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This thesis explores the phenomenon of coping with dyslexia based on the perspectives of six Greek dyslexic adults, as expressed by themselves. The research is concerned with exploration of the phenomenon by standing out from linear reductionist approaches - whether pathologising person-focused or exclusively environment-focused - as well as interactionist approaches that are simplistically additive. Instead, the study explores the phenomenon of coping with dyslexia from a transactional perspective which assumes that the factors of coping are strongly interrelated, mutually affected and altered by the transaction, suggesting a more complex and holistic understanding of the phenomenon. More specifically, the study considers the adequacy of Schlossberg’s transitional 4 S System in explaining the experiences of individuals who cope with dyslexia. To pursue the purposes of the study, a multiple case studies design was employed and semi-structured interviews were conducted. Findings suggest that for the participants, coping with dyslexia is not restricted simply to dealing with a set of difficulties, because the dyslexia ‘situation’ is a complex entity with a variety of aspects which relate directly or indirectly to literacy efficiency. Participants reported employing a complex and constantly evolving (across contexts and over time) system of different coping strategies. In fact, findings suggest that coping with dyslexia is not a stable entity but a transactional process which is characterised by fluidity, non-linear evolution and involvement of multiple factors. The 4 S System managed as an analytic tool to adequately identify and explain the complex transactionist relationships between the involved factors and the system of coping as a whole. Finally, in terms of effectiveness, findings suggested that there are no magic recipes. The usefulness of a coping or support activity seems to be an individualistic issue determined by contemporariness and so, a flexible approach towards coping with dyslexia is suggested.

Energi är ett ständigt aktuellt ämne, där byggnader står för en stor del av energianvändningen i Europa och Sverige. Samtidigt som energieffektiviseringar genomförs måste ett tillräckligt luftflöde bibehållas i byggnaden för att uppnå en komfortabel inomhusmiljö. Detta medför att en stor mängd energi cirkulerar i byggnadens ventilationssystem. Rapporten innehåller en simulering för att fastställa hur stor del denna är, kontra det totala energibehovet för ett flerbostadshus beläget i Kalmar, Sverige. Resultatet visar att ventilationen står för 35 % av det totala värmebehovet. Potentialen för återvinningsbar energi beräknades för att utvärdera hur mycket energi som kan sparas genom att installera en frånluftsvärmepump på ventilationssystemet. Simuleringar visar att vid ett godkänt minimumflöde på 0,35 l/s∙m2, skulle fastigheten kunna vara självförsörjande på värme under sommarmånaderna. Detta innebär att det går att återvinna ca 57 kWh/m2∙år, en reducering av energibehovet med 30 %. Vidare arbete skulle innebära fler mätningar på flöden, temperatur och fuktigheter.

Since the development of high-throughput technologies, we can capture large quantities of gene¡¦s expression data from DNA microarray data, so there are some technologies have been proposed to model gene regulatory networks. Gene regulatory networks is mainly used to express the relationship between the genes, but only can express a simple relationship, and can¡¦t clearly show how the operation between genes regulatory. In the simulation method of gene regulation, the mathematical methods are more often used. In the mathematical methods, S-system is the most widely used in non-linear differential equations. When the use of mathematical simulation of gene regulatory networks, there are mainly two aspects¡G(1) deciding on the model structure and (2) estimating the involved parameter values. However, when using S-system simulated the gene regulatory networks, we can only know the gene profiles, and there is no way to know the regulatory relationships between genes, but in order to understand the relationship between genes, we must clearly understand how genes work. Therefore, we propose to encode parameter values to infer the regulatory parameter values between genes. We propose the method of encoding parameter values, and using six artificial genetic datasets, and assuming 100% parameter values are known, 90% known, 70% known, 50% known, 30% known, 10% known. The experimental results show, besides it can infer a high proportion of non-regulation, positive regulation and negative regulation, also can infer more precise parameter values, and also has a clear understanding of the regulatory relationship between genes.

Understanding the mechanisms of gene regulation in the field of systems biology is a very important issue. With the development of bio-information technology, we can capture large quantities of gene¡¦s expression data from DNA microarray data. In order to discover the relationship of gene regulation, the simulation of gene regulatory networks have been proposed. Among these simulations methods, the S-system model is the most widely used in non-linear differential equations. It can simulate the dynamic behavior of gene regulatory networks and gene expression, but can¡¦t explain the structure and orientation of gene regulatory networks. Therefore, we propose a Boolean knowledge-based approach to assist the S-system modeling of gene regulatory networks. In this study, we derive the positive and negative regulatory relationships between genes from the regulation of S-system parameters, and use the structure of Boolean networks as our knowledge base. According to the results of the experiment, we can verify our assumptions for the regulation of the S-system parameters, and also has a better understanding of the regulatory relationship between genes.

<p>The inverse problem of modeling biochemical processes mathematically from measured time course data falls into the category of system identification and parameter estimation. Analyzing the time course data would provide valuable insights into the model structure and dynamics of the biochemical system. Based on the types of biochemical reactions, such as metabolic networks and genetic networks, several modeling frameworks have been proposed, developed and proved effective, including the Michaelis-Menten equation, the Biochemical System Theory (BST), etc. One bottleneck in analyzing the obtained data is the estimation of parameter values within the system model.</p> <p>As most models for molecular biological systems are nonlinear with respect to both parameters and system state variables, estimation of parameters in these models from experimental measurement data is thus a nonlinear estimation problem. In principle, all algorithms for nonlinear optimization can be used to deal with this problem, for example, the Gauss-Newton iteration method and its variants. However, these methods do not take the special structures of biological system models into account. When the number of parameters to be determined increases, it will be challenging and computationally expensive to apply these conventional methods.</p> <p>In this research, several methods are proposed for estimating parameters in two classes of widely used biological system models: the S-system model and the linear fractional model (LFM), by utilizing their structure specialties. For the S-system, two estimation methods are designed. 1) Based on the two-term structure (production and degradation) of the model, an alternating iterative least squares method is proposed. 2) A separation nonlinear least squares method is proposed to deal with the partially linear structure of the model. For the LFM, two estimation methods are provided. 1) The separation nonlinear least squares method can also be adopted to treat the partially linear structure of the LFM, and moreover a modified iterative version is included. 2) A special strategy using the separation principle and the weighted least squares method is implemented to turn the cost function into a quadratic form and thus the estimates for parameters can be analytically solved. Simulation results have demonstrated the effectiveness of the proposed methods, which have shown better performance in terms of estimation accuracy and computation time, compared with those conventional nonlinear estimation methods.</p>

<p>The inverse problem of modeling biochemical processes mathematically from measured time course data falls into the category of system identification and parameter estimation. Analyzing the time course data would provide valuable insights into the model structure and dynamics of the biochemical system. Based on the types of biochemical reactions, such as metabolic networks and genetic networks, several modeling frameworks have been proposed, developed and proved effective, including the Michaelis-Menten equation, the Biochemical System Theory (BST), etc. One bottleneck in analyzing the obtained data is the estimation of parameter values within the system model.</p> <p>As most models for molecular biological systems are nonlinear with respect to both parameters and system state variables, estimation of parameters in these models from experimental measurement data is thus a nonlinear estimation problem. In principle, all algorithms for nonlinear optimization can be used to deal with this problem, for example, the Gauss-Newton iteration method and its variants. However, these methods do not take the special structures of biological system models into account. When the number of parameters to be determined increases, it will be challenging and computationally expensive to apply these conventional methods.</p> <p>In this research, several methods are proposed for estimating parameters in two classes of widely used biological system models: the S-system model and the linear fractional model (LFM), by utilizing their structure specialties. For the S-system, two estimation methods are designed. 1) Based on the two-term structure (production and degradation) of the model, an alternating iterative least squares method is proposed. 2) A separation nonlinear least squares method is proposed to deal with the partially linear structure of the model. For the LFM, two estimation methods are provided. 1) The separation nonlinear least squares method can also be adopted to treat the partially linear structure of the LFM, and moreover a modified iterative version is included. 2) A special strategy using the separation principle and the weighted least squares method is implemented to turn the cost function into a quadratic form and thus the estimates for parameters can be analytically solved. Simulation results have demonstrated the effectiveness of the proposed methods, which have shown better performance in terms of estimation accuracy and computation time, compared with those conventional nonlinear estimation methods.</p>

Abstract ¡§The economic miracle of Taiwan¡¨ is the result of heavy interference of the State into economic development. After democratization, the State is not as convenient as it was with the authoritative period, as far as economic sector is concerned. The case for Bin-nan industrial exploit should be able to increase national income for 1%, but stalled for 11 years, it stays at the origin. It means that the State has lost the autonomy in forming and setting up policies that are closely related to the welfare of the public. Utilizing the Model of The theory of Claus Offe¡¦s system analysis for exploring the changes in autonomy of state after democratization, aided with case for Bin-nan industrial exploit, we discussed the economic, legitimate, and political sub-system and made throughout interpretation. It is clear that in the highly controversial case for Bin-nan industrial exploit, the State slowed down the pace of development approval in exchange of support of the administration of the public and left the capitalists to communicate and negotiate with the local and social groups. The State expressed its support of the project orally on the one hand and assist in administration operations to avoid capital flee on the other hand, which avoid the non-support of current administration from the public due to full support of capitalist, which may lead to the legitimacy crisis of the administration. During the economic development process after democratization of Taiwan, the State is still holding the dominating position in the implementation of mercantilism and is still playing the initiative role in economic development and continues in promoting capital accumulation and in pushing industried technology. The will in developing economy has indicated that the State has its preoccupies position, so the State inevitably has dual consideration in the selection of autonomy policy, which is expecting continuous capital accumulation and securing the consent from the people for its legitimate ruling base.

The daily sleep-wake cycle usually consists of three distinct states: wakefulness, non-rapid-eye-movement (NREM) and rapid-eye-movement (REM). The process of switching between different states is complex, but a common assumption is that it is regulated primarily by two processes (the circadian and the homeostatic process) via reciprocal interactions of several downstream neuron groups. These interactions not only result in often rapid transitions from one state to another, but also allow for a certain degree of bi-stability that locks the organism in a given state for some while before it switches back. In order to better understand how the behavioral states are regulated by different neuron groups, I describe how to use the S-system method for the development of a mathematical model consisting of two phases. The first phase covers the switch between wakefulness and sleep, which is controlled by the interactions between wake- and sleep-promoting neurons, whereas the second phase addresses the generation of NREM-REM alternation, which is believed to be regulated by REM-OFF and REM-ON neurons. In this set-up I interpret the circadian rhythm as external input and homeostatic regulation as a feedback controller. Both open-loop and closed-loop forms of the two-phase model are investigated and implemented. Discharging activities of the corresponding neuron groups and the switches of behavioral states are shown in the simulation results, from which we can easily identify the basic roles of wake- and sleep-promoting neurons, REM-OFF and REM-ON neurons. The special regulatory function of the neuropeptide orexin is also tested by simulation.

Made available in DSpace on 2014-12-17T14:13:35Z (GMT). No. of bitstreams: 1 MariaCGM_DISSERT.pdf: 783345 bytes, checksum: 2bbd27cd96c8b3b35673be95266c5187 (MD5) Previous issue date: 2010-09-17 / Since Demirjian's system of estimating dental maturity was first described, many researchers from different countries have tested its accuracy among diverse populations. Some of these studies have pointed out a need to determine population-specific standards. In Brazil, the Northeast region is the one that most suffers the negative impact of exodus, specially related to the increase of abandoned children in the cities. The aim of this study was to test the accuracy of Demirjian's system for assessing the dental maturity of northeastern Brazilian children, so as to present a scale for maturity score conversion into dental age developed specifically for this population. This could be used for forensic, anthropological and legal matters, and also as a model for other countries attempting to formulate their own conversion scales. Panoramic radiographs of 1,491 children (821 females and 670 males), aged 7 to 13 years, from Cear? state, northeast Brazil, were assessed by a single observer to determine dental age (DA) according to Demirjian's system. The mean percentage of intra-observer agreement was 86.6%, with a mean Cohen's Kappa coefficient of 0.67 (substantial agreement). The DA was compared by paired t-test to subjects' chronological age (CA). The differences between CA and DA in all age groups were statistically significant (p<0.0001), demonstrating a great advancement in DA among Brazilians. Scatter plots were drawn for both genders, and the data were fitted to a growth curve, y = 100/ (1 + e-a(x b)). Graphs corresponding to the 50th percentile curves were produced. A table with new values for the conversion of maturity score into dental age for northeastern Brazilian children is presented. The great advancement in DA, as obtained by Demirjian's system in this population, justified the determination of specific scores for dental maturity assessment / A estimativa da maturidade dent?ria tem sido descrita na literatura basicamente atrav?s de dois m?todos, a observa??o direta do processo de erup??o do dente na cavidade oral ou por meio de radiografias. A radiografia panor?mica, obtida por t?cnica extra-oral de uso dos raios X, ? um elemento essencial para o diagn?stico por imagens em Radiologia odontol?gica. Este trabalho apresenta dois estudos quantitativos anal?tico-descritivos utilizando o m?todo de determina??o da idade dental atrav?s de radiografia panor?mica em crian?as brasileiras nordestinas. Um estudo piloto realizado com 325 crian?as (191 meninas e 134 meninos) de 7 a 16 anos, da cidade de Fortaleza, objetivando determinar as interrela??es entre as suas idades cronol?gica (data de nascimento), ?ssea (pelo m?todo de Grewlich & Pyle) e dental (segundo Demirjian et al.). Outro estudo, j? publicado, conduzido com 1.491 crian?as (821 meninas e 670 meninos) cearenses, de 7 a 13 anos, visando avaliar a aplicabilidade do m?todo de Demirjian na popula??o estudada. Em ambos os estudos, mostra-se que a estimativa de idade dental utilizando as tabelas de convers?o de maturidade dental propostas por Demirjian et al. n?o se ad?qua ? popula??o pesquisada. Assim, uma escala de valores de convers?o de maturidade dental em idade dental foi desenvolvida especificamente para crian?as nordestinas e ? agora apresentada, visando ? sua aplica??o n?o s? na cl?nica, mas em quest?es forenses, antropol?gicas, legais e/ou criminais. As pesquisas de car?ter interdisciplinar envolveram pesquisadores das ?reas de Odontologia (Odontopediatria, Ortodontia e Radiologia); Medicina (Endocrinologia e Metabologia); e F?sica, preenchendo os requisitos de multidisciplinaridade do Programa de P?s-Gradua??o em Ci?ncias da Sa?de