Lightweight multilayer interactive attention network for aspect-based sentiment analysis by Wenjun Zheng, Shunxiang Zhang, Cheng Yang, Peng Hu

“…Such correlation degree is calculated by multiple computational layers with neural attention models. Third, we use a parameter-sharing strategy among the computational layers. …”
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Evaluation of the pharmacological potential of N-((5-phenyl-6,11-dihydro-[1,2,4]triazolo[1’,5’:1,6]pyrido[3,4-b]indol-2-yl)methyl)benzamides by S. O. Fedotov

“…Advanced molecular docking techniques were employed to identify potential binding sites with model enzymes and to characterize the energetic and spatial features of ligand-target interactions. Ligand structures were generated using MarvinSketch 6.3.0, HyperChem 8, and AutoDock Tools 1.5.6, while protein targets were prepared with Discovery Studio 4.0 and AutoDock Tools 1.5.6. …”
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RAMAS-Net: a module-optimized convolutional network model for aortic valve stenosis recognition in echocardiography by Yejia Gan, Wanzhong Huang, Yan Deng, Xiaoying Xie, Yuanyuan Gu, Yaozhuang Zhou, Qian Zhang, Maosheng Zhang, Yangchun Liu

“…The model enhanced the ResNet50 backbone by replacing Stage 4 with Spatial and Channel Reconstruction Convolution (SCConv) and Multi-Dconv Head Transposed Attention (MDTA) modules, aiming to reduce redundant computations and improve feature extraction capabilities.ResultsThe proposed method was evaluated on the TMED-2 echocardiography dataset, achieving an accuracy of 94.67%, an F1-score of 94.37%, and an AUC of 0.95 for AS identification. …”
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RLita: A Region-Level Image–Text Alignment Method for Remote Sensing Foundation Model by Qiang Zhang, Decheng Wang, Xiao Yu

“…Specifically, a region-level image–text alignment optimization method is proposed to represent the features of images and texts as visual and sematic representation vectors in one embedding space for better model generalization, and a parameter-efficient tuning strategy is designed to reduce computational resources. …”
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An Overview of the Application of Harmony Search for Chemical Engineering Optimization by R. M. Fonseca-Pérez, O. Del-Mazo-Alvarado, A. Meza-de-Luna, A. Bonilla-Petriciolet, Z. W. Geem

“…The main features of the HS method and several of its popular variants and hybrid versions including their relevant algorithm characteristics are described and discussed. …”
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Isogeometric analysis of the lithosphere under topographic loading: Igalith v1.0.0 by R. Rosandi, Y. Rosandi, B. Simeon

“…For Europe, the computed lithospheric depression is compared with available Mohorovičić depth data. …”
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Organic Terahertz Generators with Wide Entire‐Molecular Phonon‐Free Range and Their Application in Broadband Terahertz Spectroscopy by Yun‐Sang Lee, Chaeyoon Kim, Jungkwon OH, Woojin Yoon, Hoseop Yun, Mojca Jazbinsek, Fabian Rotermund, O‐Pil Kwon

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Seismic Shear Strength Prediction of Reinforced Concrete Shear Walls by Stacking Multiple Machine Learning Models by Siming Tian, Xiangyong Ni, Yang Wang

“…Machine learning (ML) technology can deeply capture the mapping relationship between each input feature and the target value, and provide a more flexible and effective prediction method for RCSW shear-bearing capacity. …”
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Analytical and Dynamical Study of Solitary Waves in a Fractional Magneto-Electro-Elastic System by Sait San, Beenish, Fehaid Salem Alshammari

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Improved lightweight DeepLabV3+ for bare rock extraction from high-resolution UAV imagery by Pengde Lai, Chao Lv, Lv Zhou, Shengxiong Yang, Jiao Xu, Qiulin Dong, Meilin He

“…Meanwhile, the improved model had a parameter count of 6.98 M and a computational complexity of 7.24G, achieving enhanced accuracy while maintaining computational efficiency. …”
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Selecting of statins optimum dosage regimen in patients with acute Q-wave myocardial infarction after thrombolytic therapy by V. D. Syvolap, S. M. Kyselov, A. A. Alferov

“…Further studies of pathogenetic mechanisms and the clinical features of the course of acute Q-wave myocardial infarction left ventricular allow to identify possible ways of preventing life-threatening complications and optimize treatment tactics…”
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Bio-inspired multi-dimensional deep fusion learning for predicting dynamical aerospace propulsion systems by Michael Qian Vergnolle, Eastman Z. Y. Wu, Yanan Sui, Qian Wang

“…Additionally, a dual-way learning workflow using TwinBlock, inspired by the cooperative behavior of visual cells, is implemented to enhance perception of dynamical multi-scale features at a reduced computational cost. TimeWaves demonstrates reliable and robust performance in predicting rocket combustion instability, a key challenge in the aerospace industry.…”
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Multi-Channel Underwater Acoustic Signal Analysis Using Improved Multivariate Multiscale Sample Entropy by Jing Zhou, Yaan Li, Mingzhou Wang

“…This paper explores the optimal parameter selection range for the IMMSE algorithm and compares its sensitivity to noise and computational efficiency with traditional multivariate entropy algorithms. …”
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ES-UNet: efficient 3D medical image segmentation with enhanced skip connections in 3D UNet by Minyoung Park, Seungtaek Oh, Junyoung Park, Taikyeong Jeong, Sungwook Yu

“…Methods We propose ES-UNet, a 3D segmentation architecture that achieves superior segmentation performance while offering competitive efficiency across multiple computational metrics, including memory usage, inference time, and parameter count. …”
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AMD-FV: Adaptive margin loss and dual path network+ for deep face verification. by Zeeshan Ahmed Khan, Waqar Ahmed, Panos Liatsis

“…Input dissimilarity information is used to estimate the margin, while the scale parameter is computed using the number of classes and AML's range. …”
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Time-adaptive phase estimation by Brennan de Neeve, Andrey V. Lebedev, Vlad Negnevitsky, Jonathan P. Home

“…Phase estimation is known to be a robust method for single-qubit gate calibration in quantum computers, while Bayesian estimation is widely used in devising optimal methods for learning in quantum systems. …”
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A turbulence reduced order model based on non-interpolated convolutional autoencoder by WU Pin, ZHANG Bo, SONG Chao, ZHOU Zhu

“…This paper introduces an innovative solution: a non-interpolated convolutional autoencoder, designed to extract nonlinear features from the flow field while curbing parameter count, evading interpolation errors, and mitigating additional computational burdens. …”
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Modeling of lifetime scenarios with non-monotonic failure rates. by Amani Abdullah Alahmadi, Olayan Albalawi, Rana H Khashab, Arne Johannssen, Suleman Nasiru, Sanaa Mohammed Almarzouki, Mohammed Elgarhy

“…Various measures of uncertainty for the MKWD such as Rényi entropy, exponential entropy, Havrda and Charvat entropy, Arimoto entropy, Tsallis entropy, extropy, weighted extropy and residual extropy are computed. We discuss eight different parameter estimation methods and conduct a Monte Carlo simulation study to evaluate the performance of these different estimators. …”
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Modeling and Analysis of Integrated Pest Control Strategies via Impulsive Differential Equations by Joseph Páez Chávez, Dirk Jungmann, Stefan Siegmund

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Lightweight vision transformer model for pine wilt disease detection using aerial RGB image and adversarial data augmentation by Qing Li, Wenhui Chen

“…The framework achieves 7.4 % mAP improvement over baseline models on our established PWD dataset, with a 51.1 % frames per second (FPS) increase and 50 % parameter reduction. Firstly, a FasterNet-based backbone reduces computational complexity while preserving high-level semantic features. …”
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