DR-NTU (Data) (Nanyang Technological University)
DR-NTU (Data) (Nanyang Technological University)Not a member yet
1955 research outputs found
Sort by
Replication Data for: PyQuake3D: A Python Tool for 3-D Earthquake Sequence Simulations of Seismic and Aseismic Slip
No full textThis repository contains the source code and input data necessary to reproduce the numerical experiments presented in the accompanying methodological paper. It includes the full PyQuake3D simulation framework (version 1.0.0), along with all input geometry and parameter files used in the study. The examples provided cover the key cases discussed in the manuscript, including simulations of seismic cycles on a planar fault with frictional heterogeneity, a geologically realistic model of the East Anatolian Fault Zone, and a laboratory-inspired fault slip experiment. Together, these materials allow for full reproducibility of the results and figures presented in the paper. For further details on how to configure and run the simulations, please refer to the included user manual. For any questions or collaboration inquiries, please contact Dr. Luca Dal Zilio ([email protected]) or Dr. Rongjiang Tang ([email protected])
Replication Data for: Alginate exopolymer significantly modulates the viscoelastic properties and resilience of bacterial biofilms
No full textThe data set contains the raw data of the microscopy image files of biofilms and the recolonizing bacteria, the mat files used to generate the mean square displacements in particle tracking experiments (before during and after treatment with NAC), excel files with compiled data used to generate figure in the manuscript
Unlocking the Power of SAM 2 for Few-Shot Segmentation
No full textFew-Shot Segmentation (FSS) aims to learn class-agnostic segmentation on few classes to segment arbitrary classes, but at the risk of overfitting. To address this, some methods use the well-learned knowledge of foundation models (e.g., SAM) to simplify the learning process. Recently, SAM 2 has extended SAM by supporting video segmentation, whose class-agnostic matching ability is useful to FSS. A simple idea is to encode support foreground (FG) features as memory, with which query FG features are matched and fused. Unfortunately, the FG objects in different frames of SAM 2's video data are always the same identity, while those in FSS are different identities, i.e., the matching step is incompatible. Therefore, we design Pseudo Prompt Generator to encode pseudo query memory, matching with query features in a compatible way. However, the memories can never be as accurate as the real ones, i.e., they are likely to contain incomplete query FG, but some unexpected query background (BG) features, leading to wrong segmentation. Hence, we further design Iterative Memory Refinement to fuse more query FG features into the memory, and devise a Support-Calibrated Memory Attention to suppress the unexpected query BG features in memory. Extensive experiments have been conducted on PASCAL-5i and COCO-20i to validate the effectiveness of our design, e.g., the 1-shot mIoU can be 4.2% better than the best baseline
Replication Data for: Observation of returning Thouless pumping
No full textThis repository contains the data and code used for the analyses presented in the manuscript "Cheng, Z., Yue, S., Long, Y. et al. Observation of returning Thouless pumping. Nat Commun 16, 9669 (2025). https://doi.org/10.1038/s41467-025-64671-w"
It is also related to preprint arXiv:2505.0680
Data used for: Extremely stiff and lightweight auxetic metamaterial designs enabled by asymmetric strut cross-sections
No full textData used in the journal publication "Extremely stiff and lightweight auxetic metamaterial designs enabled by asymmetric strut cross-sections
Replication Data for: Direct determination of multiphoton absorption cross-sections by transient absorption spectroscopy
No full textSingle- and multi-photon absorption cross-sections quantify the likelihood that a material will absorb one or more photons at a given wavelength. This crtical parameter is fundamental to understanding light-matter interactions that underpin key applications in spectroscopy, photochemistry and advanced imaging techniques like multi-photon microscopy and deep tissue imaging. Conventional methods for measuring absorption cross-sections are often limited by sensitivity to sample morphology, type, concentration, and high excitation intensities – factors that can compromise reliability, increase experimental complexity, and risk sample damage. Herein, we present a direct, robust, and versatile method for quantifying absorption cross-sections across single- to multi-photon regimes, based on the saturation behaviour of transient absorption signals. Using this approach, we report for the first time the three-photon and four-photon absorption cross-sections of CsPbI3 perovskite nanocrystals and CdSe/ZnS quantum dots under 1700 nm and 2100 nm excitation. These values excceed those of incumbent materials used for mouse deep-brain imaging by at least an order of magnitude. Our method does not rely on photoluminescence signals, making it suitable for weakly or non-emissive materials. Importantly, our work provides a powerful generalizable tool to accelerate the discovery and optimization of next generation photon-harvesting materials
Replication Data for: Degradability and remineralization of peat-derived terrestrial dissolved organic carbon in the Sunda Shelf Sea
No full textDataset and code for the analysis in this study
SFDM: Robust Decomposition of Geometry and Reflectance for Realistic Face Rendering from Sparse-view Images
No full textIn this study, we introduce a novel two-stage technique for decomposing and reconstructing facial features from sparse-view images, a task made challenging by the unique geometry and complex skin reflectance of each individual. To synthesize 3D facial models more realistically, we endeavor to decouple key facial attributes from the RGB color, including geometry, diffuse reflectance, and specular reflectance. Specifically, we design a Sparse-view Face Decomposition Model (SFDM): 1) In the first stage, we create a general facial template from a wide array of individual faces, encapsulating essential geometric and reflectance characteristics. 2) Guided by this template, we refine a specific facial model for each individual in the second stage, considering the interaction between geometry and reflectance, as well as the effects of subsurface scattering on the skin. With these advances, our method can reconstruct high-quality facial representations from as few as three images. The comprehensive evaluation and comparison reveal that our approach outperforms existing methods by effectively disentangling geometric and reflectance components, significantly enhancing the quality of synthesized novel views, and paving the way for applications in facial relighting and reflectance editing
Final Data for: Symmetry Breaking and Spin−Orbit Coupling for Individual Vacancy-Induced In-Gap States in MoS2 Monolayers
No full textFinal Data for: "Symmetry Breaking and Spin−Orbit Coupling for Individual Vacancy-Induced In-Gap States in MoS2 Monolayers
Replication Data for: Training Children's Strategic Reasoning
No full textThis projects investigates how theory-of-mind training through a series of drama classes influences children's decision-making