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Introduction and Objectives: The relationship between anemia and the outcome of patients with cirrhosis is not completely clear. Therefore, we performed this large-scale epidemiological study to investigate the prevalence and severity of anemia in patients with cirrhosis and acute decompensation or liver injury and how anemia impacts short-term and long-term outcomes. Patients and Methods: Patients with cirrhosis and acute decompensation (AD) or acute liver injury (ALI) were enrolled in the Chinese AcuTe on CHronic LIver FailurE (CATCH-LIFE) studies, which consisted of two large, multicenter, prospective, observational cohorts between January 2015 and December 2016 and July 2018 and January 2019. We conducted data analysis on the prevalence of anemia and determined the relationship between anemia and prognosis. Results: Among 1979 patients, 1389 (70.2%) had anemia, among whom 599 (41.3%) had mild anemia, 595 (15.8%) had moderate anemia and 195 (2.4%) had severe anemia. A linear association between hemoglobin level and 90-day or 1-year LT-free mortality was shown, and a 10 g/L decrease in hemoglobin level was associated with a 6.8% extra risk of 90-day death and a 5.7% extra risk of 1-year death. Severe anemia was an independent risk factor for 90-day [HR=1.649 (1.100, 2.473), p=0.016] and 1-year LT-free mortality [HR=1.610 (1.159, 2.238), p=0.005]. Multinomial logistic regression analysis further identified that severe anemia was significantly associated with post-28-day mortality but not within-28-day mortality [ABSTRACT FROM AUTHOR]

Background and Aims: Hepatitis B virus (HBV) reactivation is a serious condition and has been extensively described in chemotherapeutic immunosuppressive population. However, little is known about HBV reactivation in immunocompetent patients with chronic hepatitis B (CHB). In this study, we evaluated the prevalence and the clinical significance of HBV reactivation in CHB patients with acute exacerbations. Method: Patients were screened from two prospective multicenter observational cohorts (CATCH-LIFE cohort). A total of 1,020 CHB patients with previous antiviral treatment history were included to assess the prevalence, risk factors, clinical characteristics of HBV reactivation, and its influence on the progression of chronic liver disease. Results: The prevalence of HBV reactivation was 51.9% in CHB patients with acute exacerbations who had antiviral treatment history in our study. Among the 529 patients with HBV reactivation, 70.9% of them were triggered by discontinued antiviral treatment and 5.9% by nucleos(t)ide analogs (NUCs) resistance. The prevalence of antiviral treatment disruption and NUCs resistance in patients with HBV reactivation is much higher than that in the patients without (70.9% vs. 0.2%, and 5.9% vs. 0, respectively, both p<0.001). Stratified and interaction analysis showed that HBV reactivation was correlated with high short-term mortality in cirrhosis subgroup (HR=2.1, p<0.001). Cirrhotic patients with HBV reactivation had a significantly higher proportion of developing hepatic failure (45.0% vs. 20.3%, p<0.001), acute-on-chronic liver failure (ACLF; 31.4% vs. 21.8%, p=0.005), and short-term death (14.0% vs. 5.9% for 28-day, and 23.3% vs. 12.4% for 90-day, both p<0.001) than those without. HBV reactivation is an independent risk factor of 90-day mortality for cirrhosis patients (OR=1.70, p=0.005), as well as hepatic encephalopathy, ascites, and bacterial infection. Conclusion: This study clearly demonstrated that there was a high prevalence of HBV reactivation in CHB patients, which was mainly triggered by discontinued antiviral treatment. The HBV reactivation strongly increased the risk of developing hepatic failure, ACLF and short-term death in HBV-related cirrhotic patients, which may suggest that HBV reactivation would be a new challenge in achieving the WHO target of 65% reduction in mortality from hepatitis B by 2030. [ABSTRACT FROM AUTHOR]

Huge amounts of unstructured data including image, video, audio, and text are ubiquitously generated and shared, and it is a challenge to protect sensitive personal information in them, such as human faces, voiceprints, and authorships. Differential privacy is the standard privacy protection technology that provides rigorous privacy guarantees for various data. This survey summarizes and analyzes differential privacy solutions to protect unstructured data content before it is shared with untrusted parties. These differential privacy methods obfuscate unstructured data after they are represented with vectors and then reconstruct them with obfuscated vectors. We summarize specific privacy models and mechanisms together with possible challenges in them. We also discuss their privacy guarantees against AI attacks and utility losses. Finally, we discuss several possible directions for future research. [ABSTRACT FROM AUTHOR]

In this technology-based era, network-based systems are facing new cyber-attacks on daily bases. Traditional cybersecurity approaches are based on old threat-knowledge databases and need to be updated on a daily basis to stand against new generation of cyber-threats and protect underlying network-based systems. Along with updating threat-knowledge databases, there is a need for proper management and processing of data generated by sensitive real-time applications. In recent years, various computing platforms based on representation learning algorithms have emerged as a useful resource to manage and exploit the generated data to extract meaningful information. If these platforms are properly utilized, then strong cybersecurity systems can be developed to protect the underlying network-based systems and support sensitive real-time applications. In this survey, we highlight various cyber-threats, real-life examples, and initiatives taken by various international organizations. We discuss various computing platforms based on representation learning algorithms to process and analyze the generated data. We highlight various popular datasets introduced by well-known global organizations that can be used to train the representation learning algorithms to predict and detect threats. We also provide an in-depth analysis of research efforts based on representation learning algorithms made in recent years to protect the underlying network-based systems against current cyberthreats. Finally, we highlight various limitations and challenges in these efforts and available datasets that need to be considered when using them to build cybersecurity system [ABSTRACT FROM AUTHOR]

Integration of embedded multimedia devices with powerful computing platforms, e.g., machine learning platforms, helps to build smart cities and transforms the concept of Internet of Things into Internet ofMultimedia Things (IoMT). To provide different services to the residents of smart cities, the IoMT technology generates big multimedia data. The management of big multimedia data is a challenging task for IoMT technology. Without proper management, it is hard to maintain consistency, reusability, and reconcilability of generated big multimedia data in smart cities. Various machine learning techniques can be used for automatic classification of raw multimedia data and to allow machines to learn features and perform specific tasks. In this survey, we focus on various machine learning platforms that can be used to process and manage big multimedia data generated by different applications in smart cities. We also highlight various limitations and research challenges that need to be considered when processing big multimedia data in real-time. [ABSTRACT FROM AUTHOR]

In a contemporary data center, Linux applications often generate a large quantity of real-time system call traces, which are not suitable for traditional host-based intrusion detection systems deployed on every single host. Training data mining models with system calls on a single host that has static computing and storage capacity is time-consuming, and intermediate datasets are not capable of being efficiently handled. It is cumbersome for the maintenance and updating of host-based intrusion detection systems (HIDS) installed on every physical or virtual host, and comprehensive system call analysis can hardly be performed to detect complex and distributed attacks among multiple hosts. Considering these limitations of current system-callbased HIDS, in this article, we provide a review of the development of system-call-based HIDS and future research trends. Algorithms and techniques relevant to system-call-based HIDS are investigated, including feature extractionmethods and various data mining algorithms. TheHIDS dataset issues are discussed, including currently available datasets with system calls and approaches for researchers to generate new datasets. The application of system-call-based HIDS on current embedded systems is studied, and related works are investigated. Finally, future research trends are forecast regarding three aspects, namely, the reduction of the false-positive rate, the improvement of detection efficiency, and the enhancement of collaborative security. [ABSTRACT FROM AUTHOR]

Applications in risk-critical domains such as emergency management and industrial control systems need near-real-time stream data processing in large-scale sensing networks. The key problem is how to ensure online end-to-end security (e.g., confidentiality, integrity, and authenticity) of data streams for such applications. We refer to this as an online security verification problem. Existing data security solutions cannot be applied in such applications as they cannot deal with data streams with high-volume and high-velocity data in real time. They introduce a significant buffering delay during security verification, resulting in a requirement for a large buffer size for the stream processing server. To address this problem, we propose a Dynamic Key-Length-Based Security Framework (DLSeF) based on a shared key derived from synchronized prime numbers; the key is dynamically updated at short intervals to thwart potential attacks to ensure end-to-end security. Theoretical analyses and experimental results of the DLSeF framework show that it can significantly improve the efficiency of processing stream data by reducing the security verification time and buffer usage without compromising security. [ABSTRACT FROM AUTHOR]

The reliability and security of multimedia contents in transmission, communications, storage, and usage have attracted special attention. Robust image hashing, also referred to as perceptual image hashing, is widely applied in multimedia authentication and forensics, image retrieval, image indexing, and digital image watermarking. In this work, a novel robust image hashing method based on quaternion Zernike moments (QZMs) is proposed. QZMs offer a sound way to jointly deal with the three channels of color images without discarding chrominance information; the generated hash is thus shorter than the hash of three channels separately processing. The proposed approach's performance was evaluated on the color images database of UCID and compared with several recent and efficient methods. These experiments show that the proposed scheme provides a short hash in length that is robust to most common image content-preserving manipulations like JPEG compression, filtering, noise, scaling, and large angle rotation operations. [ABSTRACT FROM AUTHOR]

Background: Accurate quantitative detection of hepatitis C virus (HCV) RNA is critical for diagnosis of acute or chronic HCV infection, and for follow-up of virologic response during HCV targeted therapy. In the present study, traceability and reproducibility of a novel China-certified domestic Sansure HCV RNA diagnostic assay (Sansure, Changsha, Hunan, China) was evaluated and the clinical performance of this assay was also analyzed.Methods: Traceability of the Sansure HCV RNA assay to the WHO international standard for HCV (genotype 1a) was detected across multiple centers. Reproducibility, accuracy (the differences of observed average concentrations and expected concentrations) and precision were assessed using series dilutions of World HCV RNA performance panel WWHV303-02 (HCV-1b), WWHV303-04(HCV-2a), WWHV303-11(HCV-3a) and WWHV303-19 (HCV-6a). In addition, both Sansure HCV RNA and CAP/CTM HCV (Roche, Branchburg, NJ, USA) assays were used to detect HCV RNA in 346 EDTA anti-coagulated plasma samples from previous HCV-infected patients, during and after antiviral therapy.Results: The Sansure assay showed good traceability by agreeing with the HCV-1a WHO standard across all five concentrations tested (25, 50, 100, 1000, 10,000 IU/ml). The differences between observed average concentrations and expected concentrations were all within 0.2 log10 IU/ml. HCV WWHV303 standards across 4 HCV genotypes (1b, 2a, 3a and 6a) were used for evaluation of reproducibility and the accuracy of the test were all within 0.2 log10 IU/ml. The inter-assay variations across the above 4 HCV genotypes were all less than 0.03 on each evaluated concentration, indicating good precision of Sansure HCV RNA assay. In clinical practice, concordant results were determined in 99.42% (344/346) samples (215 positive and 129 negative samples). Two specimens with negative HCV RNA results by Sansure assay were detected positive by CAP/CTM HCV test. Correlation analysis indicated a significantly positive correlation in detected HCV RNA concentrations (r = 0.9439, P < 0.0001). HCV RNA levels in 95.35% (205/215) specimens were within mean difference ± 1.96 SD as tested by both assays.Conclusions: With the advantages of traceability, reproducibility and lower price, Sansure HCV RNA assay represented an alternative option for HCV RNA detection in hospital and medical institution in China. [ABSTRACT FROM AUTHOR]

Scientific processes are usually time constrained with overall deadlines and local milestones. In scientific workflow systems, due to the dynamic nature of the underlying computing infrastructures such as grid and cloud, execution delays often take place and result in a large number of temporal violations. Since temporal violation handling is expensive in terms of both monetary costs and time overheads, an essential question aroused is "do we need to handle every temporal violation in scientific workflow systems?" The answer would be "true" according to existing works on workflow temporal management which adopt the philosophy similar to the handling of functional exceptions, that is, every temporal violation should be handled whenever it is detected. However, based on our observation, the phenomenon of self-recovery where execution delays can be automatically compensated for by the saved execution time of subsequent workflow activities has been entirely overlooked. Therefore, considering the nonfunctional nature of temporal violations, our answer is "not necessarily true." To take advantage of self-recovery, this article proposes a novel adaptive temporal violation handling point selection strategywhere this phenomenon is effectively utilised to avoid unnecessary temporal violation handling. Based on simulations of both real-world scientific workflows and randomly generated test cases, the experimental results demonstrate that our strategy can significantly reduce the cost on temporal violation handling by over 96% while maintaining extreme low violation rate under normal circumstances. [ABSTRACT FROM AUTHOR]

Web service composition allows users to create value-added composite Web services on existent services, where top-k composite services are helpful for users to find a satisfying composite service efficiently. However, with an increasing number of Web services and users 'various composition preferences, computing top-k composite services dynamically for different users is difficult. In view of this challenge, an optimization method for top-k composite services is proposed, based on a preference-aware service dominance relationship. Concretely speaking, firstly, user preferences are modeled with the preference-aware service dominance. Then, in local service selection, a multi-index based algorithm is proposed, named Multi-Index, for computing candidate services of each task dynamically. After that, in global optimization, combined with a service lattice, top-k composite services are selected under a dominant number-aware service ranking. A case study is also presented for illustrating the authors 'solution. At last, an experiment was conducted to verify the proposed method. [ABSTRACT FROM AUTHOR]

Background: The Macleaya spp., including Macleaya cordata and Macleaya microcarpa, are traditional anti-virus, inflammation eliminating, and insecticide herb medicines for their isoquinoline alkaloids. They are also known as the basis of the popular natural animal food addictive in Europe. However, few studies especially at genomics level were conducted on them. Hence, we performed the Macleaya spp. transcriptome and integrated it with iTRAQ proteome analysis in order to identify potential genes involved in alkaloids biosynthesis. Methodology and Principal Findings: We elaborately designed the transcriptome, proteome and metabolism profiling for 10 samples of both species to explore their alkaloids biosynthesis. From the transcriptome data, we obtained 69367 and 78255 unigenes for M. cordata and M. microcarpa, in which about two thirds of them were similar to sequences in public databases. By metabolism profiling, reverse patterns for alkaloids sanguinarine, chelerythrine, protopine, and allocryptopine were observed in different organs of two species. We characterized the expressions of enzymes in alkaloid biosynthesis pathways. We also identified more than 1000 proteins from iTRAQ proteome data. Our results strongly suggest that the root maybe the organ for major alkaloids biosynthesis of Macleaya spp. Except for biosynthesis, the alkaloids storage and transport were also important for their accumulation. The ultrastructure of laticifers by SEM helps us to prove the alkaloids maybe accumulated in the mature roots. Conclusions/Significance: To our knowledge this is the first study to elucidate the genetic makeup of Macleaya spp. This work provides clues to the identification of the potential modulate genes involved in alkaloids biosynthesis in Macleaya spp., and sheds light on researches for non-model medicinal plants by integrating different high-throughput technologies. [ABSTRACT FROM AUTHOR]

In service selection, an end user often has his or her personal preferences imposing on a candidate service's nonfunctional properties. For a service selection process promoted by a group of users, candidate services are often evaluated by a group of end users who may have different prej'erences or priorities. In this situation, it is ojten a challenging effort to make a tradeoff among various preferences or priorities of the users. In view of this challenge, a multi-criteria decision-making method, named AHP (Analytic Hierarchy Process), is introduced to transform both qualitative personal prejerences and users 'priorities into numeric weights. Furthermore, a QoS-aware service evaluation method is presented for a shared service's co-selection tak-ing advantage of AHP theory. At last, a case study is presented to demonstrate the feasibility of the method [ABSTRACT FROM AUTHOR]

With conserved structural scaffold and divergent electrophysiological functions, animal toxins are considered powerful tools for investigating the basic structure-function relationship of voltage-gated sodium channels. Jingzhaotoxin-III (β-TRTX-Cj1α) is a unique sodium channel gating modifier from the tarantula Chilobrachys jingzhao, because the toxin can selectively inhibit the activation of cardiac sodium channel but not neuronal subtypes. However, the molecular basis of JZTX-III interaction with sodium channels remains unknown. In this study, we showed that JZTX-III was efficiently expressed by the secretory pathway in yeast. Alanine-scanning analysis indicated that 2 acidic residues (Asp1, Glu3) and an exposed hydrophobic patch, formed by 4 Trp residues (residues 8, 9, 28 and 30), play important roles in the binding of JZTX-III to Nav1.5. JZTX-III docked to the Nav1.5 DIIS3-S4 linker. Mutations S799A, R800A, and L804A could additively reduce toxin sensitivity of Nav1.5. We also demonstrated that the unique Arg800, not emerging in other sodium channel subtypes, is responsible for JZTX-III selectively interacting with Nav1.5. The reverse mutation D816R in Nav1.7 greatly increased the sensitivity of the neuronal subtype to JZTX-III. Conversely, the mutation R800D in Nav1.5 decreased JZTX-III's IC50 by 72-fold. Therefore, our results indicated that JZTX-III is a site 4 toxin, but does not possess the same critical residues on sodium channels as other site 4 toxins. Our data also revealed the underlying mechanism for JZTXIII to be highly specific for the cardiac sodium channel. [ABSTRACT FROM AUTHOR]

In a scientific work flow system, a checkpoint selection strategy is used to select checkpoints along scientific work flow execution for verifying temporal constraints so that we can identify any temporal violations and handle them in time in order to ensure overall temporal correctness of the execution that is often essential for the usefulness of execution results. The problem of existing representative strategies is that they do not differentiate temporal constraints as, once a checkpoint is selected, they verify all temporal constraints. However, such a checkpoint does not need to be taken for those constraints whose consistency can be deduced from others. The corresponding verification of such constraints is consequently unnecessary and can severely impact overall temporal verification efficiency while the efficiency determines whether temporal violations can be identified quickly for handling in time. To address the problem, in this article, we develop a new temporal-dependency based checkpoint selection strategy which can select checkpoints in accordance with different temporal constraints. With our strategy, the corresponding unnecessary verification can be avoided. The comparison and experimental simulation further demonstrate that our new strategy can improve the efficiency of overall temporal verification significantly over the existing representative strategies. [ABSTRACT FROM AUTHOR]

Two forms of hepatitis B virus (HBV) C/D recombinant have been identified in western China, but little is known about their geographical and ethnic distributions, and particularly the clinical significance and specific mutations in the pre-core region. To address these questions, a total of 624 chronic HBV carriers from four ethnic populations representing five provinces in western China were enrolled in this study. Genotypes were firstly determined by restriction fragment length polymorphism, and then confirmed by full or partial genome nucleotide sequencing. The distribution of HBV genotypes was as follows: HBV/B: 40 (6.4%); HBV/C: 221 (35.4%); HBV/D: 39 (6.3%); HBV/CD: 324 (51.9%). In the 324 HBV C/D recombinant infections, 244 (75.3%) were infected with the ''CD1'' and 80 (24.7%) were infected with the ''CD2.'' The distribution of HBV genotypes exhibited distinct patterns in different regions and ethnic populations. Geographically, the C/D recombinant was the most prevalent HBV strain on the Qinghai-Tibet Plateau. Ethnically, the C/D recombinant had a higher prevalence in Tibetan patients than in other populations. Clinically, patients with HBV/CD1 showed significantly lower levels of serum total bilirubin than patients with HBV/C2. The prevalence of HBeAg was comparable between patients with HBV/CD1 and HBV/ C2 (63.3% vs 50.0%, P = 0.118) whether patients were taken together or stratified by age into three groups (65.6% vs 58.8% in ,30 years, P = 0.758; 61.9% vs 48.0% in 30-50 years, P = 0.244; 64.3% vs 33.3%, P = 0.336). Virologically HBV/CD1 had a significantly lower frequency of G1896A than HBV/C2. In conclusion, the HBV C/D recombinant is restricted to the Qinghai- Tibet Plateau in western China and is found predominantly in Tibetans. The predominance of the premature pre-core stop mutation G1896A in patients with the HBV C/D recombinant may account for the higher prevalence of HBeAg in these patients. [ABSTRACT FROM AUTHOR]

Background: The mechanisms by which chronic hepatitis B is completely resolved through antiviral therapy are unknown, and the contribution of acquired T cell immunity to hepatitis B surface antigen (HBsAg) seroclearance has not been investigated. Therefore, we measured the T-cell responses to core and envelope antigens in patients with HBsAg seroclearance. Methods: Fourteen subjects with HBsAg seroclearance following antiviral treatment for chronic hepatitis B, 7 HBeAg-positive immunotolerant HBV carriers and 9 HBeAg-negative inactive HBsAg carriers were recruited. HBVspecific T-cell responses to recombinant HBV core (rHBcAg) and envelope (rHBsAg) proteins and pools of core and envelope peptides were measured using an ELISPOT assay detecting interferon-gamma and intracellular cytokine staining (ICS) assays detecting interferon-gamma or interleukin 2. Results: Interferon-gamma ELISPOT assays showed a low frequency of weak responses to the rHBsAg and S peptide pool in the HBsAg seroclearance group, and the response frequency to the rHBcAg and the C peptide pool was higher than to the rHBsAg (P < 0.001) and S peptide pool (P = 0.001) respectively. A higher response frequency to C than S peptide pools was confirmed in the interferon-gamma ICS assays for both CD4+ (P = 0.033) and CD8+ (P = 0.040) T cells in the HBsAg seroclearance group. The responses to C and S antigens in the inactive carriers were similar. Conclusions: There was a low frequency of CD4+ and CD8+ T cell immune responses to envelope antigens in Chinese subjects with HBsAg seroclearance following antiviral therapy. It is unlikely that these immune responses are responsible for HBsAg seroclearance in these subjects. [ABSTRACT FROM AUTHOR]

The concept of cloud computing continues to spread widely, as it has been accepted recently. Cloud computing has many unique advantages which can be utilized to facilitate workflow execution. Instance-intensive cost-constrained cloud workflows are workflows with a large number of workflow instances (i.e. instance intensive) bounded by a certain budget for execution (i.e. cost constrained) on a cloud computing platform (i.e. cloud workflows). However, there are, so far, no dedicated scheduling algorithms for instance-intensive cost-constrained cloud workflows. This paper presents a novel compromised-time-cost scheduling algorithm which considers the characteristics of cloud computing to accommodate instance-intensive cost-constrained workflows by compromising execution time and cost with user input enabled on the fly. The simulation performed demonstrates that the algorithm can cut down the mean execution cost by over 15% whilst meeting the user-designated deadline or shorten the mean execution time by over 20% within the user-designated execution cost. [ABSTRACT FROM AUTHOR]