Physical properties of ethylene vinyl acetate copolymer (EVA)/natural rubber (NR) blend based foam

In this study an attempt was made to improve the rebound resilience and to decrease the density of ethylene‐vinyl acetate copolymer (EVA) foam. For this purpose, EVA was blended with natural rubber (NR), and EVA/NR blends were foamed at 155°C, 160°C, and 165°C. To investigate the correlation between crosslinking behavior and physical properties of foams, crosslinking behavior of EVA/NR blends was monitored. The physical properties of the foams were then measured as a function of foaming temperatures and blend compositions: 165°C was found to be the optimal temperature for a crosslinking of EVA/NR foam. As a result, the density of EVA/NR blend foamed at 165°C was found to be the lowest. EVA/NR (90/10) blend, foamed at 165°C, showed lower density, better rebound resilience, and greater tear strength than EVA foam. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 94: 2212–2216, 2004     

Robust fault detection of turbofan engines subject to adaptive controllers via a Total Measurable Fault Information Residual (ToMFIR) technique

This paper provides a new design of robust fault detection for turbofan engines with adaptive controllers. The critical issue is that the adaptive controllers can depress the faulty effects such that the actual system outputs remain the pre-specified values, making it difficult to detect faults/failures. To solve this problem, a Total Measurable Fault Information Residual (ToMFIR) technique with the aid of system transformation is adopted to detect faults in turbofan engines with adaptive controllers. This design is a ToMFIR-redundancy-based robust fault detection. The ToMFIR is first introduced and existing results are also summarized. The Detailed design process of the ToMFIRs is presented and a turbofan engine model is simulated to verify the effectiveness of the proposed ToMFIR-based fault-detection strategy.     

The heat treatment and the gelation are strong determinants of the kinetics of milk proteins digestion and of the peripheral availability of amino acids

This study aimed to determine the kinetics of milk protein digestion and amino acid absorption after ingestion of four dairy matrices by six minipigs: unheated or heated skim milk and corresponding rennet gels. Digestive contents and plasma samples were collected over a 7 h-period after meal ingestion. Gelation of milk slowed down the outflow of the meal from the stomach and the subsequent absorption of amino acids, and decreased their bioavailability in peripheral blood. The gelled rennet matrices also led to low levels of milk proteins at the duodenum. Caseins and β-lactoglobulin, respectively, were sensitive and resistant to hydrolysis in the stomach with the unheated matrices, but showed similar digestion with the heated matrices, with a heat-induced susceptibility to hydrolysis for β-lactoglobulin. These results suggest a significant influence of the meal microstructure (resulting from heat treatment) and macrostructure (resulting from gelation process) on the different steps of milk proteins digestion.     

Kinetics of growth and inactivation of Salmonella enterica serotype Typhimurium DT104 in pasteurised liquid egg products

The potential impact of post-pasteurisation contamination of liquid egg products with the multi-antibiotic resistant pathogen Salmonella enterica serotype Typhimurium definitive type 104 (DT104) was assessed by determining the viability of this bacterium in whole egg, albumen and 10% w/w sugared and salted yolk incubated at 4–42 °C. Results indicated that populations of S. Typhimurium DT104 were slowly inactivated in all four products when stored at 4 °C. However, based on the typical shelf-lives of cold-stored liquid egg, less than 0.6 log-kill would be achieved in those products prior to their use. Incubation at temperatures pertaining to abuse situations (10, 15, 20 and 25 °C) revealed an increasing potential for growth of S. Typhimurium DT104 in whole egg, albumen and sugared yolk, as indicated by trends in growth rate, lag duration and maximum population density. At even higher temperatures (30, 37 and 42 °C), growth rates of S. Typhimurium DT104 in whole egg and sugared yolk continued to increase. The same was true for S. Typhimurium DT104 in albumen except that growth was not observed at 42 °C and instead populations were inactivated within 30 h. At no temperature tested was S. Typhimurium DT104 able to grow in salted yolk. The influence of these growth and inactivation patterns on the risk of salmonellosis in relation to product type and storage temperature is discussed.     

Intensification of Freeze-Drying Rate of Bacillus subtilis MTCC 2396 Using Tungsten Halogen Radiation: Optimization of Moisture Content and α-Amylase Activity

A novel freeze-drying protocol has been explored to render fast and cost-effective freeze drying of hyperamylase producing Bacillus subtilis MTCC2396 employing a tungsten halogen lamp radiator (THLR) as a heat source. Response surface methodology assessed the maximum reduction in moisture content (96.07%) and minimum reduction in α-amylase (EC 3.2.1.1) activity (1.02%) in 4 h drying time at 42.5°C radiation temperature. α-amylase activity (0.046 U) and final moisture content (3.93%) of the optimally freeze-dried bacterial strain appeared satisfactory. The freeze-drying time using THLR (4 h) is remarkably lower compared to that under a conventional conductive plate heater (CPH) (10 h) at otherwise identical conditions. The higher effective moisture diffusivity of 0.0052 to 0.0078 m ²/s under THLR compared to 0.00084 to 0.0015 m ²/s under CPH (corresponding to 20–50°C) advocated the superiority of the THLR heating protocol. The higher efficacy of THLR was also evidenced through lower activation energy (8.42 kJ/mol) of moisture diffusion compared to that (12.051 kJ/mol) of CPH. The optimally freeze-dried bacteria demonstrated the same growth rate in addition to exhibiting excellent retention of bioremedial (Hg²⁺ removal) activity to that of the control.     

Exposure influences expressive timing judgments in music.

This study is concerned with the question whether, and to what extent, listeners' previous exposure to music in everyday life, and expertise as a result of formal musical training, play a role in making expressive timing judgments in music. This was investigated by using a Web-based listening experiment in which listeners with a wide range of musical backgrounds were asked to compare 2 recordings of the same composition (15 pairs, grouped in 3 musical genres), 1 of which was tempo-transformed (manipulating the expressive timing). The results show that expressive timing judgments are not so much influenced by expertise levels, as is suggested by the expertise hypothesis, but by exposure to a certain musical idiom, as is suggested by the exposure hypothesis. As such, the current study provides evidence for the idea that some musical capabilities are acquired through mere exposure to music, and that these abilities are more likely enhanced by active listening (exposure) than by formal musical training (expertise). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A framework for mining interesting high utility patterns with a strong frequency affinity

High utility pattern (HUP) mining is one of the most important research issues in data mining. Although HUP mining extracts important knowledge from databases, it requires long calculations and multiple database scans. Therefore, HUP mining is often unsuitable for real-time data processing schemes such as data streams. Furthermore, many HUPs may be unimportant due to the poor correlations among the items inside of them. Hence,the fast discovery of fewer but more important HUPs would be very useful in many practical domains. In this paper, we propose a novel framework to introduce a very useful measure, called frequency affinity, among the items in a HUP and the concept of interesting HUP with a strong frequency affinity for the fast discovery of more applicable knowledge. Moreover, we propose a new tree structure, utility tree based on frequency affinity (UTFA), and a novel algorithm, high utility interesting pattern mining (HUIPM), for single-pass mining of HUIPs from a database. Our approach mines fewer but more valuable HUPs, significantly reduces the overall runtime of existing HUP mining algorithms and is applicable to real-time data processing. Extensive performance analyses show that the proposed HUIPM algorithm is very efficient and scalable for interesting HUP mining with a strong frequency affinity.     

Prediction of Polymer Wear—An Analytical Model and Experimental Validation

Because of its industrial relevance, wear of engineering polymers has been studied extensively both experimentally and theoretically. The wear mechanism of polymers is complex due to the influence of numerous parameters and it has long been realized that a predicting tool for wear of polymers in dry and lubricated sliding is of practical importance. Polymer wear models hitherto have been largely done by fitting the experimental data to an empirical equation and some major contributions have been made by a number of authors in this area. However, a more fundamental approach would be to analyze the experimental evidence collectively on the basis of the variables involved and the mechanisms leading to particle detachment. Although some progress has been made in this direction, a need exists to consolidate the major experimental findings in order to develop a comprehensive analytical wear model. The present work attempts to develop such a wear model and validate the proposed model experimentally. The wear equations are presented in two groups, one representing primarily abrasive wear and the other the fatigue mechanism, since the two mechanisms operate in distinct roughness ranges. Each group consists of four equations representing different contact speed and temperature ranges. The results indicate that the surface forces dominate in the low roughness range while at the higher roughness ranges abrasive wear is predominant. Among other observations the results also indicate that a unique value of the ratio of equivalent elastic modulus to hardness (E^//H) exists where wear may either be insignificant or very large depending on the parametric combination. These predictions are likely to be of practical importance.     

Exploring relationships among anger, perceived organizational support, and workplace outcomes.

The present study examines anger within a perceived organizational support (POS) theory framework. Using structural equation modeling, the authors explored relationships among POS, anger, and workplace outcomes in a sample of 1,136 employees in 21 stores of a U.S. retail organization. At both individual and store levels, low POS was directly associated with greater anger. At the individual level, anger partially mediated relationships among low POS and turnover intentions, absences, and accidents on the job. Anger had direct and indirect effects on alcohol consumption and health-related risk taking. At the store level, anger had direct negative effects on inventory loss and turnover. The authors interpret these findings in light of social exchange theory and emotion regulation theory. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Behavioural Patterns and User Profiles related to energy consumption for heating

The difference between the actual and predicted energy consumption for heating in housing is thought to be partly attributable to the use of HVAC systems. More reliable data on energy consumption could help in determining the actual energy performance of dwellings and in the search for the most adequate design for housing and home amenities. Further reductions on energy consumption might also be achieved if energy-saving policy programmes were geared to different household groups. The aim of this paper is to statistically determine Behavioural Patterns associated with the energy spent on heating and to identify household and building characteristics that could contribute to the development of energy-User Profiles. This study had two outcomes: it identified Behavioural Patterns to be used in energy calculations and it discerned User Profiles with different behaviours. Five underlying groups of behavioural variables were found, which were used to define the Behavioural Patterns and User Profiles. The groups showed statistically significant differences in the scores for most of the behavioural factors. This study established clear relationships between occupant behaviour and household characteristics. However, it seems difficult to establish relationships between energy consumption and Behavioural Patterns and household groups.