979 resultados para Process Variables


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Since 1999, countries have voluntarily chosen to reform their higher education systems to join the European Higher Education Area. This paper compares Bologna Process implementation across four regions within the European Union. While there are 47 countries participating in the Bologna Process, this paper uses statistical analysis to consider 25 of the 28 EU Member States. The time period of analysis is 2000-2011, prior to Croatia’s accession to the EU on 1 July 2013. Across Europe there are inter-regional differences in how the Bologna Process has been implemented and in the political economy contexts that influence higher education reform for policy convergence. There are three explanatory variables in the political economy context: 1. competitive economic pressures and globalization 2. domestic politics at the national level 3. leadership from the supranational European Union that socially constructs regional norms Tertiary education attainment is the dependent variable of interest in this research. The objective of 40%, for 30-34 year olds, is Europe 2020 benchmark target. There are additional higher education reform criteria encompassed in the Bologna Process. These criteria concern Credit and Degree Structure, Quality Assurance, and Recognition of academic degrees among countries in the EHEA. This tertiary education attainment variable, which is of interest in this paper, does not capture the entire implementation process. Nevertheless, it is a measure of one important indicator of success in providing higher education access to populations within the context of democratic governance. This research finds that statistically GDP Per Capita is the most significant variable in relationship to tertiary education attainment across four regional areas in the European Union.

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Le VIH infecte les cellules par fusion de sa membrane avec la membrane de la cellule cible. Cette fusion est effectuée par les glycoprotéines de l'enveloppe (Env) qui sont synthétisées en tant que précurseur, gp160, qui est ensuite clivé en gp120 et gp41. La protéine gp41 est la partie transmembranaire du complexe de l'enveloppe et l’ancre à la particule virale alors que la gp120 assure la liaison au récepteur cellulaire CD4 et corécepteur CCR5 ou CXCR4. Ces interactions successives induisent des changements de conformation d’Env qui alimentent le processus d'entrée du virus conduisant finalement à l'insertion du peptide de fusion de la gp41 dans la membrane de la cellule cible. La sous-unité extérieure gp120 contient cinq régions variables (V1 à V5), dont trois (V1, V2 et V3) étant capables d’empêcher l’adoption spontanée de la conformation liée à CD4. Cependant, le rôle de régions variables V4 et V5 vis-à-vis de ces changements de conformation reste inconnu. Pour étudier leur effet, des mutants de l'isolat primaire de clade B YU2, comprenant une délétion de la V5 ou une mutation au niveau de tous les sites potentiels de N-glycosylation de la V4 (PNGS), ont été générés. L'effet des mutations sur la conformation des glycoprotéines d'enveloppe a été analysé par immunoprécipitation et résonance de plasmon de surface avec des anticorps dont la liaison dépend de la conformation adopté par la gp120. Ni le retrait des PNGS de la V4 ni la délétion de V5 n’a affecté les changements conformationnels d’Env tels que mesurés par ces techniques, ce qui suggère que les régions variables V1, V2 et V3 sont les principaux acteurs dans la prévention de l’adoption de la conformation lié de CD4 d’Env.

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The liberalisation of Eastern Europe’s market during the 1990s and the 2004 EU enlargement have had a great impact on the economies of Central and Eastern Europe (CEE). Indeed, prior to these events, the financial system and household credit markets in CEE were underdeveloped. Nonetheless, it appeared to numerous economists that the development of the CEE financial system and credit markets was following an intensely positive trend, raising the question of sustainability. Many variables impact the level and growth rate of credit; several economists point out that a convergence process might be one of the most important. Using a descriptive statistics approach, it seems likely that a convergence process began during the 1990s, when the CEE countries opened their economies. However, it also seems that the main driver of this household credit convergence process is the GDP per capita convergence process. Indeed, credit to households and GDP per capita have followed broadly similar tendencies over the last 20 years and it has been shown in the literature that they appear to influence each other. The consistency of this potential convergence process is also confirmed by the breakdown of household credit by type and maturity. There is a tendency towards similar household credit markets in Europe. However, it seems that this potential convergence process was slowed down by the financial crisis. Fortunately, the crisis also stabilised the share of loans in foreign currency in CEE countries. This might add more stability to credit markets in Eastern Europe.

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Biological wastewater treatment is a complex, multivariate process, in which a number of physical and biological processes occur simultaneously. In this study, principal component analysis (PCA) and parallel factor analysis (PARAFAC) were used to profile and characterise Lagoon 115E, a multistage biological lagoon treatment system at Melbourne Water's Western Treatment Plant (WTP) in Melbourne, Australia. In this study, the objective was to increase our understanding of the multivariate processes taking place in the lagoon. The data used in the study span a 7-year period during which samples were collected as often as weekly from the ponds of Lagoon 115E and subjected to analysis. The resulting database, involving 19 chemical and physical variables, was studied using the multivariate data analysis methods PCA and PARAFAC. With these methods, alterations in the state of the wastewater due to intrinsic and extrinsic factors could be discerned. The methods were effective in illustrating and visually representing the complex purification stages and cyclic changes occurring along the lagoon system. The two methods proved complementary, with each having its own beneficial features. (C) 2003 Elsevier B.V. All rights reserved.

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Response of an aerobic upflow sludge blanket (AUSB) reactor system to the changes in operating conditions was investigated by varying two principle operating variables: the oxygenation pressure and the flow recirculation rate. The oxygenation pressure was varied between 0 and 25 psig (relative), while flow recirculation rates were between 1,300 and 600% correspondingly. The AUSB reactor system was able to handle a volumetric loading of as high as 3.8 kg total organic carbon (TOC)/m(3) day, with a removal efficiency of 92%. The rate of TOC removal by AUSB was highest at a pressure of 20 psig and it decreased when the pressure was increased to 25 psig and the flow recirculation rate was reduced to 600%. The TOC removal rate also decreased when the operating pressure was reduced to 0 and 15 psig, with corresponding increase in flow recirculation rates to 1,300 and 1,000%, respectively. Maintenance of a high dissolved oxygen level and a high flow recirculation rate was found to improve the substrate removal capacity of the AUSB system. The AUSB system was extremely effective in retaining the produced biomass despite a high upflow velocity and the overall sludge yield was only 0.24-0.32 g VSS/g TOC removed. However, the effluent TOC was relatively high due to the system's operation at a high organic loading.

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In this paper, we describe the development of two new measures of innovation trust, ‘trust that heard’ and ‘trust that benefit’. We report the findings from their use in a survey of design engineers in two large aerospace companies. We test a range of hypotheses covering different plausible roles for trust and confirm a ‘main effects’ model, whereby the variables predict the number of ideas suggested and the number of ideas implemented. In addition, we replicate earlier findings by Axtel et al. (2000), namely that personal and job variables predict idea suggestion, whereas organizational variables predict implementation.

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Interpolated data are an important part of the environmental information exchange as many variables can only be measured at situate discrete sampling locations. Spatial interpolation is a complex operation that has traditionally required expert treatment, making automation a serious challenge. This paper presents a few lessons learnt from INTAMAP, a project that is developing an interoperable web processing service (WPS) for the automatic interpolation of environmental data using advanced geostatistics, adopting a Service Oriented Architecture (SOA). The “rainbow box” approach we followed provides access to the functionality at a whole range of different levels. We show here how the integration of open standards, open source and powerful statistical processing capabilities allows us to automate a complex process while offering users a level of access and control that best suits their requirements. This facilitates benchmarking exercises as well as the regular reporting of environmental information without requiring remote users to have specialized skills in geostatistics.

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This research was undertaken to: develop a process for the direct solvent extraction of castor oil seeds. A literature survey confirmed the desirability of establishing such a process with emphasis on the decortication, size, reduction, detoxification-deallergenization, and solvent·extraction operations. A novel process was developed for the dehulling of castor seeds which consists of pressurizing the beans and then suddenly releasing the pressure to vaccum. The degree of dehulling varied according to the pressure applied and the size of the beans. Some of the batches were difficult-to-hull, and this phenomenon was investigated using the scanning electron microscope and by thickness and compressive strength measurements. The other variables studied to lesser degrees included residence time, moisture, content, and temperature.The method was successfully extended to cocoa beans, and (with modifications) to peanuts. The possibility of continuous operation was looked into, and a mechanism was suggested to explain the method works. The work on toxins and allergens included an extensive literature survey on the properties of these substances and the methods developed for their deactivation Part of the work involved setting up an assay method for measuring their concentration in the beans and cake, but technical difficulties prevented the completion of this aspect of the project. An appraisal of the existing deactivation methods was made in the course of searching for new ones. A new method of reducing the size of oilseeds was introduced in this research; it involved freezing the beans in cardice and milling them in a coffee grinder, the method was found to be a quick, efficient, and reliable. An application of the freezing technique was successful in dehulling soybeans and de-skinning peanut kernels. The literature on the solvent extraction, of oilseeds, especially castor, was reviewed: The survey covered processes, equipment, solvents, and mechanism of leaching. three solvents were experimentally investigated: cyclohexane, ethanol, and acetone. Extraction with liquid ammonia and liquid butane was not effective under the conditions studied. Based on the results of the research a process has been suggested for the direct solvent extraction of castor seeds, the various sections of the process have analysed, and the factors affecting the economics of the process were discussed.

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This research addressed the question: "Which factors predict the effectiveness of healthcare teams?" It was addressed by assessing the psychometric properties of a new measure of team functioning with the use of data collected from 797 team members in 61 healthcare teams. This new measure is the Aston Team Performance Inventory (ATPI) developed by West, Markiewicz and Dawson (2005) and based on the IPO model. The ATPI was pilot tested in order to examine the reliability of this measure in the Jordanian cultural context. A sample of five teams comprising 3-6 members each was randomly selected from the Jordan Red Crescent health centers in Amman. Factors that predict team effectiveness were explored in a Jordanian sample (comprising 1622 members in 277 teams with 255 leaders from healthcare teams in hospitals in Amman) using self-report and Leader Ratings measures adapted from work by West, Borrill et al (2000) to determine team effectiveness and innovation from the leaders' point of view. The results demonstrate the validity and reliability of the measures for use in healthcare settings. Team effort and skills and leader managing had the strongest association with team processes in terms of team objectives, reflexivity, participation, task focus, creativity and innovation. Team inputs in terms of task design, team effort and skills, and organizational support were associated with team effectiveness and innovation whereas team resources were associated only with team innovation. Team objectives had the strongest mediated and direct association with team effectiveness whereas task focus had the strongest mediated and direct association with team innovation. Finally, among leadership variables, leader managing had the strongest association with team effectiveness and innovation. The theoretical and practical implications of this thesis are that: team effectiveness and innovation are influenced by multiple factors that must all be taken into account. The key factors managers need to ensure are in place for effective teams are team effort and skills, organizational support and team objectives. To conclude, the application of these findings to healthcare teams in Jordan will help improve their team effectiveness, and thus the healthcare services that they provide.

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Direct quantile regression involves estimating a given quantile of a response variable as a function of input variables. We present a new framework for direct quantile regression where a Gaussian process model is learned, minimising the expected tilted loss function. The integration required in learning is not analytically tractable so to speed up the learning we employ the Expectation Propagation algorithm. We describe how this work relates to other quantile regression methods and apply the method on both synthetic and real data sets. The method is shown to be competitive with state of the art methods whilst allowing for the leverage of the full Gaussian process probabilistic framework.

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Practitioners assess performance of entities in increasingly large and complicated datasets. If non-parametric models, such as Data Envelopment Analysis, were ever considered as simple push-button technologies, this is impossible when many variables are available or when data have to be compiled from several sources. This paper introduces by the 'COOPER-framework' a comprehensive model for carrying out non-parametric projects. The framework consists of six interrelated phases: Concepts and objectives, On structuring data, Operational models, Performance comparison model, Evaluation, and Result and deployment. Each of the phases describes some necessary steps a researcher should examine for a well defined and repeatable analysis. The COOPER-framework provides for the novice analyst guidance, structure and advice for a sound non-parametric analysis. The more experienced analyst benefits from a check list such that important issues are not forgotten. In addition, by the use of a standardized framework non-parametric assessments will be more reliable, more repeatable, more manageable, faster and less costly. © 2010 Elsevier B.V. All rights reserved.

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Data envelopment analysis (DEA) has been proven as an excellent data-oriented efficiency analysis method for comparing decision making units (DMUs) with multiple inputs and multiple outputs. In conventional DEA, it is assumed that the status of each measure is clearly known as either input or output. However, in some situations, a performance measure can play input role for some DMUs and output role for others. Cook and Zhu [Eur. J. Oper. Res. 180 (2007) 692–699] referred to these variables as flexible measures. The paper proposes an alternative model in which each flexible measure is treated as either input or output variable to maximize the technical efficiency of the DMU under evaluation. The main focus of this paper is on the impact that the flexible measures has on the definition of the PPS and the assessment of technical efficiency. An example in UK higher education intuitions shows applicability of the proposed approach.

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This paper critically reviews the strategic decision-making process literature, with a specific focus on the effects of context. Context refers to the top management team, strategic decision-specific characteristics, the external environment and firm characteristics. This literature review also develops an illustrative framework that incorporates these four different categories of contextual variables that influence the strategic decision-making process. As a result of the variety and pervasiveness of contextual variables featured within the literature, a comprehensive and up-to-date review is essential for organizing and synthesizing the extant literature to explicate an agenda for future research. The purpose of this literature review is threefold: first, to critically review the strategic decision-making process literature to highlight the underlying themes, issues, tensions and debates in the field; second, to identify the opportunities for future theory development; and third, to state the methodological implications arising from this review. © 2013 British Academy of Management and John Wiley & Sons Ltd.

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Despite concerted academic interest in the strategic decision-making process (SDMP) since the 1980s, a coherent body of theory capable of guiding practice has not materialised. This is because many prior studies focus only on a single process characteristic, often rationality or comprehensiveness, and have paid insufficient attention to context. To further develop theory, research is required which examines: (i) the influence of context from multiple theoretical perspectives (e.g. upper echelons, environmental determinism); (ii) different process characteristics from both synoptic formal (e.g. rationality) and political incremental (e.g. politics) perspectives, and; (iii) the effects of context and process characteristics on a range of SDMP outcomes. Using data from 30 interviews and 357 questionnaires, this thesis addresses several opportunities for theory development by testing an integrative model which incorporates: (i) five SDMP characteristics representing both synoptic formal (procedural rationality, comprehensiveness, and behavioural integration) and political incremental (intuition, and political behaviour) perspectives; (ii) four SDMP outcome variables—strategic decision (SD) quality, implementation success, commitment, and SD speed, and; (iii) contextual variables from the four theoretical perspectives—upper echelons, SD-specific characteristics, environmental determinism, and firm characteristics. The present study makes several substantial and original contributions to knowledge. First, it provides empirical evidence of the contextual boundary conditions under which intuition and political behaviour positively influence SDMP outcomes. Second, it establishes the predominance of the upper echelons perspective; with TMT variables explaining significantly more variance in SDMP characteristics than SD specific characteristics, the external environment, and firm characteristics. A newly developed measure of top management team expertise also demonstrates highly significant direct and indirect effects on the SDMP. Finally, it is evident that SDMP characteristics and contextual variables influence a number of SDMP outcomes, not just overall SD quality, but also implementation success, commitment, and SD speed.

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In the global economy, innovation is one of the most important competitive assets for companies willing to compete in international markets. As competition moves from standardised products to customised ones, depending on each specific market needs, economies of scale are not anymore the only winning strategy. Innovation requires firms to establish processes to acquire and absorb new knowledge, leading to the recent theory of Open Innovation. Knowledge sharing and acquisition happens when firms are embedded in networks with other firms, university, institutions and many other economic actors. Several typologies of innovation and firm networks have been identified, with various geographical spans. One of the first being modelled was the Industrial Cluster (or in Italian Distretto Industriale) which was for long considered the benchmark for innovation and economic development. Other kind of networks have been modelled since the late 1970s; Regional Innovation Systems represent one of the latest and more diffuse model of innovation networks, specifically introduced to combine local networks and the global economy. This model was qualitatively exploited since its introduction, but, together with National Innovation Systems, is among the most inspiring for policy makers and is often cited by them, not always properly. The aim of this research is to setup an econometric model describing Regional Innovation Systems, becoming one the first attempts to test and enhance this theory with a quantitative approach. A dataset of 104 secondary and primary data from European regions was built in order to run a multiple linear regression, testing if Regional Innovation Systems are really correlated to regional innovation and regional innovation in cooperation with foreign partners. Furthermore, an exploratory multiple linear regression was performed to verify which variables, among those describing a Regional Innovation Systems, are the most significant for innovating, alone or with foreign partners. Furthermore, the effectiveness of present innovation policies has been tested based on the findings of the econometric model. The developed model confirmed the role of Regional Innovation Systems for creating innovation even in cooperation with international partners: this represents one of the firsts quantitative confirmation of a theory previously based on qualitative models only. Furthermore the results of this model confirmed a minor influence of National Innovation Systems: comparing the analysis of existing innovation policies, both at regional and national level, to our findings, emerged the need for potential a pivotal change in the direction currently followed by policy makers. Last, while confirming the role of the presence a learning environment in a region and the catalyst role of regional administration, this research offers a potential new perspective for the whole private sector in creating a Regional Innovation System.