Optimal designs to select individuals for genotyping conditional on observed binary or survival outcomes and non-genetic covariates

In gene-disease association studies, the cost of genotyping makes it economical to use a two-stage design where only a subset of the cohort is genotyped. At the first-stage, the follow-up data along with some risk factors or non-genetic covariates are collected for the cohort and a subset of the cohort is then selected for genotyping at the second-stage. Intuitively the selection of the subset for the second-stage could be carried out efficiently if the data collected at the first-stage are utilized. The information contained in the conditional probability of the genotype given the first-stage data and the initial estimates of the parameters of interest is being maximized for efficient selection of the subset. The proposed selection method is illustrated using the logistic regression and Cox’s proportional hazards model and algorithms that can find optimal or nearly optimal designs in discrete design space are presented. Simulation comparisons between D-optimal design, extreme selection and case-cohort design suggest that D-optimal design is the most efficient in terms of variance of estimated parameters, but extreme selection may be a good alternative for practical study design.     

Approximate cost-efficient sequential designs for binary response models with application to switching measurements

The efficiency of an experimental design is ultimately measured in terms of time and resources needed for the experiment. Optimal sequential (multi-stage) design is studied in the situation where each stage involves a fixed cost. The problem is motivated by switching measurements on superconducting Josephson junctions. In this quantum mechanical experiment, the sequences of current pulses are applied to the Josephson junction sample and a binary response indicating the presence or the absence of a voltage response is measured. The binary response can be modeled by a generalized linear model with the complementary log-log link function. The other models considered are the logit model and the probit model. For these three models, the approximately optimal sample size for the next stage as a function of the current Fisher information and the stage cost is determined. The cost-efficiency of the proposed design is demonstrated in simulations based on real data from switching measurements. The results can be directly applied to switching measurements and they may lead to substantial savings in the time needed for the experiment.     

An introduction to personalization and mass customization

In this article, we address the question of how efficiently Semantic Web (SW) reasoners perform in processing (classifying and querying) taxonomies of enormous size and whether it is possible to improve on existing implementations. We use a bit-vector encoding technique to implement taxonomic concept classification and Boolean-query answering. We describe the technique we have used, which achieves high performance, and discuss implementation issues. We compare the performance of our implementation with those of the best existing SW reasoning systems over several very large taxonomies under the exact same conditions for so-called TBox reasoning. The results show that our system is among the best for concept classification and several orders-of-magnitude more efficient in terms of response time for query answering. We present these results in detail and comment them. We also discuss pragmatic issues such as cycle detection and decoding.     

Image Denoising Using Directional Adaptive Variable Exponents Model

In this paper, a new variational image denoising model is proposed. The new model could be seen to be a two-step method. In the first step, structure tensor analysis is used to infer something about the local geometry. The eigenvectors and the eigenvalues of the structure tensor are used in the construction of the denoising energy. In the second step, the actual variational denoising takes place. The steps are coupled in the sense that the energy expression is built using the underlying image, not the data. Two variable exponents are incorporated into the regularizer in order to reduce the staircasing effect, which is often present in the methods based on the first-order partial derivatives, and to increase smoothing along the image boundaries. In addition, two pointwise weight functions try to help to preserve small-scale details. In the theoretical part, the existence of a minimizer of a weak form of the original energy is considered. In the numerical part, an algorithm based on iterative minimization is presented and the numerical experiments demonstrate the possible advantages of the new model over some existing variational and partial differential equations methods.     

Design optimization of laminated composite structures using distributed grid resources

Parameter studies, genetic algorithms and Monte Carlo type calculations are examples of pleasantly parallel computational tasks. Pleasantly parallel computational tasks can be effectively calculated in computer clusters or grids. In this work, we consider a weight minimization problem of a laminated composite structure in the post-buckling region. The design variables are the number of layers and the layer orientations given in a discrete set of allowable angles for layer orientations. Optimization is carried out using a deterministic search process, where the lay-up configurations are generated iteratively in the design space from the selected design points of the population at the preceding cycle. Computation is performed using NorduGrid grid computing platform. In this work, we briefly go through some general grid concepts and the use of grid in optimization of laminated composite structures.     

Shape and cross-section optimization of plane trusses subjected to earthquake excitation using gradient and Hessian matrix calculations

This article describes a second-order shape and cross-section optimization method of plane truss subjected to earthquake excitation. The method is based on gradient and Hessian matrix calculation. First, the first and second derivatives of dynamic response with respect to design variables are calculated based on the Newmark method. Second, the inequality time-dependent constraint problem is converted into a sequence of appropriately formed unconstrained problems using the integral interior penalty function method. Then, the gradient and Hessian matrix of the integral interior penalty function are computed. Third, Marquardt's method is employed to solve the unconstrained problems. Finally, the new approach is validated through several case studies. The results show that the new optimization method is an efficient and effective approach for minimum weight design of truss structures.     

Engineering Natural Pollen Grains as Multifunctional 3D Printing Materials

The development of multifunctional 3D printing materials from sustainable natural resources is a high priority in additive manufacturing. Using an eco-friendly method to transform hard pollen grains into stimulus-responsive microgel particles, we engineered a pollen-derived microgel suspension that can serve as a functional reinforcement for composite hydrogel inks and as a supporting matrix for versatile freeform 3D printing systems. The pollen microgel particles enabled the printing of composite inks and improved the mechanical and physiological stabilities of alginate and hyaluronic acid hydrogel scaffolds for 3D cell culture applications. Moreover, the particles endowed the inks with stimulus-responsive controlled release properties. The suitability of the pollen microgel suspension as a supporting matrix for freeform 3D printing of alginate and silicone rubber inks was demonstrated and optimized by tuning the rheological properties of the microgel. Compared with other classes of natural materials, pollen grains have several compelling features, including natural abundance, renewability, affordability, processing ease, monodispersity, and tunable rheological features, which make them attractive candidates to engineer advanced materials for 3D printing applications.     

Decision problems concerning thinness and slenderness of formal languages

A language L is called thin if for almost all n there is at most one word of length n in L. A language L is called slender if there is a positive integer k such that for any n there are at most k words of length n in L. The notions of Parikh thin and Parikh slender languages are defined similarly by counting the words with the same Parikh vectors instead of the words of the same length. In this paper we discuss decision problems concerning these four properties. It is shown that all four properties are decidable for bounded semilinear languages but undecidable for DT0L languages. As a consequence all these problems are decidable for context-free languages. Received 9 June 1997 / 3 December 1997     

Modelling the structure of the calcitonin gene-related peptide

The calcitonin gene-related peptide (CGRP) is a 37 residue neuropeptidewhich causes vasodilatation, increases heart rate and inhibitsbone resorption. These effects make it an interesting lead fordrug discovery. We have combined current structural and biologicalinformation to model the structure of hCGRP-ß to beused as a basis for the rational design of novel analogues.Distinct regions of CGRP have been shown to be responsible forthe activity of the whole molecule. Thus, the structure of thepeptide was modelled in four parts which were finally combined.A random search of conformational space was performed for thefragments CGRP1–8 and CGRP30–37 which have beenshown to be central for receptor activation and binding, respectively.Five low-energy hCGRP-ß structures were obtained frommodelled fragments by molecular dynamics. The relevance of theapproach was verified by comparing the models with NMR structuresof CGRP and calcitonin. The models obtained for the N- and C-terminalfragments should enable the design of novel agonists and antagonistsof the CGRP receptor, respectively. Models of the whole moleculemay be used in the design of peptides with shortened spacersbetween the receptor-bound regions. The approach described isapplicable to several related peptide hormones, like growthhormone-releasing hormone and secretin.     

Feasibility of pulse combustion in micro gas turbines

In gas turbines, a fast decrease of efficiency appears when the output decreases; the efficiency of a large gas turbine (20…30 MW) is in the order of 40 %, the efficiency of a 30 kW gas turbine with a recuperator is in the order of 25 %, but the efficiency of a very small gas turbine (2…6 kW) in the order of 4…6 % (or 8…12 % with an optimal recuperator). This is mainly a result of the efficiency decrease in kinetic compressors, due to the Reynolds number effect. Losses in decelerating flow in a flow passage are sensitive to the Reynolds number effects. In contrary to the compression, the efficiency of expansion in turbines is not so sensitive to the Reynolds number; very small turbines are made with rather good efficiency because the flow acceleration stabilizes the boundary layer. This study presents a system where the kinetic compressor of a gas turbine is replaced with a pulse combustor. The combustor is filled with a combustible gas mixture, ignited, and the generated high pressure gas is expanded in the turbine. The process is repeated frequently, thus producing a pulsating flow to the turbine; or almost a uniform flow, if several parallel combustors are used and triggered alternately in a proper way. Almost all the compression work is made by the temperature increase from the combustion. This gas turbine type is investigated theoretically and its combustor also experimentally with the conclusion that in a 2 kW power size, the pulse flow gas turbine is not as attractive as expected due to the big size and weight of parallel combustors and due to the efficiency being in the order of 8 % to 10 %. However, in special applications having a very low power demand, below 1000 W, this solution has better properties when compared to the conventional gas turbine and it could be worth of a more detailed investigation.