Infection control / Modes of transmission

SceMoS: Scene-Aware 3D Human Motion Synthesis by Planning with Geometry-Grounded Tokens

Synthesizing text-driven 3D human motion within realistic scenes requires learning both semantic intent ("walk to the couch") and physical feasibility (e.g., avoiding collisions). Current methods use generative frameworks that simultaneously learn high-level planning and low-level contact reasoning, and rely on computationally expensive 3D scene data such as point clouds or voxel occupancy grids. ...

TeHOR: Text-Guided 3D Human and Object Reconstruction with Textures

Joint reconstruction of 3D human and object from a single image is an active research area, with pivotal applications in robotics and digital content creation. Despite recent advances, existing approaches suffer from two fundamental limitations. First, their reconstructions rely heavily on physical contact information, which inherently cannot capture non-contact human-object interactions, such as ...

MultiDiffSense: Diffusion-Based Multi-Modal Visuo-Tactile Image Generation Conditioned on Object Shape and Contact Pose

Acquiring aligned visuo-tactile datasets is slow and costly, requiring specialised hardware and large-scale data collection. Synthetic generation is p...

Local REM sleep-N1-wake sleep stage mixing in narcolepsy type 1

Type 1 narcolepsy (NT1), a disorder caused by the loss of hypocretin/orexin transmission, is characterized by daytime sleepiness and symptoms where Ra...

Inferring unobserved vector dynamics for dengue forecasting using physics-informed neural networks and mechanistic transmission models

Accurately characterising mosquito infection dynamics is essential for effective dengue prevention and control, yet these dynamics are rarely observab...

Monocular Reconstruction of Neural Tactile Fields

Robots operating in the real world must plan through environments that deform, yield, and reconfigure under contact, requiring interaction-aware 3D re...

Benchmarking Machine Learning and Automated Image Analysis for Organelle Quantification

Quantitative organelle analysis is highly sensitive to image-processing choices, limiting reproducibility across microscopy studies. Here, we systemat...

Wastewater-informed neural compartmental model for long-horizon case number projections

Wastewater-based epidemiology provides a low-cost, scalable view of community infection dynamics, but converting these signals into actionable epidemi...

Metagenomic strain tracking reveals patterns of bacterial spread and the impact of water chlorination

Bacterial infections are a major cause of morbidity and mortality among children under five in low- and middle-income countries (LMICs). Children in L...

Hand2World: Autoregressive Egocentric Interaction Generation via Free-Space Hand Gestures

Egocentric interactive world models are essential for augmented reality and embodied AI, where visual generation must respond to user input with low l...

HiCInterpolate: 4D Spatiotemporal Interpolation of Hi-C Data for Genome Architecture Analysis.

Motivation: Studying the three-dimensional (3D) structure of a genome, including chromatin loops and Topologically Associating Domains (TADs), is esse...

Deep learning enables quantitative subcellular analysis of plant-microbe interfaces

Specialized host-microbe interfaces are central to cellular interactions in plants. Intracellular structures such as haustoria formed by filamentous p...

[Advances in frontier technologies and innovative applications for the prevention and control of hospital infections associated with multidrug-resistant bacteria].

Hospital-acquired infections (HAIs) significantly increase patient mortality and healthcare burden, with multidrug-resistant organisms (MDROs) exacerb...

Bayesian neural networks enable inference of complex phylodynamic processes

Phylogenetic branching patterns carry essential information about population and diversification dynamic processes, including speciation, extinction, ...

Reducing the labeling burden in time-series mapping using Common Ground: a semi-automated approach to tracking changes in land cover and species over time

Reliable classification of Earth Observation data depends on consistent, up-to-date reference labels. However, collecting new labelled data at each ti...

Closed-loop imitation learning reveals muscle-centric and latent-goal codes in primate sensorimotor cortex

Dexterous grasping requires the seamless integration of proprioceptive feedback with predictive motor commands. Yet, how cortical circuits combine aff...

Agentomics: An Agentic System that Autonomously Develops Novel State-of-the-art Solutions for Biomedical Machine Learning Tasks

Motivation: Extracting knowledge from biomedical data is crucial for advancing our understanding of biological systems and developing novel therapeuti...

Under-Canopy Terrain Reconstruction in Dense Forests Using RGB Imaging and Neural 3D Reconstruction

Mapping the terrain and understory hidden beneath dense forest canopies is of great interest for numerous applications such as search and rescue, trai...

Urban Neural Surface Reconstruction from Constrained Sparse Aerial Imagery with 3D SAR Fusion

Neural surface reconstruction (NSR) has recently shown strong potential for urban 3D reconstruction from multi-view aerial imagery. However, existing ...

Open-Vocabulary Functional 3D Human-Scene Interaction Generation

Generating 3D humans that functionally interact with 3D scenes remains an open problem with applications in embodied AI, robotics, and interactive con...