Ultrastrong conductive in situ composite composed of nanodiamond incoherently embedded in disordered multilayer graphene

Traditional ceramics or metals cannot simultaneously achieve ultrahigh strength and high electrical conductivity. The elemental carbon can form a variety of allotropes with entirely different physical properties, providing versatility for tuning mechanical and electrical properties in a wide range. Here, by precisely controlling the extent of transformation of amorphous carbon into diamond within a narrow temperature–pressure range, we synthesize an in situ composite consisting of ultrafine nanodiamond homogeneously dispersed in disordered multilayer graphene with incoherent interfaces, which demonstrates a Knoop hardness of up to ~53 GPa, a compressive strength of up to ~54 GPa and an electrical conductivity of 670–1,240 S m(–1) at room temperature. With atomically resolving interface structures and molecular dynamics simulations, we reveal that amorphous carbon transforms into diamond through a nucleation process via a local rearrangement of carbon atoms and diffusion-driven growth, different from the transformation of graphite into diamond. The complex bonding between the diamond-like and graphite-like components greatly improves the mechanical properties of the composite. This superhard, ultrastrong, conductive elemental carbon composite has comprehensive properties that are superior to those of the known conductive ceramics and C/C composites. The intermediate hybridization state at the interfaces also provides insights into the amorphous-to-crystalline phase transition of carbon

Effects of Astragalus Polysaccharide on Immune Responses of Porcine PBMC Stimulated with PRRSV or CSFV

BACKGROUND: Astragalus polysaccharide (APS) has been used as an immunomodulator that can enhance immune responses, whereas the immunomodulatory effects of APS on porcine peripheral blood mononuclear cells (PBMCs) exposed to porcine reproductive and respiratory syndrome virus (PRRSV) and classical swine fever virus (CSFV) have not been investigated. METHODOLOGY/PRINCIPAL FINDINGS: Porcine PBMCs were cultured in complete RPMI media in the presence of the R98-strain of PRRSV (5×10(4) TCID(50)/ml) or C-strain of CSFV (10(3) TCID(50)/ml) with or without APS. The expression of mRNA for CD28, cytotoxic T-lymphocyte antigen 4 (CTLA-4), transforming growth factor-β (TGF-β), interleukin 2 (IL-2) and IL-10 was assayed by TaqMan real-time RT-PCR. The expression of mRNA for CD28 and CTLA-4 increased at 24 h after stimulation of PBMCs with CSFV and the increased production of CTLA-4 was confirmed by western blot analysis, whereas the increases were inhibited by the addition of APS. In addition, APS alone upregulated IL-2 and TGF-β mRNA expression in PBMCs and the addition of APS had the capacity to prevent a further increase in IL-2 mRNA expression in PBMCs during CSFV or PRRSV infection, but had no effect on TGF-β mRNA expression. The production of tumor necrosis factor-alpha (TNF-α) increased at 12 h after stimulation with PRRSV or CSFV, but not with PRRSV plus APS or CSFV plus APS, whereas the addition of APS to PBMCs infected with PRRSV or CSFV promoted IL-10 mRNA expression. CONCLUSIONS: We suggested that APS had immunomodulatory effects on cells exposed to PRRSV or CSFV. It might be that APS via different mechanisms affects the activities of immune cells during either PRRSV or CSFV infection. This possibility warrants further studies to evaluate whether APS would be an effective adjuvant in vaccines against PRRSV or CSFV

Spatial-Temporal Pattern of Human-Induced Land Degradation in Northern China in the Past 3 Decades—RESTREND Approach

Land degradation is one of the world’s most serious environmental issues. Human activities play an important role in it. Therefore, human-induced land degradation monitoring is of crucial scientific significance in revealing the evolution of land degradation and guiding its governance. Based on the residual trend (RESTREND) approach and using Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) 3g and monthly precipitation as data sources, a quantitative evaluation is conducted on the conditions of human-induced land degradation during 1982–2012 in northern China. The results indicate that (1) the “optimal cumulative precipitation-NDVImax” regression model constructed herein can improve the capability of recognizing human-induced land degradation of arid and semiarid areas in the RESTREND approach. Moreover, long time-series NDVI and precipitation data may reduce the uncertainty of quantifying human-induced land degradation. (2) In the past 3 decades, northern China has experienced three stages of human-induced land degradation, i.e., rapid development, overall reversal with local development, and continuous reversion. Human-induced land degradation in the agro-pastoral ecotone of northern China has shown a rapid restoration trend since the 1990s. (3) It is believed that the dominant factor of land degradation has a significant spatial-temporal scale effect and spatial heterogeneity. Therefore, concrete issues should be specifically analyzed to improve our understanding of land degradation development and reversal, the spatial-temporal pattern and the driving forces of land degradation in the past 3 decades in northern China. Climate change may be the main driving force of land degradation. However, the influence of human activities on the development and reversal of land degradation in small areas and in a short time is more remarkable

Performance Analysis of WHIPS Incremental Maintenance

Incremental maintenance incorporates new changes automatically and continuously into a data warehouse, and seems to be the best maintenance solution for very large warehouses. However, the performance of incremental maintenance algorithms is not well understood, and commercial incremental maintenance systems are still not widely available. In this paper, we study the performance of WHIPS, a prototype system developed at Stanford focusing on warehouse maintenance. We examine the efficiency of change propagation and study factors that determine the efficiency. We also compare the relative performance of different warehouse maintenance techniques. 1 Introduction A data warehouse stores integrated data from multiple, often distributed and autonomous data sources, and is typically used for decision support. One of the major challenges is to correctly and efficiently update the warehouse as the source data changes. There are basically two categories of techniques for this: refreshing and in..

Self-Maintainability of Graph Structured Views

Materialized views need to be maintained in response to changes of base data. It is desirable to do this maintenance without accessing base data, to reduce overhead and contention for base data. In this paper we study the self-maintenance problem for materialized views defined over a graph-structured database (GSDB). We formally define the notion of self-maintainability for such views, and show how to check if a base update can be incorporated into a view without referencing base data. We also characterize views that are always self-maintainable, and compute the auxiliary information that needs to be stored in order to make a view self-maintainable. 1 Introduction Materialized views copy selected or summarized data of interest to improve query performance and data availability. They are especially useful when the query site is separate from the base data, e.g., views cached for Web browsing, or stored in a data warehouse. In such an environment, materialized views can be stored close ..

The Strobe Algorithms for Multi-Source Warehouse Consistency

A warehouse is a data repository containing integrated information for efficient querying and analysis. Maintaining the consistency of warehouse data is challenging, especially if the data sources are autonomous and views of the data at the warehouse span multiple sources. Transactions containing multiple updates at one or more sources, e.g., batch updates, complicate the consistency problem. In this paper we identify and discuss three fundamental transaction processing scenarios for data warehousing. We define four levels of consistency for warehouse data and present a new family of algorithms, the Strobe family, that maintain consistency as the warehouse is updated, under the various warehousing scenarios. All of the algorithms are incremental and can handle a continuous and overlapping stream of updates from the sources. Our implementation shows that the algorithms are practical and realistic choices for a wide variety of update scenarios. 1 Introduction A data warehouse is a rep..