ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool by D. Di Santo, C. He, F. Chen, L. Giovannini

“…This tool leverages the strengths of multiple regression-based and probabilistic machine learning methods, including LASSO (see the list of abbreviations in Appendix B), support vector machine, classification and regression trees, random forest, extreme gradient boosting, Gaussian process regression, and Bayesian ridge regression. …”
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AI-Driven Mental Health Surveillance: Identifying Suicidal Ideation Through Machine Learning Techniques by Hesham Allam, Chris Davison, Faisal Kalota, Edward Lazaros, David Hua

“…Advanced preprocessing techniques, including tokenization, stemming, and feature extraction with term frequency–inverse document frequency (TF-IDF) and count vectorization, ensured high-quality data transformation. A random forest classifier was selected for its ability to handle high-dimensional data and effectively capture linguistic and emotional patterns linked to suicidal ideation. …”
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Investigation of Intestinal Microbes of Five Zokor Species Based on 16S rRNA Sequences by Yao Zou, Quan Zou, Hui Yang, Chongxuan Han

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Seasonal Tree Height Dynamic Estimation Using Multi-source Remotely Sensed Data in Shenzhen by Hang Song, Xuemei Zhang, Ting Hu, Jinglei Liu, Bing Xu

“…Tree height is a key indicator in forest ecology, reflecting tree growth status and ecosystem structure. …”
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Estimation of Landslides and Road Capacity after August 8, 2017, MS7.0 Jiuzhaigou Earthquake Using High-Resolution Remote Sensing Images by Xiao Fu, Qing Zhu, Chao Liu, Naiwen Li, Wenhua Zhuang, Zhengli Yang, Heng Lu, Min Tang

“…As the earthquake-stricken area is located in the mountainous region with forest and low residential density, the main damage is to vegetation and roads by earthquake-triggered landslides. …”
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Impact of Different Land-Use Systems on Soil Physicochemical Properties and Macrofauna Abundance in the Humid Tropics of Cameroon by Lawrence Tatanah Nanganoa, Justin Nambangia Okolle, Valentine Missi, Jacques Roberto Tueche, Lewis Dopgima Levai, Jetro Nkengafac Njukeng

“…The land-use types included secondary forest (SF), oil palm plantation (PP), banana plantation (BP), sugarcane plantation (SP), and rubber plantation (RP). …”
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Efficient Feature Selection and Hyperparameter Tuning for Improved Speech Signal-Based Parkinson’s Disease Diagnosis via Machine Learning Techniques by Deepak Painuli, Suyash Bhardwaj, Utku Kose

“…This study investigates 12 machine learning models—logistic regression (LR), support vector machine (SVM, linear/RBF), K-nearest neighbor (KNN), Naïve bayes (NB), decision tree (DT), random forest (RF), extra trees (ET), gradient boosting (GbBoost), extreme gradient boosting (XgBoost), adaboost, and multi-layer perceptron (MLP)—to develop a robust ML model capable of reliably identifying PD cases. …”
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Classification of RTV-coated porcelain insulator condition under different profiles and levels of pollution by Ali Ahmed Salem, Samir Ahmed Al-Gailani, Abdulrahman Ahmed Ghaleb Amer, Mohammad Alsharef, Mohit Bajaj, Ievgen Zaitsev, Razali Ngah, Sherif S. M. Ghoneim

“…Then, based on the proposed criteria, the performances of the Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Multi-layer Perceptron (MLP) have been trained and compared to classify polluted insulator conditions with and without coating. …”
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ViT-ISRGAN: A High-Quality Super-Resolution Reconstruction Method for Multispectral Remote Sensing Images by Yifeng Yang, Hengqian Zhao, Xiadan Huangfu, Zihan Li, Pan Wang

“…The ViT-ISRGAN model focuses on reconstructing four types of typical ground objects based on Sentinel-2 images: urban, water, farmland, and forest. Results indicate that the ViT-ISRGAN model excels in capturing texture details and color restoration, effectively extracting spectral and texture information from multispectral remote sensing images across various scenes. …”
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Central Asia Cold Case: Siberian Pine Fingers New Suspects in Growth Decline CA 1700 CE by David M. Meko, Dina F. Zhirnova, Liliana V. Belokopytova, Yulia A. Kholdaenko, Elena A. Babushkina, Nariman B. Mapitov, Eugene A. Vaganov

“…Conifer tree rings and forest productivity recorded this event across all of Altai–Sayan region.…”
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The Effects of Selective Muscle Weakness on Muscle Coordination in the Human Arm by Jinsook Roh, Randall F. Beer, Andrew Lai, Monica Rho, Kristopher R. Karvelas, Antoun M. Nader, Mark C. Kendall, William Z. Rymer

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Divergence of alpine plant populations of three Gentianaceae species in the Qinling sky Island by Peng-Cheng Fu, Bing-Jie Mo, He-Xin Wan, Shu-Wen Yang, Rui Xing, Shan-Shan Sun

“…The redundancy and gradient forest analyses revealed that several temperature- and precipitation-related variables mainly contributed to shaping the genetic differentiation among the Qinling populations and others, indicating that the three species exhibited a similar pattern of adaptations to local environments. …”
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Sources and Radiative Impact of Carbonaceous Aerosols Using Four Years Ground-Based Measurements over the Central Himalayas by Priyanka Srivastava, Manish Naja, T. R. Seshadri

“…The role of crop residue burning in northern India and forest fires is shown to be dominant in spring while local heating-purpose emissions dominate in winter. …”
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Application of Nighttime Light Data Simulation Based on Multi-Indicator System and Machine Learning Model in Predicting Potentially Suitable Economic Development Areas: A Case Stud... by Guangpeng Zhang, Li Zhang, Yiyang Chen, Meng Chen, Jingjing Tian, Yin Wu

“…Four tree-based ensemble learning models—Random Forest (RF), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Categorical Boosting (CatBoost)—were employed to predict potential urban economic development suitability zones and their suitability intensity. …”
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Statistical analysis of heat waves in the southern slopes of Alborz by Zienab Hosinpoor, AliAkbar Shamsipour, Mostafa Karimi, Faramarz khoshakhlagh

“…Heat waves are important phenomena in Iran, And its upsurge in recent years seems to have a high upside trend.This climate has a negative impact on agriculture, forest fire and forestry, water resources, energy use and human health.The purpose of the research is to explain the frequency, time distribution, continuity of thermal waves, and the identification of its occurrence in the southern foothills of central Alborz.Therefore, using the statistical methods and maximum daily temperature data of Tehran (Mehrabad), Qazvin and Semnan stations for the statistical period of 30 years (1966-2016), the mentioned characteristics were extracted.In the first step, the nonparametric method of Kendal was used to understand the variability and awareness of the monthly trend of maximum temperatures in the study period.In order to determine the severity, duration and frequency of heat wave events, the percentiles (95.98) and normalized temperature deviation (NTD) were used.The results of the study showed that the frequency of short-wave heat waves was higher.Most frequencies are related to 2-day waves, respectively, and Tehran (Mehrabad), Semnan and Qazvin stations are more frequent.The highest frequency of annual events was detected at stations in Tehran (11 waves in 2010), in Semnan (9 waves in 2015) and Qazvin (7 waves in 2015), respectively.The highest frequency of monthly heat wave events was recorded in June and September.The highest continuation (15 days) was obtained in March 2008 with the percentile method at Mehrabad station.In the normalized deviation method, the temperature was calculated as a warm wave (12 days) in 2008.The highest annual frequency of heat loss occurred in all three stations in 2015.The evolution of the process indicated an increase in the incidence of thermal waves in the cold period of the year But in other chapters, no meaningful changes were made.As it says, the decline in cold winter temperatures is on the southern slopes of Alborz.The results of the two methods showed that in the normalized deviation of the temperature, the number of thermal waves more than the percentile method was recorded, but in the percentile method, the thermal wave was more prominent in the cold period of the year.…”
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Drought resistance of introgressive spring common wheat lines with genetic material of tall wheatgrass by L. Ya. Plotnikova, A. T. Sagendykova, S. P. Kuzmina

“…The introgressive lines of spring common wheat with T. ponticum genetic material and standard cultivars were studied in the field in the southern forest-steppe of Western Siberia using generally recognized methods. …”
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The process and logical mechanism of agricultural production space contraction in mountainous areas based on actor-network theory：A case study of Lishi Village in Longde County, Ni... by CHEN Kunqiu, CHEN Yunya, LIANG Yajia, ZHENG Yuhan

“…[Results] The study found that: (1) The translation of actor networks at different stages, the entry and exit of heterogeneous actors within the networks, and the transformation of the actor networks goals comprehensively contributed to the contraction of agricultural production space through the combined effects of human and non-human actors. (2) During the transformation of the actor network in Lishi Village, the key actor changed from the local government to the young labor force, and the obligatory point of passage (OPP) changed from “returning farmland to forest and grassland” to “developing specialty farming to maximize economic income”. (3) The agricultural production space in Lishi Village has gone through two stages: explicit contraction under the ecological objective and implicit contraction under the economic objective. (4) The contraction of agricultural production space in mountainous areas follows the mechanisms of environmental logic, policy-driven logic, and multi-subject logic. …”
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Carbon Sink Estimation of Mangrove Vegetation Using Remote Sensing in Segara Anakan, Cilacap by Zahra Safira Aulia, Rizqi Rizaldi Hidayat, Amron Amron

“…Segara Anakan, the largest mangrove forest in Java Island, has the highest potential as a carbon sink in the tropics. …”
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Water Quality Variations in the Lower Yangtze River Based on GA-RF Model From GF-1, Landsat-8, and Sentinel-2 Images by Wentao Hu, Shuanggen Jin, Yuanyuan Zhang

“…In this article, GF-1, Landsat-8, and Sentinel-2 data are jointly used to develop a genetic algorithm-random forest (GA-RF) water quality inversion model weighted by the entropy method. …”
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Oilpalm-RTMDet: An lightweight oil palm detector base on RTMDet by Jirong Ding, Runlian Huang, Yehua Liang, Xin Weng, Jianjun Chen, Haotian You

“…It can not only provide accurate basic data for oil palm tree counting, yield and carbon storage estimation, but also provide technical guidance for other forest types, such as eucalyptus and pine, and single tree detection and segmentation.…”
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