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Plant disease diagnosis in field settings is challenged by subtle symptomology, high inter-class visual similarity, and class imbalance, making automated detection particularly difficult. While deep learning models achie...

Advanced materials, serving as the core material foundation underpinning economic transformation, national defense security, and technological revolution, directly determine national competitiveness through their researc...

The growing demand for intensive artificial intelligence applications, such as deep neural networks and Large Language Models (LLMs), has driven the creation of architecture extensions and accelerators for matrix multipl...

Abstract ent-Kaurane diterpenoids (ent-KTs) represent a structurally diverse class of natural products renowned for their antitumor and anti-inflammatory bioactivities. The C-14 hydroxyl modification is crucial for enhan...

Abstract Early and reliable smoke detection is critical for preventing fire-related disasters, safeguarding human lives, and ensuring infrastructure safety. Conventional sensor-based systems, however, are often constrain...

Salinity distribution is a critical determinant in the management of water resources and the protection of ecological integrity in coastal regions, drawing particular concerns in the context of increasing saltwater intru...

Abstract Bone tissue engineering scaffolds must provide structural support while permitting fluid transport and maintaining safe hydrodynamic conditions for cell activity. Triply Periodic Minimal Surface (TPMS) architect...

Generative artificial intelligence systems increasingly enable novice users to create complex websites with minimal technical expertise; however, these users often struggle to evaluate the visual quality of AI-generated ...

The analysis and modeling of educational data are of great significance to the evaluation of teaching quality and personalized learning guidance. However, the acquisition of academic data is often limited by the costs of...

Underwater radiated noise (URN) from submarine propulsors requires reliable flow prediction as a prerequisite for cavitation and acoustic analyses. This study validates a computational fluid dynamics (CFD) workflow to pr...

Zernike moments are well-suited for unmanned aerial vehicle scene matching because of their rotation invariance and robustness to noise. However, their high computational complexity poses challenges for meeting the real-...

Introduction. The performance reliability of electric vehicles (EVs) is an important factor in evaluating their suitability for widespread adoption. The reliability and lifespan of an EV depend on several critical factor...

In recent years, generative artificial intelligence represented by large language models (LLMs) and multimodal large language models (MLLMs) has achieved remarkable progress. These ultra-large-scale and complex models im...

In classical vernacular Chinese fiction, inferring affective stance in the presence of rhetorical devices often depends on implicit semantics and contextual cues, which poses substantial challenges for joint pragmatic mo...

Anaerobic co-digestion of livestock waste presents a viable approach for addressing environmental challenges and reducing greenhouse gas emissions in semi-urban and rural contexts. This study focuses on the development o...

The purpose of this study is to justify the design parameters of spiral-vortex equipment ensuring energy-efficient desulfurization of flue gases from autonomous medium-capacity gas-piston power plants (GPPPs). The study ...

Reconstructing the early spatiotemporal dynamics of emerging infectious diseases (EIDs) is essential for effective public health response but remains difficult due to reporting delays, heterogeneous surveillance systems,...

Abstract Predictive atomistic simulations have propelled materials discovery, yet routine setup and debugging still demand computer specialists. This know-how gap limits the use of Integrated Computational Materials Engi...

Abstract Simulating the response of granular materials under realistic loading scenarios is essential for ensuring the reliability of geotechnical infrastructure. This task is particularly challenging because natural soi...

Forest ecosystems play a fundamental role in sustaining global water cycles and ecological security, and accurate modeling of their eco-hydrological processes is essential for forest management, watershed regulation, and...

Foothold selection for hexapod robots in complex terrain presents a significant challenge, demanding both high computational efficiency and robust adaptability. To address this issue, this paper introduces a foothold sel...

Reliable beat-level arrhythmia detection from electrocardiogram (ECG) signals is essential for continuous patient monitoring. However, many existing deep learning models remain computationally expensive and are sensitive...

Agile, dynamic, and safe motion planning in interactive environments is a key challenge for autonomous vehicles. Most research has focused on enhancing established planning algorithms, often aiming to improve optimality ...

Soft robotics is a rapidly evolving field that leverages compliant and deformable materials to create robotic systems capable of safe human interaction, environmental adaptability, and bio-inspired motion. Unlike rigid r...