CPFD Simulation of Operation Characteristics of a 10t/d Sludge and Biomass Co-incineration Fluidized Bed Reactor by REN Shaohui, YU Qiao, LIN Li, XIANG Jiatao, MA Lun, ZHANG Shihong

“…The study establishes four primary objectives: 1) Quantify hydrodynamic transitions (bubbling/turbulent regimes) under variable fluidizing air conditions; 2) Decipher fuel property impacts (sludge/biomass particle size, feedstock type) on nitrogen/sulfur pollutant transformation pathways (HCN→CNO→NO, H₂S→SO₂); 3) Evaluate bed material efficacy (dolomite, olivine, quartz sand) for in-situ emission control; and 4) Optimize reactor geometry (height-diameter ratios, feed configurations) to maximize combustion efficiency while minimizing environmental footprints. …”
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Application of artificial intelligence in the materials science, with a special focus on fuel cells and electrolyzers by Mariah Batool, Oluwafemi Sanumi, Jasna Jankovic

“…While artificial intelligence shows great potential in studying both fuel cells and electrolyzers, existing literature often separates them, with a clear gap in comprehensive studies on electrolyzers despite their similarities. …”
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Investigation on Circadian Action and Color Quality in Laser-Based Illuminant for General Lighting and Display by Shuo-Di Lei, Bi-Jing Liu, Yang Gao, Xiao-Ya Dong, Yu-Jia Gong, Jian Xu, Yun-Xin Xu, Dong Wang, Zi-Quan Guo, Ting-Zhu Wu, Chen-Liang Zhou, Zong-Jian Cai, Yi-Jun Lu, Zhong Chen

“…In this work, the genetic algorithm is employed to optimize both circadian action factor (CAF) and color quality of laser-based illuminants (LBIs) with three, four, and five spectral bands to disclose its possible use in two common white lighting applications, i.e. bedroom lighting and office lighting. …”
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Machine Learning and Deep Learning for Diagnosis of Lumbar Spinal Stenosis: Systematic Review and Meta-Analysis by Tianyi Wang, Ruiyuan Chen, Ning Fan, Lei Zang, Shuo Yuan, Peng Du, Qichao Wu, Aobo Wang, Jian Li, Xiaochuan Kong, Wenyi Zhu

“…Studies that evaluated DL or TML algorithms assessment value on diagnosing LSS were included, while those with duplicated or unavailable data were excluded. …”
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Patterns of inflammation and immune activation by coreceptor use in people living with HIV-1 by Francisco Xavier Guerra-Castillo, Francisco Xavier Guerra-Castillo, Sandra Pinto-Cardoso, Santiago Ávila-Ríos, Monserrat Chávez-Torres, Amy Peralta-Prado, Carolina González-Torres, Javier Gaytán-Cervantes, Brenda Requena-Benitez, Dafne Díaz-Rivera, Carmen Alaez-Verson, María Concepción Hernández-García, Vilma Carolina Bekker-Méndez

“…Elevated levels of IL-6 were significantly associated with the R5 group (p = 0.01), while the X4 group showed increased expression of CD38+ and HLA-DR+CD38+ markers, although not statistically significant. …”
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The potential role of next-generation sequencing in identifying MET amplification and disclosing resistance mechanisms in NSCLC patients with osimertinib resistance by Xiao Xiao, Xiao Xiao, Ren Xu, Ren Xu, Jun Lu, Beibei Xin, Chenyang Wang, Kexin Zhu, Hao Zhang, Xinyu Chen

“…With FISH results as gold standard, enumeration algorithm was applied to establish the optimal model for identifying MET amplification using gene copy number (GCN) data.ResultsThe optimal model for identifying MET amplification was constructed based on the GCN of MET, BRAF, CDK6 and CYP3A4, which achieved a 74.0% overall agreement with FISH and performed well in identifying MET amplification except polysomy with a sensitivity of 85.7% and a specificity of 93.9%. …”
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AGW-YOLO-Based UAV Remote Sensing Approach for Monitoring Levee Cracks by HU Weibo, ZHOU Shaoliang, ZHAO Erfeng, ZHAO Xueqiang

“…Furthermore, the integration of crack detection results with coordinate transformation algorithms enabled the precise geospatial localization of cracks. …”
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Development of a Conditional Generative Adversarial Network Model for Television Spectrum Radio Environment Mapping by Oluwatobi Emmanuel Dare, Kennedy Okokpujie, Emmanuel Adetiba, Olabode Idowu-Bismark, Abdultaofeek Abayomi, Raymond Jules Kala, Emmanuel Owolabi, Udeme Christopher Ukpong

“…The U-Net generator is a 3-channel input, 16-layer architecture while the PatchGan discriminator is a 6-channel input, 7-layer architecture. …”
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Instrument Performance Analysis for Methane Point Source Retrieval and Estimation Using Remote Sensing Technique by Yuhan Jiang, Lu Zhang, Xingying Zhang, Xifeng Cao, Haiyang Dou, Lingfeng Zhang, Huanhuan Yan, Yapeng Wang, Yidan Si, Binglong Chen

“…While a spatial resolution degradation within 120 m has little impact on quantification, a high spatial resolution is important for detecting low-emission plumes. …”
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A machine learning approach to identifying key predictors of Peruvian school principals' job satisfaction by Luis Alberto Holgado-Apaza, Dany Dorian Isuiza-Perez, Nelly Jacqueline Ulloa-Gallardo, Yban Vilchez-Navarro, Ruth Nataly Aragon-Navarrete, Wilian Quispe Layme, Marleny Quispe-Layme, Danger David Castellon-Apaza, Remo Choquejahua-Acero, Jaime Cesar Prieto-Luna

“…The Histogram-Based Gradient Boosting algorithm, optimized with Bayesian techniques and trained with data balanced through Random Oversampling, achieved a balanced accuracy of 0.63 on a test set with real-world class distribution. …”
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Development and validation of dynamic clinical subphenotypes in acute pancreatitis patients using vital sign trajectories in intensive care units: a multinational cohort study by Zichen Wang, Wen Wang, Jiayue Xu, Qiao He, Che Sun, Shuangyi Xie, Kang Zou, Qing Xia, Xin Sun

“…For hyperinflammatory phenotype, the algorithm-estimated lowest-risk fluid range was 4100–4300 mL on day 1 and 3400–3600 mL on day 2; for phenotype hypoinflammatory phenotype, the optimal ranges were 2800–3800 mL and 1400–2600 mL, respectively. …”
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Comprehensive analysis on soil nitrogen prediction using near-infrared spectroscopy: Models, methods, and insights for precision agriculture by Xiaoyu Wang, Zhiyou Zhang, Yujiao Li, Jie Li, Qing Yang, Qiqi Liu, Zhijie Gong, Mengling Zhang, Xu Wang, Guanghui Xie

“…Key findings include: (1) Sample sizes for modeling predominantly ranged between 22 and 163 (80.0 %); (2) Fourier transform near-infrared spectrometers were the most widely used NIR spectrometers (43.5 %), followed by a grating near-infrared spectrometer (17.4 %); (3) The most common NIR spectrometer wavelength range was 12,804–588 cm−1 (60.9 %); (4) Smoothing techniques (SG, average, and Whittaker) were the dominant preprocessing methods (44.4 %), while partial least squares (PLS) as the most effective modeling algorithm (69.7 %). …”
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Electrophysiological changes in the acute phase after deep brain stimulation surgery by Lucia K. Feldmann, Diogo Coutinho Soriano, Jeroen Habets, Valentina D'Onofrio, Jonathan Kaplan, Varvara Mathiopoulou, Katharina Faust, Gerd-Helge Schneider, Doreen Gruber, Georg Ebersbach, Hayriye Cagnan, Andrea A. Kühn

“…While beta band activity is confirmed as a reliable biomarker for bradykinesia using chronic recordings, little is known about the ideal time point for initial electrophysiology-based programming. …”
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Surface Soil Organic Carbon Estimation Based on Habitat Patches in Southwest China by Jieyun Xiao, Wei Zhou, Ting Wang, Yao Peng, Zhan Shi, Saibo Li, Yang Li, Tianxiang Yue

“…This study proposed a new method using the partitioning around medoids clustering algorithm to partition the study area into distinct habitat patch types. …”
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Sagittal Plane Kinematic Deviations and Spatio-Temporal Gait Characteristics in Children with Idiopathic Toe Walking: A Comparative Analysis Using Statistical Parametric Mapping by Rocio Pozuelo-Calvo, Almudena Serrano-Garcia, Yolanda Archilla-Bonilla, Angel Ruiz-Zafra, Manuel Noguera-Garcia, Kawtar Benghazi-Akhlaki, Miguel Membrilla-Mesa, Carla DiCaudo, Jose Heredia-Jimenez

“…<b>Background/Objectives</b>: Idiopathic Toe Walking (ITW) is a pediatric gait disorder characterized by persistent toe-to-heel ambulation in the absence of neurological, orthopedic, or developmental abnormalities. While spatio-temporal parameters often remain within normal ranges, subtle but clinically significant kinematic deviations may underlie compensatory mechanisms that sustain gait functionality. …”
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A large-scale prospective nested case-control study: developing a comprehensive risk prediction model for early detection of pancreatic cancer in the community-based ESPRIT-AI coho... by Chaoliang Zhong, Penghao Li, Jia Zhao, Xue Han, Beilei Wang, Gang Jin

“…Multiple machine learning algorithms were compared, with the best performing algorithm selected for the final predictive model, subsequently validated using a real-world external test cohort. …”
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A cross-sectional study of evaluating cervical spondylotic myelopathy based on gait and plantar pressures by Xuhong Zhang, Zichuan Wu, Hanlin Song, Aochen Xu, Junbin Liu, Junzhe Sheng, Baifeng Sun, Min Qi, Chen Xu, Yang Liu

“…Gait parameters were obtained by capturing video of the patient while walking via a smartphone-based computer vision algorithm (using the OpenPose framework), and plantar pressure distributions were measured using wireless sensor-equipped insoles (sampling rate 50–100 Hz). …”
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Inversion of Leaf Chlorophyll Content in Different Growth Periods of Maize Based on Multi-Source Data from “Sky–Space–Ground” by Wu Nile, Su Rina, Na Mula, Cha Ersi, Yulong Bao, Jiquan Zhang, Zhijun Tong, Xingpeng Liu, Chunli Zhao

“…This study proposes an improved method based on multi-source data, combining the Sentinel-2A spectral response function (SRF) and computer algorithms, to overcome the limitations of traditional methods. …”
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Application of machine learning in predicting adolescent Internet behavioral addiction by Yao Gan, Li Kuang, Xiao-Ming Xu, Ming Ai, Jing-Lan He, Wo Wang, Su Hong, Jian mei Chen, Jun Cao, Qi Zhang

“…The model’s indicators under each algorithm were compared, evaluated with a confusion matrix, and the optimal model was selected.ResultThe proportion of male adolescents, urban household registration, and scores on the family function, planning, action, and cognitive subscales, along with psychoticism, introversion-extroversion, neuroticism, somatization, obsessive-compulsiveness, interpersonal sensitivity, depression, anxiety, hostility, paranoia, and psychosis, were significantly higher in the Internet addiction group than in the non-Internet addiction group (P &lt; 0.05). …”
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Evaluation of a Machine Learning Model Based on Laboratory Parameters for the Prediction of Influenza A and B in Chongqing, China: Multicenter Model Development and Validation Stud... by Weiwei Hu, Yulong Liu, Jian Dong, Xuelian Peng, Chunyan Yang, Honglin Wang, Yong Chen, Shan Shi, Jin Li

“…The CatBoost (CATB) algorithm was optimized via 5-fold cross-validation and random grid search using 24 routine blood parameters. …”
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