16 resultados para negative dimensional integration

em Aston University Research Archive


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Potential applications of high-damping and high-stiffness composites have motivated extensive research on the effects of negative-stiffness inclusions on the overall properties of composites. Recent theoretical advances have been based on the Hashin-Shtrikman composite models, one-dimensional discrete viscoelastic systems and a two-dimensional nested triangular viscoelastic network. In this paper, we further analyze the two-dimensional triangular structure containing pre-selected negative-stiffness components to study its underlying deformation mechanisms and stability. Major new findings are structure-deformation evolution with respect to the magnitude of negative stiffness under shear loading and the phenomena related to dissipation-induced destabilization and inertia-induced stabilization, according to Lyapunov stability analysis. The evolution shows strong correlations between stiffness anomalies and deformation modes. Our stability results reveal that stable damping peaks, i.e. stably extreme effective damping properties, are achievable under hydrostatic loading when the inertia is greater than a critical value. Moreover, destabilization induced by elemental damping is observed with the critical inertia. Regardless of elemental damping, when the inertia is less than the critical value, a weaker system instability is identified.

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In dimensional metrology, often the largest source of uncertainty of measurement is thermal variation. Dimensional measurements are currently scaled linearly, using ambient temperature measurements and coefficients of thermal expansion, to ideal metrology conditions at 20˚C. This scaling is particularly difficult to implement with confidence in large volumes as the temperature is unlikely to be uniform, resulting in thermal gradients. A number of well-established computational methods are used in the design phase of product development for the prediction of thermal and gravitational effects, which could be used to a greater extent in metrology. This paper outlines the theory of how physical measurements of dimension and temperature can be combined more comprehensively throughout the product lifecycle, from design through to the manufacturing phase. The Hybrid Metrology concept is also introduced: an approach to metrology, which promises to improve product and equipment integrity in future manufacturing environments. The Hybrid Metrology System combines various state of the art physical dimensional and temperature measurement techniques with established computational methods to better predict thermal and gravitational effects.

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While diversity might give an organization a competitive advantage, individuals have a tendency to prefer homogenous group settings. Prior research suggests that group members who are dissimilar (vs. similar) to their peers in terms of a given diversity attribute (e.g. demographics, attitudes, values or traits) feel less attached to their work group, experience less satisfying and more conflicted relationships with their colleagues, and consequently are less effective. However, prior empirical findings tend to be weak and inconsistent, and it remains unclear when, how and to what extent such differences affect group members’ social integration (i.e. attachment with their work group, satisfaction and conflicted relationships with their peers) and effectiveness. To address these issues the current study conducted a meta-analysis and integrated the empirical results of 129 studies. For demographic diversity attributes (such as gender, ethnicity, race, nationality, age, functional background, and tenure) the findings support the idea that demographic dissimilarity undermines individual member performance via lower levels of social integration. These negative effects were more pronounced in pseudo teams – i.e. work groups in which group members pursue individual goals, work on individual tasks, and are rewarded for their individual performance. These negative effects were however non-existent in real teams - i.e. work groups in which groups members pursue group goals, work on interdependent tasks, and are rewarded (at least partially) based on their work group’s performance. In contrast, for underlying psychological diversity attributes (such as attitudes, personality, and values), the relationship between dissimilarity and social integration was more negative in real teams than in pseudo teams, which in return translated into even lower individual performance. At the same time however, differences in underlying psychological attributes had an even stronger positive effect on dissimilar group member’s individual performance, when the negative effects of social integration were controlled for. This implies that managers should implement real work groups to overcome the negative effects of group member’s demographic dissimilarity. To harness the positive effects of group members’ dissimilarity on underlying psychological attributes, they need to make sure that dissimilar group members become socially integrated.

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For a number of years following the Orange revolution of 2004, Ukraine aspired to join the European Union. Although full integration was never a short-term prospect, European integration, through the Association Agreement and the Deep and Comprehensive Free Trade Area, offers considerable benefits to Ukraine. However, the country was severely affected by the Great Slump of 2008–9 in the global economy, and this profoundly negative experience has shaped Ukrainian domestic and foreign policy in the subsequent period, putting paid to aspirations to EU membership and influencing the Ukrainian government's decision to seek a closer relationship with Russia immediately following the presidential election of 2010. Nevertheless, closer relations with Russia should not adversely affect Ukraine's efforts at EU integration.

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Advances in both computer technology and the necessary mathematical models capable of capturing the geometry of arbitarily shaped objects has led to the development in this thesis of a surface generation package called 'IBSCURF' aimed at providing a more economically viable solution to free-form surface manufacture. A suit of computer programs written in FORTRAN 77 has been developed to provide computer aids for every aspect of work in designing and machining free-form surfaces. A vector-valued parametric method was used for shape description and a lofting technique employed for the construction of the surface. The development of the package 'IBSCURF' consists of two phases. The first deals with CAD. The design process commences in defining the cross-sections which are represented by uniform B-spline curves as approximations to give polygons. The order of the curve and the position and number of the polygon vertices can be used as parameters for the modification to achieve the required curves. When the definitions of the sectional curves is complete, the surface is interpolated over them by cubic cardinal splines. To use the CAD function of the package to design a mould for a plastic handle, a mathematical model was developed. To facilitate the integration of design and machining using the mathematical representation of the surface, the second phase of the package is concerned with CAM which enables the generation of tool offset positions for ball-nosed cutters and a general post-processor has been developed which automatically generates NC tape programs for any CNC milling machine. The two phases of these programs have been successfully implemented, as a CAD/CAM package for free-form surfaces on the VAX 11/750 super-minicomputer with graphics facilities for displaying drawings interactively on the terminal screen. The development of this package has been beneficial in all aspects of design and machining of free form surfaces.

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Relational demographers and dissimilarity researchers contend that group members who are dissimilar (vs. similar) to their peers in terms of a given diversity attribute (e.g. demographics, attitudes, values or traits) feel less attached to their work group, experience less satisfying and more conflicted relationships with their colleagues, and consequently are less effective. However, qualitative reviews suggest empirical findings tend to be weak and inconsistent (Chattopadhyay, Tluchowska and George, 2004; Riordan, 2000; Tsui and Gutek, 1999), and that it remains unclear when, how and to what extent such differences (i.e. relational diversity) affect group members social integration (i.e. attachment with their work group, satisfaction and conflicted relationships with their peers) and effectiveness (Riordan, 2000). This absence of meta-analytically derived effect size estimates and the lack of an integrative theoretical framework leave practitioners with inconclusive advice regarding whether the effects elicited by relational diversity are practically relevant, and if so how these should be managed. The current research develops an integrative theoretical framework, which it tests by using meta-analysis techniques and adding two further empirical studies to the literature. The first study reports a meta-analytic integration of the results of 129 tests of the relationship between relational diversity with social integration and individual effectiveness. Using meta-analytic and structural equation modelling techniques, it shows different effects of surface- and deep-level relational diversity on social integration Specifically, low levels of interdependence accentuated the negative effects of surface-level relational diversity on social integration, while high levels of interdependence accentuated the negative effects of deep-level relational diversity on social integration. The second study builds on a social self-regulation framework (Abrams, 1994) and suggests that under high levels of interdependence relational diversity is not one but two things: visibility and separation. Using ethnicity as a prominent example it was proposed that separation has a negative effect on group members effectiveness leading for those high in visibility and low in separation to overall positive additive effects, while to overall negative additive effects for those low in visibility and high in separation. These propositions were sustained in a sample of 621 business students working in 135 ethnically diverse work groups in a business simulation course over a period of 24 weeks. The third study suggests visibility has a positive effect on group members self-monitoring, while separation has a negative effect. The study proposed that high levels of visibility and low levels of separation lead to overall positive additive effects on self-monitoring but overall negative additive effects for those low in visibility and high in separation. Results from four waves of data on 261 business students working in 69 ethnically diverse work groups in a business simulation course held over a period of 24 weeks support these propositions.

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Sentiment analysis has long focused on binary classification of text as either positive or negative. There has been few work on mapping sentiments or emotions into multiple dimensions. This paper studies a Bayesian modeling approach to multi-class sentiment classification and multidimensional sentiment distributions prediction. It proposes effective mechanisms to incorporate supervised information such as labeled feature constraints and document-level sentiment distributions derived from the training data into model learning. We have evaluated our approach on the datasets collected from the confession section of the Experience Project website where people share their life experiences and personal stories. Our results show that using the latent representation of the training documents derived from our approach as features to build a maximum entropy classifier outperforms other approaches on multi-class sentiment classification. In the more difficult task of multi-dimensional sentiment distributions prediction, our approach gives superior performance compared to a few competitive baselines. © 2012 ACM.

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Visual perception begins by dissecting the retinal image into millions of small patches for local analyses by local receptive fields. However, image structures extend well beyond these receptive fields and so further processes must be involved in sewing the image fragments back together to derive representations of higher order (more global) structures. To investigate the integration process, we also need to understand the opposite process of suppression. To investigate both processes together, we measured triplets of dipper functions for targets and pedestals involving interdigitated stimulus pairs (A, B). Previous work has shown that summation and suppression operate over the full contrast range for the domains of ocularity and space. Here, we extend that work to include orientation and time domains. Temporal stimuli were 15-Hz counter-phase sine-wave gratings, where A and B were the positive and negative phases of the oscillation, respectively. For orientation, we used orthogonally oriented contrast patches (A, B) whose sum was an isotropic difference of Gaussians. Results from all four domains could be understood within a common framework in which summation operates separately within the numerator and denominator of a contrast gain control equation. This simple arrangement of summation and counter-suppression achieves integration of various stimulus attributes without distorting the underlying contrast code.

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Prior research linking demographic (e.g., age, ethnicity/race, gender, and tenure) and underlying psychological (e.g., personality, attitudes, and values) dissimilarity variables to individual group member's work-related outcomes produced mixed and contradictory results. To account for these findings, this study develops a contingency framework and tests it using meta-analytic and structural equation modelling techniques. In line with this framework, results showed different effects of surface-level (i.e., demographic) dissimilarity and deep-level (i.e., underlying psychological) dissimilarity on social integration, and ultimately on individual effectiveness related outcomes (i.e., turnover, task, and contextual performance). Specifically, surface-level dissimilarity had a negative effect on social integration under low but not under high team interdependence. In return, social integration fully mediated the negative relationship between surface-level dissimilarity and individual effectiveness related outcomes under low interdependence. In contrast, deep-level dissimilarity had a negative effect on social integration, which was stronger under high and weaker under low team interdependence. Contrary to our predictions, social integration did not mediate the negative relationship between deep-level dissimilarity and individual effectiveness related outcomes but suppressed positive direct effects of deep-level dissimilarity on individual effectiveness related outcomes. Possible explanations for these counterintuitive findings are discussed. © 2011 The British Psychological Society.

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The interlayer pores of swelling 2:1 clays provide an ideal 2-dimensional environment in which to study confined fluids. In this paper we discuss our understanding of the structure and dynamics of interlayer fluid species in expanded clays, based primarily on the outcome of recent molecular modelling and neutron scattering studies. Counterion solvation is compared with that measured in bulk solutions, and at a local level the cation-oxygen coordination is found to be remarkably similar in these two environments. However, for the monovalent ions the contribution to the first coordination shell from the clay surfaces increases with counterion radius. This gives rise to inner-sphere (surface) complexes in the case of potassium and caesium. In this context, the location of the negative clay surface charge (i.e. arising from octahedral or tetrahedral substitution) is also found to be of major importance. Divalent cations, such as calcium, eagerly solvate to form outer-sphere complexes. These complexes are able to pin adjacent clay layers together, and thereby prevent colloidal swelling. Confined water molecules form hydrogen bonds to each other and to the clays' surfaces. In this way their local environment relaxes to close to the bulk water structure within two molecular layers of the clay surface. Finally, we discuss the way in which the simple organic molecules methane, methanol and ethylene glycol behave in the interlayer region of hydrated clays. Quasi-elastic neutron scattering of isotopically labelled interlayer CH 3OD and (CH2OD)2 in deuterated clay allows us to measure the diffusion of the CH3- and CH2-groups in both clay and liquid environments. We find that in both the one-layer methanol solvates and the two-layer glycol solvates the diffusion of the most mobile organic molecules is close to that in the bulk solution.

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Modification of human islets prior to transplantation may improve long-term clinical outcome in terms of diabetes management, by supporting graft function and reducing the potential for allo-rejection. Intragraft incorporation of stem cells secreting beta (β)-cell trophic and immunomodulatory factors represents a credible approach, but requires suitable culture methods to facilitate islet alteration without compromising integrity. This study employed a three-dimensional rotational cell culture system (RCCS) to achieve modification, preserve function, and ultimately influence immune cell responsiveness to human islets. Islets underwent intentional dispersal and rotational culture-assisted aggregation with amniotic epithelial cells (AEC) exhibiting intrinsic immunomodulatory potential. Reassembled islet constructs were assessed for functional integrity, and their ability to induce an allo-response in discrete T-cell subsets determined using mixed islet:lymphocyte reaction assays. RCCS supported the formation of islet:AEC aggregates with improved insulin secretory capacity compared to unmodified islets. Further, the allo-response of peripheral blood mononuclear cell (PBMC) and purified CD4+ and CD8+ T-cell subsets to AEC-bearing grafts was significantly (p < 0.05) attenuated. Rotational culture enables pre-transplant islet modification involving their integration with immunomodulatory stem cells capable of subduing the allo-reactivity of T cells relevant to islet rejection. The approach may play a role in achieving acute and long-term graft survival in islet transplantation.

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This paper describes how dimensional variation management could be integrated throughout design, manufacture and verification, to improve quality while reducing cycle times and manufacturing cost in the Digital Factory environment. Initially variation analysis is used to optimize tolerances during product and tooling design and also results in the creation of a simplified representation of product key characteristics. This simplified representation can then be used to carry out measurability analysis and process simulation. The link established between the variation analysis model and measurement processes can subsequently be used throughout the production process to automatically update the variation analysis model in real time with measurement data. This ‘live’ simulation of variation during manufacture will allow early detection of quality issues and facilitate autonomous measurement assisted processes such as predictive shimming. A study is described showing how these principles can be demonstrated using commercially available software combined with a number of prototype applications operating as discrete modules. The commercially available modules include Catia/Delmia for product and process design, 3DCS for variation analysis and Spatial Analyzer for measurement simulation. Prototype modules are used to carry out measurability analysis and instrument selection. Realizing the full potential of Metrology in the Digital Factory will require that these modules are integrated and software architecture to facilitate this is described. Crucially this integration must facilitate the use of realtime metrology data describing the emerging assembly to update the digital model.

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The focus of this study is on the governance decisions in a concurrent channels context, in the case of uncertainty. The study examines how a firm chooses to deploy its sales force in times of uncertainty, and the subsequent performance outcome of those deployment choices. The theoretical framework is based on multiple theories of governance, including transaction cost analysis (TCA), agency theory, and institutional economics. Three uncertainty variables are investigated in this study. The first two are demand and competitive uncertainty which are considered to be industry-level market uncertainty forms. The third uncertainty, political uncertainty, is chosen as it is an important dimension of institutional environments, capturing non-economic circumstances such as regulations and political systemic issues. The study employs longitudinal secondary data from a Thai hotel chain, comprising monthly observations from January 2007 – December 2012. This hotel chain has its operations in 4 countries, Thailand, the Philippines, United Arab Emirates – Dubai, and Egypt, all of which experienced substantial demand, competitive, and political uncertainty during the study period. This makes them ideal contexts for this study. Two econometric models, both deploying Newey-West estimations, are employed to test 13 hypotheses. The first model considers the relationship between uncertainty and governance. The second model is a version of Newey-West, using an Instrumental Variables (IV) estimator and a Two-Stage Least Squares model (2SLS), to test the direct effect of uncertainty on performance and the moderating effect of governance on the relationship between uncertainty and performance. The observed relationship between uncertainty and governance observed follows a core prediction of TCA; that vertical integration is the preferred choice of governance when uncertainty rises. As for the subsequent performance outcomes, the results corroborate that uncertainty has a negative effect on performance. Importantly, the findings show that becoming more vertically integrated cannot help moderate the effect of demand and competitive uncertainty, but can significantly moderate the effect of political uncertainty. These findings have significant theoretical and practical implications, and extend our knowledge of the impact on uncertainty significantly, as well as bringing an institutional perspective to TCA. Further, they offer managers novel insight into the nature of different types of uncertainty, their impact on performance, and how channel decisions can mitigate these impacts.

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Background: Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. Methods: CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. Discussion: From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research. Trial registration: ClinicalTrials.gov identifier NCT01655706. Registered July 27, 2012.