Monomial Relization of Crystal Bases for Special Linear Lie Algebras

We give a new realization of crystal bases for finite dimensional irreducible modules over special linear Lie algebras using the monomials introduced by H. Nakajima. We also discuss the connection between this monomial realization and the tableau realization given by Kashiwara and Nakashima.Comment: 15 page

Young Wall Realization of Crystal Bases for Classical Lie Algebras

In this paper, we give a new realization of crystal bases for finite dimensional irreducible modules over classical Lie algebras. The basis vectors are parameterized by certain Young walls lying between highest weight and lowest weight vectors.Comment: 27page

Nakajima monomials, Young walls and Kashiwara embedding for Uq(An(1))

AbstractIn this paper, we realize the crystal basis B(λ) of the irreducible highest weight module V(λ) of level 1 for Uq(An(1)) using Nakajima monomials satisfying some conditions. Also, from this monomial realization, we obtain the image of Kashiwara embedding Ψιλ:B(λ)↪Z∞⊗Rλ, where ι is some infinite sequence from the index set of simple roots. Finally, we give a Uq(An(1))-crystal isomorphism between Young wall realization and monomial realization, and so we can understand the image of Kashiwara embedding Ψιλ:B(λ)↪Z∞⊗Rλ using the combinatorics of Young walls

Removal of Refractory Dissolved Organic Carbon in the Amundsen Sea, Antarctica.

The removal mechanism of refractory deep-ocean dissolved organic carbon (deep-DOC) is poorly understood. The Amundsen Sea Polynya (ASP) serves as a natural test basin for assessing the fate of deep-DOC when it is supplied with a large amount of fresh-DOC and exposed to strong solar radiation during the polynya opening in austral summer. We measured the radiocarbon content of DOC in the water column on the western Amundsen shelf. The radiocarbon content of DOC in the surface water of the ASP reflected higher primary production than in the region covered by sea ice. The radiocarbon measurements of DOC, taken two years apart in the ASP, were different, suggesting rapid cycling of DOC. The increase in DOC concentration was less than expected from the observed increase in radiocarbon content from those at the greatest depths. Based on a radiocarbon mass balance, we show that deep-DOC is consumed along with fresh-DOC in the ASP. Our observations imply that water circulation through the surface layer, where fresh-DOC is produced, may play an important role in global DOC cycling

An Empirical Study on the factors influencing the utilization and the effectiveness of Enterprise Instant Messenger

Communication technology has been recognized to play an important role in boosting organization’s competitiveness and viability by facilitating efficient communication and information sharing. Lately, many organizations began to actively adopt the self-developed Enterprise Instant Messenger (EIM) as a common organizational communication medium after experiencing security problem with public messengers like MSN. Its utilization and tangible benefits of EIM, however, vary. There’s an urgent need to understand how each organization embraces EIM and to empirically evaluate whether active use of EIM can result in a better communication, eventually leading into better business productivity. In this research we try to investigate those antecedents which may have affected the high use of EIM and a better decision making efficiency. Theoretical justification of research variables and causal relationships of our research model are mainly based on Technology Acceptance Model (TAM), media selection theory, and social influence model. Through a survey data analysis of 171 EIM users, it was found that perceived usefulness, social influence, the externally-orientated organizational culture had a significant effect on the high use of EIM. In addition, the use of EIM was found to have a significant effect on the efficiency in the decision-making process

Performance Comparison of Design Optimization and Deep Learning-based Inverse Design

Surrogate model-based optimization has been increasingly used in the field of engineering design. It involves creating a surrogate model with objective functions or constraints based on the data obtained from simulations or real-world experiments, and then finding the optimal solution from the model using numerical optimization methods. Recent advancements in deep learning-based inverse design methods have made it possible to generate real-time optimal solutions for engineering design problems, eliminating the requirement for iterative optimization processes. Nevertheless, no comprehensive study has yet closely examined the specific advantages and disadvantages of this novel approach compared to the traditional design optimization method. The objective of this paper is to compare the performance of traditional design optimization methods with deep learning-based inverse design methods by employing benchmark problems across various scenarios. Based on the findings of this study, we provide guidelines that can be taken into account for the future utilization of deep learning-based inverse design. It is anticipated that these guidelines will enhance the practical applicability of this approach to real engineering design problems

Examining the Impact of Language Proficiency on Mathematics Achievement Using a High-Stakes Achievement Test

The study investigated the relationship between Korean 9th grade students Korean language proficiency and their math achievement using the data from the 2008 National Assessment of Educational Achievement (NAEA) administration. It also examined the effects of various contextual characteristics surrounding schools and students on student achievement. The contextual effects were further compared between two language proficiency groups. The findings of the study showed that fathers education, amount of conversation with parents, and self-reported effectiveness of learning were positively related to student math achievement in both language groups. However, the higher language proficiency group reported higher ratings in those aspects. In addition, male students outperformed their counterparts in the test, regardless of their language proficiency level

A Case of Extensive Spinal Cysticercosis Involving the Whole Spinal Canal in a Patient with a History of Cerebral Cysticercosis

Although cysticercosis is the most common parasitic disease affecting the central nervous system, spinal cysticercosis is rare. A rare form of spinal cysticercosis involving the whole spinal canal is presented. A 45-year-old Korean male had a history of intracranial cysticercosis and showed progressive paraparesis. Spinal magnetic resonance scan showed multiple cysts compressing the spinal cord from C1 to L1. Three different levels (C1-2, T1-3, and T11-L1) required operation. Histopathological examination confirmed cysticercosis. The patient improved markedly after surgery

Channel Assignment for Multiple Interface Nodes in Wireless Ad

In wireless networks, due to the broadcast property of the medium, nodes close to each other cannot simultaneously transmit over the same channel. One way to overcome this limitation is to use multiple independent channels available in the system. Although we can use a single wireless interface card to access multiple channels, such schemes can raise issues of compatibility (e.g., modication of the MAC protocol) and performance degradation (e.g., due to frequent channel switching). In this paper, we assume that nodes are equipped with multiple interface cards, and focus on the channel assignment problem for minimizing the total number of interferences among wireless links. We show that the problem is NP-hard and present distributed heuristics. We also present two centralized algorithms and show that the algorithms give constant factor approximation guarantees. We perform simulation experiments for the proposed distributed heuristic. The results show that compared to one-channel scenarios, our proposed algorithm can reduce the number of interferences by up to 85% when nodes are equipped with four interface cards. Through detailed packetlevel simulation experiments, we also show that depending on the scenario, the resulting channel assignment actually achieves up to seven times throughput improvement over the single-channel case