Mapping soil compaction using indicator kriging in Santa Fe province, Argentina by Carlos Agustín Alesso, María Eugenia Carrizo, Silvia del Carmen Imhoff

“…Soil compaction is a complex physical process that affects the crop performance by limiting the expansion of the roots and the reduction of water and nutrients uptake from soil. …”
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Radical and Not So Radical Transgressions: Invading Backstage Domains by Lada Čale Feldman

“…Featuring as one of the privileged metaphors in humanities and social sciences, theatre provides primarily an image of a circumscribed space whose spatial syntax and modes of human engagement take place within and with respect to the larger space of the city, the world, and, as in Calderon’s Gran teatro del mundo, the universe. …”
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Identification of Sudden Stiffness Change in the Acceleration Response of a Nonlinear Hysteretic Structure by Sheng-Lan Ma, Shao-Fei Jiang, Chen Wu, Si-Yao Wu

“…Parameters are identified within 14% of the actual as-modeled value using noisy simulation-derived structural responses. …”
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Machine learning optimization of microwave-assisted extraction of phenolics and tannins from pomegranate peel by Fatemeh Mobasheri, Mostafa Khajeh, Mansour Ghaffari-Moghaddam, Jamshid Piri, Mousa Bohlooli

“…The LSBoost/RF model demonstrated superior performance, achieving correlation coefficients (R²) of 0.9998, 0.9018, and 0.9269 for total phenolic, total tannin, and DPPH %, respectively. …”
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FR-CapsNet: Enhancing Low-Resolution Image Classification via Frequency Routed Capsules by Hasindu Dewasurendra, Kunmin Yeo, Nhan Thi Cao, Taejoon Kim

“…Though VLR images lose fine grained features, they retain high-level features captured by the low-frequency components. …”
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Machine Learning in Sensory Analysis of Mead—A Case Study: Ensembles of Classifiers by Krzysztof Przybył, Daria Cicha-Wojciechowicz, Natalia Drabińska, Małgorzata Anna Majcher

“…In the first stage, a cluster map analysis was conducted, allowing for the exploratory identification of the most characteristic features of mead. Based on this, k-means clustering was performed to evaluate how well the identified sensory features align with logically consistent groups of observations. …”
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Comparative analysis of the syncytiotrophoblast in placenta tissue and trophoblast organoids using snRNA sequencing by Madeline M Keenen, Liheng Yang, Huan Liang, Veronica J Farmer, Rizban E Worota, Rohit Singh, Amy S Gladfelter, Carolyn B Coyne

“…Comparing STB expression in first trimester, term, and TOs revealed shared features but context-dependent variability. These findings establish TOs as a robust platform to model STB differentiation and nuclear heterogeneity, providing insight into the regulatory networks that shape placental development and function.…”
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Biomimetic ECM nerve guidance conduit with dynamic 3D interconnected porous network and sustained IGF-1 delivery for enhanced peripheral nerve regeneration and immune modulation by Teng Wan, Qi-Cheng Li, Feng-Shi Zhang, Xiao-Meng Zhang, Na Han, Pei-Xun Zhang

“…The biomimetic ECM NGCs comprising a 3D interconnected porous network in a 10-mm sciatic nerve defect rat model sustain IGF-1 delivery, promoting early infiltration of macrophages and polarisation towards M2-type macrophages. …”
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A predictive framework using advanced machine learning approaches for measuring and analyzing the impact of synthetic agrochemicals on human health by Sahezpreet Singh, Puneet Kaur, Inderdeep Kaur, Gurpreet Singh, Satinder Kaur, Parminder Kaur

“…Machine learning (ML) models such as Random Forest, LightGBM, and CatBoost were employed alongside feature selection methods like mutual information gain (MI) and Recursive Feature Elimination (RFE). …”
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Deep Learning Network Selection and Optimized Information Fusion for Enhanced COVID-19 Detection: A Literature Review by Olga Adriana Caliman Sturdza, Florin Filip, Monica Terteliu Baitan, Mihai Dimian

“…Individual ResNet architectures, along with CNN models, demonstrate strong diagnostic performance through the transfer protocol; however, ViTs provide better performance, with improved readability and reduced data requirements. …”
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Improved Absorbing Aerosol Index Results for EMI on Board Atmospheric Environment Monitoring Satellite by Fuying Tang, Fuqi Si, Ang Li, Haijin Zhou, Minjie Zhao, Yuhan Luo, Yuanyuan Qian

“…Appropriate correction coefficients were determined for each ground pixel in the EMI reflectances for the ultraviolet visible through a comparison with reflectances calculated using the radiative transfer model, and correction coefficients were applied to AAI results to remove the structural features induced by viewing geometries and radiometric calibration problems. …”
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Identification of Diagnostic Biomarkers for Colorectal Polyps Based on Noninvasive Urinary Metabolite Screening and Construction of a Nomogram by Yang Xie, Yiyi Jin, Zide Liu, Jun Li, Qing Tao, Yonghui Wu, Youxiang Chen, Chunyan Zeng

“…Metabolite screening was performed using weighted gene coexpression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO), and support vector machine‐recursive feature elimination (SVM‐RFE). …”
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Towards interpretable drug interaction prediction via dual-stage attention and Bayesian calibration with active learning by Rongpei Li, Yufang Zhang, Heqi Sun, Shenggeng Lin, Guihua Jia, Yitian Fang, Chen Zhang, Xiaotong Song, Jianwei Zhao, Lyubin Hu, Yajing Yuan, Xueying Mao, Jiayi Li, Aman Kaushik, Dandan An, Dongqing Wei

“…The model was validated using data from FAERS, DrugBank, and STRING databases, with comprehensive evaluation on both computational performance and biological interpretability. …”
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Mannose-B from Codonopsis pilosula modulates LAMB1 expression to enhance trophoblast function and alleviate subchorionic hematoma by Qian Sun, Yuan Gao, Kadirya Asan, Jing Ji, Jinjin Xu, Xiaoyan Wu, Jie Ren, Wen Feng, Mengwei Song, Sen Wang, Boyu Zhang, Ying Zhou, Conghui Han, Shun Liu, Wen Yang

“…In vitro, HTR-8/Svneo cells were used to assess proliferation, migration, and invasion through CCK8, Transwell, and cell migration assays. A SCH rat model was established to evaluate changes in coagulation parameters, litter size, fetal viability, and fetal and placental weights. …”
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Évaluation comparative des algorithmes d'apprentissage automatique pour la classification des types de sols à partir de caractéristiques physico-chimiques : application de Random F... by Mamadou Ndiaye, René Boissy, Mbagnick Faye, N’kpomé Styvince Romaric Kouao

“…A set of 1000 random samples was used for training and testing, with cross-validation and confusion matrices to assess performance. The results show that SVM achieves the best performance with an overall accuracy of 98.85%, followed by Random Forest (97.13%) and KNN (95.40%), while XGBoost shows an accuracy of 93.68%. …”
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BibMon: An open source Python package for process monitoring, soft sensing, and fault diagnosis by Afrânio Melo, Tiago S.M. Lemos, Rafael M. Soares, Deris Spina, Nayher Clavijo, Luiz Felipe de O. Campos, Maurício Melo Câmara, Thiago Feital, Thiago K. Anzai, Pedro H. Thompson, Fábio C. Diehl, José Carlos Pinto

“…Key features include regression and reconstruction models, preprocessing pipelines, alarms, and visualization through control charts and diagnostic maps. …”
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Short-term ozone exposure on stroke mortality and mitigation by greenness in rural and urban areas of Shandong Province, China by Ke Zhao, Fenfen He, Bingyin Zhang, Chengrong Liu, Yang Hu, Yilin Dong, Peiyao Zhang, Chao Liu, Jing Wei, Zilong Lu, Xiaolei Guo, Qing Huang, Xianjie Jia, Jing Mi

“…Furthermore, a meta-regression model was utilized to assess the moderating effects of county-level features. …”
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Influence of TNF and IL17 Gene Polymorphisms on the Spondyloarthritis Immunopathogenesis, Regardless of HLA-B27, in a Brazilian Population by Marco A. Rocha Loures, Luciana C. Macedo, Denise M. Reis, Camila F. Oliveira, Jean L. Meneguetti, Gabriela F. Martines, Janisleya S. F. Neves, Eliana de Souza, Ana M. Sell, Jeane E. L. Visentainer

“…Spondyloarthritis (SpA) represents a heterogeneous group of immune-mediated inflammatory diseases that have overlapping clinical features, genetic predisposition, and pathogenic mechanisms. …”
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Disulfidptosis-based molecular clustering and prognostic signatures predict patient survival and the immune landscape in patients with colon cancer by Liang Wen, Yongli Ma, Jinghui Li, Dengzhuo Chen, Chengzhi Huang, Ping Wang, Suqi Wen, Gexin Wen, Jizhen Guo, Guosheng Zhang, Junjiang Wang, Xueqing Yao

“…Conclusion The prognostic features based on 10 PRDEGs performed well in predicting survival, TME status, and response to immunity in COAD patients, helping provide personalized immunotherapy strategies for patients.…”
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Comprehensive evaluation of the vector magnetic field data from Macau Science Satellite-1A by XinYi Rang, Chao Xiong, YuYang Huang, ChunYu Xu, FengJue Wang, BoHao Qian, Fan Yin, SiShan Song, Keke Zhang, PengFei Liu

“…The comprehensive evaluations performed within this study demonstrate that the MSS-1A provides high-quality magnetic field data reaching the level of the Swarm satellite, which enables a deeper understanding of the modeling of Earth’s magnetic field as well as monitoring of the magnetic environment.…”
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