Heat Transfer Enhancement in Heat Exchangers by Longitudinal Vortex Generators: A Review of Numerical and Experimental Approaches by Yidie Luo, Gongli Li, Nick S. Bennett, Zhen Luo, Adnan Munir, Mohammad S. Islam

“…Different from previous reviews that mainly focus on classical configurations and historical studies, this review also emphasizes recent developments in computational fluid dynamics and progress in interdisciplinary fields such as innovative materials, additive manufacturing, surface finishing, and machine learning. By bridging the gap between fluid dynamics, thermal enhancement, and emerging manufacturing technologies, this paper provides a forward-looking, comprehensive analysis that is valuable for both academic and industrial innovations.…”
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A local de-insulation method and its application in neural microneedle array by Xin Zhao, Chunrong Wei, Deguang Zhu, Xiaowei Yang, Guowei Han, Jin Ning, Qiang Gui, Rongyu Tang, Yijun Wang, Jingfeng Zhou, Zhaoxin Geng, Weihua Pei

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EDG-Net: Edge-Enhanced Dynamic Graph Convolutional Network for Remote Sensing Scene Classification of Mining-Disturbed Land by Xianju Li, Pan Kong, Weitao Chen, Wenxi He, Jian Feng, Jiangyuan Wang

“…Scene classification and mapping of surface mining-disturbed land can attain semantic-level information that is useful for monitoring mine geo-environment. …”
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Early Breast Cancer Prediction Using Thermal Images and Hybrid Feature Extraction-Based System by Doaa Youssef, Hanan Atef, Shaimaa Gamal, Jala El-Azab, Tawfik Ismail

“…The infrared energy emitted by the breast surface is highly related to its physiological characteristics. …”
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U-Shaped Dual Attention Vision Mamba Network for Satellite Remote Sensing Single-Image Dehazing by Tangyu Sui, Guangfeng Xiang, Feinan Chen, Yang Li, Xiayu Tao, Jiazu Zhou, Jin Hong, Zhenwei Qiu

“…In remote sensing single-image dehazing (RSSID), adjacency effects and the multi-scale characteristics of the land surface–atmosphere system highlight the importance of a network’s effective receptive field (ERF) and its ability to capture multi-scale features. …”
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Causes of baseflow variation in an inland river watershed of Northwest China by Mengwei Song, Hailong Liu, Quanlong Wu, Aminjon Gulakhmadov, Firdavs Shaimuradov

“…The formation mechanisms of baseflow are governed by multiple factors including watershed characteristics (area and topography) and runoff generation processes (rainfall versus snowmelt dominance). …”
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Nanotoxicity unveiled: Evaluating exposure risks and assessing the impact of nanoparticles on human health by Rohit Kumar, Akhilesh Kumar, Sweety Bhardwaj, Mohini Sikarwar, Sonam Sriwastaw, Gaurav Sharma, Madhu Gupta

“…Background: Nanomaterials have been widely used across medical and health sciences due to their unique physicochemical characteristics, versatile functionalisation, and remarkable tissue penetration abilities. …”
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Analysis of the 10-day ultra-marathon using a predictive XG boost model by Beat Knechtle, Elias Villiger, David Valero, Lorin Braschler, Katja Weiss, Rodrigo Luiz Vancini, Marilia S. Andrade, Volker Scheer, Pantelis T. Nikolaidis, Ivan Cuk, Thomas Rosemann, Mabliny Thuany

“…A machine learning model based on the XG Boost algorithm was built to predict running speed from the athlete´s age, gender, country of origin, country where the race takes place, the type of race and the kind of running surface. …”
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Enhancing drilling performance in 3D printed PLA implants application of PIV and ML models by K Shunmugesh, M Ganesh, R Bhavani, M. Adam Khan, M. Saravana Kumar, L. Rajeshkumar, Priyanka Mishra, Rajesh Jesudoss Hynes Navasingh, Angela Jennifa Sujana J, Jana Petru, Čep Robert

“…The inputs considered are spindle speed (SS), feed rate (fr), and drill diameter (dia), in relation to the output characteristics such as MRR, surface roughness (Ra and Rz), circularity, and cylindricity. …”
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Exploring Deep Clustering Methods in Vibro-Acoustic Sensing for Enhancing Biological Tissue Characterization by Robin Urrutia, Diego Espejo, Montserrat Guerra, Karin Vio, Thomas Suhn, Nazila Esmaeili, Axel Boese, Patricio Fuentealba, Alfredo Illanes, Christian Hansen, Victor Poblete

“…The observed differences in performance are linked to the intrinsic properties of the tissues, particularly surface characteristics such as friction and moisture, which affect signal consistency. …”
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Forecasting springtime rainfall in southeastern Australia using empirical orthogonal functions and neural networks by S. Marčelja

“…One such instance explored in this work is the prediction of austral springtime rainfall in SE Australia regions predominantly based on the surrounding ocean surface temperatures during the winter.</p> <p>In the first stage, I search for predictors by exploring correlations between the target rainfall and ocean surface temperatures at earlier times. …”
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Joint neural denoising and consolidation for portable handheld laser scan by T. Zhang, S. Filin

“…To date, point cloud denoising and consolidation (address of distribution and void regions) have been treated independently despite their complementary nature and their mutual dependence on the underlying surface representation. We argue that if treated jointly, richer shape context features can be learned and an improved enhancement framework can be derived. …”
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On the Control of the Technical Condition of Elevator Ropes Based on Artificial Intelligence and Computer Vision Technology by A. V. Panfilov, A. R. Yusupov, A. A. Korotkiy, B. F. Ivanov

“…The reliability of the results for the identification and qualification of defects exceeded 80%. Work on deep learning of the system continues.   Discussion and Conclusions. …”
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Prediction of performance and emission features of diesel engine using alumina nanoparticles with neem oil biodiesel based on advanced ML algorithms by M. S. Aswathanrayan, N. Santhosh, Srikanth Holalu Venkataramana, Kurugundla Sunil Kumar, Sarfaraz Kamangar, Amir Ibrahim Ali Arabi, Sameer Algburi, Osamah J. Al-sareji, A. Bhowmik

“…The alumina nanoparticles enhanced combustion through improved fuel atomization and oxidation due to their high surface area and catalytic effects. To further validate the effectiveness of RSM, the results are compared with the performance of several advance machine learning algorithms, including linear regression, decision tree, and random forest. …”
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Toward skillful forecasting of super El Niño events using a diffusion-based westerly wind burst parameterization by Chaopeng Ji, Mu Mu, Bo Qin, Tao Lian, Shijin Yuan, Jie Feng, Xunshu Song, Yuntao Wei, Guokun Dai, Jinyu Wang, Xianghui Fang

“…Consequently, DDPM produces more realistic eastern Pacific sea surface temperature anomaly warming patterns. These findings underscore WWB's accuracy as key to super El Niño prediction and demonstrate machine learning’s potential for WWB's parameterization.…”
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A Rice-Mapping Method with Integrated Automatic Generation of Training Samples and Random Forest Classification Using Google Earth Engine by Yuqing Fan, Debao Yuan, Liuya Zhang, Maochen Zhao, Renxu Yang

“…The spatial distribution characteristics of rice cultivation extracted by the LR algorithm were accurate and the performance was optimal. …”
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Role of unsafe medical practices and sexual behaviours in the hepatitis B and C syndemic and HIV co-infection in Rwanda: a cross-sectional study by Neil Gupta, Jean Damascene Makuza, Sabine Umuraza, Janvier Serumondo, Sabin Nsanzimana, Marie Paul Nisingizwe, Jean Olivier Twahirwa Rwema, Donatha Dushimiyimana, Dominique Savio Habimana, Alida Ngwije, Muhamed Semakula

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Subgrouping autism and ADHD based on structural MRI population modelling centiles by Clara Pecci-Terroba, Meng-Chuan Lai, Michael V. Lombardo, Bhismadev Chakrabarti, Amber N. V. Ruigrok, John Suckling, Evdokia Anagnostou, Jason P. Lerch, Margot J. Taylor, Rob Nicolson, Stelios Georgiades, Jennifer Crosbie, Russell Schachar, Elizabeth Kelley, Jessica Jones, Paul D. Arnold, Jakob Seidlitz, Aaron F. Alexander-Bloch, Edward T. Bullmore, Simon Baron-Cohen, Saashi A. Bedford, Richard A. I. Bethlehem

“…This has been a pivotal goal for neurodevelopmental research using both clinical and neuroanatomical features, though results thus far have again been inconsistent with regards to the number and characteristics of subgroups. Methods Here, we use population modelling to cluster a multi-site dataset based on global and regional centile scores of cortical thickness, surface area and grey matter volume. …”
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Computer-economical optimization method for solving inverse problems of determining electrophysical properties of objects in eddy current structroscopy by V. Ya. Halchenko, R. V. Trembovetska, V. V. Tychkov

“…The simultaneous determination of these parameters because of non-contact indirect measurements of the electromotive force (EMF) by surface eddy current probes over the surface object with the subsequent restoration of the parameter distributions along its thickness by numerical methods is an urgent task. …”
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Single-cell microbiota phenotyping reveals distinct disease and therapy-associated signatures in Crohn’s disease by Lisa Budzinski, Gi-Ung Kang, René Riedel, Toni Sempert, Leonie Lietz, René Maier, Janine Büttner, Bettina Bochow, Marcell T. Tordai, Aayushi Shah, Amro Abbas, Tanisha Momtaz, Jannike L. Krause, Robin Kempkens, Katrin Lehman, Gitta A. Heinz, Anne E. Benken, Stefanie Bartsch, Kathleen Necke, Ute Hoffmann, Mir-Farzin Mashreghi, Robert Biesen, Tilmann Kallinich, Tobias Alexander, Bosse Jessen, Carl Weidinger, Britta Siegmund, Andreas Radbruch, Anja Schirbel, Benjamin Moser, Hyun-Dong Chang

“…By multi-parameter microbiota flow cytometry (mMFC) we characterized the intestinal microbiota of 55 CD patients and 44 healthy controls for 11-parameters in total, comprising host-immunoglobulin coating and the presence of distinct surface sugar moieties. The data were analyzed by machine-learning to assess disease-specific marker patterns in the microbiota phenotype. mMFC captured detailed characteristics of CD microbiota and identified patterns to classify CD patients. …”
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