Multiaspect data are ubiquitous in modern Big Data applications. For instance, different aspects of a social network are the different types of communication between people, the time stamp of each interaction, and the location associated to each individual. How can we jointly model all those aspects and leverage the additional information that they introduce to our analysis? Tensors, which are multidimensional extensions of matrices, are a principled and mathematically sound way of modeling such multiaspect data. In this article, our goal is to popularize tensors and tensor decompositions to Big Data practitioners by demonstrating their effectiveness, outlining challenges that pertain to their application in Big Data scenarios, and presenting our recent work that tackles those challenges. We view this work as a step toward a fully automated, unsupervised tensor mining tool that can be easily and broadly adopted by practitioners in academia and industry.
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http://dx.doi.org/10.1089/big.2016.0026 | DOI Listing |
Soc Stud Sci
January 2025
Science, Technology and Innovation Studies, The University of Edinburgh, Edinburgh, Scotland, UK.
Accounts of the origins of the genomic commons typically focus on the development of public repositories and data-sharing agreements. This article tells a different story. During the 1990s in the United States, efforts of private companies to prevent the patenting of certain kinds of DNA sequences were essentially a conservative response to shifts in the sociotechnical constitution of the pharmaceutical innovation system, and to the operation of intellectual property as one of the key knowledge control regimes that regulate that system.
View Article and Find Full Text PDFInt J Cancer
January 2025
Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR.
Long-term use of low-dose aspirin has been demonstrated to reduce cancer risk, but the duration of necessary medication use remains uncertain. This study aimed to investigate the long-term chemoprotective effect of aspirin among the Chinese population. This population-based study included all aspirin users between 2000 and 2019.
View Article and Find Full Text PDFBMC Public Health
January 2025
Emerging Diseases Epidemiology Unit, Institut Pasteur, 25-28 Rue du Docteur Roux, Bâtiment Laveran, Paris, 75015, France.
Background: The capacity of the 7C model's psychological antecedents, which include confidence in vaccines, complacency, convenience, calculation, collective responsibility, confidence in the wider system, and social conformism, to explain variance in COVID-19 vaccine intentions and behaviours has been documented. However, it remains unclear whether the attitudes represented by the 7C psychological antecedents are specific to vaccination or if they are, in fact, an expression of underlying personality traits.
Methods: From February to June 2022, French adults completed self-administered questionnaires assessing COVID-19 vaccination history, the 7C antecedents, and personality traits ("ComCor" and "Cognitiv" studies).
Sci Rep
January 2025
College of Mathematics and Statistics, Chongqing University, Chongqing, 401331, China.
In this study, we introduce a coupled fractional system consisting of two fluctuating-mass oscillators with time delay and investigate their collective resonant behaviors. First, we achieve complete synchronization between the average behaviors of these oscillators. We then derive the exact analytical expression for the output amplitude gain, and based on this, we observe generalized stochastic resonance (GSR) in the system.
View Article and Find Full Text PDFAm J Hum Genet
January 2025
Shenzhen Research Institute of Big Data, Shenzhen 518172, China. Electronic address:
Genome-wide association studies (GWASs) have identified numerous genetic variants associated with complex traits, yet the biological interpretation remains challenging, especially for variants in non-coding regions. Expression quantitative trait locus (eQTL) studies have linked these variations to gene expression, aiding in identifying genes involved in disease mechanisms. Traditional eQTL analyses using bulk RNA sequencing (bulk RNA-seq) provide tissue-level insights but suffer from signal loss and distortion due to unaddressed cellular heterogeneity.
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