Effectiveness of Vegetative Filter Strips in Controlling Losses of Surface-Applied Poultry Litter Constituents

Vegetative filter strips (VFS) have been shown to have high potential for reducing nonpoint source pollution from cultivated agricultural source areas, but information from uncultivated source areas amended with poultry litter is limited. Simulated rainfall was used in analyzing effects of VFS length (0, 3.1, 6.1, 9.2, 15.2, and 21.4 m) on quality of runoff from fescue (Festuca arundinacea Schreb.) plots (1.5 x 24.4 m) amended with poultry litter (5 Mg/ha). The VFS reduced mass transport of ammonia-nitrogen (NH3-N), total Kjeldahl nitrogen (TKN), ortho-phosphorus (PO4-P), total phosphorus (TP), chemical oxygen demand (COD), and total suspended solids (TSS). Mass transport of TKN, NH3-N, TP, and PO4-P were reduced by averages of 39, 47, 40, and 39%, respectively, by 3.1 m VFS and by 81, 98, 91, and 90%, respectively, by 21.4 m VFS. Effectiveness of VFS in terms of mass transport reduction was unchanged, however, beyond 3.1 m length for TSS and COD and averaged 35 and 51%, respectively. The VFS were ineffective in removing nitrate-nitrogen from the incoming runoff. Removal of litter constituents was described very well (r2 = 0.70 to 0.94) by a first-order relationship between constituent removal and VFS length

AI ATAC 1: An Evaluation of Prominent Commercial Malware Detectors

This work presents an evaluation of six prominent commercial endpoint malware detectors, a network malware detector, and a file-conviction algorithm from a cyber technology vendor. The evaluation was administered as the first of the Artificial Intelligence Applications to Autonomous Cybersecurity (AI ATAC) prize challenges, funded by / completed in service of the US Navy. The experiment employed 100K files (50/50% benign/malicious) with a stratified distribution of file types, including ~1K zero-day program executables (increasing experiment size two orders of magnitude over previous work). We present an evaluation process of delivering a file to a fresh virtual machine donning the detection technology, waiting 90s to allow static detection, then executing the file and waiting another period for dynamic detection; this allows greater fidelity in the observational data than previous experiments, in particular, resource and time-to-detection statistics. To execute all 800K trials (100K files $\times$ 8 tools), a software framework is designed to choreographed the experiment into a completely automated, time-synced, and reproducible workflow with substantial parallelization. A cost-benefit model was configured to integrate the tools' recall, precision, time to detection, and resource requirements into a single comparable quantity by simulating costs of use. This provides a ranking methodology for cyber competitions and a lens through which to reason about the varied statistical viewpoints of the results. These statistical and cost-model results provide insights on state of commercial malware detection

Beyond the Hype: A Real-World Evaluation of the Impact and Cost of Machine Learning-Based Malware Detection

There is a lack of scientific testing of commercially available malware detectors, especially those that boast accurate classification of never-before-seen (i.e., zero-day) files using machine learning (ML). The result is that the efficacy and gaps among the available approaches are opaque, inhibiting end users from making informed network security decisions and researchers from targeting gaps in current detectors. In this paper, we present a scientific evaluation of four market-leading malware detection tools to assist an organization with two primary questions: (Q1) To what extent do ML-based tools accurately classify never-before-seen files without sacrificing detection ability on known files? (Q2) Is it worth purchasing a network-level malware detector to complement host-based detection? We tested each tool against 3,536 total files (2,554 or 72% malicious, 982 or 28% benign) including over 400 zero-day malware, and tested with a variety of file types and protocols for delivery. We present statistical results on detection time and accuracy, consider complementary analysis (using multiple tools together), and provide two novel applications of a recent cost-benefit evaluation procedure by Iannaconne & Bridges that incorporates all the above metrics into a single quantifiable cost. While the ML-based tools are more effective at detecting zero-day files and executables, the signature-based tool may still be an overall better option. Both network-based tools provide substantial (simulated) savings when paired with either host tool, yet both show poor detection rates on protocols other than HTTP or SMTP. Our results show that all four tools have near-perfect precision but alarmingly low recall, especially on file types other than executables and office files -- 37% of malware tested, including all polyglot files, were undetected.Comment: Includes Actionable Takeaways for SOC

Crop Updates 2005 - Farming Systems

This session covers forty four papers from different authors: PLENARY 1. 2005 Outlook, David Stephens and Nicola Telcik, Department of Agriculture FERTILITY AND NUTRITION 2. The effect of higher nitrogen fertiliser prices on rotation and fertiliser strategies in cropping systems, Ross Kingwell, Department of Agriculture and University of Western Australia 3. Stubble management: The short and long term implications for crop nutrition and soil fertility, Wayne Pluske, Nutrient Management Systems and Bill Bowden, Department of Agriculture 4. Stubble management: The pros and cons of different methods, Bill Bowden, Department of Agriculture, Western Australia and Mike Collins, WANTFA 5. Effect of stubble burning and seasonality on microbial processes and nutrient recycling, Frances Hoyle, The University of Western Australia 6. Soil biology and crop production in Western Australian farming systems, D.V. Murphy, N. Milton, M. Osman, F.C. Hoyle, L.K Abbott, W.R. Cookson and S. Darmawanto, The University of Western Australia 7. Urea is as effective as CAN when no rain for 10 days, Bill Crabtree, Crabtree Agricultural Consulting 8. Fertiliser (N,P,S,K) and lime requirements for wheat production in the Merredin district, Geoff Anderson, Department of Agriculture and Darren Kidson, Summit Fertilizers 9. Trace element applications: Up-front verses foliar? Bill Bowden and Ross Brennan, Department of Agriculture 10. Fertcare®, Environmental Product Stewardship and Advisor Standards for thee Fertiliser Industry, Nick Drew, Fertilizer Industry Federation of Australia (FIFA) SOIL AND LAND MANAGEMENT 11. Species response to row spacing, density and nutrition, Bill Bowden, Craig Scanlan, Lisa Sherriff, Bob French and Reg Lunt, Department of Agriculture 12. Investigation into the influence of row orientation in lupin crops, Jeff Russell, Department of Agriculture and Angie Roe, Farm Focus Consultants 13. Deriving variable rate management zones for crops, Ian Maling, Silverfox Solutions and Matthew Adams, DLI 14. In a world of Precision Agriculture, weigh trailers are not passé, Jeff Russell, Department of Agriculture 15. Cover crop management to combat ryegrass resistance and improve yields, Jeff Russell, Department of Agriculture and Angie Roe, Farm Focus Consultants 16. ARGT home page, the place to find information on annual ryegrass toxicity on the web, Dr George Yan, BART Pty Ltd 17. Shallow leading tine (SLT) ripper significantly reduces draft force, improves soil tilth and allows even distribution of subsoil ameliorants, Mohammad Hamza, Glen Riethmuller and Wal Anderson, Department of Agriculture PASTURE ANS SUMMER CROP SYSTEMS 18. New annual pasture legumes for Mediteranean farming systems, Angelo Loi, Phil Nichols, Clinton Revell and David Ferris, Department of Agriculture 19. How sustainable are phase rotations with Lucerne? Phil Ward, CSIRO Plant Industry 20. Management practicalities of summer cropping, Andrea Hills and Sally-Anne Penny, Department of Agriculture 21. Rainfall zone determines the effect of summer crops on winter yields, Andrea Hills, Sally-Anne Penny and David Hall, Department of Agriculture 22. Summer crops and water use, Andrea Hills, Sally-Anne Penny and David Hall, Department of Agriculture, and Michael Robertson and Don Gaydon, CSIRO Brisbane 23. Risk analysis of sorgum cropping, Andrea Hills and Sally-Anne Penny, Department of Agriculture, and Dr Michael Robertson and Don Gaydon, CSIRO Brisbane FARMER DECISION SUPPORT AND ADOPTION 24. Variety release and End Point Royalties – a new system? Tress Walmsley, Department of Agriculture 25. Farming system analaysis using the STEP Tool, Caroline Peek and Megan Abrahams, Department of Agriculture 26. The Leakage Calculator: A simple tool for groundwater recharge assessment, Paul Raper, Department of Agriculture 27. The cost of Salinity Calculator – your tool to assessing the profitability of salinity management options, Richard O’Donnell and Trevor Lacey, Department of Agriculture 28. Climate decision support tools, Meredith Fairbanks and David Tennant, Department of Agriculture 29. Horses for courses – using the best tools to manage climate risk, Cameron Weeks, Mingenew-Irwin Group/Planfarm and Richard Quinlan, Planfarm Agronomy 30. Use of seasonal outlook for making N decisions in Merredin, Meredith Fairbanks and Alexandra Edward, Department of Agriculture 31. Forecasts and profits, Benefits or bulldust? Chris Carter and Doug Hamilton, Department of Agriculture 32. A tool to estimate fixed and variable header and tractor depreciation costs, Peter Tozer, Department of Agriculture 33. Partners in grain: ‘Putting new faces in new places’, Renaye Horne, Department of Agriculture 34. Results from the Grower group Alliance, Tracey Gianatti, Grower Group Alliance 35. Local Farmer Group Network – farming systems research opportunities through local groups, Paul Carmody, Local Farmer Group Network GREENHOUSE GAS AND CLIMATE CHANGE 36. Changing rainfall patterns in the grainbelt, Ian Foster, Department of Agriculture 37. Vulnerability of broadscale agriculture to the impacts of climate change, Michele John, CSIRO (formerly Department of Agriculture) and Ross George, Department of Agriculture 38. Impacts of climate change on wheat yield at Merredin, Imma Farré and Ian Foster, Department of Agriculture 39. Climate change, land use suitability and water security, Ian Kininmonth, Dennis van Gool and Neil Coles, Department of Agriculture 40. Nitrous oxide emissions from cropping systems, Bill Porter, Department of Agriculture, Louise Barton, University of Western Australia 41. The potential of greenhouse sinks to underwrite improved land management in Western Australia, Richard Harper and Peter Ritson, CRC for Greenhouse Accounting and Forest Products Commission, Tony Beck, Tony Beck Consulting Services, Chris Mitchell and Michael Hill, CRC for Greenhouse Accounting 42. Removing uncertainty from greenhouse emissions, Fiona Barker-Reid, Will Gates, Ken Wilson and Rob Baigent, Department of Primary Industries - Victoria and CRC for Greenhouse Accounting (CRCGA), and Ian Galbally, Mick Meyer and Ian Weeks, CSIRO Atmospheric Research and CRCGA 43. Greenhouse in Agriculture Program (GIA), Traci Griffin, CRC for Greenhouse Accounting 44. Grains Greenhouse Accounting framework, D. Rodriguez, M. Probust, M. Meyers, D. Chen, A. Bennett, W. Strong, R. Nussey, I. Galbally and M. Howden CONTACT DETAILS FOR PRINCIPAL AUTHOR

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B.1.1.7: an ecological study

Background The SARS-CoV-2 variant B.1.1.7 was first identified in December, 2020, in England. We aimed to investigate whether increases in the proportion of infections with this variant are associated with differences in symptoms or disease course, reinfection rates, or transmissibility. Methods We did an ecological study to examine the association between the regional proportion of infections with the SARS-CoV-2 B.1.1.7 variant and reported symptoms, disease course, rates of reinfection, and transmissibility. Data on types and duration of symptoms were obtained from longitudinal reports from users of the COVID Symptom Study app who reported a positive test for COVID-19 between Sept 28 and Dec 27, 2020 (during which the prevalence of B.1.1.7 increased most notably in parts of the UK). From this dataset, we also estimated the frequency of possible reinfection, defined as the presence of two reported positive tests separated by more than 90 days with a period of reporting no symptoms for more than 7 days before the second positive test. The proportion of SARS-CoV-2 infections with the B.1.1.7 variant across the UK was estimated with use of genomic data from the COVID-19 Genomics UK Consortium and data from Public Health England on spike-gene target failure (a non-specific indicator of the B.1.1.7 variant) in community cases in England. We used linear regression to examine the association between reported symptoms and proportion of B.1.1.7. We assessed the Spearman correlation between the proportion of B.1.1.7 cases and number of reinfections over time, and between the number of positive tests and reinfections. We estimated incidence for B.1.1.7 and previous variants, and compared the effective reproduction number, Rt, for the two incidence estimates. Findings From Sept 28 to Dec 27, 2020, positive COVID-19 tests were reported by 36 920 COVID Symptom Study app users whose region was known and who reported as healthy on app sign-up. We found no changes in reported symptoms or disease duration associated with B.1.1.7. For the same period, possible reinfections were identified in 249 (0·7% [95% CI 0·6–0·8]) of 36 509 app users who reported a positive swab test before Oct 1, 2020, but there was no evidence that the frequency of reinfections was higher for the B.1.1.7 variant than for pre-existing variants. Reinfection occurrences were more positively correlated with the overall regional rise in cases (Spearman correlation 0·56–0·69 for South East, London, and East of England) than with the regional increase in the proportion of infections with the B.1.1.7 variant (Spearman correlation 0·38–0·56 in the same regions), suggesting B.1.1.7 does not substantially alter the risk of reinfection. We found a multiplicative increase in the Rt of B.1.1.7 by a factor of 1·35 (95% CI 1·02–1·69) relative to pre-existing variants. However, Rt fell below 1 during regional and national lockdowns, even in regions with high proportions of infections with the B.1.1.7 variant. Interpretation The lack of change in symptoms identified in this study indicates that existing testing and surveillance infrastructure do not need to change specifically for the B.1.1.7 variant. In addition, given that there was no apparent increase in the reinfection rate, vaccines are likely to remain effective against the B.1.1.7 variant. Funding Zoe Global, Department of Health (UK), Wellcome Trust, Engineering and Physical Sciences Research Council (UK), National Institute for Health Research (UK), Medical Research Council (UK), Alzheimer's Society