LA-ResUNet: An Efficient Linear Attention Mechanism in ResUNet for the Semantic Segmentation of Pulmonary Nodules by P. C. Sarah Prithvika, L. Jani Anbarasi

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Efficient and accurate tobacco leaf maturity detection: an improved YOLOv10 model with DCNv3 and efficient local attention integration by Yi Shi, Hong Wang, Fei Wang, Yingkuan Wang, Jianjun Liu, Long Zhao, Hui Wang, Feng Zhang, Qiongmin Cheng, Shunhao Qing

“…Furthermore, the incorporation of the Efficient Local Attention (ELA) mechanism at multiple stages of the model has substantially enhanced the efficiency and fidelity of feature extraction. …”
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EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach by Eyad Talal Attar

“…The study evaluated event-related potentials alongside theta, alpha and beta spectral power while employing machine learning techniques to distinguish meditative states from cognitive tasks.MethodsThe study utilized data from 13 participants aged 24–58, which researchers obtained through an openly accessible OpenNeuro dataset.ResultExamination of eventrelated potentials (ERPs) demonstrated that P300 amplitude showed significant growth when responding to oddball stimuli, which indicates increased attention allocation (p < 0.05). …”
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Association between the attentional network efficiency and change of direction speed ability in young male Indian footballers by Debabrata Chatterjee, Santi Ranjan Dasgupta, Santi Ranjan Dasgupta, Arkadeb Dutta, Arkadeb Dutta

“…A 2(alerting) ×3 (orienting) ×2 (executive) repeated measures ANOVA tested interactions between the attentional network components. Partial correlation was conducted between the physical (field tests) and cognitive test scores adjusted for age and BMI.ResultsCODS ability measured with IAT was significantly correlated [r = +0.507 (large), p < 0.05] with the executive control network only, nor with alerting [r = −0.039 (trivial), p > 0.05] and orienting [r = + 0.051 (trivial), p > 0.05] networks and neither the CRT task performance [r = −0.011 (trivial), p > 0.05].DiscussionA strong positive association between executive control and preplanned CODS indicates better interference control by the attentional network. …”
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Efficient Sleep, Enhanced Attention: Exploring the Interplay With RBC-Inflammation Mechanisms in Hypoxic High-Altitude Areas by Shi CY, Xue XJ, Li ZF, Huang XY, Su R, Wang NN, Zhu JG, Li H, Ma HL, Liu M, Zhang DL

“…Participants underwent an attention network test with concurrent electroencephalography to assess attentional function. …”
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Malicious Traffic Detection on Tofino Using Graph Attention Model by Xichang Gao, Lizhuang Tan, Shengpeng Chen, Peiying Zhang, Jian Wang

“…This paper presents Maltof, a malicious traffic detection method based on P4 programmable switches, aimed at enhancing the accuracy and efficiency of real-time detection. …”
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P-TAME: Explain Any Image Classifier With Trained Perturbations by Mariano V. Ntrougkas, Vasileios Mezaris, Ioannis Patras

“…Unlike traditional perturbation-based methods, which have high computational requirements, P-TAME offers an efficient alternative by generating high-resolution explanations in a single forward pass during inference. …”
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YOLO-DLHS-P: A Lightweight Behavior Recognition Algorithm for Captive Pigs by Changhua Zhong, Hao Wu, Junzhuo Jiang, Chaowen Zheng, Hong Song

“…Firstly, the C2f-DRB structure is introduced at the Backbone position, and the sizeable convolutional kernel is used to extend the receptive field to enhance the spatial perception ability of the model, and to enhance the network’s ability to capture spatial information while maintaining the number of learnable parameters and computational efficiency; The LSKA attention mechanism is then introduced to be integrated into the SPPF module to construct the SPPF-LSKA structure, which significantly improves the ability of the SPPF module to aggregate features at multiple scales; Then, the downsampling at the Neck position is optimised to the HWD algorithm, which reduces the spatial resolution of the feature map while retaining more useful information and reduces the uncertainty of the information compared with the downsampling method of the baseline model; finally, the Shape-IoU is used to replace the original CIoU, which significantly improves the detection efficiency and accuracy of the model without increasing the extra computational burden. …”
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Soil microbial carbon use efficiency and the constraints by Run Dang, Jian Liu, Eric Lichtfouse, Lifeng Zhou, Meng Zhou, Leilei Xiao

“…Abstract Background Microbial contributions to soil organic carbon formation have received increasing attention, and microbial carbon use efficiency is positively correlated with soil organic carbon storage. …”
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A generative adversarial network-based accurate masked face recognition model using dual scale adaptive efficient attention network by Jafar A. Alzubi, Kiran Sree Pokkuluri, Rajesh Arunachalam, Surendra Kumar Shukla, Sumanth Venugopal, Karthikayen Arunachalam

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Features of anxiety and attention in elementary school students of the Russian North by Olga P. Bartosh, Tatiana P. Bartosh, Marina V. Mychko

“…Magadan children were significantly more anxious than their Susuman peers on five of ten scales: in connection with the evaluation by others (M±SE: p=0.013; Me [Q1; Q3]: p<0.05); in their relationships with teachers (p=0.003; p<0.01); in terms of their learning success (p=0.016; p<0.05); in situations of knowledge testing (p=0.022; p<0.05); and they also exhibited an increase in their autonomic reactivity associated with anxiety (p=0.040; p<0.05). …”
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MEFA-Net: Multilevel Feature Extraction and Fusion Attention Network for Infrared Small-Target Detection by Jingcui Ma, Nian Pan, Dengyu Yin, Di Wang, Jin Zhou

“…Furthermore, the encoder attention fusion module (EAF) is employed, where spatial and channel attention weights are generated using dual-path pooling to achieve the adaptive fusion of deep and shallow layer features. …”
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pH-triggered CS@ZnO2 nanocomposites: Self-activated ROS generation for efficient bacterial eradication by Yu Zhang, Jun Liu, Sha Li, Jinhua Zhou, Jiushan Liu, Yan Huang

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A new thin-film solar cell prototype based on Na-doped BiFeO3 by Adán de Jesús Bautista-Morantes, Carlos Ordulio Calderón-Carvajal, Jairo Alberto Gómez-Cuaspud, Enrique Vera-López

“…The development of thin film photovoltaic devices based on third and fourth generation materials has attracted the attention of the scientific community worldwide, finding the need to experiment among different assemblies and structurally modified materials to find the best efficiency of converting solar energy into electrical energy. …”
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Efficient hydrogen evolution via neutral water electrolysis using nanocrystalline TiO2 electrocatalyst by Prashant D. Sanadi, Rajvardhan K. Chougale, Dhanaji B. Malavekar, Jin Hyeok Kim, Srinivaas Masimukku, Guo-Ping Chang-Chien, Yong-Chein Ling, Sanjay S. Kolekar, Ganesh S. Kamble

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Automatic model of sleep apnea detection using optimized weighted fusion process of hybrid convolution (1D/2D) efficient attention network from EEG signals by R. Nandakumar, Rajesh Arunachalam, R Pugalenthi, Karthikayen Arunachalam

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Long-term effects of attentional performance on functional brain network topology. by Thomas P K Breckel, Christiane M Thiel, Edward T Bullmore, Andrew Zalesky, Ameera X Patel, Carsten Giessing

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P4CN-YOLOv5s: a passion fruit pests detection method based on lightweight-improved YOLOv5s by Zhiping Tan, Zhiping Tan, Dapeng Ye, Jiancong Wang, Wenxiang Wang

“…To address this issue, this paper proposed an enhanced lightweight and efficient deep learning model, which is developed based on YOLOv5s, consists of the PLDIoU, four CBAM modules, and one newAnchors, termed P4CN-YOLOv5s, for detecting passion fruit pests. …”
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Focal Correlation and Event-Based Focal Visual Content Text Attention for Past Event Search by Pranita P. Deshmukh, S. Poonkuntran

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A hybrid deep learning model EfficientNet with GRU for breast cancer detection from histopathology images by M. Pradeepa, B. Sharmila, M. Nirmala

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