Before discovering meaningful knowledge from big data systems, it is first necessary to build a data-gathering infrastructure. Among many feasible data sources, wireless sensor networks (WSNs) are rich big data sources: a large amount of data is generated by various sensor nodes in large-scale networks. However, unlike typical wireless networks, WSNs have serious deficiencies in terms of data reliability and communication owing to the limited capabilities of the nodes. Moreover, a considerable amount of sensed data are of no interest, meaningless, and redundant when a large number of sensor nodes is densely deployed. Many studies address the existing problems and propose methods to overcome the limitations when constructing big data systems with WSN. However, a published paper that provides deep insight into this research area remains lacking. To address this gap in the literature, we present a comprehensive survey that investigates state-of-the-art research work on introducing WSN in big data systems. Potential applications and technical challenges of networks and infrastructure are presented and explained in accordance with the research areas and objectives. Finally, open issues are presented to discuss promising directions for further research.
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http://dx.doi.org/10.3390/s19071565 | 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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