Barbeekrebs9664
Similar cold extremes were found for the winter months, with PET values reaching - 30 °C, and average PS levels varying lower in the case of the peri-urban station. Graphical abstract.Trust-ability, reputation, security and quality are the main concerns for public and private financial institutions. To detect fraudulent behaviour, several techniques are applied pursuing different goals. For well-defined problems, analytical methods are applicable to examine the history of customer transactions. However, fraudulent behaviour is constantly changing, which results in ill-defined problems. Furthermore, analysing the behaviour of individual customers is not sufficient to detect more complex structures such as networks of fraudulent actors. We propose NEVA (Network dEtection with Visual Analytics), a Visual Analytics exploration environment to support the analysis of customer networks in order to reduce false-negative and false-positive alarms of frauds. Multiple coordinated views allow for exploring complex relations and dependencies of the data. A guidance-enriched component for network pattern generation, detection and filtering support exploring and analysing the relationships of nodes on different levels of complexity. In six expert interviews, we illustrate the applicability and usability of NEVA.Over the last decade, scholars across the wide spectrum of the discipline of sociology have started to reengage with questions on morality and moral phenomena. The continued wave of research in this field, which has come to be known as the new sociology of morality, is a lively research program that has several common grounds with scholarship in the field of business ethics. The aim of this thematic symposium is to open constructive dialogues between these two areas of study. In this introductory essay, we briefly present the project of the new sociology of morality and discuss its relevance for business ethics. We also review the contributions to this thematic symposium and identify four specific domains where future research can contribute to fruitful dialogues between the two fields.'Cultured' meat has attracted a considerable amount of investor and media interest as an early-stage technology. Despite uncertainties about its future impact, news media may be contributing to promissory discourses, by stressing the potential benefits from cultured meat to the environment, health, animal welfare, and feeding a growing population. The results from a content analysis of 255 articles from 12 US and UK traditional media from 2013 to 2019 show that much of the coverage is prompted by the industry sector, whose representatives are also the most quoted. Positive narratives about cultured meat are much more prominent than cautionary ones. Our findings support previous scholarship on other emerging technologies which concluded that with important variations, media treatments are largely positive.The rising number of COVID-19 cases and economic implications of lockdown measures indicate the tricky balancing act policy makers face as they implement the subsequent phases of 'unlock'. We develop a model to examine how lockdown and social distancing measures have influenced the behavioral conduct of people. The current situation highlights that policy makers need to focus on bringing awareness and social restraint among people rather than going for stringent lockdown measures. We believe this work will help the policy makers gain insights into the troubled COVID-19 times ahead, and based on the estimates, they can frame policies to navigate these wild waves in the best possible way.Coronavirus (COVID-19) has rapidly spread across many countries in pandemic proportions since the first case was reported in Hubei, China in December 2019. Understanding transmission, susceptibility and exposure risks is crucial for surveillance, control and response to the disease. Knowing the geographic distribution of health resource scarcity areas is necessary if a country is to adequately anticipate and prepare for the full impact of infections. We explored the potential to undertake a spatial risk assessment of an emerging pandemic under data scarcity in Eswatini. We used a set of socio-economic and demographic variables to identify epidemic risk prone areas in the country. Three risk zone levels for COVID-19 were identified in the country. The analysis showed that about 29% (320 818) of the population were located in the high risk zone and these were people who could potentially be infected with COVID-19 in the absence of mitigation measures. A majority of cases and deaths attributed to COVID-19 would likely remain unknown but our estimate could be used to gauge the full burden of the disease. Approximating and quantifying the number of people who may be potentially infected with COVID-19 remains impossible under data scarcity and limited healthcare capacity especially in sub-Saharan Africa. We provided an estimation method that could support the pandemic risk forecasting, preparedness and response measures in the midst of data scarcity. The resultant map products could be used to guide on-the-ground surveillance and response efforts.Objective This study aims to compare the in vitro wear rate of crosslinked, high molecular weight polyethylene coupled to 36-mm diameter ceramic heads and 32-mm diameter metal heads. Methods Ceramic-on-polyethylene (36 mm) and metal-on-polyethylene (32 mm) tribological pairs were submitted to biomechanical tests in a simulator to determine the wear rate after 15 × 10 6 cycles. Results A statistically significant difference ( p = 0.0005) was detected when comparing the wear rate of assemblies with metallic heads (average wear 14.12 mg/MC) and ceramic heads (average wear 7.46 mg/MC). Conclusion The present study demonstrated the lower wear rate in prosthetic assemblies using 36-mm crosslinked ceramic-on-polyethylene tribological pairs compared to 32-mm crosslinked metal-on-polyethylene assemblies. IC-87114 This finding demonstrates the effectiveness of ceramic-on-polyethylene tribological pairs, even with large diameter heads.