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Showing 9 of 9 academic articles

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

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

Development and validation of a predictive model for diabetic peripheral neuropathy with type 2 diabetes mellitus in Xinjiang, China

Asiguli Adili, Maihesumu Aikemu, Karanvir Singh Rana, Yihan Wei et al. • Scientific Reports (2025)

Abstract This study aims to identify risk factors associated with diabetic peripheral neuropathy (DPN) in patients with type 2 diabetesmellitus (T2DM) and to develop a predictive model to support clinical decision-making. A total of 1,001 p...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-19922-7

Real time identification of phishing attacks through machine learning enhanced browser extensions

Monika Dandotiya, Nikhil Kumar Goyal, Ajay Khunteta, Babita Tiwari • Scientific Reports (2026)

Abstract Phishing attack continues to rank among the deadliest online threats. They create phony websites in an attempt to obtain personal data. This study offers a framework for a browser extension that uses machine learning to examine URL...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-35655-7

Gut Microbiota and Targeted Biomarkers Analysis in Patients With Cognitive Impairment

Shourong Lu, Ying Yang, Qiao Xu, Shuqiang Wang et al. • Frontiers in Neurology (2022)

Gut microbial alteration is closely associated with brain disorders including cognitive impairment (CI). Gut microbes have the potential to predicate the development of diseases. However, the gut microbial markers for CI remain to be elucid...

DOAJ Open Access (DOAJ) DOI: 10.3389/fneur.2022.834403

Determinants of Tourism Demand Using Machine Learning Techniques

Musonera Abdou, Edouard Musabanganji, Herman Musahara • African Journal of Hospitality, Tourism and Leisure (2022)

The purpose of the current study was to determine factors affecting tourism demand using machine learning techniques. The results of different linear regression and random forest models on both the train and test sets were compared using RM...

DOAJ Open Access (DOAJ) DOI: https://doi.org/10.46222/ajhtl.19770720.256

Global patterns of gully occurrence and their sensitivity to environmental changes

Yixian Chen, Sofie De Geeter, Jean Poesen, Francis Matthews et al. • International Soil and Water Conservation Research (2026)

Gully formation is a significant driver of soil erosion and land degradation worldwide and often leads to important downstream impacts. Nonetheless, our understanding of the global patterns and the factors controlling this process remains l...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.iswcr.2025.09.004

Leveraging AI to Estimate Caribou Lichen in UAV Orthomosaics from Ground Photo Datasets

Galen Richardson, Sylvain G. Leblanc, Julie Lovitt, Krishan Rajaratnam et al. • Drones (2021)

Relating ground photographs to UAV orthomosaics is a key linkage required for accurate multi-scaled lichen mapping. Conventional methods of multi-scaled lichen mapping, such as random forest models and convolutional neural networks, heavily...

DOAJ Open Access (DOAJ) DOI: 10.3390/drones5030099

A machine learning approach predicts future risk to suicidal ideation from social media data

Arunima Roy, Katerina Nikolitch, Rachel McGinn, Safiya Jinah et al. • npj Digital Medicine (2020)

Abstract Machine learning analysis of social media data represents a promising way to capture longitudinal environmental influences contributing to individual risk for suicidal thoughts and behaviors. Our objective was to generate an algori...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41746-020-0287-6