Robust self supervised symmetric nonnegative matrix factorization to the graph clustering by Yi Ru, Michael Gruninger, YangLiu Dou

“…In addition, R3SNMF integrates a graph-boosting method to improve how relationships within the network are represented. …”
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Green Synthesis of Anti-Aging Gel Mask Contains Essential Oils Based Nanoemulsions by Hayder Kadhim Drais, Falah H. Ihmedee

“…These oils are recognized for their anti-inflammatory, antioxidant, antiseptic, and immune-boosting properties, making them ideal candidates for counteracting the effects of aging. …”
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Examining the role of Chinese language learners' grit and self-efficacy on their engagement in artificial intelligence-driven settings by Jingjing Chen

“…Practical recommendations are aimed at enhancing learners' self-efficacy and grit, thus boosting engagement. These results contribute to a broader picture of SDT's application in AI-driven settings, offering ground for further research into motivational processes in such learning.…”
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ChatGPT’s Usability in Expository Writing in AI-Enabled Classrooms: Perceptions of Tertiary Students and Teachers by Nikko Domingo, Rachelle Lintao

“…Additionally, they appreciate its ease of use and its role in boosting writing confidence. Teachers recognize ChatGPT's positive impact on the writing process, particularly in structuring essays and refining grammar, yet acknowledge concerns about accuracy. …”
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Designing Predictive Analytics Frameworks for Supply Chain Quality Management: A Machine Learning Approach to Defect Rate Optimization by Zainab Nadhim Jawad, Balázs Villányi

“…The framework employs advanced ML algorithms, including extreme gradient boosting (XGBoost), support vector machines (SVMs), and random forests (RFs), to accurately predict defect rates and derive actionable insights for supply chain optimization. …”
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Machine Learning for Prediction of Relapses in Multiple Drug Resistant Tuberculosis Patients by A. S. Аlliluev, O. V. Filinyuk, E. E. Shnаyder, S. V. Аksenov

“…Analysis of the characteristics of relapse prediction models in cured MDR TB patients using machine learning algorithms including decision tree, random forest, gradient boosting, and logistic regression using K-block stratified validation revealed high sensitivity (0.74 ± 0.167; 0.91 ± 0.17; 0.91 ± 0.14; 0.91 ± 0.16, respectively) and specificity (0.97 ± 0.03; 0.98 ± 0.02; 0.98 ± 0.02; 0.98 ± 0.02, respectively).Five main predictors of relapse in cured MDR-TB patients were identified: repeated courses of chemotherapy; length of history of tuberculosis; destructive process in the lungs; total duration of treatment less than 22 months; and use of less than five effective anti-TB drugs in the regimen of chemotherapy.…”
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Employing visual thinking skills in the techniques of advertising art by Bydaa Sabih Al-Gharawi

“…The conclusions showed that there is a positive relation of statistical indication between visual thinking skills and teaching the subject of advertisement art techniques in a balanced form which helped on boosting concept abilities in the way that fits with art learner. …”
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IGF1 and NRG1 Enhance Proliferation, Metabolic Maturity, and the Force-Frequency Response in hESC-Derived Engineered Cardiac Tissues by Cassady E. Rupert, Kareen L. K. Coulombe

“…This study demonstrates the therapeutic potential of IGF1 for boosting proliferation and NRG1 for promoting metabolic and contractile maturation in engineered human cardiac tissue.…”
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The Impact of Artificial Intelligence on the Future Business World by Hebah Y. AlQato

“…The advantages of AI in terms of boosting productivity, enriching consumer experiences, and encouraging creativity and development are apparent, even though there are some challenges that need to be resolved. …”
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Transcending the urban–rural dichotomy: inequality in urban green space availability among urban neighbourhoods, urban villages and rural villages in Guangzhou, China by Fubin Luo, Yunzheng Zhang, Luyang Zhang

“…Urban green spaces (UGS) are integral to sustainable urban development, yet the urbanization process has resulted in unequal distributions of green resources across different neighbourhoods. …”
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Explainable machine learning framework for biomarker discovery by combining biological age and frailty prediction by Xiheng Wang, Jie Ji

“…Then, SHapley Additive exPlanations (SHAP) analysis was conducted on the selected models. CatBoost performed the best in the BA predictor, and Gradient Boosting performed the best in the frailty predictor. …”
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Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine) by Chuin-Hen Liew, Song-Quan Ong, David Chun-Ern Ng

“…We validated AdaBoost as the best to predict COVID-19 hospitalization among children. …”
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Cross-modal gated feature enhancement for multimodal emotion recognition in conversations by Shiyun Zhao, Jinchang Ren, Xiaojuan Zhou

“…In practical applications, such as video-based recruitment interviews, customer service, health monitoring, intelligent personal assistants, and online education, ERC can facilitate the analysis of emotional cues, improve decision-making processes, and enhance user interaction and satisfaction. …”
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Efficient purification of CrocinI from saffron stigmas using antisolvent precipitation to implications for food technology by Elmira Fotouhi, Fateme Mirzajani, Hassan Rezadoost, Mohammad Hooshyari Ardakani

“…Compared to this, the use of ethyl acetoacetate as the antisolvent increased the crocin-I content from 26 to 47%. This process also reduced undesired components such as picrocrocin. …”
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Predictive modeling of ultimate tensile strength in dissimilar friction stir welded aluminum alloys via machine learning approach by Meghavath Mothilal, Atul Kumar

“…It proposes that the utilisation of these models can significantly enhance production processes and optimise material performance in industrial applications. …”
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Changes in the Distribution of Thermokarst Lakes on the Qinghai-Tibet Plateau from 2015 to 2020 by Rongrong Wei, Xia Hu, Shaojie Zhao

“…The results provide a scientific reference for the assessment and prediction of dynamic changes in thermokarst lakes on the QTP in the future, which will have important scientific significance for the studies of carbon and water processes in alpine ecosystems.…”
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Potential Illicit Financial Flow Risks in Ghana’s Gold-for-Oil Transaction by Fred M. Dzanku, Adubea J. Hall, Ama A. Ahene-Codjoe, Abigail A. Tetteh, Angela A. Alu

“…Second, it provides a political economy overview of the policy, highlighting the governance issues surrounding the policy’s formulation and implementation processes. Third, it examines existing legal and regulatory frameworks, asking if due process was followed in these processes. …”
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Nano/Micro-Enabled Modification and Innovation of Conventional Adjuvants for Next-Generation Vaccines by Xingchi Liu, Xu Yang, Lu Tao, Xuanchen Li, Guoqiang Chen, Qi Liu

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An In-depth Investigation of OBIA Classification with High-Resolution Imagery: Unravelling the Explanations Behind Deep Learning and Machine Learning by E. O. Yilmaz, T. Kavzoglu

“…In the segmentation stage, a multiresolution segmentation approach was employed, and classification process was conducted using a Convolutional Neural Network (CNN) and Extreme Gradient Boosting (XGBoost). …”
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An interpretable and stacking ensemble model for predicting heat and mass transfer of desiccant wheel by Mengyang Li, Liu Chen

“…Coefficient of Determination (R2), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE) were used to measure this stacking model: the process side outlet temperature (R2 = 0.9467, RMSE=1.5239, and MAE = 1.2721), the process side outlet humidity ratio (R2 = 0.9743, RMSE = 0.5728, MAE = 0.4531). …”
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