Nanofibers (PU and PAN) and nanoparticles (Nanoclay and MWNTs) simultaneous effects on polyurethane foam sound absorption

In this research, simultaneous effects of polyacrylonitrile (PAN) and polyurethane (PU) nanofibers, multi wall carbon nanotubes (MWNTs) and nanoclay incorporation on sound absorption behavior of polyurethane foam were studied. The most important parameters such as nanoparticles content, number and mass per unit area of nanofiber layers and foam thickness were chosen and their influences on sound absorption in a wide band of frequencies were investigated. Applying of both nanoparticles gave rise to considerable improvement in PU foam sound absorption, however in case of MWNTs more satisfied results were observed. Sound absorption tests of simultaneous incorporation of MWNTs and nanoclay showed that the optimized result can be obtained at moderate to high MWNTs percents (0.1–0.15 wt.%) and low percents of nanoclay (0.5 wt.%). On the other hand, by adding PAN or PU nanofiber layers within the PU foam structure, superior sound absorption was achieved. Upper sound absorption by increasing the numbers of nanofiber layers was obtained. Incorporation of PAN nanofiber layers showed a better effect at high mass per unit area (5 g/m²), however the higher sound absorption in case of PU nanofiber layers was observed at low mass per unit area (1 g/m²).     

Myocardial blood flow quantification from MRI by deconvolution using an exponential approximation basis

We have evaluated the use of deconvolution using an exponential approximation basis for the quantification of myocardial blood flow from perfusion cardiovascular magnetic resonance. Our experiments, based on simulated signal intensity curves, phantom acquisitions, and clinical image data, indicate that exponential deconvolution allows for accurate quantification of myocardial blood flow. Together with automated respiratory motion correction myocardial contour delineation, the exponential deconvolution enables efficient and reproducible quantification of myocardial blood flow in clinical routine.     

View merging in the presence of incompleteness and inconsistency

View merging, also called view integration, is a key problem in conceptual modeling. Large models are often constructed and accessed by manipulating individual views, but it is important to be able to consolidate a set of views to gain a unified perspective, to understand interactions between views, or to perform various types of analysis. View merging is complicated by incompleteness and inconsistency: Stakeholders often have varying degrees of confidence about their statements. Their views capture different but overlapping aspects of a problem, and may have discrepancies over the terminology being used, the concepts being modeled, or how these concepts should be structured. Once views are merged, it is important to be able to trace the elements of the merged view back to their sources and to the merge assumptions related to them. In this paper, we present a framework for merging incomplete and inconsistent graph-based views. We introduce a formalism, called annotated graphs, with a built-in annotation scheme for modeling incompleteness and inconsistency. We show how structure-preserving maps can be employed to express the relationships between disparate views modeled as annotated graphs, and provide a general algorithm for merging views with arbitrary interconnections. We provide a systematic way to generate and represent the traceability information required for tracing the merged view elements back to their sources, and to the merge assumptions giving rise to the elements.

FUZZY TRUST AGGREGATION AND PERSONALIZED TRUST INFERENCE IN VIRTUAL SOCIAL NETWORKS

Virtual marketplaces on the Web provide people with great facilities to buy and sell goods similar to conventional markets. In traditional business, reputation is subjectively built for known persons and companies as the deals are made in the course of time. As it is important to do business with trustful individuals and companies, there is a need to survive the reputation concept in virtual markets. Auction sites generally employ reputation systems based on feedbacks that provide a global view to a cyber dealer. In contrast to global trust, people usually infer their personal trust about someone whose reputation is completely or partially unknown by asking their trusted friends. Personal reputation is what makes a person trusted for some people and untrusted for others. There should be a facility for users in a virtual market to specify how much they trust a friend and also a mechanism that infers the trust of a user to another user who is not directly a friend of her. There are two main issues that should be addressed in trust inference. First, the trust modeling and aggregation problem needs to be challenged. Second, algorithms should be introduced to find and select the best paths among the existing trust paths from a source to a sink. First, as trust to a person can be stated more naturally using linguistic expressions, this work suggests employing linguistic terms for trust specification. To this end, corresponding fuzzy sets are defined for trust linguistic terms and a fuzzy trust aggregation method is also proposed. Comparing the fuzzy aggregation method to the existing aggregation methods shows superiority of fuzzy approach especially at aggregating contradictory information. Second, this paper proposes an incremental trust inference algorithm. The results show improvement in preciseness of inference for the proposed inference algorithm over the existing and recently proposed algorithm named TidalTrust.     

Supercritical Fluid Chromatography of Myrosinase Reaction Products in Ground Yellow Mustard Seed Oil

ABSTRACT: Escherichia coli O157:H7 can survive the dry fermented sausage manufacturing process. Compounds generated by enzymatic hydrolysis of glucosinolates present in ground mustard have shown potential antibacterial properties against E. coli O157:H7. In the present study, supercritical fluid chromatography (SFC) was used to investigate degradation products of 4-hydroxybenzyl glucosinolate (sinalbin), the major glucosinolate present in yellow mustard seed. Using SFC the concentration of the reactive component, 4-hydroxybenzyl isothiocyanate (PHBITC) was measured during the hydrolysis of sinalbin with myrosinase while imposing the temperature and pH regimen used for the fermentation phase of dry fermented sausage production. The PHBITC concentration grew to a maximum after 7 h and decreased rapidly. The concentration of 4-hydroxybenzyl alcohol increased rapidly to reach a maximum at 31 h and stayed at that level. The concentration of 4-hydroxybenzyl cyanate increased up to 24 h, then decreased to 65% of its maximum, and stayed constant. The stability of 4-hydroxybenzyl isothiocyanate in the presence of maltodextrin in this system was investigated. It was concluded that the major PHBITC loss in the mixture of the oil with maltodextrin occurred within the first 4 d of its storage. Practical Application: During the work 4-hydroxybenzyl isothiocyanate (PHBITC) was measured during the hydrolysis of sinalbin with myrosinase while imposing the temperature and pH regimen used for the fermentation phase of dry fermented sausage production. The results on PHBITC stability in maltodextrin presented provide precautionary information on the limited ability of this material to afford stability of PHBITC expected.