Identifying time patterns in Huntington’s disease trajectories using dynamic time warping-based clustering on multi-modal data by Alexia Giannoula, Audrey E. De Paepe, Ferran Sanz, Laura I. Furlong, Estela Camara

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Prediction of outcomes following intravenous thrombolysis in patients with acute ischemic stroke using serum UCH-L1, S100β, and NSE: a multicenter prospective cohort study employin... by Ming-Ya Luo, Yang Qu, Peng Zhang, Reziya Abuduxukuer, Li-Juan Wang, Li-Chong Yang, Zhi-Guo Li, Xiao-Dong Liu, Ce Han, Dan Li, Wei-Jia Wang, Dian-Ping Lv, Ming Liu, Jian Gao, Jing Xu, Yongfei Jiang, Hai-Nan Chen, Fu-Jin Li, Li-Ming Sun, Qi-Dong Sun, Yingbin Qi, Si-Yin Sun, Yu Zhang, Zhen-Ni Guo, Yi Yang

“…Objectives: We aimed to assess the predictive value of serum brain injury biomarkers for 3-month outcomes in AIS patients treated with IVT, using an ML-based model. …”
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Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments by Billel Essaid, Hamza Kheddar, Noureddine Batel, Muhammad E. H. Chowdhury

“…The rise of artificial intelligence (AI) has introduced innovative strategies to address these limitations. …”
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Application of Categorical Boosting to Modelling the Friction Behaviour of DC05 Steel Sheets in Strip Drawing Test by Marek Szewczyk, Krzysztof Szwajka, Sherwan Mohammed Najm, Salwa O Mohammed

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A Novel Hybrid Deep Learning Framework for Evaluating Field Evapotranspiration Considering the Impact of Soil Salinity by Yao Rong, Weishu Wang, Peijin Wu, Pu Wang, Chenglong Zhang, Chaozi Wang, Zailin Huo

“…Specifically, we integrated physical constraints from process models (Penman‐Monteith or Shuttleworth‐Wallace) and salinity‐induced stomatal stress mechanisms into the DL algorithm, and evaluated its performance by comparing four diverse scenarios. …”
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Energy Management of Industrial Energy Systems via Rolling Horizon and Hybrid Optimization: A Real-Plant Application in Germany by Loukas Kyriakidis, Rushit Kansara, Maria Isabel Roldán Serrano

“…To solve the resulting nonlinear and constrained optimization problem at each RHA iteration, we propose a novel hybrid algorithm that combines Bayesian optimization (BO) with the Interior Point OPTimizer (IPOPT). …”
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Intelligent agriculture: deep learning in UAV-based remote sensing imagery for crop diseases and pests detection by Hongyan Zhu, Hongyan Zhu, Chengzhi Lin, Chengzhi Lin, Gengqi Liu, Gengqi Liu, Dani Wang, Dani Wang, Shuai Qin, Shuai Qin, Anjie Li, Anjie Li, Jun-Li Xu, Yong He

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Drilling Condition Identification Method for Imbalanced Datasets by Yibing Yu, Huilin Yang, Fengjia Peng, Xi Wang

“…Additionally, classification loss values were reduced by 0.32, 0.3315, 0.2893, and 0.2246, respectively. …”
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Selection and Identification of a Model of Elasto-Viscoplasticity of the Filled Fluorocomposite according to Free and Constrained Compression Tests by D. S. Petukhov, A. A. Adamov, I. E. Keller

“…Tests for constrained compression were performed for two values of the strain rate, and for free compression – for three values of the strain rate in the range of 10-6 – 10-3 s-1. …”
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Cooperative and Hierarchical Optimization Design of Shipboard MVDC System for Adapting to Large, Pulsed Power Load by Zhimeng Liu, Yongbao Liu, Youhong Yu, Rui Yang

“…Supplying power to large, pulsed power loads in shipboard medium voltage direct current integrated power systems is challenging due to the limited dynamic power responsiveness of the gas turbine. …”
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Machine learning applications in the analysis of sedentary behavior and associated health risks by Ayat S Hammad, Ayat S Hammad, Ali Tajammul, Ismail Dergaa, Ismail Dergaa, Ismail Dergaa, Maha Al-Asmakh, Maha Al-Asmakh

“…When integrated with wearable sensor data and validated in real-world settings, these models can enhance the scalability and precision of AI-driven interventions. …”
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TradeWise: Towards Context-Aware Stock Market Predictions with Sentiment and Political Insights by Andreas Marpaung, David Masterson

“…Our novel approach suggests that sentiment and political insights, when processed and integrated effectively, offer substantial predictive value that could refine the accuracy of financial prediction models. …”
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MEMS and IoT in HAR: Effective Monitoring for the Health of Older People by Luigi Bibbò, Giovanni Angiulli, Filippo Laganà, Danilo Pratticò, Francesco Cotroneo, Fabio La Foresta, Mario Versaci

“…In response to this need, developing integrated digital solutions, such as IoT based wearable devices combined with artificial intelligence applications, offers a technological platform for creating Ambient Intelligence (AI) and Assisted Living (AAL) environments. …”
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Digital augmentation of aftercare for patients with anorexia nervosa: the TRIANGLE RCT and economic evaluation by Janet Treasure, Katie Rowlands, Valentina Cardi, Suman Ambwani, David McDaid, Jodie Lord, Danielle Clark Bryan, Pamela Macdonald, Eva Bonin, Ulrike Schmidt, Jon Arcelus, Amy Harrison, Sabine Landau

“…For example, a transition service adapted to the stage of illness (like the First episode and Rapid Early intervention for Eating Disorders (FREED) model of outpatient care) may be of value. Furthermore, flexible integration between the range of services and community support is essential to cover and respond to the variable range of needs in this patient group. …”
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Machine learning-driven nanoparticle toxicity by Zied Hosni, Sofiene Achour, Fatma Saadi, Yangfan Chen, Mohammed Al Qaraghuli

“…The integration of Shapley Additive exPlanations (SHAP) values provided an interpretative insight into the predictive models, allowing for a quantitative assessment of feature impact. …”
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Neuro-fuzzy inference system and white shark optimization of coagulation-flocculation of aquaculture wastewater treatment by A.F. Mohamed, H. Rezk

“…Therefore, the objective of this study is determining the optimal operating condition of coagulation-flocculation through optimizing the values of the three input parameters.METHODS: Artificial intelligence and recent optimzation algorithms are integrated to achieve the purpose of this study work. …”
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Nonuniformity Correction Method of Infrared Detector Based on Statistical Properties by Li Dandan, Ding Xiang, Chai Mengyang, Ma Chao, Sun Dexin

“…First, the pixel points of all images are reordered according to their pixel values to provide a uniform reorganisation data. Then, the linear correlated region based on the recombined data is extracted using a judgment algorithm that processes the linear correlations of multiple regions to simulate the detector's response curve and find the nonuniformity correction coefficient of each pixel. …”
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Photoprotective activity from Colombian Caribbean brown algae using HPLC-DAD metabolic profiling by MCR-ALS data analysis by Sara P. Abril, Natalia Rincón-Díaz, Mónica Puyana, Leonardo Castellanos, Freddy A. Ramos

“…These findings were correlated with the HPLC-DAD metabolic profile using the Multivariate Curve Resolution- Alternating Least Squares (MCR-ALS) algorithm and multivariate data analysis tools. Extracts from Canistrocarpus cervicornis (CCe) and Stypopodium zonale (SS) presented the most promising photoprotective activity. …”
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Hedge-Algebra-Based Phase-Locked Loop for Distorted Utility Conditions by Dinko Vukadinović, Tien Duy Nguyen, Cat Ho Nguyen, Nhu Lan Vu, Mateo Bašić, Ivan Grgić

“…Optimized fuzziness parameters and linguistic rule base of the HAC are obtained by a genetic algorithm using the integral of absolute error as the performance index during optimization. …”
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Machine Learning to Select Experiments Driven by Fundamental Science and Applications for Targeted Nuclear Data Improvement by D. Neudecker, T. E. Cutler, M. Devlin, P. Brain, N. Gibson, M. J. Grosskopf, M. W. Herman, J. Hutchinson, T. Kawano, A. Khatiwada, N. Kleedtke, E. Leal-Cidoncha, R. C. Little, A. E. Lovell, A. Stamatopoulos, E. C. Thompson, S. A. Vander Wiel, E. Williamson

“…They are contrasted to application-driven, integral, data where one or few resulting values inform a broad set of nuclear data across several nuclides and energies. …”
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