Institutional trust - development of the construct and the scale

Organisatorisen luottamuksen tutkimuksessa luottamus nähdään yleensä henkilöiden välisenä ilmiönä kuten työntekijän luottamuksena työtovereihin, esimieheen tai lähimpään johtoon. Organisatorisessa luottamuksessa on kuitenkin myös ei-henkilöityvä ulottuvuus, ns. institutionaalinen luottamus. Tähän mennessä vain muutamat tutkijat ovat omissa tutkimuksissaan käyttäneet myös institutionaalista luottamusta osana organisatorista luottamusta. Tämän työn tavoitteena on kehittää institutionaalisen luottamuksen käsitettä sekä mittari sen havainnoimiseksi organisaatioympäristössä. Kehitysprosessi koostui kolmesta vaiheesta. Ensimmäisessä vaiheessa kehitettiin mittariin tulevia väittämiä sekä arvioitiin sisällön validiteetti. Toinen vaihe käsitti aineiston keruun, väittämien karsimisen sekä vaihtoehtoisten mallien vertailun. Kolmannessa vaiheessa arvioitiin rakennevaliditeetti sekä reliabiliteetti. Työn empiirinen osatoteutettiin internet-kyselynä aikuisopiskelijoiden keskuudessa. Aineiston analysoinnissa käytettiin pääkomponenttianalyysiä sekä konfirmatorista faktorianalyysiä. Institutionaalinen luottamus muodostuu kahdesta ulottuvuudesta: kyvykkyys ja oikeudenmukaisuus. Kyvykkyys muodostuu viidestä alakomponentista: operatiivisen toiminnan organisointi, organisaation pysyvyys, kyvykkyys liiketoiminnan ja ihmisten johtamisessa, teknologinen luotettavuus sekä kilpailukyky. Oikeudenmukaisuus puolestaan muodostuu HRM-käytännöistä, organisaatiossa vallitsevasta reilun pelin hengestä sekä kommunikaatiosta. Lopullinen mittari kyvykkyydelle käsittää 18 väittämää ja oikeudenmukaisuudelle 13 väittämää. Työssä kehitetty mittari mahdollistaa organisatorisen luottamuksen entistä paremman ja luotettavamman mittaamisen. Tutkijan tietämyksen mukaan tämä onensimmäinen kokonaisvaltainen mittari institutionaalisen luottamuksen mittaamiseksi.

Lossless compression of hyperspectral images

Technological progress has made a huge amount of data available at increasing spatial and spectral resolutions. Therefore, the compression of hyperspectral data is an area of active research. In somefields, the original quality of a hyperspectral image cannot be compromised andin these cases, lossless compression is mandatory. The main goal of this thesisis to provide improved methods for the lossless compression of hyperspectral images. Both prediction- and transform-based methods are studied. Two kinds of prediction based methods are being studied. In the first method the spectra of a hyperspectral image are first clustered and and an optimized linear predictor is calculated for each cluster. In the second prediction method linear prediction coefficients are not fixed but are recalculated for each pixel. A parallel implementation of the above-mentioned linear prediction method is also presented. Also,two transform-based methods are being presented. Vector Quantization (VQ) was used together with a new coding of the residual image. In addition we have developed a new back end for a compression method utilizing Principal Component Analysis (PCA) and Integer Wavelet Transform (IWT). The performance of the compressionmethods are compared to that of other compression methods. The results show that the proposed linear prediction methods outperform the previous methods. In addition, a novel fast exact nearest-neighbor search method is developed. The search method is used to speed up the Linde-Buzo-Gray (LBG) clustering method.

The interplay of spatial and climatic landscapes in the genetic distribution of a South American parrot

AimOur aim was to understand the interplay of heterogeneous climatic and spatial landscapes in shaping the distribution of nuclear microsatellite variation in burrowing parrots, Cyanoliseus patagonus. Given the marked phenotypic differences between populations of burrowing parrots we hypothesized an important role of geographical as well climatic heterogeneity in the population structure of this species. LocationSouthern South America. MethodsWe applied a landscape genetics approach to investigate the explicit patterns of genetic spatial autocorrelation based on both geography and climate using spatial principal component analysis (sPCA). This necessitated a novel statistical estimation of the species climatic landscape, considering temperature- and precipitation-based variables separately to evaluate their weight in shaping the distribution of genetic variation in our model system. ResultsGeographical and climatic heterogeneity successfully explained molecular variance in burrowing parrots. sPCA divided the species distribution into two main areas, Patagonia and the pre-Andes, which were connected by an area of geographical and climatic transition. Moreover, sPCA revealed cryptic and conservation-relevant genetic structure: the pre-Andean populations and the transition localities were each divided into two groups, each management units for conservation. Main conclusionssPCA, a method originally developed for spatial genetics, allowed us to unravel the genetic structure related to spatial and climatic landscapes and to visualize these patterns in landscape space. These novel climatic inferences underscore the importance of our modified sPCA approach in revealing how climatic variables can drive cryptic patterns of genetic structure, making the approach potentially useful in the study of any species distributed over a climatically heterogeneous landscape.

Cosmic censorship in two-dimensional gravity

A weak version of the cosmic censorship hypothesis is implemented as a set of boundary conditions on exact semiclassical solutions of two-dimensional dilaton gravity. These boundary conditions reflect low-energy matter from the strong coupling region and they also serve to stabilize the vacuum of the theory against decay into negative energy states. Information about low-energy incoming matter can be recovered in the final state but at high energy black holes are formed and inevitably lead to information loss at the semiclassical level.

Soluble models in two-dimensional dilaton gravity

A one-parameter class of simple models of two-dimensional dilaton gravity, which can be exactly solved including back-reaction effects, is investigated at both classical and quantum levels. This family contains the RST model as a special case, and it continuously interpolates between models having a flat (Rindler) geometry and a constant curvature metric with a nontrivial dilaton field. The processes of formation of black hole singularities from collapsing matter and Hawking evaporation are considered in detail. Various physical aspects of these geometries are discussed, including the cosmological interpretation.

Motorcycle helmets: what about their coating?

In traffic accidents involving motorcycles, paint traces can be transferred from the rider's helmet or smeared onto its surface. These traces are usually in the form of chips or smears and are frequently collected for comparison purposes. This research investigates the physical and chemical characteristics of the coatings found on motorcycles helmets. An evaluation of the similarities between helmet and automotive coating systems was also performed.Twenty-seven helmet coatings from 15 different brands and 22 models were considered. One sample per helmet was collected and observed using optical microscopy. FTIR spectroscopy was then used and seven replicate measurements per layer were carried out to study the variability of each coating system (intravariability). Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were also performed on the infrared spectra of the clearcoats and basecoats of the data set. The most common systems were composed of two or three layers, consistently involving a clearcoat and basecoat. The coating systems of helmets with composite shells systematically contained a minimum of three layers. FTIR spectroscopy results showed that acrylic urethane and alkyd urethane were the most frequent binders used for clearcoats and basecoats. A high proportion of the coatings were differentiated (more than 95%) based on microscopic examinations. The chemical and physical characteristics of the coatings allowed the differentiation of all but one pair of helmets of the same brand, model and color. Chemometrics (PCA and HCA) corroborated classification based on visual comparisons of the spectra and allowed the study of the whole data set at once (i.e., all spectra of the same layer). Thus, the intravariability of each helmet and its proximity to the others (intervariability) could be more readily assessed. It was also possible to determine the most discriminative chemical variables based on the study of the PCA loadings. Chemometrics could therefore be used as a complementary decision-making tool when many spectra and replicates have to be taken into account. Similarities between automotive and helmet coating systems were highlighted, in particular with regard to automotive coating systems on plastic substrates (microscopy and FTIR). However, the primer layer of helmet coatings was shown to differ from the automotive primer. If the paint trace contains this layer, the risk of misclassification (i.e., helmet versus vehicle) is reduced. Nevertheless, a paint examiner should pay close attention to these similarities when analyzing paint traces, especially regarding smears or paint chips presenting an incomplete layer system.

Two-dimensional probabilistic inversion of plane-wave electromagnetic data: Methodology, model constraints and joint inversion with electrical resistivity data

Probabilistic inversion methods based on Markov chain Monte Carlo (MCMC) simulation are well suited to quantify parameter and model uncertainty of nonlinear inverse problems. Yet, application of such methods to CPU-intensive forward models can be a daunting task, particularly if the parameter space is high dimensional. Here, we present a 2-D pixel-based MCMC inversion of plane-wave electromagnetic (EM) data. Using synthetic data, we investigate how model parameter uncertainty depends on model structure constraints using different norms of the likelihood function and the model constraints, and study the added benefits of joint inversion of EM and electrical resistivity tomography (ERT) data. Our results demonstrate that model structure constraints are necessary to stabilize the MCMC inversion results of a highly discretized model. These constraints decrease model parameter uncertainty and facilitate model interpretation. A drawback is that these constraints may lead to posterior distributions that do not fully include the true underlying model, because some of its features exhibit a low sensitivity to the EM data, and hence are difficult to resolve. This problem can be partly mitigated if the plane-wave EM data is augmented with ERT observations. The hierarchical Bayesian inverse formulation introduced and used herein is able to successfully recover the probabilistic properties of the measurement data errors and a model regularization weight. Application of the proposed inversion methodology to field data from an aquifer demonstrates that the posterior mean model realization is very similar to that derived from a deterministic inversion with similar model constraints.

Sensory profiles of chocolates produced from cocoa cultivars resistant to Moniliophtora Perniciosa

The present study evaluated the sensory quality of chocolates obtained from two cocoa cultivars (PH16 and SR162) resistant to Moniliophtora perniciosa mould comparing to a conventional cocoa that is not resistant to the disease. The acceptability of the chocolates was assessed and the promising cultivars with relevant sensory and commercial attributes could be indicated to cocoa producers and chocolate manufacturers. The descriptive terminology and the sensory profile of chocolates were developed by Quantitative Descriptive Analysis (QDA). Ten panelists, selected on the basis of their discriminatory capacity and reproducibility, defined eleven sensory descriptors, their respective reference materials and the descriptive evaluation ballot. The data were analyzed using ANOVA, Principal Component Analysis (PCA) and Tukey's test to compare the means. The results revealed significant differences among the sensory profiles of the chocolates. Chocolates from the PH16 cultivar were characterized by a darker brown color, more intense flavor and odor of chocolate, bitterness and a firmer texture, which are important sensory and commercial attributes. Chocolates from the SR162 cultivar were characterized by a greater sweetness and melting quality and chocolates from the conventional treatment presented intermediate sensory characteristics between those of the other two chocolates. All samples indicated high acceptance, but chocolates from the PH16 and conventional cultivars obtained higher purchase intention scores.

Social trust : a public good?

Combining theories on social trust and social capital with sociopsychological approaches and applying contextual analyses to Swiss and European survey data, this thesis examines under what circumstances generalised trust, often understood as public good, may not benefit everyone, but instead amplify inequality. The empirical investigation focuses on the Swiss context, but considers different scales of analysis. Two broader questions are addressed. First, might generalised trust imply more or less narrow visions of community and solidarity in different contexts? Applying nonlinear principal component analysis to aggregate indicators, Study 1 explores inclusive and exclusive types of social capital in Europe, measured as regional configurations of generalised trust, civic participation and attitudes towards diversity. Study 2 employs multilevel models to examine how generalised trust, as an individual predisposition and an aggregate climate at the level of Swiss cantons, is linked to equality- directed collective action intention versus radical right support. Second, might high-trust climates impact negatively on disadvantaged members of society, precisely because they reflect a normative discourse of social harmony that impedes recognition of inequality? Study 3 compares how climates of generalised trust at the level of Swiss micro-regions and subjective perceptions of neighbourhood cohesion moderate the negative relationship between socio-economic disadvantage and mental health. Overall, demonstrating beneficial, as well as counterintuitive effects of social trust, this thesis proposes a critical and contextualised approach to the sources and dynamics of social cohesion in democratic societies. -- Cette thèse combine des théories sur le capital social et la confiance sociale avec des approches psychosociales et s'appuie sur des analyses contextuelles de données d'enquêtes suisses et européennes, afin d'étudier dans quelles circonstances la confiance généralisée, souvent présentée comme un bien public, pourrait ne pas bénéficier à tout le monde, mais amplifier les inégalités. Les études empiriques, centrées sur le contexte suisse, intègrent différentes échelles d'analyse et investiguent deux questions principales. Premièrement, la confiance généralisée implique-t-elle des visions plus ou moins restrictives de la communauté et de la solidarité selon le contexte? Dans l'étude 1, une analyse à composantes principales non-linéaire sur des indicateurs agrégés permet d'explorer des types de capital social inclusif et exclusif en Europe, mesurés par des configurations régionales de confiance généralisée, de participation civique, et d'attitudes envers la diversité. L'étude 2 utilise des modèles multiniveaux afin d'analyser comment la confiance généralisée, en tant que prédisposition individuelle et climat agrégé au niveau des cantons suisses, est associée à l'intention de participer à des actions collectives en faveur de l'égalité ou, au contraire, à l'intention de voter pour la droite radicale. Deuxièmement, des climats de haute confiance peuvent-ils avoir un impact négatif sur des membres désavantagés de la société, précisément parce qu'ils reflètent un discours normatif d'harmonie sociale qui empêche la reconnaissance des inégalités? L'étude 3 analyse comment des climats de confiance au niveau des micro-régions suisses et la perception subjective de faire partie d'un environnement cohésif modèrent la relation négative entre le désavantage socio-économique et la santé mentale. En démontrant des effets bénéfiques mais aussi contre-intuitifs de la confiance sociale, cette thèse propose une approche critique et contextualisée des sources et dynamiques de la cohésion sociale dans les sociétés démocratiques.

Combined T2 -preparation and two-dimensional pencil-beam inner volume selection.

PURPOSE: To improve coronary magnetic resonance angiography (MRA) by combining a two-dimensional (2D) spatially selective radiofrequency (RF) pulse with a T2 -preparation module ("2D-T2 -Prep"). METHODS: An adiabatic T2 -Prep was modified so that the first and last pulses were of differing spatial selectivity. The first RF pulse was replaced by a 2D pulse, such that a pencil-beam volume is excited. The last RF pulse remains nonselective, thus restoring the T2 -prepared pencil-beam, while tipping the (formerly longitudinal) magnetization outside of the pencil-beam into the transverse plane, where it is then spoiled. Thus, only a cylinder of T2 -prepared tissue remains for imaging. Numerical simulations were followed by phantom validation and in vivo coronary MRA, where the technique was quantitatively evaluated. Reduced field-of-view (rFoV) images were similarly studied. RESULTS: In vivo, full field-of-view 2D-T2 -Prep significantly improved vessel sharpness as compared to conventional T2 -Prep, without adversely affecting signal-to-noise (SNR) or contrast-to-noise ratios (CNR). It also reduced respiratory motion artifacts. In rFoV images, the SNR, CNR, and vessel sharpness decreased, although scan time reduction was 60%. CONCLUSION: When compared with conventional T2 -Prep, the 2D-T2 -Prep improves vessel sharpness and decreases respiratory ghosting while preserving both SNR and CNR. It may also acquire rFoV images for accelerated data acquisition.

Does phylogeographic structure relate to climatic niche divergence? A test using maritime pine (Pinus pinaster Ait.)

Aim To disentangle the effects of environmental and geographical processes driving phylogenetic distances among clades of maritime pine (Pinus pinaster). To assess the implications for conservation management of combining molecular information with species distribution models (SDMs; which predict species distribution based on known occurrence records and on environmental variables). Location Western Mediterranean Basin and European Atlantic coast. Methods We undertook two cluster analyses for eight genetically defined pine clades based on climatic niche and genetic similarities. We assessed niche similarity by means of a principal component analysis and Schoener's D metric. To calculate genetic similarity, we used the unweighted pair group method with arithmetic mean based on Nei's distance using 266 single nucleotide polymorphisms. We then assessed the contribution of environmental and geographical distances to phylogenetic distance by means of Mantel regression with variance partitioning. Finally, we compared the projection obtained from SDMs fitted from the species level (SDMsp) and composed from the eight clade-level models (SDMcm). Results Genetically and environmentally defined clusters were identical. Environmental and geographical distances explained 12.6% of the phylogenetic distance variation and, overall, geographical and environmental overlap among clades was low. Large differences were detected between SDMsp and SDMcm (57.75% of disagreement in the areas predicted as suitable). Main conclusions The genetic structure within the maritime pine subspecies complex is primarily a consequence of its demographic history, as seen by the high proportion of unexplained variation in phylogenetic distances. Nevertheless, our results highlight the contribution of local environmental adaptation in shaping the lower-order, phylogeographical distribution patterns and spatial genetic structure of maritime pine: (1) genetically and environmentally defined clusters are consistent, and (2) environment, rather than geography, explained a higher proportion of variation in phylogenetic distance. SDMs, key tools in conservation management, better characterize the fundamental niche of the species when they include molecular information.

Information transfer between large and small two-dimensional polyacrylamide gel electrophoresis.

To determine the feasibility of data transfer, an interlaboratory comparison was conducted on colon carcinoma cell line (DLD-1) proteins resolved by two-dimensional polyacrylamide gel electrophoresis either on small (6 x 7 cm) or large (16x18 cm) gels. The gels were silver-stained and scanned by laser densitometry, and the image obtained was analyzed using Melanie software. The number of spots detected was 1337+/-161 vs. 2382+/-176 for small vs. large format gels, respectively. After gel calibration using landmarks determined using pl and Mr markers, large- and small-format gels were matched and 712+/-36 proteins were found on both types of gels. Having performed accurate gel matching it was possible to acquire additional information after accessing a 2-D PAGE reference database (http://www.expasy.ch/ cgibin/map2/def?DLD1_HUMAN). Thus, the difference in gel size is not an obstacle for data transfer. This will facilitate exchanges between laboratories or consultation concerning existing databases.

Measuring early childhood health : a composite index comparing Colombian departments

This paper presents a composite index of early childhood health using a multivariate statistical approach. The index shows how child health varies across Colombian departments, -administrative subdivisions-. In recent years there has been growing interest in composite indicators as an efficient analysis tool and a way of prioritizing policies. These indicators not only enable multi-dimensional phenomena to be simplified but also make it easier to measure, visualize, monitor and compare a country’s performance in particular issues. We used data collected from the Colombian Demographic and Health Survey, DHS, for 32 departments and the capital city, Bogotá, in 2005 and 2010. The variables included in the index provide a measure of three dimensions related to child health: health status, health determinants and the health system. In order to generate the weight of the variables and take into account the discrete nature of the data, we employed a principal component analysis, PCA, using polychoric correlation. From this method, five principal components were selected. The index was estimated using a weighted average of the components retained. A hierarchical cluster analysis was also carried out. We observed that the departments ranking in the lowest positions are located on the Colombian periphery. They are departments with low per capita incomes and they present critical social indicators. The results suggest that the regional disparities in child health may be associated with differences in parental characteristics, household conditions and economic development levels, which makes clear the importance of context in the study of child health in Colombia.

Uma introdução à análise exploratória de dados multivariados

The modern technological ability to handle large amounts of information confronts the chemist with the necessity to re-evaluate the statistical tools he routinely uses. Multivariate statistics furnishes theoretical bases for analyzing systems involving large numbers of variables. The mathematical calculations required for these systems are no longer an obstacle due to the existence of statistical packages that furnish multivariate analysis options. Here basic concepts of two multivariate statistical techniques, principal component and hierarchical cluster analysis that have received broad acceptance for treating chemical data are discussed.