Influence of food availability on the diet and activity budget of two western lowland gorilla (Gorilla gorilla gorilla) groups of differing size in the Dzanga-Ndoki National Park,... by Terence Fuh Neba, Giuseppe Donati, Angelique Todd, Shelly Masi

“…Such flexibility may better allow WLG groups to track ripe fruits when available but, unlike sympatric chimpanzees, switch to more herbivorous diets when necessary, adjusting activity budgets accordingly ; WLGs thus may be considered more resilient faced with environmental change such as forest degradation.…”
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Molecular Characterization and Clinical Characteristics of m5C-Based RNA Methylation in Spinal Cord Injury: Validated by qPCR by Liang Cao, Wen Jun Pi, Qiang Zhang, Qing Li

“…We constructed a “gene signature” of m5C-based regulators of RNA modification to predict the prognosis of SCI using least absolute shrinkage and selection operator regression and random-forest strategy. We found that the m5C-related genes, deoxyribonucleic acid (DNA) methyltransferase1 (Dnmt1), methyl-CpG binding domain protein 2 (Mbd2), ubiquitin-like with PHD and ring finger domains 1 (Uhrf1), uracil-N-glycosylase (Ung), and zinc finger and BTB(brica-brac, tramtrack, and broad) domain containing 38 (Zbtb38) had high expression, and zinc finger and BTB domain containing 4 (Zbtb4) had low expression in SCI. …”
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Enhancing the estimation of cadmium content in rice leaves by integrating vegetation indices and color indices using machine learning by Xiaoyun Huang, Shengxi Chen, Tianling Fu, Chengwu Fan, Hongxing Chen, Song Zhang, Hui Chen, Song Qin, Zhenran Gao

“…Notably, the LCd estimation model developed using the random forest method exhibited the highest accuracy, with a coefficient of determination (R2) of 0.81 and a root-mean-square error of 0.120. …”
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A Pine Wilt Disease Detection Model Integrated with Mamba Model and Attention Mechanisms Using UAV Imagery by Minhui Bai, Xinyu Di, Lechuan Yu, Jian Ding, Haifeng Lin

“…Pine wilt disease (PWD) is a highly destructive worldwide forest quarantine disease that has the potential to destroy entire pine forests in a relatively brief period, resulting in significant economic losses and environmental damage. …”
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Explainable AutoML models for predicting the strength of high-performance concrete using Optuna, SHAP and ensemble learning by Muhammad Salman Khan, Tianbo Peng, Tianbo Peng, Muhammad Adeel Khan, Asad Khan, Mahmood Ahmad, Mahmood Ahmad, Kamran Aziz, Mohanad Muayad Sabri Sabri, N. S. Abd EL-Gawaad

“…This study introduces four explainable Automated Machine Learning (AutoML) models that integrate Optuna for hyperparameter optimization, SHapley Additive exPlanations (SHAP) for interpretability, and ensemble learning algorithms such as Random Forest (RF), Extreme Gradient Boosting (XGB), Light Gradient Boosting Machine (LGB), and Categorical Gradient Boosting (CB). …”
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Assessing the Effects of Tourism Activities on the Preservation of Cultural Heritage Among Communities of Rubanda DistrictUganda. by Ahabwe, John Brighton

“…Tourists treks through the dense forest to observe mountain gorillas in their natural habitat, some respondents also showed the district's forests and wetlands are home to a diverse array of bird species, making it an excellent destination for bird watching enthusiasts. …”
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Identification of heat tolerant lentil genotypes through stress tolerance indices by Rohit Sarkar, Gyan Prakash Mishra, Premakumar, Ankita Singh, Jenia Roy, Kumbarahally Murthigowda Shivaprasad, Shashidhar B. Reddappa, Sudhir Kumar, Ruchi Bansal, Uttarayan Dasgupta, Soma Gupta, Susheel Kumar Sarkar, Sanjeev Gupta, Shiv Kumar, Harsh K. Dikshit, Prachi Sripathrao Yadav, Muraleedhar S. Aski

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Characteristics of Soil Profile Greenhouse Gas Concentrations and Fluxes of Alpine Grassland as Affected by Livestock Grazing by Mingyuan Yin, Xiaopeng Gao, Yanyan Li, Yufeng Wu, Wennong Kuang, Fanjiang Zeng

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Challenges of Engineering Skillsets Essential for Driving Circularity of Smart Cities by Benjamin Neale, Sakdirat Kaewunruen, Dan Li, Ayfer Donmez Cavdar, Rand Askar, Tatjana Tambovceva, Diana Bajare

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Assessing subtle changes in arid land river basin ecological quality: A study utilizing the PIE engine platform and RSEI by Aizemaitijiang Maimaitituersun, Han Yang, Nuerbiye Aobuliaisan, Kamuran Maimaitiaili, Ouyang Chenyu

“…Despite requisitioning cultivated land, forest, and grass—key for regional balance—sustained deterioration is not anticipated due to their small areas and potential for recovery. …”
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HPLC Analysis and Antioxidant Evaluation of Acteoside-Rich Osmanthus fragrans Extracts by Sung-Ho Lee, Seong-Wook Seo, Seung-Yub Song, Deuk-Sil Oh, Jung-Hyun Shim, Goo Yoon, Ye-Yong Choi, Do-Kyung Kim, Jae-Sung Kim, In-Soo Yoon, Seung-Sik Cho

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Diversity of Picea omorika (Pančić) Purk. Populations Based on Morpho-anatomical Needle Traits and Bioclimatic Parameters by Biljana Nikolić, Nemanja Rajčević, Zorica Mitić, Sanja Jovanović, Nevena Čule, Katarina Mladenović, Marija Marković, Petar Marin

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Early life microbial succession in the gut follows common patterns in humans across the globe by Guilherme Fahur Bottino, Kevin S. Bonham, Fadheela Patel, Shelley McCann, Michal Zieff, Nathalia Naspolini, Daniel Ho, Theo Portlock, Raphaela Joos, Firas S. Midani, Paulo Schüroff, Anubhav Das, Inoli Shennon, Brooke C. Wilson, Justin M. O’Sullivan, Robert A. Britton, Deirdre M. Murray, Mairead E. Kiely, Carla R. Taddei, Patrícia C. B. Beltrão-Braga, Alline C. Campos, Guilherme V. Polanczyk, Curtis Huttenhower, Kirsten A. Donald, Vanja Klepac-Ceraj

“…Using 3154 samples from 1827 infants across 12 countries, we trained a random forest model, achieving a root mean square error of 2.56 months. …”
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Predictive models for the implementation of targeted reproductive management in multiparous cows on automatic milking systems by Fergus P. Hannon, Martin J. Green, Luke O'Grady, Chris Hudson, Anneke Gouw, Laura V. Randall

“…Using data derived solely from the AMS (RBT dataset) a binary random forest classification model was constructed for both outcomes of interest. …”
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A novel method to determine background concentrations and spatial distributions of heavy metals in soil at large scale using machine learning coupled with remote sensing-terrain at... by Magboul M. Sulieman, Fuat Kaya, Abdullah S. Al-Farraj, Eric C. Brevik

“…The proposed methodology combined measurements of the target HMs and fifty-two environmental covariates (ECOVs) derived from 2017 to 2021 Landsat 8/9 OLI and Shuttle Radar Topography Mission (SRTM)-derived terrain attributes. Random forest and stepwise multiple linear regression models were further used to digitally map the studied HMs. …”
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Identification of serum tRNA-derived small RNAs biosignature for diagnosis of tuberculosis by Zikun Huang, Qing Luo, Cuifen Xiong, Haiyan Zhu, Chao Yu, Jianqing Xu, Yiping Peng, Junming Li, Aiping Le

“…By utilizing cross-validation with a random forest algorithm approach, the training cohort achieved a sensitivity of 100% and specificity of 100%. …”
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Rapid detection of carbapenem-resistant Escherichia coli and carbapenem-resistant Klebsiella pneumoniae in positive blood cultures via MALDI-TOF MS and tree-based machine learning... by Xiaobo Xu, Zhaofeng Wang, Erjie Lu, Tao Lin, Hengchao Du, Zhongfei Li, Jiahong Ma

“…This study was based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), Decision Tree (DT), Random Forest (RF), Gradient Boosting Machine (GBM), eXtreme Gradient Boosting (XGBoost), and Extremely Randomized Trees (ERT) models were constructed to classify carbapenem-resistant Escherichia coli (CREC) and carbapenem-resistant Klebsiella pneumoniae (CRKP). …”
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Mitigating bias in AI mortality predictions for minority populations: a transfer learning approach by Tianshu Gu, Wensen Pan, Jing Yu, Guang Ji, Xia Meng, Yongjun Wang, Minghui Li

“…Results Decision Tree (DT) and Random Forest (RF) models consistently showed improvements in accuracy, precision, and ROC-AUC scores for Non-Hispanic Black, Hispanic/Latino, and Asian populations. …”
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Synergistic mapping of urban tree canopy height using ICESat-2 data and GF-2 imagery by Xiaodi Xu, Ya Zhang, Peng Fu, Chaoya Dang, Bowen Cai, Qingwei Zhuang, Zhenfeng Shao, Deren Li, Qing Ding

“…To achieve UTCH mapping at a resolution of 4 m, a synergistic model integrating data from the GF-2 and ICESat-2 grid-based canopy height was constructed using the Random Forest technique. The model’s performance was evaluated using 111 urban tree canopy height samples collected across different urban areas. …”
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Soil organic carbon contents and their major influencing factors in mangrove tidal flats: a comparison between estuarine and non-estuarine areas by Ting Wu, Jia Guo, Gang Li, Yu Jin, Wei Zhao, Guangxuan Lin, Fang-Li Luo, Yaojun Zhu, Yifei Jia, Li Wen

“…We compared the SOC and soil physicochemical properties between estuarine and non-estuarine mangrove tidal flats. The Random Forest algorithm was employed to identify the main influencing factors affecting SOC. …”
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