151 research outputs found

    Detecting and Predicting Emerging Disease in Poultry With the Implementation of New Technologies and Big Data: A Focus on Avian Influenza Virus

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    Future demands for food will place agricultural systems under pressure to increase production. Poultry is accepted as a good source of protein and the poultry industry will be forced to intensify production in many countries, leading to greater numbers of farms that house birds at elevated densities. Increasing farmed poultry can facilitate enhanced transmission of infectious pathogens among birds, such as avian influenza virus among others, which have the potential to induce widespread mortality in poultry and cause considerable economic losses. Additionally, the capability of some emerging poultry pathogens to cause zoonotic human infection will be increased as greater numbers of poultry operations could increase human contact with poultry pathogens. In order to combat the increased risk of spread of infectious disease in poultry due to intensified systems of production, rapid detection and diagnosis is paramount. In this review, multiple technologies that can facilitate accurate and rapid detection and diagnosis of poultry diseases are highlighted from the literature, with a focus on technologies developed specifically for avian influenza virus diagnosis. Rapid detection and diagnostic technologies allow for responses to be made sooner when disease is detected, decreasing further bird transmission and associated costs. Additionally, systems of rapid disease detection produce data that can be utilized in decision support systems that can predict when and where disease is likely to emerge in poultry. Other sources of data can be included in predictive models, and in this review two highly relevant sources, internet based-data and environmental data, are discussed. Additionally, big data and big data analytics, which will be required in order to integrate voluminous and variable data into predictive models that function in near real-time are also highlighted. Implementing new technologies in the commercial setting will be faced with many challenges, as will designing and operating predictive models for poultry disease emergence. The associated challenges are summarized in this review. Intensified systems of poultry production will require new technologies for detection and diagnosis of infectious disease. This review sets out to summarize them, while providing advantages and limitations of different types of technologies being researched

    Corrigendum: Detecting and Predicting Emerging Disease in Poultry With the Implementation of New Technologies and Big Data: A Focus on Avian Influenza Virus

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    Future demands for food will place agricultural systems under pressure to increase production. Poultry is accepted as a good source of protein and the poultry industry will be forced to intensify production in many countries, leading to greater numbers of farms that house birds at elevated densities. Increasing farmed poultry can facilitate enhanced transmission of infectious pathogens among birds, such as avian influenza virus among others, which have the potential to induce widespread mortality in poultry and cause considerable economic losses. Additionally, the capability of some emerging poultry pathogens to cause zoonotic human infection will be increased as greater numbers of poultry operations could increase human contact with poultry pathogens. In order to combat the increased risk of spread of infectious disease in poultry due to intensified systems of production, rapid detection and diagnosis is paramount. In this review, multiple technologies that can facilitate accurate and rapid detection and diagnosis of poultry diseases are highlighted from the literature, with a focus on technologies developed specifically for avian influenza virus diagnosis. Rapid detection and diagnostic technologies allow for responses to be made sooner when disease is detected, decreasing further bird transmission and associated costs. Additionally, systems of rapid disease detection produce data that can be utilized in decision support systems that can predict when and where disease is likely to emerge in poultry. Other sources of data can be included in predictive models, and in this review two highly relevant sources, internet based-data and environmental data, are discussed. Additionally, big data and big data analytics, which will be required in order to integrate voluminous and variable data into predictive models that function in near real-time are also highlighted. Implementing new technologies in the commercial setting will be faced with many challenges, as will designing and operating predictive models for poultry disease emergence. The associated challenges are summarized in this review. Intensified systems of poultry production will require new technologies for detection and diagnosis of infectious disease. This review sets out to summarize them, while providing advantages and limitations of different types of technologies being researched

    Do health education initiatives assist socioeconomically disadvantaged populations? : a systematic review and meta-analyses

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    Background: Health education interventions are considered critical for the prevention and management of conditions of public health concern. Although the burden of these conditions is often greatest in socio-economically disadvantaged populations, the effectiveness of interventions that target these groups is unknown. We aimed to identify and synthesize evidence of the effectiveness of health-related educational interventions in adult disadvantaged populations. Methods: We pre-registered the study on Open Science Framework https://osf.io/ek5yg/. We searched Medline, Embase, Emcare, and the Cochrane Register from inception to 5/04/2022 to identify studies evaluating the effectiveness of health-related educational interventions delivered to adults in socio-economically disadvantaged populations. Our primary outcome was health related behaviour and our secondary outcome was a relevant biomarker. Two reviewers screened studies, extracted data and evaluated risk of bias. Our synthesis strategy involved random-effects meta-analyses and vote-counting. Results: We identified 8618 unique records, 96 met our criteria for inclusion – involving more than 57,000 participants from 22 countries. All studies had high or unclear risk of bias. For our primary outcome of behaviour, meta-analyses found a standardised mean effect of education on physical activity of 0.05 (95% confidence interval (CI) = -0.09–0.19), (5 studies, n = 1330) and on cancer screening of 0.29 (95% CI = 0.05–0.52), (5 studies, n = 2388). Considerable statistical heterogeneity was present. Sixty-seven of 81 studies with behavioural outcomes had point estimates favouring the intervention (83% (95% CI = 73%-90%), p < 0.001); 21 of 28 studies with biomarker outcomes showed benefit (75% (95%CI = 56%-88%), p = 0.002). When effectiveness was determined based on conclusions in the included studies, 47% of interventions were effective on behavioural outcomes, and 27% on biomarkers. Conclusions: Evidence does not demonstrate consistent, positive impacts of educational interventions on health behaviours or biomarkers in socio-economically disadvantaged populations. Continued investment in targeted approaches, coinciding with development of greater understanding of factors determining successful implementation and evaluation, are important to reduce inequalities in health

    Outside the gate: sub-urban legal practices in early medieval England

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    Many aspects of English early medieval (Anglo-Saxon) legal landscapes can be discerned in archaeological and toponymic evidence, ranging from the locations of legislative councils and judicial assemblies to sites of capital punishment. Among the corpus of such sites a striking group can be detected at the periphery of urban spaces. Gates into a number of towns appear to have functioned as legislative meeting-places, and even gave their names to some legally constituted communities, while suburban locations also feature prominently as sites of gallows and public punishment. In this paper historical, archaeological and toponymic evidence is used to examine this phenomenon of suburban legal practices and to pose questions about the wider dimensions of the early medieval legal landscape

    Pattern selection in the absolutely unstable regime as a nonlinear eigenvalue problem: Taylor vortices in axial flow

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    A unique pattern selection in the absolutely unstable regime of a driven, nonlinear, open-flow system is analyzed: The spatiotemporal structures of rotationally symmetric vortices that propagate downstream in the annulus of the rotating Taylor-Couette system due to an externally imposed axial through-flow are investigated for two different axial boundary conditions at the in- and outlet. Unlike the stationary patterns in systems without through-flow the spatiotemporal structures of propagating vortices are independent of parameter history, initial conditions, and system's length. They do, however, depend on the axial boundary conditions, the driving rate of the inner cylinder and the through-flow rate. Our analysis of the amplitude equation shows that the pattern selection can be described by a nonlinear eigenvalue problem with the frequency being the eigenvalue. Approaching the border between absolute and convective instability the eigenvalue problem becomes effectively linear and the selection mechanism approaches that one of linear front propagation. PACS:47.54.+r,47.20.Ky,47.32.-y,47.20.FtComment: 15 pages (LateX-file), 8 figures (Postscript

    Impact of gastro-oesophageal reflux on microRNA expression, location and function

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    We have shown that miRNA expression is altered in the oesophageal squamous mucosa from individuals with gastro-oesophageal reflux and ulcerative oesophagitis. These changes in miR-143, miR-145 and miR-205 expression appear to be most pronounced in the basal layer of the oesophageal epithelium. In the context of gastro-oesophageal reflux these expression changes might influence proliferation and apoptosis and thereby regulate epithelial restoration. It is reasonable to hypothesise that they could represent early molecular events preceding the development of Barrett’s oesophagus, although proving this will require further studies as described above. Future detailed analyses of the role of these miRNAs in progression from gastro-oesophageal reflux to Barrett’s oesophagus, and then to oesophageal adenocarcinoma will be valuable, and may help in efforts to control and treat these diseases.This study was funded by a Competing Project Grant from the National Health and Medical Research Council of Australia. Cameron Smith was supported by a PROBE-NET PhD scholarship funded by a Strategic research Partnerships Grant from the Cancer Council of New South Wales

    NLO QCD+EW predictions for HV and HV +jet production including parton-shower effects

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    We present the first NLO QCD+EW predictions for Higgs boson production in association with a ℓνℓ or ℓ+ℓ− pair plus zero or one jets at the LHC. Fixed-order NLO QCD+EW calculations are combined with a QCD+QED parton shower using the recently developed resonance-aware method in the POWHEG framework. Moreover, applying the improved MiNLO technique to Hℓνℓ +jet and Hℓ+ℓ− +jet production at NLO QCD+EW, we obtain predictions that are NLO accurate for observables with both zero or one resolved jet. This approach permits also to capture higher-order effects associated with the interplay of EW corrections and QCD radiation. The behavior of EW corrections is studied for various kinematic distributions, relevant for experimental analyses of Higgsstrahlung processes at the 13 TeV LHC. Exact NLO EW corrections are complemented with approximate analytic formulae that account for the leading and next-to-leading Sudakov logarithms in the high-energy regime. In the tails of transverse-momentum distributions, relevant for analyses in the boosted Higgs regime, the Sudakov approximation works well, and NLO EW effects can largely exceed the ten percent level. Our predictions are based on the POWHEG BOX RES+OpenLoops framework in combination with the Pythia 8.1 parton shower
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