This paper studies the practice of semi-domestic reindeer (Rangifer t. tarandus) herding in Finnmark county in northern Norway. In this area, the Saami reindeer herders compete for space and grazing areas and keep large herds, while at the same time, the reindeer population is heavily exposed to carnivore predation by the lynx (Lynx lynx), the wolverine (Gulo gulo), and the golden eagle (Aquila chrysaetos). It is demonstrated that predation actually may improve the economic lot of livestock holders in this unmanaged local common setting. There are ecological as well as economic reasons as to why this happens. The ecological reason is that predation compensates for natural mortality; that is, increased predation reduces natural mortality, indicating that the net loss due to predation actually may be quite small. When predation reduces livestock density, the feeding conditions of the animals will improve, resulting in increased livestock weight and higher per animal slaughter value. At the same time, a smaller stock reduces the operating costs of the herders.
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http://dx.doi.org/10.1007/s13280-017-0910-1 | DOI Listing |
Am J Emerg Med
December 2024
Department of Health Policy & Organization, School of Public Health, The University of Alabama at Birmingham, Birmingham, AL, USA; Center for Outcomes and Effectiveness Research and Education, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, AL, USA.
Background: Leaving before medically advised (BMA) is a significant issue in the US healthcare system, leading to adverse health outcomes and increased costs. Despite previous research, multi-year studies using up-to-date nationwide emergency department (ED) data, are limited. This study examines factors associated with leaving BMA from EDs and trends over time, before and during the COVID-19 pandemic.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Leadership, Higher, and Adult Education, Ontario Institute for Studies in Education, University of Toronto, Toronto, Ontario, Canada.
In recent decades there has been significant interest among policy makers in supporting entrepreneurship among university students, with the goal to improve labor market outcomes and contribute to the economy through venture creation. Drawing from the 2018 National Graduate Survey in Canada, our study examines who engages in entrepreneurial activity after graduation, investigating differences among demographic groups and between those who participated in entrepreneurship education on campus and those who did not participate. We find that those graduates who participated in entrepreneurship education are more likely to be self-employed and own their own business three years after graduating than the general population of university graduates.
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January 2025
Centre for Agri-Environmental Research, School of Agriculture, Policy and Development, University of Reading, Reading, England, United Kingdom.
Pressures on honey bee health have substantially increased both colony mortality and beekeepers' costs for hive management across Europe. Although technological advances could offer cost-effective solutions to these challenges, there is little research into the incentives and barriers to technological adoption by beekeepers in Europe. Our study is the first to investigate beekeepers' willingness to adopt the Bee Health Card, a molecular diagnostic tool developed within the PoshBee EU project which can rapidly assess bee health by monitoring molecular changes in bees.
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January 2025
School of Economics and Trade, Guangzhou Xinhua University, Dongguan, China.
Stock price prediction is a challenging research domain. The long short-term memory neural network (LSTM) widely employed in stock price prediction due to its ability to address long-term dependence and transmission of historical time signals in time series data. However, manual tuning of LSTM parameters significantly impacts model performance.
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January 2025
School of Business Management, Zhejiang Financial College, Hangzhou, Zhejiang, China.
This paper investigates optimal ordering strategies in supply chains under two-level price fluctuations and initial profit allocation. By utilizing Copula functions to model the complex relationship between fluctuating prices and uncertain demand, the study develops both continuous and discrete decision models for practical applications. A discrete algorithm is proposed to approximate the optimal solution, with its convergence rigorously proven.
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