Health risk assessment (HRA) has been recognized as a useful tool for identifying health risks of human activities. In particular, this method has been well applied to spatially defined units, such as a production plant, a treatment facility, and a contaminated site. However, the management strategies based on the risk information will be more efficient if the comprehensive picture of total risks from all kinds of sources is depicted. In principle, the total risks can be obtained when all risk sources are assessed individually. Apparently, this approach demands huge amount of efforts. This study develops a methodology that combines substance flow and risk estimation to facilitate examination of risk in a systemic way and provide comprehensive understanding of risk generation and distribution corresponding to flows of substances in the anthroposphere and the environment. Substance flow analysis (SFA) and HRA method is integrated to produce a systemic risk assessment method, from which substance management schemes can be derived. In this study, the chromium cycle in Taiwan is used as an example to demonstrate the method, by which the associated substance flow in the economy and the risk caused by the substance in the environmental system is determined. The concentrations of pollutants in the environmental media, the resultant risks and hazard quotients are calculated with the widely-used CalTOX multimedia model.
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http://dx.doi.org/10.1016/j.envint.2006.09.011 | DOI Listing |
J Neurosurg
January 2025
13Department of Neurosurgery, Shimane Prefectural Central Hospital, Shimane, Japan.
Objective: Aneurysmal subarachnoid hemorrhage (SAH) is associated with high morbidity and mortality rates. In particular, functional outcomes of SAH caused by large or giant (≥ 10 mm) ruptured intracranial aneurysms are worsened by high procedure-related complication rates. However, studies describing the risk factors for poor functional outcomes specific to ruptured large/giant aneurysms are sparse.
View Article and Find Full Text PDFJ Occup Environ Med
January 2025
Department of Biostatistics, Florida International University, Miami, FL, United States.
Objective: To assess factors influencing Neonatal Respiratory Distress Syndrome (RDS) risk, incorporating maternal demographics, behaviors, medical conditions, pregnancy-related factors, and PM2.5 speciation pollutants exposures.
Methods: Using Florida de-identified birth records, logistic regression analyses were conducted to assess associations between maternal exposure to PM2.
Otol Neurotol
February 2025
Department of Otolaryngology-Head and Neck Surgery.
Objective: To compare fall risk scores of hearing aids embedded with inertial measurement units (IMU-HAs) and powered by artificial intelligence (AI) algorithms with scores by trained observers.
Study Design: Prospective, double-blinded, observational study of fall risk scores between trained observers and those of IMU-HAs.
Setting: Tertiary referral center.
PLoS One
January 2025
College of Business, Southern University of Science and Technology, Shenzhen, China.
In credit risk assessment, unsupervised classification techniques can be introduced to reduce human resource expenses and expedite decision-making. Despite the efficacy of unsupervised learning methods in handling unlabeled datasets, their performance remains limited owing to challenges such as imbalanced data, local optima, and parameter adjustment complexities. Thus, this paper introduces a novel hybrid unsupervised classification method, named the two-stage hybrid system with spectral clustering and semi-supervised support vector machine (TSC-SVM), which effectively addresses the unsupervised imbalance problem in credit risk assessment by targeting global optimal solutions.
View Article and Find Full Text PDFMedicine (Baltimore)
January 2025
Department of Breast, Haining Maternity and Child Health Care Hospital, Haining, Zhejieng, China.
Endosomes play a pivotal role in cellular biology, orchestrating processes such as endocytosis, molecular trafficking, signal transduction, and recycling of cellular materials. This study aims to construct an endosome-related gene (ERG)-derived risk signature for breast cancer prognosis. Transcriptomic and clinical data were retrieved from The Cancer Genome Atlas and the University of California Santa Cruz databases to build and validate the model.
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