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Abstract Microrobotic systems offer significant potential for precision medicine by enabling minimally invasive interventions in complex fluidic environments. However, effective operation in these settings requires actua...

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...

Traditional electromechanical cleaning equipment remains overly dependent on human assistance when performing cleaning tasks in unstructured marine environments. With the rapid development of robotic technologies, underw...

BackgroundTar-rich coals serve as an important coal-based oil and gas resource in China, while their pyrolysis product distribution is governed by the coupling effects of coal properties and reaction conditions. Therefor...

Abstract This study presents a novel hybrid methodology combining machine learning (ML) with conventional reservoir simulation to optimize waterflooding in the geologically complex Bahariya Formation, Western Desert, Egy...

IntroductionOsteoarthritis (OA) is a common joint disease characterized by progressive biomechanical deterioration of cartilage tissue. This study aims to develop an explainable ensemble machine learning model capable of...

Abstract Advances in AI have transformed the traditional Internet of Things (IoT) into smarter, more versatile next-generation devices. Enhanced connectivity among sensors, actuators, and appliances boosts data availabil...

Recent advances in the analysis of machine learning (ML) models for accurate prediction have led to new approaches for classifying and clustering variables related to user experience (UX). In this study, however, the foc...

Artificial intelligence (AI) is increasingly used to design and optimize small molecules. However, most current workflows remain centered on drug-candidate objectives, such as potency, ADMET, and drug-likeness, rather th...

Abstract This research employs hybrid machine learning techniques to optimize the mechanical properties of 3D-printed polylactic acid (PLA) lattice structures. By integrating random forest (RF) and XGBoost (XGB) algorith...

Abstract Effort estimation remains a persistent challenge in agile software development, particularly at the user story level where iterative delivery is emphasized. Inaccurate estimations can result in misallocated reso...

Abstract Background Optimization of biotechnological processes is traditionally limited by time-consuming trial-and-error approaches and the complexity of simultaneously optimizing multiple, often conflicting objectives....

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...

Abstract Fine particulate matter (PM2.5) is a significant air pollutant in the Indo Gangetic Basin (IGB), where levels frequently exceed national and WHO air quality standards. Ground observations from 183 CPCB automatic...

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...

Abstract Background Tuberculosis (TB) remains a critical global public health issue, particularly in rapidly urbanizing regions where population density and migration facilitate transmission. While whole-genome sequencin...

Background: Conventional HIV testing approaches continue to fall short of overcoming barriers to HIV testing, especially among key and priority populations at higher risk of acquiring and transmitting HIV. Artificial in...

Accidental ignition of energetic compounds by electrostatic discharge poses significant safety risks, highlighting the need for precise prediction of electric spark sensitivity. Here we develop a novel interpretable mach...

Abstract The design of multi-principal element alloys (MPEAs) is challenged by data scarcity and the complexity of optimizing multiple mechanical properties simultaneously. To address these challenges, we investigate an ...

This paper presents an innovative methodology for modeling and predicting high-frequency harmonic losses in the rotating field of an electrical machine powered by a frequency converter. Conventional approaches are often ...

Abstract Background Chronic conditions cause millions of deaths annually worldwide. Remote patient monitoring using wearable devices and sensors, combined with machine learning (ML), offers promising strategies for disea...

Waste material, including glass, presents significant environmental challenges due to its non-biodegradable nature and low global recycling rates. Incorporating waste glass into concrete offers a sustainable solution, bu...

Abstract Unmanned Aerial Systems (UAS) have become increasingly integral to industries such as agriculture, surveillance, transportation, and entertainment, raising significant concerns about their vulnerability to cyber...

Abstract Considering crop yield prediction as critical to optimizing agricultural practices and food security, this question is critical to U.S. agricultural planning and regional food security; relevant research on corn...