Susceptibility locus on chromosome 1q23-25 for a schizophrenia subtype resembling deficit schizophrenia identified by latent class analysis

Context: Identifying susceptibility genes for schizophrenia may be complicated by phenotypic heterogeneity, with some evidence suggesting that phenotypic heterogeneity reflects genetic heterogeneity. Objective: To evaluate the heritability and conduct genetic linkage analyses of empirically derived, clinically homogeneous schizophrenia subtypes. Design: Latent class and linkage analysis. Setting: Taiwanese field research centers. Participants: The latent class analysis included 1236 Han Chinese individuals with DSM-IV schizophrenia. These individuals were members of a large affected-sibling-pair sample of schizophrenia (606 ascertained families), original linkage analyses of which detected a maximum logarithm of odds (LOD) of 1.8 (z = 2.88) on chromosome 10q22.3. Main Outcome Measures: Multipoint exponential LOD scores by latent class assignment and parametric heterogeneity LOD scores. Results: Latent class analyses identified 4 classes, with 2 demonstrating familial aggregation. The first (LC2) described a group with severe negative symptoms, disorganization, and pronounced functional impairment, resembling “deficit schizophrenia.” The second (LC3) described a group with minimal functional impairment, mild or absent negative symptoms, and low disorganization. Using the negative/deficit subtype, we detected genome-wide significant linkage to 1q23-25 (LOD = 3.78, empiric genome-wide P = .01). This region was not detected using the DSM-IV schizophrenia diagnosis, but has been strongly implicated in schizophrenia pathogenesis by previous linkage and association studies.Variants in the 1q region may specifically increase risk for a negative/deficit schizophrenia subtype. Alternatively, these results may reflect increased familiality/heritability of the negative class, the presence of multiple 1q schizophrenia risk genes, or a pleiotropic 1q risk locus or loci, with stronger genotype-phenotype correlation with negative/deficit symptoms. Using the second familial latent class, we identified nominally significant linkage to the original 10q peak region. Conclusion: Genetic analyses of heritable, homogeneous phenotypes may improve the power of linkage and association studies of schizophrenia and thus have relevance to the design and analysis of genome-wide association studies.

Some studies on free vibration of composite laminates

Free vibration analysis is carried out to study the vibration characteristics of composite laminates using the modified shear deformation, layered, composite plate theory and employing the Rayleigh-Ritz energy approach. The analysis is presented in a unified form so as to incorporate all different combinations of laminate boundary conditions and with full coverage with regard to the various design parameters of a laminated plate. A parametric study is made using a beam characteristic function as the admissible function for the numerical calculations. The numerical results presented here are for an example case of fully clamped boundary conditions and are compared with previously published results. The effect of parameters, such as the aspect ratio of plates, ply-angle, number of layers and also the thickness ratios of plies in laminates on the frequencies of the laminate, is systematically studied. It is found that for anti-symmetric angle-ply or cross-ply laminates unique numerical values of the thickness ratios exist which improve the vibration characteristics of such laminates. Numerical values of the non-dimensional frequencies and nodal patterns, using the thickness ratio distribution of the plies, are then obtained for clamped laminates, fabricated out of various commonly used composite materials, and are presented in the form of the design curves.

Significant evidence of one or more susceptibility loci for endometriosis with near-Mendelian inheritance on chromosome 7p13-15

BACKGROUND: Endometriosis is a common disease with a heritable component. The collaborative International Endogene Study consists of two data sets (Oxford and Australia) comprising 1176 families with multiple affected. The aim was to investigate whether the apparent concentration of cases in a proportion of families could be explained by one or more rare variants with (near-)Mendelian autosomal inheritance. METHODS AND RESULTS: Linkage analyses (aimed at finding chromosomal regions harbouring disease-predisposing genes) were conducted in families with three or more affected (Oxford: n = 52; Australia: n = 196). In the Oxford data set, a non-parametric linkage score (Kong & Cox (K&C) Log of ODds (LOD)) of 3.52 was observed on chromosome 7p (genome-wide significance P = 0.011). A parametric MOD score (equal to maximum LOD maximized over 357 possible inheritance models) of 3.89 was found at 65.72 cM (D7S510) for a dominant model with reduced penetrance. After including the Australian data set, the non-parametric K&C LOD of the combined data set was 1.46 at 57.3 cM; the parametric analysis found an MOD score of 3.30 at D7S484 (empirical significance: P = 0.035) for a recessive model with high penetrance. Critical recombinant analysis narrowed the probable region of linkage down to overlapping 6.4 Mb and 11 Mb intervals containing 48 and 96 genes, respectively. CONCLUSIONS: This is the first report to suggest that there may be one or more high-penetrance susceptibility loci for endometriosis with (near-)Mendelian inheritance.

Analysis-By-Synthesis Based Switched Transform Domain Split Vq Using Gaussian Mixture Model

Using analysis-by-synthesis (AbS) approach, we develop a soft decision based switched vector quantization (VQ) method for high quality and low complexity coding of wideband speech line spectral frequency (LSF) parameters. For each switching region, a low complexity transform domain split VQ (TrSVQ) is designed. The overall rate-distortion (R/D) performance optimality of new switched quantizer is addressed in the Gaussian mixture model (GMM) based parametric framework. In the AbS approach, the reduction of quantization complexity is achieved through the use of nearest neighbor (NN) TrSVQs and splitting the transform domain vector into higher number of subvectors. Compared to the current LSF quantization methods, the new method is shown to provide competitive or better trade-off between R/D performance and complexity.

Numerical studies on CFRP strengthened steel circular members under marine environment

The durability of carbon fibre reinforced polymer (CFRP) strengthened steel circular hollow section (CHS) members has now become a real challenge to researchers. In addition, various parameters that may affect the durability of such members have not been revealed yet. This paper presents brief experimental results and the first finite element (FE) approach of CFRP strengthened steel CHS beams conditioned in simulated sea water, along with an accelerated corrosion environment at ambient (24 OC ± 4 OC) and 50 OC temperatures. The beams were loaded to failure under four-point bending. It was found that the strength and stiffness reduced significantly after conditioning in an accelerated corrosion environment. Numerical simulation is implemented using the ABAQUS static general approach. A cohesive element was utilised to model the interface element and an 8-node quadrilateral in-plane general-purpose continuum shell was used to model CFRP elements. A mixed mode cohesive law was deployed for all the three components of stresses in the proposed FE approach, which were one normal component and two shear components. The validity of the FE models was ascertained by comparing the ultimate load and load vs deflection response from experimental results. A range of parametric studies were conducted to investigate the effects of bond length, adhesive types, thickness and diameter of tubes. The results of parametric studies indicated that the adhesive with high tensile modulus performed better and durability design factors varied from section to section.

Components of productivity growth in Finnish agriculture

The objective was to measure productivity growth and its components in Finnish agriculture, especially in dairy farming. The objective was also to compare different methods and models - both parametric (stochastic frontier analysis) and non-parametric (data envelopment analysis) - in estimating the components of productivity growth and the sensitivity of results with respect to different approaches. The parametric approach was also applied in the investigation of various aspects of heterogeneity. A common feature of the first three of five articles is that they concentrate empirically on technical change, technical efficiency change and the scale effect, mainly on the basis of the decompositions of Malmquist productivity index. The last two articles explore an intermediate route between the Fisher and Malmquist productivity indices and develop a detailed but meaningful decomposition for the Fisher index, including also empirical applications. Distance functions play a central role in the decomposition of Malmquist and Fisher productivity indices. Three panel data sets from 1990s have been applied in the study. The common feature of all data used is that they cover the periods before and after Finnish EU accession. Another common feature is that the analysis mainly concentrates on dairy farms or their roughage production systems. Productivity growth on Finnish dairy farms was relatively slow in the 1990s: approximately one percent per year, independent of the method used. Despite considerable annual variation, productivity growth seems to have accelerated towards the end of the period. There was a slowdown in the mid-1990s at the time of EU accession. No clear immediate effects of EU accession with respect to technical efficiency could be observed. Technical change has been the main contributor to productivity growth on dairy farms. However, average technical efficiency often showed a declining trend, meaning that the deviations from the best practice frontier are increasing over time. This suggests different paths of adjustment at the farm level. However, different methods to some extent provide different results, especially for the sub-components of productivity growth. In most analyses on dairy farms the scale effect on productivity growth was minor. A positive scale effect would be important for improving the competitiveness of Finnish agriculture through increasing farm size. This small effect may also be related to the structure of agriculture and to the allocation of investments to specific groups of farms during the research period. The result may also indicate that the utilization of scale economies faces special constraints in Finnish conditions. However, the analysis of a sample of all types of farms suggested a more considerable scale effect than the analysis on dairy farms.

Survival analysis of time-to-event data in respiratory health research studies

This article provides a review of techniques for the analysis of survival data arising from respiratory health studies. Popular techniques such as the Kaplan–Meier survival plot and the Cox proportional hazards model are presented and illustrated using data from a lung cancer study. Advanced issues are also discussed, including parametric proportional hazards models, accelerated failure time models, time-varying explanatory variables, simultaneous analysis of multiple types of outcome events and the restricted mean survival time, a novel measure of the effect of treatment.

Finite element modelling of lamb wave propagation in prestress concrete and effect of the prestress force on the wave’s characteristic

In order to assess the structural reliability of bridges, an accurate and cost effective Non-Destructive Evaluation (NDE) technology is required to ensure their safe and reliable operation. Over 60% of the Australian National Highway System is prestressed concrete (PSC) bridges according to the Bureau of Transport and Communication Economics (1997). Most of the in-service bridges are more than 30 years old and may experience a heavier traffic load than their original intended level. Use of Ultrasonic waves is continuously increasing for (NDE) and Structural Health Monitoring (SHM) in civil, aerospace, electrical, mechanical applications. Ultrasonic Lamb waves are becoming more popular for NDE because it can propagate long distance and reach hidden regions with less energy loses. The purpose of this study is to numerically quantify prestress force (PSF) of (PSC) beam using the fundamental theory of acoustic-elasticity. A three-dimension finite element modelling approach is set up to perform parametric studies in order to better understand how the lamb wave propagation in PSC beam is affected by changing in the PSF level. Results from acoustic-elastic measurement on prestressed beam are presented, showing the feasibility of the lamb wave for PSF evaluation in PSC bridges.

Nineteenth century narratives reveal historic catch rates for Australian snapper (Pagrus auratus)

Snapper (Pagrus auratus) is widely distributed throughout subtropical and temperate southern oceans and forms a significant recreational and commercial fishery in Queensland, Australia. Using data from government reports, media sources, popular publications and a government fisheries survey carried out in 1910, we compiled information on individual snapper fishing trips that took place prior to the commencement of fisherywide organized data collection, from 1871 to 1939. In addition to extracting all available quantitative data, we translated qualitative information into bounded estimates and used multiple imputation to handle missing values, forming 287 records for which catch rate (snapper fisher−1 h−1) could be derived. Uncertainty was handled through a parametric maximum likelihood framework (a transformed trivariate Gaussian), which facilitated statistical comparisons between data sources. No statistically significant differences in catch rates were found among media sources and the government fisheries survey. Catch rates remained stable throughout the time series, averaging 3.75 snapper fisher−1 h−1 (95% confidence interval, 3.42–4.09) as the fishery expanded into new grounds. In comparison, a contemporary (1993–2002) south-east Queensland charter fishery produced an average catch rate of 0.4 snapper fisher−1 h−1 (95% confidence interval, 0.31–0.58). These data illustrate the productivity of a fishery during its earliest years of development and represent the earliest catch rate data globally for this species. By adopting a formalized approach to address issues common to many historical records – missing data, a lack of quantitative information and reporting bias – our analysis demonstrates the potential for historical narratives to contribute to contemporary fisheries management.

Born leaders: Political selection and the relative age effect in the US Congress

We present substantial evidence for the existence of a bias in the distribution of births of leading US politicians in favour of those who were the eldest in their cohort at school. This result adds to the research on the long-term effects of relative age among peers at school. We discuss parametric and non-parametric tests to identify this effect, and we show that it is not driven by measurement error, redshirting or a sorting effect of highly educated parents. The magnitude of the effect that we estimate is larger than what other studies on ‘relative age effects’ have found for broader populations but is in general consistent with research that looks at professional sportsmen. We also find that relative age does not seem to correlate with the quality of elected politicians.

Bayesian synthetic likelihood

Having the ability to work with complex models can be highly beneficial, but the computational cost of doing so is often large. Complex models often have intractable likelihoods, so methods that directly use the likelihood function are infeasible. In these situations, the benefits of working with likelihood-free methods become apparent. Likelihood-free methods, such as parametric Bayesian indirect likelihood that uses the likelihood of an alternative parametric auxiliary model, have been explored throughout the literature as a good alternative when the model of interest is complex. One of these methods is called the synthetic likelihood (SL), which assumes a multivariate normal approximation to the likelihood of a summary statistic of interest. This paper explores the accuracy and computational efficiency of the Bayesian version of the synthetic likelihood (BSL) approach in comparison to a competitor known as approximate Bayesian computation (ABC) and its sensitivity to its tuning parameters and assumptions. We relate BSL to pseudo-marginal methods and propose to use an alternative SL that uses an unbiased estimator of the exact working normal likelihood when the summary statistic has a multivariate normal distribution. Several applications of varying complexity are considered to illustrate the findings of this paper.

On probability-based inference under data missing by design

Whether a statistician wants to complement a probability model for observed data with a prior distribution and carry out fully probabilistic inference, or base the inference only on the likelihood function, may be a fundamental question in theory, but in practice it may well be of less importance if the likelihood contains much more information than the prior. Maximum likelihood inference can be justified as a Gaussian approximation at the posterior mode, using flat priors. However, in situations where parametric assumptions in standard statistical models would be too rigid, more flexible model formulation, combined with fully probabilistic inference, can be achieved using hierarchical Bayesian parametrization. This work includes five articles, all of which apply probability modeling under various problems involving incomplete observation. Three of the papers apply maximum likelihood estimation and two of them hierarchical Bayesian modeling. Because maximum likelihood may be presented as a special case of Bayesian inference, but not the other way round, in the introductory part of this work we present a framework for probability-based inference using only Bayesian concepts. We also re-derive some results presented in the original articles using the toolbox equipped herein, to show that they are also justifiable under this more general framework. Here the assumption of exchangeability and de Finetti's representation theorem are applied repeatedly for justifying the use of standard parametric probability models with conditionally independent likelihood contributions. It is argued that this same reasoning can be applied also under sampling from a finite population. The main emphasis here is in probability-based inference under incomplete observation due to study design. This is illustrated using a generic two-phase cohort sampling design as an example. The alternative approaches presented for analysis of such a design are full likelihood, which utilizes all observed information, and conditional likelihood, which is restricted to a completely observed set, conditioning on the rule that generated that set. Conditional likelihood inference is also applied for a joint analysis of prevalence and incidence data, a situation subject to both left censoring and left truncation. Other topics covered are model uncertainty and causal inference using posterior predictive distributions. We formulate a non-parametric monotonic regression model for one or more covariates and a Bayesian estimation procedure, and apply the model in the context of optimal sequential treatment regimes, demonstrating that inference based on posterior predictive distributions is feasible also in this case.

An analytical approach to the study of a class of bi-state social interaction processes

Sufficient conditions for obtaining an equivalent linear model to classes of non-linear, bi-state, social interaction processes are derived. These parametric constraints, when satisfied, permit analytical determination of the dynamics of the non-linear process of social interaction.

Interface between 2 dissimilar fluids beneath a sheetpile cofferdam

A closed form solution is presented for determining the shape and location of the interface between two dissimilar fluids (having different densities) when steady flow takes place through a homogeneous and isotropic porous medium, into a sheetpile cofferdam; the interface is assumed to be sharp and the lower fluid stationary. The solution is obtained using the inverse hodograph. Numerical results are presented in nondimensional form for various parametric conditions in the physical plane; the interface pattern, as also the seepage discharge and exit gradient distribution are shown. The critical conditions of the interface are studied.

Effect of amplifier imperfections on active networks

The deviation in the performance of active networks due to practical operational amplifiers (OA) is mainly because of the finite gain bandwidth productBand nonzero output resistanceR_0. The effect ofBandR_0on two OA impedances and single and multi-OA filters are discussed. In filters, the effect ofR_0is to add zeros to the transfer function often making it nonminimum phase. A simple method of analysis has been suggested for 3-OA biquad and coupled biquad circuits. A general method of noise minimization of the generalized impedance converter (GIC), while operating OA's within the prescribed voltage and current limits, is also discussed. The 3-OA biquadratic sections analyzed also exhibit noise behavior and signal handling capacity similar to the GIC. The GIC based structures are found to be better than other configurations both in biquadratic sections and direct realizations of higher order transfer functions.