Theoretical aspects of the method of teaching higher mathematics using the computer program Maple for students of technical universities by Amon A. Rakhimov

“…The article discusses theoretical aspects of building a methodological system for teaching higher mathematics using the Maple computer system for students of technical universities. The mathematical functionality possessed by this system makes it possible to expand the capabilities of the software used and, due to special clarity, increase the efficiency of learning the material. …”
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SORFPP: Enhancing rich sequence-driven information to identify SEPs based on fused framework on validation datasets. by Hongqi Feng, Qi Nie, Sen Yang

“…<h4>Background</h4>Genome sequencing has enabled us to find functional peptides encoded by short open read frames (sORFs) in long non-coding RNAs (lncRNAs). sORFs-encoded peptides (SEPs) regulate gene expression, signaling, and so on and have significant roles, unlike common peptides. …”
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Enhanced rain removal network with convolutional block attention module (CBAM): a novel approach to image de-raining by Ping Jiang, Junzi Zhang, Jiejie Chen

“…In terms of gradient magnitude similarity bias (GMSD), conscious learning of image block similarity (LPIPS), and reference-based supervised learning (RSR), it also greatly surpasses the basic model. …”
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Unsupervised random walk manifold contrastive hashing for multimedia retrieval by Yunfei Chen, Yitian Long, Zhan Yang, Jun Long

“…Second, we construct intra- and inter-modal similarity preservation and coexistent similarity preservation loss based on contrastive learning to constrain the training of hash functions, ensuring that the hash codes contain complete semantic association information. …”
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Generative AI for drug discovery and protein design: the next frontier in AI-driven molecular science by Uddalak Das

“…This review systematically delineates the theoretical underpinnings, algorithmic architectures, and translational applications of deep generative models—including variational autoencoders (VAEs), generative adversarial networks (GANs), autoregressive transformers, and score-based denoising diffusion probabilistic models (DDPMs)—in the rational design of bioactive small molecules and functional proteins. We examine the role of latent space learning, probabilistic manifold exploration, and reinforcement learning in inverse molecular design, focusing on optimization of pharmacologically relevant objectives such as ADMET profiles, synthetic accessibility, and target affinity. …”
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Exploring non-zero position constraints: algorithm-hardware co-designed DNN sparse training method by WANG Miao, ZHANG Shengbing, ZHANG Meng

“…On-device learning enables edge devices to continuously adapt to new data for AI applications. …”
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Automated Dead Chicken Detection in Poultry Farms Using Knowledge Distillation and Vision Transformers by Ridip Khanal, Wenqin Wu, Joonwhoan Lee

“…EfficientNet-B0 is employed as the teacher model, while DeiT-Tiny functions as the student model, balancing high accuracy and computational efficiency. …”
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Features of single treasury account management in the context of budget funds liquidity management by N. S. Sergienko

“…The key aspects of single treasury account functioning as a tool for consolidation and optimization of public finances have been presented. …”
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Human Rights Education Within ‘Presisi’ Curriculum: A Study of State Police School in North Sumatra by Fazli Rachman, Majda El Muhtaj, Reh Bungana Beru Perangin-angin, Prayetno Prayetno

“…Therefore, collaboration and innovation in using learning models and methods such as group learning, problem-solving, discussion, and active involvement of students can be continuously developed.…”
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Les schèmes de régulation de l’activité des enseignants by Roland Goigoux

“…In this article, the author comments and expands on two of the contributions contained in the dossier entitled “The Categorization of Persons in Teaching and Learning”. These two contributions deal with the cognitive functioning of teachers when they are interacting with their students. …”
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Standardized low-resolution brain electromagnetic tomography does not improve EEG Alzheimer's disease assessment by Wolfgang Frühwirt, Martin Mairhofer, Andreas Hahn, Heinrich Garn, Markus Waser, Reinhold Schmidt, Thomas Benke, Peter Dal-Bianco, Gerhard Ransmayr, Dieter Grossegger, Stephen Roberts, Georg Dorffner

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Refined matrix completion for spectrum estimation of heart rate variability by Lei Lu, Tingting Zhu, Ying Tan, Jiandong Zhou, Jenny Yang, Lei Clifton, Yuan-Ting Zhang, David A. Clifton

“…Spectral analysis of HRV provides essential insights into the functioning of the cardiac autonomic nervous system. …”
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Corporate Real Estate alignment by Monique Arkesteijn

“…I agree with Jensen’s view that a single-valued objective function is needed, but argue that in our CREM domain a financial measure is not fully suitable. …”
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Enhanced neurological anomaly detection in MRI images using deep convolutional neural networks by Ahmed Mateen Buttar, Zubair Shaheen, Abdu H. Gumaei, Mogeeb A. A. Mosleh, Mogeeb A. A. Mosleh, Indrajeet Gupta, Samah M. Alzanin, Muhammad Azeem Akbar

“…The model employs Rectified Linear Unit (ReLU) activation functions, the Adam optimizer, and a random search strategy to fine-tune hyper-parameters like learning rate, batch size, and the number of neurons in fully connected layers. …”
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Comprehensive workflow with optical navigation in minimally invasive transforaminal lumbar interbody fusion: a retrospective study by Kangheng Niu, Zhenzhen Tao, Le Cheng, Zhong Wei, Hui Kang, Tanjun Wei, Biwang Huang, Feng Xu, Chengjie Xiong

“…The learning curve for OMIS-TLIF showed proficiency after 14 cases, whereas CMIS-TLIF required 27 cases to achieve similar proficiency. …”
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Identification and evaluation of biomarkers for diagnosis of chronic hepatitis B using RNA-seq by Hong Hong, Xintong Han, Qiuxiang Hu, Huafeng Song, Bing Han

“…The aim of this study was to provide exosomal RNA biomarkers of CHB and develop a machine learning model for the non-invasive diagnosis of CHB patients. …”
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Fatigue impact of mixed reality in mass casualty incidents training by Ana María Cintora-Sanz, Raúl Muñoz-Romo, Alberto Blanco-Lara, Paula Sanchíz-Torres, Tatiana Vazquéz-Rodríguez, Helmut Schrom-Feiertag, Carmen Cardós-Alonso

“…Abstract Background Fatigue is a multifaceted state characterized by a significant lack of energy or motivation; which is perceived by the individual to interfere with usual and desired activities; it can hinder an individual’s functioning. In recent years, the rise of Mixed Rality (MR) technologies has introduced new dynamics in emergency training. …”
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Neural network prediction model based on Levy flight and natural biomimetic technology for its application in cancer prediction. by Ruiyu Zhan

“…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …”
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Improving medical image classification based on Boosted Beluga Whale Optimizer with Triangular Mutation and Cross Vision transformer models by Abdelghani Dahou, Mohamed Abd Elaziz, Ahmad O. Aseeri, Ahmed A. Ewees, Mohammed A.A. Al-qaness, Rehab Ali Ibrahim

“…In this study, we introduce a framework for medical image classification that combines deep learning models with modified Beluga Whale Optimization as a feature selection technique. …”
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Dissociated neuronal cultures as model systems for self-organized prediction by Amit Yaron, Zhuo Zhang, Dai Akita, Tomoyo Isoguchi Shiramatsu, Zenas C. Chao, Hirokazu Takahashi, Hirokazu Takahashi

“…This review synthesizes and critically examines research demonstrating their fundamental computational abilities, including predictive coding, adaptive learning, goal-directed behavior, and deviance detection. …”
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