Modified nano- and microcellulose based adsorption materials in water treatment

In recent decades, industrial activity growth and increasing water usage worldwide have led to the release of various pollutants, such as toxic heavy metals and nutrients, into the aquatic environment. Modified nanocellulose and microcellulose-based adsorption materials have the potential to remove these contaminants from aqueous solutions. The present research consisted of the preparation of five different nano/microcellulose-based adsorbents, their characterization, the study of adsorption kinetics and isotherms, the determination of adsorption mechanisms, and an evaluation of adsorbents’ regeneration properties. The same well known reactions and modification methods that were used for modifying conventional cellulose also worked for microfibrillated cellulose (MFC). The use of succinic anhydride modified mercerized nanocellulose, and aminosilane and hydroxyapatite modified nanostructured MFC for the removal of heavy metals from aqueous solutions exhibited promising results. Aminosilane, epoxy and hydroxyapatite modified MFC could be used as a promising alternative for H2S removal from aqueous solutions. In addition, new knowledge about the adsorption properties of carbonated hydroxyapatite modified MFC as multifunctional adsorbent for the removal of both cations and anions ions from water was obtained. The maghemite nanoparticles (Fe3O4) modified MFC was found to be a highly promising adsorbent for the removal of As(V) from aqueous solutions due to its magnetic properties, high surface area, and high adsorption capacity . The maximum removal efficiencies of each adsorbent were studied in batch mode. The results of adsorption kinetics indicated very fast removal rates for all the studied pollutants. Modeling of adsorption isotherms and adsorption kinetics using various theoretical models provided information about the adsorbent’s surface properties and the adsorption mechanisms. This knowledge is important for instance, in designing water treatment units/plants. Furthermore, the correspondence between the theory behind the model and properties of the adsorbent as well as adsorption mechanisms were also discussed. On the whole, both the experimental results and theoretical considerations supported the potential applicability of the studied nano/microcellulose-based adsorbents in water treatment applications.

Optimization and Measuring Techniques for Collect-and-Place Machines in Printed Circuit Board Industry

This thesis considers optimization problems arising in printed circuit board assembly. Especially, the case in which the electronic components of a single circuit board are placed using a single placement machine is studied. Although there is a large number of different placement machines, the use of collect-and-place -type gantry machines is discussed because of their flexibility and increasing popularity in the industry. Instead of solving the entire control optimization problem of a collect-andplace machine with a single application, the problem is divided into multiple subproblems because of its hard combinatorial nature. This dividing technique is called hierarchical decomposition. All the subproblems of the one PCB - one machine -context are described, classified and reviewed. The derived subproblems are then either solved with exact methods or new heuristic algorithms are developed and applied. The exact methods include, for example, a greedy algorithm and a solution based on dynamic programming. Some of the proposed heuristics contain constructive parts while others utilize local search or are based on frequency calculations. For the heuristics, it is made sure with comprehensive experimental tests that they are applicable and feasible. A number of quality functions will be proposed for evaluation and applied to the subproblems. In the experimental tests, artificially generated data from Markov-models and data from real-world PCB production are used. The thesis consists of an introduction and of five publications where the developed and used solution methods are described in their full detail. For all the problems stated in this thesis, the methods proposed are efficient enough to be used in the PCB assembly production in practice and are readily applicable in the PCB manufacturing industry.

Experimental models in vaccine research: malaria and leishmaniasis

Animal models have a long history of being useful tools, not only to test and select vaccines, but also to help understand the elaborate details of the immune response that follows infection. Different models have been extensively used to investigate putative immunological correlates of protection against parasitic diseases that are important to reach a successful vaccine. The greatest challenge has been the improvement and adaptation of these models to reflect the reality of human disease and the screening of vaccine candidates capable of overcoming the challenge of natural transmission. This review will discuss the advantages and challenges of using experimental animal models for vaccine development and how the knowledge achieved can be extrapolated to human disease by looking into two important parasitic diseases: malaria and leishmaniasis.

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.

Individual and social determinants of multiple chronic disease behavioural risk factors in Canadian children and adolescents

Contexte: Les facteurs de risque comportementaux, notamment l’inactivité physique, le comportement sédentaire, le tabagisme, la consommation d’alcool et le surpoids sont les principales causes modifiables de maladies chroniques telles que le cancer, les maladies cardiovasculaires et le diabète. Ces facteurs de risque se manifestent également de façon concomitante chez l’individu et entraînent des risques accrus de morbidité et de mortalité. Bien que les facteurs de risque comportementaux aient été largement étudiés, la distribution, les patrons d’agrégation et les déterminants de multiples facteurs de risque comportementaux sont peu connus, surtout chez les enfants et les adolescents. Objectifs: Cette thèse vise 1) à décrire la prévalence et les patrons d’agrégation de multiples facteurs de risque comportementaux des maladies chroniques chez les enfants et adolescents canadiens; 2) à explorer les corrélats individuels, sociaux et scolaires de multiples facteurs de risque comportementaux chez les enfants et adolescents canadiens; et 3) à évaluer, selon le modèle conceptuel de l’étude, l’influence longitudinale d’un ensemble de variables distales (c’est-à-dire des variables situées à une distance intermédiaire des comportements à risque) de type individuel (estime de soi, sentiment de réussite), social (relations sociales, comportements des parents/pairs) et scolaire (engagement collectif à la réussite, compréhension des règles), ainsi que de variables ultimes (c’est-à-dire des variables situées à une distance éloignée des comportements à risque) de type individuel (traits de personnalité, caractéristiques démographiques), social (caractéristiques socio-économiques des parents) et scolaire (type d’école, environnement favorable, climat disciplinaire) sur le taux d’occurrence de multiples facteurs de risque comportementaux chez les enfants et adolescents canadiens. Méthodes: Des données transversales (n = 4724) à partir du cycle 4 (2000-2001) de l’Enquête longitudinale nationale sur les enfants et les jeunes (ELNEJ) ont été utilisées pour décrire la prévalence et les patrons d’agrégation de multiples facteurs de risque comportementaux chez les jeunes canadiens âgés de 10-17 ans. L’agrégation des facteurs de risque a été examinée en utilisant une méthode du ratio de cas observés sur les cas attendus. La régression logistique ordinale a été utilisée pour explorer les corrélats de multiples facteurs de risque comportementaux dans un échantillon transversal (n = 1747) de jeunes canadiens âgés de 10-15 ans du cycle 4 (2000-2001) de l’ELNEJ. Des données prospectives (n = 1135) à partir des cycle 4 (2000-2001), cycle 5 (2002-2003) et cycle 6 (2004-2005) de l’ELNEJ ont été utilisées pour évaluer l’influence longitudinale des variables distales et ultimes (tel que décrit ci-haut dans les objectifs) sur le taux d’occurrence de multiples facteurs de risque comportementaux chez les jeunes canadiens âgés de 10-15 ans; cette analyse a été effectuée à l’aide des modèles de Poisson longitudinaux. Résultats: Soixante-cinq pour cent des jeunes canadiens ont rapporté avoir deux ou plus de facteurs de risque comportementaux, comparativement à seulement 10% des jeunes avec aucun facteur de risque. Les facteurs de risque comportementaux se sont agrégés en de multiples combinaisons. Plus précisément, l’occurrence simultanée des cinq facteurs de risque était 120% plus élevée chez les garçons (ratio observé/attendu (O/E) = 2.20, intervalle de confiance (IC) 95%: 1.31-3.09) et 94% plus élevée chez les filles (ratio O/E = 1.94, IC 95%: 1.24-2.64) qu’attendu. L’âge (rapport de cotes (RC) = 1.95, IC 95%: 1.21-3.13), ayant un parent fumeur (RC = 1.49, IC 95%: 1.09-2.03), ayant rapporté que la majorité/tous de ses pairs consommaient du tabac (RC = 7.31, IC 95%: 4.00-13.35) ou buvaient de l’alcool (RC = 3.77, IC 95%: 2.18-6.53), et vivant dans une famille monoparentale (RC = 1.94, IC 95%: 1.31-2.88) ont été positivement associés aux multiples comportements à risque. Les jeunes ayant une forte estime de soi (RC = 0.92, IC 95%: 0.85-0.99) ainsi que les jeunes dont un des parents avait un niveau d’éducation postsecondaire (RC = 0.58, IC 95%: 0.41-0.82) étaient moins susceptibles d’avoir de multiples facteurs de risque comportementaux. Enfin, les variables de type social distal (tabagisme des parents et des pairs, consommation d’alcool par les pairs) (Log du rapport de vraisemblance (LLR) = 187.86, degrés de liberté = 8, P < 0,001) et individuel distal (estime de soi) (LLR = 76.94, degrés de liberté = 4, P < 0,001) ont significativement influencé le taux d’occurrence de multiples facteurs de risque comportementaux. Les variables de type individuel ultime (âge, sexe, anxiété) et social ultime (niveau d’éducation du parent, revenu du ménage, structure de la famille) ont eu une influence moins prononcée sur le taux de cooccurrence des facteurs de risque comportementaux chez les jeunes. Conclusion: Les résultats suggèrent que les interventions de santé publique devraient principalement cibler les déterminants de type individuel distal (tel que l’estime de soi) ainsi que social distal (tels que le tabagisme des parents et des pairs et la consommation d’alcool par les pairs) pour prévenir et/ou réduire l’occurrence de multiples facteurs de risque comportementaux chez les enfants et les adolescents. Cependant, puisque les variables de type distal (telles que les caractéristiques psychosociales des jeunes et comportements des parents/pairs) peuvent être influencées par des variables de type ultime (telles que les caractéristiques démographiques et socioéconomiques), les programmes et politiques de prévention devraient également viser à améliorer les conditions socioéconomiques des jeunes, particulièrement celles des enfants et des adolescents des familles les plus démunies.

Modèles de flammelette en combustion turbulente avec extinction et réallumage : étude asymptotique et numérique, estimation d’erreur a posteriori et modélisation adaptative

On s’intéresse ici aux erreurs de modélisation liées à l’usage de modèles de flammelette sous-maille en combustion turbulente non prémélangée. Le but de cette thèse est de développer une stratégie d’estimation d’erreur a posteriori pour déterminer le meilleur modèle parmi une hiérarchie, à un coût numérique similaire à l’utilisation de ces mêmes modèles. Dans un premier temps, une stratégie faisant appel à un estimateur basé sur les résidus pondérés est développée et testée sur un système d’équations d’advection-diffusion-réaction. Dans un deuxième temps, on teste la méthodologie d’estimation d’erreur sur un autre système d’équations, où des effets d’extinction et de réallumage sont ajoutés. Lorsqu’il n’y a pas d’advection, une analyse asymptotique rigoureuse montre l’existence de plusieurs régimes de combustion déjà observés dans les simulations numériques. Nous obtenons une approximation des paramètres de réallumage et d’extinction avec la courbe en «S», un graphe de la température maximale de la flamme en fonction du nombre de Damköhler, composée de trois branches et d’une double courbure. En ajoutant des effets advectifs, on obtient également une courbe en «S» correspondant aux régimes de combustion déjà identifiés. Nous comparons les erreurs de modélisation liées aux approximations asymptotiques dans les deux régimes stables et établissons une nouvelle hiérarchie des modèles en fonction du régime de combustion. Ces erreurs sont comparées aux estimations données par la stratégie d’estimation d’erreur. Si un seul régime stable de combustion existe, l’estimateur d’erreur l’identifie correctement ; si plus d’un régime est possible, on obtient une fac˛on systématique de choisir un régime. Pour les régimes où plus d’un modèle est approprié, la hiérarchie prédite par l’estimateur est correcte.

Automated Transcription System for Malayalam Language

Malayalam is one of the 22 scheduled languages in India with more than 130 million speakers. This paper presents a report on the development of a speaker independent, continuous transcription system for Malayalam. The system employs Hidden Markov Model (HMM) for acoustic modeling and Mel Frequency Cepstral Coefficient (MFCC) for feature extraction. It is trained with 21 male and female speakers in the age group ranging from 20 to 40 years. The system obtained a word recognition accuracy of 87.4% and a sentence recognition accuracy of 84%, when tested with a set of continuous speech data.

Probabilistic models to assist maintenance of multiple instruments

The paper discusses maintenance challenges of organisations with a huge number of devices and proposes the use of probabilistic models to assist monitoring and maintenance planning. The proposal assumes connectivity of instruments to report relevant features for monitoring. Also, the existence of enough historical registers with diagnosed breakdowns is required to make probabilistic models reliable and useful for predictive maintenance strategies based on them. Regular Markov models based on estimated failure and repair rates are proposed to calculate the availability of the instruments and Dynamic Bayesian Networks are proposed to model cause-effect relationships to trigger predictive maintenance services based on the influence between observed features and previously documented diagnostics

Aspectes metodològics i aplicacions de la modelització del temps de supervivència multivariant mitjançant models mixtes

Els estudis de supervivència s'interessen pel temps que passa des de l'inici de l'estudi (diagnòstic de la malaltia, inici del tractament,...) fins que es produeix l'esdeveniment d'interès (mort, curació, millora,...). No obstant això, moltes vegades aquest esdeveniment s'observa més d'una vegada en un mateix individu durant el període de seguiment (dades de supervivència multivariant). En aquest cas, és necessari utilitzar una metodologia diferent a la utilitzada en l'anàlisi de supervivència estàndard. El principal problema que l'estudi d'aquest tipus de dades comporta és que les observacions poden no ser independents. Fins ara, aquest problema s'ha solucionat de dues maneres diferents en funció de la variable dependent. Si aquesta variable segueix una distribució de la família exponencial s'utilitzen els models lineals generalitzats mixtes (GLMM); i si aquesta variable és el temps, variable amb una distribució de probabilitat no pertanyent a aquesta família, s'utilitza l'anàlisi de supervivència multivariant. El que es pretén en aquesta tesis és unificar aquests dos enfocs, és a dir, utilitzar una variable dependent que sigui el temps amb agrupacions d'individus o d'observacions, a partir d'un GLMM, amb la finalitat d'introduir nous mètodes pel tractament d'aquest tipus de dades.

Predicting Argentine ant invasion across spatial scales via ecological niche models

La formiga argentina (Linepithema humile) es troba entre les espècies més invasores: originària d'Amèrica del Sud, actualment ha envaït nombroses àrees arreu del món. Aquesta tesi doctoral intenta fer una primera anàlisi integrada i multiescalar de la distribució de la formiga argentina mitjançant l'ús de models de nínxol ecològic. D'acord amb els resultats obtinguts, es preveu que la formiga argentina assoleixi una distribució més àmplia que l'actual. Les prediccions obtingudes a partir dels models concorden amb la distribució actualment coneguda i, a més, indiquen àrees a prop de la costa i dels rius principals com a altament favorables per a l'espècie. Aquests resultats corroboren la idea que la formiga argentina no es troba actualment en equilibri amb el medi. D'altra banda, amb el canvi climàtic, s'espera que la distribució de la formiga argentina s'estengui cap a latituds més elevades en ambdós hemisferis, i sofreixi una retracció en els tròpics a escales globals.

Inter-laboratory variation of in vitro cumulative gas production profiles of feeds using manual and automated methods

A study was conducted to estimate variation among laboratories and between manual and automated techniques of measuring pressure on the resulting gas production profiles (GPP). Eight feeds (molassed sugarbeet feed, grass silage, maize silage, soyabean hulls, maize gluten feed, whole crop wheat silage, wheat, glucose) were milled to pass a I mm screen and sent to three laboratories (ADAS Nutritional Sciences Research Unit, UK; Institute of Grassland and Environmental Research (IGER), UK; Wageningen University, The Netherlands). Each laboratory measured GPP over 144 h using standardised procedures with manual pressure transducers (MPT) and automated pressure systems (APS). The APS at ADAS used a pressure transducer and bottles in a shaking water bath, while the APS at Wageningen and IGER used a pressure sensor and bottles held in a stationary rack. Apparent dry matter degradability (ADDM) was estimated at the end of the incubation. GPP were fitted to a modified Michaelis-Menten model assuming a single phase of gas production, and GPP were described in terms of the asymptotic volume of gas produced (A), the time to half A (B), the time of maximum gas production rate (t(RM) (gas)) and maximum gas production rate (R-M (gas)). There were effects (P<0.001) of substrate on all parameters. However, MPT produced more (P<0.001) gas, but with longer (P<0.001) B and t(RM gas) (P<0.05) and lower (P<0.001) R-M gas compared to APS. There was no difference between apparatus in ADDM estimates. Interactions occurred between substrate and apparatus, substrate and laboratory, and laboratory and apparatus. However, when mean values for MPT were regressed from the individual laboratories, relationships were good (i.e., adjusted R-2 = 0.827 or higher). Good relationships were also observed with APS, although they were weaker than for MPT (i.e., adjusted R-2 = 0.723 or higher). The relationships between mean MPT and mean APS data were also good (i.e., adjusted R 2 = 0. 844 or higher). Data suggest that, although laboratory and method of measuring pressure are sources of variation in GPP estimation, it should be possible using appropriate mathematical models to standardise data among laboratories so that data from one laboratory could be extrapolated to others. This would allow development of a database of GPP data from many diverse feeds. (c) 2005 Published by Elsevier B.V.

A micro-level simulation for the prediction of intention and behaviour

In this contribution we aim at anchoring Agent-Based Modeling (ABM) simulations in actual models of human psychology. More specifically, we apply unidirectional ABM to social psychological models using low level agents (i.e., intra-individual) to examine whether they generate better predictions, in comparison to standard statistical approaches, concerning the intentions of performing a behavior and the behavior. Moreover, this contribution tests to what extent the predictive validity of models of attitude such as the Theory of Planned Behavior (TPB) or Model of Goal-directed Behavior (MGB) depends on the assumption that peoples’ decisions and actions are purely rational. Simulations were therefore run by considering different deviations from rationality of the agents with a trembling hand method. Two data sets concerning respectively the consumption of soft drinks and physical activity were used. Three key findings emerged from the simulations. First, compared to standard statistical approach the agent-based simulation generally improves the prediction of behavior from intention. Second, the improvement in prediction is inversely proportional to the complexity of the underlying theoretical model. Finally, the introduction of varying degrees of deviation from rationality in agents’ behavior can lead to an improvement in the goodness of fit of the simulations. By demonstrating the potential of ABM as a complementary perspective to evaluating social psychological models, this contribution underlines the necessity of better defining agents in terms of psychological processes before examining higher levels such as the interactions between individuals.

Heat kernel smoothing via Laplace-Beltrami eigenfunctions and its application to subcortical structure modeling

We present a new subcortical structure shape modeling framework using heat kernel smoothing constructed with the Laplace-Beltrami eigenfunctions. The cotan discretization is used to numerically obtain the eigenfunctions of the Laplace-Beltrami operator along the surface of subcortical structures of the brain. The eigenfunctions are then used to construct the heat kernel and used in smoothing out measurements noise along the surface. The proposed framework is applied in investigating the influence of age (38-79 years) and gender on amygdala and hippocampus shape. We detected a significant age effect on hippocampus in accordance with the previous studies. In addition, we also detected a significant gender effect on amygdala. Since we did not find any such differences in the traditional volumetric methods, our results demonstrate the benefit of the current framework over traditional volumetric methods.

Evaluation of regional climate simulations for air quality modelling purposes

In order to evaluate the future potential benefits of emission regulation on regional air quality, while taking into account the effects of climate change, off-line air quality projection simulations are driven using weather forcing taken from regional climate models. These regional models are themselves driven by simulations carried out using global climate models (GCM) and economical scenarios. Uncertainties and biases in climate models introduce an additional “climate modeling” source of uncertainty that is to be added to all other types of uncertainties in air quality modeling for policy evaluation. In this article we evaluate the changes in air quality-related weather variables induced by replacing reanalyses-forced by GCM-forced regional climate simulations. As an example we use GCM simulations carried out in the framework of the ERA-interim programme and of the CMIP5 project using the Institut Pierre-Simon Laplace climate model (IPSLcm), driving regional simulations performed in the framework of the EURO-CORDEX programme. In summer, we found compensating deficiencies acting on photochemistry: an overestimation by GCM-driven weather due to a positive bias in short-wave radiation, a negative bias in wind speed, too many stagnant episodes, and a negative temperature bias. In winter, air quality is mostly driven by dispersion, and we could not identify significant differences in either wind or planetary boundary layer height statistics between GCM-driven and reanalyses-driven regional simulations. However, precipitation appears largely overestimated in GCM-driven simulations, which could significantly affect the simulation of aerosol concentrations. The identification of these biases will help interpreting results of future air quality simulations using these data. Despite these, we conclude that the identified differences should not lead to major difficulties in using GCM-driven regional climate simulations for air quality projections.

Forecasting economic and financial time series with non-linear models

In this paper we discuss the current state-of-the-art in estimating, evaluating, and selecting among non-linear forecasting models for economic and financial time series. We review theoretical and empirical issues, including predictive density, interval and point evaluation and model selection, loss functions, data-mining, and aggregation. In addition, we argue that although the evidence in favor of constructing forecasts using non-linear models is rather sparse, there is reason to be optimistic. However, much remains to be done. Finally, we outline a variety of topics for future research, and discuss a number of areas which have received considerable attention in the recent literature, but where many questions remain.