Design of clinical pharmacology trials

1. There are a variety of methods that could be used to increase the efficiency of the design of experiments. However, it is only recently that such methods have been considered in the design of clinical pharmacology trials. 2. Two such methods, termed data-dependent (e.g. simulation) and data-independent (e.g. analytical evaluation of the information in a particular design), are becoming increasingly used as efficient methods for designing clinical trials. These two design methods have tended to be viewed as competitive, although a complementary role in design is proposed here. 3. The impetus for the use of these two methods has been the need for a more fully integrated approach to the drug development process that specifically allows for sequential development (i.e. where the results of early phase studies influence later-phase studies). 4. The present article briefly presents the background and theory that underpins both the data-dependent and -independent methods with the use of illustrative examples from the literature. In addition, the potential advantages and disadvantages of each method are discussed.

Network topology and the evolution of dynamics in an artificial genetic regulatory network model created by whole genome duplication and divergence

Topological measures of large-scale complex networks are applied to a specific artificial regulatory network model created through a whole genome duplication and divergence mechanism. This class of networks share topological features with natural transcriptional regulatory networks. Specifically, these networks display scale-free and small-world topology and possess subgraph distributions similar to those of natural networks. Thus, the topologies inherent in natural networks may be in part due to their method of creation rather than being exclusively shaped by subsequent evolution under selection. The evolvability of the dynamics of these networks is also examined by evolving networks in simulation to obtain three simple types of output dynamics. The networks obtained from this process show a wide variety of topologies and numbers of genes indicating that it is relatively easy to evolve these classes of dynamics in this model. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

Multilevel modelling for inference of genetic regulatory networks

Time-course experiments with microarrays are often used to study dynamic biological systems and genetic regulatory networks (GRNs) that model how genes influence each other in cell-level development of organisms. The inference for GRNs provides important insights into the fundamental biological processes such as growth and is useful in disease diagnosis and genomic drug design. Due to the experimental design, multilevel data hierarchies are often present in time-course gene expression data. Most existing methods, however, ignore the dependency of the expression measurements over time and the correlation among gene expression profiles. Such independence assumptions violate regulatory interactions and can result in overlooking certain important subject effects and lead to spurious inference for regulatory networks or mechanisms. In this paper, a multilevel mixed-effects model is adopted to incorporate data hierarchies in the analysis of time-course data, where temporal and subject effects are both assumed to be random. The method starts with the clustering of genes by fitting the mixture model within the multilevel random-effects model framework using the expectation-maximization (EM) algorithm. The network of regulatory interactions is then determined by searching for regulatory control elements (activators and inhibitors) shared by the clusters of co-expressed genes, based on a time-lagged correlation coefficients measurement. The method is applied to two real time-course datasets from the budding yeast (Saccharomyces cerevisiae) genome. It is shown that the proposed method provides clusters of cell-cycle regulated genes that are supported by existing gene function annotations, and hence enables inference on regulatory interactions for the genetic network.

Sketch design drawing, Hill House, Chapel Hill, Brisbane

Sketch floor plan and diagrams.

Sketch design drawing, Hill House, Chapel Hill, Brisbane

Three-dimensional projection sketch showing roof forms and wall finishes.

Hydraulic Design of Stepped Spillways and Downstream Energy Dissipators for Embankment Dams

In recent years, the design flows of many dams were re-evaluated, often resulting in discharges larger than the original design. In many cases, the occurrence of the revised flows could result in dam overtopping because of insufficient storage and spillway capacity. An experimental study was conducted herein to gain a better understanding of the flow properties in stepped chutes with slopes typical of embankment dams. The work was based upon a Froude similitude in large-size experimental facilities. A total of 10 configurations were tested including smooth steps, steps equipped with devices to enhance energy dissipation and rough steps. The present results yield a new design procedure. The design method includes some key issues not foreseen in prior studies : e.g., gradually varied flow, type of flow regime, flow resistance. It is believed that the outcomes are valid for a wide range of chute geometry and flow conditions typical of embankment chutes.

Design, Science and Conceptual Analysis

Philosophers expend considerable effort on the analysis of concepts, but the value of such work is not widely appreciated. This paper principally analyses some arguments, beliefs, and presuppositions about the nature of design and the relations between design and science common in the literature to illustrate this point, and to contribute to the foundations of design theory.

Research, knowledge and design

The discussion about relations between research and design has a number of strands, and presumably motivations. Putting aside the question whether or not design or “creative endeavour” should be counted as research, for reasons to do with institutional recognition or reward, the question remains how, if at all, is design research? This question is unlikely to have attracted much interest but for matters external to Architecture within the modern university. But Architecture as a discipline now needs to understand research much better than in the past when ‘research’ was whatever went on in building science, history or people/environment studies. In this paper, I begin with some common assumptions about design, considered in relation to research, and suggest how the former can constitute or be a mode of the latter. Central to this consideration is an understanding of research as the production of publicly available knowledge. The method is that of conceptual analysis which is much more fruitful than is usually appreciated. This work is part of a larger project in philosophy of design, in roughly the analytical tradition.

Measurement Function Design for Visual Tracking Applications

Extracting human postural information from video sequences has proved a difficult research question. The most successful approaches to date have been based on particle filtering, whereby the underlying probability distribution is approximated by a set of particles. The shape of the underlying observational probability distribution plays a significant role in determining the success, both accuracy and efficiency, of any visual tracker. In this paper we compare approaches used by other authors and present a cost path approach which is commonly used in image segmentation problems, however is currently not widely used in tracking applications.