A rationale for the optimisation by computer methods of the efficient use of metals and materials

The aim of the research project was to gain d complete and accurate accounting of the needs and deficiencies of materials selection and design data, with particular attention given to the feasibility of a computerised materials selection system that would include application analysis, property data and screening techniques. The project also investigates and integrates the three major aspects of materials resources, materials selection and materials recycling. Consideration of the materials resource base suggests that, though our discovery potential has increased, geologic availability is the ultimate determinant and several metals may well become scarce at the same time, thus compounding the problem of substitution. With around 2- to 20- million units of engineering materials data, the use of a computer is the only logical answer for scientific selection of materials. The system developed at Aston is used for data storage, mathematical computation and output. The system enables programs to be run in batch and interactive (on-line) mode. The program with modification can also handle such variables as quantity of mineral resources, energy cost of materials and depletion and utilisation rates of strateqic materials. The work also carries out an in-depth study of copper recycling in the U.K. and concludes that, somewhere in the region of 2 million tonnes of copper is missing from the recycling cycle. It also sets out guidelines on product design and conservation policies from the recyclability point of view.

A study of new product market search and user adoption

The research was carried out in the Aviation Division of Dunlop Limited and was initiated as a search for more diverse uses for carbon/carbon composites. An assumed communication model of adoption was refined by introducing the concept of a two way search after making cross industry comparisons of supplier and consumer behaviour. This research has examined methods of searching for new uses for advanced technology materials. Two broad approaches were adopted. First, a case history approach investigated materials that had been in a similar oosition to carbon/carbon to see how other material producing firms had tackled the problem. Second, a questionnaire survey among industrialists examined: the role and identity of material decision makers in different sized firms; the effectiveness of various information sources and channels; and the material adoption habits of different industries. The effectiveness of selected information channels was further studied by monitoring the response to publicity given to carbon/carbon. A flow chart has been developed from the results of this research which should help any material producing firm that is contemplating the introduction of a new material to the world market. Further benefit to our understanding of the innovation and adoption of new materials would accrue from work in the followino areas: "micro" type case histories; understanding more fully the role of product champions or promoters; investigating the phase difference between incremental and radical type innovations for materials; examining the relationship between the adoption rate of new materials and the advance of technology; studying the development of cost per unit function methods for material selection; and reviewing the benefits that economy of scale studies can have on material developments. These are all suggested areas for further work.

Computationsl modelling of dimethyl ether separation and steam reforming in fluidized bed reactors

This study presents a computational fluid dynamic (CFD) study of Dimethyl Ether (DME) gas adsorptive separation and steam reforming (DME-SR) in a large scale Circulating Fluidized Bed (CFB) reactor. The CFD model is based on Eulerian-Eulerian dispersed flow and solved using commercial software (ANSYS FLUENT). Hydrogen is currently receiving increasing interest as an alternative source of clean energy and has high potential applications, including the transportation sector and power generation. Computational fluid dynamic (CFD) modelling has attracted considerable recognition in the engineering sector consequently leading to using it as a tool for process design and optimisation in many industrial processes. In most cases, these processes are difficult or expensive to conduct in lab scale experiments. The CFD provides a cost effective methodology to gain detailed information up to the microscopic level. The main objectives in this project are to: (i) develop a predictive model using ANSYS FLUENT (CFD) commercial code to simulate the flow hydrodynamics, mass transfer, reactions and heat transfer in a large scale dual fluidized bed system for combined gas separation and steam reforming processes (ii) implement a suitable adsorption models in the CFD code, through a user defined function, to predict selective separation of a gas from a mixture (iii) develop a model for dimethyl ether steam reforming (DME-SR) to predict hydrogen production (iv) carry out detailed parametric analysis in order to establish ideal operating conditions for future industrial application. The project has originated from a real industrial case problem in collaboration with the industrial partner Dow Corning (UK) and jointly funded by the Engineering and Physical Research Council (UK) and Dow Corning. The research examined gas separation by adsorption in a bubbling bed, as part of a dual fluidized bed system. The adsorption process was simulated based on the kinetics derived from the experimental data produced as part of a separate PhD project completed under the same fund. The kinetic model was incorporated in FLUENT CFD tool as a pseudo-first order rate equation; some of the parameters for the pseudo-first order kinetics were obtained using MATLAB. The modelling of the DME adsorption in the designed bubbling bed was performed for the first time in this project and highlights the novelty in the investigations. The simulation results were analysed to provide understanding of the flow hydrodynamic, reactor design and optimum operating condition for efficient separation. Bubbling bed validation by estimation of bed expansion and the solid and gas distribution from simulation agreed well with trends seen in the literatures. Parametric analysis on the adsorption process demonstrated that increasing fluidizing velocity reduced adsorption of DME. This is as a result of reduction in the gas residence time which appears to have much effect compared to the solid residence time. The removal efficiency of DME from the bed was found to be more than 88%. Simulation of the DME-SR in FLUENT CFD was conducted using selected kinetics from literature and implemented in the model using an in-house developed user defined function. The validation of the kinetics was achieved by simulating a case to replicate an experimental study of a laboratory scale bubbling bed by Vicente et al [1]. Good agreement was achieved for the validation of the models, which was then applied in the DME-SR in the large scale riser section of the dual fluidized bed system. This is the first study to use the selected DME-SR kinetics in a circulating fluidized bed (CFB) system and for the geometry size proposed for the project. As a result, the simulation produced the first detailed data on the spatial variation and final gas product in such an industrial scale fluidized bed system. The simulation results provided insight in the flow hydrodynamic, reactor design and optimum operating condition. The solid and gas distribution in the CFB was observed to show good agreement with literatures. The parametric analysis showed that the increase in temperature and steam to DME molar ratio increased the production of hydrogen due to the increased DME conversions, whereas the increase in the space velocity has been found to have an adverse effect. Increasing temperature between 200 oC to 350 oC increased DME conversion from 47% to 99% while hydrogen yield increased substantially from 11% to 100%. The CO2 selectivity decreased from 100% to 91% due to the water gas shift reaction favouring CO at higher temperatures. The higher conversions observed as the temperature increased was reflected on the quantity of unreacted DME and methanol concentrations in the product gas, where both decreased to very low values of 0.27 mol% and 0.46 mol% respectively at 350 °C. Increasing the steam to DME molar ratio from 4 to 7.68 increased the DME conversion from 69% to 87%, while the hydrogen yield increased from 40% to 59%. The CO2 selectivity decreased from 100% to 97%. The decrease in the space velocity from 37104 ml/g/h to 15394 ml/g/h increased the DME conversion from 87% to 100% while increasing the hydrogen yield from 59% to 87%. The parametric analysis suggests an operating condition for maximum hydrogen yield is in the region of 300 oC temperatures and Steam/DME molar ratio of 5. The analysis of the industrial sponsor’s case for the given flow and composition of the gas to be treated suggests that 88% of DME can be adsorbed from the bubbling and consequently producing 224.4t/y of hydrogen in the riser section of the dual fluidized bed system. The process also produces 1458.4t/y of CO2 and 127.9t/y of CO as part of the product gas. The developed models and parametric analysis carried out in this study provided essential guideline for future design of DME-SR at industrial level and in particular this work has been of tremendous importance for the industrial collaborator in order to draw conclusions and plan for future potential implementation of the process at an industrial scale.

Use of narrow mass-window, high-resolution extracted product ion chromatograms for the sensitive and selective identification of protein modifications

Protein modifications, including oxidative modifications, glycosylations, and oxidized lipid-protein adducts, are becoming increasingly important as biomarkers and in understanding disease etiology. There has been a great deal of interest in mapping these on Apo B100 from low density lipoprotein (LDL). We have used extracted ion chromatograms of product ions generated using a very narrow mass window from high-resolution tandem mass spectrometric data collected on a rapid scanning quadrupole time-of-flight (QTOF) instrument, to selectively and sensitively detect modified peptides and identify the site and nature of a number of protein modifications in parallel. We have demonstrated the utility of this method by characterizing for the first time oxidized phospholipid adducts to LDL and human serum albumin and for the detection of glycosylation and kynurenin formation from the oxidation of tryptophan residues in LDL. © 2013 American Chemical Society.

The influence of organizational and national culture on new product performance

The authors conduct a meta-analysis on the combined influence of organizational and national culture on new product performance. For this purpose, they refer to the effectiveness of value congruency and develop a conceptual model describing the fit between organizational culture types as suggested by the competing values framework and national culture, as described by Hofstede's cultural dimensions. The meta-analysis is based on 489 effect sizes taken from 123 manuscripts. The findings show that organizations with a market culture show the highest new product performance, while hierarchy-type organizations show the lowest performance. The influence of national culture variables supports the effect of value congruency, and shows that in individualistic cultures the impact of a clan culture decreases, the impact of an adhocracy culture type decreases with uncertainty avoidance, and the influence of a hierarchy culture type increases with power distance. The superior effect of a market culture type can be matched by other organizational orientations, but in particular national cultures only. The combined findings underline the importance for firms that seek to improve the success rate of new products on international markets to consider the fit of a national culture with a firm's organizational culture.

An Exploratory Study on the Role of Familiarity in Product Evaluations

There is growing interest among researchers working in the areas of product-country image effects, and more generally international consumer behaviour, in the potential relationship between consumers’ familiarity with, and evaluation of, products from various countries. We use data from a consumer survey in Hungary to attempt an initial exploration of this relationship. The data support findings from earlier similar studies but also suggest that affective considerations may be playing a considerable role in the evaluations of domestic products, and that the relationship of familiarity with product evaluations may vary significantly from country to country and may not be as strong as previously thought.

The Influence of Social Responsibility Image Relative to Product and Service Quality on Brand Loyalty: An Exploratory Study of Quick-service Restaurants

Social responsibility (SR) is becoming an increasingly significant component of many firms’ strategic planning decisions. Research has shown that consumers tend to reward socially responsible behavior. However, there has been little testing of the construct in the hospitality industry. Additionally, when other important variables that influence consumer brand loyalty are considered, will brand social responsibility image (BSRI) still play a significant role? This study investigates the importance of SR and its impact on brand loyalty, relative to product quality and service quality in the quick-service restaurant industry. The authors were also interested to learn whether BSRI impacted consumers' image of product and service quality. It was found that BSRI had a positive impact on brand loyalty, product quality, and service quality. However, product quality was a significantly stronger predictor of brand loyalty than BSRI. Where the vast majority of studies of SR have utilized scenario analysis of hypothetical firms, this study utilizes consumers' perceptions of a real-world firm.

Annotated record and illustrations of Mn nodules retrieved during cruise KH-73-4 of the R/V Hakuho Maru and cruises GH76-1 and GH77-1 of the R/V Hakurei Maru

Deep sea manganese nodules from the Central Pacific Basin are mainly composed of 10Å manganite and d-MnO2 Two zones equivalent to the minerals are evidently distinguishable according to their optical properties. Microscopic and microprobe analyses revealed quite different chemical compositions and textnral characteristics of the two zones. These different feature of the two zones of nodules suggest the different conditions under which they were formed. Concentrations of 11 metal elements in the zones and inter-element relationships show that the 10Å manganite zone is a monomineralic oxide phase containing a large amount of manganese and minor amounts of useful metals, and that the d-MnO2 zone which is apparently homogeneous under the microscope is a mixture of three or more different minerals. The chemical characteristics of the two zones can explain the variation of bulk composition of deep sea manganese nodules and inter-element relationships previously reported, suggesting that the bulk compositions are attributable to the mixing of the 10Å manganite and d-MnO2 zones in various ratios. Characteristic morphology and surface structure of some types of nodules and their relationships to chemistry are also attribut able to the textural and chemical features of the above mentioned two phases. Synthesis of hydrated manganese oxides was carried out in terms of the formation of manganese minerals in the ocean. The primary product which is an equivalent to d-MnO2 was precipitated from Mn 2+ -bearing alkaline solution under oxigenated condition by air bubbling at one atmospheric pressure and room temperature. The primary product was converted to a l0Å manganite equivalent by contact with Ni 2+, Cu 2++ or CO2+ chloride solutions. This reaction caused the decrease of Ni2+, Cu2+ or CO2+ concentrations and the increase of Na+ concentration in the solution. The reaction also proceeded even in diluted solutions of nickel chloride and resulted in a complete removal of Ni2+ from the solution. Reaction products were exclusively 10Å manganite equivalents and their chemical compositions were very similar to those of 10Å manganite in manganese nodules. The maximum value of(Cu+Ni+Co)/Mn ratio of 10Å manganite zones in manganese nodules is 0.16, and the Ni/Mn ratio of synthetic 10Å manganite ranges from 0.15 to 0.18 with the average of 0.167.

Development of a knowledge sharing framework for improving the testing processes in global product development

As identified by Griffin (1997) and Kahn (2012), manufacturing organisations typically improve their market position by accelerating their product development (PD) cycles. One method for achieving this is to reduce the time taken to design, test and validate new products, so that they can reach the end customer before competition. This paper adds to existing research on PD testing procedures by reporting on an exploratory investigation carried out in a UK-based manufacturing plant. We explore the organisational and managerial factors that contribute to the time spent on testing of new products during development. The investigation consisted of three sections, viz. observations and process modelling, utilisation metrics and a questionnaire-based investigation, from which a proposed framework to improve and reduce the PD time cycle is presented. This research focuses specifically on the improvement of the utilisation of product testing facilities and the links to its main internal stakeholders - PD engineers.

HPLC Determination of Angiotensin-Converting Enzyme Activity on Toyopearl HW-40S Column

Angiotensin-converting enzyme (EC3.4.15. I; ACE), isa membrane-bounddipeptidyl carboxypeptidase that mediates the cleavage of the C-terminal dipeptide His-Leu of the decapeptide angiotensin, generating the most powerful endogenous vaso-constricting angiotensin.
Some ACE inhibitors, such as Captopril, have been used as anti-hypertensive drugs. Moreover in recent years, large quantities of ACE inhibitors have been identijied and isolated from peptides derivedfrom food material such as casein, soy protein, jish protein and so on. Functional food with hypotensive effect has been developed on the basis of these works.
Typicalprocedures for screening hypotensive peptides offood origins are separationof products of peptic and tryptic digestion of proteins followed by inhibitory activitydetermination of each fraction. A method developed by Cushman has been the mostwidely used, in which ACE activity is determined by the amount of hippuric acid
generated as a product of enzymatic reaction of ACE with tripeptide of hippuryl-Lhistidyl-L-leucine. Hippuric acid is determined spectrophotometrically at 228 nm after its isolation from the reaction system by ethylacetate extraction, which not only requires alarge quantity of reagent but also results in large error.
An improved method based on Cushman ’s method is proposed in this paper. In this method, an enzymatic reaction system is based on Cushman’s method, while isolation and determination of hippuric acid is performed by medium perjormance gel chromatography on a Toyopearl HW-40s column. Due to the size exclusion nature of the column with somewhat hydrophobic properties, complete separation of four existing fractions in the reaction system is obtained within a smallfraction of the time necessary in Cushman’s method, with ideal reproducibility.

Influence of host plant structure and microclimate on the abundance and behaviour of Tephritid fly

Microclimate and host plant architecture significantly influence the abundance and behavior of insects. However, most research in this field has focused at the invertebrate assemblage level, with few studies at the single-species level. Using wild Solanum mauritianum plants, we evaluated the influence of plant structure (number of leaves and branches and height of plant) and microclimate (temperature, relative humidity, and light intensity) on the abundance and behavior of a single insect species, the monophagous tephritid fly Bactrocera cacuminata (Hering). Abundance and oviposition behavior were signficantly influenced by the host structure (density of foliage) and associated microclimate. Resting behavior of both sexes was influenced positively by foliage density, while temperature positively influenced the numbers of resting females. The number of ovipositing females was positively influenced by temperature and negatively by relative humidity. Feeding behavior was rare on the host plant, as was mating. The relatively low explanatory power of the measured variables suggests that, in addition to host plant architecture and associated microclimate, other cues (e.g., olfactory or visual) could affect visitation and use of the larval host plant by adult fruit flies. For 12 plants observed at dusk (the time of fly mating), mating pairs were observed on only one tree. Principal component analyses of the plant and microclimate factors associated with these plants revealed that the plant on which mating was observed had specific characteristics (intermediate light intensity, greater height, and greater quantity of fruit) that may have influenced its selection as a mating site.

Experience of problem-based learning (PBL) in virtual space : a phenomenographical study

This thesis reports the outcomes of an investigation into students’ experience of Problem-based learning (PBL) in virtual space. PBL is increasingly being used in many fields including engineering education. At the same time many engineering education providers are turning to online distance education. Unfortunately there is a dearth of research into what constitutes an effective learning experience for adult learners who undertake PBL instruction through online distance education. Research was therefore focussed on discovering the qualitatively different ways that students experience PBL in virtual space. Data was collected in an electronic environment from a course, which adopted the PBL strategy and was delivered entirely in virtual space. Students in this course were asked to respond to open-ended questions designed to elicit their learning experience in the course. Data was analysed using the phenomenographical approach. This interpretative research method concentrated on mapping the qualitative differences in students’ interpretations of their experience in the course. Five qualitatively different ways of experiencing were discovered: Conception 1: ‘A necessary evil for program progression’; Conception 2: ‘Developing skills to understand, evaluate, and solve technical Engineering and Surveying problems’; Conception 3: ‘Developing skills to work effectively in teams in virtual space’; Conception 4: ‘A unique approach to learning how to learn’; Conception 5: ‘Enhancing personal growth’. Each conception reveals variation in how students attend to learning by PBL in virtual space. Results indicate that the design of students’ online learning experience was responsible for making students aware of deeper ways of experiencing PBL in virtual space. Results also suggest that the quality and quantity of interaction with the team facilitator may have a significant impact on the student experience in virtual PBL courses. The outcomes imply pedagogical strategies can be devised for shifting students’ focus as they engage in the virtual PBL experience to effectively manage the student learning experience and thereby ensure that they gain maximum benefit. The results from this research hold important ramifications for graduates with respect to their ease of transition into professional work as well as their later professional competence in terms of problem solving, ability to transfer basic knowledge to real-life engineering scenarios, ability to adapt to changes and apply knowledge in unusual situations, ability to think critically and creatively, and a commitment to continuous life-long learning and self-improvement.

Effective web service discovery using a combination of a semantic model and a data mining technique

With the advent of Service Oriented Architecture, Web Services have gained tremendous popularity. Due to the availability of a large number of Web services, finding an appropriate Web service according to the requirement of the user is a challenge. This warrants the need to establish an effective and reliable process of Web service discovery. A considerable body of research has emerged to develop methods to improve the accuracy of Web service discovery to match the best service. The process of Web service discovery results in suggesting many individual services that partially fulfil the user’s interest. By considering the semantic relationships of words used in describing the services as well as the use of input and output parameters can lead to accurate Web service discovery. Appropriate linking of individual matched services should fully satisfy the requirements which the user is looking for. This research proposes to integrate a semantic model and a data mining technique to enhance the accuracy of Web service discovery. A novel three-phase Web service discovery methodology has been proposed. The first phase performs match-making to find semantically similar Web services for a user query. In order to perform semantic analysis on the content present in the Web service description language document, the support-based latent semantic kernel is constructed using an innovative concept of binning and merging on the large quantity of text documents covering diverse areas of domain of knowledge. The use of a generic latent semantic kernel constructed with a large number of terms helps to find the hidden meaning of the query terms which otherwise could not be found. Sometimes a single Web service is unable to fully satisfy the requirement of the user. In such cases, a composition of multiple inter-related Web services is presented to the user. The task of checking the possibility of linking multiple Web services is done in the second phase. Once the feasibility of linking Web services is checked, the objective is to provide the user with the best composition of Web services. In the link analysis phase, the Web services are modelled as nodes of a graph and an allpair shortest-path algorithm is applied to find the optimum path at the minimum cost for traversal. The third phase which is the system integration, integrates the results from the preceding two phases by using an original fusion algorithm in the fusion engine. Finally, the recommendation engine which is an integral part of the system integration phase makes the final recommendations including individual and composite Web services to the user. In order to evaluate the performance of the proposed method, extensive experimentation has been performed. Results of the proposed support-based semantic kernel method of Web service discovery are compared with the results of the standard keyword-based information-retrieval method and a clustering-based machine-learning method of Web service discovery. The proposed method outperforms both information-retrieval and machine-learning based methods. Experimental results and statistical analysis also show that the best Web services compositions are obtained by considering 10 to 15 Web services that are found in phase-I for linking. Empirical results also ascertain that the fusion engine boosts the accuracy of Web service discovery by combining the inputs from both the semantic analysis (phase-I) and the link analysis (phase-II) in a systematic fashion. Overall, the accuracy of Web service discovery with the proposed method shows a significant improvement over traditional discovery methods.

The central role of communication in developing trust and its effect on employee involvement

Communication plays an important role in the development of trust within an organization. While a number of researchers have studied the relationship of trust and communication, little is known about the specific linkages among quality of information, quantity of information, openness, trust, and outcomes such as employee involvement. This study tests these relationships using communication audit data from 218 employees in the oil industry. Using mediation analysis and structural equation modeling, we found that quality of information predicted trust of one's coworkers and supervisors while adequacy of information predicted one's trust of top management. Trust of coworkers, supervisors, and top management influenced perceptions of organizational openness, which in turn influenced employees' ratings of their own level of involvement in the organization's goals. This study suggests that the relationship between communication and trust is complex, and that simple strategies focusing on either quality or quantity of information may be ineffective for dealing with all members in an organization.

In the mouth of the imagination : positioning children as co-researchers and co-artists to create a professional children's theatre production

In recent decades a number of Australian artists and teacher/artists have given serious attention to the creation of performance forms and performance engagement models that respect children’s intelligence, engage with themes of relevance, avoid the cliche´s of children’s theatre whilst connecting both sincerely and playfully with current understandings of the way in which young children develop and engage with the world. Historically a majority of performing arts companies touring Australian schools or companies seeking schools to view a performance in a dedicated performance venue engage with their audiences in what can be called a ‘drop-in drop-out’ model. A six-month practice-led research project (The Tashi Project) which challenged the tenets of the ‘drop-in drop-out’ model has been recently undertaken by Sandra Gattenhof and Mark Radvan in conjunction with early childhood students from three Brisbane primary school classrooms who were positioned as co-researchers and co-artists. The children, researchers and performers worked in a complimentary relationship in both the artistic process and the development of product.