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Author(s): K. E. Westaway (corresponding author) [1]; J. Louys [2]; R. Due Awe [3]; M. J. Morwood [4]; G. J. Price [5]; J.-x. Zhao [5]; M. Aubert [6]; R. Joannes-Boyau [...]

The article focuses on the impact of the decision of the U.S. Supreme Court case Federal Trade Commission (FTC) v. Actavis Inc. on the patent holders. Topics discussed include exclusionary rights of patent holders, motivating the parties for reverse payment settlements and promoting pro-competitive from the court's decision. It also discusses the role of incentives in the settlement of the case.

ABSTRACT Natural river-floodplain systems are characterized by their dynamic hydrology and diverse geomorphology resulting in a wide range of habitats that support high fish diversity and production. Various factors (e.g. hydrological dynamics, water quality, and biotic processes) have been proposed to explain fish distribution in large river floodplains, but it is still widely acknowledged that the mechanisms involved may vary in diverse floodplain systems and that they are not fully understood. To determine how flooding dynamics and floodplain geomorphology influence fish species distributions across the Volga-Akhtuba floodplain, Russian Federation, we examined the distributions of eight species with respect to variables reflecting floodplain hydrology and geomorphology. On the basis of fish catches in 40 floodplain water bodies at the end of summer in 2006-2008, we found that frequency of occurrence of most fish species remained stable along the time. The distribution of fish species was strongly influenced by the size and shape of water bodies as well as flood extent. Therefore, the long-term flood variability that drives the geomorphic heterogeneity of the floodplain creates suitable habitats across ranges of fish flow guilds (rheophilic, eurytopic, and limnophilic), resulting in high diversity of the floodplain ichthyofauna. We conclude that this diverse habitat availability is a highly significant factor influencing fish distribution in the Volga-Akhtuba floodplain. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The contribution of forest degradation to changes in forest carbon stocks remains poorly quantified and constitutes a main source of uncertainty in the forest carbon budget. Charcoal production is a major source of forest degradation in sub-Saharan Africa. We used multitemporal Sentinel-2 imagery to monitor and quantify forest degradation extent in the main supplying area of a major urban center of southern Africa over a 4-year period. We implemented an indirect approach combining Sentinel-2 imagery to map kiln and field measurements to estimate AGB removals and carbon losses from charcoal production. This work generated 10 m resolution maps of forest degradation extent from charcoal production in the study area at quarterly intervals from 2016–2019. These maps reveal an intense and rapid forest degradation process and expose the spatial and temporal patterns of forest degradation from charcoal production with high detail. The total area under charcoal production over the study period reached 26,647 ha (SD = 320.8) and the forest degradation front advanced 10.5 km in a 4-year period, with an average of 19.4 ha of woodlands degraded daily. By the end of 2019, charcoal production disturbed most mopane stands in the study area and woodland fragmentation increased in 70.4 % of the mopane woodlands. We estimated that charcoal production was responsible for 2,568,761 Mg (SD = 42,130) of aboveground biomass extracted from the forest and 1,284,381 Mg (SD = 21,075) of carbon loss. The magnitude of these figures underlines the relevance of charcoal production as a main cause of forest cover change and remarks the existing uncertainties in the quantification of forest degradation processes. These results illustrate the potential of multitemporal medium resolution imagery to quantify forest degradation in sub-Saharan Africa and improve REDD + Monitoring, Reporting, and Verification systems in compliance with international reporting commitments.

Crop yield forecasting is performed monthly during the growing season by the United States Department of Agriculture’s National Agricultural Statistics Service. The underpinnings are long-established probability surveys reliant on farmers’ feedback in parallel with biophysical measurements. Over the last decade though, satellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) has been used to corroborate the survey information. This is facilitated through the Global Inventory Modeling and Mapping Studies/Global Agricultural Monitoring system, which provides open access to pertinent real-time normalized difference vegetation index (NDVI) data. Hence, two relatively straightforward MODIS-based modeling methods are employed operationally. The first model constitutes mid-season timing based on the maximum peak NDVI value, while the second is reflective of late-season timing by integrating accumulated NDVI over a threshold value. Corn model results nationally show the peak NDVI method provides a R2 of 0.88 and a coefficient of variation (CV) of 3.5%. The accumulated method, using an optimally derived 0.58 NDVI threshold, improves the performance to 0.93 and 2.7%, respectively. Both these models outperform simple trend analysis, which is 0.48 and 7.4%, correspondingly. For soybeans the R2 results of the peak NDVI model are 0.62, and 0.73 for the accumulated using a 0.56 threshold. CVs are 6.8% and 5.7%, respectively. Spring wheat’s R2 performance with the accumulated NDVI model is 0.60 but just 0.40 with peak NDVI. The soybean and spring wheat models perform similarly to trend analysis. Winter wheat and upland cotton show poor model performance, regardless of method. Ultimately, corn yield forecasting derived from MODIS imagery is robust, and there are circumstances when forecasts for soybeans and spring wheat have merit too.

Purpose: The purpose of this study is to describe current diabetes education practice and specific interventions and responsibilities of diabetes educators in the United States.Methods: The 2008 National Practice Survey (NPS) instrument consisted of 53 items addressing diabetes education program structure, processes and interventions, outcomes and quality improvement activities, and the chronic care model. The survey was hosted online for American Association of Diabetes Educators (AADE) members. Participants totaled 2447 members, constituting a 25% return rate. Data from the 2008 NPS were analyzed and compared with results from previous surveys.Results: Nearly two-thirds of respondents in 2008 provided diabetes education in a single location, most commonly in a clinical outpatient/managed care setting (39%). Most programs provided comprehensive services. Managers noted that 42% of their programs were either cost/revenue neutral or profitable. Programs varied in types of services, number of patient visits, team member functions, time spent on services, and instructional methods used. At least 50% of managers said their programs report outcome data, and 88% participate in quality/performance improvement activities. Nearly two-thirds of respondents were unfamiliar with the AADE-adopted chronic care model.Conclusions: Many 2008 NPS results concur with those obtained in 2005 through 2007. Areas of variability among programs suggest a need for standardized interventions and practice guidelines. Educators are encouraged to report outcomes to elucidate the contributions of their programs to patient care. AADE can use the results and comparative data obtained from the 2008 survey when developing practice, research, and advocacy activities. [ABSTRACT FROM AUTHOR]