InvVis: Large-Scale Data Embedding for Invertible Visualization

We present InvVis, a new approach for invertible visualization, which is reconstructing or further modifying a visualization from an image. InvVis allows the embedding of a significant amount of data, such as chart data, chart information, source code, etc., into visualization images. The encoded image is perceptually indistinguishable from the original one. We propose a new method to efficiently express chart data in the form of images, enabling large-capacity data embedding. We also outline a model based on the invertible neural network to achieve high-quality data concealing and revealing. We explore and implement a variety of application scenarios of InvVis. Additionally, we conduct a series of evaluation experiments to assess our method from multiple perspectives, including data embedding quality, data restoration accuracy, data encoding capacity, etc. The result of our experiments demonstrates the great potential of InvVis in invertible visualization.Comment: IEEE VIS 202

Service Outsourcing Character Oriented Privacy Conflict Detection Method in Cloud Computing

Cloud computing has provided services for users as a software paradigm. However, it is difficult to ensure privacy information security because of its opening, virtualization, and service outsourcing features. Therefore how to protect user privacy information has become a research focus. In this paper, firstly, we model service privacy policy and user privacy preference with description logic. Secondly, we use the pellet reasonor to verify the consistency and satisfiability, so as to detect the privacy conflict between services and user. Thirdly, we present the algorithm of detecting privacy conflict in the process of cloud service composition and prove the correctness and feasibility of this method by case study and experiment analysis. Our method can reduce the risk of user sensitive privacy information being illegally used and propagated by outsourcing services. In the meantime, the method avoids the exception in the process of service composition by the privacy conflict, and improves the trust degree of cloud service providers

An improved key-phase-free blade tip-timing technique for nonstationary test conditions and its application on large-scale centrifugal compressor blades

7partially_openopenHe, Changbo; Antoni, Jerome; Daga, Alessandro Paolo; Li, Hongkun; Chu, Ning; Lu, Siliang; Li, ZhixiongHe, Changbo; Antoni, Jerome; Daga, Alessandro Paolo; Li, Hongkun; Chu, Ning; Lu, Siliang; Li, Zhixion

MicroRNA-320a inhibits cell proliferation, migration and invasion by targeting BMI-1 in nasopharyngeal carcinoma

AbstractIn the present study, we investigated the roles and molecular mechanisms of miR-320a in human nasopharyngeal carcinoma (NPC). miR-320a expression was strongly reduced in NPC tissues and cell lines. Overexpression of miR-320a significantly suppressed NPC cell growth, migration, invasion and tumor growth in a xenograft mouse model. A luciferase reporter assay revealed that miR-320a could directly bind to the 3′ UTR of BMI-1. Overexpression of BMI-1 rescued miR-320a-mediated biological function. BMI-1 expression was found to be up-regulated and inversely correlated with miR-320a expression in NPC. Collectively, our data indicate that miR-320a plays a tumor suppressor role in the development and progression of NPC and may be a novel therapeutic target against NPC

Advances in Patient Classification for Traditional Chinese Medicine: A Machine Learning Perspective

As a complementary and alternative medicine in medical field, traditional Chinese medicine (TCM) has drawn great attention in the domestic field and overseas. In practice, TCM provides a quite distinct methodology to patient diagnosis and treatment compared to western medicine (WM). Syndrome (ZHENG or pattern) is differentiated by a set of symptoms and signs examined from an individual by four main diagnostic methods: inspection, auscultation and olfaction, interrogation, and palpation which reflects the pathological and physiological changes of disease occurrence and development. Patient classification is to divide patients into several classes based on different criteria. In this paper, from the machine learning perspective, a survey on patient classification issue will be summarized on three major aspects of TCM: sign classification, syndrome differentiation, and disease classification. With the consideration of different diagnostic data analyzed by different computational methods, we present the overview for four subfields of TCM diagnosis, respectively. For each subfield, we design a rectangular reference list with applications in the horizontal direction and machine learning algorithms in the longitudinal direction. According to the current development of objective TCM diagnosis for patient classification, a discussion of the research issues around machine learning techniques with applications to TCM diagnosis is given to facilitate the further research for TCM patient classification

Tourism-Related CO 2

The rapid development of the tourism industry has been accompanied by an increase in CO2 emissions and has a certain degree of impact on climate change. This study adopted the bottom-up approach to estimate the spatiotemporal change of CO2 emissions of the tourism industry in China and its 31 provinces over the period 2000–2015. In addition, the decoupling index was applied to analyze the decoupling effects between tourism-related CO2 emissions and tourism economy from 2000 to 2015. The results showed that the total CO2 emissions of the tourism industry rose from 37.95 Mt in 2000 to 100.98 Mt in 2015 with an average annual growth rate of 7.1%. The highest CO2 emissions from the tourism industry occurred in eastern coastal China, whereas the least CO2 emissions were in the west of China. Additionally, the decoupling of CO2 emissions from economic growth in China’s tourism industry had mainly gone through the alternations of negative decoupling and weak decoupling. The decoupling states in most of the Chinese provinces were desirable during the study period. This study may serve as a scientific reference regarding decision-making in the sustainable development of the tourism industry in China

Global Seafood Trade: Insights in Sustainability Messaging and Claims of the Major Producing and Consuming Regions

Seafood supply chains are complex, not least in the diverse origins of capture fisheries and through aquaculture production being increasingly shared across nations. The business-to-business (B2B) seafood trade is supported by seafood shows that facilitate networking and act as fora for signaling of perceptions and values. In the Global North, sustainability related certifications and messaging have emerged as an important driver to channel the demands of consumers, institutions, and lead firms. This study investigates which logos, certifications, and claims were presented at the exhibitor booths within five seafood trade shows in China, Europe, and USA. The results indicate a difference in the way seafood is advertised. Messaging at the Chinese shows had less of an emphasis on sustainability compared to that in Europe and the USA, but placed a greater emphasis on food safety and quality than on environmental concerns. These findings suggest cultural differences in the way seafood production and consumption is communicated through B2B messaging. Traders often act as choice editors for final consumers. Therefore, it is essential to convey production processes and sustainability issues between traders and the market. An understanding of culture, messaging strategies, and interpretation could support better communication of product characteristics such as sustainability between producers, traders, and consumers

MDA5 against enteric viruses through induction of interferon-like response partially via the JAK-STAT cascade

Enteric viruses including hepatitis E virus (HEV), human norovirus (HuNV), and rotavirus are causing global health issues. The host interferon (IFN) response constitutes the first-line defense against viral infections. Melanoma Differentiation-Associated protein 5 (MDA5) is an important cytoplasmic receptor sensing viral infection to trigger IFN production, and on the other hand it is also an IFN-stimulated gene (ISG). In this study, we investigated the effects and mode-of-action of MDA5 on the infection of enteric viruses. We found that MDA5 potently inhibited HEV, HuNV and rotavirus replication in multiple cell models. Overexpression of MDA5 induced transcription of important antiviral ISGs through IFN-like response, without triggering of functional IFN production. Interestingly, MDA5 activates the expression and phosphorylation of STAT1, which is a central component of the JAK-STAT cascade and a hallmark of antiviral IFN response. However, genetic silencing of STAT1 or pharmacological inhibition of the JAK-STAT cascade only partially attenuated the induction of ISG transcription and the antiviral function of MDA5. Thus, we have demonstrated that MDA5 effectively inhibits HEV, HuNV and rotavirus replication through provoking a non-canonical IFN-like response, which is partially dependent on JAK-STAT cascade