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IntroductionTiller production is a critical determinant of turfgrass canopy density and plant performance, yet manual tiller counting is too labor-intensive for large breeding programs.MethodsTo address this limitation, ...

Abstract Quantum Machine Learning (QML) is emerging as a promising technology for tackling complex computational challenges, although its practical implementation faces significant obstacles owed to the inherent noise in...

Increasingly, unipolar quantum optoelectronic devices such as quantum cascade lasers are employed for the targeted generation of dynamic waveforms in the mid-infrared and terahertz regime. These include for example short...

Precision agriculture plays a crucial role in sustainable food production and resource-efficient land management. A key component of precision agriculture is the semantic segmentation of crops and weeds that enables auto...

The development goal of artificial intelligence is to enable machines to think and act like humans, solving complex problems, and more importantly, interacting effectively in a complex, dynamic, and uncertain physical wo...

Trajectory reconstruction from sparse and noisy GPS data is critical for applications such as urban mobility analysis, transportation planning, and navigation systems. However, large sampling intervals and the typically ...

Abstract Machine learning surrogate models of Kohn-Sham Density Functional Theory Hamiltonians provide a powerful tool for accelerating the prediction of electronic properties of materials, such as electronic band struct...

ABSTRACT Objective The proximal femoral laterally bionic intramedullary nail (PFLBN) is a novel cephalomedullary fixation system incorporating an additional lateral wall screw. This study aimed to compare the stress dist...

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...

As a key element of human settlements and fundamental features in maps, buildings play a critical role in urban planning and environmental monitoring. Automatically extracting buildings from remote sensing images is of s...

Introduction: The identification of chemical compounds that interfere with SARS-CoV-2 replication continues to be a priority in several academic and pharmaceutical laboratories. Computational tools and approaches have th...

The remarkable success of large language models (LLMs) in code generation has transformed software development, with systems like Codex, CodeGen, and StarCoder demonstrating strong capabilities in synthesizing functional...

Abstract Background Gastrointestinal stromal tumors (GISTs) are primarily treated with tyrosine kinase inhibitors (TKIs) such as imatinib. However, the development of drug resistance remains a critical clinical challenge...

Unmanned surface vehicles (USVs) operating in open-sea environments experience significant roll motion due to wave-induced excitation. The dynamic roll response depends on various factors, including vessel speed, wave en...

The RAG1 and RAG2 genes encode proteins essential for initiating V(D)J recombination in T cell receptor and immunoglobulin gene loci. Biallelic pathogenic variants in these genes are implicated in a spectrum of immunodef...

Abstract Efficiently and accurately extracting key information from videos has become a core challenge in the current computer vision. Traditional methods rely on manual features and shallow models, making it difficult t...

Introduction and aims: Oral and maxillofacial surgery (OMFS) produces complex clinical data, while artificial intelligence (AI) applications in this field remain limited despite great potential. This study aimed to map t...

Abstract The Broad Learning System (BLS) provides an effective framework for nonlinear mapping, offering advantages over traditional deep neural networks through its expanded input node architecture. While BLS has demons...

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...

The Fast Steering Mirror (FSM) is a critical beam steering component in precision optical systems. However, its design often relies on repetitive finite element analysis (FEM) and experimentation due to the lack of unive...

Abstract BackgroundDepression affects more than 300 million people worldwide and is a leading contributor to the global disease burden. Traditional diagnostic methods, such as structured clinical interviews, ...

IntroductionAcute Lymphoblastic Leukemia (ALL) is a hematological malignancy, which is life-threatening and demands rapid and precise diagnosis to either enhance or worsen the survival chances. Traditional diagnostic met...

Urban analytics has emerged as a transformative tool for addressing the challenges of urbanization and fostering sustainable smart cities. Despite its growing significance, a gap remains in the literature on integrating ...

This paper presents an innovative parallel computational methodology employing adaptive fractional differential operators to address Monkeypox epidemiological modeling challenges. The complex dynamics of such models ofte...