Adapting Global Standards to a Changing World

In 1996, Ira Millstein received a phone call from Paris. It came from the Organization for Economic Co-operation and Development (OECD) asking him to head a small international group of distinguished businesspeople, including Sir Adrian Cadbury. Their assignment would be to provide economists and policy makers with advice for future work in the area of corporate governance. At the time, the topic was little understood among policy makers and its wider economic implications were rarely discussed. But OECD, already well known for its analysis of both macroeconomics and structural policies, wanted to change that. They looked at corporate governance as an increasingly important field of economic reform and believed that the experiences of business, legal scholars and economists could help in shaping better policies and advice

Sample Preparation for in vitro Analysis of Iodine in Thyroid Tissue using X-ray Fluorescence

Iodine is enriched and stored in the thyroid gland. Due to several factors, the size of the thyroid iodine pool varies both between individuals and within individuals over time. Excess iodine as well as iodine deficiency may promote thyroid cancer. Therefore, knowledge of iodine content and distribution within thyroid cancer tissue is of interest. X-ray fluorescence analysis (XRF) and secondary ion mass spectrometry (SIMS) are two methods that can be used to assess iodine content in thyroid tissue. With both techniques, choice of sample preparation affects the results. Aldehyde fixatives are required for SIMS analysis while a freezing method might be satisfactory for XRF analysis. The aims of the present study were primarily to evaluate a simple freezing technique for preserving samples for XRF analysis and also to use XRF to evaluate the efficacy of using aldehyde fixatives to prepare samples for SIMS analysis. Ten porcine thyroids were sectioned into four pieces that were either frozen or fixed in formaldehyde, glutaraldehyde, or a modified Karnovsky fixative. The frozen samples were assessed for iodine content with XRF after 1 and 2 months, and the fixed samples were analyzed for iodine content after 1 week. Freezing of untreated tissue yielded no significant iodine loss, whereas fixation with aldehydes yielded an iodine loss of 14–30%, with Karnovsky producing the least loss

Improving the kinematic performance of the SCARA-Tau PKM

One well acknowledged drawback of traditional parallel kinematic machines (PKMs) is that the ratio of accessible workspace to robot footprint is small for these structures. This is most likely a contributing reason why relatively few PKMs are used in industry today. The SCARA-Tau structure is a parallel robot concept designed with the explicit goal of overcoming this limitation and developing a PKM with a workspace similar to that of a serial type robot of the same size. This paper shows for the first time how a proposed variant of the SCARA-Tau PKM can improve the usability of this robot concept further by significantly reducing the dependence between tool platform position and orientation of the original concept. The inverse kinematics of the proposed variant is derived and a comparison is made between this structure and the original SCARA-Tau concept, both with respect to platform orientation changes and workspace

Bayesian detection of periodic mRNA time profiles without use of training examples

BACKGROUND: Detection of periodically expressed genes from microarray data without use of known periodic and non-periodic training examples is an important problem, e.g. for identifying genes regulated by the cell-cycle in poorly characterised organisms. Commonly the investigator is only interested in genes expressed at a particular frequency that characterizes the process under study but this frequency is seldom exactly known. Previously proposed detector designs require access to labelled training examples and do not allow systematic incorporation of diffuse prior knowledge available about the period time. RESULTS: A learning-free Bayesian detector that does not rely on labelled training examples and allows incorporation of prior knowledge about the period time is introduced. It is shown to outperform two recently proposed alternative learning-free detectors on simulated data generated with models that are different from the one used for detector design. Results from applying the detector to mRNA expression time profiles from S. cerevisiae showsthat the genes detected as periodically expressed only contain a small fraction of the cell-cycle genes inferred from mutant phenotype. For example, when the probability of false alarm was equal to 7%, only 12% of the cell-cycle genes were detected. The genes detected as periodically expressed were found to have a statistically significant overrepresentation of known cell-cycle regulated sequence motifs. One known sequence motif and 18 putative motifs, previously not associated with periodic expression, were also over represented. CONCLUSION: In comparison with recently proposed alternative learning-free detectors for periodic gene expression, Bayesian inference allows systematic incorporation of diffuse a priori knowledge about, e.g. the period time. This results in relative performance improvements due to increased robustness against errors in the underlying assumptions. Results from applying the detector to mRNA expression time profiles from S. cerevisiae include several new findings that deserve further experimental studies

Simulation of CPT penetration in sensitive clay

This paper presents the results from numerical simulations of CPTu penetration in a natural clay combining the SCLAY1S constitutive model with a large deformation Finite Element framework including a coupled deformation and porewater pressure formulation. The hierarchical model formulation of SCLAY1S captures many features of a natural sensitive clay, such as the evolving anisotropic strength-stiffness response, as well as the degradation of the initial bonding. A sensitivity analysis is performed varying the overconsolidation ratio (QCR), bonding and anisotropy, also the hydraulic conductivity (hence, cv) of the clay. The findings indicate that some soil properties (the cv and OCR) impact both the normalised cone resistance Qt and the generation of excess porewater pressures. In contrast the sensitivity St of soft soils primarily affects Qt. In the current work it seems that the effects of the inherent and stress induced (from CPT penetration) anisotropy is not detected using these normalised plots

The Octahedral Hexarot - a novel 6-DOF parallel manipulator

A novel 6-DOF parallel kinematic manipulator named the Octahedral Hexarot is presented and analyzed. It is shown that this manipulator has the important benefits of combining a large positional workspace in relation to its footprint with a sizable range of platform rotations. These features are obtained by combining a rotation-symmetric actuating arm system with links in an octahedral-like configuration. Thus the manipulator consists of a central cylindrical column with six actuated rotating upper arms that can rotate indefinitely around the central column. Each upper arm is connected to a manipulated platform by one 5-DOF lower arm link. The link arrangement of the Octahedral Hexarot is inspired by the original Gough platform. The manipulated platform is an equilateral triangle and the joint positions on the upper arms approximately form an equilateral triangle. A task dependent optimization procedure for the structural parameters is proposed and the workspace of the resulting manipulator is analyzed in depth.<br /

On the feasibility of utilising gearing to extend the rotational workspace of a class of parallel robots

Parallel manipulators provide several benefits compared to serial manipulators of similar size. These advantages typically include higher speed and acceleration, improved position accuracy and increased stiffness. However, parallel manipulators also suffer from several disadvantages. These drawbacks commonly include a small ratio of the positional workspace relative to the manipulator footprint and a limited rotational capability of the manipulated platform. A few parallel manipulators featuring a large ratio of the positional workspace relative to the footprint have been proposed. This paper investigates the feasibility of employing gearing to extend the range of the end-effector rotation of such mechanisms. The objective is to achieve parallel manipulators where both the positional and rotational workspace are comparable to that of serial manipulators

Improved variance estimation of classification performance via reduction of bias caused by small sample size

BACKGROUND: Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm that the classifier is robust with good generalization performance to new examples, or at least that it performs better than random guessing. A suggested alternative is to obtain a confidence interval of the error rate using repeated design and test sets selected from available examples. However, it is known that even in the ideal situation of repeated designs and tests with completely novel samples in each cycle, a small test set size leads to a large bias in the estimate of the true variance between design sets. Therefore different methods for small sample performance estimation such as a recently proposed procedure called Repeated Random Sampling (RSS) is also expected to result in heavily biased estimates, which in turn translates into biased confidence intervals. Here we explore such biases and develop a refined algorithm called Repeated Independent Design and Test (RIDT). RESULTS: Our simulations reveal that repeated designs and tests based on resampling in a fixed bag of samples yield a biased variance estimate. We also demonstrate that it is possible to obtain an improved variance estimate by means of a procedure that explicitly models how this bias depends on the number of samples used for testing. For the special case of repeated designs and tests using new samples for each design and test, we present an exact analytical expression for how the expected value of the bias decreases with the size of the test set. CONCLUSION: We show that via modeling and subsequent reduction of the small sample bias, it is possible to obtain an improved estimate of the variance of classifier performance between design sets. However, the uncertainty of the variance estimate is large in the simulations performed indicating that the method in its present form cannot be directly applied to small data sets

Revealing cell cycle control by combining model-based detection of periodic expression with novel cis-regulatory descriptors

<p>Abstract</p> <p>Background</p> <p>We address the issue of explaining the presence or absence of phase-specific transcription in budding yeast cultures under different conditions. To this end we use a model-based detector of gene expression periodicity to divide genes into classes depending on their behavior in experiments using different synchronization methods. While computational inference of gene regulatory circuits typically relies on expression similarity (clustering) in order to find classes of potentially co-regulated genes, this method instead takes advantage of known time profile signatures related to the studied process.</p> <p>Results</p> <p>We explain the regulatory mechanisms of the inferred periodic classes with <it>cis</it>-regulatory descriptors that combine upstream sequence motifs with experimentally determined binding of transcription factors. By systematic statistical analysis we show that periodic classes are best explained by combinations of descriptors rather than single descriptors, and that different combinations correspond to periodic expression in different classes. We also find evidence for additive regulation in that the combinations of <it>cis</it>-regulatory descriptors associated with genes periodically expressed in fewer conditions are frequently subsets of combinations associated with genes periodically expression in more conditions. Finally, we demonstrate that our approach retrieves combinations that are more specific towards known cell-cycle related regulators than the frequently used clustering approach.</p> <p>Conclusion</p> <p>The results illustrate how a model-based approach to expression analysis may be particularly well suited to detect biologically relevant mechanisms. Our new approach makes it possible to provide more refined hypotheses about regulatory mechanisms of the cell cycle and it can easily be adjusted to reveal regulation of other, non-periodic, cellular processes.</p