A Specific Time Lag Regulation of Soil Moisture Across Layers on Soil Salinization in the Northeast Tibetan Plateau Agroecosystem by Di Wei, Ziqi Zhang, Lin Yan, Jia Yu, Yun Zhang, Bo Wang

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Effectiveness evaluation of the complex medical and psychological method of treating patients with insomnia by A. V. Vasil'eva, T. A. Karavaeva, Yu. P. Kolesova, D. S. Radionov, D. A. Starunskaya, M. V. Fomicheva, S. M. Abdullaeva

“…The quantitative evaluation of the effectiveness of the method was carried out on seven indicators: (1) Improvement in the subjective characteristics of sleep, (2) Improvement in the quality of sleep, (3) Reduction of the insomnia severity index, (4) Reduction of daytime sleepiness, (5) Reduction of the consequences of sleep disorders, (6) Decreased anxiety, (7) Improved overall clinical impression. …”
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Detecting Covid-19 Fake News on Twitter/X in French: Deceptive Writing Strategies by Ming Ming Chiu, Alex Morakhovski, Zhan Wang, Jeong-Nam Kim

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Mitochondrial insights: key biomarkers and potential treatments for diabetic nephropathy and sarcopenia by Yi Wei Chen, Shan He, Yu Wang, Lian Ying Hu, Qin Kai Chen, Si Yi Liu

“…Utilizing four machine learning algorithms (LASSO, SVM, XGBoost, RF), we pinpointed three mitochondrial hub genes. …”
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MATHEMATICAL MODEL AND DELAY TIME OF REFLECTED SIGNAL IN SYNTHETIC APERTURE SONAR by S. R. Heister, T. T. Tran

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CHARACTERISTICS OF THE NOISE STABILITY OF RADIO COMMUNICATION SYSTEMS WITH FREQUENSY HOPING by I. I. Skib, A. V. Martsinovich, E. L. Kreidik, V. A. Cherdyntsev

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Free space method using a vector network analyzer to determine the dielectric permittivity of materials in microwave range by N. A. Pevneva, A. L. Gurskii, A. M. Kostrikin

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Common Secret Key Derivation Based on Synchronized Artificial Neuronal Networks Using Multispeed Weighted Coefficients Correction by V. F. Golikov, N. V. Brych

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PARAMETRIC AUDIO CODER BASED ON SPARSE APPROXIMATION WITH FRAME-BASED PSYCHOACOUSTIC OPTIMIZED WAVELET PACKET DICTIONARY by Al. A. Petrovsky, V. Y. Herasimovich

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Integer linear programming for unsupervised training set selection in molecular machine learning by Matthieu Haeberle, Puck van Gerwen, Ruben Laplaza, Ksenia R Briling, Jan Weinreich, Friedrich Eisenbrand, Clémence Corminboeuf

“…Within the context of physics-inspired machine learning (ML) applied to chemistry, we demonstrate the relevance of an ILP formulation to select molecular training sets for predictions of size-extensive properties. We show that our algorithm outperforms existing unsupervised training set selection approaches, especially when predicting properties of molecules larger than those present in the training set. …”
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Identifying bellwether sewershed sites for sustainable disease surveillance in Bengaluru, India: a longitudinal studyResearch in context by Rebecca Fern Daniel, Subash K. Kannan, Namrta Daroch, Sutharsan Ganesan, Farhina Mozaffer, Vishwanath Srikantaiah, Lingadahalli Subrahmanya Shashidhara, Rakesh Mishra, Farah Ishtiaq

“…This was achieved by integrating established metrics for wastewater analysis, calculating sample-to-sample percentage rate of change, and applying algorithms to differentiate signal from noise, thereby validating factors contributing to the precision and reliability of outbreak predictions. …”
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An Improved Diagnosis Approach for Short-Circuit Fault Diagnosis in MPC-Based Current Source Inverter System by Jonggrist Jongudomkarn, Pirat Khunkitti, Apirat Siritaratiwat

“…In the presence of faulty switches, the algorithm identifies the phase of the reference current where the predicted currents align with the reference values. …”
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An integrated machine learning framework for developing and validating a prognostic risk model of gastric cancer based on endoplasmic reticulum stress-associated genes by Gang Wei, Yan Wang, Ru Liu, Lei Liu

“…The tumor immune dysfunction and exclusion(TIDE) algorithm was applied to determine the susceptibility of individuals in high- and low-risk categories to immunotherapy. …”
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Analysis of the impact of mobile robots on the efficiency of warehousing and transport processes in modern textile manufacturing by Karabegović Isak

“…AMRs leverage advanced technologies such as LiDAR sensors, SLAM algorithms, artificial intelligence, and IoT systems to navigate complex industrial environments autonomously, optimize routes, and execute tasks without direct human intervention. …”
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Advanced lightweight deep learning vision framework for efficient pavement damage identification by Shuai Dong, Yunlong Wang, Jin Cao, Jia Ma, Yang Chen, Xin Kang

“…Moreover, LPDD-YOLO can obtain a 47.3% reduction in parameters and a 54.4% decrease in GFLOPs. …”
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Distribution Generation Network Arrangement by Capacitor Placement and Sizing in Renewable Energy Sources with Uncertainties Based on Self-adaption Kho-Kho Optimizer by Lu Xingxing

“…Further research will explore multi objective algorithms and the incorporation of additional types of distributed generation to continue improving reliability and stability.…”
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Evaluating Spatial Patterns of Ecosystem Services based on a Comparative Approach on Spatial Statistics in the Central Part of Isfahan Province by Sedighe Abdollahi, Alireza Ildoromi, Abdolrassoul Salmanmahini, Sima Fakheran

“…Then, spatial accuracy of the investigated algorithms was evaluated and compared using the Receiving Operator Characteristic method. …”
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Transferring Face Recognition Techniques to Entomology: An ArcFace and ResNet Approach for Improving Dragonfly Classification by Zhong Li, Shaoyan Pu, Jingsheng Lu, Ruibin Song, Haomiao Zhang, Xuemei Lu, Yanan Wang

“…The model is mainly built based on the classic face recognition algorithm (ResNet50+ArcFace), and ResNet50 is used as the comparison algorithm for model performance. …”
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Evaluation method of hydrophobicity of composite insulators based on improved Mask R-CNN by SHENG Fei, CAO Liu, LIU Yulong, HUANG Jie, HUANG Yaqian, ZHU Yanqing

“…In this paper, the classification problem is transformed into the target detection problem, and the improved mask region-based convolutional neural network (Mask R-CNN) algorithm is used to evaluate the hydrophobicity level of composite insulators. …”
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Bayesian Adaptive Lasso for the Partial Functional Linear Spatial Autoregressive Model by Dengke Xu, Ruiqin Tian, Ying Lu

“…This study introduces a partial functional linear spatial autoregressive model which can explore the relationship between a scalar spatially dependent response variable and predictive variables containing both multiple scalar covariates and a functional covariate. …”
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