Filling Ability and Passing Ability of Self-Consolidating Concrete

This paper reviews statistical models obtained from a composite factorial design study, which was carried out to determine the influence of three key parameters of mixture composition on filling ability and passing ability of self-consolidating concrete (SCC). This study was a part of the European project “Testing SCC”- GRD2-2000-30024. The parameters considered in this study were the dosages of water and high-range water-reducing admixture (HRWRA), and the volume of coarse aggregates. The responses of the derived statistical models were slump flow, T50 , T60, V-funnel flow time, Orimet flow time, and blocking ratio (L-box). The retention of these tests was also measured at 30 and 60 minutes after adding the first water. The models are valid for mixtures made with 188 to 208 L/m3 (317 to 350 lb/yd3) of water, 3.8 to 5.8 kg/m3 (570 to 970 mL/100 kg of binder) of HRWRA, and 220 to 360 L/m3 (5.97 to 9.76 ft3/yd3) of coarse aggregates. The utility of such models to optimize concrete mixtures and to achieve a good balance between filling ability and passing ability is discussed. Examples highlighting the usefulness of the models are presented using isoresponse surfaces to demonstrate single and coupled effects of mixture parameters on slump flow, T50 , T60 , V-funnel flow time, Orimet flow time, and blocking ratio. The paper also illustrates the various trade-offs between the mixture parameters on the derived responses that affected the filling and the passing ability.

Mature DC from skin and skin-draining LN retain the ability to acquire and efficiently present targeted antigen.

Skin-draining LN contain several phenotypically distinguishable DC populations, which may be immature or mature. Mature DC are generally considered to have lost the capacity to acquire and present newly encountered Ag. Using antibody-opsonized liposomes as Ag carriers, we show that mature DC purified from skin explants are able to efficiently capture liposomes, process Ag encapsulated within them and activate Ag-specific CD4(+) T cells. Explant DC from mice with Langerhans cells (LC) expressing the primate diphtheria toxin receptor that were exposed to diphtheria toxin in vivo presented Ag as well as explant DC from wild-type mice, indicating that LC are not required and dermal DC are probably responsible for this presentation. We further show that all DC subtypes from LN that capture opsonized Ag are capable of cross-presenting it to CD8(+) T cells. Induction of additional maturation in vivo by LPS or treatment with double-stranded RNA did not alter the Ag presentation capacity of the skin or LN DC subtypes. These results suggest that mature DC present in skin-draining LN may play an important role in the induction of primary and/or secondary immune responses against Ag delivered to the LN that they take up by receptor-mediated endocytosis.

Willingness to Pay for Rural Landscape Improvements: Combining Mixed Logit and Random-Effects Models

This paper reports the findings from a discrete-choice experiment designed to estimate the economic benefits associated with rural landscape improvements in Ireland. Using a mixed logit model, the panel nature of the dataset is exploited to retrieve willingness-to-pay values for every individual in the sample. This departs from customary approaches in which the willingness-to-pay estimates are normally expressed as measures of central tendency of an a priori distribution. Random-effects models for panel data are subsequently used to identify the determinants of the individual-specific willingness-to-pay estimates. In comparison with the standard methods used to incorporate individual-specific variables into the analysis of discrete-choice experiments, the analytical approach outlined in this paper is shown to add considerable explanatory power to the welfare estimates.

Combining multiple prioritized knowledge bases by negotiation.

Recently, several belief negotiation models have been introduced to deal with the problem of belief merging. A negotiation model usually consists of two functions: a negotiation function and a weakening function. A negotiation function is defined to choose the weakest sources and these sources will weaken their point of view using a weakening function. However, the currently available belief negotiation models are based on classical logic, which makes them difficult to define weakening functions. In this paper, we define a prioritized belief negotiation model in the framework of possibilistic logic. The priority between formulae provides us with important information to decide which beliefs should be discarded. The problem of merging uncertain information from different sources is then solved by two steps. First, beliefs in the original knowledge bases will be weakened to resolve inconsistencies among them. This step is based on a prioritized belief negotiation model. Second, the knowledge bases obtained by the first step are combined using a conjunctive operator which may have a reinforcement effect in possibilistic logic.

Identifying the influence of geology, land use, and anthropogenic activities on riverine sulfate on a watershed scale by combining hydrometric, chemical and isotopic approaches

Throughout the last few decades, sulfate concentrations in streamwater have received considerable attention due to their dominant role in anthropogenic acidification of surface waters. The objectives of this study conducted in the Oldman River Basin in Alberta (Canada) were to determine the influence of geology, land use and anthropogenic activities on sources, concentrations and fluxes of riverine sulfate on a watershed scale. This was achieved by combining hydrological, chemical and isotopic techniques. Surface water samples were collected from the main stem and tributaries of the Oldman River on a monthly basis between December 2000 and March 2003 and analyzed for chemical and isotopic compositions. At a given sampling site, sulfate sources were primarily dependent on geology and did not vary with time or flow condition. With increasing flow distance a gradual shift from ?34S values > 10 ‰ and ?18O values > 0 ‰ of riverine sulfate indicating evaporite dissolution and soil-derived sulfate in the predominantly forested headwaters, to negative ?34S and ?18O values suggested that sulfide oxidation was the predominant sulfate source in the agriculturally used downstream part of the watershed. Significant increases in sulfate concentrations and fluxes with downstream distance were observed, and were attributed to anthropogenically enhanced sulfide oxidation due to the presence of an extensive irrigation drainage network with seasonally varying water levels. Sulfate-S exports in an artificially drained subbasin (64 kg S/ha/yr) were found to exceed those in a naturally drained subbasin (4 kg S/ha/yr) by an order of magnitude. Our dataset suggests that the naturally occurring process of sulfide oxidation has been enhanced in the Oldman River Basin by the presence of an extensive network of drainage and irrigation canals.

A comprehensive comparison between generalized incidence calculus and Dempster-Shafer theory of evidence.

Dealing with uncertainty problems in intelligent systems has attracted a lot of attention in the AI community. Quite a few techniques have been proposed. Among them, the Dempster-Shafer theory of evidence (DS theory) has been widely appreciated. In DS theory, Dempster's combination rule plays a major role. However, it has been pointed out that the application domains of the rule are rather limited and the application of the theory sometimes gives unexpected results. We have previously explored the problem with Dempster's combination rule and proposed an alternative combination mechanism in generalized incidence calculus. In this paper we give a comprehensive comparison between generalized incidence calculus and the Dempster-Shafer theory of evidence. We first prove that these two theories have the same ability in representing evidence and combining DS-independent evidence. We then show that the new approach can deal with some dependent situations while Dempster's combination rule cannot. Various examples in the paper show the ways of using generalized incidence calculus in expert systems.

Adding value to renewables: a one pot process combining microbial cells and hydrogen transfer catalysis to utilise waste glycerol from biodiesel production

Waste glycerol was converted to secondary amines in a one pot reaction, using Clostridium butyricum and catalytic hydrogen transfer-mediated amination.