Agency for Science, Technology and Research

About: Agency for Science, Technology and Research is a government organization based out in Singapore, Singapore. It is known for research contribution in the topics: Catalysis & Population. The organization has 16013 authors who have published 24427 publications receiving 832302 citations. The organization is also known as: A*STAR & A-Star.

Nonlinear dielectric thin films for high-power electric storage with energy density comparable with electrochemical supercapacitors

Abstract: Although batteries possess high energy storage density, their output power is limited by the slow movement of charge carriers, and thus capacitors are often required to deliver high power output. Dielectric capacitors have high power density with fast discharge rate, but their energy density is typically much lower than electrochemical supercapacitors. Increasing the energy density of dielectric materials is highly desired to extend their applications in many emerging power system applications. In this paper, we review the mechanisms and major characteristics of electric energy storage with electrochemical supercapacitors and dielectric capacitors. Three types of in-house-produced ferroic nonlinear dielectric thin film materials with high energy density are described, including (Pb0.97La0.02)(Zr0.90Sn0.05Ti0.05)O3 (PLZST) antiferroelectric ceramic thin films, Pb(Zn1/3Nb2/3)O3-Pb(Mg1/3Nb2/3) O3-PbTiO3 (PZN-PMN-PT) relaxor ferroelectric ceramic thin films, and poly(vinylidene fluoride) (PVDF)-based polymer blend thin films. The results showed that these thin film materials are promising for electric storage with outstandingly high power density and fairly high energy density, comparable with electrochemical supercapacitors.

Deep transfer metric learning

Abstract: Conventional metric learning methods usually assume that the training and test samples are captured in similar scenarios so that their distributions are assumed to be the same. This assumption doesn't hold in many real visual recognition applications, especially when samples are captured across different datasets. In this paper, we propose a new deep transfer metric learning (DTML) method to learn a set of hierarchical nonlinear transformations for cross-domain visual recognition by transferring discriminative knowledge from the labeled source domain to the unlabeled target domain. Specifically, our DTML learns a deep metric network by maximizing the inter-class variations and minimizing the intra-class variations, and minimizing the distribution divergence between the source domain and the target domain at the top layer of the network. To better exploit the discriminative information from the source domain, we further develop a deeply supervised transfer metric learning (DSTML) method by including an additional objective on DTML where the output of both the hidden layers and the top layer are optimized jointly. Experimental results on cross-dataset face verification and person re-identification validate the effectiveness of the proposed methods.

Optimum Forward Light Scattering by Spherical and Spheroidal Dielectric Nanoparticles with High Refractive Index

Abstract: High-refractive index dielectric nanoparticles may exhibit strong directional forward light scattering at visible and near-infrared wavelengths due to interference of simultaneously excited electric and magnetic dipole resonances. For a spherical particle shape, the so-called first Kerker’s condition can be realized, at which the backward scattering practically vanishes for some combination of refractive index and particle size. However, realization of Kerker’s condition for spherical particles is only possible at the tail of the scattering resonances, when the particle scatters light weakly. Here we demonstrate that significantly higher forward scattering can be realized if spheroidal particles are considered instead. For each value of refractive index n exists an optimum shape of the particle, which produces minimum backscattering efficiency together with maximum forward scattering. This effect is achieved due to the overlapping of magnetic and electric dipole resonances of the spheroidal particle at th...

Roles of NF-κB in health and disease : mechanisms and therapeutic potential

Abstract: The NF-kappaB (nuclear factor kappaB) family of transcription factors are involved in a myriad of activities, including the regulation of immune responses, maturation of immune cells, development of secondary lymphoid organs and osteoclastogenesis. Fine tuning by positive and negative regulators keeps the NF-kappaB signalling pathway in check. Microbial products and genetic alterations in NF-kappaB and other signalling pathway components can lead to deregulation of NF-kappaB signalling in several human diseases, including cancers and chronic inflammatory disorders. NF-kappaB-pathway-specific therapies are being actively investigated, and these hold promises as interventions of NF-kappaB-related ailments.

A Pathogenic Role for CD4+ T Cells during Chikungunya Virus Infection in Mice

Abstract: Chikungunya virus (CHIKV) is an alphavirus that causes chronic and incapacitating arthralgia in humans. Injury to the joint is believed to occur because of viral and host immune-mediated effects. However, the exact involvement of the different immune mediators in CHIKV-induced pathogenesis is unknown. In this study, we assessed the roles of T cells in primary CHIKV infection, virus replication and dissemination, and virus persistence, as well as in the mediation of disease severity in adult RAG2−/−, CD4−/−, CD8−/−, and wild-type CHIKV C57BL/6J mice and in wild-type mice depleted of CD4+ or CD8+ T cells after Ab treatment. CHIKV-specific T cells in the spleen and footpad were investigated using IFN-γ ELISPOT. Interestingly, our results indicated that CHIKV-specific CD4+, but not CD8+, T cells are essential for the development of joint swelling without any effect on virus replication and dissemination. Infection in IFN-γ−/− mice demonstrated that pathogenic CD4+ T cells do not mediate inflammation via an IFN-γ–mediated pathway. Taken together, these observations strongly indicate that mechanisms of joint pathology induced by CHIKV in mice resemble those in humans and differ from infections caused by other arthritogenic viruses, such as Ross River virus.