diffusion models

A rigorous data-driven approach to defect nucleation in metals linking kinetic properties and (dis)order parameters.

Nucleation processes, through which a new structure progressively forms within a pre-existing homogeneous phase, are fundamental in materials science but are also typically non-trivial to elucidate. Cases in which defects (or disorder) nucleate within an initially ordered structure are no exception. A prominent example...

Technological ecosystem mapping in facilities management: insights from patent data mining

Purpose This study aims to examine the technological evolution of the facilities management (FM) sector through patent-based analysis, identifying innovation trajectories, leading countries and organizations and the primary thematic domains driving digital transformation. It also explores how intellectual property (IP)...

On the existence of optimal set-valued decoders and their accuracy bounds for ill-posed inverse problems

Abstract Ill-posed inverse problems occur everywhere in the sciences, including medical imaging, radar, astronomy, etc., yielding underdetermined or ill-posed linear (non-linear) reconstruction problems. There are now a myriad of techniques to design decoders/reconstruction methods that can tackle such problems, rangin...

Reconsideration of the DTI-ALPS index as a glymphatic surrogate: disease-specific findings in small vessel disease due to cerebral amyloid angiopathy or arteriolosclerosis

Objectives To explore the disease-specific performance of diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index in cerebral amyloid angiopathy (CAA) and arteriolosclerosis CSVD (aCSVD). Methods We retrospectively enrolled probable CAA or aCSVD patients who underwent 5.0T MRI. Disease-specific...

Multimodal artificial intelligence in epilepsy: antiseizure medication response, epileptogenic zone localization, and surgical outcome prediction

Epilepsy remains difficult to manage because approximately 30% of patients develop drug-resistant epilepsy, epileptogenic zones may remain occult on conventional magnetic resonance imaging, and surgical outcomes vary substantially. Multimodal artificial intelligence (AI) can integrate structural and functional MRI, pos...

Climate-conditional diffusion models for synthetic soil fertility data in data-scarce regions

DIRECT 1.0: a diffusion-based generative model for dense sea surface temperature reconstructions from sparse satellite observations

DI, a conditional generative framework for dense SST reconstruction that models the full distribution of plausible solutions rather than a single deterministic estimate, is introduced, enabling reliable SST reconstruction from sparse satellite observations.

Diffusion Equation with Riemann–Liouville Derivative in the Angular Domain

This paper is concerned with a boundary value problem for a fractional-order diffusion equation involving the Riemann–Liouville fractional derivative with respect to time in an angular domain. The distinctive feature of the formulation is that the lower limit of the fractional operator coincides with the spatial variab...

Data-Driven Molecular Design of TFC Membrane Monomers with Reduced PFAS Affinity

Abstract Per- and polyfluoroalkyl substances (PFAS) are persistent aquatic contaminants that challenge nanofiltration (NF) and reverse osmosis (RO) treatment, particularly when trace-level permeation compromises water-quality goals. Beyond steric and electrostatic exclusion, PFAS transport through thin-film composite (...

AlphaFold 3: Architecture and Applications in Protein–Ligand Complex Prediction

This article systematically reviews the technical architecture and core algorithm modules of AlphaFold3, and looks forward to the application progress in the construction of protein-ligand complex structures, including the improvement in the confidence of pocket-type ligands paired with G protein-coupled receptors comp...

A Case Study on the Robustness of Traffic Signal Control from a Data Science Perspective: The RobustLight Diffusion Reinforcement Learning Framework

Damaged sensor data, often caused by noise interference and data loss, impairs the decision-making accuracy of Deep Reinforcement Learning (DRL) traffic signal control models. This paper takes RobustLight (ICML 2025) as the core case and analyzes it from a data science perspective. We introduce DRL-based traffic signal...

Evolution, Comparison, and Trend Prospects of Text Generated Images Based on Deep Learning

This paper summarizes the mainstream optimization research directions, such as lightweight, multi architecture integration, and multi condition controllable generation, such as lightweight, multi architecture integration, and multi condition controllable generation.