Two contrasting types of individuals were each predicted to agree, for different reasons, that conventional ethical standards of society need not be upheld if organizational interests appear to demand otherwise. The hypotheses were investigated using questionnaire responses from two samples (employed and student, total N=308). Clear support was obtained for the prediction that individuals inclined toward self-interest and behavior counter to conventional standards would agree with the preceding position. Partial support was obtained for the hypothesis that individuals who simply feel (...) obligated to support an employing organization would also agree. While the latter's perspective may be somewhat narrow or perhaps even cynical, they do not seem to reflect the self-interest profile of the first group. This study also extends the groundbreaking work of Froelich and Kottke by exploring individual difference correlates of their promising ethics scale assessing the extent of agreement that organizational interests legitimately supersede more conventional ethical standards. (shrink)

This collection reconsiders the notion of life and conceptualizes those forms of life which have been excluded from modern philosophy, such as post-Anthropocene life, the life of non-human animals and the life of inorganic objects"-- Provided by publisher.

The sudden emergence of the COVID-19 pandemic brought global disruption to every aspect of society including healthcare, supply chain, the economy, and social interaction. Among the many emergent considerations were the safety and public health of the public, patients, essential workers, and healthcare professionals. In certain locations, clinical research was halted—or terminated—in deference to the immediate needs of patient care, and clinical trials focusing on the treatment and prevention of coronavirus infection were prioritized over studies focusing on other diseases. Difficult (...) decisions were made rapidly; flexibility and reconsideration were necessary not only because the intensity and severity of infection varied over time and by locale but also because knowledge of the disease and understanding of its treatment grew. Here we discuss the ethical challenges in decision-making and competing ethical tensions during the pandemic in an effort to advance future preparedness. (shrink)

This chapter contains sections titled: How Common Are Serial Killings? What is a Serial Killer? I Think Therefore I Kill: The Philosophical Musings of Serial Killers Can You Blame Them? Ethics, Evil, and Serial Killing Dangerous Infatuations: The Public Fascination with Serial Killers A Eulogy for Emotion: The Lack of Empathy and the Urge to Kill Creepy Cognition: Talking and Thinking about Serial Killers Psycho‐ology: Killer Mindsets and Meditations on Murder A Solemn Afterword: A Message from the Victim's Network A (...) Timeline of Serial Killers Notes. (shrink)

Air transport is playing an increasing role in the world economy every year. This is facilitated by technological development and the latest developments in the aviation industry, globalization. This paper provides an overview of artificial neural network training methods for airfare predicting. The articles for 2017-2019 were analyzed in order to determine the model with the most accurate prediction. The researchers conducted research on open data collected by themselves and set themselves the goal of creating a model that would advise (...) a user the best time to buy a ticket when the price would be the lowest. The review of the papers by similar themes revealed that the Bagging Regression Tree model has the highest results with an accuracy of 88% and the random forest method has an accuracy of 87%. Civil aviation plays an important role in the economy of each country. Aviation is the best way to cover long distances in comfort in the shortest time. Airlines offer customers a variety of opportunities to travel both within the country and abroad. The main problem of interaction between airlines and customers is the airfare: the former want to sell more at the higher price, and the latter want to buy cheaper. Therefore, companies use their own private algorithms for dynamic pricing and constantly monitor the market situation, responsive to changes in demand and the actions of competitors. This behavior allows them to achieve a balance between the desires of airlines and customers. Scientists are trying to invent a way to predict airfare so that air travelers can buy them at the lowest price. The results of the work in this area provide general rules for the best purchase. For example, according to the article thebest day to buy a ticket by expedia.com for a domestic flight on the United States is Sunday, and the best period is 57 days before departure. This article provides an overview of the works, the authors of which compared the models of machine learning. Achievements in this area are limited to direct flights of a certain domestic market and 88% accuracy of the forecast. The Bagging Regression Tree model described in the article can be considered the best result. This trained model can make predictions based only on two parameters: the number of free cargo and the number of days left before departure and has an accuracy of 88%. (shrink)

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