Relation of Cotton Root Rot and Fusarium Wilt to the Acidity and Alkalinity of the Soil.

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Using Soil and Water Conservation Contests for Extension: Experiences from the Bolivian Mountain Valleys

Soil and water conservation (SWC) contests among farmer groups were organized in five rural villages in the Bolivian mountain valleys. The contests were aimed at quickly achieving widespread sustainable results. This article analyzes the effectiveness of these contests as an extension tool. Mixed results were obtained. In three villages, participation rates in the SWC activities introduced in the contests were still high even 2 years after project withdrawal. These were all villages where a solid foundation for sustainable development had been laid before the contests were held. Two years later, most families were still involved in maintenance of the SWC practices introduced in the contests, and many farmers had started to experiment with different soil management practices. However, replications of these SWC practices were not widespread, Conservation Leaders did not continue with their training activities, and the quality of maintenance of the practices was often not satisfactory. In order to become a more effective extension tool and achieve widespread impact, SWC contests must receive continued support by a catalyst agency. Moreover, other SWC contests should also be organized in which practices are not predefined. Given that SWC contests are a low-budget extension tool, local municipalities could become more actively involved

Applied Machine Learning for the Prediction of Growth of Abdominal Aortic Aneurysm in Humans

Objective: Accurate prediction of abdominal aortic aneurysm (AAA) growth in an individual can allow personalised stratification of surveillance intervals and better inform the timing for surgery. The authors recently described the novel significant association between flow mediated dilatation (FMD) and future AAA growth. The feasibility of predicting future AAA growth was explored in individual patients using a set of benchmark machine learning techniques. Methods: The Oxford Abdominal Aortic Aneurysm Study (OxAAA) prospectively recruited AAA patients undergoing the routine NHS management pathway. In addition to the AAA diameter, FMD was systemically measured in these patients. A benchmark machine learning technique (non-linear Kernel support vector regression) was applied to predict future AAA growth in individual patients, using their baseline FMD and AAA diameter as input variables. Results: Prospective growth data were recorded at 12 months (360 ± 49 days) in 94 patients. Of these, growth data were further recorded at 24 months (718 ± 81 days) in 79 patients. The average growth in AAA diameter was 3.4% at 12 months, and 2.8% per year at 24 months. The algorithm predicted the individual's AAA diameter to within 2 mm error in 85% and 71% of patients at 12 and 24 months. Conclusions: The data highlight the utility of FMD as a biomarker for AAA and the value of machine learning techniques for AAA research in the new era of precision medicine

The Swift Ultra-Violet/Optical Telescope

The UV/Optical Telescope (UVOT) is one of three instruments flying aboard the Swift Gamma-ray Observatory. It is designed to capture the early (approximately 1 minute) UV and optical photons from the afterglow of gamma-ray bursts in the 170-600 nm band as well as long term observations of these afterglows. This is accomplished through the use of UV and optical broadband filters and grisms. The UVOT has a modified Ritchey-Chretien design with micro-channel plate intensified charged-coupled device detectors that record the arrival time of individual photons and provide sub-arcsecond positioning of sources. We discuss some of the science to be pursued by the UVOT and the overall design of the instrument.Comment: 55 Pages, 28 Figures, To be published in Space Science Review

The SARS-CoV-2 Alpha variant was associated with increased clinical severity of COVID-19 in Scotland: A genomics-based retrospective cohort analysis

Objectives The SARS-CoV-2 Alpha variant was associated with increased transmission relative to other variants present at the time of its emergence and several studies have shown an association between Alpha variant infection and increased hospitalisation and 28-day mortality. However, none have addressed the impact on maximum severity of illness in the general population classified by the level of respiratory support required, or death. We aimed to do this. Methods In this retrospective multi-centre clinical cohort sub-study of the COG-UK consortium, 1475 samples from Scottish hospitalised and community cases collected between 1st November 2020 and 30th January 2021 were sequenced. We matched sequence data to clinical outcomes as the Alpha variant became dominant in Scotland and modelled the association between Alpha variant infection and severe disease using a 4-point scale of maximum severity by 28 days: 1. no respiratory support, 2. supplemental oxygen, 3. ventilation and 4. death. Results Our cumulative generalised linear mixed model analyses found evidence (cumulative odds ratio: 1.40, 95% CI: 1.02, 1.93) of a positive association between increased clinical severity and lineage (Alpha variant versus pre-Alpha variants). Conclusions The Alpha variant was associated with more severe clinical disease in the Scottish population than co-circulating lineages

Investigation of hospital discharge cases and SARS-CoV-2 introduction into Lothian care homes

Summary Background The first epidemic wave of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Scotland resulted in high case numbers and mortality in care homes. In Lothian, over one-third of care homes reported an outbreak, while there was limited testing of hospital patients discharged to care homes. Aim To investigate patients discharged from hospitals as a source of SARS-CoV-2 introduction into care homes during the first epidemic wave. Methods A clinical review was performed for all patients discharges from hospitals to care homes from 1st March 2020 to 31st May 2020. Episodes were ruled out based on coronavirus disease 2019 (COVID-19) test history, clinical assessment at discharge, whole-genome sequencing (WGS) data and an infectious period of 14 days. Clinical samples were processed for WGS, and consensus genomes generated were used for analysis using Cluster Investigation and Virus Epidemiological Tool software. Patient timelines were obtained using electronic hospital records. Findings In total, 787 patients discharged from hospitals to care homes were identified. Of these, 776 (99%) were ruled out for subsequent introduction of SARS-CoV-2 into care homes. However, for 10 episodes, the results were inconclusive as there was low genomic diversity in consensus genomes or no sequencing data were available. Only one discharge episode had a genomic, time and location link to positive cases during hospital admission, leading to 10 positive cases in their care home. Conclusion The majority of patients discharged from hospitals were ruled out for introduction of SARS-CoV-2 into care homes, highlighting the importance of screening all new admissions when faced with a novel emerging virus and no available vaccine