Improving the accuracy of heat balance integral methods applied to thermal problems with time dependent boundary conditions

In this paper the two main drawbacks of the heat balance integral methods are examined. Firstly we investigate the choice of approximating function. For a standard polynomial form it is shown that combining the Heat Balance and Refined Integral methods to determine the power of the highest order term will either lead to the same, or more often, greatly improved accuracy on standard methods. Secondly we examine thermal problems with a time-dependent boundary condition. In doing so we develop a logarithmic approximating function. This new function allows us to model moving peaks in the temperature profile, a feature that previous heat balance methods cannot capture. If the boundary temperature varies so that at some time t & 0 it equals the far-field temperature, then standard methods predict that the temperature is everywhere at this constant value. The new method predicts the correct behaviour. It is also shown that this function provides even more accurate results, when coupled with the new CIM, than the polynomial profile. Analysis primarily focuses on a specified constant boundary temperature and is then extended to constant flux, Newton cooling and time dependent boundary conditions.

Discrete time Non-homogeneous Semi-Markov Processes applied to Models for Disability Insurance

In this paper, we present a stochastic model for disability insurance contracts. The model is based on a discrete time non-homogeneous semi-Markov process (DTNHSMP) to which the backward recurrence time process is introduced. This permits a more exhaustive study of disability evolution and a more efficient approach to the duration problem. The use of semi-Markov reward processes facilitates the possibility of deriving equations of the prospective and retrospective mathematical reserves. The model is applied to a sample of contracts drawn at random from a mutual insurance company.

Multiple imputations applied to the DREAM3 phosphoproteomics challenge: a winning strategy.

DREAM is an initiative that allows researchers to assess how well their methods or approaches can describe and predict networks of interacting molecules [1]. Each year, recently acquired datasets are released to predictors ahead of publication. Researchers typically have about three months to predict the masked data or network of interactions, using any predictive method. Predictions are assessed prior to an annual conference where the best predictions are unveiled and discussed. Here we present the strategy we used to make a winning prediction for the DREAM3 phosphoproteomics challenge. We used Amelia II, a multiple imputation software method developed by Gary King, James Honaker and Matthew Blackwell[2] in the context of social sciences to predict the 476 out of 4624 measurements that had been masked for the challenge. To chose the best possible multiple imputation parameters to apply for the challenge, we evaluated how transforming the data and varying the imputation parameters affected the ability to predict additionally masked data. We discuss the accuracy of our findings and show that multiple imputations applied to this dataset is a powerful method to accurately estimate the missing data. We postulate that multiple imputations methods might become an integral part of experimental design as a mean to achieve cost savings in experimental design or to increase the quantity of samples that could be handled for a given cost.

Geometry and physics of catenanes applied to the study of DNA replication.

The concept of ideal geometric configurations was recently applied to the classification and characterization of various knots. Different knots in their ideal form (i.e., the one requiring the shortest length of a constant-diameter tube to form a given knot) were shown to have an overall compactness proportional to the time-averaged compactness of thermally agitated knotted polymers forming corresponding knots. This was useful for predicting the relative speed of electrophoretic migration of different DNA knots. Here we characterize the ideal geometric configurations of catenanes (called links by mathematicians), i.e., closed curves in space that are topologically linked to each other. We demonstrate that the ideal configurations of different catenanes show interrelations very similar to those observed in the ideal configurations of knots. By analyzing literature data on electrophoretic separations of the torus-type of DNA catenanes with increasing complexity, we observed that their electrophoretic migration is roughly proportional to the overall compactness of ideal representations of the corresponding catenanes. This correlation does not apply, however, to electrophoretic migration of certain replication intermediates, believed up to now to represent the simplest torus-type catenanes. We propose, therefore, that freshly replicated circular DNA molecules, in addition to forming regular catenanes, may also form hemicatenanes.

New imaging techniques applied to Paleogene radiolaria

A simple and time efficient technique to illustrate specimens is described and demonstrated with Paleogene radiolarians. This method produces Scanning Electron Microscope (SEM) and composite focal depth Transmitted Light Microscope (TLM) images for single radiolarian specimens. We propose the use of this technique to clarify radiolarian taxonomy. This technique has distinct advantages over previously published time consuming techniques that can also require toxic materials.

Clinical research: how to be involved

The Northern Ireland Clinical Research Network (NICRN) undertakes research in a range of medical fields, which have recently been expanded to include mental health. The NICRN is part of a UK-wide initiative to provide opportunities for patients and clinicians to participate in high-quality clinical research.This suite of leaflets provides both the public and clinical researchers with an introduction to the work of the NICRN. They provide an overview of the NICRN's goals and highlight what the network can offer to patients, carers and researchers. Each leaflet includes specific details on the NICRN's work in that area and reasons why clinical research plays such a vital role in improving the delivery of health and social care

Quantitative paleoparasitology applied to archaeological sediments

Three techniques to extract parasite remains from archaeological sediments were tested. The aim was to improve the sensibility of recommended paleoparasitological techniques applied in archaeological remains. Sediment collected from the pelvic girdle of a human body found in Cabo Vírgenes, Santa Cruz, Argentina, associated to a Spanish settlement founded in 1584 known as Nombre de Jesús, was used to search for parasites. Sediment close to the skull was used as control. The techniques recommended by Jones, Reinhard, and Dittmar and Teejen were used and compared with the modified technique presented here, developed to improve the sensibility to detect parasite remains. Positive results were obtained only with the modified technique, resulting in the finding of Trichuris trichiura eggs in the sediment.

Response of Triatoma infestans to pour-on cypermethrin applied to chickens under laboratory conditions

This article reports the effects of a pour-on formulation of cypermethrin (6% active ingredient) applied to chickens exposed to Triatoma infestans, the main vector of Chagas disease in rural houses of the Gran Chaco Region of South America. This study was designed as a completely random experiment with three experimental groups and five replicates. Third instar nymphs were fed on chickens treated with 0, 1 and 2 cc of the formulation. Nymphs were allowed to feed on the chickens at different time intervals after the insecticide application. Third-instar nymphs fed on treated chickens showed a higher mortality, took less blood during feeding and had a lower moulting rate. The mortality rate was highest seven days after the insecticide solution application and blood intake was affected until 30 days after the application of the solution.

An empirical study of machine learning techniques applied to image watermarking

A study of how the machine learning technique, known as gentleboost, could improve different digital watermarking methods such as LSB, DWT, DCT2 and Histogram shifting.

Immune response to the mumps component of the MMR vaccine in the routine of immunisation services in the Brazilian National Immunisation Program

A non-controlled longitudinal study was conducted to evaluate the combined vaccine against measles, mumps and rubella (MMR) immunogenicity in 150 children vaccinated in the routine of three health units in the city of Rio de Janeiro, Brazil, 2008-2009, without other vaccines administered during the period from 30 days before to 30 days after vaccination. A previous study conducted in Brazil in 2007, in 1,769 children ranging from 12-15 months of age vaccinated against yellow fever and MMR simultaneously or at intervals of 30 days or more between doses, had shown low seroconversion for mumps regardless of the interval between administration of the two vaccines. The current study showed 89.5% (95% confidence interval: 83.3; 94.0) seroconversion rate for mumps. All children seroconverted for measles and rubella. After revaccination, high antibody titres and seroconversion rates were achieved against mumps. The results of this study and others suggest that two MMR doses confer optimal immunoresponses for all three antigens and the possible need for additional doses should be studied taking into account not only serological, but also epidemiological data, as there is no serological correlate of protection for mumps.

3-d residual eddy current field characterisation: applied to diffusion weighted magnetic resonance imaging.

Clinical use of the Stejskal-Tanner diffusion weighted images is hampered by the geometric distortions that result from the large residual 3-D eddy current field induced. In this work, we aimed to predict, using linear response theory, the residual 3-D eddy current field required for geometric distortion correction based on phantom eddy current field measurements. The predicted 3-D eddy current field induced by the diffusion-weighting gradients was able to reduce the root mean square error of the residual eddy current field to ~1 Hz. The model's performance was tested on diffusion weighted images of four normal volunteers, following distortion correction, the quality of the Stejskal-Tanner diffusion-weighted images was found to have comparable quality to image registration based corrections (FSL) at low b-values. Unlike registration techniques the correction was not hindered by low SNR at high b-values, and results in improved image quality relative to FSL. Characterization of the 3-D eddy current field with linear response theory enables the prediction of the 3-D eddy current field required to correct eddy current induced geometric distortions for a wide range of clinical and high b-value protocols.

Markov chain montecarlo method applied to rounding zeros of compositional data: first approach

As stated in Aitchison (1986), a proper study of relative variation in a compositional data set should be based on logratios, and dealing with logratios excludes dealing with zeros. Nevertheless, it is clear that zero observations might be present in real data sets, either because the corresponding part is completelyabsent –essential zeros– or because it is below detection limit –rounded zeros. Because the second kind of zeros is usually understood as “a trace too small to measure”, it seems reasonable to replace them by a suitable small value, and this has been the traditional approach. As stated, e.g. by Tauber (1999) and byMartín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2000), the principal problem in compositional data analysis is related to rounded zeros. One should be careful to use a replacement strategy that does not seriously distort the general structure of the data. In particular, the covariance structure of the involvedparts –and thus the metric properties– should be preserved, as otherwise further analysis on subpopulations could be misleading. Following this point of view, a non-parametric imputation method isintroduced in Martín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2000). This method is analyzed in depth by Martín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2003) where it is shown that thetheoretical drawbacks of the additive zero replacement method proposed in Aitchison (1986) can be overcome using a new multiplicative approach on the non-zero parts of a composition. The new approachhas reasonable properties from a compositional point of view. In particular, it is “natural” in the sense thatit recovers the “true” composition if replacement values are identical to the missing values, and it is coherent with the basic operations on the simplex. This coherence implies that the covariance structure of subcompositions with no zeros is preserved. As a generalization of the multiplicative replacement, in thesame paper a substitution method for missing values on compositional data sets is introduced

Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors

Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

Comparison of antibiotic drops placed in the conjunctival cul-de-sac to antibiotic ointment applied to the lid margin in reduction of bacterial colonization on the lid margin.

PURPOSE: To compare the efficacy of antibiotic drops placed in the conjunctival cul-de-sac to antibiotic ointment applied to the lid margin in reduction of bacterial colonization on the lid margin. METHODS: A randomized, prospective, single-masked study was conducted on 19 patients with culture-proven colonization of bacteria on the lid margins. Ophthalmic eligibility criteria included the presence of > or =50 colony-forming units/mL (CFU/mL) of bacteria on both right and left lids. Each patient received one drop of ofloxacin in one eye every night for one week, followed by one drop once a week for one month. In the same manner, each patient received bacitracin ointment (erythromycin or gentamicin ointment if lid margin bacteria were resistant to bacitracin) to the lid margin of the fellow eye. Quantitative lid cultures were taken at initial visit, one week, one month, and two months. Fifteen volunteers (30 lids) served as controls. Lid cultures were taken at initial visit, one week, and one month. RESULTS: Both antibiotic drop and ointment reduced average bacterial CFU/mL at one week and one month. Average bacterial CFU/mL reestablished to baseline values at two months. There was no statistically significant difference between antibiotic drop and ointment in reducing bacterial colonization on the lid margin. CONCLUSION: Antibiotic drops placed in the conjunctival cul-de-sac appear to be as effective as ointment applied to the lid margins in reducing bacterial colonization in patients with > or =50 CFU/mL of bacteria on the lid margins.

Development of model observers applied to 3D breast tomosynthesis microcalcifications and masses

The development of model observers for mimicking human detection strategies has followed from symmetric signals in simple noise to increasingly complex backgrounds. In this study we implement different model observers for the complex task of detecting a signal in a 3D image stack. The backgrounds come from real breast tomosynthesis acquisitions and the signals were simulated and reconstructed within the volume. Two different tasks relevant to the early detection of breast cancer were considered: detecting an 8 mm mass and detecting a cluster of microcalcifications. The model observers were calculated using a channelized Hotelling observer (CHO) with dense difference-of-Gaussian channels, and a modified (Partial prewhitening [PPW]) observer which was adapted to realistic signals which are not circularly symmetric. The sustained temporal sensitivity function was used to filter the images before applying the spatial templates. For a frame rate of five frames per second, the only CHO that we calculated performed worse than the humans in a 4-AFC experiment. The other observers were variations of PPW and outperformed human observers in every single case. This initial frame rate was a rather low speed and the temporal filtering did not affect the results compared to a data set with no human temporal effects taken into account. We subsequently investigated two higher speeds at 5, 15 and 30 frames per second. We observed that for large masses, the two types of model observers investigated outperformed the human observers and would be suitable with the appropriate addition of internal noise. However, for microcalcifications both only the PPW observer consistently outperformed the humans. The study demonstrated the possibility of using a model observer which takes into account the temporal effects of scrolling through an image stack while being able to effectively detect a range of mass sizes and distributions.