31 to 40 of 3,409 Results
May 8, 2026 - NIE Data Repository (Harvested)
Ali, Farhan, 2026, "Related data for: Curiosity in Times of Uncertainty: Dynamics of Student Question-Posing in Online Educational Discussion", https://doi.org/10.25340/R4/SYASFR
Related data for: Curiosity in Times of Uncertainty: Dynamics of Student Question-Posing in Online Educational DiscussionThis Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data. |
May 8, 2026 - NIE Data Repository (Harvested)
Yong, Minglee; Tilley, Jacqueline L., 2026, "Related Data for: Sociocultural influences on cognitive mechanisms underlying obsessive‐compulsive symptoms: The role of fear of losing out, conformity, and religiosity", https://doi.org/10.25340/R4/K4L1FH
Sociocultural factors are known to influence the phenomenology of obsessive-compulsive disorder (OCD). However, less is known about how these factors could be related to the underlying mechanisms of OCD. This study aimed to explore the influence of sociocultural factors, namely,...This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data. |
May 8, 2026 - NIE Data Repository (Harvested)
Yong, Minglee; Fang, Angela; McCarty, Carolyn A., 2026, "Related Data for: Longitudinal coupling of obsessive-compulsive symptoms with depressive and anxiety symptoms: A cross-domain latent growth curve analysis", https://doi.org/10.25340/R4/YVLYDH
Obsessive-compulsive (OC) symptoms frequently co-occur with depressive and anxiety symptoms, yet the covariation of these symptoms over time is understudied. In this study, 2364 young adults (18–30 years) from a public university in Singapore were followed across five waves over...This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data. |
May 7, 2026School of Physical and Mathematical Sciences (SPMS)
Research topics: • AI for Photonics • Scientific Deep Learning • Optical Super-resolution Imaging • Optical Metrology • Topological AI • Structured Light |
May 4, 2026 - TAN Li Yi
Tan, Li Yi, 2026, "Replication Data for: An Investigation into the Occupational Safety of Using Fe3O4 Silica-Coated Magnetic Particles for Fingerprint Dusting", https://doi.org/10.21979/N9/0EBMNO, DR-NTU (Data), V1, UNF:6:BFfoThAzHZSoffSc35HA7Q== [fileUNF]
Replication Data for: An Investigation into the Occupational Safety of Using Fe3O4 Silica-Coated Magnetic Particles for Fingerprint Dusting |
May 2, 2026School of Physical and Mathematical Sciences (SPMS)
Research Topics: Electromagnetic metamaterials and metasurfaces Domain knowledge-guided AI design methods AI-empowered design of electromagnetic metamaterials and antennas Phased array antennas Time-reversal electromagnetics Electromagnetic toroidal pulses |
Apr 30, 2026 - Bent WEBER
Huang, Zihao; Weber, Bent, 2026, "Final Data for: Controlling an altermagnetic spin density wave in the kagome magnet CsCr3Sb5", https://doi.org/10.21979/N9/JBLUVG, DR-NTU (Data), V2
This file contains all source data in main text |
Apr 29, 2026 - Mengda REN
Lo, Chih Hung; Ren, Mengda; Loi, Gavin Wen Zhao; Saipuljumri, Eka Norfaishanty; Indajang, Jonathan; Lim, Kah Leong; Zeng, Jialiu, 2026, "Replication Data for: Lysosome-Acidifying Nanoparticles Rescue A30P α-Synuclein Induced Neuronal Death in Cellular and Drosophila Models of Parkinson's Disease", https://doi.org/10.21979/N9/SBCIPP, DR-NTU (Data), V1, UNF:6:LEO4c+Jaez4Egr2Ht866VQ== [fileUNF]
Source data for Lo, C. H., et al. (2026). "Lysosome-Acidifying Nanoparticles Rescue A30P α-Synuclein Induced Neuronal Death in Cellular and Drosophila Models of Parkinson's Disease." Advanced Healthcare Materials n/a(n/a): e02906. https://doi.org/10.1002/adhm.202502906 |
Apr 28, 2026 - S-Lab for Advanced Intelligence
Xu, Yuanmu; Hou, Guanli; Hu, Jiangbei; Ren, Tenglong; Wang, Xiaokun; Zhang, Yalan; Ban, Xiaojuan; Qian, Chen; Hou, Fei; He, Ying, 2025, "PGA-NeuS: Physics and Geometry-Augmented Neural Implicit Surfaces for Rigid Bodies", https://doi.org/10.21979/N9/LTXKFL, DR-NTU (Data), V2
This paper tackles the challenges of physics-based simulation of rigid bodies in neural rendering, focusing on 3D model representation and collision handling. A synthetic and real-world dataset is also included in the paper. |
