Comparison of Conjunctive Probiotic Use Versus No Probiotic Use in Outcomes of Antibiotic-Associated Diarrhea

Antibiotics are utilized in the medical community for the treatment of bacterial infections. Consequently, the use of antibiotics may result in certain gastrointestinal side effects. Antibiotic-associated diarrhea is one side effect that can be seen in patient populations that are on an antibiotic regimen. Due to this side effect profile, patient compliance on an antibiotic regimen may be compromised. This lack in patient compliance led to increased interest to determine if there are treatment options available to prevent or reduce instances of antibiotic-associated diarrhea. One treatment option of interest includes the use of probiotics. The purpose of this literature review is to determine if conjunctive use of probiotic supplementation during an antibiotic regimen demonstrates protective effects in preventing or reducing the incidence of antibiotic-associated diarrhea. Studies that were included analyzed probiotic use versus a placebo in treatment of antibiotic-associated diarrhea in pediatric, adult, and elderly populations in an outpatient or inpatient clinical setting. The data available at this time suggests that supplementing with probiotics during an antibiotic regimen may be effective in prevention and reduction of antibiotic-associated diarrhea in pediatric and adult populations

IEA Wind Task 32: Wind lidar identifying and mitigating barriers to the adoption of wind lidar

IEA Wind Task 32 exists to identify and mitigate barriers to the adoption of lidar for wind energy applications. It leverages ongoing international research and development activities in academia and industry to investigate site assessment, power performance testing, controls and loads, and complex flows. Since its initiation in 2011, Task 32 has been responsible for several recommended practices and expert reports that have contributed to the adoption of ground-based, nacelle-based, and floating lidar by the wind industry. Future challenges include the development of lidar uncertainty models, best practices for data management, and developing community-based tools for data analysis, planning of lidar measurements and lidar configuration. This paper describes the barriers that Task 32 identified to the deployment of wind lidar in each of these application areas, and the steps that have been taken to confirm or mitigate the barriers. Task 32 will continue to be a meeting point for the international wind lidar community until at least 2020 and welcomes old and new participants

Increased power gains from wake steering control using preview wind direction information

Yaw controllers typically rely on measurements taken at the wind turbine, resulting in a slow reaction to wind direction changes and subsequent power losses due to misalignments. Delayed yaw action is especially problematic in wake steering operation because it can result in power losses when the yaw misalignment angle deviates from the intended one due to a changing wind direction. This study explores the use of preview wind direction information for wake steering control in a two-turbine setup with a wind speed in the partial load range. For these conditions and a simple yaw controller, results from an engineering model identify an optimum preview time of 90 s. These results are validated by forcing wind direction changes in a large-eddy simulation model. For a set of six simulations with large wind direction changes, the average power gain from wake steering increases from only 0.44 % to 1.32 %. For a second set of six simulations with smaller wind direction changes, the average power gain from wake steering increases from 1.24 % to 1.85 %. Low-frequency fluctuations are shown to have a larger impact on the performance of wake steering and the effectiveness of preview control, in particular, than high-frequency fluctuations. From these results, it is concluded that the benefit of preview wind direction control for wake steering is substantial, making it a topic worth pursuing in future work.</p

Analyzing high resolution topography for advancing the understanding of mass and energy transfer through landscapes: A review

International audienceThe study of mass and energy transfer across landscapes has recently evolved to comprehensive considerations acknowledging the role of biota and humans as geomorphic agents, as well as the importance of small-scale landscape features. A contributing and supporting factor to this evolution is the emergence over the last two decades of technologies able to acquire high resolution topography (HRT) (meter and sub-meter resolution) data. Landscape features can now be captured at an appropriately fine spatial resolution at which surface processes operate; this has revolutionized the way we study Earth-surface processes. The wealth of information contained in HRT also presents considerable challenges. For example, selection of the most appropriate type of HRT data for a given application is not trivial. No definitive approach exists for identifying and filtering erroneous or unwanted data, yet inappropriate filtering can create artifacts or eliminate/distort critical features. Estimates of errors and uncertainty are often poorly defined and typically fail to represent the spatial heterogeneity of the dataset, which may introduce bias or error for many analyses. For ease of use, gridded products are typically preferred rather than the more information-rich point cloud representations. Thus many users take advantage of only a fraction of the available data, which has furthermore been subjected to a series of operations often not known or investigated by the user. Lastly, standard HRT analysis work-flows are yet to be established for many popular HRT operations, which has contributed to the limited use of point cloud data.In this review, we identify key research questions relevant to the Earth-surface processes community within the theme of mass and energy transfer across landscapes and offer guidance on how to identify the most appropriate topographic data type for the analysis of interest. We describe the operations commonly performed from raw data to raster products and we identify key considerations and suggest appropriate work-flows for each, pointing to useful resources and available tools. Future research directions should stimulate further development of tools that take advantage of the wealth of information contained in the HRT data and address the present and upcoming research needs such as the ability to filter out unwanted data, compute spatially variable estimates of uncertainty and perform multi-scale analyses. While we focus primarily on HRT applications for mass and energy transfer, we envision this review to be relevant beyond the Earth-surface processes community for a much broader range of applications involving the analysis of HRT

Expert Elicitation on Wind Farm Control

Wind farm control is an active and growing field of research in which the control actions of individual turbines in a farm are coordinated, accounting for inter-turbine aerodynamic interaction, to improve the overall performance of the wind farm and to reduce costs. The primary objectives of wind farm control include increasing power production, reducing turbine loads, and providing electricity grid support services. Additional objectives include improving reliability or reducing external impacts to the environment and communities. In 2019, a European research project (FarmConners) was started with the main goal of providing an overview of the state-of-the-art in wind farm control, identifying consensus of research findings, data sets, and best practices, providing a summary of the main research challenges, and establishing a roadmap on how to address these challenges. Complementary to the FarmConners project, an IEA Wind Topical Expert Meeting (TEM) and two rounds of surveys among experts were performed. From these events we can clearly identify an interest in more public validation campaigns. Additionally, a deeper understanding of the mechanical loads and the uncertainties concerning the effectiveness of wind farm control are considered two major research gaps

Development of a global ~90m water body map using multi-temporal Landsat images

This paper describes the development of a Global 3 arc-second Water Body Map (G3WBM), using an automated algorithm to process multi-temporal Landsat images from the Global Land Survey (GLS) database. We used 33,890 scenes from 4 GLS epochs in order to delineate a seamless water body map, without cloud and ice/snow gaps. Permanent water bodies were distinguished from temporal water-covered areas by calculating the frequency of water body existence from overlapping, multi-temporal, Landsat scenes. By analyzing the frequency of water body existence at 3 arc-second resolution, the G3WBM separates river channels and floodplains more clearly than previous studies. This suggests that the use of multi-temporal images is as important as analysis at a higher resolution for global water body mapping. The global totals of delineated permanent water body area and temporal water-covered area are 3.25 and 0.49 million km2 respectively, which highlights the importance of river-floodplain separation using multi-temporal images. The accuracy of the water body classification was validated in Hokkaido (Japan) and in the contiguous United States using an existing water body databases. There was almost no commission error, and about 70% of lakes > 1 km2 shows relative water area error < 25%. Though smaller water bodies (< 1 km2) were underestimated mainly due to omission of shoreline pixels, the overall accuracy of the G3WBM should be adequate for larger scale research in hydrology, biogeochemistry, and climate systems and importantly includes a quantification of the temporal nature of global water bodies