Staffing & Scheduling

Fidelity to territory and mate and the causes and consequences of breeding dispersal in American goshawk (Astur atricapillus).

Using mark-resight data, we investigated fidelity to territory and mate as well as breeding dispersal rates and the causes and consequences of breeding dispersal in a 20-year study of American goshawks (Astur atricapillus) in Arizona, USA. Generalized Additive Mixed Models were used to identify the relative contributions of four prominent explanatory variables (eggs laid, nest failed, nest success...

High-Performance Ferroelectric Field-Effect Transistors Based on Ultrathin Indium Oxide for Neuromorphic Computing.

The emergence of artificial intelligence has revealed the limitations of traditional von Neumann computing systems in fulfilling the current computational requirements. In-memory computing (IMC) has been generally considered as a promising architecture to break the von Neumann bottleneck, where the FeFET is a strong candidate for developing IMC hardware, but remains challenging. In this work, we d...

Machine-learning-assisted universal protein activation in living mice.

A universal strategy to precisely control protein activation in living animals is crucial for gain-of-function study of proteins under in vivo setting...

Investigation of novel carboxymethyl chitosan-based bioinks for 3D bioprinting of neural tissues.

The formulation of bioinks is critical for successful 3D bioprinting. It influences printability, stability, and cell behavior. This study focused on ...

Early signs of strong El Niño-Southern Oscillation episodes.

The El Niño-Southern Oscillation (ENSO) is the Earth's most prominent source of year-to-year climate variability, occurring in the tropical Pacific bu...

Machine learning based adaptive traffic prediction and control using edge impulse platform.

Traffic congestion and delays are two major challenges in modern vehicle traffic control systems. These issues can be mitigated through an efficient a...

SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End Devices.

The proliferation of end devices has led to a distributed computing paradigm, wherein on-device machine learning models continuously process diverse d...

Triaging Clients at Risk of Disengagement from HIV Care: Application of a Predictive Model to Clinical Trial Data in South Africa.

PURPOSE: To reach South Africa's targets for HIV treatment and viral suppression, retention on antiretroviral therapy (ART) must increase. Here, we ai...

Multi-response optimization and validation analysis in the detection of acetochlor and butachlor by HPLC based on D-optimal design methodology.

Acetochlor and butachlor, widely used herbicides, pose environmental and health risks through water contamination. This study developed a high-perform...

Dual-action membrane-chimeric liposomes with self-reinforcing targeting for acute lung injury treatment.

Acute lung injury (ALI) is a common acute and critical syndrome with high mortality. The uncontrollable feedback loop of inflammation is the primary c...

Artificial Intelligence Methods in the Detection of Oral Diseases on Pantomographic Images-A Systematic Narrative Review.

Artificial intelligence (AI) is playing an increasingly important role in everyday dental practice and diagnosis, especially in the area of analysing...

Surgery scheduling based on large language models.

Large Language Models (LLMs) have shown remarkable potential in various fields. This study explores their application in solving multi-objective combi...

Unsupervised Test-Time Adaptation for Hepatic Steatosis Grading Using Ultrasound B-Mode Images.

Ultrasound (US) is considered a key modality for the clinical assessment of hepatic steatosis (i.e., fatty liver) due to its noninvasiveness and avail...

Active Organic Salts Enabling Non-Intrusive Electrolyte Presodiation Strategy.

Na-ion batteries show great promise, but their practical utilization is hindered by irreversible Na-ion loss during cell formation, resulting in initi...

Technological advancement spurs Komagataella phaffii as a next-generation platform for sustainable biomanufacturing.

Biomanufacturing stands as a cornerstone of sustainable industrial development, necessitating a shift toward non-food carbon feedstocks to alleviate a...

Machine Learning for Hand Surgeons: Emerging Clinical Applications.

Machine learning (ML) is transforming medicine and holds substantial potential in hand surgery to manage complex conditions, predict surgical outcomes...

Interpretable inverse iteration mean shift networks for clustering tasks.

Neural networks have become the standard approach for tasks such as computer vision, machine translation and pattern recognition. While they exhibit s...

Development and Validation of the Novel Exergame-Integrated Robotic Stepper Device for Seated Lower Limb Rehabilitation.

Seated rehabilitation is essential in early-stage recovery for patients who can sit but cannot stand or walk. Robotic-based lower limb rehabilitation ...

Integrating genetic variation with deep learning provides context for variants impacting transcription factor binding during embryogenesis.

Understanding how genetic variation impacts transcription factor (TF) binding remains a major challenge, limiting our ability to model disease-associa...

Artificial intelligence-based modeling of biogas production in a combined microbial electrolysis cell-anaerobic digestion system using artificial neural networks and adaptive neuro-fuzzy inference system.

Accurate prediction of biogas production is essential for optimizing process performance, enhancing system stability, and enabling efficient resource ...