The Effect of auriculotherapy on sleep quality in children with attention deficit hyperactivity disorder: a randomized clinical trial by Laleh Mohammadi, Zahra Tagharrobi, Khadijeh Sharifi, Zahra Sooki, Mohammad Zare, Fatemeh Zare Joshaghani

“…Abstract Introduction Considering the importance of sleep disorders in children with attention-deficit/hyperactivity disorder (ADHD) and effective therapeutic strategies, the present study aimed to investigate the effects of auriculotherapy on sleep quality in children with ADHD. …”
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Possible association between Sever’s disease and attention deficit hyperactivity disorder. a prospective observational study by Nevzat Gonder, Ibrahim Halil Demir, Volkan Özel, Kubra Ilicepinar, Musa Alperen Bilgin

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Prediction of lithium-ion battery SOC based on IGA-GRU and the fusion of multi-head attention mechanism by Pei Tang, Minnan Jiang, Weikai Xu, Zhengyu Ding, Mao Lv

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Enhancing Handwritten Digit Recognition using Auxiliary Classifier Generative Adversarial Networks and Self-attention Mechanism by Hu Tingkai

“…This research study investigates the integration of the self-attention mechanism and the Auxiliary Classifier Generative Adversarial Networks (ACGAN)to improve handwritten digital recognition using the MNIST data set. …”
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Economic Evaluation of a Novel Treatment of Attention-Deficit/Hyperactivity Disorder in US Motor Vehicle Drivers by Jacie T. Cooper, John E. Schneider, Jim Potenziano, David S. Fam

“…**Background:** Attention-deficit/hyperactivity disorder (ADHD) affects approximately 4.4% of US adults. …”
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DS-SwinUNet: Redesigning Skip Connection With Double Scale Attention for Land Cover Semantic Segmentation by Zirui Shen, Wanjie Liu, Sheng Xu

“…In recent years, the development of visual transformer has gradually replaced convolutional neural networks in the visual domain with attention computation, causing pure transformer networks to become a trend. …”
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Empowering Urdu sentiment analysis: an attention-based stacked CNN-Bi-LSTM DNN with multilingual BERT by Lal Khan, Atika Qazi, Hsien-Tsung Chang, Mousa Alhajlah, Awais Mahmood

“…We suggest an attention-based, stacked, two-layer CNN-Bi-LSTM DNN to overcome these glitches. …”
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A Cloud API Personalized Recommendation Method Based on Multiple Attribute Features and Mashup Requirement Attention by Limin Shen, Yuying Wang, Chengyu Li, Zhen Chen

Subjects: “…Attention mechanism…”
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Impact of psychostimulants on microbiota and short-chain fatty acids alterations in children with attention-deficit/hyperactivity disorder by Nonglak Boonchooduang, Orawan Louthrenoo, Narueporn Likhitweerawong, Chanon Kunasol, Chanisa Thonusin, Sirawit Sriwichaiin, Wichwara Nawara, Nipon Chattipakorn, Siriporn C. Chattipakorn

“…Abstract Attention-deficit/hyperactivity disorder (ADHD), a common neurodevelopmental disorder in children, is associated with alterations in gut microbiota and short-chain fatty acids (SCFAs), which are metabolites influencing the gut-brain axis. …”
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Exploiting a Spatial Attention Mechanism for Improved Depth Completion and Feature Fusion in Novel View Synthesis by Anh Minh Truong, Wilfried Philips, Peter Veelaert

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A Computational Model of Attention-Guided Visual Learning in a High-Performance Computing Software System by Alice Ahmed, Md. Tanim Hossain

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Global-Local Self-Attention-Based Long Short-Term Memory with Optimization Algorithm for Speaker Identification by Pravin Marotrao Ghate, Bhagvat D. Jadhav, Shriram Sadashiv Kulkarni, Pravin Balaso Chopade, Prabhakar N. Kota

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Refining breast cancer classification: Customized attention integration approaches with dense and residual networks for enhanced detection by Mohammad Sakif Alam, Anwar Hossain Efat, SM Mahedy Hasan, Md Palash Uddin

“…Methods We propose a dense-ResNet attention integration (DRAI) architecture that combines DenseNet and ResNet models with three attention mechanisms to enhance feature extraction from the BreakHis dataset. …”
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Feature Fusion Model Using Transfer Learning and Bidirectional Attention Mechanism for Plant Pipeline Leak Detection by Yujin Han, Yourak Choi, Jonghyuk Lee, Ji-Hoon Bae

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Alterations of attention and impulsivity in the rat following a transgenerational decrease in dietary omega-3 fatty acids by Joachim Hauser, Ewelina Stollberg, Andreas Reissmann, Ivo Kaunzinger, Klaus W. Lange

“…The present study investigated the effects of nutritional omega-3 PUFAs on attentional functions and impulsive behavior in Wistar rats. …”
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Research on power plant security issues monitoring and fault detection using attention based LSTM model by Shengda Wang, Zeng Dou, Danni Liu, Han Xu, Ji Du

“…Methodology For the purpose of this investigation, an attention-based long short-term memory (Att-LSTM) model was used for the categorization of time series actual data. …”
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Enhancing Precipitation Nowcasting Through Dual-Attention RNN: Integrating Satellite Infrared and Radar VIL Data by Hao Wang, Rong Yang, Jianxin He, Qiangyu Zeng, Taisong Xiong, Zhihao Liu, Hongfei Jin

“…To address this limitation, we introduce the Dual-Attention Recurrent Neural Network (DA-RNN), a model that combines satellite infrared (IR) data with radar-derived vertically integrated liquid (VIL) content. …”
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Attention Deficits in Stroke Patients: The Role of Lesion Characteristics, Time from Stroke, and Concomitant Neuropsychological Deficits by Simona Spaccavento, Chiara Valeria Marinelli, Roberto Nardulli, Luigi Macchitella, Umberto Bivona, Laura Piccardi, Pierluigi Zoccolotti, Paola Angelelli

“…Attention impairments are frequent in stroke patients with important consequences on the rehabilitation outcomes and quality of life. …”
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AFT-SAM: Adaptive Fusion Transformer with a Sparse Attention Mechanism for Audio–Visual Speech Recognition by Na Che, Yiming Zhu, Haiyan Wang, Xianwei Zeng, Qinsheng Du

“…Aiming at the problems of serious information redundancy, complex inter-modal information interaction, and difficult multimodal fusion faced by the audio–visual speech recognition system when dealing with complex multimodal information, this paper proposes an adaptive fusion transformer algorithm (AFT-SAM) based on a sparse attention mechanism. The algorithm adopts the sparse attention mechanism in the feature-encoding process to reduce excessive attention to non-important regions and dynamically adjusts the attention weights through adaptive fusion to capture and integrate the multimodal information more effectively and reduce the impact of redundant information on the model performance. …”
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Eyetracking a meeting of minds: teachers’ and students’ joint attention during synchronous online language tutorials by Shi Lijing, Stickler Ursula

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