TelescopeML. II. Convolutional Neural Networks for Predicting Brown Dwarf Atmospheric Parameters by Ehsan (Sam) Gharib-Nezhad, Hamed Valizadegan, Natasha E. Batalha, Miguel J. S. Martinho, Ben W.P. Lew

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Intraoperative hypotension prediction in cardiac and noncardiac procedures: is HPI truly worthwhile? A systematic review and meta-analysis by Erfan Shirmohamadi, Reza Hosseini Dolama, Narjes Mohammadzadeh, Navid Ebrahimi, Negar Ghasemloo

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Anti-Tetanus Vaccination Is Associated with Reduced Occurrence and Slower Progression of Parkinson’s Disease—A Retrospective Study by Ariel Israel, Eli Magen, Eytan Ruppin, Eugene Merzon, Shlomo Vinker, Nir Giladi

“…<b>Background:</b> Parkinson’s disease (PD) is a neurodegenerative disorder that progressively damages the autonomic and central nervous systems, leading to hallmark symptoms such as resting tremor, bradykinesia, and rigidity. Despite extensive research, the underlying cause of PD remains unclear, and current treatments are unable to halt the progression of the disease. …”
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Spironolactone Reduces the Risk of Death in Veterans With Heart Failure With Preserved Ejection Fraction by Katherine E. Kurgansky, Rachel Parker, Luc Djousse, David R. Gagnon, Jacob Joseph

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Task Scheduling in Cloud Environment&#x2013;Techniques, Applications, and Tools: A Systematic Literature Review by Olanrewaju L. Abraham, Md Asri Bin Ngadi, Johan Bin Mohamad Sharif, Mohd Kufaisal Mohd Sidik

“…The paper offers a systematic literature review of task scheduling in cloud computing, introducing a novel classification taxonomy and a comparative review of various techniques. This taxonomy categorizes metaheuristic scheduling techniques based on scheduling algorithms, problem nature, task types, primary scheduling objectives, task-resource mapping, scheduling constraints, and testing environments. …”
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Neonatal and perinatal mortality in the urban continuum: a geospatial analysis of the household survey, satellite imagery and travel time data in Tanzania by Lenka Benova, Claudia Hanson, Aliki Christou, Aline Semaan, Peter M Macharia, Jessie Pinchoff, Andrea B Pembe

“…A three-category urbanicity measure (core urban, semi-urban and rural) was defined and compared with the binary DHS measure. Travel time to the nearest hospital was modelled using least-cost path algorithm for each cluster. …”
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Exploring the Realization of Creative Dimensions within the Metaverse: The Case of Tabriz Metropolis by Saied Jaffari namvar, Hossein Nazmfar, Ibrahim Taghav

“…To ascertain the relative importance of research components, 20 experts were consulted using the preferential weighting evaluation ratio algorithm (SOARA). …”
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Evolution and Knowledge Structure of Wearable Technologies for Vulnerable Road User Safety: A CiteSpace-Based Bibliometric Analysis (2000–2025) by Gang Ren, Zhihuang Huang, Tianyang Huang, Gang Wang, Jee Hang Lee

“…Contemporary research emphasizes context-adaptive interfaces, seamless V2X integration, and user-centered design, and future work should focus on lightweight communication protocols, adaptive sensory algorithms, and personalized safety profiles. …”
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Beamforming interferometry bathymetry method based on multi-coprime sensor array by Tian Zhou, Jiajun Shen, Jianjun Zhu, Wanyuan Zhang, Dongdong Peng

“…In this article, a multi-coprime array is proposed to address the problem, utilizing about half number of array elements and reducing hardware complexity compared with uniform linear array. Then, a low-complexity beamforming interferometry algorithm via multi-coprime array is proposed to reduce computational complexity. …”
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Modelling distillate output of a solar distiller with eco-friendly wood-based steam generation basin using machine learning model and starling murmuration optimizer by Mohammed Azmi Al-Betar, Otto L. Muskens, Karrar A. Hammoodi, Mohamed Abd Elaziz, Qusai Yousef Shambour, Salam Fraihat, Ammar H. Elsheikh

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Impacts of noise and interference on the bit error rate of the FBMC-OQAM modulation scheme in 5G systems by A. Androon, O. V. Tikhonova

“…The research results can be used in the development of 5G networks.…”
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Evaluating ensemble models for fair and interpretable prediction in higher education using multimodal data by Felipe Emiliano Arévalo-Cordovilla, Marta Peña

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Transcriptomic exploration yields novel perspectives on the regulatory network underlying trichome initiation in Gossypium arboreum hypocotyl by Yuxing Xie, Luying Yang, Zewei Zhao, Mingquan Ding, Yuefen Cao, Xin Hu, Junkang Rong

“…Utilizing three machine learning algorithms (SVM-RFE, Boruta, and LASSO), we consistently prioritized five key regulators: Ga02G1392 (TBR), Ga03G0474 (OMR1), Ga12G2860 (ACO1), Ga11G2117 (BBX19), and Ga12G2864 (CUE). …”
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The role of explainable AI in enhancing breast cancer diagnosis using machine learning and deep learning models by Zulfikar Ali Ansari, Manish Madhava Tripathi, Rafeeq Ahmed

“…This work presents a thorough assessment of XAI approaches classified by data kinds (imaging, genomic, and clinical), a comparative analysis of LIME (Local Interpretable Model-agnostic Explanations), SHAP (SHapley Additive exPlanations), and Grad-CAM, and highlights important issues and future directions of research. …”
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Ten-year cardiovascular risk estimation in type 2 diabetes in Europe using the novel SCORE2-Diabetes model by G. G. Arabidze, M. N. Mamedov, H. R. Akhundova

“…The article presents a validated prognostic score (SCORE2-Diabetes) developed by a group of European researchers in collaboration with the European Society of Cardiology (ESC) for 10-year cardiovascular risk in type 2 diabetes (T2D) in Europe. …”
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A novel method for asynchronous source localisation based on time of arrival measurements by Huijie Zhu, Sheng Liu, Zhiqiang Yao, Moses Chukwuka Okonkwo, Zheng Peng

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Integrating Machine Learning, SHAP Interpretability, and Deep Learning Approaches in the Study of Environmental and Economic Factors: A Case Study of Residential Segregation in Las... by Jingyi Liu, Yuxuan Cai, Xiwei Shen

“…By integrating traditional econometric techniques with machine learning and deep learning models, the study investigates (1) the correlation between housing prices, environmental quality, and segregation; (2) the differentiated impacts on various ethnic groups; and (3) the comparative effectiveness of predictive models. Among the tested algorithms, LGBM (Light Gradient Boosting) delivered the highest predictive accuracy and robustness. …”
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Comparison of Deep Learning Techniques in Detection of Sickle Cell Disease. by Mabirizi, Vicent, Kawuma, Simon, Kyarisiima, Addah, Bamutura, David, Atwiine, Barnabas, Nanjebe, Deborah, Oyesigye, Adolf Mukama

“…To this end, there exists a need to evaluate the SCD models using the same dataset. Thus, in this research study, we carried out a comparative investigation and evaluated predominate pre-trained models used to detect SCD using the same dataset to ascertain which one has the best accuracy. …”
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A novel fusion positioning navigation system for greenhouse strawberry spraying robot using LiDAR and ultrasonic tags by Haoran Tan, Xueguan Zhao, Hao Fu, Minli Yang, Changyuan Zhai

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Enhancing safety in surface mine blasting operations with IoT based ground vibration monitoring and prediction system integrated with machine learning by Mangalpady Aruna, Harsha Vardhan, Abhishek Kumar Tripathi, Satyajeet Parida, N. V. Raja Sekhar Reddy, Krishna Moorthy Sivalingam, Li Yingqiu, P. V. Elumalai

“…The study also employed Support Vector Regression (SVR), Gradient Boosting Regression (GBR), and Random Forest (RF) algorithms to predict Peak Particle Velocity (PPV) values. …”
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