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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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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Implementing Remote Radiotherapy Planning to Increase Patient Flow at a Johannesburg Academic Hospital, South Africa: Protocol for a Prospective Feasibility Study by Duvern Ramiah, Sonwabile Ngcezu, Oluwatosin Ayeni, Okechinyere Achilonu, Mariam Adeleke, Theo Nair, Joseph Otten, Daniel Mmereki

“…Phase 1 (feasibility) encompasses system commissioning, including beam modeling, computed tomography (CT)-to-electron density calibration, multileaf collimator (MLC) optimization, and dose calculations using the anisotropic analytical algorithm. …”
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Estimation and evaluation of iron reserves in the eastern area of Eileh1 mine, Razavi Khorasan province by Hamid Esmati Daroneh, Maryam Gholamzadeh

“…E1-RC-BH-9.2 and E1-RC-BH-27, while the minimum depth is 9 meters, associated with Rasol borehole No. …”
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Research of Regenerative Braking Strategy for Electric Vehicles by Van Nghia Le, Hoang Phuc Dam, Trong Hoan Nguyen, S. V. Kharitonchik, V. A. Kusyak

“…Serial production of high-tech electric vehicles with a long range contributes to the stabilization of the energy market and the sustainable development of the whole fuel-energy sector. To evaluate the possibility of optimizing the electric vehicles energy consumption, various regenerative braking strategies are discussed in the article based on the Nissan Leaf electric vehicle, which simulation model includes submodules of the traction electric motor, hybrid braking system, traction rechargeable battery and tires. …”
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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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Performance evaluation of inset feed microstrip patch antenna parameters with different substrate materials for 5G wireless applications by Kebbekoppalu Shrinivasa Praveena, M Patil Chandrashekar

“…The proposed method uses a new hybrid GA-PSO algorithm with Dynamic Adaptive Mutation and Inertia Control (DAMIC). …”
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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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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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Preliminary performance analysis using the PPP-RTK service of the National Land and Mapping Center in Taiwan by J.-Y. Lin, C.-H. Chu, F.-Y. Chu, K.-W. Chiang, M.-L. Tsai

“…Regarding real-time performance, while (Precise Point Positioning-Real Time Kinematic)PPP-RTK's corresponding accuracy is not as high as Network-RTK (NRTK), PPP-RTK can provide rapid positioning solutions with a single antenna and single Global Navigation Satellite System(GNSS) receiver. …”
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Artificial Intelligence-Assisted Clinical Decision-Making: A Perspective on Advancing Personalized Precision Medicine for Elderly Diabetes Patients by Hu J, Ren L, Wang T, Yao P

“…Nonetheless, several challenges persist, including issues related to data standardization, algorithm transparency, and patient privacy protection. …”
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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 < 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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Research on Characteristics and Influencing Factors of High Temperature Disaster Risk in Wuhan Based on Local Climate Zone by Shujing GUO, Li ZHANG

“…Furthermore, highly correlated LCZ types are screened out under the optimal size, the multicollinearity of all LCZ landscape pattern indices is examined and those with multicollinearity are excluded. …”
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Subcortical Brain Segmentation Based on a Novel Discriminative Dictionary Learning Method and Sparse Coding by Xiang Li, Ying Wei, Yunlong Zhou, Bin Hong

“…For the shared dictionary, a regularization term is used to minimize the between-class scatter of corresponding shared coefficients so that they can learn shared image patterns. The optimization algorithms are developed to solve the problems in the learning step. …”
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