Staffing & Scheduling

Energy-aware load balancing in cloud environments using graph neural networks and grey wolf optimization.

Cloud computing infrastructures must constantly maintain a balance between resource utilization and energy consumption to work effective under dynamic workloads. The training expense and generalizability of machine learning-based load balancing algorithms are both considerable, while existing methods often fails in adjusting in real time conditions. To work with both energy-aware and scalable load...

Trade-offs and synergies of ecosystem services in high density cities: Revealing nonlinear driving mechanisms through machine learning.

Metropolises are confronted with ecosystem degradation driven by rapid urbanization and continuously intensified human activities, posing significant challenges to human well-being and urban sustainable development. Identifying the trade-offs and synergies among ecosystem services (ESs) and their underlying driving mechanisms forms the foundation for implementing effective ecological management st...

Machine learning approaches for resource management and forecasting in energy consumption systems.

Renewable Energy Systems (RES) have become necessary with the growing need for sustainable energy globally; however, RES faces several problems such a...

How to Train a Shallow Ensemble.

Shallow ensembles provide a convenient strategy for uncertainty quantification in machine-learning interatomic potentials, which is computationally ef...

Artificial intelligence in the assessment of epilepsy-related genetic mutations: Learned from GABAA receptors and GABA transporter 1.

This review examines how recent genetic and technological advances have transformed our understanding and treatment of genetic epilepsies (GEs), with ...

NRRS: Neural Russian Roulette and Splitting.

We propose a novel framework for Russian Roulette and Splitting (RRS) tailored to wavefront path tracing, a highly parallel rendering architecture tha...

Musculoskeletal Interventions: The Past, Present, and Future.

Musculoskeletal radiology has transitioned to "musculoskeletal imaging and intervention," encompassing both traditional diagnostic roles and specializ...

Older adults' perceptions of artificial intelligence in healthcare: an exploratory quantitative analysis.

BACKGROUND AND OBJECTIVES: Artificial intelligence (AI) has the potential to improve healthcare outcomes. There is limited literature regarding older ...

Resource Use Patterns in US Telehealth Services: Machine Learning and Clustering Analysis Across 4 Specialties.

BACKGROUND: The expansion of telehealth services, particularly during the COVID-19 pandemic, has transformed health care delivery in the United States...

Advances in neuropharmacology: Innovative drug strategies targeting synaptic plasticity, neuroinflammation, and ion channel regulation for future CNS treatments.

As our understanding of the molecular and cellular mechanisms underlying central nervous system (CNS) disorders expands, neuropharmacology is undergoi...

Intelligent technologies in operating room nursing: A bibliometric analysis of research.

BACKGROUND: The integration of intelligent technologies in operating room nursing represents a rapidly evolving field. Intelligent operating room nurs...

From Anger Detection to Intensity Modeling: A Two-Stage Machine Learning Approach Using Driving Performance and Physiological Signals.

OCCUPATIONAL APPLICATIONSThis study demonstrated that driver anger can be feasibly modeled across three intensity levels using combined driving perfor...

SelfBlending: Artificial Intelligence-driven Augmentation with Hand Interactions for Seamless Reality Blending in Virtual Environments.

Accessing real-world objects during immersive virtual reality (VR) experiences remains challenging, as current cross-reality systems often rely on pre...

Molecular skeleton programming of premediators in sulfur electrochemistry.

Molecular mediators have demonstrated broad applicability in electrolyte chemistry of lithium-sulfur batteries, transforming sulfur conversion from tr...

Rationale and design of a multicenter, prospective, diagnostic clinical study: A study protocol for evaluating the diagnostic validation of deep learning-based noninvasive CT-FFR for in-stent restenosis.

INTRODUCTION: Currently, there are many diagnostic strategies for in-stent restenosis (ISR) used clinically, including invasive coronary angiography (...

Review of risk perception research by cognitive neuroscience technologies in high-risk industry.

Risk perception failure is one of the primary causes of unsafe behavior in high-risk industries. While traditional studies hold value, they often fail...

DDA/DIA mass spectrometry coupled with molecular networking and machine learning: high-coverage profiling of pyrrolizidine alkaloids.

Pyrrolizidine alkaloids (PAs) are naturally occurring toxic secondary metabolites found in plants. However, the identification of PAs often relies on ...

Enabling Advanced Bioinspired Computing and Hardware Security in Sb2(S,Se)3 Memristors via Titanium Interfacial Engineering.

Neuromorphic systems for artificial intelligence require capabilities for both sophisticated sensory perception and secure data processing. However, t...

Artificial Intelligence (AI) Impact on Dental Education and Curriculum: A Systematic Review Following PRISMA Guidelines.

IMPORTANCE: AI technologies increasingly influence dental education, but their instructional value, stakeholder perspectives, and institutional implic...

Alpha phase coding supports feature binding during working memory maintenance.

The ability to successfully retain and manipulate information in working memory (WM) requires that objects' individual features are bound into cohesiv...