Korea Institute of Science and Technology Information

About: Korea Institute of Science and Technology Information is a facility organization based out in Daejeon, South Korea. It is known for research contribution in the topics: Gravitational wave & LIGO. The organization has 1152 authors who have published 2319 publications receiving 93849 citations. The organization is also known as: Korea Institute of Science and Technology Information & KISTI.

Observation of e+e- →π+π-π0χbJ and search for Xb →ω (1S) at s =10.867GeV

Abstract: The e(+)e(-) -> pi(+)pi(-) pi(0)chi(bj) ( J = 0, 1, 2) processes are studied using a 118 fb(-1) data sample acquired with the Belle detector at a center-of-mass energy of 10.867 GeV. Unambiguous pi(+)pi(-) pi(0)chi(bj) ( J = 1, 2), omega chi(b1) signals are observed, and indication for omega chi(b2) is seen, both for the first time, and the corresponding cross section measurements are presented. No significant pi(+)pi(-) pi(0)chi(b0) or omega chi(b0) signals are observed, and 90% confidence level upper limits on the cross sections for these two processes are obtained. In the pi(+)pi(-) pi(0) invariant mass spectrum, significant non-omega signals are also observed. We search for the X(3872)-like state (named X-b) decaying into omega Upsilon(1S); no significant signal is observed with a mass between 10.55 and 10.65 GeV= c(2).

Molecular challenges in microalgae towards cost-effective production of quality biodiesel

Abstract: Based on their environmental benefits, microalgae are currently the most favorable renewable biofeedstock materials for biodiesel production. However, the possibility of an economically viable production system using microalgae is still technology-driven, not yet market-driven due to its higher production cost. Accordingly, to establish industrial manufacturing systems for microalgal biodiesel, it is critical to develop technology for its cost-effective production. Here, we propose some novel molecular strategies, which have not been attempted for microalgal biodiesel production and are conducive to cost-effective production of biodiesel from microalgae. These include genetic manipulation strategies for higher biomass yield and extracellular production of free fatty acids, triacylglycerol, and fatty acid ethyl ester (biodiesel) with high quality, which could be exploited as a breakthrough technology for the cost-efficient production of microalgal biodiesel.

Self-avoiding polymer trapped inside a cylindrical pore: Flory free energy and unexpected dynamics.

Abstract: We study the elastic and dynamic behavior of a self-avoiding chain confined inside a cylindrical pore using a Flory-type approach and molecular-dynamics simulations. In the Hookean regime, we find that the effective spring constant of the chain is given by ${k}_{\text{eff}}\ensuremath{\sim}{N}^{\ensuremath{-}1}{D}^{\ensuremath{-}\ensuremath{\gamma}}$, where $N$ is the number of monomers and $D$ the diameter of the pore. While the Flory approach reproduces the earlier scaling result $\ensuremath{\gamma}=1/3$, our simulations confirm a more recent numerical result $\ensuremath{\gamma}\ensuremath{\approx}0.9$ for the computationally accessible regimes. In the absence of hydrodynamic interactions, the relaxation dynamics of a stretched-and-released chain in this regime is characterized by a global relaxation time ${\ensuremath{\tau}}_{R}\ensuremath{\sim}{N}^{2}{D}^{\ensuremath{\gamma}}$ with the same exponent $\ensuremath{\gamma}$ for ${k}_{\text{eff}}$. We also discuss how chain relaxation under confinement is influenced by hydrodynamic interactions. In the presence (or absence) of the hydrodynamic interaction, the finite-size effect observed in ${k}_{\text{eff}}$ is shown to persist in chain relaxation, resulting in ${\ensuremath{\tau}}_{R}$ markedly different from previous results.

New multi-stage similarity measure for calculation of pairwise patent similarity in a patent citation network

Abstract: Being able to effectively measure similarity between patents in a complex patent citation network is a crucial task in understanding patent relatedness. In the past, techniques such as text mining and keyword analysis have been applied for patent similarity calculation. The drawback of these approaches is that they depend on word choice and writing style of authors. Most existing graph-based approaches use common neighbor-based measures, which only consider direct adjacency. In this work we propose new similarity measures for patents in a patent citation network using only the patent citation network structure. The proposed similarity measures leverage direct and indirect co-citation links between patents. A challenge is when some patents receive a large number of citations, thus are considered more similar to many other patents in the patent citation network. To overcome this challenge, we propose a normalization technique to account for the case where some pairs are ranked very similar to each other because they both are cited by many other patents. We validate our proposed similarity measures using US class codes for US patents and the well-known Jaccard similarity index. Experiments show that the proposed methods perform well when compared to the Jaccard similarity index.