Project description:In deceased donor kidney transplantation, acute kidney injury (AKI) prioir to surgery is a major determinant of delayed graft function (DGF), but AKI is histologically silent and difficult to assess. We hypothesized that a molecular measurement of AKI would add power to conventional risk assessments to predict the early poor allograft function at first week post transplantation.
Project description:Mangrove forest plays a very important role for both ecosystem services and biodiversity conservation. In Vietnam, mangrove is mainly distributed in the Mekong delta. Recently, mangrove areas in this region decreased rapidly in both quality and quantity. The forest became bare, divided and scattered into many small patches, which was a major driver of ecosystem degradation. Without a quantitative method for effectively assessing mangrove health in the regional scale, the sustainably conserving mangrove is the challenge for the local governments. Remote sensing data has been widely used for monitoring mangrove distributions, while the characterization of spatial metrics is important to understand the underlying processes of mangrove change. The objectives of this study were to develop an approach to monitor mangrove health in Mui Ca Mau, Ca Mau province of Vietnam by utilizing satellite image textures to assess the mangrove patterns. The research result showed that mangrove areas increased double by 2015, but the forest had become more fragmented. We can be seen those changes in land use mainly come from land conversion from forest to shrimp farms, settlements areas and public constructions. The conserving existing mangrove forest in Mui Ca Mau should consider the relations between mangrove health and influencing factors indicated in the manuscript.
Project description:Research productivity and impact are often considered in professional evaluations of academics, and performance metrics based on publications and citations increasingly are used in such evaluations. To promote evidence-based and informed use of these metrics, we collected publication and citation data for 437 tenure-track faculty members at 33 research-extensive universities in the United States belonging to the National Association of University Fisheries and Wildlife Programs. For each faculty member, we computed 8 commonly used performance metrics based on numbers of publications and citations, and recorded covariates including academic age (time since Ph.D.), sex, percentage of appointment devoted to research, and the sub-disciplinary research focus. Standardized deviance residuals from regression models were used to compare faculty after accounting for variation in performance due to these covariates. We also aggregated residuals to enable comparison across universities. Finally, we tested for temporal trends in citation practices to assess whether the "law of constant ratios", used to enable comparison of performance metrics between disciplines that differ in citation and publication practices, applied to fisheries and wildlife sub-disciplines when mapped to Web of Science Journal Citation Report categories. Our regression models reduced deviance by ¼ to ½. Standardized residuals for each faculty member, when combined across metrics as a simple average or weighted via factor analysis, produced similar results in terms of performance based on percentile rankings. Significant variation was observed in scholarly performance across universities, after accounting for the influence of covariates. In contrast to findings for other disciplines, normalized citation ratios for fisheries and wildlife sub-disciplines increased across years. Increases were comparable for all sub-disciplines except ecology. We discuss the advantages and limitations of our methods, illustrate their use when applied to new data, and suggest future improvements. Our benchmarking approach may provide a useful tool to augment detailed, qualitative assessment of performance.
Project description:With the majority of the global human population living in coastal regions, correctly characterizing the climate risk that ocean-dependent communities and businesses are exposed to is key to prioritizing the finite resources available to support adaptation. We apply a climate risk analysis across the European fisheries sector to identify the most at-risk fishing fleets and coastal regions and then link the two analyses together. We employ an approach combining biological traits with physiological metrics to differentiate climate hazards between 556 populations of fish and use these to assess the relative climate risk for 380 fishing fleets and 105 coastal regions in Europe. Countries in southeast Europe as well as the United Kingdom have the highest risks to both fishing fleets and coastal regions overall, while in other countries, the risk-profile is greater at either the fleet level or at the regional level. European fisheries face a diversity of challenges posed by climate change; climate adaptation, therefore, needs to be tailored to each country, region, and fleet's specific situation. Our analysis supports this process by highlighting where and what adaptation measures might be needed and informing where policy and business responses could have the greatest impact.