Integration of Multispectral Face Recognition and Multi-PTZ Camera Automated Surveillance for Security Applications

Due to increasing security concerns, a complete security system should consist of two major components, a computer-based face-recognition system and a real-time automated video surveillance system. A computer-based face-recognition system can be used in gate access control for identity authentication. In recent studies, multispectral imaging and fusion of multispectral narrow-band images in the visible spectrum have been employed and proven to enhance the recognition performance over conventional broad-band images, especially when the illumination changes. Thus, we present an automated method that specifies the optimal spectral ranges under the given illumination. Experimental results verify the consistent performance of our algorithm via the observation that an identical set of spectral band images is selected under all tested conditions. Our discovery can be practically used for a new customized sensor design associated with given illuminations for an improved face recognition performance over conventional broad-band images. In addition, once a person is authorized to enter a restricted area, we still need to continuously monitor his/her activities for the sake of security. Because pantilt-zoom (PTZ) cameras are capable of covering a panoramic area and maintaining high resolution imagery for real-time behavior understanding, researches in automated surveillance systems with multiple PTZ cameras have become increasingly important. Most existing algorithms require the prior knowledge of intrinsic parameters of the PTZ camera to infer the relative positioning and orientation among multiple PTZ cameras. To overcome this limitation, we propose a novel mapping algorithm that derives the relative positioning and orientation between two PTZ cameras based on a unified polynomial model. This reduces the dependence on the knowledge of intrinsic parameters of PTZ camera and relative positions. Experimental results demonstrate that our proposed algorithm presents substantially reduced computational complexity and improved flexibility at the cost of slightly decreased pixel accuracy as compared to Chen and Wang\u27s method [18]. © Versita sp. z o.o

Evidence of Wealth Effect of Corporate Spin-Offs in China

Is corporate spin-offs less attended as a wealth-generating asset restructuring in the People s Republic of China China Was the wealth effect of China s corporate spin-off occurring in the State Capital Economy Although China s Initial Public Offering IPO incidences and volumes are vigorous China s corporate spin-offs started late and lack extensive applications In July 2020 alone a total of seventy-five companies completed IPO in mainland China and abroad despite the outbreak of the COVID- 19 pandemic This paper aimed to provide evidence on the wealth effect of the combination of China corporate spin-off announcements parent and subsidiary We took twenty-four Chinese listed companies that have been successfully spin-off as a whole to explore the corporate spin-off wealth effect on their market value and the empirical results of positive returns were convincing Compared with the prior corporate spin-off researches in China this paper is more comprehensive as we examined the shareholders wealth effect of the corporate spin-off announcements from the years 2000 to 2018 in the Shanghai Stock Exchange SSE and Shenzhen Stock Exchange SZS

Activation of Sp1-mediated transcription by Rta of Epstein–Barr virus via an interaction with MCAF1

Rta is a transcription factor encoded by BRLF1 of the Epstein–Barr virus (EBV). This factor is expressed during the immediate-early stage of the lytic cycle to activate the genes required for EBV lytic development. Although transcription activation by Rta is frequently associated with the binding of Rta to the Rta-response element (RRE) in promoters, Rta sometimes activates promoters without an RRE. Here we show that Rta interacts with an Sp1-interacting protein, MBD1-containing chromatin-associated factor 1 (MCAF1). This interaction is critical to the formation of an Sp1–MCAF1–Rta complex at Sp1 sites. Therefore, following lytic induction and the expression of Rta, Rta increases Sp1-mediated transcription. The genes that are thus activated include p16, p21, SNRPN and BRLF1. However, the binding of Rta to RRE prevents the interaction between Rta and MCAF1; therefore, transcription activation by RRE depends only on Rta, and not on MCAF1 or Sp1. Furthermore, this study finds that MCAF1 promotes the expression of Rta and Zta from EBV, indicating that MCAF1 participates EBV lytic activation. Our study documents the critical role of Rta in regulating the transcription of the genes that are mediated by Sp1

The role of state ownership and institutions in the innovation performance of emerging market enterprises: evidence from China

Although it has been suggested that institutional context influences a firm's innovation performance, the role of regulatory institutions has been underexplored. Extending previous research, this study investigates whether and how regulatory institutions (i.e. state ownership, region-specific marketization and industry-specific institutional policy) affect innovation performance of emerging market enterprises (EMEs). Evidence derived from a large sample of Chinese manufacturing firms demonstrates that state ownership positively moderates the effect of R&D intensity on innovation performance. However, state ownership is not equally beneficial for all firms. Our analysis shows that region-specific marketization and industry-specific institutional policy enhance the innovation-enhancing effect of state ownership. By revealing the role of regulatory institutions, our study points to the importance of looking beyond firm boundaries to understand why EMEs are able to innovate despite their weak internal capabilities

Differential expression of centrosomal proteins at different stages of human glioma

BACKGROUND: High-grade gliomas have poor prognosis, requiring aggressive treatment. The aim of this study is to explore mitotic and centrosomal dysregulation in gliomas, which may provide novel targets for treatment. METHODS: A case-control study was performed using 34 resected gliomas, which were separated into low- and high-grade groups. Normal human brain tissue was used as a control. Using immunohistochemical analysis, immunofluorescent microscopy, and RT-PCR, detection of centrins 1 and 2, γ-tubulin, hNinein, Aurora A, and Aurora B, expression was performed. Analysis of the GBM8401 glioma cell line was also undertaken to complement the in vivo studies. RESULTS: In high-grade gliomas, the cells had greater than two very brightly staining centrioles within large, atypical nuclei, and moderate-to-strong Aurora A staining. Comparing with normal human brain tissue, most of the mRNAs expression in gliomas for centrosomal structural proteins, including centrin 3, γ-tubulin, and hNinein isoforms 1, 2, 5 and 6, Aurora A and Aurora B were elevated. The significant different expression was observed between high- and low-grade glioma in both γ-tubulin and Aurora A mRNA s. In the high-grade glioma group, 78.6% of the samples had higher than normal expression of γ-tubulin mRNA, which was significantly higher than in the low-grade glioma group (18.2%, p < 0.05). CONCLUSIONS: Markers for mitotic dysregulation, such as supernumerary centrosomes and altered expression of centrosome-related mRNA and proteins were more frequently detected in higher grade gliomas. Therefore, these results are clinically useful for glioma staging as well as the development of novel treatments strategies

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features

Chinese Social Media Reaction to the MERS-Cov and Avian Influenza A (H7N9) Outbreaks

Background: As internet and social media use have skyrocketed, epidemiologists have begun to use online data such as Google query data and Twitter trends to track the activity levels of influenza and other infectious diseases. In China, Weibo is an extremely popular microblogging site that is equivalent to Twitter. Capitalizing on the wealth of public opinion data contained in posts on Weibo, this study used Weibo as a measure of the Chinese people’s reactions to two different outbreaks: the 2012 Middle East Respiratory Syndrome Coronavirus (MERS-CoV) outbreak, and the 2013 outbreak of human infection of avian influenza A(H7N9) in China. Methods: Keyword searches were performed in Weibo data collected by The University of Hong Kong’s Weiboscope project. Baseline values were determined for each keyword and reaction values per million posts in the days after outbreak information was released to the public. Results: The results show that the Chinese people reacted significantly to both outbreaks online, where their social media reaction was two orders of magnitude stronger to the H7N9 influenza outbreak that happened in China than the MERS-CoV outbreak that was far away from China. Conclusions: These results demonstrate that social media could be a useful measure of public awareness and reaction to disease outbreak information released by health authorities

Environmental Tax Reform, R&D Subsidies and CO2 Emissions: View Double Dividend Hypothesis

This study investigated whether environmental taxes achieve the double dividend of coexistence of economic growth and environmental protection. The research method used dynamic industrial relations models to estimate the influence of environmental taxes influence on the economy and environment. The goal was to conduct an objective analysis with scientific data. The conclusions provide a clue indicating that environmental taxes could only be used to facilitate short-term coexistence between economic growth and environmental protection. Once entering the mid-term and long term, the lack of innovation and technical progress would eventually cause economic development and environmental protection to diverge, which is why studies are yet to reach a consensus. The results suggest that although using environmental taxes to promote economic development and environmental protection can achieve the double dividend in the short term, in the midterm, the first dividend disappears unless a solution for improved energy efficiency and technical innovation can be determined immediately. Furthermore, to sustain its economic development and environmental protection efforts, Taiwan must first optimize its industrial structure, which can only be achieved through advanced research and development. Keywords: Environmental Tax Reform, R&D Subsidies, CO2 Emissions, Double Dividend Hypothesis JEL Classifications: C67, D57, Q50, Q5

Generation of T Follicular Helper Cells Is Mediated by Interleukin-21 but Independent of T Helper 1, 2, or 17 Cell Lineages

SummaryAfter activation, CD4+ helper T (Th) cells differentiate into distinct effector subsets. Although chemokine (C-X-C motif) receptor 5-expressing T follicular helper (Tfh) cells are important in humoral immunity, their developmental regulation is unclear. Here we show that Tfh cells had a distinct gene expression profile and developed in vivo independently of the Th1 or Th2 cell lineages. Tfh cell generation was regulated by ICOS ligand (ICOSL) expressed on B cells and was dependent on interleukin-21 (IL-21), IL-6, and signal transducer and activator of transcription 3 (STAT3). However, unlike Th17 cells, differentiation of Tfh cells did not require transforming growth factor β (TGF-β) or Th17-specific orphan nuclear receptors RORα and RORγ in vivo. Finally, naive T cells activated in vitro in the presence of IL-21 but not TGF-β signaling preferentially acquired Tfh gene expression and promoted germinal-center reactions in vivo. This study thus demonstrates that Tfh is a distinct Th cell lineage