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Related Approaches (relate + approach)
Selected AbstractsJAC: declarative Java concurrencyCONCURRENCY AND COMPUTATION: PRACTICE & EXPERIENCE, Issue 5 2006Max Haustein Abstract The Java programming language has a low-level concurrency model which is hard to use and does not blend well with inheritance. JAC is an extension of Java that introduces a higher level of concurrency, hiding threads and separating thread synchronization from application logic in a declarative fashion. The emphasis is on limiting the differences between sequential and concurrent code, thus furthering code reuse, and on avoiding inheritance anomalies. This is achieved by taking a middle road between concurrent code on the one hand and complete separation of sequential application logic from concurrency mechanisms on the other. An extensive comparison with related approaches is given for motivating our design decisions. Copyright © 2005 John Wiley & Sons, Ltd. [source] Quantitative structure-activity relationship methods: Perspectives on drug discovery and toxicologyENVIRONMENTAL TOXICOLOGY & CHEMISTRY, Issue 8 2003Roger Perkins Abstract Quantitative structure,activity relationships (QSARs) attempt to correlate chemical structure with activity using statistical approaches. The QSAR models are useful for various purposes including the prediction of activities of untested chemicals. Quantitative structure,activity relationships and other related approaches have attracted broad scientific interest, particularly in the pharmaceutical industry for drug discovery and in toxicology and environmental science for risk assessment. An assortment of new QSAR methods have been developed during the past decade, most of them focused on drug discovery. Besides advancing our fundamental knowledge of QSARs, these scientific efforts have stimulated their application in a wider range of disciplines, such as toxicology, where QSARs have not yet gained full appreciation. In this review, we attempt to summarize the status of QSAR with emphasis on illuminating the utility and limitations of QSAR technology. We will first review two-dimensional (2D) QSAR with a discussion of the availability and appropriate selection of molecular descriptors. We will then proceed to describe three-dimensional (3D) QSAR and key issues associated with this technology, then compare the relative suitability of 2D and 3D QSAR for different applications. Given the recent technological advances in biological research for rapid identification of drug targets, we mention several examples in which QSAR approaches are employed in conjunction with improved knowledge of the structure and function of the target receptor. The review will conclude by discussing statistical validation of QSAR models, a topic that has received sparse attention in recent years despite its critical importance. [source] Turbulence modelling of problem aerospace flowsINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 3 2006Paul G. Tucker Abstract Unsteady Reynolds averaged Navier,Stokes (URANS) and detached eddy simulation (DES) related approaches are considered for high angle of attack NACA0012 airfoil, wing,flap, generic tilt-rotor airfoil and double-delta geometry flows. These are all found to be problem flows for URANS models. For DES fifth-order upwinding is found too dissipative and the use of, for high speed flows, instability prone centred differencing essential. An existing hybrid ILES,RANS modelling approach, intended for flexible geometry, relatively high numerical dissipation codes is tested along with differential wall distance algorithms. The former gives promising results. The standard turbulence modelling approaches are found to give perhaps a surprising results variation. Results suggest that for the problem flows, the explicit algebraic stress and Menter shear stress transport (SST) URANS models are more accurate than the economical Spalart,Allmaras (SA). However, the explicit algebraic stress model (EASM) in its k,, form is impractically expensive to converge. Here, SA predictions lack a rotation correction term and this is likely to improve these results. Copyright © 2005 John Wiley & Sons, Ltd. [source] Expression profiling of Wilms tumors reveals new candidate genes for different clinical parametersINTERNATIONAL JOURNAL OF CANCER, Issue 8 2006B. Zirn Abstract Wilms tumor is the most frequent renal neoplasm in children, but our understanding of its genetic basis is still limited. We performed cDNA microarray experiments using 63 primary Wilms tumors with the aim of detecting new candidate genes associated with malignancy grade and tumor progression. All tumors had received preoperative chemotherapy as mandated by the SIOP protocol, which sets this study apart from related approaches in the Unites States that are based on untreated samples. The stratification of expression data according to clinical criteria allowed a rather clear distinction between different subsets of Wilms tumors. Clear-cut differences in expression patterns were discovered between relapse-free as opposed to relapsed tumors and tumors with intermediate risk as opposed to high risk histology. Several differentially expressed genes, e.g.TRIM22, CENPF, MYCN, CTGF, RARRES3 and EZH2, were associated with Wilms tumor progression. For a subset of differentially expressed genes, microarray data were confirmed by real-time RT-PCR on the original set of tumors. Interestingly, we found the retinoic acid pathway to be deregulated at different levels in advanced tumors suggesting that treatment of these tumors with retinoic acid may represent a promising novel therapeutic approach. © 2005 Wiley-Liss, Inc. [source] Empirical preprocessing methods and their impact on NIR calibrations: a simulation studyJOURNAL OF CHEMOMETRICS, Issue 2 2005S. N. Thennadil Abstract The extraction of chemical information from dense particulate suspensions, such as industrial slurries and biological suspensions, using near-infrared (NIR) spectroscopic measurements is complicated by sample-to-sample path length variations due to light scattering. Empirical preprocessing techniques such as multiplicative scatter correction (MSC), extended MSC and derivatives have been applied to remove these effects and in some cases have shown promise. While the performance of these techniques and other related approaches is known to depend on the nature and extent of the variations and on the measurement configuration, detailed investigations into the efficacy of these approaches under various conditions have not been previously undertaken. The main obstacle to carrying out such investigations has been the lack of, and the difficulty in obtaining, an accurate and comprehensive experimental data set. In this work, simulations that generate ,actual' measurements were carried out to obtain ,experimental' spectroscopic data on particulate systems. This was achieved by solving the exact transport equation for light propagation. A model system comprising four chemical components with one consisting of spherical submicron particles was considered. Total diffuse transmittance and reflectance data generated through simulations for moderate particle concentrations were used as the basis for examining the effect of particle size variations and measurement configurations on the efficacy of a number of preprocessing techniques in enhancing the performance of partial least squares (PLS) models for predicting the concentration of one of the non-scattering chemical species. Additionally, a form of extended multiplicative signal correction based on considerations arising from fundamental light scattering theory is proposed and found to perform better than the other techniques for the cases considered in the study. Copyright © 2005 John Wiley & Sons, Ltd. [source] A tale of two matrices: multivariate approaches in evolutionary biologyJOURNAL OF EVOLUTIONARY BIOLOGY, Issue 1 2007M. W. BLOWS Abstract Two symmetric matrices underlie our understanding of microevolutionary change. The first is the matrix of nonlinear selection gradients (,) which describes the individual fitness surface. The second is the genetic variance,covariance matrix (G) that influences the multivariate response to selection. A common approach to the empirical analysis of these matrices is the element-by-element testing of significance, and subsequent biological interpretation of pattern based on these univariate and bivariate parameters. Here, I show why this approach is likely to misrepresent the genetic basis of quantitative traits, and the selection acting on them in many cases. Diagonalization of square matrices is a fundamental aspect of many of the multivariate statistical techniques used by biologists. Applying this, and other related approaches, to the analysis of the structure of , and G matrices, gives greater insight into the form and strength of nonlinear selection, and the availability of genetic variance for multiple traits. [source] Applications of neural network analyses to in vivo 1H magnetic resonance spectroscopy of Parkinson disease patientsJOURNAL OF MAGNETIC RESONANCE IMAGING, Issue 1 2002David Axelson PhD Abstract Purpose To apply neural network analyses to in vivo magnetic resonance spectra of controls and Parkinson disease (PD) patients for the purpose of classification. Materials and Methods Ninety-seven in vivo proton magnetic resonance spectra of the basal ganglia were recorded from 31 patients with (PD) and 14 age-matched healthy volunteers on a 1.5-T imager. The PD patients were grouped as follows: probable PD (N = 15), possible PD (N = 11), and atypical PD (N = 5). Total acquisition times of approximately five minutes were achieved with a TE (echo time) of 135 msec, a TR (repetition time) of 2000 msec, and 128 scan averages. Neural network (back propagation, Kohonen, probabilistic, and radial basis function) and related (generative topographic mapping) data analyses were performed. Results Conventional data analysis showed no statistically significant differences in metabolite ratios based on measuring signal intensities. The trained networks could distinguish control from PD with considerable accuracy (true positive fraction 0.971, true negative fraction 0.933). When four classes were defined, approximately 88% of the predictions were correct. The multivariate analysis indicated metabolic changes in the basal ganglia in PD. Conclusion A variety of neural network and related approaches can be successfully applied to both qualitative visualization and classification of in vivo spectra of PD patients. J. Magn. Reson. Imaging 2002;16:13,20. © 2002 Wiley -Liss, Inc. [source] Approaches to the identification of susceptibility genesPARASITE IMMUNOLOGY, Issue 5 2009A. COLLINS SUMMARY Although previous studies have revealed a great deal about the genetic basis of susceptibility and resistance to parasite infection, there is now an opportunity to considerably enhance understanding through genome-wide association mapping. The application of association mapping to complex inheritance has recently become achievable given reduced costs, sophisticated genotyping platforms and powerful statistical methods which build upon increased knowledge of the linkage disequilibrium structure of the human genome. Linkage mapping and related approaches remain useful for the localization of the rarer genetic variants and candidate region association studies can be a very cost-effective route to progress. However, genome-wide association offers the greatest promise, despite the challenges posed by phenotype complexity, ensuring genotype coverage/quality and robust statistical analysis. The available approaches for mapping genes underlying susceptibility are reviewed here, emphasizing their relative merits and drawbacks and highlighting specific software tools and resources that enable successful mapping. [source] 2153: Can we treat glaucoma by non-IOP related approaches?ACTA OPHTHALMOLOGICA, Issue 2010I STALMANS Intra-ocular pressure is the main risk factor for the progression of glaucoma. However, intra-ocular pressure lowering is not always sufficient to halt the progressive ganglion cell loss. Indeed, additional risk factors have been identified for glaucoma progression that can explain why some patients progress despite rigourous intra-ocular pressure lowering. Vascular risk factors, such as low perfusion pressure, can be taken into account in the management of our glaucoma patients. The treatment options for these vascular risk factors will be discussed during the lecture. Moreover, neuroprotective strategies might open therapeutic perspectives to directly support the ganglion cells and thus help stabilizing the disease. Possible neuroprotective agents will be highlighted. [source] | |||||||||||||