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Human decomposition studies aim to understand the various factors influencing human decay to assess the deceased and develop postmortem interval (PMI) estimation methods. These types of studies are typically conducted through physical experiments examining the deceased; however, big data systems have the potential to transform how large-scale forensic anthropology research questions can be addressed with curated images of donors with known demographic, climatic, and postmortem historical data. This study introduces ICPUTRD (Image Cloud Platform for Use in Tagging and Research on Decomposition), a web-based software system, which enables forensic scientists to easily access, enhance (or curate), and analyze very large photographic collections documenting the longitudinal process of human decomposition. ICPUTRD, a JavaScript-based application, was designed and built through a combination of the Waterfall and Agile software development life-cycle methods and provides an image search and tagging features with a predefined nomenclature of forensic-related keywords. To evaluate the system, a user study was conducted, involving 27 participants who completed pre- and post-study surveys and three research tasks. Analysis of the study results confirmed the feasibility and practicality of ICPUTRD to facilitate aspects of forensic research and casework involving large collections of digital photographs of human decomposition. It was observed that the nomenclature lacked certain law enforcement keywords, so future work will focus on expanding it to ensure ICPUTRD is suited for all its intended users.
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http://dx.doi.org/10.1111/1556-4029.15448 | DOI Listing |
Arch Environ Contam Toxicol
September 2025
Ecole Polytechnique Fédérale de Lausanne (EPFL), School of Architecture, Civil and Environmental Engineering, 1015, Lausanne, Switzerland.
Pollution from past industrial activities can remain unnoticed for years or even decades because the pollutant has only recently gained attention or been identified by measurements. Modeling the emission history of pollution is essential for estimating population exposure and apportioning potential liability among stakeholders. This paper proposes a novel approach for reconstructing the history of polychlorinated dibenzo-p-dioxin (PCDD) and polychlorinated dibenzofuran (PCDF) pollution from municipal solid waste incinerators (MSWIs) with unknown past emissions.
View Article and Find Full Text PDFClin Interv Aging
September 2025
Party Committee Office, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China.
Objective: Living alone is becoming increasingly common among the elderly population, and there is a close relationship between living alone and chronic diseases in relation to depression. However, the interplay between them has not been fully investigated. This study aims to explore the role of the number of chronic diseases in the relationship between living alone and depressive symptoms among older adults in China.
View Article and Find Full Text PDFFront Biosci (Landmark Ed)
August 2025
Department of Microbiology, School of Medicine, Kitasato University, Sagamihara-shi, 252-0374 Kanagawa, Japan.
Background: Vitamin D decomposition products target a myristic acid sidechain of the predominant glycerophospholipid constructed in the biomembranes of causing gastric cancer in humans, and disrupt the membrane structure, followed by bacteriolysis. No earlier studies, however, elucidate whether vitamin D decomposition products interact with the glycerophospholipids that construct the eukaryotic biomembranes and confer whatever cell disorders.
Methods: A gastric cancer cell line, MKN45, and a non-cancer cell line, Vero, were used in this study.
Electromagn Biol Med
September 2025
Computer Science and Business Systems, Sri Krishna College of Engineering and Technology, Coimbatore, India.
Subject-independent emotion detection using EEG (Electroencephalography) using Vibrational Mode Decomposition and deep learning is made possible by the scarcity of labelled EEG datasets encompassing a variety of emotions. Labelled EEG data collection over a wide range of emotional states from a broad and varied population is challenging and resource-intensive. As a result, models trained on small or biased datasets may fail to generalize well to unknown individuals or emotional states, resulting in lower accuracy and robustness in real-world applications.
View Article and Find Full Text PDFNeuroimage
September 2025
The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, P.R. China; Brain-Computer Interface & Brain-Inspired Intelligence Key Laboratory of Sichuan Province, University of Electronic
Functional magnetic resonance imaging (fMRI) opens a window on observing spontaneous activities of the human brain in vivo. However, the high complexity of fMRI signals makes brain functional representations intractable. Here, we introduce a state decomposition method to reduce this complexity and decipher individual brain functions at multiple levels.
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