Nyquist Stability Analysis of an AC-Grid Connected VSC-HVDC System Using a Distributed Parameter DC Cable Model

In this paper, a two-terminal VSC-HVDC system embedded in a weak grid ac environment is considered, emphasizing modeling, controller design, and small-signal stability analysis. Traditionally, the dc cable is modeled by \Pi -sections, implying that care has to be taken when using the model for higher frequencies or in cases of higher cable impedance density, such as submarine cables. Here, a distributed parameter cable model is used to overcome this problem. The VSC-HVDC system can be described as two cascaded blocks. The first block is a transfer function that will differ depending on what input and output variables are considered, but which is in all realistic cases stable. The second block is a feedback loop, where the forward path is a rational function and the return path is a dissipative infinite dimensional function, remaining the same in all cases. The stability is then analyzed, using the Nyquist criterion, in a straightforward manner. Numerical examples are given by the use of MATLAB. The result is that if the VSC-HVDC system using a single \Pi -section cable model is stable, so is the VSC-HVDC system using a distributed parameter cable model

Efficient Attribute-Based Encryption with Privacy-Preserving Key Generation and Its Application in Industrial Cloud

Due to the rapid development of new technologies such as cloud computing, Internet of Things (IoT), and mobile Internet, the data volumes are exploding. Particularly, in the industrial field, a large amount of data is generated every day. How to manage and use industrial Big Data primely is a thorny challenge for every industrial enterprise manager. As an emerging form of service, cloud computing technology provides a good solution. It receives more and more attention and support due to its flexible configuration, on-demand purchase, and easy maintenance. Using cloud technology, enterprises get rid of the heavy data management work and concentrate on their main business. Although cloud technology has many advantages, there are still many problems in terms of security and privacy. To protect the confidentiality of the data, the mainstream solution is encrypting data before uploading. In order to achieve flexible access control to encrypted data, attribute-based encryption (ABE) is an outstanding candidate. At present, more and more applications are using ABE to ensure data security. However, the privacy protection issues during the key generation phase are not considered in the current ABE systems. That is to say, the key generation center (KGC) knows both of attributes and corresponding keys of each user. This problem is especially serious in the industrial big data scenario, because it will cause great damage to the business secrets of industrial enterprises. In this paper, we design a new ABE scheme that protects user\u27s privacy during key issuing. In our new scheme, we separate the functionality of attribute auditing and key generating to ensure that the KGC cannot know user\u27s attributes and that the attribute auditing center (AAC) cannot obtain the user\u27s secret key. This is ideal for many privacy-sensitive scenarios, such as industrial big data scenario

Fractional Black-Scholes Model and Technical Analysis of Stock Price

In the stock market, some popular technical analysis indicators (e.g., Bollinger bands, RSI, ROC, etc.) are widely used to forecast the direction of prices. The validity is shown by observed relative frequency of certain statistics, using the daily (hourly, weekly, etc.) stock prices as samples. However, those samples are not independent. In earlier research, the stationary property and the law of large numbers related to those observations under Black-Scholes stock price model and stochastic volatility model have been discussed. Since the fitness of both Black-Scholes model and short-range dependent process has been questioned, we extend the above results to fractional Black-Scholes model with Hurst parameter H>1/2, under which the stock returns follow a kind of long-range dependent process. We also obtain the rate of convergence

LncRNA-ATB inhibits the proliferation and invasion of NSCLC cells by regulating MiR-200s expression

Purpose: To investigate the effect of lncRNA-ATB on the proliferation and invasion of non-small cell lung cancer (NSCLC) cells, and its mechanism of action. Methods: LncRNA-ATB mRNA levels in carcinoma tissues and normal adjacent tissues of 38 NSCLC patients in Peking University Shougang Hospital were determined by reverse transcription-polymerase chain reaction (RT-PCR). Human NSCLC A549 cell line was divided into control and lncRNA-ATB inhibition (si-ATB) groups, respectively. The proliferation and invasion of cells in each group were assessed. Subsequently, the effect of lncRNA-ATB inhibition on the growth of NSCLC cells was evaluated by subcutaneous tumor formation assay. Results: The expression of lncRNA-ATB was significantly higher in carcinoma tissues than in normal adjacent tissues in NSCLC patients. Cell counting kit-8 (CCK-8) assay results showed that si-ATB group displayed a weakened ability of the cells to proliferate (p < 0.05). Furthermore, deoxyribonucleic acid (DNA) replication ability was weaker in si-ATB group than in the control group. Wound healing assay results showed that the migration ability of cells in the si-ATB group was lower than that in the control group. Also, lncRNA-ATB knockdown inhibited the invasion ability of human NSCLC cells (p < 0.05). Tumor formation assay data indicate that lncRNA-ATB knockdown significantly repressed the subcutaneous tumor formation ability of NSCLC cells. Furthermore, lncRNA-ATB knockdown in NSCLC cells up-regulated miR-200a, miR-200b and miR-200c. Conclusion: The expression level of LncRNA-ATB is elevated in carcinoma tissues of NSCLC patients, and its knockdown suppresses the proliferation and invasion of NSCLC cells by up-regulating miR-200s. This finding suggests that it is a potential strategy for the management of NSCLC patients

An Evaluation on Bridge Bearing Capacity under Scour and Re-occurrence of Strong Earthquake

Plagued by frequent calamities, Bridge No.3 encountered magnitude-8 earthquake on May 12, 2008 and several years later its pile foundation was intensively scoured. The smallest scour depth was 4.5 meters and the largest scour depth was 9.2 meters. Considering intense scour and re-occurrence of strong earthquake, the Chinese existing standard and seismic response analysis are used to study bearing capacity and seismic performance of pier and pile foundation of Bridge No.3 before and after scour. It is proved by calculation that the bridge is stable before scour and can hardly bear strong earthquake and intense scour after scour, therefore consolidation is required. The study result may serve as an important reference for the bridge affected by serious scour and strong earthquake

Rheumatoid Arthritis and Risk of Atrial Fibrillation: Results from Pooled Cohort Studies and Mendelian Randomization Analysis

Observational research has indicated that individuals diagnosed with rheumatoid arthritis (RA) have an elevated likelihood of developing atrial fibrillation (AF). Herein, we performed meta-analysis and Mendelian randomization (MR) analysis to explore the correlation and potential causal relationship between RA and AF. We searched PubMed, Embase, and Web of Science for cohort studies comparing AF risk among participants with and without RA. Quantitative synthesis of the adjusted risk ratio (RR) or hazard ratio was performed with the random-effects model. RA and AF were studied with two-sample MR analysis with the random-effects inverse variance weighted method. Patients with RA had a higher risk of AF than participants without RA [RR = 1.32, 95% confidence interval (CI): 1.23–1.43, P < 0.0001]. Genetically predicted RA was not associated with a significantly elevated risk of AF (odds ratio = 1.009, 95% CI: 0.986–1.032, P = 0.449). After adjustment for confounding factors in multifactorial MR, RA and AF still showed no correlation. Sensitivity analyses yielded similar results, thus indicating the robustness of the causal association. Overall, RA was associated with elevated risk of AF in our meta-analysis. However, genetically predicted RA may not be causal

DRUM: Inference of Disease-Associated m6A RNA Methylation Sites From a Multi-Layer Heterogeneous Network

Recent studies have revealed that the RNA N6-methyladenosine (m6A) modification plays a critical role in a variety of biological processes and associated with multiple diseases including cancers. Till this day, transcriptome-wide m6A RNA methylation sites have been identified by high-throughput sequencing technique combined with computational methods, and the information is publicly available in a few bioinformatics databases; however, the association between individual m6A sites and various diseases are still largely unknown. There are yet computational approaches developed for investigating potential association between individual m6A sites and diseases, which represents a major challenge in the epitranscriptome analysis. Thus, to infer the disease-related m6A sites, we implemented a novel multi-layer heterogeneous network-based approach, which incorporates the associations among diseases, genes and m6A RNA methylation sites from gene expression, RNA methylation and disease similarities data with the Random Walk with Restart (RWR) algorithm. To evaluate the performance of the proposed approach, a ten-fold cross validation is performed, in which our approach achieved a reasonable good performance (overall AUC: 0.827, average AUC 0.867), higher than a hypergeometric test-based approach (overall AUC: 0.7333 and average AUC: 0.723) and a random predictor (overall AUC: 0.550 and average AUC: 0.486). Additionally, we show that a number of predicted cancer-associated m6A sites are supported by existing literatures, suggesting that the proposed approach can effectively uncover the underlying epitranscriptome circuits of disease mechanisms. An online database DRUM, which stands for disease-associated ribonucleic acid methylation, was built to support the query of disease-associated RNA m6A methylation sites, and is freely available at: www.xjtlu.edu.cn/biologicalsciences/drum

IL-10 plays a central regulatory role in the cytokines induced by hepatitis C virus core protein and polyinosinic acid:polycytodylic acid

Hepatitis C virus (HCV) can cause persistent infection and chronic liver disease, and viral factors are involved in HCV persistence. HCV core protein, a highly conserved viral protein, not only elicits an immunoresponse, but it also regulates it. In addition, HCV core protein interacts with toll-like receptors (TLRs) on monocytes, inducing them to produce cytokines. Polyinosinic acid:polycytodylic acid (polyI:C) is a synthetic analogue of double-stranded RNA that binds to TLR3 and can induce secretion of type I IFN from monocytes. Cytokine response against HCV is likely to affect the natural course of infection as well as HCV persistence. However, possible effects of cytokines induced by HCV core protein and polyI:C remain to be investigated. In this study, we isolated CD14+ monocytes from healthy donors, cultured them in the presence of HCV core protein and/or polyI:C, and characterized the induced cytokines, phenotypes and mechanisms. We demonstrated that HCV core protein- and polyI:C-stimulated CD14+ monocytes secreted tumor necrosis factor-α (TNF-α), interleukin (IL)-1β, IL-10, and type I interferon (IFN). Importantly, TNF-α and IL-1β regulated the secretion of IL-10, which then influenced the expression of signal transducer and activator of transcription 1 (STAT1) and interferon regulatory factor 1 (IRF1) and subsequently the production of type I IFN. Interestingly, type I IFN also regulated the production of IL-10, which in turn inhibited the nuclear factor (NF)-κB subunit, reducing TNF-α and IL-1β levels. Therefore, IL-10 appears to play a central role in regulating the production of cytokines induced by HCV core protein and polyI:C