Comparative Study on the Structures of Chinese and Korean Compound Words

The goal of the research was to compare the compound words in Chinese, an isolated language, and Korean, an agglutinative language. This research used library research. The researchers found that the main characteristics of the formation of Korean compound words were that the latter element was the central word. The method of word formation decided its lexical category. Moreover, most of the internal relationships of the compound words were connection and modification. While in Chinese, the endocentric compound noun decided the part of speech of the compound word, and could be the proceeding element or the latter element. Furthermore, Chinese contained no complicated morphological changes. It is concluded that Korean is a Subject–Object–Verb (SOV) language, where verb elements demonstrate a central feature of the compound verb are always a trailing part. Thus, there is no exocentric compound verb in Korean. By contrast, Chinese is a typical SVO language. When constituting the compound verbs, nouns or adjectives can function as the structural elements. Therefore, there is no permanent position for head words

Effect of activated alloys on hydrogen discharge kinetics of MgH2 nanocrystals

This is the post-print version of the final paper published in Journal of Alloys and Compounds. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2007 Elsevier B.V.Activated alloys synthesized by arc-melting were examined as catalysts for improving the hydrogen sorption characteristics of nanostructured magnesium hydride, proposed as a reversible hydrogen storage material. The MgH2-catalyst absorbing materials were prepared by ball milling of pure MgH2 with hydrided Zr47Ni53, Zr9Ni11, and other investigated alloys. The nanostructured MgH2-intermetallic systems were tested at 250 °C and catalyst addition of eutectoid Zr47Ni53 resulted in the fastest desorption time and highest initial desorption rate. Also, the catalyzed Mg-hydride with activated Zr9Ni11 and Zr7Ni10 phases showed fast desorption kinetics. Moreover, the results demonstrated that the composition of dispersed ZrxNiy catalysts has a strong influence on the amount of accumulated hydrogen and desorption rate of Mg-nanocomposite.National Research Council Canad

Social media use and impact during the holiday travel planning process

Through an empirical study among holiday travellers, residing in the Former Soviet Union Republics, this paper presents a comprehensive view of role and impact of social media on the whole holiday travel planning process: Before, during and after the trip, providing insights on usage levels, scope of use, level of influence and trust. Findings suggest that social media are predominantly used after holidays for experience sharing. It is also shown that there is a strong correlation between perceived level of influence from social media and changes made in holiday plans prior to final decisions. Moreover, it is revealed that user-generated content is perceived as more trustworthy when compared to official tourism websites, travel agents and mass media advertising

Reconfigurable Optical Datacom Networks by Self-supervised Learning

This paper presents a self-supervised machine learning approach for cognitive reconfiguration in a Hyper-X-like flexible-bandwidth optical interconnect architecture. The proposed approach makes use of a clustering algorithm to learn the traffic patterns from historical traces. A heuristic algorithm is developed for optimizing the connectivity graph for each identified traffic pattern. Further, to mitigate the scalability issue induced by frequent clustering operations, we parameterize the learned traffic patterns by a deep neural network classifier. The classifier is trained offline by supervised learning to enable classification of traffic matrices during online operations, thereby facilitating cognitive reconfiguration decision making. Simulation results show that compared with a static all-to-all interconnection, the proposed approach can improve throughput by up to 1.76× while reducing end-to-end packet latency and flow completion time by up to 2.8× and 25×, respectively

The Mre11-Rad50-Nbs1 complex mediates activation of TopBP1 by ATM

The activation of ATR-ATRIP in response to double-stranded DNA breaks (DSBs) depends upon ATM in human cells and Xenopus egg extracts. One important aspect of this dependency involves regulation of TopBP1 by ATM. In Xenopus egg extracts, ATM associates with TopBP1 and thereupon phosphorylates it on S1131. This phosphorylation enhances the capacity of TopBP1 to activate the ATR-ATRIP complex. We show that TopBP1 also interacts with the Mre11-Rad50-Nbs1 (MRN) complex in egg extracts in a checkpoint-regulated manner. This interaction involves the Nbs1 subunit of the complex. ATM can no longer interact with TopBP1 in Nbs1-depleted egg extracts, which suggests that the MRN complex helps to bridge ATM and TopBP1 together. The association between TopBP1 and Nbs1 involves the first pair of BRCT repeats in TopBP1. In addition, the two tandem BRCT repeats of Nbs1 are required for this binding. Functional studies with mutated forms of TopBP1 and Nbs1 suggested that the BRCT-dependent association of these proteins is critical for a normal checkpoint response to DSBs. These findings suggest that the MRN complex is a crucial mediator in the process whereby ATM promotes the TopBP1-dependent activation of ATR-ATRIP in response to DSBs

Magnetic levitation force between a superconducting bulk magnet and a permanent magnet

The current density in a disk-shaped superconducting bulk magnet and the magnetic levitation force exerted on the superconducting bulk magnet by a cylindrical permanent magnet are calculated from first principles. The effect of the superconducting parameters of the superconducting bulk is taken into account by assuming the voltage-current law and the material law. The magnetic levitation force is dominated by the remnant current density, which is induced by switching off the applied magnetizing field. High critical current density and flux creep exponent may increase the magnetic levitation force. Large volume and high aspect ratio of the superconducting bulk can enhance the magnetic levitation force further.Comment: 18 pages and 8 figure

On Cooperative Fault Management in Multi-Domain Optical Networks Using Hybrid Learning

This paper presents a hybrid learning approach for cooperative fault management in multi-domain optical networks (MD-ONs). The proposed approach relies on a broker-based MD-ON architecture for coordination of inter-domain service provisioning. We first propose a self-supervised learning design for soft failure detection. The self-supervised learning design makes use of a clustering algorithm for extracting normal and abnormal patterns from optical performance monitoring data and a supervised learning-based classifier trained with the learned patterns for online detection. To facilitate high soft failure detection accuracy in the absence of sufficient abnormal data for training, the proposed design estimates model uncertainties during predictions and identifies instances associated with high uncertainties as also soft failures. Then, we extend the self-supervised learning design and present a federated learning framework for the broker plane and DMs to learn cooperatively while complying with the privacy constraints of each domain. Finally, a data-driven soft failure localization scheme that operates by analyzing the patterns of data is proposed as a complement to the existing approaches. Performance evaluations indicate that the self-supervised learning design can achieve soft failure detection accuracy of up to ∼ 97% with 0.01%-0.04% false alarm rate, while federated learning enables DMs to realize >90% soft failure detection rates in the cases of highly unbalanced data distribution (two of the three domains possess zero abnormal data for training)

When Task Scheduling Meets Flexible-bandwidth Optical Interconnects: A Cross-layer Resource Orchestration Design

We propose a cross-layer resource orchestration design for task scheduling in flexible-bandwidth optical data center networks. Results show the proposed design can achieve 8.2 ×, 1.9 × and 4.8 × reductions of request blocking probability, end-to-end delay and packet loss rate, compared with the baseline

Theorizing Routines with Computational Sequence Analysis: A Critical Realism Framework

We develop a methodological framework to develop process theories on routines by leveraging large volumes of digital trace data following critical realism principles. Our framework begins with collecting and preprocessing digital trace data, corresponding to the empirically observed experience of critical realism. In the second and third steps of the framework, we identify a finite set of similar repetitive patterns (routines) through computational analysis. We accomplish this by combining frequent subsequence mining and clustering analysis to transform empirical observation into a set of routines that correspond to actual happening in critical realism. Then, we employ a retroduction approach to identify generative mechanisms of the routines. In the final step, we validate the generative mechanisms by evaluating proposed processual explanations and/or eliminating alternatives. We provide an illustrative example of developing a process theory in relation to the collaboration pattern in Wikipedia