Low-carbon optimization scheduling of IES based on enhanced diffusion model for scenario deep generation by Danhao Wang, Daogang Peng, Dongmei Huang, Huirong Zhao, Bogang Qu

“…To effectively address these uncertainties, this paper proposes a scheduling method for IES based on an enhanced DM (Diffusion Models). Firstly, a mathematical model of a regional IES encompassing energy supply devices, energy coupling devices, and energy storage devices is constructed. …”
Get full text

The Approximate Solutions of Three-Dimensional Diffusion and Wave Equations within Local Fractional Derivative Operator by Hassan Kamil Jassim

“…We used the local fractional variational iteration transform method (LFVITM) coupled by the local fractional Laplace transform and variational iteration method to solve three-dimensional diffusion and wave equations with local fractional derivative operator. …”
Get full text

A Lightweight Conditional Diffusion Segmentation Network Based on Deformable Convolution for Surface Defect Detection by Jiusheng Chen, Yibo Zhao, Haibing Wang

“…To solve this problem, a lightweight conditional diffusion segmentation network based on deformable convolution is proposed. …”
Get full text

Approximate and Exact Solutions to Fractional Order Cauchy Reaction-Diffusion Equations by New Combine Techniques by Adnan Khan, Muhammad Imran Liaqat, Muhammad Younis, Ashraful Alam

“…In this paper, we present a simple and efficient novel semianalytic method to acquire approximate and exact solutions for the fractional order Cauchy reaction-diffusion equations (CRDEs). …”
Get full text

Multi-target digital material design via a conditional denoising diffusion probability model by Wei Yue, Yuan Gao, Zhenliang Pan, Fanping Sui, Liwei Lin

“…This work proposes and demonstrates a customizer based on a classifier-free, conditional denoising diffusion probability model (cDDPM) to efficiently create the layouts of digital materials meeting the design goal of multiple mechanical properties all together. …”
Get full text

Predicting hydrogen diffusion in nickel–manganese random alloys using machine learning interatomic potentials by Kazuma Ito, Naoki Matsumura, Yuto Iwasaki, Yasufumi Sakai, Misaho Yamamura, Tomohiko Omura, Junichiro Yamabe, Hisao Matsunaga

“…This approach enables accurate prediction of hydrogen diffusion in random alloys and provides atomic-level insights into alloying effects.…”
Get full text

Electron diffusion at Sn perovskite/fullerene derivative interfaces and its influence on open-circuit voltage by Atushi Sato, Seira Yamaguchi, Akio Hasegawa, Yukihiro Shimoi, Tomoya Nakamura, Atsushi Wakamiya, Kazuhiro Marumoto

“…These insights support efficient optimization of the charge-transporting layer for additional improvement of V OC.…”
Get full text

Quantifying Extremely Rapid Flux Enhancements of Radiation Belt Relativistic Electrons Associated With Radial Diffusion by Si Liu, Qi Yan, Chang Yang, Qinghua Zhou, Zhaoguo He, Yihua He, Zhonglei Gao, Fuliang Xiao

“…Numerical calculations show that chorus can efficiently accelerate seed electrons at L ∼ 8.3. Then radial diffusion further increased the phase space density of relativistic electrons throughout the outer radiation belts, with a remarkable agreement with the observation in magnitude and timescale. …”
Get full text

Optimal Estimation of Shear Strength Parameters Based on Copula Theory Coupling Information Diffusion Technique by Xinlong Zhou, Guang Zhang, Shaohua Hu, Junzhe Li

“…Results indicate that information diffusion distribution can efficiently capture the random volatility of real distributions of shear strength parameters and hold remarkable superiority in modeling marginal distributions. …”
Get full text

Exploring Performance Degradation of Proton Exchange Membrane Fuel Cells Based on Diffusion Transformer Model by Lingling Lv, Pucheng Pei, Peng Ren, He Wang, Geng Wang

“…Proton exchange membrane fuel cells (PEMFCs) stand at the forefront of energy conversion technology, efficiently converting the chemical energy of hydrogen and oxygen directly into electricity. …”
Get full text

Tumor-Associated Macrophages as Key Modulators of Disease Progression in Diffuse Large B-Cell Lymphoma by Corina Joldes, Laura Jimbu, Oana Mesaros, Mihnea Zdrenghea, Bogdan Fetica

“…This paper investigates the connection between TAMs, disease progression, and treatment responses in the most frequent solid hematologic cancer, diffuse large B-cell lymphoma.…”
Get full text

Scalable quality control on processing of large diffusion-weighted and structural magnetic resonance imaging datasets. by Michael E Kim, Chenyu Gao, Nancy R Newlin, Gaurav Rudravaram, Aravind R Krishnan, Karthik Ramadass, Praitayini Kanakaraj, Kurt G Schilling, Blake E Dewey, David A Bennett, Sid O'Bryant, Robert C Barber, Derek Archer, Timothy J Hohman, Shunxing Bao, Zhiyuan Li, Bennett A Landman, Nazirah Mohd Khairi, Alzheimer’s Disease Neuroimaging Initiative, HABS-HD Study Team

“…While researchers must spend time on robust visual QC of data, there are mechanisms by which the process can be streamlined and efficient.…”
Get full text

GraspLDM: Generative 6-DoF Grasp Synthesis Using Latent Diffusion Models by Kuldeep R. Barad, Andrej Orsula, Antoine Richard, Jan Dentler, Miguel A. Olivares-Mendez, Carol Martinez

“…In this work, we present GraspLDM, a modular generative framework for 6-DoF grasp synthesis that uses diffusion models as priors in the latent space of a VAE. …”
Get full text

DiffBTS: A Lightweight Diffusion Model for 3D Multimodal Brain Tumor Segmentation by Zuxin Nie, Jiahong Yang, Chengxuan Li, Yaqin Wang, Jun Tang

“…DiffBTS replaces the conventional self-attention module in the traditional diffusion models by introducing an efficient 3D self-attention mechanism. …”
Get full text

Anodapter: A Unified Framework for Generating Aligned Anomaly Images and Masks Using Diffusion Models by Minkyoung Shin, Seonggyun Jeong, Yong Seok Heo

“…Unlike earlier models such as AnomalyDiffusion, which use separate models for mask and image generation, Anodapter integrates both tasks into a single diffusion model through its proposed Switch Adapter, eliminating misalignment and improving realism. …”
Get full text

Diff-Tree: A Diffusion Model for Diversified Tree Point Cloud Generation with High Realism by Haifeng Xu, Yongjian Huai, Xiaoying Nie, Qingkuo Meng, Xun Zhao, Xuanda Pei, Hao Lu

“…To address these limitations, we propose Diff-Tree, a novel diffusion model-based framework for generating diverse and realistic tree point cloud with reduced dependence on real-world data. …”
Get full text

Neural SHAKE: geometric constraints in neural differential equations by Justin S. Diamond, Markus A. Lill

“…This technique generates lower-energy molecular conformations, enables more efficient subspace exploration, and formally subsumes classifier-guidance-type methods by treating geometric constraints as strict algebraic conditions within the diffusion process. …”
Get full text

Efficient numerosity estimation under limited time. by Joseph A Heng, Michael Woodford, Rafael Polania

“…This model accurately predicts many features of human numerosity estimation as a function of temporal exposure, indicating that humans can rapidly and efficiently sample numerosity information over time. …”
Get full text

Adoption of digital logistics platforms in the maritime logistics industry: based on diffusion of innovations and extended technology acceptance by Yanfeng Liu, Shanshan Zhao, Shuxian Zhao

“…Abstract In the context of an increasingly complex global shipping network and heightened market demand fluctuations, the maritime and logistics industry faces challenges such as greater supply chain management uncertainty and limited improvements in operational efficiency. As a core enabler of digital transformation, digital logistics platforms (DLP) enhance transportation efficiency, strengthen supply chain resilience, and bolster corporate competitiveness. …”
Get full text

Applicability Analysis of Reduced-Order Methods with Proper Orthogonal Decomposition for Neutron Diffusion in Molten Salt Reactor by Zhengyang Zhou, Ming Lin, Maosong Cheng, Yuqing Dai, Xiandi Zuo

“…A set of reduced-order modeling frameworks based on Proper Orthogonal Decomposition (POD) is developed to improve the computational efficiency for neutron diffusion calculations while maintaining accuracy, especially for small samples. …”
Get full text