Academic Articles & Research Papers

Design principles for natural SGLT2 modulators from multi-scale computation.

Population genomics reveals multi-scale mechanisms sustaining schistosomiasis re-emergence in a near-elimination setting.

An integrated multi-scale framework for economically feasible landscape connectivity in working agricultural systems.

Alterations in Hip and Knee Joint Contact Force Waveforms and Orientation Induced by Gait Modifications: A Case Study

Introduction & Purpose Idiopathic torsional deformities of lower limb bones can affect a patient’s gait pattern and joint health, while their cause remains unidentified (Koller et al., 2026). Abnormal joint loadings and the progression of ...

Improved object detection method for autonomous driving based on DETR

Object detection is a critical component in the development of autonomous driving technology and has demonstrated significant growth potential. To address the limitations of current techniques, this paper presents an improved object detecti...

Turbulence properties and kinetic signatures of electrons in Kelvin-Helmholtz waves during a geomagnetic storm

The Kelvin–Helmholtz instability (KHI), in its nonlinear phase, plays a significant role in transporting solar-wind plasma into Earth’s magnetosphere. This study investigates the turbulence properties and reconnection signatures observed at...

Air pollution mapping and variability over five European cities

Mapping urban pollution is essential for assessing population exposure and addressing associated health impacts. High urban concentrations are due to the proximity of sources such as traffic or residential heating, and to urban density with...

Non-invasive large-scale imaging of concurrent neuronal, astrocytic, and hemodynamic activity with hybrid multiplexed fluorescence and magnetic resonance imaging (HyFMRI)

Abstract A critical gap currently exists in systematic understanding and experimental validation of the role of astrocytes in neurovascular coupling and their functional links with other brain cells. Despite a broad selection of functional ...

Efficient tuna detection and counting with improved YOLOv8 and ByteTrack in pelagic fisheries

Accurate estimation of tuna catch is crucial for effective pelagic fishery management and resource conservation. However, existing manual counting methods suffer from issues such as low accuracy and poor timeliness, highlighting the urgent ...

DAF-UNet: Deformable U-Net with Atrous-Convolution Feature Pyramid for Retinal Vessel Segmentation

Segmentation of retinal vessels from fundus images is critical for diagnosing diseases such as diabetes and hypertension. However, the inherent challenges posed by the complex geometries of vessels and the highly imbalanced distribution of ...

Lightweight MS-DSCNN-AttMPLSTM for High-Precision Misalignment Fault Diagnosis of Wind Turbines

Wind turbine (WT) misalignment fault diagnosis is constrained by critical signal processing challenges: weak fault features, intense background noise, and poor generalization. This study proposes a lightweight method for high-precision faul...

YOLOv11n-GrapeLite: A Lightweight Multi-Variety Grape Recognition Model

To address the challenges of rapid and accurate grape variety identification in natural orchard environments, along with the demand for efficient deployment on mobile devices, we propose in this paper YOLOv11n-GrapeLite, a lightweight model...

From molecules to data: the emerging impact of chemoinformatics in chemistry

Abstract Chemoinformatics is a rapidly advancing field that integrates chemistry, computer science, and data analysis to enhance the study and application of chemical systems. This interdisciplinary approach leverages computational tools an...

DELP-Net: A Differentiable Entropy Layer Pyramid Network for End-to-End Low-Rate DoS Detection

Low-rate Denial-of-Service (LDoS) attacks exploit periodic traffic pulses to trigger congestion while maintaining a low average rate, making them highly stealthy and difficult to distinguish from legitimate bursty traffic using threshold-ba...

Enhanced Intrusion Detection in Drone Networks: A Cross-Layer Convolutional Attention Approach for Drone-to-Drone and Drone-to-Base Station Communications

Due to Internet of Drones (IoD) technology, drone networks have proliferated, transforming surveillance, logistics, and disaster management. Distributed Denial of Service (DDoS) attacks, malware infections, and communication abnormalities i...

MSDNet: A Multi-Scale Feature Representation Network Model for Tunnel Bolt Detection

Bolts are critical components of tunnel linings, essential for ensuring safe tunnel operation. Due to their susceptibility to corrosion and detachment, it is vital to closely monitor them during maintenance. However, identifying a large num...

TransCat: a hybrid CNN-transformer network with KAN for medical image segmentation

Medical image segmentation is a fundamental task in computer vision and plays an important role in clinical diagnosis and treatment planning. Existing methods are mainly built on either convolutional neural networks (CNNs) or Transformer-ba...

Lightweight Road Image Segmentation Algorithm Based on Multi-Scale Feature Fusion for Blind Guiding Scenarios

Image segmentation is a crucial technology for environmental perception, and it is widely used in various scenarios such as autonomous driving and virtual reality. With the rapid development of technology, computer vision-based blind guidin...

Adversarial Attack on Object Detection via Object Feature-Wise Attention and Perturbation Extraction

Deep neural networks are commonly used in computer vision tasks, but they are vulnerable to adversarial samples, resulting in poor recognition accuracy. Although traditional algorithms that craft adversarial samples have been effective in a...

SAIN:structure-aware image inpainting for large missing areas

Abstract Image inpainting is crucial for restoring missing or corrupted regions in images, with diverse applications in computer vision and digital content creation. Existing deep learning-based methods, however, often struggle with large o...