DR-NTU (Data) (Nanyang Technological University)
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Replication data for: Orfamide A and other secreted factors of Pseudomonas protegens control Pseudomonas aeruginosa biofilm dynamics
No full textThis includes the original replication data files for the submission of the manuscript "Orfamide A and other secreted factors of Pseudomonas protegens control Pseudomonas aeruginosa biofilm dynamics." It includes confocal microscopy image files, prism files for statistical analysis, and plate scan images
Replication Data for: Anti-noise window: subjective perception of active noise reduction and effect of informational masking
No full textThis repository contains replication data to the paper titled: "Anti-noise window: subjective perception of active noise reduction and effect of informational masking
Replication Data for: Regio- and Stereoselective Synthesis of Enol Carboxylate, Phosphate, and Sulfonate Esters via Iodo(III)functionalization of Alkynes
No full textThe experimental data for "Regio- and Stereoselective Synthesis of Enol Carboxylate, Phosphate, and Sulfonate Esters via Iodo(III)functionalization of Alkynes" are deposited
Related Data for: Pearls Hide Behind Linearity: Simplifying Deep Convolutional Networks for Embedded Hardware Systems via Linearity Grafting
No full textThe related data for "Pearls Hide Behind Linearity: Simplifying Deep Convolutional Networks for Embedded Hardware Systems via Linearity Grafting"
Related data for: Quantifying uncertainties in tropical cyclone wind hazard assessment due to synthetic track stochastic variability for Southeast Asia
No full textThis data set contains the rate-adjusted STORM event sets and 100-year return period gust wind hazard maps related to the paper: Jian, W., Lo, E.Y-M., Stojanovski, P., & Pan, T-C. (2023). Quantifying uncertainties in tropical cyclone wind hazard assessment due to synthetic track stochastic variability for Southeast Asia. Weather and Climate Extremes. https://doi.org/10.1016/j.wace.2023.10059
Asset Tokenization
No full textThe increasing adoption of blockchain technology by Singapore’s
financial and healthcare sectors have gained public attention on the
potential benefits of asset tokenization—the conversion of physical
assets (e.g., properties, equities) into fractional digital tokens on a
blockchain platform with legal ownership rights.
To date, financial companies have tokenized assets such as properties
or stocks where individuals could legally purchase or sell fractional
shares of a properties/equities at affordable quantum. In healthcare,
tokenizing health data (e.g., medical health records, physiological data
from health apps/wearables) is gaining traction, where individuals
decide how their data would be used (funnelling it for research or to
make purchasing/investment decision with it).
While there are potential benefits of asset tokenization such as
democratizing access, ownership, and decision-making of health and
financial assets traditionally available to the rich, the benefits may not
be equally accrued by all populations, and potentially may amplify
health and financial inequalities instead of closing them.
This is a experimental survey where we examined factors and messaging conditions where individuals are motivated to exchange their health data for tokenized financial assets
Replication Data for: Dicke superradiance requires interactions beyond nearest-neighbors
No full textPhoton-mediated interactions within an excited ensemble of emitters can result in Dicke superradiance, where the emission rate is greatly enhanced, manifesting as a high-intensity burst at short times. The superradiant burst is most commonly observed in systems with long-range interactions between the emitters, although the minimal interaction range remains unknown. Here, we put forward a new theoretical method to bound the maximum emission rate by upper bounding the spectral radius of an auxiliary Hamiltonian. We harness this tool to prove that for an arbitrary ordered array with only nearest-neighbor interactions in all dimensions, a superradiant burst is not physically observable. We show that Dicke superradiance requires minimally the inclusion of next-nearest-neighbor interactions. For exponentially decaying interactions, the critical coupling is found to be asymptotically independent of the number of emitters in all dimensions, thereby defining the threshold interaction range where the collective enhancement balances out the decoherence effects. Our findings provide key physical insights to the understanding of collective decay in many-body quantum systems, and the designing of superradiant emission in physical systems for applications such as energy harvesting and quantum sensing
Replication Data for: Forman Persistent Ricci Curvature (FPRC) in Protein-Ligand Binding Affinity Predictions
No full textArtificial intelligence (AI) techniques have already been gradually applied to the entire drug design process, from target discovery, lead discovery, lead optimization and preclinical development to the final three phases of clinical trials. Currently, one of the central challenges for AI-based drug design is molecular featurization, which is to identify or design appropriate molecular descriptors or fingerprints. Efficient and transferable molecular descriptors are key to the success of all AI-based drug design models. Here we propose Forman persistent Ricci curvature (FPRC)-based molecular featurization and feature engineering, for the first time. Molecular structures and interactions are modeled as simplicial complexes, which are generalization of graphs to their higher dimensional counterparts. Further, a multiscale representation is achieved through a filtration process, during which a series of nested simplicial complexes at different scales are generated. Forman Ricci curvatures (FRCs) are calculated on the series of simplicial complexes, and the persistence and variation of FRCs during the filtration process is defined as FPRC. Moreover, persistent attributes, which are FPRC-based functions and properties, are employed as molecular descriptors, and combined with machine learning models, in particular, gradient boosting tree (GBT). Our FPRC-GBT models are extensively trained and tested on three most commonly-used datasets, including PDBbind-2007, PDBbind-2013 and PDBbind-2016. It has been found that our results are better than the ones from machine learning models with traditional molecular descriptors
Replication Data for: Ideal Unconventional Weyl Point in a Chiral Photonic Metamaterial
No full textReplication Data for: Ideal Unconventional Weyl Point in a Chiral Photonic Metamateria
Replication Data for: Active Ultrahigh‐Q (0.2 × 106) THz Topological Cavities on a Chip
No full textRapid scaling of semiconductor devices has led to an increase in the number of processor cores and integrated functionalities onto a single chip to support the growing demands of high-speed and large volume consumer electronics. This burgeoning demand for an ever-increasing on-chip communication bandwidth has been a great challenge over the recent decades and has motivated a plethora of research to improve interconnect capacities in terms of bandwidth density for enhanced throughput and energy efficiency. Low-loss terahertz silicon interconnects with larger bandwidth offers good prospects to solve the existing inter/intra chip bandwidth density and energy efficiency bottleneck to cater to the heavy demands of enhanced on-chip system performance of most computers and embedded systems. Here, we present a low-loss terahertz topological interconnect-cavity system that can actively route signals through the interconnect and cavity with sharp bends, by coupling to a topological whispering gallery mode resonance with an ultra-high-quality (Q) factor of 0.2 × 106. The topologically protected large Q factor cavity enables energy-efficient optical control of the ultra-high-Q resonance showing 50 dB modulation. We further demonstrate the dynamic control of the critical coupling between the topological interconnect-cavity system that provides huge design flexibility for on-chip active tailoring of the cavity resonance linewidth, frequency, and modulation through complete suppression of the back reflection due to the topological protection. The on-chip topological cavity is CMOS-compatible and highly desirable for hybrid electronic-photonic technologies that holds the key for development of the sixth (6G) generation terahertz communication devices, including on-chip modulators, switches, signal routers, antennas, and multiplexers. Ultra-high-Q cavity also paves the path for the design of low threshold topological lasers, quantum integrated circuits, and nonlinear topological photonics