Portraying the nature of corruption: Using an explorative case-study design

What is the nature of corruption in Western democracies? To answer this research question, the authors study 10 Dutch corruption cases in depth, looking at confidential criminal files. The cases allow them to sketch a general profile of a corruption case. The authors offer nine propositions to portray the nature of corruption. They conclude that corruption usually takes place within enduring relationships, that the process of becoming corrupt can be characterized as a slippery slope, and that important motives for corruption, aside from material gain, include friendship or love, status, and the desire to impress others. The explorative multiple case study methodology helps to expand our understanding of the way in which officials become corrupt. © 2008 The American Society for Public Administration

Learning about Organizational Management through “Organizational Management”: Closing the Gap

Using the whale course situation as a work organization the author was able to teach an introductory management course in which the students experienced key organizational processes: leadership, decision making, problem solving, communication, conflict, cooperation and competition. This experience approximates the organizational reality better than a conventional course. Two classes (110, 40) of business seniors in a midwestern university participated in the experiment. This paper reports the rationale, methodology and caveats of this experiment

Dispersion/dilution enhances phytoplankton blooms in low-nutrient waters

International audienceSpatial characteristics of phytoplankton blooms often reflect the horizontal transport properties of the oceanic turbulent flow in which they are embedded. Classically, bloom response to horizontal stirring is regarded in terms of generation of patchiness following large-scale bloom initiation. Here, using satellite observations from the North Pacific Subtropical Gyre and a simple ecosystem model, we show that the opposite scenario of turbulence dispersing and diluting fine-scale (∼1–100 km) nutrient-enriched water patches has the critical effect of regulating the dynamics of nutrients–phytoplankton–zooplankton ecosystems and enhancing accumulation of photosynthetic biomass in low-nutrient oceanic environments. A key factor in determining ecological and biogeochemical consequences of turbulent stirring is the horizontal dilution rate, which depends on the effective eddy diffusivity and surface area of the enriched patches. Implementation of the notion of horizontal dilution rate explains quantitatively plankton response to turbulence and improves our ability to represent ecological and biogeochemical processes in oligotrophic oceans

Automated Evaluation of Human Embryo Blastulation and Implantation Potential using Deep‐Learning

In in vitro fertilization (IVF) treatments, early identification of embryos with high implantation potential is required for shortening time to pregnancy while avoiding clinical complications to the newborn and the mother caused by multiple pregnancies. Current classification tools are based on morphological and morphokinetic parameters that are manually annotated using time‐lapse video files. However, manual annotation introduces interobserver and intraobserver variability and provides a discrete representation of preimplantation development while ignoring dynamic features that are associated with embryo quality. A fully automated and standardized classifiers are developed by training deep neural networks directly on the raw video files of >6200 blastulation‐labeled and >5500 implantation‐labeled embryos. Prediction of embryo implantation is more accurate than the current state‐of‐the‐art morphokientic classifier. Embryo classification improves with video length where the most predictive images show only partial association with morphological features. Deep learning substitute to human evaluation of embryo developmental competence thus contributes to implementing single embryo transfer methodology

Decoupling Physical from Biological Processes to Assess the Impact of Viruses on a Mesoscale Algal Bloom

Phytoplankton blooms are ephemeral events of exceptionally high primary productivity that regulate the flux of carbon across marine food webs [1–3]. Quantification of bloom turnover [4] is limited by a fundamental difficulty to decouple between physical and biological processes as observed by ocean color satellite data. This limitation hinders the quantification of bloom demise and its regulation by biological processes [5, 6], which has important consequences on the efficiency of the biological pump of carbon to the deep ocean [7–9]. Here, we address this challenge and quantify algal blooms’ turnover using a combination of satellite and in situ data, which allows identification of a relatively stable oceanic patch that is subject to little mixing with its surroundings. Using a newly developed multisatellite Lagrangian diagnostic, we decouple the contributions of physical and biological processes, allowing quantification of a complete life cycle of a mesoscale (∼10–100 km) bloom of coccolithophores in the North Atlantic, from exponential growth to its rapid demise. We estimate the amount of organic carbon produced during the bloom to be in the order of 24,000 tons, of which two-thirds were turned over within 1 week. Complimentary in situ measurements of the same patch area revealed high levels of specific viruses infecting coccolithophore cells, therefore pointing at the importance of viral infection as a possible mortality agent. Application of the newly developed satellite-based approaches opens the way for large-scale quantification of the impact of diverse environmental stresses on the fate of phytoplankton blooms and derived carbon in the ocean