Comparison of Brain Activation Between Different Modes of Motor Acquisition: A Functional Near‐Infrared Study by Meng‐Hsuan Tsou, Pei‐Yun Chen, Yi‐Ting Hung, Yong‐Wei Lim, Shiuan‐Ling Huang, Yan‐Ci Liu

“…ABSTRACT Background Different modes of motor acquisition, including motor execution (ME), motor imagery (MI), action observation (AO), and mirror visual feedback (MVF), are often used when learning new motor behavior and in clinical rehabilitation. …”
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Protocol for the development of a reporting guideline for causal and counterfactual prediction models in biomedicine by Yi Guo, Hua Xu, Fei Wang, Jie Xu, Jiang Bian, Robert Lucero, Mattia Prosperi

“…In stage 3, a computer-based, real-time Delphi survey will be performed to consolidate the PRECOG checklist, involving experts in causal inference, epidemiology, statistics, machine learning, informatics and protocols/standards. Stage 4 will involve the write-up of the PRECOG guideline based on the results from the prior stages. …”
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Differential effects of clary sage (Salvia sclarea L.) oil and linalyl acetate on depression levels in diabetic foot ulcer patients with T2DM: a randomized blinded controlled trial by Ji Won Son, Purum Kang, Sun Seek Min, Geun Hee Seol, Geun Hee Seol

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AKADEMI DESAIN ANIMASI DENGAN PENDEKATAN ARSITEKTUR NUSANTARA by St Aisyah Rahman, Kurnia Afdillah, Taufik Arfan

“…Kata kunci : Akademi Animasi; Arsitektur Nusantara; Perancangan   Abstract_At this time, The use of animation today has covered the whole sector, start from entertainment such as film, from education as a media of learning in schools, until to the business world as a media of promotion and sales. …”
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Application of Phi (<italic>&#x03A6;</italic>), the Golden Ratio, in Computing: A Systematic Review by M. Akhtaruzzaman, Jamal Uddin Tanvin, Amir Akramin Shafie, Fahim Shahryer, Sachitra Halder

“…The review also categorizes findings by their specific applications and contexts, providing valuable insights into <inline-formula> <tex-math notation="LaTeX">$\phi $ </tex-math></inline-formula>&#x2019;s impact on mathematics, cryptography, search algorithms, machine learning, artificial intelligence, photonics, natural sciences, system design, power engineering, robotics, and practical human life. …”
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mmPrivPose3D: A dataset for pose estimation and gesture command recognition in human-robot collaboration using frequency modulated continuous wave 60Hhz RaDARMendeley Data by Nima Roshandel, Constantin Scholz, Hoang-Long Cao, Milan Amighi, Hamed Firouzipouyaei, Aleksander Burkiewicz, Sebastien Menet, Felipe Ballen-Moreno, Dylan Warawout Sisavath, Emil Imrith, Antonio Paolillo, Jan Genoe, Bram Vanderborght

“…Our dataset serves as a fundamental resource for developing machine learning algorithms to improve the accuracy of pose estimation and gesture recognition using RaDAR data.…”
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Impact of Psychosocial and Palliative Care Training on Nurses’ Competences and Care of Patients With Cancer in Cameroon: Protocol for Quasi-Experimental Study by Nahyeni Bassah, Nicholas Tendongfor, Bachi-Ayukokang Ebob-Anya, Vivian A E Eta, Malika Esembeson, Ndzi Eric Ngah, Salisu Ango Abdul-Rahim

“…Finally, to assess the impact of the training program we will undertake a pre and posttest survey of nurses’ palliative and psychosocial oncology competences, a pre and post training audit of patients’ nursing records to examine nurses’ practice of palliative and psychosocial oncology care and undertake a critical-incident interview of nurses’ transfer of learning to practice. Descriptive and inferential statistics will be used to analysis quantitative data, while qualitative data will be analyzed using the framework approach. …”
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RailPC: A large‐scale railway point cloud semantic segmentation dataset by Tengping Jiang, Shiwei Li, Qinyu Zhang, Guangshuai Wang, Zequn Zhang, Fankun Zeng, Peng An, Xin Jin, Shan Liu, Yongjun Wang

“…To harness the potential of supervised learning methods in the domain of 3D railway semantic segmentation, we introduce RailPC, a new point cloud benchmark. …”
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Contemporaneous Emotion Regulation Theoretical Models: A Systematic Review by Camila Florencia Cremades, Cristian Javier Garay, Martín Juan Etchevers, Roberto Muiños, Graciela Mónica Peker, Juan Martín Gómez Penedo

“…We identify that people's learning history is an important factor in the development of emotional regulation skills. …”
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Pembangunan Aplikasi Mobile Pengenalan Objek Untuk Pendidikan Anak Usia Dini by Muhammad Fadhlan Supriadi, Ema Rachmawati, Anditya Arifianto

“…We used MobileNet architecture as a pre-trained model that had previously been trained on COCO datasets, and implement transfer learning for 20 types of objects commonly found inside the house. …”
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A multi‐tagged SAR ocean image dataset identifying atmospheric boundary layer structure in winter tradewind conditions by Chen Wang, Justin E. Stopa, Doug Vandemark, Ralph Foster, Alex Ayet, Alexis Mouche, Bertrand Chapron, Peter Sadowski

“…The dataset complements existing hand‐labelled ocean SAR image datasets and offers the potential for new deep‐learning SAR image classification model developments. …”
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Development of a model for detection and analysis of inclusions in tomographic images of iron castings using decision trees by Dorota Wilk-Kołodziejczyk, Aleksandra Nowotny, Izabela Krzak, Adam Tchórz, Krzysztof Jaśkowiec, Marcin Małysza, Adam Bitka, Mirosław Głowacki, Marzanna Książek, Łukasz Marcjan

“…The available (experimental) data make it possible to unequivocally identify belonging to one of these groups. The use of machine learning methods to recognize the relationships between the physical parameters of particles helps to improve the analysis process. …”
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Effectiveness of a training program for the acquisition of motor milestones in infants: a randomized clinical trial by Luis Fernández-Sola, Beatriz Cano-Díez, Yessica Pons-Solaz, Begoña Vera-Egido, Sergio Moreno-González

“…The experimental group scored significantly higher, with a 25-point higher percentile in each assessment. Conclusion A learning program aimed at increasing parents’ knowledge of their infant´s gross motor development improved it. …”
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Algorithm of Strawberry Disease Recognition Based on Deep Convolutional Neural Network by Li Ma, Xueliang Guo, Shuke Zhao, Doudou Yin, Yiyi Fu, Peiqi Duan, Bingbing Wang, Li Zhang

“…In this paper, based on the deep convolution neural network technology, the recognition of strawberry common diseases was studied, as well as a new method based on deep convolution neural network (DCNN) strawberry disease recognition algorithm, through the normal training of strawberry image feature representation in different scenes, and then through the application of transfer learning method, the strawberry disease image features are added to the training set, and finally the features are classified and recognized to achieve the goal of disease recognition. …”
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Is Everyone Beating Around the Bush?: A Qualitative Study Examining the Status of Shared Decision-Making Between Veterans Affairs Providers and Surgical Patients in the ICU by M. Andrew Millis, MD, MPH, C. Ann Vitous, MA, MPH, Cara Ferguson, BS, Maedeh Marzoughi, BS, Erin Kim, BS, Sarah E. Bradley, PhD, MPH, CPH, Ashley Duby, MS, Pasithorn A. Suwanabol, MD, MS

“…Participant dialogue was deductively mapped into 8 established SDM components: describing treatment options; determining roles in the decision-making process; fostering partnerships; health care professional preferences; learning about the patient; patient preferences; supporting the decision-making process; and tailoring the information. …”
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Algorithm of Behaviour of Virtual Avatars During Public Speaking Training in a VR Environment by Karol Jędrasiak, Robert Robert Wolański, Damian Bereska

“…The virtual avatars, powered by the algorithm, were able to simulate realistic human behaviours and responses, thus providing a more engaging and immersive learning experience for users. The application offered a variety of realistic training scenarios, interactive avatar feedback, customisation options, and progress tracking and analysis features. …”
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Biomarker Investigation Using Multiple Brain Measures from MRI Through Explainable Artificial Intelligence in Alzheimer’s Disease Classification by Davide Coluzzi, Valentina Bordin, Massimo W. Rivolta, Igor Fortel, Liang Zhan, Alex Leow, Giuseppe Baselli

“…As the leading cause of dementia worldwide, Alzheimer’s Disease (AD) has prompted significant interest in developing Deep Learning (DL) approaches for its classification. However, it currently remains unclear whether these models rely on established biological indicators. …”
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SOME ASPECTS OF THE ANALYSIS OF CYCLICAL FLUCTUATIONS IN THE ECONOMY (IN THE CASE OF THE CORONAVIRUS PANDEMIC CRISIS) by Kamoliddin Jabbarov

“…The study underscores the importance of learning from past crises and adapting poli­cies to address the unique challenges posed by the COVID-19 pandemic, ultimately aiming for a more resilient and inclusive global economic recovery.…”
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Prediction of Dynamic Plasmapause Location Using a Neural Network by Deyu Guo, Song Fu, Zheng Xiang, Binbin Ni, Yingjie Guo, Minghang Feng, Jianguang Guo, Zejun Hu, Xudong Gu, Jianan Zhu, Xing Cao, Qi Wang

“…Abstract As a common boundary layer that distinctly separates the regions of high‐density plasmasphere and low‐density plasmatrough, the plasmapause is essential to comprehend the dynamics and variability of the inner magnetosphere. Using the machine learning framework PyTorch and high‐quality Van Allen Probes data set, we develop a neural network model to predict the global dynamic variation of the plasmapause location, along with the identification of 6,537 plasmapause crossing events during the period from 2012 to 2017. …”
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Adapted Swin Transformer-based real-time plasma shape detection and control in HL-3 by Qianyun Dong, Zhengwei Chen, Rongpeng Li, Zongyu Yang, Feng Gao, Yihang Chen, Fan Xia, Wulyu Zhong, Zhifeng Zhao

“…By adopting multi-task learning and knowledge distillation techniques, the model is capable of robustly detecting six shape parameters under visual interference conditions such as bright light from the divertor and gas injection, thereby avoiding cumbersome manual labeling. …”
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