Teaching computational reproducibility for neuroimaging

We describe a project-based introduction to reproducible and collaborative neuroimaging analysis. Traditional teaching on neuroimaging usually consists of a series of lectures that emphasize the big picture rather than the foundations on which the techniques are based. The lectures are often paired with practical workshops in which students run imaging analyses using the graphical interface of specific neuroimaging software packages. Our experience suggests that this combination leaves the student with a superficial understanding of the underlying ideas, and an informal, inefficient, and inaccurate approach to analysis. To address these problems, we based our course around a substantial open-ended group project. This allowed us to teach: (a) computational tools to ensure computationally reproducible work, such as the Unix command line, structured code, version control, automated testing, and code review and (b) a clear understanding of the statistical techniques used for a basic analysis of a single run in an MRI scanner. The emphasis we put on the group project showed the importance of standard computational tools for accuracy, efficiency, and collaboration. The projects were broadly successful in engaging students in working reproducibly on real scientific questions. We propose that a course on this model should be the foundation for future programs in neuroimaging. We believe it will also serve as a model for teaching efficient and reproducible research in other fields of computational science

Implementation costs of a multi-component program to increase human papillomavirus (HPV) vaccination in a network of pediatric clinics

Introduction: HPV vaccination is both a clinically and cost-effective way to prevent HPV-related cancers. Increased focus on preventing HPV infection and HPV-related cancers has motivated development of strategies to increase adolescent vaccination rates. This analysis estimates the average cost associated with implementing programs aimed at increasing HPV vaccination from the perspective of the clinic decision makers. As providers and healthcare organizations consider vaccination initiatives, it is important for them to understand the costs associated with implementing these programs. Methods: Healthcare provider assessment and feedback, reminders, and education; and parent education/reminder strategies were implemented in a large pediatric clinic network between October 2015 and February 2018 to improve HPV vaccination rates. A micro-costing method was used in 2018 to prospectively estimate program implementation costs with the clinic as the unit of analysis. A sensitivity analysis assessed the effects of variability in levels of participation. Results: Assessment and feedback reports and provider education were implemented among 51 clinics at average per clinic cost of $786 and$368 respectively. Electronic vaccination reminders were delivered to providers and parents at a per clinic cost of $824. The parent education implementation cost was$2,126 per clinic. Conclusion: The four complimentary HPV evidence-based strategies were delivered at a total cost of $157,534 or$4,749 per clinic, including staff training and participant recruitment, reaching 155,000 HPV vaccine eligible adolescents

Drought climate adaptation program: producing enhanced agricultural crop insurance systems: summary report

Queensland farmers are subject to highly variable climatic conditions, including drought and floods, which can undermine production. Insurance could play an important role in helping Queensland farmers manage their climate risk. However, currently, the use of insurance to manage climate-related production risk is poorly understood and utilised by farmers. This project aims to address this gap by providing information on climate risks and the role of insurance for managing these. This project conducted focused reviews on climate risk in agriculture and on how insurance products could be used to address these risks. The project also carried out on-ground surveys from cotton and sugar industry and conducted modelling to assess risks and the role of insurance for cotton and sugar cane farmers in Queensland. Prototype climate assessment risk and reporting tools were also developed. The reviews carried out in this project identified that Queensland’s agricultural sector is highly exposed to production volatility as a result of weather risks. It is our view that the Queensland agricultural sector has an excellent opportunity to provide its farmers with protection against uninsured seasonal risks to crop production. Key climate and farming systems risks were identified by interviewing a total of 55 farmers (23 cotton growers and 32 sugar cane growers) across Queensland. Key climate risks to the cotton industry include hail, drought/dry years (lack of rainfall during planting and season), quality downgrade (discolouration), excessive heat, floods and wet weather (during the season and especially during harvest). Similarly, for the sugar industry, key climate risks include drought, flood, excessive rainfall during harvest, cyclone, pests and disease. Key messages from farmer surveys are that current insurance products available to Queensland farmers (specifically, cotton and sugar cane farmers) may not address critical risks to the production and/or profitability of these systems and that farmers would prefer to have comprehensive insurance products available that cover them against profitability losses across multiple risk factors. Based on survey findings three prototype insurance products were developed for the cotton industry Insurance products developed were Drought Cover: insufficient rainfall during the planting season – August to November; Drought Cover: insufficient rainfall during growing season – November to February; and Wet Harvest Cover: excessive rainfall during harvest season – March to June. Two prototype insurance products were developed for the sugar industry. They include; Cyclone Cover: crop damage during cyclone season – November to April; and Wet Harvest Cover: excessive rainfall during harvest season – June to December Rainfall-indexed based worked examples were also developed for sugar and cotton industry growers

Drought climate adaptation program: producing enhanced agricultural crop insurance systems: final report

Queensland farmers are subject to highly variable climatic conditions, including drought and floods, which can undermine production. Insurance could play an important role in helping Queensland farmers manage their climate risk. However, currently the use of insurance to manage climate related production risk is poorly understood and utilised by farmers. This project aims to address this gap by providing information on climate risks and the role of insurance for managing these. This project conducted focussed reviews on climate risk in agriculture and on how insurance products could be used to address these risks. The project also carried out on-ground surveys from cotton and sugar industry and conducted modelling to assess risks and the role of insurance for cotton and sugar cane farmers in Queensland. Prototype climate assessment risk and reporting tools were also developed. The reviews carried out in this project identified that Queensland’s agricultural sector is highly exposed to production volatility as a result of weather risks. It is our view that the Queensland agricultural sector has an excellent opportunity to provide its farmers with protection against uninsured seasonal risks to crop production. Key climate and farming systems risks were identified by interviewing a total of 55 farmers (23 cotton growers and 32 sugar cane growers) across Queensland. Key climate risks to the cotton industry include hail, drought/dry years (lack of rainfall during planting and season), quality downgrade (discolouration), excessive heat, floods and wet weather (during season and especially during harvest). Similarly, for the sugar industry, key climate risks include, drought, flood, excessive rainfall during harvest, cyclone, pests and disease. Key messages from farmer surveys are that current insurance products available to Queensland farmers (specifically, cotton and sugar cane farmers) may not address critical risks to the production and/or profitability of these systems and that farmers would prefer to have comprehensive insurance products available that cover them against profitability losses across multiple risk factors. A ‘climate and agricultural risk assessment and reporting tool’ (prototype) was developed as part of the project. This ‘tool’ allows quantification of key climate risks, initially for the sugar and cotton industry. The tool provides an option to generate a detail climate risk report based on historical data and a future seasonal climate forecast for an individual location. The tool data also serves as a dataset portal, allowing for the download of data in a required template. Cotton and sugarcane crop models APSIM and DSSAT were employed to simulate the growth and yield for 10 and 12 sites, respectively, across Queensland over the period 1940-2017 for various crop management factors. Comparing the simulated yields (from each model or the mean simulated value from ensemble models) to the observed yield (available at regional scale) the trend in year to year variability is satisfactorily captured for cotton on average, whereas for sugarcane there is a trend to overestimate or underestimate the yield depending on the site. Based on survey findings three prototype insurance products were developed for the cotton industry Insurance products developed were Drought Cover: insufficient rainfall during the planting season – August to November; Drought Cover: insufficient rainfall during growing season – November to February; and Wet Harvest Cover: excessive rainfall during harvest season – March to June. Two prototype insurance products were developed for sugar industry. They include; Cyclone Cover: crop damage during cyclone season – November to April; and Wet Harvest Cover: excessive rainfall during harvest season – June to December. Rainfall-indexed based worked examples were also developed for sugar and cotton industry growers to better appreciate the insurance mechanisms

Drought climate adaptation program: producing enhanced agricultural crop insurance systems: final report

Queensland farmers are subject to highly variable climatic conditions, including drought and floods, which can undermine production. Insurance could play an important role in helping Queensland farmers manage their climate risk. However, currently the use of insurance to manage climate related production risk is poorly understood and utilised by farmers. This project aims to address this gap by providing information on climate risks and the role of insurance for managing these. This project conducted focussed reviews on climate risk in agriculture and on how insurance products could be used to address these risks. The project also carried out on-ground surveys from cotton and sugar industry and conducted modelling to assess risks and the role of insurance for cotton and sugar cane farmers in Queensland. Prototype climate assessment risk and reporting tools were also developed. The reviews carried out in this project identified that Queensland’s agricultural sector is highly exposed to production volatility as a result of weather risks. It is our view that the Queensland agricultural sector has an excellent opportunity to provide its farmers with protection against uninsured seasonal risks to crop production. Key climate and farming systems risks were identified by interviewing a total of 55 farmers (23 cotton growers and 32 sugar cane growers) across Queensland. Key climate risks to the cotton industry include hail, drought/dry years (lack of rainfall during planting and season), quality downgrade (discolouration), excessive heat, floods and wet weather (during season and especially during harvest). Similarly, for the sugar industry, key climate risks include, drought, flood, excessive rainfall during harvest, cyclone, pests and disease. Key messages from farmer surveys are that current insurance products available to Queensland farmers (specifically, cotton and sugar cane farmers) may not address critical risks to the production and/or profitability of these systems and that farmers would prefer to have comprehensive insurance products available that cover them against profitability losses across multiple risk factors. A ‘climate and agricultural risk assessment and reporting tool’ (prototype) was developed as part of the project. This ‘tool’ allows quantification of key climate risks, initially for the sugar and cotton industry. The tool provides an option to generate a detail climate risk report based on historical data and a future seasonal climate forecast for an individual location. The tool data also serves as a dataset portal, allowing for the download of data in a required template. Cotton and sugarcane crop models APSIM and DSSAT were employed to simulate the growth and yield for 10 and 12 sites, respectively, across Queensland over the period 1940-2017 for various crop management factors. Comparing the simulated yields (from each model or the mean simulated value from ensemble models) to the observed yield (available at regional scale) the trend in year to year variability is satisfactorily captured for cotton on average, whereas for sugarcane there is a trend to overestimate or underestimate the yield depending on the site. Based on survey findings three prototype insurance products were developed for the cotton industry Insurance products developed were Drought Cover: insufficient rainfall during the planting season – August to November; Drought Cover: insufficient rainfall during growing season – November to February; and Wet Harvest Cover: excessive rainfall during harvest season – March to June. Two prototype insurance products were developed for sugar industry. They include; Cyclone Cover: crop damage during cyclone season – November to April; and Wet Harvest Cover: excessive rainfall during harvest season – June to December. Rainfall-indexed based worked examples were also developed for sugar and cotton industry growers to better appreciate the insurance mechanisms

Стохастическое дифференциальное уравнение нейтрального типа в гильбертовом пространстве

Стохастические дифференциальные уравнени

Tropical cyclone insurance for Queensland agriculture

This report is for Queensland agricultural producers and related industries as well as local and state governments interested in insurance options that mitigate the financial risks associated with cyclones. The report outlines the risks and impacts of cyclones on the Queensland agricultural sector and the availability of insurance solutions to mitigate the financial consequences of such events. The cyclone insurance solutions outlined in this report are preliminary and the parameters and pricing will vary according to the location covered and as more data become available

Overview of recent physics results from MAST

New results from MAST are presented that focus on validating models in order to extrapolate to future devices. Measurements during start-up experiments have shown how the bulk ion temperature rise scales with the square of the reconnecting field. During the current ramp-up, models are not able to correctly predict the current diffusion. Experiments have been performed looking at edge and core turbulence. At the edge, detailed studies have revealed how filament characteristics are responsible for determining the near and far scrape off layer density profiles. In the core the intrinsic rotation and electron scale turbulence have been measured. The role that the fast ion gradient has on redistributing fast ions through fishbone modes has led to a redesign of the neutral beam injector on MAST Upgrade. In H-mode the turbulence at the pedestal top has been shown to be consistent with being due to electron temperature gradient modes. A reconnection process appears to occur during edge localized modes (ELMs) and the number of filaments released determines the power profile at the divertor. Resonant magnetic perturbations can mitigate ELMs provided the edge peeling response is maximised and the core kink response minimised. The mitigation of intrinsic error fields with toroidal mode number n  >  1 has been shown to be important for plasma performance

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead