Firm Actions Toward Data Breach Incidents and Firm Equity Value: An Empirical Study

Managing information resources including protecting the privacy of customer data plays a critical role in most firms. Data breach incidents may be extremely costly for firms. In the face of a data breach event, some firms are reluctant to disclose information to the public. Firm may be concerned with the potential drop in the market value following the revelation of a data breach. This paper examines the impact of data breach incidents to the firm’s market value/equity value, and explores the possibility that certain firm behaviors may reduce the cost of the incidents. We use regression analysis to identify the factors that affect cumulative abnormal stock return (CAR). Our results indicate that when data breach happens, firms not only should notify customers or the public timely, but also try to control the amount of information disclosed. These findings should provide corporate executives with guidance on managing public disclosure of data breach incidents

CrowdIQ: A New Opinion Aggregation Model

In this study, we investigate the problem of aggregating crowd opinions for decision making. The Wisdom of Crowds (WoC) theory explains how crowd opinions should be aggregated in order to improve the performance of decision making. Crowd independence and a weighting mechanism are two important factors to crowd wisdom. However, most existing crowd opinion aggregation methods fail to build a differential weighting mechanism for identifying the expertise of individuals and appropriately accounting for crowd dependence when aggregating their judgments. We propose a new crowd opinion aggregation model, namely CrowdIQ, that has a differential weighting mechanism and accounts for individual dependence. We empirically evaluate CrowdIQ in comparison to four baseline methods using real data collected from StockTwits. The results show that, CrowdIQ significantly outperforms all baseline methods in terms of both a quadratic prediction scoring measure and simulated investment returns

A Domain Oriented LDA Model for Mining Product Defects from Online Customer Reviews

Online reviews provide important demand-side knowledge for product manufacturers to improve product quality. However, discovering and quantifying potential products’ defects from large amounts of online reviews is a nontrivial task. In this paper, we propose a Latent Product Defect Mining model that identifies critical product defects. We define domain-oriented key attributes, such as components and keywords used to describe a defect, and build a novel LDA model to identify and acquire integral information about product defects. We conduct comprehensive evaluations including quantitative and qualitative evaluations to ensure the quality of discovered information. Experimental results show that the proposed model outperforms the standard LDA model, and could find more valuable information. Our research contributes to the extant product quality analytics literature and has significant managerial implications for researchers, policy makers, customers, and practitioners

Discovery of tissue-specific exons using comprehensive human exon microarrays

Comprehensive exon microarrays with a simple intra-gene normalization algorithm were used to detect human tissue-specific alternative splicing events, suggesting significant expression outside of known exons and well annotated genes and a high frequency of alternative splicing events

Machine Learning in Nuclear Physics

Advances in machine learning methods provide tools that have broad applicability in scientific research. These techniques are being applied across the diversity of nuclear physics research topics, leading to advances that will facilitate scientific discoveries and societal applications. This Review gives a snapshot of nuclear physics research which has been transformed by machine learning techniques.Comment: Comments are welcom

Mode-division multiplexed transmission with inline few-mode fiber amplifier

We demonstrate mode-division multiplexed WDM transmission over 50-km of few-mode fiber using the fiber\u27s LP01 and two degenerate LP11 modes. A few-mode EDFA is used to boost the power of the output signal before a few-mode coherent receiver. A 6x6 time-domain MIMO equalizer is used to recover the transmitted data. We also experimentally characterize the 50-km few-mode fiber and the few-mode EDFA

\u3cem\u3eLkb1\u3c/em\u3e Inactivation Drives Lung Cancer Lineage Switching Governed by Polycomb Repressive Complex 2

Adenosquamous lung tumours, which are extremely poor prognosis, may result from cellular plasticity. Here, we demonstrate lineage switching of KRAS+ lung adenocarcinomas (ADC) to squamous cell carcinoma (SCC) through deletion of Lkb1 (Stk11) in autochthonous and transplant models. Chromatin analysis reveals loss of H3K27me3 and gain of H3K27ac and H3K4me3 at squamous lineage genes, including Sox2, ΔNp63 and Ngfr. SCC lesions have higher levels of the H3K27 methyltransferase EZH2 than the ADC lesions, but there is a clear lack of the essential Polycomb Repressive Complex 2 (PRC2) subunit EED in the SCC lesions. The pattern of high EZH2, but low H3K27me3 mark, is also prevalent in human lung SCC and SCC regions within ADSCC tumours. Using FACS-isolated populations, we demonstrate that bronchioalveolar stem cells and club cells are the likely cells-of-origin for SCC transitioned tumours. These findings shed light on the epigenetics and cellular origins of lineage-specific lung tumours

Roadmap on commercialization of metal halide perovskite photovoltaics

Perovskite solar cells (PSCs) represent one of the most promising emerging photovoltaic technologies due to their high power conversion efficiency. However, despite the huge progress made not only in terms of the efficiency achieved, but also fundamental understanding of the relevant physics of the devices and issues which affect their efficiency and stability, there are still unresolved problems and obstacles on the path toward commercialization of this promising technology. In this roadmap, we aim to provide a concise and up to date summary of outstanding issues and challenges, and the progress made toward addressing these issues. While the format of this article is not meant to be a comprehensive review of the topic, it provides a collection of the viewpoints of the experts in the field, which covers a broad range of topics related to PSC commercialization, including those relevant for manufacturing (scaling up, different types of devices), operation and stability (various factors), and environmental issues (in particular the use of lead). We hope that the article will provide a useful resource for researchers in the field and that it will facilitate discussions and move forward toward addressing the outstanding challenges in this fast-developing field

DNA methylation on N6-adenine in mammalian embryonic stem cells

It has been widely accepted that 5-methylcytosine is the only form of DNA methylation in mammalian genomes. Here we identify N6-methyladenine as another form of DNA modification in mouse embryonic stem cells. Alkbh1 encodes a demethylase for N6-methyladenine. An increase of N6-methyladenine levels in Alkbh1-deficient cells leads to transcriptional silencing. N6-methyladenine deposition is inversely correlated with the evolutionary age of LINE-1 transposons; its deposition is strongly enriched at young (6 million years old) L1 elements. The deposition of N6-methyladenine correlates with epigenetic silencing of such LINE-1 transposons, together with their neighbouring enhancers and genes, thereby resisting the gene activation signals during embryonic stem cell differentiation. As young full-length LINE-1 transposons are strongly enriched on the X chromosome, genes located on the X chromosome are also silenced. Thus, N6-methyladenine developed a new role in epigenetic silencing in mammalian evolution distinct from its role in gene activation in other organisms. Our results demonstrate that N6-methyladenine constitutes a crucial component of the epigenetic regulation repertoire in mammalian genomes