Earnings Management Of Mergers And Acquisitions Of Target Candidates And Deal Withdrawn

In this paper, we investigate the tendencies of target candidate companies to manage earnings, which affects financial reporting quality, in order to increase transaction value, and the withdrawal of deals as a result of low financial reporting quality in M&A in a sample of 316 mergers and acquisitions in South Korea between 2002 and 2011. Using the accruals quality measure developed by Dechow and Dichev (2002) as a proxy for financial reporting quality, we find the following. First, the financial reporting quality of target candidate firms is lower than that of non-target candidate firms because target candidate firms engage in earnings management prior to M&A. Second, low-quality financial reporting of target firms is positively related to the likelihood of deal withdrawal as a result of poor financial reporting quality

Class-Attentive Diffusion Network for Semi-Supervised Classification

Recently, graph neural networks for semi-supervised classification have been widely studied. However, existing methods only use the information of limited neighbors and do not deal with the inter-class connections in graphs. In this paper, we propose Adaptive aggregation with Class-Attentive Diffusion (AdaCAD), a new aggregation scheme that adaptively aggregates nodes probably of the same class among K-hop neighbors. To this end, we first propose a novel stochastic process, called Class-Attentive Diffusion (CAD), that strengthens attention to intra-class nodes and attenuates attention to inter-class nodes. In contrast to the existing diffusion methods with a transition matrix determined solely by the graph structure, CAD considers both the node features and the graph structure with the design of our class-attentive transition matrix that utilizes a classifier. Then, we further propose an adaptive update scheme that leverages different reflection ratios of the diffusion result for each node depending on the local class-context. As the main advantage, AdaCAD alleviates the problem of undesired mixing of inter-class features caused by discrepancies between node labels and the graph topology. Built on AdaCAD, we construct a simple model called Class-Attentive Diffusion Network (CAD-Net). Extensive experiments on seven benchmark datasets consistently demonstrate the efficacy of the proposed method and our CAD-Net significantly outperforms the state-of-the-art methods. Code is available at https://github.com/ljin0429/CAD-Net.Comment: Accepted to AAAI 202

A Novel Thin Film Transistor Using Double Amorphous Silicon Active Layer

We have fabricated a novel low off-state leakage current thin-film transistor (TFT) using a chlorine incorporated amorphous silicon [a-Si:H(:Cl)] and amorphous silicon (a-Si:H) stacked active layer, in which conduction channel is formed in a-Si:H and a-Si:H(:Cl) is photo-insensitive material. The off-state photo-leakage current of the a-Si:H(:Cl)/a-Si:H TFT is much lower than that a conventional a-Si:H TFT

Analysis of Problems in Cut Slope Survey and Design Based on Case Studies

In construction of roads or large residential complexes, the formation of large scale cut slopes is inevitable due to the large proportion of mountains in Korea. The problems involving the slope stability has emerged as a major concern. Inaccurate subsurface exploration can result in slope failure during or after the construction, thereby increasing the construction cost and delaying the construction duration. This study reviews problems involving the cut slope survey methods, design criteria, and examining the collapse mechanisms through various case studies. This study suggests the optimum survey methods and design criteria based on the possible failure mechanisms

Progress in Understanding and Sequencing the Genome of Brassica rapa

Brassica rapa, which is closely related to Arabidopsis thaliana, is an important crop and a model plant for studying genome evolution via polyploidization. We report the current understanding of the genome structure of B. rapa and efforts for the whole-genome sequencing of the species. The tribe Brassicaceae, which comprises ca. 240 species, descended from a common hexaploid ancestor with a basic genome similar to that of Arabidopsis. Chromosome rearrangements, including fusions and/or fissions, resulted in the present-day “diploid” Brassica species with variation in chromosome number and phenotype. Triplicated genomic segments of B. rapa are collinear to those of A. thaliana with InDels. The genome triplication has led to an approximately 1.7-fold increase in the B. rapa gene number compared to that of A. thaliana. Repetitive DNA of B. rapa has also been extensively amplified and has diverged from that of A. thaliana. For its whole-genome sequencing, the Brassica rapa Genome Sequencing Project (BrGSP) consortium has developed suitable genomic resources and constructed genetic and physical maps. Ten chromosomes of B. rapa are being allocated to BrGSP consortium participants, and each chromosome will be sequenced by a BAC-by-BAC approach. Genome sequencing of B. rapa will offer a new perspective for plant biology and evolution in the context of polyploidization

Microfiber-microcavity system for efficient single photon collection

Funded by the National Research Foundation of Korea (NRF) grant (MSIP) (NRF-2007-341-C00018, NRF-2014M3C1A3052567); State of Bavaria.Single photon sources are key components for various quantum information processing. For practical quantum applications, bright single photon sources with efficient fiber-optical interfaces are highly required. Here, bright fiber-coupled single photon sources based on InAs quantum dots are demonstrated through the k-vector matching between a microfiber mode and a normal mode of the linear photonic crystal cavity. One of the modes of the linear photonic crystal cavity whose k-vector is similar to that of the microfiber mode is employed. From independent transmission measurement, the coupling efficiency directly into the fiber of 58% is obtained. When the quantum dot and cavity system is non-resonantly pumped with 80 MHz pulse train, a raw count rate of 1.81 MHz is obtained with g(2)(0) = 0.46. Resonant pump is expected to improve the rather high g(2)(0) value. Time-resolved photoluminescence is also measured to confirm the three-fold Purcell enhancement. This system provides a promising route for efficient direct fiber collections of single photons for quantum information processing.PostprintPeer reviewe

Quantitative Analysis and Biological Efficacies regarding the Neuroprotective and Antineuroinflammatory Actions of the Herbal Formula Jodeungsan in HT22 Hippocampal Cells and BV-2 Microglia

Jodeungsan (JDS) is a traditional herbal formula that comprises seven medicinal herbs and is broadly utilized to treat hypertension, dementia, and headache. However, the effects of JDS and its herbal components on neurodegenerative diseases have not been reported. We examined the inhibitory effects of JDS and its seven components on neuronal cell death and inflammation using HT22 hippocampal cells and BV-2 microglia, respectively. Among its seven herbal components, Uncaria sinensis (US), Chrysanthemum morifolium (CM), Zingiber officinale (ZO), Pinellia ternata (PT), Citrus unshiu (CU), and Poria cocos (PC) exhibited significant neuroprotective effects in HT22 cells. In BV-2 cells, JDS significantly suppressed the production of tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6), indicating the antineuroinflammatory activity of JDS. In addition, the herbal extracts from ZO, Panax ginseng (PG), PT, CU, and PC exhibited inhibitory effects on the inflammatory response in microglia. These data imply that the JDS effect on neurodegeneration occurs via coordination among its seven components. To establish a quality control for JDS, a simultaneous analysis using five standard compounds identified hesperidin (37.892±1.228 mg/g) as the most abundant phytochemical of JDS. Further investigation of the combinatorial activities of two or more standard compounds will be necessary to verify their antineurodegenerative regulatory mechanisms