Low-temperature sol-gel preparation of ordered nanoparticles of tungsten carbide/oxide

Tungsten carbide/oxide particles have been prepared by the gel precipitation of tungstic acid in the presence of an organic gelling agent [10% ammonium poly(acrylic acid) in water, supplied by Ciba Specialty Chemicals]. The feed solution; a homogeneous mixture of sodium tungstate and ammonium poly(acrylic acid) in water, was dropped from a 1-mm jet into hydrochloric acid saturated hexanol/concentrated hydrochloric acid to give particles of a mixture of tungstic acid and poly(acrylic acid), which, after drying in air at 100 degrees C and heating to 900 degrees C in argon for 2 h, followed by heating in carbon dioxide for a further 2 h and cooling, gives a mixture of WO, WC, and a trace of NaxWO3, with the carbon for the formation of WC being provided by the thermal carbonization of poly(acrylic acid). The pyrolyzed product is friable and easily broken down in a pestle and mortar to a fine powder or by ultrasonics, in water, to form a stable colloid. The temperature of carbide formation by this process is significantly lower (900 degrees C) than that reported for the commercial preparation of tungsten carbide, typically > 1400 degrees C. In addition, the need for prolonged grinding of the constituents is obviated because the reacting moieties are already in intimate contact on a molecular basis. X-ray diffraction, particle sizing, transmission electron microscopy, surface area, and pore size distribution studies have been carried out, and possible uses are suggested. A flow diagram for the process is described.

Pyrolysis of polymer-derived carbons in the formation of graphitizing carbons and nanoparticles of zirconia

Carbons have been prepared by the low-temperature pyrolysis, under argon, of a number of long-chain polymers. We have found that the resistivity (Omega cm(-1)) varies considerably with the temperature of pyrolysis; thus, for ammonium polyacrylate, the resistivity of that pyrolyzed at 600 degrees C is 9.7 x 10(4) Omega cm(-1) whereas that pyrolyzed at 1000 degrees C is ca. 3 Omega cm(-1). A similar situation arises for the other polymers studied (including radiolyzed cross-linked polyacrylamide). All those pyrolyzed at 600 degrees C had a resistivity of > 1 x 10(6) Omega cm(-1), whereas those pyrolyzed at 1000 degrees C had a resistivity of ca. 3-5 Omega cm(-1). A notable exception was that of unirradiated polyacrylamide, where the resistivity remained at > 1 x 10(6) Omega cm(-1) over the range of temperatures studied. The decrease of resistivity with increase of temperature of pyrolysis has been related to the formation of glassy carbon. Nanoparticles (4 nm) of tetragonal zirconia were formed when zirconium polyacrylate was pyrolyzed under similar conditions.

Vertical distribution, size and composition of the weed seedbank under various tillage and herbicide treatments in a sequence of industrial crops

Investigations were conducted during the 2003, 2004 and 2005 growing seasons in northern Greece to evaluate effects of tillage regime (mouldboard plough, chisel plough and rotary tiller), cropping sequence (continuous cotton, cotton-sugar beet rotation and continuous tobacco) and herbicide treatment on weed seedbank dynamics. Amaranthus spp. and Portulaca oleracea were the most abundant species, ranging from 76% to 89% of total weed seeds found in 0-15 and 15-30 cm soil depths during the 3 years. With the mouldboard plough, 48% and 52% of the weed seedbank was found in the 0-15 and 15-30 cm soil horizons, while approximately 60% was concentrated in the upper 15 cm soil horizon for chisel plough and rotary tillage. Mouldboard ploughing significantly buried more Echinochloa crus-galli seeds in the 15-30 cm soil horizon compared with the other tillage regimes. Total seedbank (0-30 cm) of P. oleracea was significantly reduced in cotton-sugar beet rotation compared with cotton and tobacco monocultures, while the opposite occurred for E. crus-galli. Total seed densities of most annual broad-leaved weed species (Amaranthus spp., P. oleracea, Solanum nigrum) and E. crus-galli were lower in herbicide treated than in untreated plots. The results suggest that in light textured soils, conventional tillage with herbicide use gradually reduces seed density of small seeded weed species in the top 15 cm over several years. In contrast, crop rotation with the early established sugar beet favours spring-germinating grass weed species, but also prevents establishment of summer-germinating weed species by the early developing crop canopy.

A knowledge-driven management approach to environmental-conscious construction

This paper aims to introduce a knowledge-based managemental prototype entitled Eþ for environmental-conscious construction relied on an integration of current environmental management tools in construction area. The overall objective of developing the Eþ prototype is to facilitate selectively reusing the retrievable knowledge in construction engineering and management areas assembled from previous projects for the best practice in environmental-conscious construction. The methodologies adopted in previous and ongoing research related to the development of the Eþ belong to the operations research area and the information technology area, including literature review, questionnaire survey and interview, statistical analysis, system analysis and development, experimental research and simulation, and so on. The content presented in this paper includes an advanced Eþ prototype, a comprehensive review of environmental management tools integrated to the Eþ prototype, and an experimental case study of the implementation of the Eþ prototype. It is expected that the adoption and implementation of the Eþ prototype can effectively facilitate contractors to improve their environmental performance in the lifecycle of projectbased construction and to reduce adverse environmental impacts due to the deployment of various engineering and management processes at each construction stage.

Ontology modeling for generation of clinical pathways

Purpose: Increasing costs of health care, fuelled by demand for high quality, cost-effective healthcare has drove hospitals to streamline their patient care delivery systems. One such systematic approach is the adaptation of Clinical Pathways (CP) as a tool to increase the quality of healthcare delivery. However, most organizations still rely on are paper-based pathway guidelines or specifications, which have limitations in process management and as a result can influence patient safety outcomes. In this paper, we present a method for generating clinical pathways based on organizational semiotics by capturing knowledge from syntactic, semantic and pragmatic to social level. Design/methodology/approach: The proposed modeling approach to generation of CPs adopts organizational semiotics and enables the generation of semantically rich representation of CP knowledge. Semantic Analysis Method (SAM) is applied to explicitly represent the semantics of the concepts, their relationships and patterns of behavior in terms of an ontology chart. Norm Analysis Method (NAM) is adopted to identify and formally specify patterns of behavior and rules that govern the actions identified on the ontology chart. Information collected during semantic and norm analysis is integrated to guide the generation of CPs using best practice represented in BPMN thus enabling the automation of CP. Findings: This research confirms the necessity of taking into consideration social aspects in designing information systems and automating CP. The complexity of healthcare processes can be best tackled by analyzing stakeholders, which we treat as social agents, their goals and patterns of action within the agent network. Originality/value: The current modeling methods describe CPs from a structural aspect comprising activities, properties and interrelationships. However, these methods lack a mechanism to describe possible patterns of human behavior and the conditions under which the behavior will occur. To overcome this weakness, a semiotic approach to generation of clinical pathway is introduced. The CP generated from SAM together with norms will enrich the knowledge representation of the domain through ontology modeling, which allows the recognition of human responsibilities and obligations and more importantly, the ultimate power of decision making in exceptional circumstances.

A design of evaluation method for SaaS in cloud computing

Purpose: This paper aims to design an evaluation method that enables an organization to assess its current IT landscape and provide readiness assessment prior to Software as a Service (SaaS) adoption. Design/methodology/approach: The research employs a mixed of quantitative and qualitative approaches for conducting an IT application assessment. Quantitative data such as end user’s feedback on the IT applications contribute to the technical impact on efficiency and productivity. Qualitative data such as business domain, business services and IT application cost drivers are used to determine the business value of the IT applications in an organization. Findings: The assessment of IT applications leads to decisions on suitability of each IT application that can be migrated to cloud environment. Research limitations/implications: The evaluation of how a particular IT application impacts on a business service is done based on the logical interpretation. Data mining method is suggested in order to derive the patterns of the IT application capabilities. Practical implications: This method has been applied in a local council in UK. This helps the council to decide the future status of the IT applications for cost saving purpose.

A semiotic approach of multi-agent simulation for policy evaluation

Nowadays the changing environment becomes the main challenge for most of organizations, since they have to evaluate proper policies to adapt to the environment. In this paper, we propose a multi-agent simulation method to evaluate policies based on complex adaptive system theory. Furthermore, we propose a semiotic EDA (Epistemic, Deontic, Axiological) agent model to simulate agent's behavior in the system by incorporating the social norms reflecting the policy. A case study is also provided to validate our approach. Our research present better adaptability and validity than the qualitative analysis and experiment approach and the semiotic agent model provides high creditability to simulate agents' behavior.

Joint importance of multistate systems

Importance measures in reliability engineering are used to identify weak areas of a system and signify the roles of components in either causing or contributing to proper functioning of the system. Traditional importance measures for multistate systems mainly concern reliability importance of an individual component and seldom consider the utility performance of the systems. This paper extends the joint importance concepts of two components from the binary system case to the multistate system case. A joint structural importance and a joint reliability importance are defined on the basis of the performance utility of the system. The joint structural importance measures the relationship of two components when the reliabilities of components are not available. The joint reliability importance is inferred when the reliabilities of the components are given. The properties of the importance measures are also investigated. A case study for an offshore electrical power generation system is given.

Connectivity measures for internet topologies on the level of autonomous systems

Classical measures of network connectivity are the number of disjoint paths between a pair of nodes and the size of a minimum cut. For standard graphs, these measures can be computed efficiently using network flow techniques. However, in the Internet on the level of autonomous systems (ASs), referred to as AS-level Internet, routing policies impose restrictions on the paths that traffic can take in the network. These restrictions can be captured by the valley-free path model, which assumes a special directed graph model in which edge types represent relationships between ASs. We consider the adaptation of the classical connectivity measures to the valley-free path model, where it is -hard to compute them. Our first main contribution consists of presenting algorithms for the computation of disjoint paths, and minimum cuts, in the valley-free path model. These algorithms are useful for ASs that want to evaluate different options for selecting upstream providers to improve the robustness of their connection to the Internet. Our second main contribution is an experimental evaluation of our algorithms on four types of directed graph models of the AS-level Internet produced by different inference algorithms. Most importantly, the evaluation shows that our algorithms are able to compute optimal solutions to instances of realistic size of the connectivity problems in the valley-free path model in reasonable time. Furthermore, our experimental results provide information about the characteristics of the directed graph models of the AS-level Internet produced by different inference algorithms. It turns out that (i) we can quantify the difference between the undirected AS-level topology and the directed graph models with respect to fundamental connectivity measures, and (ii) the different inference algorithms yield topologies that are similar with respect to connectivity and are different with respect to the types of paths that exist between pairs of ASs.