Uncovering mercury accumulation and the potential for bacterial bioremediation in response to contamination in the Singalila National Park by Sukanya Acharyya, Soumya Majumder, Sudeshna Nandi, Arindam Ghosh, Sumedha Saha, Malay Bhattacharya

“…Abstract Several recent investigations into montane regions have reported on excess mercury accumulation in high-altitude forest ecosystems. This study explored the Singalila National Park, located on the Singalila ridge of the Eastern Himalayas, revealing substantial mercury contamination. …”
Get full text

Downscaling and Projection of Multi-CMIP5 Precipitation Using Machine Learning Methods in the Upper Han River Basin by Ren Xu, Nengcheng Chen, Yumin Chen, Zeqiang Chen

“…Support vector machine for regression (SVR) was superior to multilayer perceptron (MLP) and random forest (RF). The downscaling results based on the BMA ensemble simulation and SVR models were regarded as the best performing overall (PCC, RMSE, and Rbias were 0.82, 35.07, mm and −5.45%, respectively). (3) Based on BMA and SVR models, the projected precipitations show a weak increasing trend on the whole under RCP4.5 and RCP8.5. …”
Get full text

Machine-learning-based cost prediction models for inpatients with mental disorders in China by Yuxuan Ma, Xi Tu, Xiaodong Luo, Linlin Hu, Chen Wang

“…Performance of these six algorithms was evaluated through 5- old cross-validation combined with bootstrap method to select the most suitable algorithm and identify key factors influencing ADHC. Results The random forest (RF) model demonstrated better performance (R-squared (R2) = 0.6417 (95% CI, 0.6236–0.6611), root-mean-square error (RMSE) = 0.2398 (95% CI, 0.2252–0.2553), mean-absolute error (MAE) = 0.1677 (95% CI, 0.1626–0.1735), mean-absolute-percentage error (MAPE) = 0.0295 (95% CI, 0.0287–0.0304)). …”
Get full text

Association of plasma biomarkers of Alzheimer’s pathology and neurodegeneration with gait performance in older adults by Farwa Ali, Jeremy A. Syrjanen, Dan J. Figdore, Walter K. Kremers, Michelle M. Mielke, Clifford R. Jack, David S. Knopman, Prashanthi Vemuri, Jonathan Graff-Radford, B. Gwen Windham, Leland R. Barnard, Ronald C. Petersen, Alicia Algeciras-Schimnich

Get full text

Narrow Dietary Niche With High Overlap Between Snow Leopards and Himalayan Wolves Indicates Potential for Resource Competition in Shey Phoksundo National Park, Nepal by Sandesh Lamichhane, Bikram Shrestha, Bhumi Prakash Chaudhary Tharu, Raj Kumar Koirala, Bishnu Prasad Bhattarai, Pratigyan Poudel, Binaya Adhikari, Gopal Khanal

Get full text

Qwen-2.5 Outperforms Other Large Language Models in the Chinese National Nursing Licensing Examination: Retrospective Cross-Sectional Comparative Study by Shiben Zhu, Wanqin Hu, Zhi Yang, Jiani Yan, Fang Zhang

“…Seven LLMs were evaluated on these multiple-choice questions, and 9 machine learning models, including Logistic Regression, Support Vector Machine, Multilayer Perceptron, k-nearest neighbors, Random Forest, LightGBM, AdaBoost, XGBoost, and CatBoost, were used to optimize overall performance through ensemble techniques. …”
Get full text

Childhood neurodivergent traits, inflammation and chronic disabling fatigue in adolescence: a longitudinal case–control study by Neil A Harrison, Hugo D Critchley, Jessica Eccles, Kevin A Davies, Lisa Quadt, Rod Bond, Jenny Csecs

Get full text

Cooperative Overbooking-Based Resource Allocation and Application Placement in UAV-Mounted Edge Computing for Internet of Forestry Things by Xiaoyu Li, Long Suo, Wanguo Jiao, Xiaoming Liu, Yunfei Liu

“…Due to the high mobility and low cost, unmanned aerial vehicle (UAV)-mounted edge computing (UMEC) provides an efficient way to provision computing offloading services for Internet of Forestry Things (IoFT) applications in forest areas without sufficient infrastructure. Multiple IoFT applications can be consolidated into fewer UAV-mounted servers to improve the resource utilization and reduce deployment costs with the precondition that all applications’ Quality of Service (QoS) can be met. …”
Get full text

Construction of machine learning-based models for screening the high-risk patients with gastric precancerous lesions by Shuxian Yu, Haiyang Jiang, Jing Xia, Jie Gu, Mengting Chen, Yan Wang, Xiaohong Zhao, Zehua Liao, Puhua Zeng, Tian Xie, Xinbing Sui

“…Then, the prediction model was established using ten different machine learning algorithms and the Random Forest (RF) model achieved the highest accuracy at 85.65%. …”
Get full text

The emerging role of blood-based biomarkers in early detection of colorectal cancer: A systematic review by Faris Shweikeh, Yuhao Zeng, Abdur Rahman Jabir, Erica Whittenberger, Saurav P. Kadatane, Yuting Huang, Mohamad Mouchli, Dani Ran Castillo

Get full text

Evaluation of Four Multiple Imputation Methods for Handling Missing Binary Outcome Data in the Presence of an Interaction between a Dummy and a Continuous Variable by Sara Javadi, Abbas Bahrampour, Mohammad Mehdi Saber, Behshid Garrusi, Mohammad Reza Baneshi

“…MI methods included using predictive mean matching with an interaction term in the imputation model in MICE (MICE-interaction), classification and regression tree (CART) for specifying the imputation model in MICE (MICE-CART), the implementation of random forest (RF) in MICE (MICE-RF), and MICE-Stratified method. …”
Get full text

Genetic methods in honey bee breeding by M. D. Kaskinova, A. M. Salikhova, L. R. Gaifullina, E. S. Saltykova

“…A method based on the analysis of polymorphisms of the tRNAleu-COII locus and microsatellite nuclear DNA loci has been developed to identify the dark forest bee A. m. mellifera and does not allow one to differentiate subspecies from C (A. m. carnica and A. m. ligustica) and O (A. m. caucasica) evolutionary lineages from each other. …”
Get full text

Successful domestication of Neonothopanus Hygrophanus (Mont.) De Kesel & Degreef and Lentinus Squarrosulus Mont., indigenous saprophytic edible mushrooms from Kibira National Park... by Vincent Nteziryayo, Anthony M. Mshandete, Donatha D. Tibuhwa

“…The country is endowed with indigenous forests that harbour a wide diversity of mushrooms with potential for domestication. …”
Get full text

Application of multi-indexing approach within a GIS framework to investigate the quality and contamination of ground water in Barisal sadar, Bangladesh by Md. Numan Hossain, M. Farhad Howladar, Sohag Ahammed, Md Rezwanul Haque, Majedul Islam Khan, Muyeed Hasan, Tayabur Rashid Chowdhury, Alamgir Hosain

Get full text

Study on influencing factors of age-adjusted Charlson comorbidity index in patients with Alzheimer's disease based on machine learning model by Jian Ding, Jian Ding, Zheng Long, Yiming Liu, Min Wang

“…Multiple logistic regression, LASSO regression, random forest, Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) models were used to screen for feature factors significantly correlated with aCCI. …”
Get full text

Physical Activity, Obesity, and Hypertension among Adults in a Rapidly Urbanised City by Qianqian Dun, Wanglin Xu, Maozhen Fu, Nengjian Wu, Justin B. Moore, Ting Yu, Xin Li, Yating Du, Biao Zhang, Qiaomai Wang, Yiting Duan, Ziqi Meng, Shuangshuang Tian, Yuliang Zou

Get full text

Evaluation of synthetic wheat lines (Triticum durum/Aegilops tausсhii) for vegetative period and resistance to diseases by V. P. Shamanin, I. V. Pototskaya, S. S. Shepelev, V. E. Pozherukova, A. Yu. Truschenko, A. S. Chursin, A. I. Morgunov

“…Research was performed on the experimental field of Omsk SAU under conditions of southern forest-steppe of West Siberia in 2016. Between synthetics, there was revealed a genotypic difference in the vegetative period duration and resistance to diseases. …”
Get full text

Resource availability and competition shape pollinator trophic specialization in longleaf pine savannas by Pablo Moreno-García, Johanna E. Freeman, Benjamin Baiser, Joshua W. Campbell, Daijiang Li

Get full text

Predicting the risk of gastroparesis in critically ill patients after CME using an interpretable machine learning algorithm – a 10-year multicenter retrospective study by Yuan Liu, Songyun Zhao, Wenyi Du, Wei Shen, Ning Zhou

“…In the present study, four advanced machine learning algorithms—Extreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Machine (SVM), and k-nearest neighbor (KNN)—were employed to develop predictive models. …”
Get full text

Modeling vegetation density with remote sensing, normalized difference vegetation index and biodiversity plants in watershed area by R.Z. Ekaputri, T. Hidayat, H.K. Surtikanti, W. Surakusumah

“…Moreover, the process of converting forests into plantations or agricultural lands has resulted in environmental degradation. …”
Get full text