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Hybrid heterogeneous ensemble learning framework for flood susceptibility mapping in Balochistan, Pakistan

Muhammad Afaq Hussain, Zhanlong Chen, Biswajeet Pradhan, Sansar Raj Meena et al. • Journal of Hydrology: Regional Studies (2025)

Study region: The National Highways 85 and 50, key routes of the China–Pakistan Economic Corridor (CPEC) in Balochistan, Pakistan. Study focus: Flooding is a natural disaster that is becoming increasingly frequent and severe. The National H...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.ejrh.2025.102718

Enhanced Deep Learning Model for Classification of Retinal Optical Coherence Tomography Images

Esraa Hassan, Samir Elmougy, Mai R. Ibraheem, M. Shamim Hossain et al. • Sensors (2023)

Retinal optical coherence tomography (OCT) imaging is a valuable tool for assessing the condition of the back part of the eye. The condition has a great effect on the specificity of diagnosis, the monitoring of many physiological and pathol...

DOAJ Open Access (DOAJ) DOI: 10.3390/s23125393

Investigating Spatial Effects through Machine Learning and Leveraging Explainable AI for Child Malnutrition in Pakistan

Xiaoyi Zhang, Muhammad Usman, Ateeq ur Rehman Irshad, Mudassar Rashid et al. • ISPRS International Journal of Geo-Information (2024)

While socioeconomic gradients in regional health inequalities are firmly established, the synergistic interactions between socioeconomic deprivation and climate vulnerability within convenient proximity and neighbourhood locations with heal...

DOAJ Open Access (DOAJ) DOI: 10.3390/ijgi13090330

Machine learning-based dynamic risk measurement for white sugar futures under geopolitical risks

Zihao Qiu, Siyu Chen, Zixin Feng, Ruitong Luo et al. • Frontiers in Physics (2025)

Futures, as significant financial derivatives, play a crucial role in financial markets by fulfilling price discovery functions and providing efficient risk hedging tools. Against the backdrop of geopolitical conflicts, market risk emerges ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fphy.2025.1674717

MiRNA Profiles in Lymphoblastoid Cell Lines of Finnish Prostate Cancer Families.

Daniel Fischer, Tiina Wahlfors, Henna Mattila, Hannu Oja et al. • PLoS ONE (2015)

BACKGROUND:Heritable factors are evidently involved in prostate cancer (PrCa) carcinogenesis, but currently, genetic markers are not routinely used in screening or diagnostics of the disease. More precise information is needed for making tr...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0127427

A robust and uncertainty-aware machine learning framework for PM2.5 prediction in a coastal urban Indian environment: implications for sustainable air quality management

Salvator Lawrence, Srimuruganandam Bhathmanabhan • Sustainable Environment Research (2026)

Abstract Accurate prediction of fine particulate matter (PM2.5) remains challenging because atmospheric processes are nonlinear, nonstationary, and influenced by temporal variability, measurement uncertainty, and episodic pollution events. ...

DOAJ Open Access (DOAJ) DOI: 10.1186/s42834-026-00296-y

Near infrared spectroscopy predicts crude protein concentration in hemp grain

Ryan V. Crawford, Jamie L. Crawford, Julie L. Hansen, Lawrence B. Smart et al. • Agrosystems, Geosciences & Environment (2026)

Abstract This study evaluated near‐infrared spectroscopy (NIRS) for nondestructive crude protein (CP) prediction in hemp (Cannabis sativa L.) grain and validated the biological basis of spectral predictions. Note that 149 whole grain sample...

DOAJ Open Access (DOAJ) DOI: 10.1002/agg2.70328

MRI Application in Quantification of Epiphyseal Development in the Wrist and Bone Age Estimation of Han Male Adolescents in East China

ZHOU Zhi-lu, ZHANG Dong-fei, CHEN Jie-min, WANG Ya-hui et al. • Fayixue Zazhi (2024)

ObjectiveTo investigate the value of wrist MRI in bone age estimation for male adolescents in Shanghai, Zhejiang and Jiangsu.MethodsA total of 124 Han male adolescents aged 6.0 to 18.0 years from Shanghai, Zhejiang and Jiangsu were selected...

DOAJ Open Access (DOAJ) DOI: 10.12116/j.issn.1004-5619.2023.231203

Bacterial Succession in Microbial Biofilm as a Potential Indicator for Postmortem Submersion Interval Estimation

Finkelbergs Dmitrijs, Juanjuan Guo, Juanjuan Guo, Juanjuan Guo et al. • Frontiers in Microbiology (2022)

Bacteria acts as the main decomposer during the process of biodegradation by microbial communities in the ecosystem. Numerous studies have revealed the bacterial succession patterns during carcass decomposition in the terrestrial setting. T...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmicb.2022.951707

Alterations in the gut microbiota and its metabolites contribute to metabolic maladaptation in dairy cows during the development of hyperketonemia

Zhengzhong Luo, Zhenlong Du, Yixin Huang, Tao Zhou et al. • mSystems (2024)

ABSTRACTMetabolic maladaptation in dairy cows after calving can lead to long-term elevation of ketones, such as β-hydroxybutyrate (BHB), representing the condition known as hyperketonemia, which greatly influences the health and production ...

DOAJ Open Access (DOAJ) DOI: 10.1128/msystems.00023-24

Geographic Object-Based Image Analysis Framework for Mapping Vegetation Physiognomic Types at Fine Scales in Neotropical Savannas

Fernanda F. Ribeiro, Dar A. Roberts, Laura L. Hess, Frank W. Davis et al. • Remote Sensing (2020)

Regional maps of vegetation structure are necessary for delineating species habitats and for supporting conservation and ecological analyses. A systematic approach that can discriminate a wide range of meaningful and detailed vegetation cla...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs12111721

Topograpaphic controls and future vulnerability of recurrent snowpatches in the Gaspé Peninsula (Québec, Canada)

Valentin Riva, Daniel Germain • Arctic, Antarctic, and Alpine Research (2026)

Snowpatches are sensitive indicators of environmental change in mountain environments because their occurrence reflects interactions among topography, snow redistribution, and climate. Despite their ecological and geomorphological significa...

DOAJ Open Access (DOAJ) DOI: 10.1080/15230430.2026.2739774

Neurotoxicity of PM<sub>2.5</sub>-Bound Multi-Pollutant Mixtures in Parkinson’s Disease: Exploring the <i>INPP5D</i>/SHIP1-PI3K-AKT Axis via an Integrative Multi-Omics Study

Lufei Chen, Chaoxian Dai, Zhenfang Wu, Yuhan Lin et al. • Journal of Xenobiotics (2026)

Accumulating epidemiological evidence links ambient PM2.5 exposure to elevated Parkinson’s disease (PD) risk, yet the neurotoxicity triggered by PM2.5 multi-pollutant mixtures under real co-exposure scenarios remains insufficiently elucidat...

DOAJ Open Access (DOAJ) DOI: 10.3390/jox16060184

Artificial neural network–based model for sleep quality prediction for frontline medical staff during major medical assistance

Qingquan Chen, Zeshun Chen, Xi Zhu, Jiajing Zhuang et al. • Digital Health (2024)

Background: The sleep quality of medical staff was severely affected during COVID-19, but the factors influencing the sleep quality of frontline staff involved in medical assistance remained unclear, and screening tools for their sleep qual...

DOAJ Open Access (DOAJ) DOI: 10.1177/20552076241287363

Artificial intelligence–aided diagnosis model for acute respiratory distress syndrome combining clinical data and chest radiographs

Kai-Chih Pai, Wen-Cheng Chao, Yu-Len Huang, Ruey-Kai Sheu et al. • Digital Health (2022)

Objective The aim of this study was to develop an artificial intelligence–based model to detect the presence of acute respiratory distress syndrome (ARDS) using clinical data and chest X-ray (CXR) data. Method The transfer learning method w...

DOAJ Open Access (DOAJ) DOI: 10.1177/20552076221120317

Integrating machine learning algorithms and explainable artificial intelligence approach for predicting patient unpunctuality in psychiatric clinics

Alireza Kasaie, Suchithra Rajendran • Healthcare Analytics (2023)

This study addresses patient unpunctuality, a major concern affecting patient waiting time, resource utilization, and quality of care. We develop and compare four machine learning models, including multinomial logistic regression, decision ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.health.2023.100242

Effect of chemical treatment on the mechanical and thermal performance of flax fiber reinforced aluminium 6082 laminate: a machine learning-enhanced investigation

M. Vinod, B. S. Nithyananda, Shrishail B. Sollapur, Satish Gajbhiv et al. • Scientific Reports (2026)

Abstract This work examined the role of alkaline and epoxy-based surface chemical treatments on the mechanical and thermal properties of flax fiber reinforced Aluminum Alloy 6082 hybrid Fiber Metal Laminates (FMLs), integrated with machine ...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-58852-w