Weighted rank regression for clustered data analysis

We consider ranked-based regression models for clustered data analysis. A weighted Wilcoxon rank method is proposed to take account of within-cluster correlations and varying cluster sizes. The asymptotic normality of the resulting estimators is established. A method to estimate covariance of the estimators is also given, which can bypass estimation of the density function. Simulation studies are carried out to compare different estimators for a number of scenarios on the correlation structure, presence/absence of outliers and different correlation values. The proposed methods appear to perform well, in particular, the one incorporating the correlation in the weighting achieves the highest efficiency and robustness against misspecification of correlation structure and outliers. A real example is provided for illustration.

Rank-based regression for analysis of repeated measures

We consider rank-based regression models for repeated measures. To account for possible withinsubject correlations, we decompose the total ranks into between- and within-subject ranks and obtain two different estimators based on between- and within-subject ranks. A simple perturbation method is then introduced to generate bootstrap replicates of the estimating functions and the parameter estimates. This provides a convenient way for combining the corresponding two types of estimating function for more efficient estimation.

Induced smoothing for rank regression with censored survival times

Adaptions of weighted rank regression to the accelerated failure time model for censored survival data have been successful in yielding asymptotically normal estimates and flexible weighting schemes to increase statistical efficiencies. However, for only one simple weighting scheme, Gehan or Wilcoxon weights, are estimating equations guaranteed to be monotone in parameter components, and even in this case are step functions, requiring the equivalent of linear programming for computation. The lack of smoothness makes standard error or covariance matrix estimation even more difficult. An induced smoothing technique overcame these difficulties in various problems involving monotone but pure jump estimating equations, including conventional rank regression. The present paper applies induced smoothing to the Gehan-Wilcoxon weighted rank regression for the accelerated failure time model, for the more difficult case of survival time data subject to censoring, where the inapplicability of permutation arguments necessitates a new method of estimating null variance of estimating functions. Smooth monotone parameter estimation and rapid, reliable standard error or covariance matrix estimation is obtained.

Efficient regression analysis with ranked-set sampling

This article is motivated by a lung cancer study where a regression model is involved and the response variable is too expensive to measure but the predictor variable can be measured easily with relatively negligible cost. This situation occurs quite often in medical studies, quantitative genetics, and ecological and environmental studies. In this article, by using the idea of ranked-set sampling (RSS), we develop sampling strategies that can reduce cost and increase efficiency of the regression analysis for the above-mentioned situation. The developed method is applied retrospectively to a lung cancer study. In the lung cancer study, the interest is to investigate the association between smoking status and three biomarkers: polyphenol DNA adducts, micronuclei, and sister chromatic exchanges. Optimal sampling schemes with different optimality criteria such as A-, D-, and integrated mean square error (IMSE)-optimality are considered in the application. With set size 10 in RSS, the improvement of the optimal schemes over simple random sampling (SRS) is great. For instance, by using the optimal scheme with IMSE-optimality, the IMSEs of the estimated regression functions for the three biomarkers are reduced to about half of those incurred by using SRS.

Spontaneous symmetry breaking in twisted noncommutative quantum theories

We analyze aspects of symmetry breaking for Moyal spacetimes within a quantization scheme which preserves the twisted Poincare´ symmetry. Towards this purpose, we develop the Lehmann-Symanzik- Zimmermann (LSZ) approach for Moyal spacetimes. The latter gives a formula for scattering amplitudes on these spacetimes which can be obtained from the corresponding ones on the commutative spacetime. This formula applies in the presence of spontaneous breakdown of symmetries as well. We also derive Goldstone’s theorem on Moyal spacetime. The formalism developed here can be directly applied to the twisted standard model.

Methodological and Empirical Advances in the Quantitative Analysis of Spontaneous Responses in Psychophysiological Time Series

The aim of the present study was to advance the methodology and use of time series analysis to quantify dynamic structures in psychophysiological processes and thereby to produce information on spontaneously coupled physiological responses and their behavioral and experiential correlates. Series of analyses using both simulated and empirical cardiac (IBI), electrodermal (EDA), and facial electromyographic (EMG) data indicated that, despite potential autocorrelated structures, smoothing increased the reliability of detecting response coupling from an interindividual distribution of intraindividual measures and that especially the measures of covariance produced accurate information on the extent of coupled responses. This methodology was applied to analyze spontaneously coupled IBI, EDA, and facial EMG responses and vagal activity in their relation to emotional experience and personality characteristics in a group of middle-aged men (n = 37) during the administration of the Rorschach testing protocol. The results revealed new characteristics in the relationship between phasic end-organ synchronization and vagal activity, on the one hand, and individual differences in emotional adjustment to novel situations on the other. Specifically, it appeared that the vagal system is intimately related to emotional and social responsivity. It was also found that the lack of spontaneously synchronized responses is related to decreased energetic arousal (e.g., depression, mood). These findings indicate that the present process analysis approach has many advantages for use in both experimental and applied research, and that it is a useful new paradigm in psychophysiological research. Keywords: Autonomic Nervous System; Emotion; Facial Electromyography; Individual Differences; Spontaneous Responses; Time Series Analysis; Vagal System

The effect of interrogative function on intonation in spontaneous and read Finnish

Goals This study aims to map the effect of interrogative function on the intonation of spontaneous and read Finnish. Earlier research shows that the most prominent feature in Finnish question intonation is an appeal to the listener. Question word questions typically start with a high peak which is followed by falling intonation. In yes/no questions, F0 remains on a high level until the word carrying sentence stress and then falls. Final rises are mainly found in intonation clichés such as "Ai mitä?" ("What?") These earlier results are based on read speech and enacted dialogues. In this study, questions and statements found in spontaneous dialogues were compared. These utterances were also compared with read versions of the same utterances. Fundamental frequency values were compared using a mixed model. Contours were also grouped using auditory and visual inspection. Thus it was possible to compare frequencies of contour types according to utterance type and speech style. The position of questions in the F0 distribution of the whole material was also investigated in this study. Method The material consisted of four spontaneous dialogues and their read versions. The speakers were young adults from the Helsinki metropolitan area, four females and four males. The whole material was first divided into broad dialogue function categories arising from the material and F0 curves were calculated for each category. After this, 277 questions and 244 statements were selected for closer inspection. Values reflecting F0 distribution and contour shape were measured from the F0 contours of these utterances. A mixed model was used to analyse the differences. Utterance type, question type, speech style and speaker gender were used as fixed effects. The frequencies of F0 contour types were compared using a Chi square test. Additional material in this study came from eight young female speakers in central Finland. Results and conclusions In the mixed model analysis, significant differences were found both between questions and statements and between spontaneous and read speech. Generally, utterance type affected the variables reflecting contour type while speech style affected the variables reflecting F0 distribution. The effect of question type was not clearly visible. In read speech the contours resembled earlier results more closely. Speakers had different strategies in differentiating between questions and statements. In the whole material, F0 was slightly higher in questions than in statements. The effect of dialectal background could be seen in the contour types. The results show that interrogative function affects intonation in both spontaneous and read Finnish.

Spontaneous fermentation of traditional sago starch in Papua New Guinea

Sago starch is an important dietary carbohydrate in lowland Papua New Guinea (PNG). An investigation was conducted to determine whether microbes play a role in its preservation using traditional methods. In 12 stored sago samples collected from PNG villages, lactic acid bacteria (LAB) were present (>= 3.6 x 10(4) cfu/g) and pH ranged from 6.8 to 4.2. Acetic and propionic acids were detected in all samples, while butyric, lactic and valeric acids were present in six or more. In freshly prepared sago, held in sealed containers in the laboratory at 30 degrees C, spontaneous fermentation by endogenous microflora of sago starch was observed. This was evident by increasing concentrations of acetic, butyric and lactic acids over 4 weeks, and pH reducing from 4.9 to 3.1: both LAB and yeasts were involved. Survival of potential bacterial pathogens was monitored by seeding sago starch with similar to 10(4)/g of selected organisms. Numbers of Bacillus cereus, Listeria monocytogenes and Staphylococcus aureus fell to <30/g within 7 days. Salmonella sp. was present only in low numbers after 7 days (<36/g), but Escherichia coli was still detectable after three weeks (>10(2)/g). Fermentation appeared to increase the storability and safety of the product.

Cellular and network mechanisms generating spontaneous population events in the immature rat hippocampus

Distinct endogenous network events, generated independently of sensory input, are a general feature of various structures of the immature central nervous system. In the immature hippocampus, these type of events are seen as "giant depolarizing potentials" (GDPs) in intracellular recordings in vitro. GABA, the major inhibitory neurotransmitter of the adult brain, has a depolarizing action in immature neurons, and GDPs have been proposed to be driven by GABAergic transmission. Moreover, GDPs have been thought to reflect an early pattern that disappears during development in parallel with the maturation of hyperpolarizing GABAergic inhibition. However, the adult hippocampus in vivo also generates endogenous network events known as sharp (positive) waves (SPWs), which reflect synchronous discharges of CA3 pyramidal neurons and are thought to be involved in cognitive functions. In this thesis, mechanisms of GDP generation were studied with intra- and extracellular recordings in the neonatal rat hippocampus in vitro and in vivo. Immature CA3 pyramidal neurons were found to generate intrinsic bursts of spikes and to act as cellular pacemakers for GDP activity whereas depolarizing GABAergic signalling was found to have a temporally non-patterned facilitatory role in the generation of the network events. Furthermore, the data indicate that the intrinsic bursts of neonatal CA3 pyramidal neurons and, consequently, GDPs are driven by a persistent Na+ current and terminated by a slow Ca2+-dependent K+ current. Gramicidin-perforated patch recordings showed that the depolarizing driving force for GABAA receptor-mediated actions is provided by Cl- uptake via the Na-K-C1 cotransporter, NKCC1, in the immature CA3 pyramids. A specific blocker of NKCC1, bumetanide, inhibited SPWs and GDPs in the neonatal rat hippocampus in vivo and in vitro, respectively. Finally, pharmacological blockade of the GABA transporter-1 prolonged the decay of the large GDP-associated GABA transients but not of single postsynaptic GABAA receptor-mediated currents. As a whole the data in this thesis indicate that the mechanism of GDP generation, based on the interconnected network of bursting CA3 pyramidal neurons, is similar to that involved in adult SPW activity. Hence, GDPs do not reflect a network pattern that disappears during development but they are the in vitro counterpart of neonatal SPWs.

To reactivate or not to reactivate : Control of KSHV lytic replication is essential for apoptosis in response to p53 restoration

Kaposi's sarcoma herpesvirus (KSHV) is an oncogenic human virus and the causative agent of three human malignancies: Kaposi's sarcoma (KS), Multicentric Castleman's Disease (MCD), and primary effusion lymphoma (PEL). In tumors, KSHV establishes latent infection during which it produces no infectious particles. Latently infected cells can enter the lytic replication cycle, and upon provision of appropriate cellular signals, produce progeny virus. PEL, commonly described in patients with AIDS, represents a diffuse large-cell non-Hodgkin's lymphoma, with median survival time less than six months after diagnosis. As tumor suppressor gene TP53 mutations occur rarely in PEL, the aim of this thesis was to investigate whether non-genotoxic activation of the p53 pathway can eradicate malignant PEL cells. This thesis demonstrates that Nutlin-3, a small-molecule inhibitor of the p53-MDM2 interaction, efficiently restored p53 function in PEL cells, leading to cell cycle arrest and massive apoptosis. Furthermore, we found that KSHV infection activated DNA damage signaling, rendering the cells more sensitive to p53-dependent cell death. We also showed in vivo the therapeutic potential of p53 restoration that led to regression of subcutaneous and intraperitoneal PEL tumor xenografts without adversely affecting normal cells. Importantly, we demonstrated that in a small subset of intraperitoneal PEL tumors, spontaneous induction of viral reactivation dramatically impaired Nutlin-3-induced p53-mediated apoptosis. Accordingly, we found that elevated KSHV lytic transcripts correlated with PEL tumor burden in animals and that inhibition of viral reactivation in vitro restored cytotoxic activity of a small-molecule inhibitor of the p53-MDM2 interaction. Latency provides a unique opportunity for KSHV to escape host immune surveillance and to establish persistent infections. However, to maintain viral reservoirs and spread to other hosts, KSHV must be reactivated from latency and enter into the lytic growth phase. We showed that phosphorylation of nucleolar phosphoprotein nucleophosmin (NPM) by viral cyclin-CDK6 is critical for establishment and maintenance of the KSHV latency. In short, this study provides evidence that the switch between latent phase and lytic replication is a critical step that determines the outcome of viral infection and the pathogenesis of KSHV-induced malignancies. Our data may thus contribute to development of novel targeted therapies for intervention and treatment of KSHV-associated cancers.

Regression Rate Studies in Hypergolic System

Regression ra tes of a hypergolic combination of fuel and oxidiser have been experimentally measured as a function of chamber pressure, mass flux and the percentage component of the hypergolic compound in natural rubber. The hypergolic compound used is difurfurylidene cyclohexanone (DFCH) which is hypergolic with the oxidiser red fuming nitric acid (RFNA) with ignition dela y of 60-70 ms. The data of weight loss versus time is obtained for burn times varying between 5 and 20 seconds. Two methods of correlating the data using mass flux of oxidiser and the total flux of hot gases have shown that index n of the regression law r=aGoxn or r=aGnxn-1 (x the axial distance) is about 0.5 or a little lower and not 0.8 even though the flow through the port is turbulent. It is argued that the reduction of index n is due to heterogeneous reaction between the liquid oxidiser and the hypergolic fuel component on the surface.

Joint Regression and Association Models for Repeated Categorical Responses

The focus of this study is on statistical analysis of categorical responses, where the response values are dependent of each other. The most typical example of this kind of dependence is when repeated responses have been obtained from the same study unit. For example, in Paper I, the response of interest is the pneumococcal nasopharengyal carriage (yes/no) on 329 children. For each child, the carriage is measured nine times during the first 18 months of life, and thus repeated respones on each child cannot be assumed independent of each other. In the case of the above example, the interest typically lies in the carriage prevalence, and whether different risk factors affect the prevalence. Regression analysis is the established method for studying the effects of risk factors. In order to make correct inferences from the regression model, the associations between repeated responses need to be taken into account. The analysis of repeated categorical responses typically focus on regression modelling. However, further insights can also be gained by investigating the structure of the association. The central theme in this study is on the development of joint regression and association models. The analysis of repeated, or otherwise clustered, categorical responses is computationally difficult. Likelihood-based inference is often feasible only when the number of repeated responses for each study unit is small. In Paper IV, an algorithm is presented, which substantially facilitates maximum likelihood fitting, especially when the number of repeated responses increase. In addition, a notable result arising from this work is the freely available software for likelihood-based estimation of clustered categorical responses.

Deformation and stability regression models for soil nail walls

Lateral displacement and global stability are the two main stability criteria for soil nail walls. Conventional design methods do not adequately address the deformation behaviour of soil nail walls, owing to the complexity involved in handling a large number of influencing factors. Consequently, limited methods of deformation estimates based on empirical relationships and in situ performance monitoring are available in the literature. It is therefore desirable that numerical techniques and statistical methods are used in order to gain a better insight into the deformation behaviour of soil nail walls. In the present study numerical experiments are conducted using a 2 4 factorial design method. Based on analysis of the maximum lateral deformation and factor-of-safety observations from the numerical experiments, regression models for maximum lateral deformation and factor-of-safety prediction are developed and checked for adequacy. Selection of suitable design factors for the 2 4 factorial design of numerical experiments enabled the use of the proposed regression models over a practical range of soil nail wall heights and in situ soil variability. It is evident from the model adequacy analyses and illustrative example that the proposed regression models provided a reasonably good estimate of the lateral deformation and global factor of safety of the soil nail walls.

Land use regression model (LUR) for ultrafine particles in Brisbane

Traffic-related air pollution has been associated with a wide range of adverse health effects. One component of traffic emissions that has been receiving increasing attention is ultrafine particles(UFP, < 100 nm), which are of concern to human health due to their small diameters. Vehicles are the dominant source of UFP in urban environments. Small-scale variation in ultrafine particle number concentration (PNC) can be attributed to local changes in land use and road abundance. UFPs are also formed as a result of particle formation events. Modelling the spatial patterns in PNC is integral to understanding human UFP exposure and also provides insight into particle formation mechanisms that contribute to air pollution in urban environments. Land-use regression (LUR) is a technique that can use to improve the prediction of air pollution.