7 research outputs found

    A global experience‐sampling method study of well‐being during times of crisis: The CoCo project

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    We present a global experience-sampling method (ESM) study aimed at describing, predicting, and understanding individual differences in well-being during times of crisis such as the COVID-19 pandemic. This international ESM study is a collaborative effort of over 60 interdisciplinary researchers from around the world in the “Coping with Corona” (CoCo) project. The study comprises trait-, state-, and daily-level data of 7490 participants from over 20 countries (total ESM measurements = 207,263; total daily measurements = 73,295) collected between October 2021 and August 2022. We provide a brief overview of the theoretical background and aims of the study, present the applied methods (including a description of the study design, data collection procedures, data cleaning, and final sample), and discuss exemplary research questions to which these data can be applied. We end by inviting collaborations on the CoCo dataset

    Epigenetic Features of Animal Biotechnologies

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    International audienceEpigenetic mechanisms play a crucial role in many biological processes, such as regulation of gene expression especially after fertilization and during early embryonic development. Indeed, the parental genomes that carry special epigenetic signatures, undergo important chromatin remodelling through epigenetic modifications during the first embryonic cleavages, some of which are crucial for the production of healthy embryos. It is therefore very important for breeders and embryologists to understand how parentally inherited genomes may be epigenetically altered by animal biotechnologies as it could affect embryo quality and further development. This chapter introduces some of the basic epigenetic parameters underpinning early embryonic development and how they could be affected during the processes of embryo in vitro production, somatic cell nuclear transfer or stem cells derivatio

    Memetic Algorithms for Business Analytics and Data Science: A Brief Survey

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    This chapter reviews applications of Memetic Algorithms in the areas of business analytics and data science. This approach originates from the need to address optimization problems that involve combinatorial search processes. Some of these problems were from the area of operations research, management science, artificial intelligence and machine learning. The methodology has developed considerably since its beginnings and now is being applied to a large number of problem domains. This work gives a historical timeline of events to explain the current developments and, as a survey, gives emphasis to the large number of applications in business and consumer analytics that were published between January 2014 and May 2018

    Rheumatic manifestations of chikungunya: emerging concepts and interventions

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