THE APPROVAL OF COMPLEX TREATMENT EFFECTIVENESS OF GENERALIZED PERIODONTITIS FOR THE PATIENTS AFTER TRANSMITTED CORONAVIRUS DISEASE AND REMAIN ON REHABILITATION by T.I. Matviykiv, M.M. Rozhko

“…Examination of areas compromised by generalized periodontitis and abutment teeth based on the obtained periotestometric data of tooth mobility, indicates a significant reduction in inflammation and strengthening of the ligaments and is a highly informative diagnostic method. …”
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National-scale mapping topsoil organic carbon of cropland in China using multitemporal Sentinel-2 images by Jie Xue, Xianglin Zhang, Songchao Chen, Zhongxing Chen, Rui Lu, Feng Liu, Bas van Wesemael, Zhou Shi

“…Finally, bootstrapping random forest models were fitted using the covariates selected through forward recursive feature selection (FRFS), and the spatial prediction SOC map was created. The results indicated that the framework was suitable for mapping SOC in croplands of China, with the best model using remote sensing indices and environmental covariates selected through FRFS achieving an R2 of 0.62, an RMSE of 4.84 g kg−1, and an uncertainty depicted by a 90 % prediction interval range of 17.88 g kg−1. …”
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Occlusion-Robust Multi-Target Tracking and Segmentation Framework with Mask Enhancement by Hao Sheng, Defa Zhang, Dazhi Yang, Da Yang, Xi Liu, Wei Ke

“…Our framework achieves the best performance on the MOTSA (84.4%), MT, and FN metrics, with a 6.1% reduction in FN compared to the state-of-the-art method. …”
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Integrating Social Determinants of Health in Machine Learning–Driven Decision Support for Diabetes Case Management: Protocol for a Sequential Mixed Methods Study by Seung-Yup Lee, Leslie W Hayes, Bunyamin Ozaydin, Steven Howard, Alison M Garretson, Heather M Bradley, Andrew M Land, Erin W DeLaney, Amy O Pritchett, Amanda L Furr, Ashleigh Allgood, Matthew C Wyatt, Allyson G Hall, Jane C Banaszak-Holl

“…The paper presents a design for prediction validation and preimplementation assessment that uses a mixed methods approach to guide the implementation of the system. …”
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Two-Stage Distributionally Robust Optimal Scheduling for Integrated Energy Systems Considering Uncertainties in Renewable Generation and Loads by Keyong Hu, Qingqing Yang, Lei Lu, Yu Zhang, Shuifa Sun, Ben Wang

“…In modeling uncertainties, this article utilizes historical data on PV, WT, and loads, combined with the adjustability of decision variables, to generate a large set of initial scenarios through the Monte Carlo (MC) sampling algorithm. These scenarios are subsequently reduced using a combination of the K-means clustering algorithm and the Simultaneous Backward Reduction (SBR) technique to obtain representative scenarios. …”
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An Innovative Online Adaptive High-Efficiency Controller for Micro Gas Turbine: Design and Simulation Validation by Rui Yang, Yongbao Liu, Xing He, Zhimeng Liu

“…To evaluate the performance changes of the gas turbine, we applied deep learning techniques to enhance the extreme learning machine (ELM) algorithm, resulting in the development of a high-precision, high-real-time deep extreme learning machine (DL_ELM) prediction model. …”
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Architecture of the discrete sosine transformation processor for image compression systems on the losless-to-lossy circuit by V. V. Kliuchenia

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ICSO: A Novel Hybrid Evolutionary Approach with Crisscross and Perturbation Mechanisms for Optimizing Generative Adversarial Network Latent Space by Zhihui Chen, Ting Lan, Zhanchuan Cai, Zonglin Liu, Renzhang Chen

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Abnormality detection and privacy protection strategies for power marketing inspection business of cyber–physical–social systems using big data and artificial intelligence by Li Kai, Mo Pingyan, Yang Yongjiao, Xie Hanyang, Shen Zhixiong

“…The proposed model incorporates a work order correlation matching algorithm, a fault interval detection algorithm, an electricity consumption prediction algorithm, and a business anomaly identification algorithm. …”
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A modern view on the management of patients with ulcerative colitis of mild and moderate severity in outpatient practice by A. M. Kharitidis, O. B. Shchukina

“…It is indicated that for the choice of tactics and treatment algorithm, the extent of the lesion, as well as the severity of the current exacerbation, classified as mild, moderate and severe, are important. …”
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Delivering Dual Polarization-Division-Multiplexing Millimeter-Wave Signals at W-Band by One Pair of Antennas by Yifan Chen, Jiangnan Xiao, Ze Dong

“…The bit error ratio (BER) is less than the new-generation forward-error-correction (eFEC) threshold of 2 × 10^−2 with CMA algorithm for equalization.…”
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Public and mental health professionals’ perspectives on social media and suicide exposure by Jo Bell, Christopher Westoby

“…Results Four key themes emerged: (1) The communicative ecology of social media (where the public act as content purveyors, rapidly disseminating varied and often unregulated narratives); (2) Harmful effects (including the copycat effect and toxic discourse); (3) Positive effects (where protective discourse and moderation offer harm reduction opportunities); and (4) Challenges in intervention (including content moderation difficulties and algorithmic biases that amplify harmful narratives). …”
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Identification breeds equity: the regulation effect of group decision-making on beauty premium by Lu Cheng, Qingguo Ma, Yijin He, Yulin Tan, Linanzi Zhang, Wenwei Qiu

“…For exploring the underlying mechanism, this study employed a genetic-algorithm-based modelling method to analyse participants’ trial-by-trial dynamic adjustment in group environment. …”
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Hyperneutron Stars from an Ab Initio Calculation by Hui Tong, Serdar Elhatisari, Ulf-G. Meißner​

“…These predictions are in good agreement with the latest astrophysical constraints derived from observations of massive neutron stars, gravitational waves, and joint mass–radius measurements. …”
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Development of a host-signature-based machine learning model to diagnose bacterial and viral infections in febrile children by Fang Bai, Zelong Gong, Dong Cui, Xiaomei Zhang, Wenteng Hong, Yi Gao, Kai Lin, Weijie Chen, Lu Li, Juan Huang, Biying Zheng, Junfa Xu, Na Xiao

“…Subsequently, L1 regularization algorithms and variable significance analysis (multilayer perceptron) were used to simplify and rank the predictive features, and LCN2 (100.0%), IFI27 (84.4%), SLPI (63.2%), IFIT2 (44.6%) and PI3 (44.5%) were identified as the top predictors. …”
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Day-ahead photovoltaic power generation forecasting with the HWGC-WPD-LSTM hybrid model assisted by wavelet packet decomposition and improved similar day method by Ruxue Bai, Jinsong Li, Jinsong Liu, Yuetao Shi, Suoying He, Wei Wei

“…While deep learning algorithms have shown promise in energy applications, single algorithms often struggle with unstable predictions and limited generalizability for predicting photovoltaic (PV) output. …”
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Bayesian Adaptive Lasso for Regression Models with Nonignorable Missing Responses by Yuanying Zhao, Xingde Duan

“…We extend the partial posterior predictive p value for goodness-of-fit statistic to investigate the plausibility of the posited model. …”
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On Fuzzy Soft Expert Sets by Hilal Donmez, Serdar Enginoglu

“…Furthermore the results of this algorithm and Maji et al's algorithm without reduction are equivalent. …”
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Using Satellites to Monitor Soil Texture in Typical Black Soil Areas and Assess Its Impact on Crop Growth by Liren Gao, Yuhong Zhang, Deqiang Zang, Qian Yang, Huanjun Liu, Chong Luo

“…The results show that (1) the order of prediction accuracy differs for different soil texture types; April is determined to have the highest prediction accuracy for silt and sand, while May exhibits the greatest accuracy for clay. (2) Adding environmental variables can significantly improve the accuracy of soil texture predictions; the root mean square error (RMSE) has decreased to varying degrees (silt: 0.84; clay: 0.04; sand: 0.85). (3) Soybean growth has the strongest response to soil texture; clay grain is the key factor affecting crop growth in drought scenarios, and sand grain is the dominant factor influencing flooding. …”
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Feature Importance Analysis for Compressive Bearing Capacity of HSCM Piles Based on GA-BPNN by Fangzhou Chu, Jiakuan Ma, Yang Luan, Shilin Chen

“…To address the complex pile–soil interaction mechanisms in predicting the compressive bearing capacity of HSCM piles (Helix Stiffened Cement Mixing piles) in marine soft soil regions, this study proposes an intelligent prediction method based on a GA-BPNN (Genetic Algorithm-Optimized Back Propagation Neural Network). …”
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