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The integration of renewable energy sources into modern power systems is a global priority aimed at reducing carbon emissions, decreasing fossil fuel dependency, and advancing sustainable development goals. In this conte...

Abstract Corollary discharge denotes internal signals about the expected sensory consequences of one’s own actions, leading to reduced sensory responses to self-generated stimulation. To investigate the underlying neur...

Vegetation optical depth (VOD), as a key parameter of vegetation, plays an important role in the process of vegetation growth and change. The spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) technolog...

IntroductionThe COVID-19 pandemic has reduced system resilience, caused economic welfare loss, and widened disparities in healthcare access. This study aims to identify the macro-level factors contributing to COVID-19 va...

Nitrogen dioxide (NO2) is a critical air pollutant with significant environmental and human health impacts, yet global and long-term NO2 datasets with daily continuity and fine spatial resolution remain limited. In this ...

Peatlands are major carbon stores that are sensitive to climate change and increasingly affected by human activity. Accurate assessment of carbon stocks and modelling of peatland responses to future climate scenarios req...

Abstract Graph neural networks (GNNs) are widely used as surrogates for costly experiments and first-principles simulations to study the behavior of compounds at atomistic scale, and their architectural complexity is con...

Abstract Globally groundwater depletion threatens water security with aquifer storage declining at 300 km³/year. Climate change intensifies flood frequency and magnitude causing agricultural and other losses. Punjab, I...

Abstract The Error Diffusion Learning Algorithm (EDLA) is a learning scheme that performs synaptically local weight updates driven by a single, globally defined error signal. Although originally proposed as an alternativ...

Abstract The integration of the sixth-generation (6G) communication technology and the Industrial Internet of Things (IIoT) has realized the intelligence and automation of industrial applications. However, due to the com...

In the context of global warming, heavy precipitation is a frequent and impactful hazardous event. Timely identification of meteorological conditions associated with heavy rainfall is critical for urban flood risk manage...

Abstract Background Knee osteoarthritis (OA) is a leading global cause of disability, yet conventional tools lack sensitivity for early detection and precise prognostication. Artificial intelligence (AI) and machine lear...

Abstract Federated Learning (FL) has been widely used in Internet of Things (IoT) environments as a promising decentralized framework capable of collaborative model training without exposing local data. Despite its advan...

Global food security relies heavily on rice production, which is continuously threatened by crop diseases. Although deep learning (DL) models have demonstrated strong diagnostic performance, their high computational and ...

Lung diseases such as pneumonia, tuberculosis, COVID-19, and lung cancer remain significant global health challenges that demand rapid and accurate diagnosis to improve patient outcomes. This study proposes NASNet-ViT, a...

Life cycle assessment (LCA) is critical for credible climate decisions, although practice varies contextually. This review explains when to use attributional (ALCA) versus consequential (CLCA) LCAs, consolidating guidanc...

The Global Flood Awareness System (GloFAS) is a promising flood-modelling tool available for most river basins worldwide. However, it contains inherent biases, notably linked to its spatial resolution. This study propose...

Tuberculosis (TB) continues to be one of the foremost public health issues in the world, and remains the second most salient communicable cause of death after COVID-19. In 2022, TB accounted for 10.6 million new infectio...

IntroductionWhilst individually rare, affecting only a small percentage of the population, rare diseases as a whole impact around 6% of the global population (with this number likely an underestimate). Rare diseases are ...

BackgroundChildhood obesity represents a significant global public health challenge. Accurate and rapid prediction models for identifying obesity risk in children and adolescents are essential for facilitating early prev...

Abstract Background Colorectal signet ring cell carcinoma (CSRCC) is a rare subtype of colorectal cancer characterized by an exceptionally poor prognosis. Currently, accurate survival prediction models for CSRCC are lack...

Environmental, social, and governance (ESG) considerations are becoming increasingly vital in evaluating corporate performance and addressing global challenges. This study examines the ESG emphasis of leading companies i...

Ethnomathematics, which integrates mathematical practices grounded in cultural traditions, has gained prominence as an approach to fostering culturally responsive learning in elementary mathematics education. This system...

Abstract The Internet plays a pivotal role in tackling global climate challenges, particularly in facilitating a transition toward low-carbon behavior. However, the mechanisms by which the Internet shapes low-carbon beha...