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The shift toward sustainable and intelligent buildings has accelerated the demand for advanced maintenance strategies that reduce energy waste, downtime, and improve reliability. Traditional maintenance approaches (react...

Importance Emergency departments (EDs) face significant documentation burdens due to reliance on unstructured clinical narratives, hindering efficiency, particularly in pediatric care. Large language models (LLMs) offer ...

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...

Prompt engineering involves manual design and optimization of text-based instructions or queries, enabling precise control over outputs generated by pre-trained large language models (LLMs) and ensuring alignment with de...

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...

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 Finding interesting phenomena is the core of scientific discovery, but the notion of interestingness is vaguely defined and heavily reliant on manual judgment. We present InterFeat, an integrative pipeline for a...

In recent years, large language models and agent systems based on them have been considered a promising tool for the digital transformation of public administration. However, the practical effectiveness of such systems i...

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, ...

Abstract BackgroundRisk of bias (RoB) assessment of randomized clinical trials (RCTs) is vital to answering systematic review questions accurately. Manual RoB assessment for hundreds of RCTs is a cognitively ...

This research investigates how multilingual news circulation produces fundamentally new textual formations rather than reproducing the original message across languages. By tracing a single news event through three media...

Abstract BackgroundGenerative artificial intelligence models, especially reasoning large language models (LLMs), are gaining adoption in health care for diagnostic decision support and medical education. Deep...

The public sphere often struggles with a trade-off between authentic, small-scale discourse and broad, superficial debate dominated by influential entities. This study explores how media and information literacy (MIL) ca...

Few-shot object detection (FSOD) recently garnered increasing attention in remote sensing images (RSIs). Although FSOD has achieved success in natural sense, the large size and complex backgrounds of RSIs make FSOD espec...

Understanding how consumers behave in e-commerce is essential for businesses, especially in today’s digital world where people rely heavily on online shopping platforms. A key part of this understanding comes from sent...

ABSTRACT: Objective: To investigate the effects of commonly prescribed antibiotics and nonsteroidal anti-inflammatory drugs (NSAIDs) during early life on enamel development through a systematic review with quantitative ...

Abstract This article explores how collective attention can be both disrupted and enhanced by artificial intelligence. It examines how the rise of algorithmic recommendation systems, generative media, and large-scale lan...

Background: This explorative study focuses on the representations of multiplication that Mozambican primary teachers use. With a particular focus on representations of multiplication, the article presents examples of mo...

Abstract Collaborative filtering and neural recommendation models have advanced substantially over the past decade, yet they frequently struggle to capture the fine-grained structure of user preferences and the rich, mul...

Abstract Background N6-methyladenosine ( $$m^{6}A$$ ) plays a crucial role in enriching RNA functional and genetic information. While deep learning has advanced $$m^{6}A$$ site identification, current state-of-the-art me...

This Campbell systematic review examines the impact of reducing the maximum duration of unemployment benefits on job‐finding rates. Seven studies were included in the review, all of which are from European countries. I...

This Campbell systematic review assesses the effectiveness of school‐based decision‐making. The review summarises findings from 17 impact studies and nine studies of barriers and enablers. School‐based decision‐m...

Abstract Background Agroforestry, the intentional integration of trees or other woody perennials with crops or livestock in production systems, is being widely promoted as a conservation and development tool to help meet...

Artificial intelligence, particularly large-language models, increasingly informs clinical decision-making, from triage to treatment recommendations. While promising efficiency and objectivity, these systems can encode a...