A willingness-aware user recruitment strategy based on the task attributes in mobile crowdsensing by Yang Liu, Yong Li, Wei Cheng, Weiguang Wang, Junhua Yang

“…Finally, we use the greedy method to optimize the user recruitment for each task to select the most suitable users for the tasks. …”
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Design and simulation of a 5 KW solar-powered hybrid electric vehicle charging station with a ANN–Kalman filter MPPT and MPC-based inverter control for reduced THD by Youness Hakam, Hajar Ahessab, Ahmed Gaga, Mohamed Tabaa, Benachir El Hadadi

“…Unlike traditional MPPT methods, which face challenges with multiple peaks in the Power–Voltage (P–V) curve, the hybrid algorithm enhances tracking accuracy, reduces errors, and cuts tracking time by up to 99.93%. …”
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Integrating Model‐Informed Drug Development With AI: A Synergistic Approach to Accelerating Pharmaceutical Innovation by Karthik Raman, Rukmini Kumar, Cynthia J. Musante, Subha Madhavan

“…By integrating the predictive power of computational models and the data‐driven insights of AI, the synergy between these approaches has the potential to accelerate drug discovery, optimize treatment strategies, and usher in a new era of personalized medicine, benefiting patients, researchers, and the pharmaceutical industry as a whole.…”
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TAL-SRX: an intelligent typing evaluation method for KASP primers based on multi-model fusion by Xiaojing Chen, Xiaojing Chen, Jingchao Fan, Jingchao Fan, Shen Yan, Longyu Huang, Longyu Huang, Longyu Huang, Guomin Zhou, Guomin Zhou, Jianhua Zhang, Jianhua Zhang

“…Then, a hybrid neural network is constructed by combining ANN and LSTM to capture nonlinear relationships and extract complex features, while the Transformer algorithm is introduced to capture global dependencies in high-dimensional feature space. …”
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Building a composition-microstructure-performance model for C–V–Cr–Mo wear-resistant steel via the thermodynamic calculations and machine learning synergy by Shuaiwu Tong, Shuaijun Zhang, Chong Chen, Tao Jiang, Peng Li, Shizhong Wei

“…Furthermore, feature importance analysis, conducted using the Random Forest algorithm, revealed significant differences in the factors affecting sliding friction and abrasive wear. …”
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Hydropower system in the Yarlung-Tsangpo Grand Canyon can mitigate flood disasters caused by climate change by Fengbo Zhang, Qin Yang, Jianhua Wang, Huan Liu, Qinghui Zeng, Long Yan, Baolong Zhao, Jiaxuan Tang, Kang Zhao, Yining Zang, Wei Liu, Peng Hu

“…Here we evaluate the water-energy-ecosystem nexus in this hydropower system using the Water and Energy Transfer Processes in Large River Basins model and the Non-Dominated Sorting Genetic Algorithm III model. Key findings reveal that reservoir operations with medium replenishment flow (1000 m³ s−1) during dry periods achieve an optimal balance among hydropower generation annually (2231 × 108 kWh), flood mitigation (peak clipping rate 22.8%), and minimal ecosystem impact (eco-index 0.45). …”
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The Role of Immunohistochemistry as a Surrogate Marker in Molecular Subtyping and Classification of Bladder Cancer by Tatiana Cano Barbadilla, Martina Álvarez Pérez, Juan Daniel Prieto Cuadra, Mª Teresa Dawid de Vera, Fernando Alberca-del Arco, Isabel García Muñoz, Rocío Santos-Pérez de la Blanca, Bernardo Herrera-Imbroda, Elisa Matas-Rico, Mª Isabel Hierro Martín

“…Further research is required to determine the optimal combination of markers, establish a consensus diagnostic algorithm, and validate IHC through large-scale trials. …”
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Comparative performance evaluation of quartz and snail shell powders modified concrete: Mechanical, machine learning, and microstructural assessments by Md. Habibur Rahman Sobuz, Md. Kanan Chowdhury Tilak, SM Arifur Rahman, Fahim Shahriyar Aditto, Faiz Uddin Ahmed Shaikh, Md. Kawsarul Islam Kabbo, M Jameel, Md. Munir Hayet Khan

“…As seen by adding the optimal SSP replacements of eco-friendly concrete mixtures, it boosted mechanical strength while lowering carbon footprint, making it a sustainable building concrete construction.…”
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Transcriptional fingerprinting of regulatory T cells: ensuring quality in cell therapy applications by Zhang Cheng, Li-Jie Wang, Yuchi Honaker, Steven A. Cincotta, Claire E. Page, Sydney Vollhardt, Victor Yuan, S. Alice Long, Yuanyuan Xiao, Joshua N. Beilke, Joseph R. Arron, Jeffrey A. Bluestone

“…We employed a non-parametric algorithm to score Treg manufacturing products for their cell identity and expansion fingerprints.ResultsThe identity fingerprint reflects Treg cell identity by effectively distinguishing Treg from Teff cells irrespective of their activation status, with 100% sensitivity and specificity, while the expansion fingerprint discriminates expanded versus endogenous Treg or Teff cells. …”
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Acute kidney disease in hospitalized pediatric patients: risk prediction based on an artificial intelligence approach by Lingyu Xu, Siqi Jiang, Chenyu Li, Xue Gao, Chen Guan, Tianyang Li, Ningxin Zhang, Shuang Gao, Xinyuan Wang, Yanfei Wang, Lin Che, Yan Xu

“…Predictive models were constructed using eight machine learning algorithms and two ensemble algorithms, with the optimal model identified through AUROC. …”
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Machine learning-based integration develops relapse related signature for predicting prognosis and indicating immune microenvironment infiltration in breast cancer by Junyi Li, Shixin Li, Dongpo Zhang, Yibing Zhu, Yue Wang, Xiaoxiao Xing, Juefei Mo, Yong Zhang, Daixiang Liao, Jun Li

“…To address these limitations, this study systematically analyzed RNA-seq high-throughput data and combined 10 machine learning algorithms to construct 117 models. The optimal algorithm combination, StepCox[both] and ridge regression, was identified, and an immune-related gene signature (IRGS) composed of 12 genes was developed. …”
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Frailty in older adults patients: a prospective observational cohort study on subtype identification by Zhikai Yang, Chen Ji, Ting Wang, Wei He, Yuhao Wan, Min Zeng, Di Guo, Lingling Cui, Hua Wang

“…This study applied the K-means clustering algorithm to analyze 27 variables, determining the optimal cluster number using the Elbow method and Silhouette coefficient. …”
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Magnetic Resonance Imaging Texture Analysis Based on Intraosseous and Extraosseous Lesions to Predict Prognosis in Patients with Osteosarcoma by Yu Mori, Hainan Ren, Naoko Mori, Munenori Watanuki, Shin Hitachi, Mika Watanabe, Shunji Mugikura, Kei Takase

“…A support vector machine algorithm with 3-fold cross-validation was used to construct and validate the models. …”
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Blind deconvolution estimation by multi-exponential models and alternated least squares approximations: Free-form and sparse approach. by Daniel U Campos-Delgado, Omar Gutierrez-Navarro, Ricardo Salinas-Martinez, Elvis Duran, Aldo R Mejia-Rodriguez, Miguel J Velazquez-Duran, Javier A Jo

“…A least squares formulation is considered for both BDE algorithms. To overcome the nonlinear interaction in the decision variables, an alternating least squares (ALS) methodology iteratively solves both estimation problems based on non-negative and constrained optimizations. …”
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Segmentasi Pelanggan B2B dengan Model LRFM Menggunakan Algoritma Fuzzy C-Means pada Rotte Bakery by Dea Putri Ananda, Siti Monalisa

“…The results revealed that there are five optimal clusters for agent customers with a DBI value of 0.57, while outlet customers have four clusters with a DBI value of 0.49. …”
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Stochastic <i>H</i>_∞ Filtering of the Attitude Quaternion by Daniel Choukroun, Lotan Cooper, Nadav Berman

“…Thanks to the bilinear structure of the quaternion state-space model, the algorithm parameters are independent of the state. …”
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CSEPC: a deep learning framework for classifying small-sample multimodal medical image data in Alzheimer’s disease by Jingyuan Liu, Xiaojie Yu, Hidenao Fukuyama, Toshiya Murai, Jinglong Wu, Qi Li, Zhilin Zhang

“…Addressing this obstacle is crucial for improving diagnostic accuracy and optimizing treatment strategies for those affected by AD. …”
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A Deep Learning Method for Photovoltaic Power Generation Forecasting Based on a Time-Series Dense Encoder by Xingfa Zi, Feiyi Liu, Mingyang Liu, Yang Wang

“…Deep learning has become a widely used approach in photovoltaic (PV) power generation forecasting due to its strong self-learning and parameter optimization capabilities. In this study, we apply a deep learning algorithm, known as the time-series dense encoder (TiDE), which is an MLP-based encoder–decoder model, to forecast PV power generation. …”
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Vis/NIR Spectroscopy and Vis/NIR Hyperspectral Imaging for Non-Destructive Monitoring of Apricot Fruit Internal Quality with Machine Learning by Tiziana Amoriello, Roberto Ciorba, Gaia Ruggiero, Francesca Masciola, Daniela Scutaru, Roberto Ciccoritti

“…In this study, prediction models were developed based on a multilayer perceptron artificial neural network (ANN-MLP) combined with the Levenberg–Marquardt learning algorithm. Regarding the Vis/NIR spectrophotometer dataset, good predictive performances were achieved for TSS (R² = 0.855) and DM (R² = 0.857), while the performance for TA was unsatisfactory (R² = 0.681). …”
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Simple Yet Powerful: Machine Learning-Based IoT Intrusion System With Smart Preprocessing and Feature Generation Rivals Deep Learning by Kazim Kivanc Eren, Kerem Kucuk, Fatih Ozyurt, Omar H. Alhazmi

“…In contrast, classical machine learning techniques offer a more efficient alternative but are often overlooked due to a lack of focus on data pre-processing, which is critical for achieving optimal performance. Here we propose a classical machine learning system, built around a Random Forest classifier paired with a novel feature extraction algorithm adapted from Explainable Boosted Linear Regression (EBLR). …”
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