Estimating equations for removal data analysis

We consider the problem of estimating a population size from successive catches taken during a removal experiment and propose two estimating functions approaches, the traditional quasi-likelihood (TQL) approach for dependent observations and the conditional quasi-likelihood (CQL) approach using the conditional mean and conditional variance of the catch given previous catches. Asymptotic covariance of the estimates and the relationship between the two methods are derived. Simulation results and application to the catch data from smallmouth bass show that the proposed estimating functions perform better than other existing methods, especially in the presence of overdispersion.

A quasi-likelihood approach for ordered categorical data with overdispersion

Quasi-likelihood (QL) methods are often used to account for overdispersion in categorical data. This paper proposes a new way of constructing a QL function that stems from the conditional mean-variance relationship. Unlike traditional QL approaches to categorical data, this QL function is, in general, not a scaled version of the ordinary log-likelihood function. A simulation study is carried out to examine the performance of the proposed QL method. Fish mortality data from quantal response experiments are used for illustration.

A Fuzzy Approximation Scheme for Sequential Learning in Pattern Recognition

An adaptive learning scheme, based on a fuzzy approximation to the gradient descent method for training a pattern classifier using unlabeled samples, is described. The objective function defined for the fuzzy ISODATA clustering procedure is used as the loss function for computing the gradient. Learning is based on simultaneous fuzzy decisionmaking and estimation. It uses conditional fuzzy measures on unlabeled samples. An exponential membership function is assumed for each class, and the parameters constituting these membership functions are estimated, using the gradient, in a recursive fashion. The induced possibility of occurrence of each class is useful for estimation and is computed using 1) the membership of the new sample in that class and 2) the previously computed average possibility of occurrence of the same class. An inductive entropy measure is defined in terms of induced possibility distribution to measure the extent of learning. The method is illustrated with relevant examples.

The genetic structure of Australasian green turtles (Chelonia mydas): Exploring the geographical scale of genetic exchange

Ecological and genetic studies of marine turtles generally support the hypothesis of natal homing, but leave open the question of the geographical scale of genetic exchange and the capacity of turtles to shift breeding sites. Here we combine analyses of mitochondrial DNA (mtDNA) variation and recapture data to assess the geographical scale of individual breeding populations and the distribution of such populations through Australasia. We conducted multiscale assessments of mtDNA variation among 714 samples from 27 green turtle rookeries and of adult female dispersal among nesting sites in eastern Australia. Many of these rookeries are on shelves that were flooded by rising sea levels less than 10 000 years (c. 450 generations) ago. Analyses of sequence variation among the mtDNA control region revealed 25 haplotypes, and their frequency distributions indicated 17 genetically distinct breeding stocks (Management Units) consisting either of individual rookeries or groups of rookeries in general that are separated by more than 500 km. The population structure inferred from mtDNA was consistent with the scale of movements observed in long-term mark-recapture studies of east Australian rookeries. Phylogenetic analysis of the haplotypes revealed five clades with significant partitioning of sequence diversity (Φ = 68.4) between Pacific Ocean and Southeast Asian/Indian Ocean rookeries. Isolation by distance was indicated for rookeries separated by up to 2000 km but explained only 12% of the genetic structure. The emerging general picture is one of dynamic population structure influenced by the capacity of females to relocate among proximal breeding sites, although this may be conditional on large population sizes as existed historically across this region.

Parameterizing Unconditional Skewness in Models for Financial Time Series

In this paper we consider the third-moment structure of a class of time series models. It is often argued that the marginal distribution of financial time series such as returns is skewed. Therefore it is of importance to know what properties a model should possess if it is to accommodate unconditional skewness. We consider modeling the unconditional mean and variance using models that respond nonlinearly or asymmetrically to shocks. We investigate the implications of these models on the third-moment structure of the marginal distribution as well as conditions under which the unconditional distribution exhibits skewness and nonzero third-order autocovariance structure. In this respect, an asymmetric or nonlinear specification of the conditional mean is found to be of greater importance than the properties of the conditional variance. Several examples are discussed and, whenever possible, explicit analytical expressions provided for all third-order moments and cross-moments. Finally, we introduce a new tool, the shock impact curve, for investigating the impact of shocks on the conditional mean squared error of return series.

Comprehensive Path-sensitive Data-flow Analysis

Data-flow analysis is an integral part of any aggressive optimizing compiler. We propose a framework for improving the precision of data-flow analysis in the presence of complex control-flow. W initially perform data-flow analysis to determine those control-flow merges which cause the loss in data-flow analysis precision. The control-flow graph of the program is then restructured such that performing data-flow analysis on the resulting restructured graph gives more precise results. The proposed framework is both simple, involving the familiar notion of product automata, and also general, since it is applicable to any forward data-flow analysis. Apart from proving that our restructuring process is correct, we also show that restructuring is effective in that it necessarily leads to more optimization opportunities. Furthermore, the framework handles the trade-off between the increase in data-flow precision and the code size increase inherent in the restructuring. We show that determining an optimal restructuring is NP-hard, and propose and evaluate a greedy strategy. The framework has been implemented in the Scale research compiler, and instantiated for the specific problem of Constant Propagation. On the SPECINT 2000 benchmark suite we observe an average speedup of 4% in the running times over Wegman-Zadeck conditional constant propagation algorithm and 2% over a purely path profile guided approach.

Matkalla suomalaiseksi ja hoiva-alan ammattilaiseksi? : Venäläis- ja virolaistaustaisten naisten ja suomalaisuuden kohtaamiset kuulumista rakentamassa

The research examines the process by which a sense of belonging to Finnish society is constructed among women of Russian and Estonian background who are multiply marginalised in Finnish society. It does so by analysing the encounters between their nationality and 'being Finnis'. Attention is focused on the question of what kind of "journey" they take after moving to Finland, how a sense of belonging is constructed especially along the paths followed in education and at work, and what kind of agency is available to them. The thesis is connected with post-colonial research and also draws from studies on citizenship and nationality as well as the social structures of interaction, when analysing careers. As the educational system forms the most central context of the research, the work is also focused on educational sociology. The research methodology includes life history and a narrative approach. The raw data is from thematic interviews concerning the life experiences of women of immigrant backgrounds. They were studying in Finland to be practical nurses or to complete Bachelor of Social Service degree. According to the study, the women had been encountered as alien, strange, and carrying a shade of "otherness". The experience of inclusion in Finnish communities and society turned out to be conditional, an inclusion based on the notion of a citizen worker, which is defined by national needs. The person from abroad is placed in the position of someone who fills gaps in the services of the welfare state. The choice of education in the care sector and the overall necessity of obtaining Finnish education turned out to be socially directed. Gendered structures of education and working life were found to act as a frame in which the decisions of the immigrant women were made. Although national education policy emphasis as an orientation to global labour markets, the immigrant student is placed above all in the position of an object to be made suitable for the Finnish labour market. Citizenship, a goal of education, requires consent to being "socialised" into Finnish society as well as learning to be Finnish. One s only option to negotiate appearing suitable as a member is to construct oneself into someone who adopts Finnish and Western cultural values, values which favour individuality. However, Finnish education is a resource to Finnishness. Finnish education enables a sense of being Finnish, and empowers the job applicant for example, and in addition to providing cultural, human and social capital strengthen inclusion as well. The study confirms the view that the encounter of an immigrant is still characterised by its colonial nature. It shows that encounters with Finns and Finnish society place the person of immigrant background, even one receiving a Finnish education, in the position of "the other". The journey as an immigrant continues. The immigrant has access only to certain predefined subject positions, which limits agency. When categorised as an immigrant, one becomes a per-son who is different and "other", while the sense of belonging as a member of Finnish society without conditions appears to be somewhat unreachable. Yet, new arrivals are capable of acting change. An immigrant woman can challenge the positions offered to her and present herself as strong. Her life story has often included struggle, and she has the fortitude strength to change her circumstances. Key words: life story, post-colonial encounter, nationality, citizenship, the career of immi-grant, position, agency

Dynamic Bayesian network inferencing for non-homogeneous complex systems

Dynamic Bayesian Networks (DBNs) provide a versatile platform for predicting and analysing the behaviour of complex systems. As such, they are well suited to the prediction of complex ecosystem population trajectories under anthropogenic disturbances such as the dredging of marine seagrass ecosystems. However, DBNs assume a homogeneous Markov chain whereas a key characteristics of complex ecosystems is the presence of feedback loops, path dependencies and regime changes whereby the behaviour of the system can vary based on past states. This paper develops a method based on the small world structure of complex systems networks to modularise a non-homogeneous DBN and enable the computation of posterior marginal probabilities given evidence in forwards inference. It also provides an approach for an approximate solution for backwards inference as convergence is not guaranteed for a path dependent system. When applied to the seagrass dredging problem, the incorporation of path dependency can implement conditional absorption and allows release from the zero state in line with environmental and ecological observations. As dredging has a marked global impact on seagrass and other marine ecosystems of high environmental and economic value, using such a complex systems model to develop practical ways to meet the needs of conservation and industry through enhancing resistance and/or recovery is of paramount importance.

State Dependent Attempt Rate Modeling of Single Cell IEEE 802.11 WLANs with Homogeneous Nodes and Poisson Arrivals

Analytical models of IEEE 802.11-based WLANs are invariably based on approximations, such as the well-known mean-field approximations proposed by Bianchi for saturated nodes. In this paper, we provide a new approach for modeling the situation when the nodes are not saturated. We study a State Dependent Attempt Rate (SDAR) approximation to model M queues (one queue per node) served by the CSMA/CA protocol as standardized in the IEEE 802.11 DCF. The approximation is that, when n of the M queues are non-empty, the attempt probability of the n non-empty nodes is given by the long-term attempt probability of n saturated nodes as provided by Bianchi's model. This yields a coupled queue system. When packets arrive to the M queues according to independent Poisson processes, we provide an exact model for the coupled queue system with SDAR service. The main contribution of this paper is to provide an analysis of the coupled queue process by studying a lower dimensional process and by introducing a certain conditional independence approximation. We show that the numerical results obtained from our finite buffer analysis are in excellent agreement with the corresponding results obtained from ns-2 simulations. We replace the CSMA/CA protocol as implemented in the ns-2 simulator with the SDAR service model to show that the SDAR approximation provides an accurate model for the CSMA/CA protocol. We also report the simulation speed-ups thus obtained by our model-based simulation.

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.

Oncolytic Adenoviruses for Gynecologic Cancer

Gene therapy is a promising novel approach for treating cancers resistant to or escaping currently available modalities. Treatment approaches are based on taking advantage of molecular differences between normal and tumor cells. Various strategies are currently in clinical development with adenoviruses as the most popular vehicle. Recent developments include improving targeting strategies for gene delivery to tumor cells with tumor specific promoters or infectivity enhancement. A rapidly developing field is as well replication competent agents, which allow improved tumor penetration and local amplification of the anti-tumor effect. Adenoviral cancer gene therapy approaches lack cross-resistance with other treatment options and therefore synergistic effects are possible. This study focused on development of adenoviral vectors suitable for treatment of various gynecologic cancer types, describing the development of the field from non-replicating adenoviral vectors to multiple-modified conditional replicating viruses. Transcriptional targeting of gynecologic cancer cells by the use of the promoter of vascular endothelial growth factor receptor type 1 (flt-1) was evaluated. Flt-1 is not expressed in the liver and thus an ideal promoter for transcriptional targeting of adenoviruses. Our studies implied that the flt-1 promoter is active in teratocarcinomas.and therefore a good candidate for development of oncolytic adenoviruses for treatment of this often problematic disease with then poor outcome. A tropism modified conditionally replicating adenovirus (CRAd), Ad5-Δ24RGD, was studied in gynecologic cancers. Ad5-Δ24RGD is an adenovirus selectively replication competent in cells defective in the p16/Rb pathway, including many or most tumor cells. The fiber of Ad5-Δ24RGD contains an integrin binding arginine-glycine-aspartic acid motif (RGD-4C), allowing coxackie-adenovirus receptor independent infection of cancer cells. This approach is attractive because expression levels of CAR are highly variable and often low on primary gynecological cancer cells. Oncolysis could be shown for a wide variety of ovarian and cervical cancer cell lines as well as primary ovarian cancer cell spheroids, a novel system developed for in vitro analysis of CRAds on primary tumor substrates. Biodistribution was evaluated and preclinical safety data was obtained by demonstrating lack of replication in human peripheral blood mononuclear cells. The efficicacy of Ad5-Δ24RGD was shown in different orthotopic murine models including a highly aggressive intraperitoneal model of disseminated ovarian cancer cells, where Ad5-Δ24RGD resulted in complete eradication of intraperitoneal disease in half of the mice. To further improve the selectivity and specificity of CRAds, triple-targeted oncolytic adenoviruses were cloned, featuring the cyclo-oxygenase-2 (cox-2) promoter, E1A transcomplementation and serotype chimerism. Those viruses were evaluated on ovarian cancer cells for specificity and oncolytic potency with regard to two different cox2 versions and three different variants of E1A (wild type, delta24 and delta2delta24). Ad5/3cox2Ld24 emerged as the best combination due to enhanced selectivity without potency lost in vitro or in an aggressive intraperitoneal orthotopic ovarian tumor model. In summary, the preclinical therapeutic efficacy of the CRAds tested in this study, taken together with promising biodistribution and safety data, suggest that these CRAds are interesting candidates for translation into clinical trials for gynecologic cancer.

Quantitative Trait Loci for CD4:CD8 Lymphocyte Ratio Are Associated with Risk of Type 1 Diabetes and HIV-1 Immune Control

Abnormal expansion or depletion of particular lymphocyte subsets is associated with clinical manifestations such as HIV progression to AIDS and autoimmune disease. We sought to identify genetic predictors of lymphocyte levels and reasoned that these may play a role in immune-related diseases. We tested 2.3 million variants for association with five lymphocyte subsets, measured in 2538 individuals from the general population, including CD4+ T cells, CD8+ T cells, CD56+ natural killer (NK) cells, and the derived measure CD4:CD8 ratio. We identified two regions of strong association. The first was located in the major histocompatibility complex (MHC), with multiple SNPs strongly associated with CD4:CD8 ratio (rs2524054, p = 2.1 × 10−28). The second region was centered within a cluster of genes from the Schlafen family and was associated with NK cell levels (rs1838149, p = 6.1 × 10−14). The MHC association with CD4:CD8 replicated convincingly (p = 1.4 × 10−9) in an independent panel of 988 individuals. Conditional analyses indicate that there are two major independent quantitative trait loci (QTL) in the MHC region that regulate CD4:CD8 ratio: one is located in the class I cluster and influences CD8 levels, whereas the second is located in the class II cluster and regulates CD4 levels. Jointly, both QTL explained 8% of the variance in CD4:CD8 ratio. The class I variants are also strongly associated with durable host control of HIV, and class II variants are associated with type-1 diabetes, suggesting that genetic variation at the MHC may predispose one to immune-related diseases partly through disregulation of T cell homeostasis.

Single household domestic water heater design and control utilising PV energy: The untapped energy storage solution

Photovoltaic (PV) panels and electric domestic water heater with storage (DWH) are widely used in households in many countries. However, DWH should be explored as an energy storage mechanism before batteries when households have excess PV energy. Through a residential case study in Queensland, Australia, this paper presents a new optimized design and control solution to reduce water heating costs by utilizing existing DWH energy storage capacity and increasing PV self-consumption for water heating. The solution is produced by evaluating the case study energy profile and numerically maximizing the use of PV for DWH. A conditional probability matrix for different solar insolation and hot water usage days is developed to test the solution. Compared to other tariffs, this solution shows cost reduction from 20.8% to 63.3% This new solution could encourage solar households move to a more economical and carbon neutral water heating method.

Separate and interacting effects within the catechol-O-methyltransferase (COMT) are associated with schizophrenia

Several lines of evidence have implicated the catechol-O-methyltransferase (COMT) gene as a candidate for schizophrenia (SZ) susceptibility, not only because it encodes a key dopamine catabolic enzyme but also because it maps to the velocardiofacial syndrome region of chromosome 22q11 which has long been associated with SZ predisposition. The interest in COMT as a candidate SZ risk factor has led to numerous case-control and family-based studies, with the majority placing emphasis on examining a functional Val/Met polymorphism within this enzyme. Unfortunately, these studies have continually produced conflicting results. To assess the genetic contribution of other COMT variants to SZ susceptibility, we investigated three single-nucleotide polymorphisms (SNPs) (rs737865, rs4633, rs165599) in addition to the Val/Met variant (rs4680) in a highly selected sample of Australian Caucasian families containing 107 patients with SZ. The Val/Met and rs4633 variants showed nominally significant associations with SZ (P<0.05), although neither of the individual SNPs remained significant after adjusting for multiple testing (most significant P=0.1174). However, haplotype analyses showed strong evidence of an association; the most significant being the three-marker haplotype rs737865-rs4680-rs165599 (global P=0.0022), which spans more than 26 kb. Importantly, conditional analyses indicated the presence of two separate and interacting effects within this haplotype, irrespective of gender. In addition, our results indicate the Val/Met polymorphism is not disease-causing and is simply in strong linkage disequilibrium with a causative effect, which interacts with another as yet unidentified variant approximately 20 kb away. These results may help explain the inconsistent results reported on the Val/Met polymorphism and have important implications for future investigations into the role of COMT in SZ susceptibility.

Bayesian estimation of the dynamics of pandemic (H1N1) 2009 influenza transmission in Queensland: A space–time SIR-based model

Background A pandemic strain of influenza A spread rapidly around the world in 2009, now referred to as pandemic (H1N1) 2009. This study aimed to examine the spatiotemporal variation in the transmission rate of pandemic (H1N1) 2009 associated with changes in local socio-environmental conditions from May 7–December 31, 2009, at a postal area level in Queensland, Australia. Method We used the data on laboratory-confirmed H1N1 cases to examine the spatiotemporal dynamics of transmission using a flexible Bayesian, space–time, Susceptible-Infected-Recovered (SIR) modelling approach. The model incorporated parameters describing spatiotemporal variation in H1N1 infection and local socio-environmental factors. Results The weekly transmission rate of pandemic (H1N1) 2009 was negatively associated with the weekly area-mean maximum temperature at a lag of 1 week (LMXT) (posterior mean: −0.341; 95% credible interval (CI): −0.370–−0.311) and the socio-economic index for area (SEIFA) (posterior mean: −0.003; 95% CI: −0.004–−0.001), and was positively associated with the product of LMXT and the weekly area-mean vapour pressure at a lag of 1 week (LVAP) (posterior mean: 0.008; 95% CI: 0.007–0.009). There was substantial spatiotemporal variation in transmission rate of pandemic (H1N1) 2009 across Queensland over the epidemic period. High random effects of estimated transmission rates were apparent in remote areas and some postal areas with higher proportion of indigenous populations and smaller overall populations. Conclusions Local SEIFA and local atmospheric conditions were associated with the transmission rate of pandemic (H1N1) 2009. The more populated regions displayed consistent and synchronized epidemics with low average transmission rates. The less populated regions had high average transmission rates with more variations during the H1N1 epidemic period.