Enhancing proximal and remote sensing of soil organic carbon: A local modelling approach guided by spectral and spatial similarities by Qi Sun, Pu Shi

“…As a result, the optimal modelling strategy, with partial least squares regression (PLSR) as the local fitting algorithm, consistently produced superior performances (R2: 0.66 to 0.82) than the conventional global modelling approach (R2: 0.59 to 0.77) for all three data types. …”
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Integration of multi-temporal SAR data and robust machine learning models for improvement of flood susceptibility assessment in the southwest coast of India by Pankaj Prasad, Sourav Mandal, Sahil Sandeep Naik, Victor Joseph Loveson, Simanku Borah, Priyankar Chandra, Karthik Sudheer

“…These flood locations are correlated with sixteen flood conditioning geo-environmental variables. The Boruta algorithm has been applied to determine the importance of each flood conditioning parameter. …”
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An Optimized Multi-Stage Framework for Soil Organic Carbon Estimation in Citrus Orchards Based on FTIR Spectroscopy and Hybrid Machine Learning Integration by Yingying Wei, Xiaoxiang Mo, Shengxin Yu, Saisai Wu, He Chen, Yuanyuan Qin, Zhikang Zeng

“…The proposed framework includes (1) FTIR spectral acquisition; (2) a comparative evaluation of nine spectral preprocessing techniques; (3) dimensionality reduction via three representative feature selection algorithms, namely the Successive Projections Algorithm (SPA), Competitive Adaptive Reweighted Sampling (CARS), and Principal Component Analysis (PCA); (4) regression modeling using six machine learning algorithms, namely the Random Forest (RF), Support Vector Regression (SVR), Gray Wolf Optimized SVR (SVR-GWO), Partial Least Squares Regression (PLSR), Principal Component Regression (PCR), and the Back-propagation Neural Network (BPNN); and (5) comprehensive performance assessments and the identification of the optimal modeling pathway. …”
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Harnessing Artificial Intelligence and Innovative Vaccines for Mpox Diagnosis and Control: A Comprehensive Narrative Review by Excel Onajite Ernest-Okonofua, Zainab Abdullahi Zubairu, Malik Olatunde Oduoye, Maryam Tariq, Syed Muhammad, Zainab Siddiqua, Monica Vuyyuru, Benjamin Wafula, Riaz Akhtar, Abdulbasit Fasasi, Samuel Chinonso Ubechu, Bakare Sikiru Olayinka

“…Future directions should be focused on healthcare professionals to establish the validity and reliability of the models, a measure of the algorithm’s robustness, and the continuous auditing of AI systems.…”
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Rapid discrimination and quantification of chemotypes in Perillae folium using FT-NIR spectroscopy and GC–MS combined with chemometrics by Dai-xin Yu, Cheng Qu, Jia-yi Xu, Jia-yu Lu, Di-di Wu, Qi-nan Wu

“…Based on FT-NIR data, different chemotypes were accurately classified. The random forest algorithm achieved >90 % accuracy in chemotype classification. …”
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Comparative Quantitative and Discriminant Analysis of Wheat Flour with Different Levels of Chemical Azodicarbonamide Using NIR Spectroscopy and Hyperspectral Imaging by Hongju He, Yuling Wang, Shengqi Jiang, Jie Zhang, Jicai Bi, Hong Qiao, Leiqing Pan, Xingqi Ou

“…The raw spectra were preprocessed using 14 methods and then mined by the partial least squares (PLS) algorithm to fit ADA levels using different numbers of WF samples for training and validation in five datasets (N_Training/_Validation = 189/21, 168/42, 147/63, 126/84, 105/105), yielding better abilities of NIR Savitzky–Golay 1st derivative (SG1D) spectra-based PLS models and raw HSI spectra-based PLS models in quantifying ADA with higher determination coefficients and lower root-mean-square errors in validation (R²_V & RMSEV), as well as establishing 100% accuracy in PLS discriminant analysis (PLS-DA) models for identifying excessive ADA-contained WF in each dataset. …”
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A Novel Synchronization-Based Approach for Functional Connectivity Analysis by Angela Lombardi, Sabina Tangaro, Roberto Bellotti, Alessandro Bertolino, Giuseppe Blasi, Giulio Pergola, Paolo Taurisano, Cataldo Guaragnella

“…Popular approaches for quantifying functional coupling between fMRI time series are linear zero-lag correlation methods; however, they might reveal only partial aspects of the functional links between brain areas. …”
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Enhancing Laser-Induced Breakdown Spectroscopy Quantification Through Minimum Redundancy and Maximum Relevance-Based Feature Selection by Manping Wang, Yang Lu, Man Liu, Fuhui Cui, Rongke Gao, Feifei Wang, Xiaozhe Chen, Liandong Yu

“…This study validates the effectiveness of the mRMR algorithm for LIBS feature extraction and highlights the potential of feature selection techniques to enhance predictive accuracy. …”
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A deep learning approach for SMAP soil moisture downscaling informed by thermal inertia theory by Mengyuan Xu, Haoxuan Yang, Annan Hu, Lee Heng, Linyi Li, Ning Yao, Gang Liu

“…In this study, we attempt to use an SM downscaling approach that integrates thermal inertia (TI) theory with the DenseNet deep network algorithm. This approach provides partial interpretability of the physical mechanisms while utilizing DenseNet’s superior nonlinear learning ability and feature reuse capability for downscaling the Soil Moisture Active Passive (SMAP) satellite product, generating daily 1 km × 1 km SM. …”
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Research on the Inversion Method of Dust Content on Mining Area Plant Canopies Based on UAV-Borne VNIR Hyperspectral Data by Yibo Zhao, Shaogang Lei, Xiaotong Han, Yufan Xu, Jianzhu Li, Yating Duan, Shengya Sun

“…Various regression models, including extreme learning machine (ELM), random forest (RF), partial least squares regression (PLSR), and support vector machine (SVM), were utilized to establish dust inversion models. …”
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Management and edaphoclimatic factors that determine soybean top-performing farmers in Brazil by Victor Delino Barasuol Scarton, Ivan Ricardo Carvalho, Christiane de Fátima Colet, Leonardo Cesar Pradebon, Willyan Júnior Adorian Bandeira, Jaqueline Piesanti Sangiovo, Murilo Vieira Loro, José Antonio Gonzalez da Silva

“…Grain yield was analyzed using centered means with partial least squares, followed by linear regression models and t-tests (p < 0.05). …”
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A Gradient Boosting Crash Prediction Approach for Highway-Rail Grade Crossing Crash Analysis by Pan Lu, Zijian Zheng, Yihao Ren, Xiaoyi Zhou, Amin Keramati, Denver Tolliver, Ying Huang

“…Moreover, contributors’ importance and partial-dependent relations are generated to further understand the relationship of identified contributors and HRGC crash likelihood to concur “black box” issues that most machine learning methods face. …”
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A pig behavior-tracking method based on a multi-channel high-efficiency attention mechanism by Qifeng Li, Zhenyuan Zhuo, Ronghua Gao, Rong Wang, Na Zhang, Yan Shi, Tonghui Wu, Weihong Ma

“…The tracking component used the Bytetrack algorithm to accurately track the movement trajectories of individual pigs. …”
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A Detection Line Counting Method Based on Multi-Target Detection and Tracking for Precision Rearing and High-Quality Breeding of Young Silkworm (<i>Bombyx mori</i>) by Zhenghao Li, Hao Chang, Mingrui Shang, Zhanhua Song, Fuyang Tian, Fade Li, Guizheng Zhang, Tingju Sun, Yinfa Yan, Mochen Liu

“…The experimental results demonstrate that the recall, precision, and average precision (<i>AP</i>_50:95) of the improved detection algorithm are 87.9%, 91.3% and 72.7%, respectively. …”
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A Study on Canopy Volume Measurement Model for Fruit Tree Application Based on LiDAR Point Cloud by Na Guo, Ning Xu, Jianming Kang, Guohai Zhang, Qingshan Meng, Mengmeng Niu, Wenxuan Wu, Xingguo Zhang

“…In the domain of point cloud feature extraction, an improved Alpha Shape algorithm is proposed for extracting point cloud contours. …”
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Prediction of the Quality of Anxi Tieguanyin Based on Hyperspectral Detection Technology by Tao Wang, Yongkuai Chen, Yuyan Huang, Chengxu Zheng, Shuilan Liao, Liangde Xiao, Jian Zhao

“…The characteristic wavelengths were extracted via principal component analysis (PCA), competitive adaptive reweighted sampling (CARS), and the successive projection algorithm (SPA). The contents of free amino acid and tea polyphenol in Tieguanyin tea were predicted by the back propagation (BP) neural network, partial least squares regression (PLSR), random forest (RF), and support vector machine (SVM). …”
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Rapid Recognition of Geoherbalism and Authenticity of a Chinese Herb by Data Fusion of Near-Infrared Spectroscopy (NIR) and Mid-Infrared (MIR) Spectroscopy Combined with Chemometri... by Haiyan Fu, Qiong Shi, Liuna Wei, Lu Xu, Xiaoming Guo, Ou Hu, Wei Lan, Shunping Xie, Tianming Yang

“…In this paper, a supervised pattern recognition method based on the PLSDA algorithm by NIR and the NIR-MIR fusion spectra has been established to identify geoherbalism of Angelica dahurica from different regions and authenticity of Corydalis yanhusuo W. …”
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An artificial intelligence and machine learning-driven CFD simulation for optimizing thermal performance of blood-integrated ternary nano-fluid by Mohib Hussain, Du Lin, Hassan Waqas, Qasem M. Al-Mdallal

“…An AI-integrated, the Levenberg-Marquardt algorithm is employed with a neural network back propagation approach (ANN-LMA) for comprehensive analysis of viscous dissipation and the Lorentz force effects influenced tri-hybrid nano-fluid mixture. …”
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Dexmedetomidine induces immunogenic cancer cell death and sensitizes tumors to PD-1 blockade by Peng Liu, Guido Kroemer, Oliver Kepp, Jonathan Pol, Liwei Zhao, Lucillia Bezu, Allan Sauvat, Jiani Liu, Killian Carnet Le Provost, Andrea Checcoli

“…A machine learning-based algorithm trained with information on the biological effects and molecular descriptors of analgesics, anesthetics, hypnotics and opioids predicted antitumor effects for dexmedetomidine (DEX). …”
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Vegetation Greening Promoted the Precipitation Recycling Process in Xinjiang by Xuewei Li, Xingming Hao, Sen Zhang, Guanyu Hou, Jingjing Zhang, Xue Fan, Zhuoyi Zhao

“…This study has systematically examined the precipitation recycling process in a typical arid region using the Eltahir and Bras model, random forest algorithm, and partial least-squares structural equation modeling. …”
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