Individual and societal bases of national identity - A comparative multi-level analysis

In a previous study (Jones and Smith, 1999) we established that much the same core pattern of national identity characterizes many developed countries. Using the national identity module from the 1995 International Social Survey Programme, we identified two dimensions of national identity: an ascriptive dimension resembling the concept of ethnic identity described in the historical and theoretical literature, and a voluntarist dimension closer to the notion of civic identity. Some writers view these dimensions in terms of a historical sequence but we find that both constructs coexist in the minds of individual respondents in the nations we examine (we exclude Bulgaria and the Philippines from the present but not the earlier analysis). The dataset used for the multilevel analyses reported here consists of 28 589 respondents in the remaining 21 countries included in the national identity database for the 1995 round of surveys. The macrosociological literature on national identity does not offer well-defined predictions about what precise patterns of national identification we might expect to find among the masses of the developed countries. There are, however, recurring themes from which one can construct plausible hypotheses about how countries might differ according to their level of development, broadly conceived. Thus, we hypothesize that forces such as post-industrialism and globalization tend to favour the more open voluntaristic form of national identity over the more restrictive ascribed form. We develop different multi-level models in order to evaluate specific hypotheses pertaining to such issues, by simultaneously relating individual and societal characteristics to the relative strength of individual commitment to these different types of national identity.

Concepts and tools for comprehensive sustainability assessments for tourism destinations: a comparative review

This paper reviews a wide range of tools for comprehensive sustainability assessments at whole tourism destinations, covering socio-cultural, economic and environmental issues. It considers their strengths, weaknesses and site specific applicability. It is intended to facilitate their selection (and combination where necessary). Tools covered include Sustainability Indicators, Environmental Impact Assessment, Life Cycle Assessment, Environmental Audits, Ecological Footprints, Multi-Criteria Analysis and Adaptive Environmental Assessment. Guidelines for evaluating their suitability for specific sites and situations are given as well as examples of their use.

Chemical analysis of powdered metallurgical slags by X-ray fluorescence spectrometry

Slag composition determines the physical and chemical properties as well as the application performance of molten oxide mixtures. Therefore, it is necessary to establish a routine instrumental technique to produce accurate and precise analytical results for better process and production control. In the present paper, a multi-component analysis technique of powdered metallurgical slag samples by X-ray Fluorescence Spectrometer (XRFS) has been demonstrated. This technique provides rapid and accurate results, with minimum sample preparation. It eliminates the requirement for a fused disc, using briquetted samples protected by a layer of Borax(R). While the use of theoretical alpha coefficients has allowed accurate calibrations to be made using fewer standard samples, the application of pseudo-Voight function to curve fitting makes it possible to resolve overlapped peaks in X-ray spectra that cannot be physically separated. The analytical results of both certified reference materials and industrial slag samples measured using the present technique are comparable to those of the same samples obtained by conventional fused disc measurements.

Use of the EM algorithm to detect QTL affecting multiple-traits in an across half-sib family analysis

QTL detection experiments in livestock species commonly use the half-sib design. Each male is mated to a number of females, each female producing a limited number of progeny. Analysis consists of attempting to detect associations between phenotype and genotype measured on the progeny. When family sizes are limiting experimenters may wish to incorporate as much information as possible into a single analysis. However, combining information across sires is problematic because of incomplete linkage disequilibrium between the markers and the QTL in the population. This study describes formulae for obtaining MLEs via the expectation maximization (EM) algorithm for use in a multiple-trait, multiple-family analysis. A model specifying a QTL with only two alleles, and a common within sire error variance is assumed. Compared to single-family analyses, power can be improved up to fourfold with multi-family analyses. The accuracy and precision of QTL location estimates are also substantially improved. With small family sizes, the multi-family, multi-trait analyses reduce substantially, but not totally remove, biases in QTL effect estimates. In situations where multiple QTL alleles are segregating the multi-family analysis will average out the effects of the different QTL alleles.

Confirmatory factor analysis and psychometric properties of the Anxiety Sensitivity Index-Revised in clinical and normative populations

The present investigation aimed to critically examine the factor structure and psychometric properties of the Anxiety Sensitivity Index - Revised (ASI-R). Confirmatory factor analysis using a clinical sample of adults (N = 248) revealed that the ASI-R could be improved substantially through the removal of 15 problematic items in order to account for the most robust dimensions of anxiety sensitivity. This modified scale was renamed the 21-item Anxiety Sensitivity Index (21-item ASI) and reanalyzed with a large sample of normative adults (N = 435), revealing configural and metric invariance across groups. Further comparisons with other alternative models, using multi-sample analysis, indicated the 21-item ASI to be the best fitting model for both groups. There was also evidence of internal consistency, test-retest reliability, and construct validity for both samples suggesting that the 21-item ASI is a useful assessment device for investigating the construct of anxiety sensitivity in both clinical and normative populations.

A way forward for land-use planning to achieve policy goals by using spatial modelling scenarios

This paper investigates how demographic (socioeconomic) and land-use (physical and environmental) data can be integrated within a decision support framework to formulate and evaluate land-use planning scenarios. A case-study approach is undertaken with land-use planning scenarios for a rapidly growing coastal area in Australia, the Shire of Hervey Bay. The town and surrounding area require careful planning of the future urban growth between competing land uses. Three potential urban growth scenarios are put forth to address this issue. Scenario A ('continued growth') is based on existing socioeconomic trends. Scenario B ('maximising rates base') is derived using optimisation modelling of land-valuation data. Scenario C ('sustainable development') is derived using a number of social, economic, and environmental factors and assigning weightings of importance to each factor using a multiple criteria analysis approach. The land-use planning scenarios are presented through the use of maps and tables within a geographical information system, which delineate future possible land-use allocations up until 2021. The planning scenarios are evaluated by using a goal-achievement matrix approach. The matrix is constructed with a number of criteria derived from key policy objectives outlined in the regional growth management framework and town planning schemes. The authors of this paper examine the final efficiency scores calculated for each of the three planning scenarios and discuss the advantages and disadvantages of the three land-use modelling approaches used to formulate the final scenarios.

Monitoring the condition of savanna riparian zones in Northern Australia using high spatial resolution imagery and a field based rapid assessment method

Government agencies responsible for riparian environments are assessing the combined utility of field survey and remote sensing for mapping and monitoring indicators of riparian zone condition. The objective of this work was to compare the Tropical Rapid Appraisal of Riparian Condition (TRARC) method to a satellite image based approach. TRARC was developed for rapid assessment of the environmental condition of savanna riparian zones. The comparison assessed mapping accuracy, representativeness of TRARC assessment, cost-effectiveness, and suitability for multi-temporal analysis. Two multi-spectral QuickBird images captured in 2004 and 2005 and coincident field data covering sections of the Daly River in the Northern Territory, Australia were used in this work. Both field and image data were processed to map riparian health indicators (RHIs) including percentage canopy cover, organic litter, canopy continuity, stream bank stability, and extent of tree clearing. Spectral vegetation indices, image segmentation and supervised classification were used to produce RHI maps. QuickBird image data were used to examine if the spatial distribution of TRARC transects provided a representative sample of ground based RHI measurements. Results showed that TRARC transects were required to cover at least 3% of the study area to obtain a representative sample. The mapping accuracy and costs of the image based approach were compared to those of the ground based TRARC approach. Results proved that TRARC was more cost-effective at smaller scales (1-100km), while image based assessment becomes more feasible at regional scales (100-1000km). Finally, the ability to use both the image and field based approaches for multi-temporal analysis of RHIs was assessed. Change detection analysis demonstrated that image data can provide detailed information on gradual change, while the TRARC method was only able to identify more gross scale changes. In conclusion, results from both methods were considered to complement each other if used at appropriate spatial scales.

Precision-recall operating characteristic (P-ROC) curves in imprecise environments

Traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. In this paper, we consider the case of imprecise environments, where little may be known about these factors and they may well vary significantly when the system is applied. Specifically, the use of precision-recall analysis is investigated and compared to the more well known performance measures such as error-rate and the receiver operating characteristic (ROC). We argue that while ROC analysis is invariant to variations in class priors, this invariance in fact hides an important factor of the evaluation in imprecise environments. Therefore, we develop a generalised precision-recall analysis methodology in which variation due to prior class probabilities is incorporated into a multi-way analysis of variance (ANOVA). The increased sensitivity and reliability of this approach is demonstrated in a remote sensing application.

Analysis of dynamic models for structural insight and model reduction .2. A multi-stage compressor shutdown case-study

In this second paper, the three structural measures which have been developed are used in the modelling of a three stage centrifugal synthesis gas compressor. The goal of this case study is to determine the essential mathematical structure which must be incorporated into the compressor model to accurately model the shutdown of this system. A simple, accurate and functional model of the system is created via three structural measures. It was found that the model can be correctly reduced into its basic modes and that the order of the differential system can be reduced from 51(st) to 20(th). Of the 31 differential equational 21 reduce to algebraic relations, 8 become constants and 2 can be deleted thereby increasing the algebraic set from 70 to 91 equations. An interpretation is also obtained as to which physical phenomena are dominating the dynamics of the compressor add whether the compressor will enter surge during the shutdown. Comparisons of the reduced model performance against the full model are given, showing the accuracy and applicability of the approach. Copyright (C) 1996 Elsevier Science Ltd

Some vocabulary and grammar for the analysis of multi-environment trials, as applied to the analysis of FPB and PPB trials

For the improvement of genetic material suitable for on farm use under low-input conditions, participatory and formal plant breeding strategies are frequently presented as competing options. A common frame of reference to phrase mechanisms and purposes related to breeding strategies will facilitate clearer descriptions of similarities and differences between participatory plant breeding and formal plant breeding. In this paper an attempt is made to develop such a common framework by means of a statistically inspired language that acknowledges the importance of both on farm trials and research centre trials as sources of information for on farm genetic improvement. Key concepts are the genetic correlation between environments, and the heterogeneity of phenotypic and genetic variance over environments. Classic selection response theory is taken as the starting point for the comparison of selection trials (on farm and research centre) with respect to the expected genetic improvement in a target environment (low-input farms). The variance-covariance parameters that form the input for selection response comparisons traditionally come from a mixed model fit to multi-environment trial data. In this paper we propose a recently developed class of mixed models, namely multiplicative mixed models, also called factor-analytic models, for modelling genetic variances and covariances (correlations). Mixed multiplicative models allow genetic variances and covariances to be dependent on quantitative descriptors of the environment, and confer a high flexibility in the choice of variance-covariance structure, without requiring the estimation of a prohibitively high number of parameters. As a result detailed considerations regarding selection response comparisons are facilitated. ne statistical machinery involved is illustrated on an example data set consisting of barley trials from the International Center for Agricultural Research in the Dry Areas (ICARDA). Analysis of the example data showed that participatory plant breeding and formal plant breeding are better interpreted as providing complementary rather than competing information.