Statistical analysis of the associations of hereditary factors with the risk of Type 1 diabetes and Diabetic Nephropathy based on the familial data collected through ascertaiment from population-based registers

In genetic epidemiology, population-based disease registries are commonly used to collect genotype or other risk factor information concerning affected subjects and their relatives. This work presents two new approaches for the statistical inference of ascertained data: a conditional and full likelihood approaches for the disease with variable age at onset phenotype using familial data obtained from population-based registry of incident cases. The aim is to obtain statistically reliable estimates of the general population parameters. The statistical analysis of familial data with variable age at onset becomes more complicated when some of the study subjects are non-susceptible, that is to say these subjects never get the disease. A statistical model for a variable age at onset with long-term survivors is proposed for studies of familial aggregation, using latent variable approach, as well as for prospective studies of genetic association studies with candidate genes. In addition, we explore the possibility of a genetic explanation of the observed increase in the incidence of Type 1 diabetes (T1D) in Finland in recent decades and the hypothesis of non-Mendelian transmission of T1D associated genes. Both classical and Bayesian statistical inference were used in the modelling and estimation. Despite the fact that this work contains five studies with different statistical models, they all concern data obtained from nationwide registries of T1D and genetics of T1D. In the analyses of T1D data, non-Mendelian transmission of T1D susceptibility alleles was not observed. In addition, non-Mendelian transmission of T1D susceptibility genes did not make a plausible explanation for the increase in T1D incidence in Finland. Instead, the Human Leucocyte Antigen associations with T1D were confirmed in the population-based analysis, which combines T1D registry information, reference sample of healthy subjects and birth cohort information of the Finnish population. Finally, a substantial familial variation in the susceptibility of T1D nephropathy was observed. The presented studies show the benefits of sophisticated statistical modelling to explore risk factors for complex diseases.

Statistical analysis of spectral data: A methodology for designing an intelligent monitoring system for the diabetic foot

Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

A differential transformation technique for the analysis of a class of non-linear time varying systems

The scope of the differential transformation technique, developed earlier for the study of non-linear, time invariant systems, has been extended to the domain of time-varying systems by modifications to the differential transformation laws proposed therein. Equivalence of a class of second-order, non-linear, non-autonomous systems with a linear autonomous model of second order is established through these transformation laws. The feasibility of application of this technique in obtaining the response of such non-linear time-varying systems is discussed.

The Feminist Transformation of Bioethics : An Analysis of Theoretical Perspectives and Practical Applications in Feminist Bioethics

The purpose of this study is to examine how transformation is defining feminist bioethics and to determine the nature of this transformation. Behind the quest for transformation is core feminism and its political implications, namely, that women and other marginalized groups have been given unequal consideration in society and the sciences and that this situation is unacceptable and should be remedied. The goal of the dissertation is to determine how feminist bioethicists integrate the transformation into their respective fields and how they apply the potential of feminism to bioethical theories and practice. On a theoretical level, feminist bioethicists wish to reveal how current ways of knowing are based on inequality. Feminists pay special attention especially to communal and political contexts and to the power relations endorsed by each community. In addition, feminist bioethicists endorse relational ethics, a relational account of the self in which the interconnectedness of persons is important. On the conceptual level, feminist bioethicists work with beliefs, concepts, and practices that give us our world. As an example, I examine how feminist bioethicists have criticized and redefined the concept of autonomy. Feminist bioethicists emphasize relational autonomy, which is based on the conviction that social relationships shape moral identities and values. On the practical level, I discuss stem cell research as a test case for feminist bioethics and its ability to employ its methodologies. Analyzing these perspectives allowed me first, to compare non-feminist and feminist accounts of stem cell ethics and, second, to analyze feminist perspectives on the novel biotechnology. Along with offering a critical evaluation of the stem cell debate, the study shows that sustainable stem cell policies should be grounded on empirical knowledge about how donors perceive stem cell research and the donation process. The study indicates that feminist bioethics should develop the use of empirical bioethics, which takes the nature of ethics seriously: ethical decisions are provisional and open for further consideration. In addition, the study shows that there is another area of development in feminist bioethics: the understanding of (moral) agency. I argue that agency should be understood to mean that actions create desires.

A statistical analysis of audience sound absorption (A)

The absorption produced by the audience in concert halls is considered a random variable. Beranek's proposal [L. L. Beranek, Music, Acoustics and Architecture (Wiley, New York, 1962), p. 543] that audience absorption is proportional to the area they occupy and not to their number is subjected to a statistical hypothesis test. A two variable linear regression model of the absorption with audience area and residual area as regressor variables is postulated for concert halls without added absorptive materials. Since Beranek's contention amounts to the statement that audience absorption is independent of the seating density, the test of the hypothesis lies in categorizing halls by seating density and examining for significant differences among slopes of regression planes of the different categories. Such a test shows that Beranek's hypothesis can be accepted. It is also shown that the audience area is a better predictor of the absorption than the audience number. The absorption coefficients and their 95% confidence limits are given for the audience and residual areas. A critique of the regression model is presented.

Evolution of Transformation Texture in a Metastable B - Titanium Alloy

Texture evolution in h. c. p. (alpha) phase derived from aging of a differently processed metastable b.c.c. (beta) titanium alloy was investigated. The study was aimed at examining (i) the effect of different b. c. c. cold rolling textures and (ii) the effect of different defect structures on the h. c. p transformation texture. The alloy metastable beta alloy Ti-10V-4.5Fe-1.5Al was rolled at room temperature by unidirectional (UDR) and multi-step cross rolling (MSCR). A piece of the as-rolled materials were subjected to aging in order to derive the h. c. p. (alpha) phase. In the other route, the as-rolled materials were recrystallized and then aged. Textures were measured using X-ray as well as Electron Back Scatter Diffraction. Rolling texture of beta phase, as characterized by the presence of a strong gamma fibre, was found stronger in M S C R compared to UDR, although they were qualitatively similar. The stronger texture of MSCR sample could be attributed to the inhomogeneous deformation taking place in the sample that might contribute to weakening of texture. Upon recrystallization in beta phase field close to beta-transus. the textures qualitatively resembled the corresponding beta deformation textures; however, they got strengthed. The aging of differently beta rolled samples resulted in the product alpha-phase with different textures. The (UDR + Aged) sample had a stronger texture than (MSCR + Aged) sample, which could be due to continuation of defect accumulation in UDR sample, thus providing more potential sites for the nucleation of alpha phase. The trend was reversed in samples recrystallized prior to aging. The (MSCR + Recrystallized + Aged) sample showed stronger texture of alpha phase than the (UDR + Recrystallized + Aged) sample. This could be attributed to extensive defect annihilation in the UDR sample on recrystallization prior to aging. The (MSCR + Aged) sample exhibited more alpha variants when compared to (MSCR + Recrystallized + Aged) sample. This has been attributed to the availability of more potential sites for nucleation of alpha phase in the former. It could be concluded that alpha transformation texture depends mainly on the defect structure of the parent phase.

Statistical Analysis of Wrist Pulse Signals Obtained Under Different Food Intake Conditions

It is well known that wrist pulse signals contain information about the status of health of a person and hence diagnosis based on pulse signals has assumed great importance since long time. In this paper the efficacy of signal processing techniques in extracting useful information from wrist pulse signals has been demonstrated by using signals recorded under two different experimental conditions viz. before lunch condition and after lunch condition. We have used Pearson's product-moment correlation coefficient, which is an effective measure of phase synchronization, in making a statistical analysis of wrist pulse signals. Contour plots and box plots are used to illustrate various differences. Two-sample t-tests show that the correlations show statistically significant differences between the groups. Results show that the correlation coefficient is effective in distinguishing the changes taking place after having lunch. This paper demonstrates the ability of the wrist pulse signals in detecting changes occurring under two different conditions. The study assumes importance in view of limited literature available on the analysis of wrist pulse signals in the case of food intake and also in view of its potential health care applications.

Statistical analysis of synthetic earthquake catalogs generated by models with various levels of fault zone disorder

The stress release model, a stochastic version of the elastic rebound theory, is applied to the large events from four synthetic earthquake catalogs generated by models with various levels of disorder in distribution of fault zone strength (Ben-Zion, 1996) They include models with uniform properties (U), a Parkfield-type asperity (A), fractal brittle properties (F), and multi-size-scale heterogeneities (M). The results show that the degree of regularity or predictability in the assumed fault properties, based on both the Akaike information criterion and simulations, follows the order U, F, A, and M, which is in good agreement with that obtained by pattern recognition techniques applied to the full set of synthetic data. Data simulated from the best fitting stress release models reproduce, both visually and in distributional terms, the main features of the original catalogs. The differences in character and the quality of prediction between the four cases are shown to be dependent on two main aspects: the parameter controlling the sensitivity to departures from the mean stress level and the frequency-magnitude distribution, which differs substantially between the four cases. In particular, it is shown that the predictability of the data is strongly affected by the form of frequency-magnitude distribution, being greatly reduced if a pure Gutenburg-Richter form is assumed to hold out to high magnitudes.

The degree of predictability of earthquakes in several regions of China: statistical analysis of historical data

The stress release model, a stochastic version of the elastic-rebound theory, is applied to the historical earthquake data from three strong earthquake-prone regions of China, including North China, Southwest China, and the Taiwan seismic regions. The results show that the seismicity along a plate boundary (Taiwan) is more active than in intraplate regions (North and Southwest China). The degree of predictability or regularity of seismic events in these seismic regions, based on both the Akaike information criterion (AIC) and fitted sensitivity parameters, follows the order Taiwan, Southwest China, and North China, which is further identified by numerical simulations. (c) 2004 Elsevier Ltd. All rights reserved.