Sources of characters useful for breeding in hulless barley by N. V. Tetyannikov, N. A. Bome

“…Their genotypes were evaluated in the northern forest steppe environments of Tyumen Province (2015– 2017) according to the guidelines developed by the N.I. …”
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Sorghum yield prediction based on remote sensing and machine learning in conflict affected South Sudan by John Karongo, Joseph Ivivi Mwaniki, John Ndiritu, Victor Mokaya

“…We use five Machine Learning (ML) techniques, including Random Forest (RF), Decision Tree (DT), Extreme Gradient Boosting (XGboost), Support Vector Machine (SVM) and Artificial Neural Network (ANN) to predict 2021 end-of-season sorghum yield in conflict affected Upper Nile and Western Bahr El Gazal states. …”
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Simulated wind erosion and local dust deposition affect soil micro-food web by changing resource availability by Cancan Zhao, Yujie Li, Zeli Zhou, Rongrong Wu, Mengfei Su, Hongquan Song

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Improving the perceived contribution of sustainable tourism through the residents’ empowerment and support for tourism development: A different age group context by Lorena Bašan, Ivana Perušina, Marija Ham

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Evaluating regional sustainable energy potential through hierarchical clustering and machine learning by Selen Avcı Azkeskin, Zerrin Aladağ

“…To validate the clustering results, supervised classification methods—including K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost)—are utilized, alongside ensemble models based on RF and XGBoost. …”
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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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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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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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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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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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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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Assessing the Inter-Rater and Inter-Trial Reliability of the NeurOptics Pupillary Light Response-3000 Pupillometer by Deborah A Jehu, Lori A Bolgla, Samantha Armas, Forest Dutton

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Digital Twin Framework Using Real-Time Asset Tracking for Smart Flexible Manufacturing System by Asif Ullah, Muhammad Younas, Mohd Shahneel Saharudin

“…The algorithms include Support Vector Machines (SVM), Random Forests (RF), Decision Trees, K-Nearest Neighbors (KNN) and Convolutional Neural Networks (CNN). …”
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Contribution of domestic animals’ feces to the occurrence of diarrhoea among children aged 6–48 months in Sidama region, Ethiopia: a laboratory-based matched case-control study by Argaw Ambelu, Gorfu Geremew Gunsa, Alemayehu Haddis

“…The diarrhoea risk factors were identified using conditional logistic regressions and the random forest method using R.4.3.2.Results Of the faecal specimens diagnosed, 250 (64.1%) tested positive for one or more pathogens. …”
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Sierra Espuña (Librillos, 2023) by Miguel Ángel González Espinosa

“…It presents a green mantle composed of a pine forest as a result of the repopulation undertaken by Ricardo Codorníu more than a century ago, with species such as Aleppo pine, maritime pine, black pine, laricio pine and other pine varieties. …”
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Machine learning algorithms for predicting delayed hyponatremia after transsphenoidal surgery for patients with pituitary adenoma by Kunzhe Lin, Jianping Zhang, Lin Zhao, Liangfeng Wei, Shousen Wang

“…In the training dataset, the best predictive performance was observed for XGBoost (area under the ROC curve; AUC = 0.821), followed by Random Forest (AUC = 0.8), Logistic Regression (AUC = 0.793), Support Vector Machine (AUC = 0.776), naïve Bayes (AUC = 0.774), K-Nearest Neighbors (AUC = 0.742), and Decision Tree (AUC = 0.717). …”
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Evaluation of extracts from Phyllostachys makinoi for their antibacterial and accelerated wound healing potential by Te-Hua Liu, Ju-Yun Wu, Meng-Chun Cheng, Bang-Yuan Chen, Tsung-Yu Tsai

“…Abstract Phyllostachys makinoi, an endemic bamboo species in Taiwan, is underutilized, despite its rich forest resources. Known for its antioxidant, anti-inflammatory, and antibacterial properties, this study explores the antimicrobial, anti-inflammatory, and wound-healing activities of P. makinoi extracts. …”
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