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Aims The current study aimed to determine the chemical compositions of ginger extract (GE) and to assess the antibacterial activities of GE against the ginger bacterial wilt pathogen Ralstonia solanacearum and to screen their mechanisms of action. Methods and Results A total of 393 compounds were identified by using ultra-performance liquid chromatography and tandem-mass spectrometry. The antibacterial test indicated that GE had strong antibacterial activity against R. solanacearum and that the bactericidal effect exhibited a dose-dependent manner. The minimum inhibitory concentration and minimum bactericidal concentration of R. solanacearum were 3.91 and 125 mg/ml, respectively. The cell membrane permeability and integrity of R. solanacearum were destroyed by GE, resulting in cell content leakage, such as electrolytes, nucleic acids, proteins, extracellular adenosine triphosphate and exopoly saccharides. In addition, the activity of cellular succinate dehydrogenase and alkaline phosphatase of R. solanacearum decreased gradually with an increase in the GE concentration. Scanning electron microscopy analysis revealed that GE treatment changed the morphology of the R. solanacearum cells. Further experiments demonstrated that GE delayed or slowed the occurrence of bacterial wilt on ginger. Conclusions GE has a significant antibacterial effect on R. solanacearum, and the antibacterial effect is concentration dependent. The GE treatments changed the morphology, destroyed membrane permeability and integrity, reduced key enzyme activity and inhibit the synthesis of the virulence factor EPS of R. solanacearum. GE significantly controlled the bacterial wilt of ginger during infection. Significance and Impact of the Study This research provides insight into the antimicrobial mechanism of GE against R. solanacearum, which will open a new application field for GE.

The sensor-cloud system (SCS) integrates sensors, sensor networks, and cloud for managing sensors, collecting and processing data, and decision-making based on data processed. Though the SCS has received tremendous attention from both academia and industry because of its numerous exciting applications, it still faces the challenge in reliability. The reliability of an SCS is generally referred to as the ability to perform required functions for a given period of time. This work is focused on the $K$ -terminal reliability of an SCS, which is concerned with the successful communication between all pairs of network nodes belonging to a pre-specified subset $K$ . The increased complexity and scale of real-life SCSs require new efficient techniques to evaluate their $K$ -terminal reliability. In this work we make novel contributions by proposing a network simplification method that can effectively remove all redundant network edges and vertices, leading to a significantly reduced network model for accurate and efficient $K$ -terminal reliability analysis. The method is based on graph decomposition and reconstruction through articulation vertices. Empirical studies show that the proposed simplification method integrated with the binary-decision-diagrams based evaluation algorithm can significantly speed up $K$ -terminal reliability analysis of large real-life SCSs.

Fault Tree is an important model for reliability and safety assessment. The analysis performed on a fault tree can be either qualitative or quantitative. Both types of analyses may involve identifying minimal cut sets (MCS) or mincuts, each of which is a minimal combination of basic events (component failures) whose occurrence causes the top event (system failure) to occur. Considerable research efforts have been expended in the identification of MCSs for single-phased systems and networks. However, only little work is available for phased-mission systems (PMSs) and the existing method involves a large number of redundant computations in the MCS identification for eliminating redundancies across generated cut sets. This article proposes an MCS identification method based on binary decision diagrams (BDD) generated from the PMS fault tree using the backward ordering. By examining cut sets encoded by the generated BDD model, we identify two kinds of redundancies (inclusion relation-based and intra-implication relation-based) that prevent a cut set from being an MCS. Correspondingly, two BDD operations are developed for eliminating these two kinds of redundancies, contributing to correct and efficient MCS identification. As demonstrated through experiments on a highly-reliable distributed computing infrastructure PMS, the proposed MCS identification method is more efficient than the existing method.

Background: In recent years, several reports have tried to prove this connection between rs1800872 polymorphism in interleukin-10 and cervical cancer among different populations, but the results are debatable. Thus, we collected all the published literature and conducted an integrated meta-analysis, which provided better evidence-based medicine for the relationship between rs1800872 polymorphism in interleukin-10 and risk of cervical cancer. Methods: We systematically performed our search on PubMed, EMBASE, Web of Science, WanFang database, and CNKI for all papers related to this research, published up to August 1, 2020. Summary odds ratios (OR) with 95% confidence interval (95% CI) were calculated in allelic, homozygous, heterozygous, dominant, and recessive model to appraise the association. Results: The meta-analysis included 8 studies containing 1393 cervical cancer cases and 1307 controls. The aggregate data under heterozygous model and dominant inheritance model (OR = 0.66, 95% CI: 0.55--0.80) indicated a significant association between rs1800872 and the low risk of cervical cancer in the entire population. And the aggregated data under the dominant inheritance model shows that rs1800872 is significantly associated with the reduction in the risk of cervical tumors in the entire population. Conclusion: Our conclusion is that the AC/AA + AC variant of Rs1800872 indicates a protective effect in the development of cervical cancer.

The earth simulator is the most important testing equipment ground-based for the infrared earth sensor, and it is also a key component in the satellite controlling system. for three orbit heights 18000Km, 35786Km and 42000Km, in this paper we adopt a project of collimation and replaceable earth diaphragm and develop a high orbit collimation earth simulator. This simulator can afford three angles 15.19°, 17.46° and 30.42°, resulting simulating the earth on the ground which can be seen in out space by the satellite. In this paper we introduce the components, integer structure, and the earth's field angles testing method of the earth simulator in detail. Germanium collimation lens is the most important component in the earth simulator. According to the optical configuration parameter of Germanium collimation lens, we find the location and size of the earth diaphragm and the hot earth by theoretical analyses and optics calculation, which offer foundation of design in the study of the earth simulator. The earth angle is the index to scale the precision of earth simulator. We test the three angles by experiment and the results indicate that three angles errors are all less than ±0.05°.

The principal Epstein–Barr virus (EBV) oncoprotein, latent membrane protein 1 (LMP1) is strongly associated with nasopharyngeal carcinoma (NPC), a prevalent cancer in China. The epidermal growth factor receptor (EGFR) is important in carcinogenesis, as it is a ubiquitously expressed receptor tyrosine kinase. Signal transducer and activator of transcription 3 (STAT3) is a master transcriptional regulator in proliferation and apoptosis. Our previous study demonstrated that the nuclear EGFR could bind to the cyclin D1 promoter directly in the presence of LMP1, and the correlation between EGFR and STAT3 in NPC remains to be further explored. Here, we have shown that the interaction of EGFR and STAT3 increased in the nucleus in the presence of LMP1. LMP1 promoted both EGFR and STAT3 binding to the promoter region of cyclin D1, in turn, enhancing the promoter activity of cyclin D1. Furthermore, we demonstrated that both transcriptional activity and mRNA levels of cyclin D1 were decreased by small molecule interference of EGFR and STAT3 activity. These findings may provide a novel linkage between the EGFR and STAT3 signaling pathways and the activation of cyclin D1 by LMP1 in the carcinogenesis of NPC.

The incidence of osteoporosis continues to increase with progressively aging populations. The purpose of this study was to detect the effects of glucocorticoid (GC) treatment on bone mineral density (BMD), biomechanical strength and micro-architecture in cancellous and cortical bone in ovariectomized (OVX) rabbits. Twenty adult female New Zealand white rabbits were randomly divided into three groups. The OVX-GC group (n=8) received a bilateral ovariectomy first and then daily GC treatment (methylprednisolone sodium succinate, 1mg/kg/day) for 4 weeks beginning 2 weeks after ovariectomy treatment. The OVX group (n=4) received a bilateral ovariectomy without GC treatment. The sham group (n=8) only received the sham operation. BMD was determined prior to and 6 weeks after the operation in the spine. Six weeks after the operation, the animals were sacrificed, and cancellous bone specimens were harvested from the femoral condyle and lumbar vertebrae. Cortical bone specimens were obtained from the femoral midshaft. The femoral specimens were scanned for apparent BMD. All specimens were tested mechanically and analyzed by microcompute tomography (micro-CT). In cancellous bone, GC treatment resulted in significant decreases in BMD, bone biomechanical strength and micro-architecture parameters in lumbar vertebrae. Similar trends in BMD and micro-architectural changes were also observed in the femoral condyle in the OVX-GC group compared with the sham group. However, there was no significant decline in any parameter in either lumbar vertebrae or femoral condyle in the OVX group. Similarly, no significant difference was found in any parameter in cortical bone among the three groups. Thus, the 4-week GC treatment in OVX rabbits could result in a significant bone loss in cancellous bone but not in cortical bone. This model is comparable to the osteoporosis-related changes in humans. OVX alone was not sufficient to induce osteoporosis.

The significant performance-to-cost ratio advantage of clusters, combined with recent advances in middleware (programming environment) and networking technologies, has made them the single most popular and fastest growing platform for high performance computing in recent years. While the message passing interface (MPI) still dominates as a means of parallel programming in clusters, it is nevertheless desirable for programmers to program in a single address space, not only across a cluster but also among multiple, likely heterogeneous, clusters so as to significantly extend the computing power of a single cluster. In this paper we propose a distributed shared object (DSO) model based on a distributed hierarchical consistency model (DHCM) protocol for heterogeneous clusters. DHCM, inspired by but significantly improved over the local consistency, is designed to help maintain coherence and consistency in a DSO programming environment and to adapt to different levels of consistency. The notion of adaptive consistency is proposed and partially implemented to improve the efficiency in consistency control, and scalability is addressed as well through the hierarchical structure of the protocol design. We implemented this model purely in Java for portability and heterogeneity. The performance of DHCM is evaluated by executing the LU application chosen from the SPLASH-2 benchmark suite on a 128-node Linux cluster. The experimental results show that the protocol with a hierarchical structure significantly outperforms the protocol with a single-tier in terms of execution time, indicating higher scalability.

In this paper, we introduce I-MINDS (intelligent multiagent infrastructure for distributed system in education), an application based on multiagent system intelligence that enables students to actively participate in a virtual classroom rather than passively listening to lectures in a traditional virtual classroom. I-MINDS agents, equipped with intelligence of their own, and knowledge about other agents in the system, have the ability to collect information from and collaborate with other agents and serve their users (students and teachers alike) behind-the-scene effectively. Rather than being programmed to do a specific job, each agent has the ability to self-configure and learn based on the behavior of its users and its stored experience. To support the communication and collaboration process among the intelligent agents, we developed a hierarchical system that is more flexible and extensible.

In this paper, we describe an Intelligent Multiagent Infrastructure for Distributed Systems in Education (or I-MINDS) framework that applies an agent-oriented information system for education purposes. Our design employs distributed computing principles (i.e., Java Object Passing Interface and the Distributed Shared Object model) to facilitate cooperation among agents, data gathering and information dissemination, making the infrastructure portable, expandable and secure. Our motivations are to help teachers teach better and students learn better. A teacher, with the help of a teacher agent, is able to address important questions and survey the profile of each student (that is automatically maintained by the teacher agent). A student, with the help of a student agent, is able to collaborate with other students without having to form a buddies group him or herself. Thus, with the agents and a collaborative multiagent system, the I-MINDS framework is able to manage, process and share information intelligently.