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Half logistic exponentiated inverse Rayleigh distribution: Properties and application to life time data.
PLoS One
January 2025
Department of Statistics, University of Kerala, Trivandrum, India.
This paper presents a novel extension of the exponentiated inverse Rayleigh distribution called the half-logistic exponentiated inverse Rayleigh distribution. This extension improves the flexibility of the distribution for modeling lifetime data for both monotonic and non-monotonic hazard rates. The statistical properties of the half-logistic exponentiated inverse Rayleigh distribution, such as the quantiles, moments, reliability, and hazard function, are examined.
View Article and Find Full Text PDFIntegrating machine learning, suspect and nontarget screening reveal the interpretable fates of micropollutants and their transformation products in sludge.
J Hazard Mater
January 2025
School of Environmental Studies, China University of Geosciences, Wuhan, Hubei 430074, China; National Engineering Research Center of Industrial Wastewater Detoxication and Resource Recovery, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China. Electronic address:
Activated sludge enriches vast amounts of micropollutants (MPs) when wastewater is treated, posing potential environmental risks. While standard methods typically focus on target analysis of known compounds, the identity, structure, and concentration of transformation products (TPs) of MPs remain less understood. Here, we employed a novel approach that integrates machine learning for the quantification of nontarget TPs with advanced target, suspect, and nontarget screening strategies.
View Article and Find Full Text PDFMachine learning outperforms humans in microplastic characterization and reveals human labelling errors in FTIR data.
J Hazard Mater
December 2024
Discipline of Chemistry, The University of Newcastle, University Drive, Newcastle, New South Whales 2308, Australia; School of Chemistry, Monash University, Wellington Road, Melbourne, Victoria 3800, Australia. Electronic address:
Microplastics are ubiquitous and appear to be harmful, however, the full extent to which these inflict harm has not been fully elucidated. Analysing environmental sample data is challenging, as the complexity in real data makes both automated and manual analysis either unreliable or time-consuming. To address challenges, we explored a dense feed-forward neural network (DNN) for classifying Fourier transform infrared (FTIR) spectroscopic data.
View Article and Find Full Text PDFEffectiveness and Safety of Dose-Specific DOACs in Patients With Atrial Fibrillation: A Systematic Review and Network Meta-Analysis.
Cardiovasc Ther
January 2025
College of Pharmacy and Institute of Pharmaceutical Science and Technology, Hanyang University, Ansan-si, Gyeonggi-do, Republic of Korea.
Dose adjustments of direct-acting oral anticoagulants (DOACs) for atrial fibrillation are based on pivotal clinical trials assessing their effectiveness and safety in controlled settings. However, the appropriateness of these dosing strategies in real-world practice is uncertain. The purpose of this study is to compare the effectiveness and safety of dose-specific DOACs with those of warfarin.
View Article and Find Full Text PDFConstruction and application of optimized model for mine water inflow prediction based on neural network and ARIMA model.
Sci Rep
January 2025
Key Laboratory of Karst Georesources and Environment, College of Resources and Environmental Engineering, Guizhou University, Ministry of Education, Guizhou University, Guiyang, 550025, China.
Mine water influx is a significant geological hazard during mine development, influenced by various factors such as geological conditions, hydrology, climate, and mining techniques. This phenomenon is characterized by non-linearity and high complexity, leading to frequent water accidents in coal mines. These accidents not only impact coal production quality but also jeopardize the safety of mine staff.
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