Infection control / Modes of transmission

Rapid Development of Efficient Participant-Specific Computational Models of the Wrist

While computational modeling may help to develop new treatment options for hand and wrist injuries, at present, few models exist. The time and expertise required to develop and use these models is considerable. Moreover, most do not allow for variation of material properties, instead relying on literature reported averages. We have developed a novel automated workflow combining non-linear morphi...

Learning the Contact Manifold for Accurate Pose Estimation During Peg-in-Hole Insertion of Complex Geometries

Contact-rich assembly of complex, non-convex parts with tight tolerances remains a formidable challenge. Purely model-based methods struggle with discontinuous contact dynamics, while model-free methods require vast data and often lack precision. In this work, we introduce a hybrid framework that uses only contact-state information between a complex peg and its mating hole to recover the full SE...

Reflectance Prediction-based Knowledge Distillation for Robust 3D Object Detection in Compressed Point Clouds

Regarding intelligent transportation systems for vehicle networking, low-bitrate transmission via lossy point cloud compression is vital for facilit...

A Data-Driven Approach to Assessing Hepatitis B Mother-to-Child Transmission Risk Prediction Model: Machine Learning Perspective.

BACKGROUND: Hepatitis B virus (HBV) can be transmitted from mother to child either through transplacental infection or via blood-to-blood contact duri...

Self-powered smart contact lenses: a multidisciplinary approach to micro-scale energy and 900 MHz - 1.1 GHz bandwidth microfabricated loop antennas communication systems

Smart contact lenses are at the forefront of integrating microelectronics, biomedical engineering, and optics into wearable technologies. This work ...

Impact of Distance on Epidemiological Dynamics in Human Connection Network with Mobility

The spread of infectious diseases is often influenced by human mobility across different geographical regions. Although numerous studies have invest...

Sampling-Based System Identification with Active Exploration for Legged Robot Sim2Real Learning

Sim-to-real discrepancies hinder learning-based policies from achieving high-precision tasks in the real world. While Domain Randomization (DR) is c...

A Digital Score Based on Circulating-Tumor-Cells-Derived mRNA Quantification and Machine Learning for Early Colorectal Cancer Detection.

Circulating tumor cells (CTCs) serve as valuable biomarkers in tumor circulation, carrying essential primary tumor information. The purification of CT...

EpiLLM: Unlocking the Potential of Large Language Models in Epidemic Forecasting

Advanced epidemic forecasting is critical for enabling precision containment strategies, highlighting its strategic importance for public health sec...

Single Image Reflection Removal via inter-layer Complementarity

Although dual-stream architectures have achieved remarkable success in single image reflection removal, they fail to fully exploit inter-layer compl...

Poisson random measure noise-induced coherence in epidemiological priors informed deep neural networks to identify the intensity of virus dynamics.

Differential equations-based epidemiological compartmental systems and deep neural networks-based artificial intelligence can effectively analyze and ...

Prediction of airborne bacterial concentrations and identification of critical factors in contaminated waste facilities: Insights into interpretable machine learning models.

The efficient prediction of airborne bacterial concentrations is crucial for better understanding and management of environmental sanitation risks in ...

Automated and AI-Based Communication in the GP Practice as a Replacement for Personal Doctor-Patient Contact - A Patient Survey on Acceptance.

BACKGROUND/AIM: The study examines patient acceptance of automated and AI-based communication as a replacement for personal doctor-patient contact in ...

Contactless Cardiac Pulse Monitoring Using Event Cameras

Time event cameras are a novel technology for recording scene information at extremely low latency and with low power consumption. Event cameras out...

Neural Code Translation With LIF Neuron Microcircuits.

Spiking neural networks (SNNs) provide an energy-efficient alternative to traditional artificial neural networks, leveraging diverse neural encoding s...

Deep Learning Based Surface Classification of Functionalized Polymer Coatings.

Low-technology characterization of material surfaces poses a challenge of significant importance for many scientific fields such as medical implants, ...

Few-shot Semantic Encoding and Decoding for Video Surveillance

With the continuous increase in the number and resolution of video surveillance cameras, the burden of transmitting and storing surveillance video i...

A deep learning and molecular modeling approach to repurposing Cangrelor as a potential inhibitor of Nipah virus.

Deforestation, urbanization, and climate change have significantly increased the risk of zoonotic diseases. Nipah virus (NiV) of Paramyxoviridae famil...

Investigation of Bleeding Disorders: When and How Should We Test Platelet Functions?

Inherited platelet disorders (IPDs) are rare conditions with diverse underlying pathophysiology which should be suspected in patients presenting with ...

Enhancing Monocular Height Estimation via Sparse LiDAR-Guided Correction

Monocular height estimation (MHE) from very-high-resolution (VHR) remote sensing imagery via deep learning is notoriously challenging due to the lac...