Dirichlet latent modelling enables effective learning and sampling of the functional protein design space by Evgenii Lobzaev, Giovanni Stracquadanio

“…Here we propose an autoregressive model, called Temporal Dirichlet Variational Autoencoder (TDVAE), which exploits the mathematical properties of the Dirichlet distribution and temporal convolution to efficiently learn high-order information from a functionally related, possibly remotely similar, set of sequences. …”
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Precise Sizing and Collision Detection of Functional Nanoparticles by Deep Learning Empowered Plasmonic Microscopy by Jingan Wang, Yi Sun, Yuting Yang, Cheng Zhang, Weiqiang Zheng, Chen Wang, Wei Zhang, Lianqun Zhou, Hui Yu, Jinghong Li

“…Here, it is demonstrated that deep learning‐empowered plasmonic microscopy (Deep‐SM) enables precise sizing and collision detection of functional chemical and biological nanoparticles. …”
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The role and function of the Musi Rawas learning activities center as a non-formal unit by Hartoyo Hartoyo, Sudarwan Danim, Muhammad Kristiawan

Subjects: “…learning activities center…”
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Enhanced Reward Function Design for Source Term Estimation Based on Deep Reinforcement Learning by Junhee Lee, Hongro Jang, Minkyu Park, Hyondong Oh

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Development of Relation and Function e-Modules Based on Contextual Learning Integrated with Islamic Values by Dwi Setiawati Radjak, Turmudi Turmudi, Imam Sujarwo

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A Deep Learning-Augmented Density Functional Framework for Reaction Modeling with Chemical Accuracy by Jin Xiao, Yingfeng Zhang, Bowen Li, Shuwen Zhang, Ya Gao, Wei Chen, Han Wang, John Z. H. Zhang, Tong Zhu

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Hydrograph and recession flows simulations using deep learning: Watershed uniqueness and objective functions by Abhinav Gupta, Sean A. McKenna

“…Further, the DL models were trained on two different objective functions. The performance of the global model in a watershed depended strongly upon the objective function used. …”
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IMPLEMENTATION OF LEARNING MANAGEMENT SYSTEMS WITH GENERATIVE ARTIFICIAL INTELLIGENCE FUNCTIONS IN THE POST-PANDEMIC ENVIRONMENT by Denis-Cătălin Arghir

“…The system goes beyond traditional LMS functionalities by providing suggestions to enhance and diversify lessons. …”
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MAL-Net: Model-Adaptive Learned Network for Slow-Time Ambiguity Function Shaping by Jun Wang, Xiangqing Xiao, Jinfeng Hu, Ziwei Zhao, Kai Zhong, Chaohai Li

“…Designing waveforms with a Constant Modulus Constraint (CMC) to achieve desirable Slow-Time Ambiguity Function (STAF) characteristics is significantly important in radar technology. …”
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Enhancing Antimicrobial Peptide Functionality and Manufacturability Through Deep Learning-Based Sequence Design by Aysenur Soyturk Patat, Aycan Gundogdu, Ozkan Ufuk Nalbantoglu

“…While deep learning methods have shown success, they often neglect critical functional aspects of proteins. …”
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A comparative machine learning study of schizophrenia biomarkers derived from functional connectivity by Victoria Shevchenko, R. Austin Benn, Robert Scholz, Wei Wei, Carla Pallavicini, Ulysse Klatzmann, Francesco Alberti, Theodore D. Satterthwaite, Demian Wassermann, Pierre-Louis Bazin, Daniel S. Margulies

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Retracted: Analysis of Psychological and Emotional Tendency Based on Brain Functional Imaging and Deep Learning by Discrete Dynamics in Nature and Society

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The influence of learning ability of irradiated and intact rats-parents on higher brain function of their offspring by V. V. Panfilova, O. I. Kolganova, O. F. Chibisova, L. P. Zhavoronkov

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Cognitive functions and their effect on disability in learning process and knowledge application in patients with arterial hypertension by S. Ya. Yanovska

“…The aim of the investigation is to determine the influence of cognitive functions on disability in learning process and knowledge application in patients with hypertension. …”
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Non-invasive arterial input function estimation using an MRA atlas and machine learning by Rajat Vashistha, Hamed Moradi, Amanda Hammond, Kieran O’Brien, Axel Rominger, Hasan Sari, Kuangyu Shi, Viktor Vegh, David Reutens

“…Abstract Background Quantifying biological parameters of interest through dynamic positron emission tomography (PET) requires an arterial input function (AIF) conventionally obtained from arterial blood samples. …”
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Identifying MOFs for electrochemical energy storage via density functional theory and machine learning by Tian Sun, Zhenxiang Wang, Liang Zeng, Guang Feng

“…Metal-organic frameworks (MOFs) are promising electrode materials, while new MOFs with high conductivity, high stability, and abundant redox-reactive sites are demanded to meet the growing needs of EES. Density Functional Theory (DFT) could calculate these properties of MOFs and provide atomic-level insights into the mechanisms, based on which machine learning (ML) can screen MOFs for EES efficiently. …”
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Functional dissection of a neuronal brain circuit mediating higher-order associative learning by El Yazid Rachad, Stephan Hubertus Deimel, Lisa Epple, Yogesh Vasant Gadgil, Anna-Maria Jürgensen, Magdalena Springer, Chen-Han Lin, Martin Paul Nawrot, Suewei Lin, André Fiala

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Transfer learning-based techniques for efficient 3D-reconstruction of functionally graded materials by Pouria Hamidpour, Alireza Araee, Majid Baniassadi

“…This paper proposes a novel method for 3D reconstruction of functionally graded materials (FGMs) using transfer learning techniques to overcome the limitations of experimental 3D microscopy. …”
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A study on the psychological functioning of children with specific learning difficulties and typically developing children by Nurul Shafira Adi, Azizah Othman, Hue San Kuay, Qarem Mohamed Mustafa

“…Objective This study examines the psychological functioning of children with dyslexia and compares it with typically developing children. …”
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Machine learning assisted in situ synthesis of functional microbiomes towards sustainable wastewater treatment by Shubo Zhang, Sai Gong, Ran Yin, Jinfeng Wang, Yanru Wang, Hongqiang Ren

“…The in situ synthesis of functional microbiomes is a novel and promising method for sustainable control of ECs. …”
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