A lightweight remote sensing image detection model with feature aggregation diffusion network by Xiaohui Cheng, Xukun Wang, Yun Deng, Qiu Lu, Yanping Kang, Jian Tang, Yuanyuan Shi, Junyu Zhao

“…A dilation-wise residual module further optimizes multi-scale feature extraction. Evaluated on benchmark datasets, LightFAD-YOLO achieves 1.7 % higher mAP0.5 and 6.4 % improved mAP0.5:0.95 over baseline models, with 9.9 % lower computational load. …”
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SuperMOT: Decoupling Motion and Fusing Temporal Pyramid Features for UAV Multiobject Tracking by Libo Ren, Wenxin Yin, Wenhui Diao, Kun Fu, Xian Sun

“…It can be observed that the input sizes commonly selected by mainstream UAV multiobject trackers to reduce computational load are suboptimal for capturing the semantic features of small objects. …”
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Spatially engineering tri-layer nanofiber dressings featuring asymmetric wettability for wound healing by Tingting Shi, Yuan Liu, Donghui Wang, Dan Xia, Baoe Li, Ruodan Xu, Ning Li, Chunyong Liang, Menglin Chen

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Microstructural and microvascular features of white matter hyperintensities and their association with small vessel disease markers by Lily L. Wang, Brady J. Williamson, Bin Zhang, Aakanksha Sriwastawa, Yasmin N. Aziz, Eleni Antzoulatos, Cody B. Stephens, Achala Vagal, Pooja Khatri, Mark W. DiFrancesco

“…Abstract White matter hyperintensities (WMH) are the most prominent imaging feature of small vessel disease (SVD). WMH and other imaging features of SVD are likely the result of ongoing insults associated with cognitive decline and cerebrovascular events. …”
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Feature selection for specific prediction targets at the user level in a district heating network by Samanta A. Weber, Michael Fischlschweiger, Dirk Volta, Jens Geisler

“…In comparison to studies targeting the heat load and suggesting outside air temperature as the most relevant predictor, it was found that for the herein proposed prediction targets, this feature is of secondary relevance (roughly 6–10%). …”
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Features of daily blood pressure fluctuations in patients with obstructive sleep apnea syndrome and obesity by O. I. Tokarenko, Ya. O. Andreeva

“…Objective: to study the features of daily blood pressure fluctuations according to the ambulatory blood pressure monitoring (ABPM) in patients with obstructive sleep apnea syndrome (OSAS) and obesity without arterial hypertension (AH). …”
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Invariant Feature Matching in Spacecraft Rendezvous and Docking Optical Imaging Based on Deep Learning by Dongwen Guo, Shuang Wu, Desheng Weng, Chenzhong Gao, Wei Li

“…And, in the feature matcher, it employs feature classification to reduce computational load, thereby achieving high-precision matching. …”
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Features of Accumulation of Essential Oil in Bitter Wormwood Herbs of Flora of Voronezh Region of Russia by N. A. Dyakova, A. I. Slivkin, I. M. Korenskaya

“…The aim of this study the features of the accumulation of essential oil in bitter wormwood herbs, collected in agro- and urbo-cenoses of the Voronezh region.Materials and methods. …”
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EFINet: Efficient Feature Interaction Network for Real-Time RGB-D Semantic Segmentation by Zhe Yang, Baozhong Mu, Mingxun Wang, Xin Wang, Jie Xu, Baolu Yang, Cheng Yang, Hong Li, Rongqi Lv

“…Currently, although convolutional neural network (CNN) methods are less accurate than Transformer-based methods, they offer stronger real-time performance under the same computational load. Therefore, in this study, we proposed the Efficient Feature Interaction Network (EFINet), a real-time RGB-D segmentation method that uses a lightweight CNN encoder and incorporates encoder blocks with a lightweight upsampling method Dysample and the carefully optimized number of ConvNeXt V2 blocks, to redesign the decoder and minimize redundant computations. …”
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Features of cardiopulmonary reserve in patients with chronic thromboembolic pulmonary hypertension with concomitant rhythm disturbances by A. S. Klinkova, O. V. Kamenskaya, I. Yu. Loginova, S. S. Porotnikova, I. I. Volkova, D. V. Doronin, A. M. Chernyavskiy

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Exploring Technical Features to Enhance Control in Videoconferencing Psychotherapy: Quantitative Study on Clinicians’ Perspectives by Francesco Cataldo, Shanton Chang, Antonette Mendoza, George Buchanan, Nicholas Van Dam

“…A path analysis was conducted to investigate the relationships between the factors loaded. The results of the analysis revealed a significant relationship between “challenges in VCP” and “features to enhance the therapeutic relationship” (adjusted beta [Adjβ]=–0.54, 95% CI 0.29-0.79; P<.001) and “features to enhance TR” and “enhancing control” (Adjβ=0.25, 95% CI 0.15-0.35; P<.001). …”
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Traffic environment perception algorithm based on multi-task feature fusion and orthogonal attention by Zhengfeng LI, Mingen ZHONG, Yihong ZHANG, Kang FAN, Zhiying DENG, Jiawei TAN

“…This mechanism minimizes computational load while amplifying significant spatial features within the input images. …”
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Schizo-Net: A <italic>novel</italic> Schizophrenia Diagnosis Framework Using Late Fusion Multimodal Deep Learning on Electroencephalogram-Based Brain Connectivity Indices by Nitin Grover, Aviral Chharia, Rahul Upadhyay, Luca Longo

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Power Grid Load Forecasting Using a CNN-LSTM Network Based on a Multi-Modal Attention Mechanism by Wangyong Guo, Shijin Liu, Liguo Weng, Xingyu Liang

“…This model aims to address the issue in traditional methods where complex temporal features and important information in power grid load data are not fully captured. …”
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Identification of Defects in Low-Speed and Heavy-Load Mechanical Systems Using Multi-Fusion Analytic Mode Decomposition Method by Yanlei Liu, Kun Zhang, Miaorui Yang, Xu Zhang, Yonggang Xu

“…In view of the higher requirements of modern machinery for multi-sensor information acquisition and fusion technology, this paper proposes a novel multi-fusion analytic mode decomposition (MFAMD) method to separate and demodulate fault features in signals. In low-speed and heavy-load equipment, the signals collected by multiple sensors contain unknown and unequal fault features and interference. …”
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TRANSFORMATION AND SCATTERING OF SURFACE WAVES ON THE ACOUSTIC LOAD TO ULTRASONIC EVALUATION AND MEASUREMENTS. Part 2. The object to study – solid with ledge by A. R. Baev, A. L. Mayorov, M. V. Asadchaya, G. E. Konovalov, O. S. Sergeeva

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Integration of LSTM networks with gradient boosting machines (GBM) for assessing heating and cooling load requirements in building energy efficiency by Reenu Batra, Shakti Arora, Mayank Mohan Sharma, Sonu Rana, Kanishka Raheja, Abeer Saber, Mohd Asif Shah

“…Due to rising demand for energy-efficient buildings, advanced predictive models are needed to evaluate heating and cooling load requirements. This research presents a unified strategy that blends LSTM networks and GBM to improve building energy load estimates’ precision and reliability. …”
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Predictability of viral load dynamics in the early phases of SARS-CoV-2 through a model-based approach by Andrea Bondesan, Antonio Piralla, Elena Ballante, Antonino Maria Guglielmo Pitrolo, Silvia Figini, Fausto Baldanti, Mattia Zanella

“…The proposed methods exploit real data and the multiscale structure of the infection dynamics to provide robust predictions of the epidemic dynamics. We focused on viral load kinetics whose dynamical features are typically available in the symptomatic stage of the infection. …”
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Design and Performance Verification of Dynamic Load Aware Geographic Routing Protocol in IEEE 802.15.4a Networks by Young-Duk Kim, Soon Kwon, Joon-Woo Son, Dongkyun Kim

“…In this paper, we propose a new dynamic load aware geographical routing protocol, named DLAG, which periodically monitors the channel condition of each node and forwards a packet to the neighboring node with the least traffic load by defining new buffer threshold values for controlling the congestion. …”
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Factors Affecting Mechanical Properties of Impulse Friction Stir Welded AA2024-T351 Under Static and Cyclic Loads by Iuliia Morozova, Aleksei Obrosov, Anton Naumov, Vesselin Michailov, Nikolay Doynov

“…This study investigates the factors affecting the mechanical performance of conventional and impulse friction stir welded (FSW and IFSW) AA2024-T351 joints under static and cyclic loading. Emphasis is placed on the influence of fracture-inducing features such as oxide inclusions, constituent particle distributions, crystallographic texture, and precipitation state. …”
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