% permit, and 46% license) or had attended a driver’s education course (67%). After experiencing the simulation respondents felt that the consequences of driving distracted (53%) and driving impaired (61%) were worse than previously expected. In addition, participants said that they would never drive distracted (70%) or drive impaired (90%). A majority of participants (72%) feel that simulation is the most effective way to teach driving related topics. Conclusion: Teen D.R.I.V.E. offers a valuable experience to teenagers, teaching them about the dangers of driving distracted and impaired. Participants are likely to never drive impaired compared or distracted. Most teenagers feel simulation teaches these driving lessons most effectively

Artifact-Based Rendering: Harnessing Natural and Traditional Visual Media for More Expressive and Engaging 3D Visualizations

We introduce Artifact-Based Rendering (ABR), a framework of tools, algorithms, and processes that makes it possible to produce real, data-driven 3D scientific visualizations with a visual language derived entirely from colors, lines, textures, and forms created using traditional physical media or found in nature. A theory and process for ABR is presented to address three current needs: (i) designing better visualizations by making it possible for non-programmers to rapidly design and critique many alternative data-to-visual mappings; (ii) expanding the visual vocabulary used in scientific visualizations to depict increasingly complex multivariate data; (iii) bringing a more engaging, natural, and human-relatable handcrafted aesthetic to data visualization. New tools and algorithms to support ABR include front-end applets for constructing artifact-based colormaps, optimizing 3D scanned meshes for use in data visualization, and synthesizing textures from artifacts. These are complemented by an interactive rendering engine with custom algorithms and interfaces that demonstrate multiple new visual styles for depicting point, line, surface, and volume data. A within-the-research-team design study provides early evidence of the shift in visualization design processes that ABR is believed to enable when compared to traditional scientific visualization systems. Qualitative user feedback on applications to climate science and brain imaging support the utility of ABR for scientific discovery and public communication.Comment: Published in IEEE VIS 2019, 9 pages of content with 2 pages of references, 12 figure

Geography, environment, and colonization history interact with morph type to shape genomic variation in an Arctic fish

Funding Information: Thanks go to our editor and three anonymous reviewers whose suggestions greatly improved this study. We thank S. Avery, J. Callahan, S. Duffy, S. Hann, L. Pike, R. Solomon, A. Walsh, for assistance with sample collection and fieldwork. We are grateful to X. Dallaire and J.S. Moore for providing samples from Ungava, Bay (HAB) and to L. Bernatchez for his valuable comments on an earlier version of this manuscript. Thanks to Parks Canada for allowing us access to the Torngat Mountains National Park and the Nunatsiavut government for allowing us to collect samples from their lands. Thanks to A. Belay at Mount Sinai Hospital for her help with sequencing, A. Mesmer for help with genotyping, and S. Lehnert for insightful data analysis suggestions. We also thank the Institute for Biodiversity, Ecosystem Science, and Sustainability of the Department of Environment and Conservation of the Government of Labrador and Newfoundland for funding for this project; NSERC for the Strategic Grant STPGP 430198 and Discovery Grant awarded to DER, for the CGS‐D awarded to SJS; the Killam Trust for the Level 2 Izaak awarded to SJS; and the Government of Nova Scotia for the Graduate Scholarship awarded to SJS. Publisher Copyright: © 2023 The Authors. Molecular Ecology published by John Wiley & Sons Ltd.Peer reviewedPublisher PD

Landscape, colonization and life history : their effects on genetic diversity in four sympatric species inhabiting a dendritic system

Funding: Marine Alliance for Science and Technology for Scotland (MASTS), which is funded by the Scottish Funding Council (grant reference HR09011) (O.E.G.).To what degree are patterns of genetic structure in fragmented systems the result of contemporary landscape vs. history? We examined the distribution of genetic diversity as a function of colonization history and contemporary landscape in four fish species inhabiting a hierarchically fragmented, unaltered system, the Kogaluk drainage (Labrador): lake trout, longnose sucker, round whitefish, and lake chub. The footprint of colonization history was still observable in the three species where this issue was examined regardless of the generations since their arrival. ABC analyses suggest colonization took place from the southwest. The species exhibit similar diversity patterns despite different Nes and generation intervals. Contemporary gene flow was largely negligible except for gene flow from a centrally located lake. These results suggest landscape has driven colonization history, which still has influence on genetic structuring. The species are widespread. Understanding how they behave in the pristine Kogaluk provides a baseline against which to evaluate how other anthropogenically perturbed systems are performing. Improved understanding of historical and contemporary processes is required to fully explain diversity patterns in complex metapopulationsPostprintPeer reviewe

Select Atrophied Regions in Alzheimer disease (SARA): An improved volumetric model for identifying Alzheimer disease dementia

INTRODUCTION: Volumetric biomarkers for Alzheimer disease (AD) are attractive due to their wide availability and ease of administration, but have traditionally shown lower diagnostic accuracy than measures of neuropathological contributors to AD. Our purpose was to optimize the diagnostic specificity of structural MRIs for AD using quantitative, data-driven techniques. METHODS: This retrospective study assembled several non-overlapping cohorts (total n = 1287) with publicly available data and clinical patients from Barnes-Jewish Hospital (data gathered 1990-2018). The Normal Aging Cohort (n = 383) contained amyloid biomarker negative, cognitively normal (CN) participants, and provided a basis for determining age-related atrophy in other cohorts. The Training (n = 216) and Test (n = 109) Cohorts contained participants with symptomatic AD and CN controls. Classification models were developed in the Training Cohort and compared in the Test Cohort using the receiver operating characteristics areas under curve (AUCs). Additional model comparisons were done in the Clinical Cohort (n = 579), which contained patients who were diagnosed with dementia due to various etiologies in a tertiary care outpatient memory clinic. RESULTS: While the Normal Aging Cohort showed regional age-related atrophy, classification models were not improved by including age as a predictor or by using volumetrics adjusted for age-related atrophy. The optimal model used multiple regions (hippocampal volume, inferior lateral ventricle volume, amygdala volume, entorhinal thickness, and inferior parietal thickness) and was able to separate AD and CN controls in the Test Cohort with an AUC of 0.961. In the Clinical Cohort, this model separated AD from non-AD diagnoses with an AUC 0.820, an incrementally greater separation of the cohort than by hippocampal volume alone (AUC of 0.801, p = 0.06). Greatest separation was seen for AD vs. frontotemporal dementia and for AD vs. non-neurodegenerative diagnoses. CONCLUSIONS: Volumetric biomarkers distinguished individuals with symptomatic AD from CN controls and other dementia types but were not improved by controlling for normal aging

Audit Tendering in the UK: A Review of Stakeholders’ Views

This study reports the results of a content analysis of the comment letters sent to the UK Financial Reporting Council (FRC), in response to its consultation document on the 2012 revisions of the UK Corporate Governance Code, concerning the proposal for mandatory audit tendering. The results indicate a general support for the FRC’s proposals with a number of key concerns related to audit quality, auditor independence and audit cost. There is also clear conflict of interests among some stakeholder groups such as audit firms and companies on one side and institutional investors on the other side. There is evidence of conflict of interest between Big 4 and non-Big 4 audit firms. Implications for future consultations and legislations are also discussed

MTar: a computational microRNA target prediction architecture for human transcriptome

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) play an essential task in gene regulatory networks by inhibiting the expression of target mRNAs. As their mRNA targets are genes involved in important cell functions, there is a growing interest in identifying the relationship between miRNAs and their target mRNAs. So, there is now a imperative need to develop a computational method by which we can identify the target mRNAs of existing miRNAs. Here, we proposed an efficient machine learning model to unravel the relationship between miRNAs and their target mRNAs.</p> <p>Results</p> <p>We present a novel computational architecture MTar for miRNA target prediction which reports 94.5% sensitivity and 90.5% specificity. We identified 16 positional, thermodynamic and structural parameters from the wet lab proven miRNA:mRNA pairs and MTar makes use of these parameters for miRNA target identification. It incorporates an Artificial Neural Network (ANN) verifier which is trained by wet lab proven microRNA targets. A number of hitherto unknown targets of many miRNA families were located using MTar. The method identifies all three potential miRNA targets (5' seed-only, 5' dominant, and 3' canonical) whereas the existing solutions focus on 5' complementarities alone.</p> <p>Conclusion</p> <p>MTar, an ANN based architecture for identifying functional regulatory miRNA-mRNA interaction using predicted miRNA targets. The area of target prediction has received a new momentum with the function of a thermodynamic model incorporating target accessibility. This model incorporates sixteen structural, thermodynamic and positional features of residues in miRNA: mRNA pairs were employed to select target candidates. So our novel machine learning architecture, MTar is found to be more comprehensive than the existing methods in predicting miRNA targets, especially human transcritome.</p

Enhancing assertive community treatment with cognitive behavioral social skills training for schizophrenia: study protocol for a randomized controlled trial

BACKGROUND: Schizophrenia leads to profound disability in everyday functioning (e.g., difficulty finding and maintaining employment, housing, and personal relationships). Medications can effectively reduce positive symptoms (e.g., hallucinations and delusions), but they do not meaningfully improve daily life functioning. Psychosocial evidence-based practices (EBPs) improve functioning, but these EBPs are not available to most people with schizophrenia. The field must close the research and service delivery gap by adapting EBPs for schizophrenia to facilitate widespread implementation in community settings. Our hybrid effectiveness and implementation study represents an initiative to bridge this divide. In this study we will test whether an existing EBP (i.e., Cognitive Behavioral Social Skills Training (CBSST)) modified to work in practice settings (i.e., Assertive Community Treatment (ACT) teams) commonly available to persons with schizophrenia results in better consumer outcomes. We will also identify key factors relevant to developing future CBSST implementation strategies. METHODS/DESIGN: For the effectiveness study component, persons with schizophrenia will be recruited from existing publicly funded ACT teams operating in community settings. Participants will be randomized to one of the 2 treatments (ACT alone or ACT + Adapted CBSST) and followed longitudinally for 18 months with assessments every 18 weeks after baseline (5 in total). The primary outcome domain is psychosocial functioning (e.g., everyday living skills and activities related to employment, education, and housing) as measured by self-report, testing, and observation. Additional outcome domains of interest include mediators of change in functioning, symptoms, and quality of services. Primary analyses will be conducted using linear mixed-effects models for continuous data. The implementation study component consists of a structured, mixed qualitative-quantitative methodology (i.e., Concept Mapping) to characterize and assess the implementation experience from multiple stakeholder perspectives in order to inform future implementation initiatives. DISCUSSION: Adapting CBSST to fit into the ACT service delivery context found throughout the United States creates an opportunity to substantially increase the number of persons with schizophrenia who could have access to and benefit from EBPs. As part of the implementation learning process training materials and treatment workbooks have been revised to promote easier use of CBSST in the context of brief community-based ACT visits. TRIAL REGISTRATION: ClinicalTrials.gov NCT02254733. Date of registration: 25 April 2014

Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN)

The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case-control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual's point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of 'sporadic' AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers