Sensory profile and drivers of liking for grape nectar among smoker and nonsmoker consumers

Decreased gustatory and olfactory capacity is one of the problems caused by tobacco use. The objectives of this study were to determine the sensory profile of six grape nectar samples sweetened with different sweeteners and to verify the drivers of liking in two distinct consumer groups: smokers and nonsmokers. The sensory profile was constructed by twelve trained panelists using quantitative descriptive analysis (QDA). Consumer tests were performed with 112 smokers and 112 nonsmokers. Partial least squares regression analyses was used to identify the drivers of acceptance and rejection of the grape nectars among the two consumer groups. According to the QDA, the samples differed regarding six of the nineteen attributes generated. The absolute averages of the affective test were lower in the group of smokers; possibly because smoking influences acceptance and eating preferences, especially with regard to sweet foods. The results showed that the grape flavor was the major driver of preference for acceptance of the nectar, while astringency, wine aroma, bitterness and sweetness, and bitter aftertaste were drivers of rejection in the two groups of consumers, with some differences between the groups.

Spectral Analysis of Symmetric and Anti-Symmetric Pairwise Kernels

This work investigates theoretical properties of symmetric and anti-symmetric kernels. First chapters give an overview of the theory of kernels used in supervised machine learning. Central focus is on the regularized least squares algorithm, which is motivated as a problem of function reconstruction through an abstract inverse problem. Brief review of reproducing kernel Hilbert spaces shows how kernels define an implicit hypothesis space with multiple equivalent characterizations and how this space may be modified by incorporating prior knowledge. Mathematical results of the abstract inverse problem, in particular spectral properties, pseudoinverse and regularization are recollected and then specialized to kernels. Symmetric and anti-symmetric kernels are applied in relation learning problems which incorporate prior knowledge that the relation is symmetric or anti-symmetric, respectively. Theoretical properties of these kernels are proved in a draft this thesis is based on and comprehensively referenced here. These proofs show that these kernels can be guaranteed to learn only symmetric or anti-symmetric relations, and they can learn any relations relative to the original kernel modified to learn only symmetric or anti-symmetric parts. Further results prove spectral properties of these kernels, central result being a simple inequality for the the trace of the estimator, also called the effective dimension. This quantity is used in learning bounds to guarantee smaller variance.

Modelling the simultaneous effects of intellectual capital and knowledge management on the organisational performance of Finnish companies

The aim of this study was to contribute to the current knowledge-based theory by focusing on a research gap that exists in the empirically proven determination of the simultaneous but differentiable effects of intellectual capital (IC) assets and knowledge management (KM) practices on organisational performance (OP). The analysis was built on the past research and theoreticised interactions between the latent constructs specified using the survey-based items that were measured from a sample of Finnish companies for IC and KM and the dependent construct for OP determined using information available from financial databases. Two widely used and commonly recommended measures in the literature on management science, i.e. the return on total assets (ROA) and the return on equity (ROE), were calculated for OP. Thus the investigation of the relationship between IC and KM impacting OP in relation to the hypotheses founded was possible to conduct using objectively derived performance indicators. Using financial OP measures also strengthened the dynamic features of data needed in analysing simultaneous and causal dependences between the modelled constructs specified using structural path models. The estimates were obtained for the parameters of structural path models using a partial least squares-based regression estimator. Results showed that the path dependencies between IC and OP or KM and OP were always insignificant when analysed separate to any other interactions or indirect effects caused by simultaneous modelling and regardless of the OP measure used that was either ROA or ROE. The dependency between the constructs for KM and IC appeared to be very strong and was always significant when modelled simultaneously with other possible interactions between the constructs and using either ROA or ROE to define OP. This study, however, did not find statistically unambiguous evidence for proving the hypothesised causal mediation effects suggesting, for instance, that the effects of KM practices on OP are mediated by the IC assets. Due to the fact that some indication about the fluctuations of causal effects was assessed, it was concluded that further studies are needed for verifying the fundamental and likely hidden causal effects between the constructs of interest. Therefore, it was also recommended that complementary modelling and data processing measures be conducted for elucidating whether the mediation effects occur between IC, KM and OP, the verification of which requires further investigations of measured items and can be build on the findings of this study.

Optimal Recycling Combination of Ash in South-East Finland

The present world energy production is heavily relying on the combustion of solid fuels like coals, peat, biomass, municipal solid waste, whereas the share of renewable fuels is anticipated to increase in the future to mitigate climate change. In Finland, peat and wood are widely used for energy production. In any case, the combustion of solid fuels results in generation of several types of thermal conversion residues, such as bottom ash, fly ash, and boiler slag. The predominant residue type is determined by the incineration technology applied, while its composition is primarily relevant to the composition of fuels combusted. An extensive research has been conducted on technical suitability of ash for multiple recycling methods. Most of attention was drawn to the recycling of the coal combustion residues, as coal is the primary solid fuel consumed globally. The recycling methods of coal residues include utilization in a cement industry, in concrete manufacturing, and mine backfilling, to name few. Biomass combustion residues were also studied to some extent with forest fertilization, road construction, and road stabilization being the predominant utilization options. Lastly, residues form municipal solid waste incineration attracted more attention recently following the growing number of waste incineration plants globally. The recycling methods of waste incineration residues are the most limited due to its hazardous nature and varying composition, and include, among others, landfill construction, road construction, mine backfilling. In the study, environmental and economic aspects of multiple recycling options of thermal conversion residues generated within a case-study area were studied. The case-study area was South-East Finland. The environmental analysis was performed using an internationally recognized methodology — life cycle assessment. Economic assessment was conducted applying a widely used methodology — cost-benefit analysis. Finally, the results of the analyses were combined to enable easier comparison of the recycling methods. The recycling methods included the use of ash in forest fertilization, road construction, road stabilization, and landfill construction. Ash landfilling was set as a baseline scenario. Quantitative data about the amounts of ash generated and its composition was obtained from companies, their environmental reports, technical reports and other previously published literature. Overall, the amount of ash in the case-study area was 101 700 t. However, the data about 58 400 t of fly ash and 35 100 t of bottom ash and boiler slag were included in the study due to lack of data about leaching of heavy metals in some cases. The recycling methods were modelled according to the scientific studies published previously. Overall, the results of the study indicated that ash utilization for fertilization and neutralization of 17 600 ha of forest was the most economically beneficial method, which resulted in the net present value increase by 58% compared to ash landfilling. Regarding the environmental impact, the use of ash in the construction of 11 km of roads was the most attractive method with decreased environmental impact of 13% compared to ash landfilling. The least preferred method was the use of ash for landfill construction since it only enabled 11% increase of net present value, while inducing additional 1% of negative impact on the environment. Therefore, a following recycling route was proposed in the study. Where possible and legally acceptable, recycle fly and bottom ash for forest fertilization, which has strictest requirements out of all studied methods. If the quality of fly ash is not suitable for forest fertilization, then it should be utilized, first, in paved road construction, second, in road stabilization. Bottom ash not suitable for forest fertilization, as well as boiler slag, should be used in landfill construction. Landfilling should only be practiced when recycling by either of the methods is not possible due to legal requirements or there is not enough demand on the market. Current demand on ash and possible changes in the future were assessed in the study. Currently, the area of forest fertilized in the case-study are is only 451 ha, whereas about 17 600 ha of forest could be fertilized with ash generated in the region. Provided that the average forest fertilizing values in Finland are higher and the area treated with fellings is about 40 000 ha, the amount of ash utilized in forest fertilization could be increased. Regarding road construction, no new projects launched by the Center of Economic Development, Transport and the Environment in the case-study area were identified. A potential application can be found in the construction of private roads. However, no centralized data about such projects is available. The use of ash in stabilization of forest roads is not expected to increased in the future with a current downwards trend in the length of forest roads built. Finally, the use of ash in landfill construction is not a promising option due to the reducing number of landfills in operation in Finland.

Linking of stress offset score (SOS), work satisfaction, and organizational commitment to intentions to quit

The purpose of this study was to identify the impact of stressors and offsetting satistiers, measured in this study with Stress Offset Score (SOS), on intentions to quit and examine the mediating and moderating effects of three facets of work satisfaction (job satisfaction, pay satisfaction, and satisfaction with supervisor) and two facets of organizational commitment (affective and nonnative commitment) on this relationship. The sample was composed of 2990 employees from 21 public and private organizations. The interaction of each type of work satisfaction and organizational commitment, with SOS, was tested using Ordinary Least Squares (OLS) procedures. Intentions to quit was the dependent variable. The research questions were determine: (1) Does SOS predict intentions to quit? (2) Does work satisfaction mediate the predictive relationship of SOS on intentions to quit? (3) Does organizational commitment mediate the predictive relationship of SOS on intent to quit? (4) Does work satisfaction moderate the predictive relationship of SOS on intentions to quit? and (5) Does organizational commitment moderate the predictive relationship of SOS on intentions to quit? The results indicated that SOS was negatively correlated with intentions to quit. Each of the types of work satisfaction and organizational commitment variables showed a partial mediated relationship with SOS and each relationship was highly significant, while normative commitment explained more of the relationship then other mediators. The study also tested for interactions but no statistical significant relationships where established between any of the interaction terms (e.g., SOSxJob Satisfaction and SOSxAffcctive Commitment) and intentions to quit.

Molecular dynamics calculation of mean square displacement in alkali metals and rare gas solids and comparison with lattice dynamics

Molec ul ar dynamics calculations of the mean sq ua re displacement have been carried out for the alkali metals Na, K and Cs and for an fcc nearest neighbour Lennard-Jones model applicable to rare gas solids. The computations for the alkalis were done for several temperatures for temperature vol ume a swell as for the the ze r 0 pressure ze ro zero pressure volume corresponding to each temperature. In the fcc case, results were obtained for a wide range of both the temperature and density. Lattice dynamics calculations of the harmonic and the lowe s t order anharmonic (cubic and quartic) contributions to the mean square displacement were performed for the same potential models as in the molecular dynamics calculations. The Brillouin zone sums arising in the harmonic and the quartic terms were computed for very large numbers of points in q-space, and were extrapolated to obtain results ful converged with respect to the number of points in the Brillouin zone.An excellent agreement between the lattice dynamics results was observed molecular dynamics and in the case of all the alkali metals, e~ept for the zero pressure case of CSt where the difference is about 15 % near the melting temperature. It was concluded that for the alkalis, the lowest order perturbation theory works well even at temperat ures close to the melting temperat ure. For the fcc nearest neighbour model it was found that the number of particles (256) used for the molecular dynamics calculations, produces a result which is somewhere between 10 and 20 % smaller than the value converged with respect to the number of particles. However, the general temperature dependence of the mean square displacement is the same in molecular dynamics and lattice dynamics for all temperatures at the highest densities examined, while at higher volumes and high temperatures the results diverge. This indicates the importance of the higher order (eg. ~* ) perturbation theory contributions in these cases.

An analysis of the methyl rotation dynamics in the So (x' A) and T (a A) states of thioacetaldehyde from Pyrolysis jet spectra /

Jet-cooled, laser-induced phosphorescence excitation spectra (LIP) of thioacetaldehyde CH3CHS, CH3CDS, CD3CHS and CD3CDS have been observed over the region 15800 - 17300 cm"^ in a continuous pyrolysis jet. The vibronic band structure of the singlet-triplet n -* n* transition were attributed to the strong coupling of the methyl torsion and aldehydic hydrogen wagging modes . The vibronic peaks have been assigned in terms of two upper electronic state (T^) vibrations; the methyl torsion mode v^g, and the aldehydic hydrogen wagging mode v^^. The electronic origin O^a^ is unequivocally assigned as follows: CH3CHS (16294.9 cm"'' ), CH3CDS (16360.9 cm"'' ), CD3CHS (16299.7 cm"^ ), and CD3CDS (16367.2 cm"'' ). To obtain structural and dynamical information about the two electronic states, potential surfaces V(e,a) for the 6 (methyl torsion) and a (hydrogen wagging) motions were generated by ab initio quantum mechanical calculations with a 6-3 IG* basis in which the structural parameters were fully relaxed. The kinetic energy coefficients BQ(a,e) , B^(a,G) , and the cross coupling term B^(a,e) , were accurately represented as functions of the two active coordinates, a and 9. The calculations reveal that the molecule adopts an eclipsed conformation for the lower Sq electronic state (a=0°,e=0"') with a barrier height to internal rotation of 541.5 cm"^ which is to be compared to 549.8 cm"^ obtained from the microwave experiment. The conformation of the upper T^ electronic state was found to be staggered (a=24 . 68° ,e=-45. 66° ) . The saddle point in the path traced out by the aldehyde wagging motion was calculated to be 175 cm"^ above the equilibrium configuration. The corresponding maxima in the path taken by methyl torsion was found to be 322 cm'\ The small amplitude normal vibrational modes were also calculated to aid in the assignment of the spectra. Torsional-wagging energy manifolds for the two states were derived from the Hamiltonian H(a,e) which was solved variationally using an extended two dimensional Fourier expansion as a basis set. A torsionalinversion band spectrum was derived from the calculated energy levels and Franck-Condon factors, and was compared with the experimental supersonic-jet spectra. Most of the anomalies which were associated with the interpretation of the observed spectrum could be accounted for by the band profiles derived from ab initio SCF calculations. A model describing the jet spectra was derived by scaling the ab initio potential functions. The global least squares fitting generates a triplet state potential which has a minimum at (a=22.38° ,e=-41.08°) . The flatter potential in the scaled model yielded excellent agreement between the observed and calculated frequency intervals.

The Seemingly Unrelated Dynamic Cointegration Regression Model and Testing for Purching Power Parity.

This paper studies seemingly unrelated linear models with integrated regressors and stationary errors. By adding leads and lags of the first differences of the regressors and estimating this augmented dynamic regression model by feasible generalized least squares using the long-run covariance matrix, we obtain an efficient estimator of the cointegrating vector that has a limiting mixed normal distribution. Simulation results suggest that this new estimator compares favorably with others already proposed in the literature. We apply these new estimators to the testing of purchasing power parity (PPP) among the G-7 countries. The test based on the efficient estimates rejects the PPP hypothesis for most countries.

Exact Tests for Contemporaneous Correlation of Disturbances in Seemingly Unrelated Regressions.

This paper proposes finite-sample procedures for testing the SURE specification in multi-equation regression models, i.e. whether the disturbances in different equations are contemporaneously uncorrelated or not. We apply the technique of Monte Carlo (MC) tests [Dwass (1957), Barnard (1963)] to obtain exact tests based on standard LR and LM zero correlation tests. We also suggest a MC quasi-LR (QLR) test based on feasible generalized least squares (FGLS). We show that the latter statistics are pivotal under the null, which provides the justification for applying MC tests. Furthermore, we extend the exact independence test proposed by Harvey and Phillips (1982) to the multi-equation framework. Specifically, we introduce several induced tests based on a set of simultaneous Harvey/Phillips-type tests and suggest a simulation-based solution to the associated combination problem. The properties of the proposed tests are studied in a Monte Carlo experiment which shows that standard asymptotic tests exhibit important size distortions, while MC tests achieve complete size control and display good power. Moreover, MC-QLR tests performed best in terms of power, a result of interest from the point of view of simulation-based tests. The power of the MC induced tests improves appreciably in comparison to standard Bonferroni tests and, in certain cases, outperforms the likelihood-based MC tests. The tests are applied to data used by Fischer (1993) to analyze the macroeconomic determinants of growth.

Asymptotic Approximations in the Near-Integrated Model with a Non-Zero Initial Condition

This paper considers various asymptotic approximations in the near-integrated firstorder autoregressive model with a non-zero initial condition. We first extend the work of Knight and Satchell (1993), who considered the random walk case with a zero initial condition, to derive the expansion of the relevant joint moment generating function in this more general framework. We also consider, as alternative approximations, the stochastic expansion of Phillips (1987c) and the continuous time approximation of Perron (1991). We assess how these alternative methods provide or not an adequate approximation to the finite-sample distribution of the least-squares estimator in a first-order autoregressive model. The results show that, when the initial condition is non-zero, Perron's (1991) continuous time approximation performs very well while the others only offer improvements when the initial condition is zero.

Exact Skewness-Kurtosis Tests for Multivariate Normality and Goodness-of-fit in Multivariate Regressions with Application to Asset Pricing Models

We study the problem of testing the error distribution in a multivariate linear regression (MLR) model. The tests are functions of appropriately standardized multivariate least squares residuals whose distribution is invariant to the unknown cross-equation error covariance matrix. Empirical multivariate skewness and kurtosis criteria are then compared to simulation-based estimate of their expected value under the hypothesized distribution. Special cases considered include testing multivariate normal, Student t; normal mixtures and stable error models. In the Gaussian case, finite-sample versions of the standard multivariate skewness and kurtosis tests are derived. To do this, we exploit simple, double and multi-stage Monte Carlo test methods. For non-Gaussian distribution families involving nuisance parameters, confidence sets are derived for the the nuisance parameters and the error distribution. The procedures considered are evaluated in a small simulation experi-ment. Finally, the tests are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995.

Projection-Based Statistical Inference in Linear Structural Models with Possibly Weak Instruments

It is well known that standard asymptotic theory is not valid or is extremely unreliable in models with identification problems or weak instruments [Dufour (1997, Econometrica), Staiger and Stock (1997, Econometrica), Wang and Zivot (1998, Econometrica), Stock and Wright (2000, Econometrica), Dufour and Jasiak (2001, International Economic Review)]. One possible way out consists here in using a variant of the Anderson-Rubin (1949, Ann. Math. Stat.) procedure. The latter, however, allows one to build exact tests and confidence sets only for the full vector of the coefficients of the endogenous explanatory variables in a structural equation, which in general does not allow for individual coefficients. This problem may in principle be overcome by using projection techniques [Dufour (1997, Econometrica), Dufour and Jasiak (2001, International Economic Review)]. AR-types are emphasized because they are robust to both weak instruments and instrument exclusion. However, these techniques can be implemented only by using costly numerical techniques. In this paper, we provide a complete analytic solution to the problem of building projection-based confidence sets from Anderson-Rubin-type confidence sets. The latter involves the geometric properties of “quadrics” and can be viewed as an extension of usual confidence intervals and ellipsoids. Only least squares techniques are required for building the confidence intervals. We also study by simulation how “conservative” projection-based confidence sets are. Finally, we illustrate the methods proposed by applying them to three different examples: the relationship between trade and growth in a cross-section of countries, returns to education, and a study of production functions in the U.S. economy.

An Autoregressive Spectral Density Estimator at Frequency Zero for Nonstationarity Tests.

Many unit root and cointegration tests require an estimate of the spectral density function at frequency zero at some process. Kernel estimators based on weighted sums of autocovariances constructed using estimated residuals from an AR(1) regression are commonly used. However, it is known that with substantially correlated errors, the OLS estimate of the AR(1) parameter is severely biased. in this paper, we first show that this least squares bias induces a significant increase in the bias and mean-squared error of kernel-based estimators.

Non-negative matrix decomposition approaches to frequency domain analysis of music audio signals

On étudie l’application des algorithmes de décomposition matricielles tel que la Factorisation Matricielle Non-négative (FMN), aux représentations fréquentielles de signaux audio musicaux. Ces algorithmes, dirigés par une fonction d’erreur de reconstruction, apprennent un ensemble de fonctions de base et un ensemble de coef- ficients correspondants qui approximent le signal d’entrée. On compare l’utilisation de trois fonctions d’erreur de reconstruction quand la FMN est appliquée à des gammes monophoniques et harmonisées: moindre carré, divergence Kullback-Leibler, et une mesure de divergence dépendente de la phase, introduite récemment. Des nouvelles méthodes pour interpréter les décompositions résultantes sont présentées et sont comparées aux méthodes utilisées précédemment qui nécessitent des connaissances du domaine acoustique. Finalement, on analyse la capacité de généralisation des fonctions de bases apprises par rapport à trois paramètres musicaux: l’amplitude, la durée et le type d’instrument. Pour ce faire, on introduit deux algorithmes d’étiquetage des fonctions de bases qui performent mieux que l’approche précédente dans la majorité de nos tests, la tâche d’instrument avec audio monophonique étant la seule exception importante.

Labour, industries and the politics of immigration

Cette thèse par articles examine les causes et conséquences économiques des politiques d'immigration du point de vue des pays receveurs. Je soutiens que les politiques d'immigration affectent la composition industrielle, et que l'immigration non-qualifiée a ralenti le développement des secteurs haute-technologie dans les pays de l'OCDE au cours des dernières décennies. Néanmoins, les gouvernements élus ont des incitatifs à accroître les niveaux d'immigration et à admettre des immigrants non-qualifiés, afin de conserver l'appui du secteur privé, et de façon à éviter les réactions négatives qui résulteraient de l'affaiblissement des industries traditionnelles. Le premier article s'appuie sur un modèle de progrès technologique endogène et soutient que les activités de recherche des entreprises croissent avec l'offre relative en travail qualifié, et se contractent avec l'offre relative en travail non-qualifié. À l'aide de données panel sur les pays de l'OCDE entre 1971 et 2003, j'estime l'élasticité des dépenses en R&D par rapport à l'offre relative de facteurs au moyen d'un modèle OLS dynamique (DOLS). Les résultats sont conséquents avec les propositions théoriques, et je démontre que l'immigration non-qualifiée a ralenti l'intensité des investissements privés en R&D. Le deuxième article examine la réponse des gouvernements fédéraux canadiens au lobbying des entreprises sur l'enjeu de l'immigration, à l'aide de données trimestrielles entre 1996 et 2011. J'argue que les gouvernements ont des incitatifs électoraux à accroître les niveaux d'immigration malgré les préférences restrictives du public sur cet enjeu, afin de s'assurer de l'appui des groupes d'intérêt corporatifs. Je teste cet argument à l'aide d'un modèle vectoriel autorégressif. Un résultat clé est la réponse positive des influx de travailleurs temporaires à l'intensité du lobbying des entreprises. Le troisième article soutient que les gouvernements ont des incitatifs à gérer la sélection des immigrants de façon à préserver la composition industrielle régionale. Je teste cet argument avec des données panel sur les provinces canadiennes entre 2001 et 2010, et un devis de recherche basé sur l'approche des doubles moindres carrés (two-stage least squares). Les résultats tendent à appuyer l'argument principal : les provinces dont l'économie repose davantage sur des industries traditionnelles sont susceptibles de recevoir une plus grande proportion d'immigrants non-qualifiés, ce qui contribue à renforcer cette spécialisation.