Double-diffusive magnetoconvection in a tilted porous parallelogrammic domain with discrete heated-cooled segments: Leveraging machine learning and CFD approach by P. Ravindra, M. Sankar, Suresh Rasappan, Wardah Abdullah Al Majrafi, Pugalarasu Rajan, S. Sanal Kumar

Get full text

Functional mapping of human dynamin-1-like GTPase domain based on x-ray structure analyses. by Julia Wenger, Eva Klinglmayr, Chris Fröhlich, Clarissa Eibl, Ana Gimeno, Manuel Hessenberger, Sandra Puehringer, Oliver Daumke, Peter Goettig

Get full text

PHILOSOPHICAL AND ANTHROPOLOGICAL IMPORTANCE OF DEVELOPMENT OF ARTIFICIALLY CREATED INTELLIGENT SYSTEMS by Yu. D. Gensitskiy

“…Such system becomes smarter, including the intelligent writing of internal cognitive function, that the ability to rewrite their existing cognitive function to make it work better. …”
Get full text

A Comparison of Approaches for Segmenting the Reaching and Targeting Motion Primitives in Functional Upper Extremity Reaching Tasks by Kyle L. Jackson, Zoran Duric, Susannah M. Engdahl, Anthony C. Santago, Siddhartha Sikdar, Lynn H. Gerber

“…There is growing interest in the kinematic analysis of human functional upper extremity movement (FUEM) for applications such as health monitoring and rehabilitation. …”
Get full text

Large-scale urban building function mapping by integrating multi-source web-based geospatial data by Wei Chen, Yuyu Zhou, Eleanor C. Stokes, Xuesong Zhang

“…Morphological (e.g. shape, size, and height) and function (e.g. working, living, and shopping) information of buildings is highly needed for urban planning and management as well as other applications such as city-scale building energy use modeling. …”
Get full text

Using Machine Learning to Predict Cognitive Decline in Older Adults From the Chinese Longitudinal Healthy Longevity Survey: Model Development and Validation Study by Hao Ren, Yiying Zheng, Changjin Li, Fengshi Jing, Qiting Wang, Zeyu Luo, Dongxiao Li, Deyi Liang, Weiming Tang, Li Liu, Weibin Cheng

“…ObjectiveThe objective of this study was to explore the application of machine learning (ML) to integrate blood biomarkers, life behaviors, and disease history to predict the decline in cognitive function. …”
Get full text

Emerging Diagnostic Approaches for Musculoskeletal Disorders: Advances in Imaging, Biomarkers, and Clinical Assessment by Rahul Kumar, Kiran Marla, Kyle Sporn, Phani Paladugu, Akshay Khanna, Chirag Gowda, Alex Ngo, Ethan Waisberg, Ram Jagadeesan, Alireza Tavakkoli

“…Molecular imaging and biochemical markers such as CTX-II (C-terminal cross-linked telopeptides of type II collagen) and PINP (procollagen type I N-propeptide) provide early, objective indicators of tissue degeneration and bone turnover, while genetic and epigenetic profiling can elucidate individual patterns of susceptibility. Point-of-care ultrasound and portable diagnostic devices have expanded real-time imaging and functional assessment capabilities across diverse clinical settings. …”
Get full text

Effectiveness of stationary cycling with electromyographic biofeedback on neuromuscular control and function in individuals with knee osteoarthritis: a feasibility study by Chia-Ming Chang, Huynh Chung, Horng-Chaung Hsu, Li-Tzu Chen, Ruei-Yi Lin, Hsiu-Chen Lin

“…Abstract Background To evaluate the effects of stationary cycling with electromyographic (EMG) biofeedback on neuromuscular control and function in individuals with knee osteoarthritis (OA). …”
Get full text

Application of Machine Learning Methods for Identifying Wave Aberrations from Combined Intensity Patterns Generated Using a Multi-Order Diffractive Spatial Filter by Paval. A. Khorin, Aleksey P. Dzyuba, Aleksey V. Chernykh, Muhammad A. Butt, Svetlana N. Khonina

Get full text

Does neural computation feel like something? by Albert Gidon, Jaan Aru, Matthew E. Larkum, Matthew E. Larkum

Get full text

An Implementation of Creep Test Assisting System with Dial Gauge Needle Reading and Smart Lighting Function for Laboratory Automation by Dezheng Kong, Nobuo Funabiki, Shihao Fang, Noprianto, Mitsuhiro Okayasu, Pradini Puspitaningayu

Get full text

The use of brain-machine interface, motor imagery, and action observation in the rehabilitation of individuals with Parkinson's disease: A protocol study for a randomized clinical... by Kátine Marchezan Estivalet, Tatiana Salayaran de Aguiar Pettenuzzo, Natália Lopes Mazzilli, Luis Fernando Ferreira, Fernanda Cechetti

“…Each participant will be assessed at three points: pre-intervention, post-intervention, and at a follow-up four weeks after the intervention ends. …”
Get full text

A Multi-Input Multi-Output Considering Correlation and Hysteresis Prediction Method for Gravity Dam Displacement with Interpretative Functions by Bo Xu, Yuan Yao, Xuan Wang, Linsong Sun, Bin Ou, Yanming Zhang

Get full text

Deep-Learning-Driven Insights into Nitrogen Leaching for Sustainable Land Use and Agricultural Practices by Caixia Hu, Jie Li, Yaxu Pang, Lan Luo, Fang Liu, Wenhao Wu, Yan Xu, Houyu Li, Bingcang Tan, Guilong Zhang

“…A machine learning (ML) model for predicting nitrate leaching was then developed, with the random forest (RF) model outperforming the support vector machine (SVM), extreme gradient boosting (XGBoost), and convolutional neural network (CNN) models, achieving an R² of 0.75. …”
Get full text

Prediction of Lithium-Ion Battery State of Health Using a Deep Hybrid Kernel Extreme Learning Machine Optimized by the Improved Black-Winged Kite Algorithm by Juncheng Fu, Zhengxiang Song, Jinhao Meng, Chunling Wu

“…First, to address the limitations of traditional extreme learning machines (ELMs) in capturing non-linear features and their poor generalization ability, the concepts of auto encoders (AEs) and hybrid kernel functions are introduced to enhance ELM, resulting in the establishment of the DHKELM model for SOH prediction. …”
Get full text

CLU, FOS, and CXCL8 as diagnostic biomarkers for heart failure progression post-acute myocardial infarction: an integrated RNA-Seq and multi-machine learning study by Jingjing Wei, Peng Yu, Peng Yu, Yucai Hu, Lijie Qiao, Lijie Qiao, Bin Li, Bin Li, Haitao Li, Shiyang Xie, Zhengwei Dong, Aolong Wang, Yilin Zhang, Xinlu Wang, Yongxia Wang, Mingjun Zhu

“…Subsequently, candidate biomarkers were identified using machine learning and the MCODE plugin, with ROC used to describe the accuracy. …”
Get full text

Dynamic, Interpretable, Machine Learning–Based Outcome Prediction as a New Emerging Opportunity in Acute Ischemic Stroke Patient Care: A Proof-of-Concept Study by Ivan Petrović, Sava Njegovan, Olivera Tomašević, Dmitar Vlahović, Sonja Rajić, Željko Živanović, Isidora Milosavljević, Ana Balenović, Nikola Jorgovanović

Get full text

Clinical evaluation of usefulness and effectiveness of sitting-type continuous passive motion machines in patients with total knee arthroplasty: a dual-center randomized controlled... by Byung Chan Lee, Chang-Won Moon, Woo Sung Choi, Young Mo Kim, Yong Bum Joo, Da Gyo Lee, Sook Joung Lee, Eunseok Choi, Jong Hun Ji, Dong Whan Suh, Kang Hee Cho

Get full text

Development of forced cooling technology using a DLC coating tool with a small through-hole and a communicating tube regarding the turning for difficult-to-machine material by Ikuo TANABE, Hiromi ISOBE

“…When a difficult-to-machine material was used for the workpiece, the temperature becomes the melting point over and the tool insert is easily melted. …”
Get full text

Use the 4S (Signal-Safe Speckle Subtraction): Explainable Machine Learning Reveals the Giant Exoplanet AF Lep b in High-contrast Imaging Data from 2011 by Markus J. Bonse, Timothy D. Gebhard, Felix A. Dannert, Olivier Absil, Faustine Cantalloube, Valentin Christiaens, Gabriele Cugno, Emily O. Garvin, Jean Hayoz, Markus Kasper, Elisabeth Matthews, Bernhard Schölkopf, Sascha P. Quanz

“…We find that PCA learns the shape of the telescope point-spread function for high numbers of PCA components. …”
Get full text