Images of Europeans: In-Group Trust and Support for European Integration. Jean Monnet/Robert Schuman Paper Series Vol. 14 No. 3, March 2014

Prior research on citizen support for European integration does not consider how individuals’ evaluations of European nationalities are associated with support. This paper fills this gap by developing a political cohesion model based on social identity theory. I claim that the probability of supporting integration increases with greater levels of trust in fellow Europeans, which assumes to reflect their positive images. Also, trust in eastern European Union nationalities has the highest impact on the probability for support, followed by trust in the southern nationalities, and then northern nationalities due to the eastern and southern nationalities relatively lower economic development. Controlling for various factors, the ordered logistic regression analysis of the European Election Study (2004) data support these claims.

Spatial distribution of key zooplankton species using continuous plankton recorder (CPR) data from the North Atlantic (2000-2009)

The continuous plankton recorder (CPR) survey is an upper layer plankton monitoring program that has regularly collected samples, at monthly intervals, in the North Atlantic and adjacent seas since 1946. Water from approximately 6 m depth enters the CPR through a small aperture at the front of the sampler and travels down a tunnel where it passes through a silk filtering mesh of 270 µm before exiting at the back of the CPR. The plankton filtered on the silk is analyzed in sections corresponding to 10 nautical miles (approx. 3 m**3 of seawater filtered) and the plankton microscopically identified (Richardson et al., 2006 and reference therein). In the present study we used the CPR data to investigate the current basin scale distribution of C. finmarchicus (C5-C6), C. helgolandicus (C5-C6), C. hyperboreus (C5-C6), Pseudocalanus spp. (C6), Oithona spp. (C1-C6), total Euphausiida, total Thecosomata and the presence/absence of Cnidaria and the Phytoplankton Colour Index (PCI). The PCI, which is a visual assessment of the greenness of the silk, is used as an indicator of the distribution of total phytoplankton biomass across the Atlantic basin (Batten et al., 2003). Monthly data collected between 2000 and 2009 were gridded using the inverse-distance interpolation method, in which the interpolated values were the nodes of a 2 degree by 2 degree grid. The resulting twelve monthly matrices were then averaged within the year and in the case of the zooplankton the data were log-transformed (i.e. log10 (x+1).

Micromesistius poutassou (blue whiting) abundance and biomass data in Bay of Biscay estimated from acoustic surveys (2000-2012)

Acoustic and pelagic trawl data were collected during various pelagic surveys carried out by IFREMER in May between 2000 and 2012 (except 2001), on the eastern continental shelf of the Bay of Biscay (Pelgas series). The acoustic data were collected with a Simrad EK60 echosounder operating at 38 kHz (beam angle at -3 dB: 7°, pulse length set to 1.024 ms). The echosounder transducer was mounted on the vessel keel, at 6 m below the sea surface. The sampling design were parallel transects spaced 12 nm apart which were orientated perpendicular to the coast line from 20 m to about 200 m bottom depth. The nominal sailing speed was 10 knots and 3 knots on average during fishing operations. The scrutinising (species identification) of acoustic data was done by first characterising acoustic schools by type and then linking these types with the species composition of specific trawl hauls. The data set contains nautical area backscattering values, biomass and abundance estimates for blue whiting for one nautical mile long transect lines. Further information on the survey design, scrutinising and biomass estimation can be found in Doray et al. 2012.

Survey bottom trawl data of Micromesistius poutassou (blue whiting) in Bay of Biscay and Celtic Sea from the EVHOE time series (1997-2011)

Data were collected during various groundfish surveys carried out by IFREMER from October to December between 1997 and 2011, on the eastern continental shelf of the Bay of Biscay and in the Celtic Sea (EVHOE series). The sampling design was stratified according to latitude and depth. A 36/47 GOV trawl was used with a 20 mm mesh codend liner. Haul duration was 30 minutes at a towing speed of 4 knots. Fishing was restricted to daylight hours. Catch weights and catch numbers were recorded for all species and body size measured. The weights and numbers per haul were transformed into abundances per km**2 by considering the swept area of a standard haul (0.069 km**2).

Responses to a merger: The effects of premerger group status and integration pattern

Adopting a social identity perspective, the research was designed to examine the interplay between premerger group status and integration pattern in the prediction of responses to a merger. The research employed a 2 (status: high versus low) x 3 (integration pattern: assimilation versus integrational equality versus transformation) between-participants factorial design. We predicted that integration pattern and group status would interact such that the responses of the members of high status group would be most positive under conditions of an assimilation pattern, whereas members of low status groups were expected to favour an integration-equality pattern. After working on a task in small groups, group status was manipulated and the groups worked on a second task. The merger was then announced and the integration pattern was manipulated (e.g., in terms of the logo, location, and decision rules). The main dependent variables were assessed after the merged groups had worked together on a third task. As expected, there was evidence that the effects of group status on responses to the merger were moderated by integration pattern. Field data also indicated that both premerger status and perceived integration pattern influenced employee responses to an organisational merger.

Data-driven fuzzy analysis in quantitative mineral resource assessment

The integration of geo-information from multiple sources and of diverse nature in developing mineral favourability indexes (MFIs) is a well-known problem in mineral exploration and mineral resource assessment. Fuzzy set theory provides a convenient framework to combine and analyse qualitative and quantitative data independently of their source or characteristics. A novel, data-driven formulation for calculating MFIs based on fuzzy analysis is developed in this paper. Different geo-variables are considered fuzzy sets and their appropriate membership functions are defined and modelled. A new weighted average-type aggregation operator is then introduced to generate a new fuzzy set representing mineral favourability. The membership grades of the new fuzzy set are considered as the MFI. The weights for the aggregation operation combine the individual membership functions of the geo-variables, and are derived using information from training areas and L, regression. The technique is demonstrated in a case study of skarn tin deposits and is used to integrate geological, geochemical and magnetic data. The study area covers a total of 22.5 km(2) and is divided into 349 cells, which include nine control cells. Nine geo-variables are considered in this study. Depending on the nature of the various geo-variables, four different types of membership functions are used to model the fuzzy membership of the geo-variables involved. (C) 2002 Elsevier Science Ltd. All rights reserved.

A new perspective on the integration responsiveness pressures confronting multinational firms

The Integration-Responsiveness framework of Prahalad and Doz (1987) has been used extensively in the international business literature to typify the diverse and often-conflicting environmental pressures confronting firms as they expand worldwide. Although the IR framework has been successfully applied for over a decade, many theoretical and empirical studies have focused on the consequences of these pressures rather than the pressures themselves. Prahalad and Doz identified the economic, technological, political, customer and competitive factors that create the global integration and local responsiveness pressures on the diverse businesses and functions in MNEs. This article explains the methodology, including the procedure for data collection and analysis. The researchers conclude with a discussion of their findings and directions for future research, speculating as to the appropriate definition of the domain of IR pressures and the criteria they might use to validate measures of these.

Information integration in molecular bioscience

Integrating information in the molecular biosciences involves more than the cross-referencing of sequences or structures. Experimental protocols, results of computational analyses, annotations and links to relevant literature form integral parts of this information, and impart meaning to sequence or structure. In this review, we examine some existing approaches to integrating information in the molecular biosciences. We consider not only technical issues concerning the integration of heterogeneous data sources and the corresponding semantic implications, but also the integration of analytical results. Within the broad range of strategies for integration of data and information, we distinguish between platforms and developments. We discuss two current platforms and six current developments, and identify what we believe to be their strengths and limitations. We identify key unsolved problems in integrating information in the molecular biosciences, and discuss possible strategies for addressing them including semantic integration using ontologies, XML as a data model, and graphical user interfaces as integrative environments.

Formal considerations of rule-based messaging for Business Process Integration

In the last decade, with the expansion of organizational scope and the tendency for outsourcing, there has been an increasing need for Business Process Integration (BPI), understood as the sharing of data and applications among business processes. The research efforts and development paths in BPI pursued by many academic groups and system vendors, targeting heterogeneous system integration, continue to face several conceptual and technological challenges. This article begins with a brief review of major approaches and emerging standards to address BPI. Further, we introduce a rule-driven messaging approach to BPI, which is based on the harmonization of messages in order to compose a new, often cross-organizational process. We will then introduce the design of a temporal first order language (Harmonized Messaging Calculus) that provides the formal foundation for general rules governing the business process execution. Definitions of the language terms, formulae, safety, and expressiveness are introduced and considered in detail.

Modelling pre-clearing vegetation distribution using GIS-integrated statistical, ecological and data models: A case study from the wet tropics of Northeastern Australia

Traditional vegetation mapping methods use high cost, labour-intensive aerial photography interpretation. This approach can be subjective and is limited by factors such as the extent of remnant vegetation, and the differing scale and quality of aerial photography over time. An alternative approach is proposed which integrates a data model, a statistical model and an ecological model using sophisticated Geographic Information Systems (GIS) techniques and rule-based systems to support fine-scale vegetation community modelling. This approach is based on a more realistic representation of vegetation patterns with transitional gradients from one vegetation community to another. Arbitrary, though often unrealistic, sharp boundaries can be imposed on the model by the application of statistical methods. This GIS-integrated multivariate approach is applied to the problem of vegetation mapping in the complex vegetation communities of the Innisfail Lowlands in the Wet Tropics bioregion of Northeastern Australia. The paper presents the full cycle of this vegetation modelling approach including sampling sites, variable selection, model selection, model implementation, internal model assessment, model prediction assessments, models integration of discrete vegetation community models to generate a composite pre-clearing vegetation map, independent data set model validation and model prediction's scale assessments. An accurate pre-clearing vegetation map of the Innisfail Lowlands was generated (0.83r(2)) through GIS integration of 28 separate statistical models. This modelling approach has good potential for wider application, including provision of. vital information for conservation planning and management; a scientific basis for rehabilitation of disturbed and cleared areas; a viable method for the production of adequate vegetation maps for conservation and forestry planning of poorly-studied areas. (c) 2006 Elsevier B.V. All rights reserved.

Data flow and validation in workflow modelling

A complete workflow specification requires careful integration of many different process characteristics. Decisions must be made as to the definitions of individual activities, their scope, the order of execution that maintains the overall business process logic, the rules governing the discipline of work list scheduling to performers, identification of time constraints and more. The goal of this paper is to address an important issue in workflows modelling and specification, which is data flow, its modelling, specification and validation. Researchers have neglected this dimension of process analysis for some time, mainly focussing on structural considerations with limited verification checks. In this paper, we identify and justify the importance of data modelling in overall workflows specification and verification. We illustrate and define several potential data flow problems that, if not detected prior to workflow deployment may prevent the process from correct execution, execute process on inconsistent data or even lead to process suspension. A discussion on essential requirements of the workflow data model in order to support data validation is also given..

Methods for Categorical Longitudinal Survey Data: Understanding Employment Status of Australian Women

Many variables that are of interest in social science research are nominal variables with two or more categories, such as employment status, occupation, political preference, or self-reported health status. With longitudinal survey data it is possible to analyse the transitions of individuals between different employment states or occupations (for example). In the statistical literature, models for analysing categorical dependent variables with repeated observations belong to the family of models known as generalized linear mixed models (GLMMs). The specific GLMM for a dependent variable with three or more categories is the multinomial logit random effects model. For these models, the marginal distribution of the response does not have a closed form solution and hence numerical integration must be used to obtain maximum likelihood estimates for the model parameters. Techniques for implementing the numerical integration are available but are computationally intensive requiring a large amount of computer processing time that increases with the number of clusters (or individuals) in the data and are not always readily accessible to the practitioner in standard software. For the purposes of analysing categorical response data from a longitudinal social survey, there is clearly a need to evaluate the existing procedures for estimating multinomial logit random effects model in terms of accuracy, efficiency and computing time. The computational time will have significant implications as to the preferred approach by researchers. In this paper we evaluate statistical software procedures that utilise adaptive Gaussian quadrature and MCMC methods, with specific application to modeling employment status of women using a GLMM, over three waves of the HILDA survey.

Data visualization during the early stages of drug discovery

Multidimensional compound optimization is a new paradigm in the drug discovery process, yielding efficiencies during early stages and reducing attrition in the later stages of drug development. The success of this strategy relies heavily on understanding this multidimensional data and extracting useful information from it. This paper demonstrates how principled visualization algorithms can be used to understand and explore a large data set created in the early stages of drug discovery. The experiments presented are performed on a real-world data set comprising biological activity data and some whole-molecular physicochemical properties. Data visualization is a popular way of presenting complex data in a simpler form. We have applied powerful principled visualization methods, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), to help the domain experts (screening scientists, chemists, biologists, etc.) understand and draw meaningful decisions. We also benchmark these principled methods against relatively better known visualization approaches, principal component analysis (PCA), Sammon's mapping, and self-organizing maps (SOMs), to demonstrate their enhanced power to help the user visualize the large multidimensional data sets one has to deal with during the early stages of the drug discovery process. The results reported clearly show that the GTM and HGTM algorithms allow the user to cluster active compounds for different targets and understand them better than the benchmarks. An interactive software tool supporting these visualization algorithms was provided to the domain experts. The tool facilitates the domain experts by exploration of the projection obtained from the visualization algorithms providing facilities such as parallel coordinate plots, magnification factors, directional curvatures, and integration with industry standard software. © 2006 American Chemical Society.

Integration and devolvement of human resource practices in Nepal

Purpose: The purpose of this study is to explore the nature of human resource management in publicly listed finance sector companies in Nepal. In particular, it explores the extent to which HR practice is integrated into organisational strategy and devolved to line management. Design/methodology/ approach: A structured interview was conducted with the senior executive responsible for human resource management in 26 commercial banks and insurance companies in Nepal. Findings: The degree of integration of HR practice appears to be increasing within this sector, but this is dependent on the maturity of the organisations. The devolvement of responsibility to line managers is at best partial, and in the case of the insurance companies, it is more out of necessity due to the absence of a strong central HR function. Research limitations/implications: The survey is inevitably based on a small sample; however this represents 90 per cent of the relevant population. The data suggest that Western HR is making inroads into more developed aspects of Nepalese business. Compared with Nepalese business as a whole, the financial sector appears relatively Westernised, although Nepal still lags India in its uptake of HR practices. Practical implications: It appears unlikely from a cultural perspective that the devolvement of responsibility will be achieved as a result of HR strategy. National cultural, political and social factors continue to be highly influential in shaping the Nepalese business environment. Originality/value: Few papers have explored HR practice in Nepal. This paper contributes to the overall assessment of HR uptake globally and highlights emic features impacting on that uptake. © Emerald Group Publishing Limited.