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Moral conflicts occur when faced with making decisions about how to best deal with a child's situation. Thoughts about the child's best interest and relationship with his/her parents as well as the informants´ own safety, were central. The comparative meta- analysis of both data sets revealed these conflicts commence with a moral sensitivity of possible negative consequences for the child. Moral sensitivity can be viewed as a "good" personal attribute, it paradoxically might lead to moral stress despite an open ethical climate. Based on the results of this study, further research on the interpersonal aspects of dealing with moral conflicts involved in reporting suspected child abuse is indicated.After the Green Building Regulations in the Zhejiang Province was put into effect in May 2016, cities and prefectures in the province were given directives to set their own individual targets for the provision of green buildings. The city of Ningbo decided to use this opportunity to develop a systematic procedure, using Fuzzy Analytical Hierarchy Process (FAHP), to identify which allotments within the municipal area have the greatest potential of delivering green buildings, ensuring the set targets are fair and deliverable. This paper explains in detail the use of FAHP in the production of the Specific Plans for Green Buildings for the city of Ningbo in the Zhejiang Province of China. This innovative multi-faceted method incorporates the level of development in each of the 3213 land allotments in the municipal area, assessing each one for critical aspects such as environmental potential, local economic development land-use and land prices in order to determine an individual roadmap for the ratio of green buil (this is not currently the case in most residential buildings in China). These aspects are also discussed in this paper.Originating in China, the Coronavirus has reached the world at different speeds and levels of strength. #link# This paper provides an initial understanding of some driving factors and their consequences. Since transmission requires people, the human factor behind globalization is essential. Globalization, a major force behind global wellbeing and equality, is highly associated with this factor. The analysis investigates the impact globalization has on the speed of initial transmission to a country and on the scale of initial infections in the context of other driving factors. Our cross-country analysis finds that measures of globalization are positively related to the spread of the virus, both in speed and scale. However, the study also finds that globalized countries are better equipped to keep fatality rates low. link2 The conclusion is not to reduce globalization to avoid pandemics, but to better monitor the human factor at the outbreak and mobilize collaboration forces to curtail diseases.Quantiles are available in various problems for developing probability distributions. In some problems quantiles are elicited from experts and used for fitting parametric models, which induce non-elicited information. In some other problems comparisons are made with a quantile of an assumed model which is noncommittal to the quantile information. The maximum entropy (ME) principle provides models that avoid these issues. However, the information theory literature has been mainly concerned about models based on moment information. This paper explores the ME models that are the minimum elaborations of the uniform and moment-based ME models by quantiles. This property provides diagnostics for the utility of elaboration in terms of the information value of each type of information over the other. The ME model with quantiles and moments is represented as the mixture of truncated distributions on consecutive intervals whose shapes and existence are determined by the moments. Elaborations of several ME distributions by quantiles are presented. The ME model based only on quantiles elicited by the fixed interval method possesses a useful property for pooling information elicited from multiple experts. The elaboration of Laplace distribution is an extension of the information theory connection with minimum risk under symmetric loss functions to the asymmetric linear loss. This extension produces a new Asymmetric Laplace distribution. link3 Application examples compare ME priors with a parametric model fitted to elicited quantiles, illustrate measuring uncertainty and disagreement of economic forecasters based on elicited probabilities, and adjust ME models for a fundamental quantile in an inventory management problem.Policymakers during COVID-19 operate in uncharted territory and must make tough decisions. Operational Research - the ubiquitous 'science of better' - plays a vital role in supporting this decision-making process. To that end, using data from the USA, India, UK, Germany, and Singapore up to mid-April 2020, we provide predictive analytics tools for forecasting and planning during a pandemic. We forecast COVID-19 growth rates with statistical, epidemiological, machine- and deep-learning models, and a new hybrid forecasting method based on nearest neighbors and clustering. selleck and forecast the excess demand for products and services during the pandemic using auxiliary data (google trends) and simulating governmental decisions (lockdown). Our empirical results can immediately help policymakers and planners make better decisions during the ongoing and future pandemics.Infectious diseases, both established and emerging, impose a significant burden globally. Successful management of infectious diseases requires considerable effort and a multidisciplinary approach to tackle the complex web of interconnected biological, public health and economic systems. Through a wide range of problem-solving techniques and computational methods, operational research can strengthen health systems and support decision-making at all levels of disease control. From improved understanding of disease biology, intervention planning and implementation, assessing economic feasibility of new strategies, identifying opportunities for cost reductions in routine processes, and informing health policy, this paper highlights areas of opportunity for operational research to contribute to effective and efficient infectious disease management and improved health outcomes.Superforecasting has drawn the attention of academics - despite earlier contradictory findings in the literature, arguing that humans can consistently and successfully forecast over long periods. It has also enthused practitioners, due to the major implications for improving forecast-driven decision-making. The evidence in support of the superforecasting hypothesis was provided via a 4-year project led by Tetlock and Mellers, which was based on an exhaustive experiment with more than 5000 experts across the globe, resulting in identifying 260 superforecasters. The result, however, jeopardizes the applicability of the proposition, as exciting as it may be for the academic world; if every company in the world needs to rely on the aforementioned 260 experts, then this will end up an impractical and expensive endeavor. Thus, it would make sense to test the superforecasting hypothesis in real-life conditions when only a small pool of experts is available, and there is limited time to identify the superforecasters. If under these constrained conditions the hypothesis still holds, then many small and medium-sized organizations could identify fast and consequently utilize their own superforecasters. In this study, we provide supportive empirical evidence from an experiment with an initial (small) pool of 314 experts and an identification phase of (just) 9 months. Furthermore - and corroborating to the superforecasting literature, we also find preliminary evidence that even an additional training of just 20 min, can influence positively the number of superforecasters identified.The current intense food production-consumption is one of the main sources of environmental pollution and contributes to anthropogenic greenhouse gas emissions. Organic farming is a potential way to reduce environmental impacts by excluding synthetic pesticides and fertilizers from the process. Despite ecological benefits, it is unlikely that conversion to organic can be financially viable for farmers, without additional support and incentives from consumers. This study models the interplay between consumer preferences and socio-environmental issues related to agriculture and food production. We operationalize the novel concept of extended agro-food supply chain and simulate adaptive behavior of farmers, food processors, retailers, and customers. Not only the operational factors (e.g., price, quantity, and lead time), but also the behavioral factors (e.g., attitude, perceived control, social norms, habits, and personal goals) of the food suppliers and consumers are considered in order to foster organic farming. We propose an integrated approach combining agent-based, discrete-event, and system dynamics modeling for a case of wine supply chain. Findings demonstrate the feasibility and superiority of the proposed model over the traditional sustainable supply chain models in incorporating the feedback between consumers and producers and analyzing management scenarios that can urge farmers to expand organic agriculture. Results further indicate that demand-side participation in transition pathways towards sustainable agriculture can become a time-consuming effort if not accompanied by the middle actors between consumers and farmers. In practice, our proposed model may serve as a decision-support tool to guide evidence-based policymaking in the food and agriculture sector.

In late 2019, the world saw a viral outbreak of unprecedented scale that sent a significant fraction of humankind into either quarantine or lockdown. Coronavirus disease 2019 (COVID-19) is a respiratory tract infection caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which was first recognized in Wuhan, China, in December 2019.

We created and administered a 17-item questionnaire for health care professionals (HCPs) to assess their level of knowledge towards this ongoing and evolving pandemic. It was disseminated through Web- and mobile-based social networks. The questions were sourced and created from various standard national and international guidelines available at the time of writing.

A total of 827 medical personnel participated in the study. Among them, 65.5%scored between 60% and 79%, indicating a moderate level of knowledge. There was no statistically significant difference in the scores of doctors, nursing officers and dental surgeons (

=0.200). Participants had good knowledge regarding clinical symptoms, mode of transmission and preventive measures. But the study identified some gaps in knowledge in the implementation of management protocols, handling of dead bodies and biomedical waste management of COVID-19 cases.

With this understanding, regular training, drills and knowledge dissemination along with skill development through learning correct practices focusing on HCP at all levels are the current needs.

With this understanding, regular training, drills and knowledge dissemination along with skill development through learning correct practices focusing on HCP at all levels are the current needs.