Lateral Deformation and Associated Settlement Resulting From Embankment Loading of Soft Clay and Silt Deposits

602 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2001.Using the empirical database and the developed procedures, it was possible to make successful prediction of lateral deformation and associated settlement for embankments on soft clay and silt deposits.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

Combining Artificial Intelligence and Image Processing for Diagnosing Diabetic Retinopathy in Retinal Fundus Images

Retinopathy is an eye disease caused by diabetes, and early detection and treatment can potentially reduce the risk of blindness in diabetic retinopathy sufferers. Using retinal Fundus images, diabetic retinopathy can be diagnosed, recognized, and treated. In the current state of the art, sensitivity and specificity are lacking. However, there are still a number of problems to be solved in state-of-the-art techniques like performance, accuracy, and being able to identify DR disease effectively with greater accuracy. In this paper, we have developed a new approach based on a combination of image processing and artificial intelligence that will meet the performance criteria for the detection of disease-causing diabetes retinopathy in Fundus images. Automatic detection of diabetic retinopathy has been proposed and has been carried out in several stages. The analysis was carried out in MATLAB using software-based simulation, and the results were then compared with those of expert ophthalmologists to verify their accuracy. Different types of diabetic retinopathy are represented in the experimental evaluation, including exudates, micro-aneurysms, and retinal hemorrhages. The detection accuracies shown by the experiments are greater than 98.80 percent

Table_2_Plant virus diversity in bee and pollen samples from apple (Malus domestica) and sweet cherry (Prunus avium) agroecosystems.xlsx

IntroductionHoney bee (Apis mellifera) pollination is widely used in tree fruit production systems to improve fruit set and yield. Many plant viruses can be associated with pollen or transmitted through pollination, and can be detected through bee pollination activities. Honey bees visit multiple plants and flowers in one foraging trip, essentially sampling small amounts of pollen from a wide area. Here we report metagenomics-based area-wide monitoring of plant viruses in cherry (Prunus avium) and apple (Malus domestica) orchards in Creston Valley, British Columbia, Canada, through bee-mediated pollen sampling.MethodsPlant viruses were identified in total RNA extracted from bee and pollen samples, and compared with profiles from double stranded RNA extracted from leaf and flower tissues. CVA, PDV, PNRSV, and PVF coat protein nucleotide sequences were aligned and compared for phylogenetic analysis.ResultsA wide array of plant viruses were identified in both systems, with cherry virus A (CVA), prune dwarf virus (PDV), prunus necrotic ringspot virus (PNRSV), and prunus virus F (PVF) most commonly detected. Citrus concave gum associated virus and apple stem grooving virus were only identified in samples collected during apple bloom, demonstrating changing viral profiles from the same site over time. Different profiles of viruses were identified in bee and pollen samples compared to leaf and flower samples reflective of pollen transmission affinity of individual viruses. Phylogenetic and pairwise analysis of the coat protein regions of the four most commonly detected viruses showed unique patterns of nucleotide sequence diversity, which could have implications in their evolution and management approaches. Coat protein sequences of CVA and PVF were broadly diverse with multiple distinct phylogroups identified, while PNRSV and PDV were more conserved.ConclusionThe pollen virome in fruit production systems is incredibly diverse, with CVA, PDV, PNRSV, and PVF widely prevalent in this region. Bee-mediated monitoring in agricultural systems is a powerful approach to study viral diversity and can be used to guide more targeted management approaches.</p

Table_3_Plant virus diversity in bee and pollen samples from apple (Malus domestica) and sweet cherry (Prunus avium) agroecosystems.xlsx

IntroductionHoney bee (Apis mellifera) pollination is widely used in tree fruit production systems to improve fruit set and yield. Many plant viruses can be associated with pollen or transmitted through pollination, and can be detected through bee pollination activities. Honey bees visit multiple plants and flowers in one foraging trip, essentially sampling small amounts of pollen from a wide area. Here we report metagenomics-based area-wide monitoring of plant viruses in cherry (Prunus avium) and apple (Malus domestica) orchards in Creston Valley, British Columbia, Canada, through bee-mediated pollen sampling.MethodsPlant viruses were identified in total RNA extracted from bee and pollen samples, and compared with profiles from double stranded RNA extracted from leaf and flower tissues. CVA, PDV, PNRSV, and PVF coat protein nucleotide sequences were aligned and compared for phylogenetic analysis.ResultsA wide array of plant viruses were identified in both systems, with cherry virus A (CVA), prune dwarf virus (PDV), prunus necrotic ringspot virus (PNRSV), and prunus virus F (PVF) most commonly detected. Citrus concave gum associated virus and apple stem grooving virus were only identified in samples collected during apple bloom, demonstrating changing viral profiles from the same site over time. Different profiles of viruses were identified in bee and pollen samples compared to leaf and flower samples reflective of pollen transmission affinity of individual viruses. Phylogenetic and pairwise analysis of the coat protein regions of the four most commonly detected viruses showed unique patterns of nucleotide sequence diversity, which could have implications in their evolution and management approaches. Coat protein sequences of CVA and PVF were broadly diverse with multiple distinct phylogroups identified, while PNRSV and PDV were more conserved.ConclusionThe pollen virome in fruit production systems is incredibly diverse, with CVA, PDV, PNRSV, and PVF widely prevalent in this region. Bee-mediated monitoring in agricultural systems is a powerful approach to study viral diversity and can be used to guide more targeted management approaches.</p

Table_4_Plant virus diversity in bee and pollen samples from apple (Malus domestica) and sweet cherry (Prunus avium) agroecosystems.xlsx

IntroductionHoney bee (Apis mellifera) pollination is widely used in tree fruit production systems to improve fruit set and yield. Many plant viruses can be associated with pollen or transmitted through pollination, and can be detected through bee pollination activities. Honey bees visit multiple plants and flowers in one foraging trip, essentially sampling small amounts of pollen from a wide area. Here we report metagenomics-based area-wide monitoring of plant viruses in cherry (Prunus avium) and apple (Malus domestica) orchards in Creston Valley, British Columbia, Canada, through bee-mediated pollen sampling.MethodsPlant viruses were identified in total RNA extracted from bee and pollen samples, and compared with profiles from double stranded RNA extracted from leaf and flower tissues. CVA, PDV, PNRSV, and PVF coat protein nucleotide sequences were aligned and compared for phylogenetic analysis.ResultsA wide array of plant viruses were identified in both systems, with cherry virus A (CVA), prune dwarf virus (PDV), prunus necrotic ringspot virus (PNRSV), and prunus virus F (PVF) most commonly detected. Citrus concave gum associated virus and apple stem grooving virus were only identified in samples collected during apple bloom, demonstrating changing viral profiles from the same site over time. Different profiles of viruses were identified in bee and pollen samples compared to leaf and flower samples reflective of pollen transmission affinity of individual viruses. Phylogenetic and pairwise analysis of the coat protein regions of the four most commonly detected viruses showed unique patterns of nucleotide sequence diversity, which could have implications in their evolution and management approaches. Coat protein sequences of CVA and PVF were broadly diverse with multiple distinct phylogroups identified, while PNRSV and PDV were more conserved.ConclusionThe pollen virome in fruit production systems is incredibly diverse, with CVA, PDV, PNRSV, and PVF widely prevalent in this region. Bee-mediated monitoring in agricultural systems is a powerful approach to study viral diversity and can be used to guide more targeted management approaches.</p

Table_1_Plant virus diversity in bee and pollen samples from apple (Malus domestica) and sweet cherry (Prunus avium) agroecosystems.xlsx

IntroductionHoney bee (Apis mellifera) pollination is widely used in tree fruit production systems to improve fruit set and yield. Many plant viruses can be associated with pollen or transmitted through pollination, and can be detected through bee pollination activities. Honey bees visit multiple plants and flowers in one foraging trip, essentially sampling small amounts of pollen from a wide area. Here we report metagenomics-based area-wide monitoring of plant viruses in cherry (Prunus avium) and apple (Malus domestica) orchards in Creston Valley, British Columbia, Canada, through bee-mediated pollen sampling.MethodsPlant viruses were identified in total RNA extracted from bee and pollen samples, and compared with profiles from double stranded RNA extracted from leaf and flower tissues. CVA, PDV, PNRSV, and PVF coat protein nucleotide sequences were aligned and compared for phylogenetic analysis.ResultsA wide array of plant viruses were identified in both systems, with cherry virus A (CVA), prune dwarf virus (PDV), prunus necrotic ringspot virus (PNRSV), and prunus virus F (PVF) most commonly detected. Citrus concave gum associated virus and apple stem grooving virus were only identified in samples collected during apple bloom, demonstrating changing viral profiles from the same site over time. Different profiles of viruses were identified in bee and pollen samples compared to leaf and flower samples reflective of pollen transmission affinity of individual viruses. Phylogenetic and pairwise analysis of the coat protein regions of the four most commonly detected viruses showed unique patterns of nucleotide sequence diversity, which could have implications in their evolution and management approaches. Coat protein sequences of CVA and PVF were broadly diverse with multiple distinct phylogroups identified, while PNRSV and PDV were more conserved.ConclusionThe pollen virome in fruit production systems is incredibly diverse, with CVA, PDV, PNRSV, and PVF widely prevalent in this region. Bee-mediated monitoring in agricultural systems is a powerful approach to study viral diversity and can be used to guide more targeted management approaches.</p

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population