Estimation after subpopulation selection in adaptive seamless trials

During the development of new therapies, it is not uncommon to test whether a new treatment works better than the existing treatment for all patients who suffer from a condition (full population) or for a subset of the full population (subpopulation). One approach that may be used for this objective is to have two separate trials, where in the first trial, data are collected to determine if the new treatment benefits the full population or the subpopulation. The second trial is a confirmatory trial to test the new treatment in the population selected in the first trial. In this paper, we consider the more efficient two-stage adaptive seamless designs (ASDs), where in stage 1, data are collected to select the population to test in stage 2. In stage 2, additional data are collected to perform confirmatory analysis for the selected population. Unlike the approach that uses two separate trials, for ASDs, stage 1 data are also used in the confirmatory analysis. Although ASDs are efficient, using stage 1 data both for selection and confirmatory analysis introduces selection bias and consequently statistical challenges in making inference. We will focus on point estimation for such trials. In this paper, we describe the extent of bias for estimators that ignore multiple hypotheses and selecting the population that is most likely to give positive trial results based on observed stage 1 data. We then derive conditionally unbiased estimators and examine their mean squared errors for different scenarios.

Evidence for interplay between genes and maternal stress in utero: monoamine oxidase A polymorphism moderates effects of life events during pregnancy on infant negative emotionality at 5 weeks

The low activity variant of the monoamine oxidase A (MAOA) functional promoter polymorphism, MAOA-LPR, in interaction with adverse environments (G × E) is associated with child and adult antisocial behaviour disorders. MAOA is expressed during foetal development so in utero G × E may influence early neurodevelopment. We tested the hypothesis that MAOA G × E during pregnancy predicts infant negative emotionality soon after birth. In an epidemiological longitudinal study starting in pregnancy, using a two stage stratified design, we ascertained MAOA-LPR status (low vs. high activity variants) from the saliva of 209 infants (104 boys and 105 girls), and examined predictions to observed infant negative emotionality at 5 weeks post-partum from life events during pregnancy. In analyses weighted to provide estimates for the general population, and including possible confounders for life events, there was an MAOA status by life events interaction (P = 0.017). There was also an interaction between MAOA status and neighbourhood deprivation (P = 0.028). Both interactions arose from a greater effect of increasing life events on negative emotionality in the MAOA-LPR low activity, compared with MAOA-LPR high activity infants. The study provides the first evidence of moderation by MAOA-LPR of the effect of the social environment in pregnancy on negative emotionality in infancy, an early risk for the development of child and adult antisocial behaviour disorders.

A robust sclera segmentation algorithm

Sclera segmentation is shown to be of significant importance for eye and iris biometrics. However, sclera segmentation has not been extensively researched as a separate topic, but mainly summarized as a component of a broader task. This paper proposes a novel sclera segmentation algorithm for colour images which operates at pixel-level. Exploring various colour spaces, the proposed approach is robust to image noise and different gaze directions. The algorithm’s robustness is enhanced by a two-stage classifier. At the first stage, a set of simple classifiers is employed, while at the second stage, a neural network classifier operates on the probabilities’ space generated by the classifiers at stage 1. The proposed method was ranked the 1st in Sclera Segmentation Benchmarking Competition 2015, part of BTAS 2015, with a precision of 95.05% corresponding to a recall of 94.56%.

How to be a fig wasp down under: the diversity and structure of an Australian fig wasp community

Endophytic insects and their parasitoids provide valuable models for community ecology. The wasp communities in inflorescences of fig trees have great potential for comparative studies, but we must first describe individual communities. Here, we add to the few detailed studies of such communities by describing the one associated with Ficus rubiginosa in Australia. First, we describe community composition, using two different sampling procedures. Overall, we identified 14 species of non-pollinating fig wasp (NPFW) that fall into two size classes. Small wasps, including pollinators, gallers and their parasitoids, were more abundant than large wasps (both galler and parasitoid species). We show that in figs where wasps emerge naturally, the presence of large wasps may partly explain the low emergence of small wasps. During fig development, large gallers oviposit first, before and around the time of pollination, while parasitoids lay eggs after pollination. We further show that parasitoids in the subfamily Sycoryctinae, which comprise the majority of all individual NPFWs, segregate temporally by laying eggs at different stages of fig development. We discuss our results in terms of species co-existence and community structure and compare our findings to those from fig wasp communities on other continents.

e-Leadership through strategic alignment: an empirical study of small and medium sized enterprises in the digital age

Small and medium sized enterprises (SMEs) play an important role in the European economy. A critical challenge faced by SME leaders, as a consequence of the continuing digital technology revolution, is how to optimally align business strategy with digital technology to fully leverage the potential offered by these technologies in pursuit of longevity and growth. There is a paucity of empirical research examining how e-leadership in SMEs drives successful alignment between business strategy and digital technology fostering longevity and growth. To address this gap, in this paper we develop an empirically derived e-leadership model. Initially we develop a theoretical model of e-leadership drawing on strategic alignment theory. This provides a theoretical foundation on how SMEs can harness digital technology in support of their business strategy enabling sustainable growth. An in-depth empirical study was undertaken interviewing 42 successful European SME leaders to validate, advance and substantiate our theoretically driven model. The outcome of the two stage process – inductive development of a theoretically driven e-leadership model and deductive advancement to develop a complete model through in-depth interviews with successful European SME leaders – is an e-leadership model with specific constructs fostering effective strategic alignment. The resulting diagnostic model enables SME decision makers to exercise effective e-leadership by creating productive alignment between business strategy and digital technology improving longevity and growth prospects.

Osteoconductivity of modified fluorcanasite glass-ceramics for bone tissue augmentation and repair

Modified fluorcanasite glasses were fabricated by either altering the molar ratios of Na(2)O and CaO or by adding P(2)O(5) to the parent stoichiometric glass compositions. Glasses were converted to glass-ceramics by a controlled two-stage heat treatment process. Rods (2 mm x 4 mm) were produced using the conventional lost-wax casting technique. Osteoconductive 45S5 bioglass was used as a reference material. Biocompatibility and osteoconductivity were investigated by implantation into healing defects (2 mm) in the midshaft of rabbit femora. Tissue response was investigated using conventional histology and scanning electron microscopy. Histological and histomorphometric evaluation of specimens after 12 weeks implantation showed significantly more bone contact with the surface of 45S5 bioglass implants when compared with other test materials. When the bone contact for each material was compared between experimental time points, the Glass-Ceramic 2 (CaO rich) group showed significant difference (p = 0.027) at 4 weeks, but no direct contact at 12 weeks. Histology and backscattered electron photomicrographs showed that modified fluorcanasite glass-ceramic implants had greater osteoconductivity than the parent stoichiometric composition. Of the new materials, fluorcanasite glass-ceramic implants modified by the addition of P(2)O(5) showed the greatest stimulation of new mineralized bone tissue formation adjacent to the implants after 4 and 12 weeks implantation. (C) 2010 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 94A: 760-768, 2010

Histological Outcomes on the Development of New Space-making Devices for Maxillary Sinus Floor Augmentation

Background: Previous studies have pointed out that the mere elevation of the maxillary sinus membrane promotes bone formation without the use of augmentation materials. Purpose: This experimental study aimed at evaluating if the two-stage procedure for sinus floor augmentation could benefit from the use of a space-making device in order to increase the bone volume to enable later implant installation with good primary stability. Materials and Methods: Six male tufted capuchin primates (Cebus apella) were subjected to extraction of the three premolars and the first molar on both sides of the maxilla to create an edentulous area. The sinuses were opened using the lateral bone-wall window technique, and the membrane was elevated. One resorbable space-making device was inserted in each maxillary sinus, and the bone window was returned in place. The animals were euthanatized after 6 months, and biopsy blocks containing the whole maxillary sinus and surrounding soft tissues were prepared for ground sections. Results: The histological examination of the specimens showed bone formation in contact with both the schneiderian membrane and the device in most cases even when the device was displaced. The process of bone formation indicates that this technique is potentially useful for two-stage sinus floor augmentation. The lack of stabilization of the device within the sinus demands further improvement of space-makers for predictable bone augmentation. Conclusions: It is concluded that (1) the device used in this study did not trigger any important inflammatory reaction; (2) when the sinus membrane was elevated, bone formation was a constant finding; and (3) an ideal space-making device should be stable and elevate the membrane to ensure a maintained connection between the membrane and the secluded space.

Production of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) P(3HB-co-3HV) with a broad range of 3HV content at high yields by Burkholderia sacchari IPT 189

The biosynthesis of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) from sucrose and propionic acid by Burkholderia sacchari IPT 189 was studied using a two-stage bioreactor process. In the first stage, this bacterium was cultivated in a balanced culture medium until sucrose exhaustion. In the second stage, a solution containing sucrose and propionic acid as carbon source was fed to the bioreactor at various sucrose/propionic acid (s/p) ratios at a constant specific flow rate. Copolymers with 3HV content ranging from 40 down to 6.5 (mol%) were obtained with 3HV yield from propionic acid (Y-3HV/prop) increasing from 1.10 to 1.34 g g(-1). Copolymer productivity of 1 g l(-1) h(-1) was obtained with polymer biomass content rising up to 60% by increasing a specific flow rate at a constant s/p ratio. Increasing values of 3HV content were obtained by varying the s/p ratios. A simulation of production costs considering Y-3HV/prop obtained in the present work indicated that a reduction of up to 73% can be reached, approximating US$ 1.00 per kg which is closer to the value to produce P3HB from sucrose (US$ 0.75 per kg).

On the cutting stock problem under stochastic demand

This paper addresses the one-dimensional cutting stock problem when demand is a random variable. The problem is formulated as a two-stage stochastic nonlinear program with recourse. The first stage decision variables are the number of objects to be cut according to a cutting pattern. The second stage decision variables are the number of holding or backordering items due to the decisions made in the first stage. The problem`s objective is to minimize the total expected cost incurred in both stages, due to waste and holding or backordering penalties. A Simplex-based method with column generation is proposed for solving a linear relaxation of the resulting optimization problem. The proposed method is evaluated by using two well-known measures of uncertainty effects in stochastic programming: the value of stochastic solution-VSS-and the expected value of perfect information-EVPI. The optimal two-stage solution is shown to be more effective than the alternative wait-and-see and expected value approaches, even under small variations in the parameters of the problem.

Comparing diagnostic tests with missing data

When missing data occur in studies designed to compare the accuracy of diagnostic tests, a common, though naive, practice is to base the comparison of sensitivity, specificity, as well as of positive and negative predictive values on some subset of the data that fits into methods implemented in standard statistical packages. Such methods are usually valid only under the strong missing completely at random (MCAR) assumption and may generate biased and less precise estimates. We review some models that use the dependence structure of the completely observed cases to incorporate the information of the partially categorized observations into the analysis and show how they may be fitted via a two-stage hybrid process involving maximum likelihood in the first stage and weighted least squares in the second. We indicate how computational subroutines written in R may be used to fit the proposed models and illustrate the different analysis strategies with observational data collected to compare the accuracy of three distinct non-invasive diagnostic methods for endometriosis. The results indicate that even when the MCAR assumption is plausible, the naive partial analyses should be avoided.

Open Issues in Control ofAutomotive R744 Air-ConditioningSystems

In this thesis, one of the current control algorithms for the R744 cycle, which tries tooptimize the performance of the system by two SISO control loops, is compared to acost-effective system with just one actuator. The operation of a key component of thissystem, a two stage orifice expansion valve is examined in a range of typical climateconditions. One alternative control loop for this system, which has been proposed byBehr group, is also scrutinized.The simulation results affirm the preference of using two control-loops instead of oneloop, but refute advantages of the Behr alternate control approach against one-loopcontrol. As far as the economic considerations of the A/C unit are concerned, usinga two-stage orifice expansion valve is desired by the automotive industry, thus basedon the experiment results, an improved logic for control of this system is proposed.In the second part, it is investigated whether the one-actuator control approach isapplicable to a system consisting of two parallel evaporators to allow passengers tocontrol different climate zones. The simulation results show that in the case of usinga two-stage orifice valve for the front evaporator and a fixed expansion valve forthe rear one, a proper distribution of the cooling power between the front and rearcompartment is possible for a broad range of climate conditions.

Applicatiion of Almost ideal demand system for a pharmaceutical

This thesis is an application of the Almost Ideal Demand System approach of Deaton and Muellbauer,1980, for a particular pharmaceutical, Citalopram, in which GORMAN´s (1971) multi-stage budgeting approach is applied basically since it is one of the most useful approach in estimating demand for differentiated products. Citalopram is an antidepressant drug that is used in the treatment of major depression. As for most other pharmaceuticals whose the patent has expired, there exist branded and generic versions of Citalopram. This paper is aimed to define its demand system with two stage models for the branded version and five generic versions, and to show whether generic versions are able to compete with the branded version. I calculated the own price elasticities, and it made me possible to compare and make a conclusion about the consumers’ choices over the brand and generic drugs. Even though the models need for being developed with some additional variables, estimation results of models and uncompensated price elasticities indicated that the branded version has still power in the market, and generics are able to compete with lower prices. One important point that has to be taken into consideration is that the Swedish pharmaceutical market faced a reform on October 1, 2002, that aims to make consumer better informed about the price and decrease the overall expenditures for pharmaceuticals. Since there were not significantly enough generic sales to take into calculation before the reform, my paper covers sales after the reform.

Triggering Solar-Powered Vehicle Activated Signs using Self Organising Maps with K-means

Solar-powered vehicle activated signs (VAS) are speed warning signs powered by batteries that are recharged by solar panels. These signs are more desirable than other active warning signs due to the low cost of installation and the minimal maintenance requirements. However, one problem that can affect a solar-powered VAS is the limited power capacity available to keep the sign operational. In order to be able to operate the sign more efficiently, it is proposed that the sign be appropriately triggered by taking into account the prevalent conditions. Triggering the sign depends on many factors such as the prevailing speed limit, road geometry, traffic behaviour, the weather and the number of hours of daylight. The main goal of this paper is therefore to develop an intelligent algorithm that would help optimize the trigger point to achieve the best compromise between speed reduction and power consumption. Data have been systematically collected whereby vehicle speed data were gathered whilst varying the value of the trigger speed threshold. A two stage algorithm is then utilized to extract the trigger speed value. Initially the algorithm employs a Self-Organising Map (SOM), to effectively visualize and explore the properties of the data that is then clustered in the second stage using K-means clustering method. Preliminary results achieved in the study indicate that using a SOM in conjunction with K-means method is found to perform well as opposed to direct clustering of the data by K-means alone. Using a SOM in the current case helped the algorithm determine the number of clusters in the data set, which is a frequent problem in data clustering.

Recent developments in statistical methods for detecting genetic loci affecting phenotypic variability

A number of recent works have introduced statistical methods for detecting genetic loci that affect phenotypic variability, which we refer to as variability-controlling quantitative trait loci (vQTL). These are genetic variants whose allelic state predicts how much phenotype values will vary about their expected means. Such loci are of great potential interest in both human and non-human genetic studies, one reason being that a detected vQTL could represent a previously undetected interaction with other genes or environmental factors. The simultaneous publication of these new methods in different journals has in many cases precluded opportunity for comparison. We survey some of these methods, the respective trade-offs they imply, and the connections between them. The methods fall into three main groups: classical non-parametric, fully parametric, and semi-parametric two-stage approximations. Choosing between alternatives involves balancing the need for robustness, flexibility, and speed. For each method, we identify important assumptions and limitations, including those of practical importance, such as their scope for including covariates and random effects. We show in simulations that both parametric methods and their semi-parametric approximations can give elevated false positive rates when they ignore mean-variance relationships intrinsic to the data generation process. We conclude that choice of method depends on the trait distribution, the need to include non-genetic covariates, and the population size and structure, coupled with a critical evaluation of how these fit with the assumptions of the statistical model.

Decision Support Systems And Promoting Socially Just Environmental Management

The Mauri Model DMF is unique in its approach to the management of water resources as the framework offers a transparent and inclusive approach to considering the environmental, economic, social and cultural aspects of the decisions being contemplated. The Mauri Model DMF is unique because it is capable of including multiple-worldviews and adopts mauri (intrinsic value or well-being) in the place of the more common monetised assessments of pseudo sustainability using Cost Benefit Analysis. The Mauri Model DMF uses a two stage process that first identifies participants’ worldviews and inherent bias regarding water resource management, and then facilitates transparent assessment of selected sustainability performance indicators. The assessment can then be contemplated as the separate environmental, economic, social and cultural dimensions of the decision, and collectively as an overall result; or the priorities associated with different worldviews can be applied to determine the sensitivity of the result to different cultural contexts or worldviews.