A Flexible Framework Integrating Digital and Social Competences in Vocational Education Across Diverse Contexts by María José Hernández-Serrano, Joe Cullen, Barbara Jones, Noelia Morales Romo

“…Conclusions highlight the need to combine digital and social skills together with media literacy through flexible pathways to achieve better results for teaching, learning, and empowering learners.…”
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Cognitive Impairment in Opium Use Disorder by Hossein Sanjari Moghaddam, Behrang Shadloo, Helen Shahkhah, Abbas Tafakhori, Maryam Haghshomar, Shakila Meshkat, Vajiheh Aghamollaii

“…Thirty outpatients with OUD and 20 healthy controls (HCs) were assessed using a neuropsychological battery consisted of Auditory Verbal Learning Test-Revised (AVLT-R), Brief Visuospatial Memory Test-Revised (BVMT-R), Digit Forward and Backward Tests (DFT and DBT), and WAIS-R Digit Symbol Substitution Test (DSST). …”
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Utilisation des sécrétions de myriapodes chez les lémurs et les sapajous : fonction curative ou signalisation sociale ? by Bruno Simmen, Laurent Tarnaud

“…Handling the millipedes in itself does not automatically result in millipedes secreting benzoquinones so that when lemurs and capuchin monkeys bite the arthropods (eventually blowing the legs off), they increase the probability of repulsive liquid being oozed. Associative learning of the handling conditions required to trigger millipedes’ secretions appears very efficient given the rare and opportunistic use of these arthropods by both primate species. …”
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Programme de développement professionnel des fonctionnaires en vue de la création d’un environnement éducatif sûr dans le cadre de la loi martiale by Iryna Trubavina, Oleksandr Cherednychenko, Kirill Nedria, Nadiia Oliinyk

“…Scientific novelty is substantiated by the content of the program and selection of approaches to learning. Practical significance is the development of a training program for civil servants and officials of local self-government bodies. …”
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Remimazolam Combined with Andrographolide Improve Postoperative Cognitive Dysfunction in Rats after Cardiopulmonary Bypass through the AMPK/SIRT1 Signaling Pathway by Chong Chen, Lixia Lan, Kai Xu

“…Introduction: The effects of remimazolam (Re) in combination with andrographolide (AP) on learning, memory, and motor abilities in rats following cardiopulmonary bypass (CPB) surgery were studied. …”
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Hidden Markov Model-Based Video Recognition for Sports by Zhiyuan Wang, Chongyuan Bi, Songhui You, Junjie Yao

“…A multistream residual neural network is used to extract features from video data of three modalities, and the extracted feature vectors are fed into the attention mechanism network, then, the more critical information for video recognition is selected from a large amount of spatiotemporal information, further learning the temporal dependencies existing between consecutive video frames, and finally fusing the multistream network outputs to obtain the final prediction category. …”
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DFTD-YOLO: Lightweight Multi-Target Detection From Unmanned Aerial Vehicle Viewpoints by Yuteng Chen, Zhaoguang Liu

“…Due to the low detection accuracy of small and dense target objects in multi-target detection tasks from the unmanned aerial vehicle (UAV) perspective and the deployment of deep learning models for UAVs as embedded devices, these models must be lightweight. …”
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A Computer Vision-Based Framework for Snow Removal Operation Routing by Mohamed Karaa, Hakim Ghazzai, Yehia Massoud, Lokman Sboui

“…For segments monitored by CCTV cameras, we exploit images and supervised learning models to perform this task. For unmonitored roads, we use the Graph Convolutional Network architecture to predict parameters in a semi-supervised manner. …”
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MACEDONIAN NATIONAL INNOVATION SYSTEM – MAIN CHALLENGES by Radmil Polenakovik, Ivana Stankovska, Bojan R. Jovanovski

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Spatial-Temporal Fusion Graph Neural Networks With Mixed Adjacency for Weather Forecasting by Ang Guo, Yanghe Liu, Shiyu Shao, Xiaowei Shi, Zhenni Feng

“…Many existing approaches based on deep learning models, e.g., recurrent neutral networks and graph neural networks, have been proposed for weather forecasting. …”
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Metasurface-enabled multifunctional single-frequency sensors without external power by Masaya Tashiro, Kosuke Ide, Kosei Asano, Satoshi Ishii, Yuta Sugiura, Akira Uchiyama, Hiroki Wakatsuchi

“…Moreover, we provide a method for predicting physical parameters via the machine learning-based approach of random forest regression. …”
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Combined Online-Discussion as a Tool for Formation of Future Engineers’ Reflexion under Conditions of Education Digitalization. by S. A. Mikheev

“…The four-stage technology of pedagogical application of combined OD combining online-discussions with face-to-face reflexive classes is described, taking into account the mediated nature of learning in the digital environment and psychological features of future engineers related to the specifics of technical thinking. …”
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Automated Classification of Circulating Tumor Cells and the Impact of Interobsever Variability on Classifier Training and Performance by Carl-Magnus Svensson, Ron Hübler, Marc Thilo Figge

“…The automated analysis of medical data is a growing field where different machine learning techniques are used to minimize the time-consuming task of manual analysis. …”
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Is Objective Structured Practical Examination a Better Option than Conventional Practical Examination in Assessing Students’ Competency? An Analytical Research by Arup J. Rout, Pallabi Dasgupta, Tushar K. Saha, Daliya Biswas

“…Background: There was always a need for some innovative assessment method like an objective structured practical examination (OSPE) which is objective, reliable, and valid over conventional practical examinations (CPEs), which lack objectivity and reliability and carries risk of teachers’ bias as learning is assessment-driven. The aim of this study was to find out the effectiveness of OSPE over CPE among seventh-semester medical students and to assess the objectivity of structured questions among different OSPE stations. …”
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Impact of COVID-19 on the quality of higher education in Pakistan: students’ perspective by Maham Khalid, Aamir Sarwar, Sardar Ahmad, Bushra Rehman

“…Addressing challenges highlighted could lead to a promising future for eLearning, increasing opportunities for wider participation. …”
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BharatSim: An agent-based modelling framework for India. by Philip Cherian, Jayanta Kshirsagar, Bhavesh Neekhra, Gaurav Deshkar, Harshal Hayatnagarkar, Kshitij Kapoor, Chandrakant Kaski, Ganesh Kathar, Swapnil Khandekar, Saurabh Mookherjee, Praveen Ninawe, Riz Fernando Noronha, Pranjal Ranka, Vaibhhav Sinha, Tina Vinod, Chhaya Yadav, Debayan Gupta, Gautam I Menon

“…BharatSim uses a synthetic population created by applying statistical methods and machine learning algorithms to survey data from multiple sources, including the Census of India, the India Human Development Survey, the National Sample Survey, and the Gridded Population of the World. …”
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DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection by Shaofu Lin, Yang Yang, Xiliang Liu, Li Tian

“…First, this study proposes the Dynamic Spatial-Frequency Attention (DSFA) mechanism, the Pyramid Attention Refinement (PAR) bottleneck structure, and optimizes the feature propagation method to achieve dynamic decoupling of the spatial and frequency domains in multi-scale representation learning. Secondly, a hybrid loss function has been developed with weights optimized employing the Bayesian Optimization algorithm to provide a strategic method for parameter tuning in similar research. …”
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Trained quantity discrimination in the invasive red-eared slider and a comparison with the native stripe-necked turtle by Feng-Chun Lin, Pei-Jen Lee Shaner, Ming-Ying Hsieh, Martin J. Whiting, Si-Min Lin

“…Specifically, our experimental designs aimed to quantify the learning ability as numerosity pairs increased in difficulty (termed fixed numerosity tests), and the immediate response when turtles were presented with varied challenges concurrently in the same tests (termed mixed numerosity tests). …”
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Efficient Preference Clustering via Random Fourier Features by Jingshu Liu, Li Wang, Jinglei Liu

“…Approximations based on random Fourier features have recently emerged as an efficient and elegant method for designing large-scale machine learning tasks. Unlike approaches using the Nyström method, which randomly samples the training examples, we make use of random Fourier features, whose basis functions (i.e., cosine and sine ) are sampled from a distribution independent from the training sample set, to cluster preference data which appears extensively in recommender systems. …”
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DCWM-LSTM: A Novel Attack Detection Framework for Robotic Arms by Esra Nergis Yolacan, Hande Cavsi Zaim

“…In response to these challenges, this study proposes a new approach that leverages deep learning techniques for attack detection. We present a new framework, LSTM-based Dynamic Compound Weight Mechanism (DCWM), designed to identify cyberattacks targeting robotic arms effectively. …”
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