Ecological momentary interventions for mental health: A scoping review. by Andreas Balaskas, Stephen M Schueller, Anna L Cox, Gavin Doherty

“…Recent years have seen increased exploration of the use of sensors and machine learning, but the role of humans in the delivery of EMI is also varied. …”
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Integration of predictive and computational intelligent techniques: A hybrid optimization mechanism for PMSM dynamics reinforcement by Shaswat Chirantan, Bibhuti Bhusan Pati

“…We address the challenges of traditional control methods that struggle with the dynamics and nonlinear nature of PMSMs, offering a solution that leverages the predictive capabilities of MPC and the adaptive learning potential of neural networks. Our SNN-MPC model is contrasted with state-of-the-art genetic algorithm (GA) and ant colony optimization (ACO) methods through a comprehensive simulation analysis. …”
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RASGRF2 as a potential pathogenic gene mediating the progression of alcoholic hepatitis to alcohol-related cirrhosis and hepatocellular carcinoma by Zhengyuan Chen, Danfeng Fan, Tianyi Hang, Xiaoqing Yue

“…After screening with two machine learning algorithms, five shared genes remained. Combining the results of the immune infiltration and bulk transcriptome results from an independent validation cohort, the core shared gene was determined to be RASGRF2. …”
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An integrated toolbox for creating neuromorphic edge applications by Lars Niedermeier, Nikil Dutt, Jeffrey L Krichmar

“…spiking neural networks (SNNs) and neuromorphic models are believed to be more efficient in general and have more biological realism than the activation functions typically used in deep neural networks, transformer models and generative AI. SNNs have local learning rules, are able to learn on small data sets, and can adapt through neuromodulation. …”
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Erythrocyte modified controlling nutritional status as a biomarker for predicting poor prognosis in post-surgery breast cancer patients by Jingjing Hu, Jiaming Dong, Xiang Yang, Zhiyi Ye, Guoming Hu

“…The predictive effects of nutritional and inflammatory indicators on DFS were evaluated. Machine learning was used to evaluate and rank laboratory indicators, select relatively important variables to modify nutritional or inflammatory indicators with the best predictive power, and evaluate their predictive role in patients’ postoperative recurrence and metastasis. …”
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Comparative Analysis of YOLOv8 and HSV Methods for Traffic Density Measurement by Prof. I Gede Pasek Suta Wijaya, Muhamad Nizam Azmi, Ario Yudo Husodo

“…In contrast, the YOLOv8 segmentation method utilizes a deep learning approach to detect and segment vehicles, providing potentially more precise measurements. …”
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Three-Dimensional Digital Surgical Planning and Rapid Prototyped Surgical Guides in Bernese Periacetabular Osteotomy by Bruno Gonçalves Schröder e Souza, Flavia de Souza Bastos, Valdeci Manoel de Oliveira, Alfredo Chaoubah

“…Bernese periacetabular osteotomy (PAO) developed by Ganz is currently the treatment of choice for skeletally mature symptomatic patients with developmental dysplasia of the hip (DDH) without osteoarthritis. However, the steep learning curve and considerable number of severe complications lead surgeons to seek for alternatives to promote greater reproducibility and safety of this procedure. …”
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Digital intelligence technology and curriculum ideology in sports colleges: the mediating roles of teaching effectiveness and student engagement by Ziqi Wang, Xiangui Bu, Siyu Hong, Zixuan Jia, Zeqi Huang, Wenjun Wang

“…Student engagement accounted for a greater proportion of variance compared to teaching effectiveness, emphasizing the critical role of interactive learning in ideological and political education.DiscussionThis study introduces a novel chain mediation pathway—DIT → Teaching Effectiveness → Student Engagement → Curriculum Ideology—highlighting the synergistic relationship between teaching quality and learner participation. …”
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Study of tactics and personal security measures of the dialogue police during the protection of public order at mass events by O. A. Morhunov, I. V. Vlasenko

“…The scientific approach and the definition of new directions and technologies are impossible without the use of research studies of the scientific and pedagogical staff of higher education institutions with specific learning conditions. The article analyzes the work of the dialogue police, identifies directions for improving their activities in terms of serving at mass events. …”
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Application of Artificial Intelligence Models for Evapotranspiration Prediction along the Southern Coast of Turkey by Mohammed Majeed Hameed, Mohamed Khalid AlOmar, Siti Fatin Mohd Razali, Mohammed Abd Kareem Khalaf, Wajdi Jaber Baniya, Ahmad Sharafati, Mohammed Abdulhakim AlSaadi

“…For this purpose, twenty input combinations including hydrological and geographical parameters were introduced to three different approaches called multiple linear regression MLR, random forest RF, and extreme learning machine ELM. Moreover, in this study, large investigation was done, involving the establishment of 60 models and their assessment using ten statistical measures. …”
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A Novel Hybrid Model for Credit Risk Assessment of Supply Chain Finance Based on Topological Data Analysis and Graph Neural Network by Kosar Farajpour Mojdehi, Babak Amiri, Amirali Haddadi

“…Results demonstrate that the proposed BallMapper- Graph Neural Network (BM-GNN) model achieves higher accuracy and F1-scores, outperforming traditional machine learning approaches. Notably, incorporating network-based features alongside financial ratios yields the most favorable results in credit risk assessment. …”
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Code-Switching ASR for Low-Resource Indic Languages: A Hindi-Marathi Case Study by Hemant Palivela, Meera Narvekar, David Asirvatham, Shashi Bhushan, Vinay Rishiwal, Udit Agarwal

“…This work critically evaluates current methods and proposes improvements using modern deep-learning techniques to address the primary challenges in developing efficient ASR models for Hindi and Marathi. …”
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Seurat function argument values in scRNA-seq data analysis: potential pitfalls and refinements for biological interpretation by Mikhail Arbatsky, Ekaterina Vasilyeva, Veronika Sysoeva, Ekaterina Semina, Ekaterina Semina, Valeri Saveliev, Kseniya Rubina

“…Here we narrow our focus down to a small set of mathematical methods applied upon standard processing of scRNA-seq data: preprocessing, dimensionality reduction, integration, and clustering (using machine learning methods for clustering). Normalization and scaling are standard manipulations for the pre-processing with LogNormalize (natural-log transformation), CLR (centered log ratio transformation), and RC (relative counts) being employed as methods for data transformation. …”
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Polymers for the treatment of Alzheimer’s disease by Yunfeng Zhu, Haibin Xu, Chaoyan Yu, Wenting Jiang, Xiaowen Hou, Mingyue Ma, Ji Wu

“…It is a neurodegenerative disorder, and its main clinical symptoms include the loss of established memories, a decline in learning capacity, and the buildup of β-amyloid peptides. …”
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Children Who Experience Unintentional Injuries: Their Functional Profiles by Sara Rosenblum, Tal Nardi-Moses, Helly Goez, Naor Demeter

“…Sixty percent of the children in the research (injured) group had been prediagnosed with learning disabilities or attention deficit hyperactivity disorders, compared with no child in the control (uninjured) group. …”
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On the implications of artificial intelligence methods for feature engineering in reliability sector with computer knowledge graph by Heling Jiang, Yongping Xia, Changjie Yu, Zhao Qu, Huaiyong Li

“…To improve operational efficiency and lower long-term maintenance costs, policy ideas include standardizing data collection techniques, investing in real-time monitoring systems, and implementing machine learning-based predictive maintenance across industries.…”
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Text-Based Price Recommendation System for Online Rental Houses by Lujia Shen, Qianjun Liu, Gong Chen, Shouling Ji

“…In this paper, we analyzed the relationship between the description of each listing and its price, and proposed a text-based price recommendation system called TAPE to recommend a reasonable price for newly added listings. We used deep learning techniques (e.g., feedforward network, long short-term memory, and mean shift) to design and implement TAPE. …”
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Anomaly Detection for Time Series with Difference Rate Sample Entropy and Generative Adversarial Networks by Keke Gao, Wenbin Feng, Xia Zhao, Chongchong Yu, Weijun Su, Yuqing Niu, Lu Han

“…To emphasize the features of collected maker gas and overcome the low anomaly detection accuracy caused by the inadequate learning of the normal mode, this paper adopted a method of anomaly detection for time series with difference rate sample entropy and generative adversarial networks. …”
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Intercultural approach on photoprotection and skin cancer prevention in nursing students by Carla Cristina Calderón Cabezas, Angélica Salomé Herrera Molina, Yolanda Elizabeth Salazar Granizo, Jimena Alexandra Morales Guaraca, Paola Maricela Machado Herrera, Jacobo Cambil Martín

“…<br /><strong>Results:</strong> the intercultural practice of photoprotection in nursing students was related to three central categories: culture/health with cultural photoprotection care; environment with worldview and cultural environment; and promotion with learning and/or education needs on photoprotection respectively. …”
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Attention-based interactive multi-level feature fusion for named entity recognition by Yiwu Xu, Yun Chen

“…Recently, Deep Neural Networks (DNNs) have been extensively applied to NER tasks owing to the rapid development of deep learning technology. However, despite their advancements, these models fail to take full advantage of the multi-level features (e.g., lexical phrases, keywords, capitalization, suffixes, etc.) of entities and the dependencies between different features. …”
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