Intelligent collaborative management and control platform for continuous mining equipment in open-pit mines by Zhiyong LEI, Xiaolong MA, Shujun ZHAO, Shiming ZHANG, Bin YAN

“…The platform integrates advanced technologies, including dual-ring network transmission, network security protocols, multi-machine cooperative control, digital twin modeling, and big data analytics, facilitating effective coordination among coal miners, transfer machines, unloaders, and conveyors for seamless continuous mining operations.Three critical technical challenges are addressed: ① The implementation of dual-ring network transmission technology reduces data transmission latency and enhances network stability. ② A secure network transmission framework has been developed to safeguard data confidentiality and integrity. ③ The multi-machine cooperative control system incorporates data acquisition, process control, and 3D visualization modules, employing real-time monitoring and optimized control algorithms to boost mining and transportation efficiency while ensuring the continuity of multi-machine operations. …”
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Improving the Performance of Electrotactile Brain–Computer Interface Using Machine Learning Methods on Multi-Channel Features of Somatosensory Event-Related Potentials by Marija Novičić, Olivera Djordjević, Vera Miler-Jerković, Ljubica Konstantinović, Andrej M. Savić

“…We systematically tested classification performance using machine learning algorithms, including logistic regression, k-nearest neighbors, support vector machines, random forests, and artificial neural networks. …”
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Impact of climate change on the potential global prevalence of Macrophomina phaseolina (Tassi) Goid. under several climatological scenarios by Peter F. Farag, Dalal Hussien M. Alkhalifah, Shimaa K. Ali, Aya I. Tagyan, Wael N. Hozzein

“…Maximum Entropy (MaxEnt) model was used to predict the spatial distribution of this fungus throughout the world while algorithms of DIVA-GIS were chosen to confirm the predicted model.ResultsBased on the Jackknife test, minimum temperature of coldest month (bio_6) represented the most effective bioclimatological parameter to fungus distribution with a 52.5% contribution. …”
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Hemorrhage risk associated with triple antithrombotic therapy: a focused real-world pharmacovigilance disproportional analysis study by Kannan Sridharan, Gowri Sivaramakrishnan

“…Conclusion This study highlights the elevated hemorrhage risk associated with TAT, particularly with rivaroxaban, while apixaban appears safer in terms of bleeding and mortality. …”
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The effect of implementing parenteral nutrition guideline on growth and clinical outcomes in preterm infants: a comparative study by Majid Mahallei, Lida Gorbani, Mohammad Bagher Hoseini, Elnaz Shaseb, Bahareh Mehramuz, Khatereh Rezazadeh

“…The PRE group received individualized PN formulations based on clinician discretion, while the POST group received PN guided by a newly introduced, stepwise algorithmic protocol aiming to optimize early protein and energy intake. …”
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A Lightweight Method for Detecting Bearing Surface Defects Based on Deep Learning and Ontological Reasoning by Xiaolin Shi, Haisong Xu, Han Zhang, Yi Li, Xinshuo Li, Fan Yang

“…The recognition accuracy is ensured while keeping the model lightweight. Combined with ontological reasoning, it is able to determine the repairability of defects, which provides a reliable basis for the maintenance decision of bearings. …”
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Perbandingan Klasifikasi Antara KNN dan Naive Bayes pada Penentuan Status Gunung Berapi dengan K-Fold Cross Validation by Firman Tempola, Miftah Muhammad, Amal Khairan

“…While for data validation use k-fold cross validation. …”
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New Challenging Systemic Therapies for Juvenile Scleroderma: A Comprehensive Review by Chiara Sassetti, Claudia Borrelli, Martha Mazuy, Cristina Guerriero, Donato Rigante, Susanna Esposito

“…Large, multicenter, long-term trials are urgently needed to establish safety, efficacy, and optimal treatment algorithms that are tailored to the pediatric population.…”
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MMLT: Efficient object tracking through machine learning-based meta-learning by Bibek Das, Asfak Ali, Suvojit Acharjee, Jaroslav Frnda, Sheli Sinha Chaudhuri

“…Object tracking in computer vision is challenging due to the complexities of spatiotemporal data, including occlusions, abrupt motion changes, temporal coherence, object identity maintenance, and scale variations. While Deep learning algorithms address these challenges, however, they typically require significant computational resources, exhibit high complexity, and demand large amounts of training data. …”
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Applicability Evaluation of Provincial Precipitation Real-time Analysis Product in Beijing by Zhao Wenfang, Wang Huiying, Meng Huifang, Miao Yupeng, Huang Mingming, Fan Min, Tang Wei

“…The intensity of light rain exceeds the observation, while the spatial distribution difference of bias is evident. …”
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Neural Networks vs. Regression: A Comparative Analysis in Medical Data Processing by Minodora ANDOR, Gheorghe Ioan MIHALAŞ

“…The regression model followed standard statistical guidelines, while the FFNN required optimization of hyperparameters, including the number of layers, activation functions, learning rate, and  optimization algorithms. …”
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Efficient evidence selection for systematic reviews in traditional Chinese medicine by Yizhen Li, Zhe Huang, Zhongzhi Luan, Shujing Xu, Yunan Zhang, Lin Wu, Darong Wu, Dongran Han, Yixing Liu

“…Results Our finding demonstrated that the new method accurately selected potential literature based on consistent criteria while significantly reducing the time required for the process. …”
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Machine learning-driven development of a stratified CES-D screening system: optimizing depression assessment through adaptive item selection by Ruo-Fei Xu, Zhen-Jing Liu, Shunan Ouyang, Qin Dong, Wen-Jing Yan, Dong-Wu Xu

“…Abstract Objective To develop a stratified screening tool through machine learning approaches for the Center for Epidemiologic Studies Depression Scale (CES-D-20) while maintaining diagnostic accuracy, addressing the efficiency limitations in large-scale applications. …”
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Exploring suicidal thoughts among prospective university students: a study with applications of machine learning and GIS techniques by Mohammed A. Mamun, Firoj Al-Mamun, Md Emran Hasan, Nitai Roy, Moneerah Mohammad ALmerab, David Gozal, Md. Shakhaoat Hossain

“…Logistic regression analysis identified significant risk factors, while Machine Learning algorithms, including CatBoost and K-Nearest Neighbors, were used for prediction. …”
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Artificial Intelligence Models Accuracy for Odontogenic Keratocyst Detection From Panoramic View Radiographs: A Systematic Review and Meta‐Analysis by Reyhaneh Shoorgashti, Mohadeseh Alimohammadi, Sana Baghizadeh, Bahareh Radmard, Hooman Ebrahimi, Simin Lesan

“…Accurate diagnosis is vital for effective management, but manual image interpretation can be inconsistent. While deep learning algorithms in AI have shown promise in improving diagnostic accuracy for OKCs, their performance across studies is still unclear. …”
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Gene selection based on adaptive neighborhood-preserving multi-objective particle swarm optimization by Sumet Mehta, Fei Han, Muhammad Sohail, Bhekisipho Twala, Asad Ullah, Fasee Ullah, Arfat Ahmad Khan, Qinghua Ling

“…Traditional optimization algorithms often produce inconsistent and suboptimal results, while failing to preserve local data structures limiting both predictive accuracy and biological interpretability. …”
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Using large language models for enhanced fraud analysis and detection in blockchain based health insurance claims by Ruba Islayem, Senay Gebreab, Walaa AlKhader, Ahmad Musamih, Khaled Salah, Raja Jayaraman, Muhammad Khurram Khan

“…The architecture, sequence diagrams, and implementation algorithms outline the development process, while testing scenarios demonstrate the system’s ability to detect fraud such as inflated costs, unnecessary treatments, and unrendered services. …”
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A “giant bomb” in acute myocardial infarction due to coronary artery aneurysm: a case report by Jin Chen, Wei Du, Jianyu Jiang, Liugang Xu, Liugang Xu

“…The novel pathomechanism of intra-aneurysmal thrombosis secondary to pathological flow dynamics—characterized by endothelial shear stress perturbation and blood stasis—has been rarely documented. While existing literature describes therapeutic applications of surgical repair, percutaneous intervention, and pharmacotherapy in coronary artery aneurysm management, no consensus-driven protocol has been established, reflecting critical knowledge gaps in risk-stratified treatment algorithms for thrombus-laden aneurysms.Case outlineA 51-year-old female presenting with acute ST-segment elevation myocardial infarction underwent emergency coronary angiography, revealing a large right coronary artery aneurysm with significant intra-aneurysmal thrombus burden. …”
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Monitoring the antibiotic resistance in the intensive care unit of a multidisciplinary hospital by V. Yu. Zemko, V. K. Okulich, A. M. Dzyadz’ko

“…It is necessary to monitor the resistance of common microorganisms to certain antibiotics in order to develop algorithms for rational antibacterial treatment in each hospital.…”
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Cropping and Transformation Features of Non-Grain Cropland in Mainland China and Policy Implications by Yizhu Liu, Ge Shen, Tingting He

“…The parcels that were transferred into forest or grassland mainly appeared in southern and Inner Mongolia, respectively, while the parcels in northern and central areas mostly continued cropping. …”
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