Monitoring Coastal Water Turbidity Using Sentinel2—A Case Study in Los Angeles by Yuwei Kong, Karina Jimenez, Christine M. Lee, Sophia Winter, Jasmine Summers-Evans, Albert Cao, Massimiliano Menczer, Rachel Han, Cade Mills, Savannah McCarthy, Kierstin Blatzheim, Jennifer A. Jay

“…Machine learning models were assessed for predictive accuracy, with the random forest model achieving the highest performance (R² = 0.632), indicating its robustness in modeling complex turbidity patterns. …”
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Analysis on the Spatio-Temporal Characteristics of Urban Expansion and the Complex Driving Mechanism: Taking the Pearl River Delta Urban Agglomeration as a Case by Luo Liu, Jianmei Liu, Zhenjie Liu, Xuliang Xu, Binwu Wang

“…From 2000 to 2015, the most important source of urban land expansion was farmland, followed by forest land. Meanwhile, the decline in the proportion of outlying expansion type indicated that the urban land has gradually become more compact. (2) From 2000 to 2015, the socio-economic factors had a greater effect on UEI than natural factors. …”
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Structure, Mechanical Performance, and Dimensional Stability of Radiata Pine (Pinus radiata D. Don) Scrimbers by Jinguang Wei, Fei Rao, Yuxiang Huang, Yahui Zhang, Yue Qi, Wenji Yu, Chung-Yun Hse

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Assessment of Economic Management of Land Resources to Enhance Food Security by Dinara Tleshpayeva, Natalia Bondarenko, Mikhail Leontev, Galina Mashentseva, Julia Plaksa, Andrey Zharov, Diana Stepanova, Agzhan Karbozova

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High-quality DNA extraction for Desmodium gangeticum: A medicinal shrub of Shivalik Himalayas by Shiwani Singh, Maneesh S. Bhandari, Neeraj Dwivedi

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Humification and Humic Acid Composition of Suspended Soil in Oligotrophous Environments in South Vietnam by E. V. Abakumov, O. A. Rodina, A. K. Eskov

“…Suspended soils were shown to contain higher total nitrogen, phosphorus, and potassium contents than the forest soil, but the moisture content in suspended soils was significantly lower. …”
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Vegetation optical depth as a key predictor for fire risk escalation by Dinuka Kankanige, Yi Y. Liu, Ashish Sharma

“…This study investigates whether vegetation parameters can be utilized in fire risk prediction in the absence of fire weather information, and how they can be utilized to effectively reflect on the fire risk increment from a minimum point, which is the concern in bushfire occurrence. Using the McArthur Forest Fire Danger Index (FFDI) as a measure of fire danger, a clear association with the satellite-observed vegetation optical depth (VOD) was noted for segments illustrating risk increment. …”
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Parametric Design and Mechanical Characterization of a Selective Laser Sintering Additively Manufactured Biomimetic Ribbed Dome Inspired by the Chorion of Lepidopteran Eggs by Alexandros Efstathiadis, Ioanna Symeonidou, Emmanouil K. Tzimtzimis, Dimitrios Avtzis, Konstantinos Tsongas, Dimitrios Tzetzis

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Identification of Plasma Proteins Associated with Alzheimer's Disease Using Feature Selection Techniques and Machine Learning Algorithms by Zakaria Mokadem, Mohamed Djerioui, Bilal Attallah, Youcef Brik

“…The SBFS technique generated all possible combinations of protein groups from the 146 proteins, which were then trained and tested using five machine learning models: Decision Tree, Random Forest, Extremely Randomized Trees, Extreme Gradient Boosting, and Adaptive Boosting. …”
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Comparison of Conservation Strategies for California Channel Island Oak (Quercus tomentella) Using Climate Suitability Predicted From Genomic Data by Alayna Mead, Sorel Fitz‐Gibbon, John Knapp, Victoria L. Sork

“…We compare the impact of these approaches on predicted maladaptation to climate using Gradient Forest. We also introduce a climate suitability index to identify optimal pairs of seed sources and planting sites for approaches involving assisted gene flow. …”
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Machine learning-based prediction of the mechanical properties of β titanium shape memory alloys by Naoki Nohira, Taichi Ichisawa, Masaki Tahara, Itsuo Kumazawa, Hideki Hosoda

“…Four ML algorithms—Linear Regression (LIN), Support Vector Regression (SVR), Random Forest Regression (RFR), and Gradient Boosting Regression (GBR)—were employed and evaluated using metrics like mean absolute error (MAE), mean squared error (MSE), and coefficient of determination (R2). …”
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Wheat landraces as sources of high grain quality and nutritional properties by V. P. Shamanin, I. V. Pototskaya, S. A. Esse, M. S. Gladkih, S. S. Shepelev, E. V. Zuev, N. A. Vinichenko, H. Koksel, A. I. Morgounov

“…Field and laboratory research were conducted in the experimental field of Omsk State Agrarian University under the conditions of the southern forest-steppe of Western Siberia in 2020–2021. Sowing was carried out on fallow on conventional sowing dates. …”
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Variations in carbon stocks across traditional and improved agroforestry in reference to agroforestry and households’ characteristics in Southeastern Ethiopia by Boja Tilinti, Mesele Negash, Zebene Asfaw, Teshale Woldeamanuel

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Do meteorological variables impact air quality differently across urbanization gradients? A case study of Kaohsiung, Taiwan, China by Bohan Wu, Shuang Zhao, Yuxiang Liu, Chunyan Zhang

“…The results revealed that: (1) Suburban areas exhibited significantly better air quality than urban and near-urban areas, with annual AQI values of 59.58 in Meinong (outskirts), 67.86 in Renwu (suburbs area), and 76.73 in Qianjin (urban area), showing a progressive improvement in air quality from urban to suburban areas, primarily due to lower levels of urbanization and abundant forest resources; (2) Temperature and relative humidity emerged as key meteorological variables influencing AQI, with Granger causality tests indicating that temperature significantly affects AQI, especially in urban areas. …”
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Ethnobotanical Study on Wild Edible Plants in Metema District, Amhara Regional State, Ethiopia by Getinet Masresha, Yirgalem Melkamu, Getnet Chekole Walle

“…For sustainable utilization, conservation, value addition, and market linkage practices shall be strengthened to improve the livelihoods of local people and sustainable forest management.…”
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Evaluation of the Impact of Morphological Differences on Scale Effects in Green Tide Area Estimation by Ke Wu, Tao Xie, Jian Li, Chao Wang, Xuehong Zhang, Hui Liu, Shuying Bai

“…Machine learning models, including Extra Trees, LightGBM, and Random Forest, among others, classified medium and large patches into striped and non-striped types, with Extra Trees achieving outstanding performance (accuracy: 0.9844, kappa: 0.9629, F1-score: 0.9844, MIoU: 0.9637). …”
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Identification of ubiquitination-related key biomarkers and immune infiltration in Crohn’s disease by bioinformatics analysis and machine learning by Wei Chen, Zeyan Xu, Haitao Sun, Wen Feng, Zhenhua Huang

“…Key genes were selected by combining hub genes from the protein-protein interaction (PPI) network with feature genes identified by Lasso and Random Forest (RF) algorithms. Additionally, the correlation between key genes and immune infiltration was assessed, and Gene Set Enrichment Analysis (GSEA) of key genes was conducted. …”
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Rockwood Clinical Frailty Scale as a predictor of adverse outcomes among older adults undergoing aortic valve replacement: a protocol for a systematic review by Rose Galvin, Ahmed Gabr, Catherine Peters, Margaret O'Connor, Aoife Leahy, Elaine Shanahan, Tadhg Prendiville, Laura Quinlan, Anastasia Saleh, Ivan Casserly

“…Data will be plotted on forest plots where applicable. The quality of the evidence will be determined using the Grading of Recommendations, Assessment, Development and Evaluation tool.Ethics and dissemination Ethical approval is not required for this study as no primary data will be collected. …”
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Land use and land cover classification for change detection studies using convolutional neural network by V. Pushpalatha, P.B. Mallikarjuna, H.N. Mahendra, S. Rama Subramoniam, S. Mallikarjunaswamy

“…Further, change detection analysis has been carried out using classified maps and the results show that built-up areas increased by 8.34 sq. km (0.83%), agricultural land expanded by 2.21 sq. km (0.23%), and water bodies grew by 3.31 sq. km (0.35%). Conversely, forest cover declined by 1.49 sq. km (0.15%), and other land uses reduced by 11.93 sq. km (1.22%) over the decade.…”
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Machine learning-enhanced gesture recognition through impedance signal analysis by Huynh Hoang Nhut, Diep Quoc Tuan Nguyen, Dinh Minh Quan Cao, Tran Anh Tu, Dang Nguyen Chau, Phan Thien Luan, Tran Trung Nghia, Ching Congo Tak Shing

“…The machine learning model using the K-Nearest Neighbors (KNN), Gradient Boosting Machine (GBM), Naive Bayes (NB), Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM) algorithms demonstrated notable precision in performance evaluations. …”
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