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Monitoring and managing greenhouse gas emissions in each country is essential to achieving the targets of the UNFCCC framework. Thailand has reported GHG emissions but lacks high resolution spatial emission data, which i...

In this work, a structured hierarchy of hyperdatasets for Monkeypox image classification is presented, aiming to evaluate the robustness and generalization ability of deep classification models for Mpox detection. A syst...

Extreme hydrometeorological events are an increasing concern in Central Europe, particularly in the European Alps, where they pose significant threats to ecological and socio-economic systems. Risk assessment and managem...

Objective: To generate synthetic Orthopantomograms (OPGs) using generative Artificial Intelligence (AI) models and to evaluate the realism of synthetic images through assessments by humans as well as AI models. Methodolo...

This paper explores the many aspects of precipitation measurement that are relevant to providing an accurate global assessment of this important environmental parameter. Methods discussed include ground data, satellite e...

Background: Accurate prediction of facial aesthetics after orthodontic treatment is crucial for clinical planning, yet traditional methodologies often lack the required accuracy and realism. We introduce a novel generati...

Many historical administrative documents, such as the 1940 census, have been digitized and thus could be merged with geographic data. Merged data could reveal social determinants of health, health and social policy milie...

Abstract Objective Carrot (Daucus carota) is a widely cultivated vegetable crop with high nutritional value. Alternaria is one of the most damaging fungal pathogens to carrots, responsible for diseases such as leaf bligh...

We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been...

A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Successful analysis requires the integration of ...

Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information ...

BACKGROUND: PLINK 1 is a widely used open-source C/C++ toolset for genome-wide association studies (GWAS) and research in population genetics. However, the steady accumulation of data from imputation and whole-genome seq...

An updated metric developed to assess the degree of open data reusability, called MEtric for the evaLuation of Open DAta: Meloda 5 is presented. Previous version of the metric, Meloda 4, had six dimensions: the legal lic...

Abstract Purpose To design a coach-interpretable movement quality score for badminton footwork training using an adaptive neuro-fuzzy inference system. Methodology We derived compact biomechanical descriptors of timing, ...

Reliable prognostics in predictive maintenance requires not only accurate remaining useful life (RUL) estimation but also robustness under distribution shift and support for decision-making under uncertainty. However, mo...

Background: In calibration, analytical figures of merit (AFOMs) are statistical parameters of great importance for method validation. In recent decades, relevant contributions have been made to estimate AFOMs in many cal...

Abstract The computation of optimal routes considering multiple factors is a key challenge in operations research, with significant impact on practical decision-making and real-world efficiency. Optimal bus transit route...

Abstract The rising complexity of urban areas, along with growing public safety needs, has made intelligent video surveillance systems more essential. The current surveillance systems that rely on human observation and p...

Abstract Background Deep learning faces a significant bottleneck in medical image analysis due to its reliance on large-scale, expert-annotated datasets. This challenge is acute in ophthalmology, particularly for detecti...

Abstract Developing musculoskeletal hand models requires a variety of experimental biomechanics data. However, collecting robust biomechanics hand data is a time intensive process leading to a lack of widely available da...

Car-following models (CFMs) are fundamental to traffic flow analysis and autonomous driving. Although calibrated physics-based and trained data-driven CFMs can replicate human driving behavior, their reliance on specific...

Abstract Although UNet has proven its success in various tasks involving medical image segmentation, its capacity to capture global context is restricted by the finite receptive field inherent to convolutional operations...

Wildfires are natural hazards that threaten ecosystems, communities, and economies, and they have shown a significant increase in frequency and intensity in recent years. Accurate wildfire spread prediction is critical f...

IntroductionAccurate segmentation of retinal blood vessels is essential for the early diagnosis of ophthalmic and systemic diseases such as diabetes, hypertension, and cardiovascular disorders. However, challenges such a...