Precision-Enhanced and Encryption-Mixed Privacy-Preserving Data Aggregation in Wireless Sensor Networks by Geng Yang, Sen Li, Xiaolong Xu, Hua Dai, Zhen Yang

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The Association of Aortic Stenosis Severity and Symptom Status With Morbidity and Mortality by Matthew D. Solomon, MD, PhD, Alan S. Go, MD, Thomas Leong, MPH, Elisha Garcia, BS, Kathy Le, MPH, Femi Philip, MD, Edward McNulty, MD, Jacob Mishell, MD, Andrew N. Rassi, MD, David C. Lange, MD, Catherine Lee, PhD, Anthony DeMaria, MD, Rick Nishimura, MD, Andrew P. Ambrosy, MD

“…After multivariable adjustment, symptom status strongly predicted risk. Patients with symptomatic moderate AS had a similar risk to those with severe AS without symptoms (adjusted HR: 1.77 [95% CI: 1.65-1.91] vs 1.81 [95% CI: 1.51-2.17] for death, P = 0.81; aHR: 2.27 [95% CI: 2.13-2.41] vs 2.40 [95% CI: 2.08-2.77] for AS-related hospitalization, P = 0.42). …”
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Control Directo de Potencia Predictivo Robusto con Sincronismo Intrínseco by J.R. Fischer, S.A. González, I. Carugati, M.G. Judewicz, D.O. Carrica

“…In this work a novel positive sequence detector is also implemented which ensures the elimination of perturbation at the output current due to harmonics content. The control algorithm has an intrinsic synchronization scheme which avoids an additional three-phase PLL. …”
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Integrative analysis of T cell-associated markers in Ewing sarcoma reveals prognostic signatures and immune dynamics by Umair Ali Khan Saddozai, Umair Ali Khan Saddozai, Chenxu Liu, Chenxu Liu, Fei Yan, Zhendong Lu, Muhammad Babar Khawar, Muhammad Babar Khawar, Muhammad Usman Akbar, Saadullah Khattak, Haibo Sun, Haibo Sun, Ping Yang

“…The prognostic model demonstrated high predictive accuracy for 1-, 3-, and 5-year survival (AUC: 0.85, 0.82, 0.78). …”
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Comparative analysis of the human microbiome from four different regions of China and machine learning-based geographical inference by Yinlei Lei, Min Li, Han Zhang, Yu Deng, Xinyu Dong, Pengyu Chen, Ye Li, Suhua Zhang, Chengtao Li, Shouyu Wang, Ruiyang Tao

“…Individuals from the four regions could be distinguished and predicted based on a model constructed using the random forest algorithm, with the predictive effect of palmar microbiota being better than that of oral and nasal cavities. …”
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Recovering Pulsar Periodicity from Time-of-arrival Data by Finding the Shortest Vector in a Lattice by Dotan Gazith, Aaron B. Pearlman, Barak Zackay

“…Identifying such a periodicity from a discrete set of arrival times is a difficult algorithmic problem, In particular when the pulsar is in a binary system. …”
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Individualized surgical treatment using decellularized fish skin transplantation after enzymatic debridement: A two years retrospective analysis by Gerrit Freund, Benedikt Schäfer, Justus P. Beier, Anja M. Boos

“…Fish skin was found to provide a satisfying result in terms of the overall outcome of the developed scar tissue and could lead to a reduction in the area that requires autologous transplantation.…”
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A Win-Win Coordinated Scheduling Strategy Between Flexible Load Resource Operators and Smart Grid in 5G Era by Nan Zhang, Di Liu, Tianbao Liu, Xueyan Zhang, Jing Guo, Fusheng Lan, Qingyao Li, Weiyi Lu, Xiaolong Yang

“…To further enhance the optimization of energy distribution, a many-to-many proportional energy-sharing algorithm is developed, which facilitates the aggregation of scheduling capacities across multiple regions. …”
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Finding White Dwarfs’ Hidden Companions Using an Unsupervised Machine Learning Technique by Xabier Pérez-Couto, Minia Manteiga, Eva Villaver

“…Our methodology involves applying an unsupervised machine learning algorithm for dimensionality reduction and clustering, known as a self-organizing map (SOM), to Gaia BP/RP (XP) spectra. …”
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Optimal Management in the Operation of Complex Technical Systems by Dyadyura K., Oborskyi G., Prokopovych I., Khamitov V., Holubiev M.

“…Additionally, proof of the existence of an optimal verification strategy was given. An algorithm for determining the moments of verification was developed to ensure the minimum cost. …”
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ITD-YOLO: An Improved YOLO Model for Impurities in Premium Green Tea Detection by Zezhong Ding, Yanfang Li, Bin Hu, Zhiwei Chen, Houzhen Jia, Yali Shi, Xingmin Zhang, Xuesong Zhu, Wenjie Feng, Chunwang Dong

“…Simultaneously, it achieved a reduction in computational complexity with GFLOPs decreasing by 2.3 and parameters shrinking by 860350 B. …”
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Novel and Optimized Efficient Transmission Using Dynamic Routing Technique for Underwater Acoustic Sensor Networks by Swapna Babu, Bhuvaneswari Subramanian, Sujitha Madhavadhas, Kavitha Ganesan, Manjula Dhandapani, Surendiran Muthukumar Deva

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Universal Single Controller for Solving Deadlock Problems of Flexible Manufacturing Systems by Ter-Chan Row, Ching-Yun Tseng, Yen-Liang Pan

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Estimation of the water content of needles under stress by Erannis jacobsoni Djak. via Sentinel-2 satellite remote sensing by Jiaze Guo, Xiaojun Huang, Xiaojun Huang, Xiaojun Huang, Debao Zhou, Junsheng Zhang, Gang Bao, Gang Bao, Siqin Tong, Siqin Tong, Yuhai Bao, Yuhai Bao, Dashzebeg Ganbat, Dorjsuren Altanchimeg, Davaadorj Enkhnasan, Mungunkhuyag Ariunaa

“…Needle leaf water content exhibits a clear response to these changes and is highly sensitive in reflecting the degree of tree damage.MethodsIn this work, we combine vegetation indices with machine learning algorithms to estimate the water content of needles at a large scale. …”
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Functional Connectivity Changes in Primary Motor Cortex Subregions of Patients With Obstructive Sleep Apnea by Lifeng Li, Qimeng Shi, Bowen Fang, Yuting Liu, Xiang Liu, Yongqiang Shu, Yingke Deng, Yumeng Liu, Haijun Li, Junjie Zhou, Dechang Peng

“…Methods Sixty‐five patients with OSA and 65 healthy controls (HC) participants matched in age and educational background were included. Resting‐state functional MRI data were acquired for all participants using a 3T MRI system. …”
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The Role of the TIMP1/LINC01615 Axis as a Regulator of the EMT Pathway in Gastric Cancer by Jiying Liu, Yeganeh Olyaee, Khatere Mokhtari, Chaoxiang Lv, Niloufar Salimian, Maliheh Entezari, Afshin Taheriazam, Mehrdad Hashemi, Mazaher Maghsoudloo, Ling Yuan

“…Methods We utilized the TCGA-STAD dataset and differential expression gene (DEG) analysis was performed to identify overlapping genes between DEGs and the EMT pathway. The LASSO feature reduction algorithm and ROC curve analysis were applied to prioritize candidate biomarkers. …”
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Enhancing renewable energy integration through strategic stochastic optimization planning of distributed energy resources (Wind/PV/SBESS/MBESS) in distribution systems by Ahmad K. ALAhmad, Renuga Verayiah, Hussain Shareef, Agileswari Ramasamy, Saleh Ba-swaimi

“…A hybrid optimization approach combining the non-dominated sorting genetic algorithm (NSGAII) and multi-objective particle swarm optimization (MOPSO) with a decision-making algorithm is proposed to solve the planning problem. …”
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Adverse events in the neonatal intensive care unit identified by triggers by Fabiana Bragança Albanese, Deise de Souza Ventura, Deise de Souza Ventura, Maurício Wesley Perroud, Maurício Wesley Perroud, Rafael Nogueira de Souza, Mariana Vieira Morau, Marília Berlofa Visacri, Marília Berlofa Visacri, Patricia Moriel, Patricia Moriel

“…AE severity was assessed using the Neonatal Adverse Event Severity Scale (NAESS) and the World Health Organization (WHO) classification, while ADR causality was evaluated using the WHO criteria and the algorithm proposed by Du et at. Risk factors such as gestational age, birth weight, and length of hospital stay were also analyzed.ResultsA total of 249 triggers identified 168 confirmed AEs, resulting in a Positive Predictive Value (PPV) of 67.5%. …”
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Mapping Soil Available Nitrogen Using Crop-Specific Growth Information and Remote Sensing by Xinle Zhang, Yihan Ma, Shinai Ma, Chuan Qin, Yiang Wang, Huanjun Liu, Lu Chen, Xiaomeng Zhu

“…These remote sensing variables were combined with soil sample data, crop type information, and crop growth period data as predictive factors and input into a Random Forest (RF) model optimized using the Optuna hyperparameter tuning algorithm. …”
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Assessment of prostate cancer aggressiveness through the combined analysis of prostate MRI and 2.5D deep learning models by Yalei Wang, Yuqing Xin, Baoqi Zhang, Fuqiang Pan, Xu Li, Manman Zhang, Yushan Yuan, Lei Zhang, Peiqi Ma, Bo Guan, Yang Zhang

“…Models were constructed using the LightGBM algorithm: a radiomic feature model, a deep learning feature model, and a combined model integrating radiomic and deep learning features. …”
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