Both decreasing interstructural space size and increasing total cover increase shrimp abundance on artificial structures deployed in a UAE seagrass bed by Bartholomew, Aaron

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L1-CAM knock-down radiosensitizes neuroblastoma IMR-32 cells by simultaneously decreasing MycN, but increasing PTEN protein expression by Rached, Johnny

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Efficient self-attention with smart pruning for sustainable large language models by Samir Brahim Belhaouari (9427347)

“…Second, the Weight Matrix Folding method is introduced to efficiently prune the self-attention layer matrices in a simple and efficient mathematical model. …”

Serum Vitamin D Concentration ≥75 nmol/L Is Related to Decreased Cardiometabolic and Inflammatory Biomarkers, Metabolic Syndrome, and Diabetes; and Increased Cardiorespiratory Fitn... by Vijay Ganji (8710491)

An End-to-End Concatenated CNN Attention Model for the Classification of Lung Cancer With XAI Techniques by Fariha Haque (21485518)

“…To address these challenges, an end-to-end concatenated Convolutional Neural Network (CNN) attention model has been proposed for automatic lung cancer classification. …”

Agent Productivity Modeling in a Call Center Domain Using Attentive Convolutional Neural Networks by Ahmed , Abdelrahman

“…In this paper, we propose an objective framework for modeling agent productivity for real estate call centers based on speech signal processing. …”
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PredictPTB: an interpretable preterm birth prediction model using attention-based recurrent neural networks by Rawan AlSaad (14159019)

“…<h3>Background</h3><p dir="ltr">Early identification of pregnant women at risk for preterm birth (PTB), a major cause of infant mortality and morbidity, has a significant potential to improve prenatal care. However, we lack effective predictive models which can accurately forecast PTB and complement these predictions with appropriate interpretations for clinicians. …”

Micro-Expression Recognition using Convolutional Variational Attention Transformer (ConVAT) with Multihead Attention Mechanism by Hafiz Khizer bin Talib (20571467)

“…To address these limitations, we propose the Convolutional Variational Attention Transformer (ConVAT), a novel model that leverages a multi-head attention mechanism integrated with convolutional networks, optimized specifically for detailed micro-expression analysis. …”

A hybrid 3D CNN-LSTM model with soft spatial attention mechanism for accurate hyperspectral image classification by Mohamed Sultan Mohamed Ali (17317003)

“…This study introduces a hybrid deep learning model that combines 3D Convolutional Neural Networks (CNNs) with Long Short-Term Memory (LSTM) networks, incorporating residual connections and a soft spatial attention mechanism to overcome these limitations. …”

Temporal self-attention for risk prediction from electronic health records using non-stationary kernel approximation by Rawan AlSaad (14159019)

“…Yet, modeling the non-stationarity in EHR data has received less attention. …”

The Anti-Tumor Agent Sodium Selenate Decreases Methylated PP2A, Increases GSK3βY216 Phosphorylation, Including Tau Disease Epitopes and Reduces Neuronal Excitability in SHSY-5Y Neu... by Wesal Habbab (17346961)

“…Somewhat surprisingly, the catalytically active form, methylated PP2A (mePP2A) was significantly decreased. In close correlation to these data, the phosphorylation state of two substrate proteins, sensitive to PP2A activity, GSK3β and Tau were found to be increased. …”

Dual-attention Network for View-invariant Action Recognition by Gedamu Alemu Kumie (19273711)

“…The DANet is composed of relation-aware spatiotemporal self-attention and spatiotemporal cross-attention modules. …”

Robust and novel attention guided MultiResUnet model for 3D ground reaction force and moment prediction from foot kinematics by Md. Ahasan Atick Faisal (15302410)

“…The proposed deep learning model is tested on two publicly available datasets containing data from 66 healthy subjects to validate the approach. …”

Hierarchical multi-head attention LSTM for polyphonic symbolic melody generation by Ahmet Kasif (17787560)

“…As such, in this study, a hierarchical multi-head attention LSTM model is proposed for creating polyphonic symbolic melodies. …”

Social attention as a cross‐cultural transdiagnostic neurodevelopmental risk marker by Thomas W. Frazier (4229593)

“…The best-fitting model included a general social attention factor and six specific factors. …”

A slow but steady nanoLuc: R162A mutation results in a decreased, but stable, nanoLuc activity by Wesam S. Ahmed (10170053)

“…Here, we combined molecular dynamics (MD) simulation and mutational analysis to show that the R162A mutation results in a decreased but stable <u>bioluminescence </u>activity of NLuc in living cells and in vitro. …”

Applications of bioconvection for tiny particles due to two concentric cylinders when role of Lorentz force is significant by Lei Zhang (38117)

Decreased Interfacial Dynamics Caused by the N501Y Mutation in the SARS-CoV-2 S1 Spike:ACE2 Complex by Wesam S. Ahmed (10170053)

“…In this regard, the recent SARS-CoV-2 alpha, beta, and gamma variants (B.1.1.7, B.1.351, and P.1 lineages, respectively) are of great significance in that they contain several mutations that increase their transmission rates as evident from clinical reports. …”

MACGAN: An All-in-One Image Restoration Under Adverse Conditions Using Multidomain Attention-Based Conditional GAN by Maria Siddiqua (17949149)

“…Furthermore, an ablation study is conducted to analyze the contributions of the discriminator and attention blocks within the MACGAN architecture. The results confirm that both components play significant roles in the effectiveness of MACGAN, with the discriminator ensuring adversarial training and the attention blocks effectively capturing and enhancing important image features.…”

Kefir exhibits anti‑proliferative and pro‑apoptotic effects on colon adenocarcinoma cells with no significant effects on cell migration and invasion by Khoury, Nathalie

“…Results from RT‑PCR showed that kefir decreases the expression of transforming growth factor α (TGF‑α); and transforming growth factor‑β1 (TGF‑β1) in HT‑29 cells. …”
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