The Evaluation of Radiolabeled Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography for Initial Staging in Intermediate-Risk Prostate Cancer Patients... by Laura Evangelista, Priscilla Guglielmo, Giulia Giacoppo, Lucia Setti, Demetrio Aricò, Lorenzo Muraglia, Katia Marzo, Nicolò Buffi, Vittorio Fasulo, Marcello Rodari, Jelena Jandric, Antonio Salvaggio, Manuela Bonacina, Massimo Lazzeri, Giovanni Lughezzani

“…The inclusion of PSMA PET/CT in the diagnostic algorithm for patients with intermediate-risk PCa impacted patient management in 24 (13.3%) cases, based on the multidisciplinary team decision. …”
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Minimum required distance for clinically significant measurement of habitual gait speed by Myung Woo Park, Sun Gun Chung, Jaewon Beom, Kyung Su Kim, Joonghee Kim, Chul-Hyun Park, Jinkyu Lee, Keewon Kim

“…Fourteen body points were derived using a pose-estimation algorithm. Speed was calculated based on the center of mass or a leading foot which simulates a condition with a walkway sensor and validated against manual measurements. …”
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The Relationship Between Surface Meteorological Variables and Air Pollutants in Simulated Temperature Increase Scenarios in a Medium-Sized Industrial City by Ronan Adler Tavella, Daniele Feijó das Neves, Gustavo de Oliveira Silveira, Gabriella Mello Gomes Vieira de Azevedo, Rodrigo de Lima Brum, Alicia da Silva Bonifácio, Ricardo Arend Machado, Letícia Willrich Brum, Romina Buffarini, Diana Francisca Adamatti, Flavio Manoel Rodrigues da Silva Júnior

“…The greatest seasonal reduction in O₃ occurred in winter (decreasing by 10.33% and 12.32% under 1 °C and 2 °C warming scenarios, respectively), while for PM₁₀ and PM_2.5, the most significant reductions were observed in spring. …”
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Using proximal sensor data for soil salinity management and mapping by Yan GUO, Yin ZHOU, Lian-qing ZHOU, Ting LIU, Lai-gang WANG, Yong-zheng CHENG, Jia HE, Guo-qing ZHENG

“…Afterwards, fuzzy-k means algorithm was used to divide the site-specific management zones within the time series apparent soil electrical conductivity (ECa) data and the spatial correlations of variation. …”
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A Comprehensive Study of Czernik 41 and NGC 1342 Using CCD UBV and Gaia DR3 Data by Burçin Tanık Öztürk, Selçuk Bilir, Talar Yontan, Olcay Plevne, Tansel Ak, Serap Ak, Remziye Canbay, Timothy Banks

“…The distances to Czernik 41 and NGC 1342 were determined as 2485 ± 151 pc and 645 ± 42 pc, respectively, while their ages were estimated to be 69 ± 10 Myr and 1000 ± 50 Myr. …”
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MSS-YOLO: Multi-Scale Edge-Enhanced Lightweight Network for Personnel Detection and Location in Coal Mines by Wenjuan Yang, Yanqun Wang, Xuhui Zhang, Le Zhu, Tenghui Wang, Yunkai Chi, Jie Jiang

“…In addition, MSS-YOLO is combined with the SGBM binocular stereo vision matching algorithm to provide a personnel 3D spatial position solution by using disparity results. …”
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Does machine learning outperform logistic regression in predicting individual tree mortality? by Aitor Vázquez-Veloso, Astor Toraño Caicoya, Felipe Bravo, Peter Biber, Enno Uhl, Hans Pretzsch

“…Through different case studies, when more variables were used, general performance improved as expected, while more extensive datasets decreased the performance level of the algorithms. …”
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Differential expression of microRNAs and their target genes in cervical intraepithelial neoplasias of varying severity by T. A. Dimitriadi, D. V. Burtsev, E. A. Dzhenkova, D. S. Kutilin

“…To identify genes associated with target genes in common signaling pathways, GIANT (Genome-scale Integrated Analysis of gene Networks in Tissues) and network integration with several associations algorithms were used. Results. For microRNAs miR-145, miR-196b, miR-34a, miR-20a, miR-21, miR-375 and miR-96 a decrease in expression was found in the subgroup of patients with CIS, while for 4 microRNAs (miR-145, miR-34a, miR-20a and miR-375), an increase in the expression level was found for CIN1, 2. …”
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Enhancing the prediction of groundwater quality index in semi-arid regions using a novel ANN-based hybrid arctic puffin-hippopotamus optimization model by Moustafa Gamal Snousy, Hussein M. Elshafie, Ashraf R. Abouelmagd, Najmaldin Ezaldin Hassan, Mahmoud E. Abd-Elmaboud, Ali Akbar Mohammadi, Ashraf M.T. Elewa, E. EL-Sayed, Ahmed M. Saqr

“…Study focus: This study presents a novel hybrid arctic puffin–hippopotamus optimization (HPHO) algorithm combined with an artificial neural network (ANN) to improve irrigation water quality index (IWQI) predictions in semi-arid areas. …”
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Integration of Fourier and Wavelet Transform for Adsorption Mechanism of Cesium Study Based on X-Ray Diffraction and Absorption Spectroscopy by Chi-Wen Hsieh, Zih-Shiuan Chiou, Chuan-Pin Lee, Shih-Chin Tsai, Wei-Hsiang Tseng, Yu-Hung Wang, Hui-Min Chiu, Qi-Rui Sun, Chun-Liang Yeh

“…Based on the comparison with adsorption parameters of the standard CsNO3 sample, an iterative check algorithm is proposed then to yield the reasonable outcomes. …”
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EEG Microstate Dynamics during Different Physiological Developmental Stages and the Effects of Medication in Schizophrenia by Shihai Ling, Lingyan Du, Xi Tan, Guozhi Tang, Yue Che, Shirui Song

“…After pre-processing, EEG data from different groups were subjected to microstate analysis, and the K-Means clustering algorithm was applied to classify the data into 4 microstates. …”
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GYS-RT-DETR: A Lightweight Citrus Disease Detection Model Based on Integrated Adaptive Pruning and Dynamic Knowledge Distillation by Linlin Yang, Zhonghao Huang, Yi Huangfu, Rui Liu, Xuerui Wang, Zhiwei Pan, Jie Shi

“…Secondly, the model adopts two model optimization strategies: (1) The Group_taylor local pruning algorithm is used to reduce memory occupation and the number of computing parameters of the model. (2) The feature-logic knowledge distillation framework is proposed and adopted to solve the problem of information loss caused by the structural difference between teachers and students, and to ensure a good detection performance, while realizing the lightweight character of the model. …”
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Clinical characteristics of COVID-19 in children and adolescents: insights from an Italian paediatric cohort using a machine-learning approach by Carlo Giaquinto, Daniela Paolotti, Daniele Donà, Stefania Fiandrino, Piero Poletti, Michael Davis Tira, Costanza Di Chiara

“…First, we apply an unsupervised machine-learning algorithm to cluster individuals into groups. Second, we classify new patient risk groups using a random forest classifier model based on sociodemographic information, pre-existing medical conditions, vaccination status and the VOC as predictive variables. …”
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Initial experience of parenchyma-sparing liver resection with systematic selective hepatic vein reconstruction for colorectal metastases by Yevhenii Trehub, Åsmund Avdem Fretland, Artem Zelinskyi, Dzmitrii Kharkov, Oleksii Babashev, Dmytro Chieverdiuk, Artem Shchebetun, Kyrylo Khyzhniak, Maksym Pavlovskii, Andrii Strokan, Sergii Zemskov

“…No mortality was observed, while the major morbidity rate was 33%. The short-term and long-term patency of the reconstructed HVs was 88.9% and 66.7%, respectively. …”
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A case study on the application of a data-driven (XGBoost) approach on the environmental and socio-economic perspectives of agricultural groundwater management by Sheng-Wei Wang, Yen-Yu Chen, Shu-Han Hsu, Yu-Hsuan Kao, Masaomi Kimura, Li-chiu Chang, Tzi-Wen Pan, Chuen-Fa Ni

“…This study develops a groundwater level prediction model using the extreme gradient boosting (XGB) algorithm, employing power consumption, precipitation, and groundwater level data as input features. …”
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DVAEGMM: Dual Variational Autoencoder With Gaussian Mixture Model for Anomaly Detection on Attributed Networks by Wasim Khan, Mohammad Haroon, Ahmad Neyaz Khan, Mohammad Kamrul Hasan, Asif Khan, Umi Asma Mokhtar, Shayla Islam

“…Deep learning approaches like graph autoencoders are utilized to perform anomaly detection through obtaining node embeddings while dealing with the network nonlinearity and sparsity issues. …”
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AI-driven generative and reinforcement learning for mechanical optimization of 2D patterned hollow structures by Yicheng Shan, Leitao Cao, Yu Wang, Jing Ren, Chen Huang, Wenli Gao, Shengjie Ling

“…We generated a comprehensive dataet comprising 1000 samples across five distinct density classes using a custom grid pattern generation algorithm, ensuring a wide range of structural variations. …”
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Identification of diagnostic hub genes related to energy metabolism in idiopathic pulmonary fibrosis by S. Zhao, S. Zhao, B. C. Sun, N. Liu, R. Huo, L. S. Liu, J. P. Wang, J. P. Wang, C. Y. Fang, C. Y. Fang

“…Immune infiltration analyses, including the CIBERSORT algorithm, and single-sample gene set enrichment analysis (ssGSEA), were subsequently conducted.ResultsWe identified 12 EMRDEGs and eight hub genes (ACSL1, CEBPD, CFH, HMGCS1, IL6, SOCS3, TLR2, and UCP2). …”
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Development of a machine learning-based predictive risk model combining fatty acid metabolism and ferroptosis for immunotherapy response and prognosis in prostate cancer by Zhenwei Wang, Zhihong Dai, Yuren Gao, Zhongxiang Zhao, Zhen Li, Liang Wang, Xiang Gao, Qiuqiu Qiu, Xiaofu Qiu, Zhiyu Liu

“…Functional enrichment analysis revealed distinct pathway activities, with high-risk patients showing enrichment in immune-related and proliferative pathways, while low-risk patients were enriched in metabolic pathways. …”
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Quantitative inversion of suspended particulate matter in Ebinur lake, an arid region: Evidence based on radiative transfer mechanism model by Ziheng Feng, Fei Zhang, Xiaolan Cai, Changjiang Liu, Di Wu, Zhenzhou Zhu, Zia Ahmed, Shuai Yuan, Xu Ma, Lifei Wei, Xin He

“…Sensitivity analysis indicates that SPM and ζSPM are the primary drivers of remote sensing reflectance (Rrs), while CDOM strongly absorbs in the shortwave region, and Chla exhibits weak, easily masked signals. …”
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