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Correct Prediction (correct + prediction)
Selected AbstractsSolidification of binary aqueous solution cooled from aboveHEAT TRANSFER - ASIAN RESEARCH (FORMERLY HEAT TRANSFER-JAPANESE RESEARCH), Issue 1 2010Shigeo Kimura Abstract Freezing and melting phenomena are important in many different fields, including crystal growth, casting, metallurgy, geophysics, and oceanography. Solidification of a multi-component solution is the one often observed in nature. In order to investigate basic features of the freezing processes of binary systems, we conducted a series of laboratory experiments in a rectangular box cooled from above using aqueous NaNO3 solution. During the freezing, the solid phase always grows into many needle-like crystals called the mushy layer. We measured the growth of the mushy layer thickness, the solid fraction, the temperature, and the concentration distributions. The average solid fraction is found to increase with time in the mushy layer. This causes a slow descent of the released solute in the mushy layer and its eventual fall into the liquid region below because of gravity. We propose a one-dimensional model to explain the horizontally-averaged mushy layer growth. In the model, the estimate of a heat flux at the mushy-liquid interface due to natural convection is found essential for a correct prediction. The proposed theory predicts well the growth of the mushy-layer and the average solid fraction, once the convective heat flux is properly given. © 2009 Wiley Periodicals, Inc. Heat Trans Asian Res; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/htj.20278 [source] BILU implicit multiblock Euler/Navier,Stokes simulation for rotor tip vortex and wake convectionINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 6 2007Bowen Zhong Abstract In this paper, a block incomplete lower,upper (BILU) decomposition method is incorporated with a multiblock three-dimensional Euler/Navier,Stokes solver for simulation of hovering rotor tip vortices and rotor wake convection. Results of both Euler and Navier,Stokes simulations are obtained and compared with experimental observations. The comparisons include surface pressure distributions and tip vortex trajectories. The comparisons suggest that resolution of the boundary layer is important for the accurate evaluation of the blade surface loading, but is less so for the correct prediction of the vortex trajectory. Numerical tests show that, using Courant,Friedrichs,Lewy (CFL) number of 10 or 30 with the developed BILU implicit scheme can be 6,7 times faster than an explicit scheme. The importance of solution acceleration schemes that increase the permitted time-step is illustrated by comparing the evolving wake structures at different stages of the calculation. In contrast to fixed wing simulations, the extent of the wake structures is shown to require resolution of large physical time. This observation explains the poor performance that is obtained when employing convergence acceleration strategies originally intended for solution of equilibrium problems, such as the multigrid methods. Copyright © 2007 John Wiley & Sons, Ltd. [source] Multiple classifier integration for the prediction of protein structural classesJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 14 2009Lei Chen Abstract Supervised classifiers, such as artificial neural network, partition trees, and support vector machines, are often used for the prediction and analysis of biological data. However, choosing an appropriate classifier is not straightforward because each classifier has its own strengths and weaknesses, and each biological dataset has its own characteristics. By integrating many classifiers together, people can avoid the dilemma of choosing an individual classifier out of many to achieve an optimized classification results (Rahman et al., Multiple Classifier Combination for Character Recognition: Revisiting the Majority Voting System and Its Variation, Springer, Berlin, 2002, 167,178). The classification algorithms come from Weka (Witten and Frank, Data Mining: Practical Machine Learning Tools and Techniques, Morgan Kaufmann, San Francisco, 2005) (a collection of software tools for machine learning algorithms). By integrating many predictors (classifiers) together through simple voting, the correct prediction (classification) rates are 65.21% and 65.63% for a basic training dataset and an independent test set, respectively. These results are better than any single machine learning algorithm collected in Weka when exactly the same data are used. Furthermore, we introduce an integration strategy which takes care of both classifier weightings and classifier redundancy. A feature selection strategy, called minimum redundancy maximum relevance (mRMR), is transferred into algorithm selection to deal with classifier redundancy in this research, and the weightings are based on the performance of each classifier. The best classification results are obtained when 11 algorithms are selected by mRMR method, and integrated together through majority votes with weightings. As a result, the prediction correct rates are 68.56% and 69.29% for the basic training dataset and the independent test dataset, respectively. The web-server is available at http://chemdata.shu.edu.cn/protein_st/. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2009 [source] Early Risk Indicators of Substance Abuse Among NursesJOURNAL OF NURSING SCHOLARSHIP, Issue 2 2002Margaret Mary West Purpose: To investigate early risk factors that led to substance-related disorders and to predict group differences between substance-impaired (SI) and nonimpaired (NI) registered nurses. Organizing Construct: Donovan's multifactorial model of impairment, and Rogers'Science of Unitary Human Beings. Methods: Data were gathered from 100 previously SI and 100 NI nurses located through use of the Internet. Three questionnaires were used: the Zuckerman Sensation Seeking Scale (ZSSS), the Efinger Alcohol Risk Survey (EARS), and the Children of Alcoholics Screening Test (CAST). Findings: Independent t-test scores showed the two groups differed significantly on all three instruments' total scores. Discriminate analysis indicated a correct prediction of 87% for SI and 95% for NI nurses, with an overall rate of 91%. EARS scores were the best predictor of nurses with substance-related disorders (.99), followed by ZSSS (.44) and CAST (.42) scores. Conclusions: The three variables indicate early risk factors for substance-abuse impairment. Identification of nurses at risk for impairment will allow for earlier intervention and possible prevention. Methods to reduce the number of modifiable risk factors are recommended. [source] PREDICTING SENSORY COHESIVENESS, HARDNESS AND SPRINGINESS OF SOLID FOODS FROM INSTRUMENTAL MEASUREMENTSJOURNAL OF TEXTURE STUDIES, Issue 2 2008R. DI MONACO ABSTRACT The sensory evaluation of cohesiveness, hardness and springiness of 15 solid food samples was performed by eight trained assessors. The rheologic response of the 15 samples was estimated by performing cyclic compression tests and stress,relaxation tests. From the force,deformation curves of the first two cycles of the compression test, texture profile analysis parameters related to cohesiveness, hardness and springiness were calculated. Young's modulus (E), strain (di) and stress (si) at peak as well as irrecoverable strain (ri) and irrecoverable work (Li) were monitored during the first five cycles. From the stress,relaxation response, Peleg's linearization model parameters, K1 and K2, were estimated by best-fit regression. These parameters were used for predicting sensory attributes. Hardness and springiness were both accurately predicted by rheologic properties, while cohesiveness prediction was less representative. PRACTICAL APPLICATIONS This study contributes to enhance the knowledge in the research area of sensory instrumental correlation. Also, the research allows to better understanding that no single instrument is able to measure all texture attributes adequately. In fact, the results demonstrate that both stress,relaxation and cyclic compression tests need to be performed for the correct prediction of sensory responses. [source] Eosinophil cationic protein in infants with respiratory syncytial virus bronchiolitis: Predictive value for subsequent development of persistent wheezingPEDIATRIC PULMONOLOGY, Issue 6 2001Massimo Pifferi MD Abstract Infants with acute bronchiolitis during the first months of life are at increased risk of developing persistent wheezing and bronchial asthma later in life. The study of eosinophil cationic protein (ECP) suggests that eosinophil-related inflammatory mechanisms may play a role in respiratory syncytial virus (RSV) bronchiolitis. The aim of our study was to verify whether serum ECP (s-ECP) measurements are useful in predicting the development of persistent wheezing in children affected by RSV bronchiolitis during a 5 years follow-up period. Forty-eight infants were enrolled prospectively (mean age: 153.5 days). All had a clinical and radiological diagnosis of acute bronchiolitis and confirmed RSV infection. Peripheral eosinophil counts, levels of s-ECP, and serum IgE concentrations were measured during bronchiolitis. Five years later the children were re-evaluated in regard to their respiratory symptoms (standardized questionnaires) and atopic status (specific IgE levels). We observed significantly higher s-ECP levels (P <,0.001) at enrollment in subjects who developed persistent wheezing compared to subjects who did not show late wheezing. Initial s-ECP values allowed significant and correct prediction of persistent wheezing (P <,0.001). The risk to develop respiratory symptoms was 9.73 higher for infants with s-ECP levels ,,8,,g/L than for those with s-ECP levels <8,,g/L (P <,0.0001). In conclusion, our study suggests that s-ECP levels in infants with bronchiolitis are useful in predicting the risk to develop wheezing in the subsequent 5 years. Pediatr Pulmonol. 2001; 31:419,424. © 2001 Wiley-Liss, Inc. [source] Anthropometric indices as predictors of the metabolic syndrome and its components in adolescentsPEDIATRICS INTERNATIONAL, Issue 3 2010Christian Jung Abstract Background:, Overweight and related health problems are becoming increasingly recognized, especially in children and adolescents. For early screening, different anthropometrical measurements of obesity have been proposed to identify individuals at risk. We compared body mass index (BMI), BMI standard deviation score, waist circumference, waist-to-hip ratio (WHR), and waist/height ratio with respect to their power to predict the metabolic syndrome, its components and low-grade inflammation. Methods:, A total of 79 male Caucasian German adolescents (13,17 years) were studied. All anthropometrical measurements of obesity were recorded and blood samples drawn. Predictive power was estimated using receiver operating characteristic curves, by comparing the area under the curve (AUC). Results:, Except for WHR, all tested anthropometrical measurements of obesity showed comparably good AUC values for correct prediction, with the highest AUC for BMI (P < 0.001, AUC = 0.885 ± 0.039). Superior prediction power was not observed for BMI standard deviation score, waist circumference, WHR or waist/height ratio. Furthermore, BMI was the best predictor of elevated C-reactive protein levels as a marker for low-grade inflammation (P < 0.001, AUC = 0.786 ± 0.064). Conclusions:, In this cross-sectional study the well-established parameter BMI was shown to have the best predictive power to identify metabolic syndrome, its components and markers for low-grade inflammation. Newly developed parameters did not provide superior values. Future longitudinal studies are needed to compare these anthropometrical markers in larger cohorts, incorporating different age groups and ethnic backgrounds. [source] Configurational-bias sampling technique for predicting side-chain conformations in proteinsPROTEIN SCIENCE, Issue 9 2006Tushar Jain Abstract Prediction of side-chain conformations is an important component of several biological modeling applications. In this work, we have developed and tested an advanced Monte Carlo sampling strategy for predicting side-chain conformations. Our method is based on a cooperative rearrangement of atoms that belong to a group of neighboring side-chains. This rearrangement is accomplished by deleting groups of atoms from the side-chains in a particular region, and regrowing them with the generation of trial positions that depends on both a rotamer library and a molecular mechanics potential function. This method allows us to incorporate flexibility about the rotamers in the library and explore phase space in a continuous fashion about the primary rotamers. We have tested our algorithm on a set of 76 proteins using the all-atom AMBER99 force field and electrostatics that are governed by a distance-dependent dielectric function. When the tolerance for correct prediction of the dihedral angles is a <20° deviation from the native state, our prediction accuracies for ,1 are 83.3% and for ,1 and ,2 are 65.4%. The accuracies of our predictions are comparable to the best results in the literature that often used Hamiltonians that have been specifically optimized for side-chain packing. We believe that the continuous exploration of phase space enables our method to overcome limitations inherent with using discrete rotamers as trials. [source] Turbulence model and numerical scheme assessment for buffet computationsINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 11 2004Eric Goncalves Abstract The prediction of shock-induced oscillations over transonic rigid airfoils is important for a better understanding of the buffeting phenomenon. The unsteady resolution of the Navier,Stokes equations is performed with various transport-equation turbulence models in which corrections are added for non-equilibrium flows. The lack of numerical efficiency due to the CFL stability condition is circumvented by the use of a wall law approach and a dual time stepping method. Moreover, various numerical schemes are used to try and be independent of the numerical discretization. Comparisons are made with the experimental results obtained for the supercritical RA16SC1 airfoil. They show the interest in using the SST correction or realizability conditions to get correct predictions of the frequency, amplitude and pressure fluctuations over the airfoil. Copyright © 2004 John Wiley & Sons, Ltd. [source] Prediction of integral membrane protein type by collocated hydrophobic amino acid pairsJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 1 2009Ke Chen Abstract A computational model, IMP-TYPE, is proposed for the classification of five types of integral membrane proteins from protein sequence. The proposed model aims not only at providing accurate predictions but most importantly it incorporates interesting and transparent biological patterns. When contrasted with the best-performing existing models, IMP-TYPE reduces the error rates of these methods by 19 and 34% for two out-of-sample tests performed on benchmark datasets. Our empirical evaluations also show that the proposed method provides even bigger improvements, i.e., 29 and 45% error rate reductions, when predictions are performed for sequences that share low (40%) identity with sequences from the training dataset. We also show that IMP-TYPE can be used in a standalone mode, i.e., it duplicates significant majority of correct predictions provided by other leading methods, while providing additional correct predictions which are incorrectly classified by the other methods. Our method computes predictions using a Support Vector Machine classifier that takes feature-based encoded sequence as its input. The input feature set includes hydrophobic AA pairs, which were selected by utilizing a consensus of three feature selection algorithms. The hydrophobic residues that build up the AA pairs used by our method are shown to be associated with the formation of transmembrane helices in a few recent studies concerning integral membrane proteins. Our study also indicates that Met and Phe display a certain degree of hydrophobicity, which may be more crucial than their polarity or aromaticity when they occur in the transmembrane segments. This conclusion is supported by a recent study on potential of mean force for membrane protein folding and a study of scales for membrane propensity of amino acids. © 2008 Wiley Periodicals, Inc. J Comput Chem, 2009 [source] Combined Use of PCA and QSAR/QSPR to Predict the Drugs Mechanism of Action.MOLECULAR INFORMATICS, Issue 4 2009An Application to the NCI ACAM Database Abstract During the years the National Cancer Institute (NCI) accumulated an enormous amount of information through the application of a complex protocol of drugs screening involving several tumor cell lines, grouped into panels according to the disease class. The Anti-cancer Agent Mechanism (ACAM) database is a set of 122 compounds with anti-cancer activity and a reasonably well known mechanism of action, for which are available drug screening data that measure their ability to inhibit growth of a panel of 60 human tumor lines, explicitly designed as a training set for neural network and multivariate analysis. The aim of this work is to adapt a methodology (previously developed for the analysis of DNA minor groove binders) for the analysis of NCI ACAM database, using Principal Component Analysis (PCA) and QSAR/QSPR for the prediction of the mechanism of action of anti-cancer drugs. The entire database was splitted in a training set of 60 structures and a test set of 48 ones, and each set was expressed in form of a matrix on which further procedures were performed. Three statistical parameters were calculated: First Attempt of Prediction (FAP) expresses the percentage of correct predictions at first attempt, Total Attempt of Prediction (TAP) expresses the total percentage of correct predictions across all the three attempts, Non-Classified (NC) expresses the percentage of compounds whose mechanism of action has failed to be predicted. The predictive ability of this approach is variable, but the results obtained are generally good; using 50% Growth Inhibiting concentration (GI50) values as training data, we were able to assign a correct mechanism of action with a good degree of reliability (more than 79%). [source] No visible optical variability from a relativistic blast wave encountering a wind termination shockMONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY: LETTERS (ELECTRONIC), Issue 1 2009H. J. Van Eerten ABSTRACT Gamma-ray burst afterglow flares and rebrightenings of the optical and X-ray light curves have been attributed to both late-time inner engine activity and density changes in the medium surrounding the burster. To test the latter, we study the encounter between the relativistic blast wave from a gamma-ray burster and a stellar wind termination shock. The blast wave is simulated using a high-performance adaptive mesh relativistic hydrodynamic code, amrvac, and the synchrotron emission is analysed in detail with a separate radiation code. We find no bump in the resulting light curve, not even for very high density jumps. Furthermore, by analysing the contributions from the different shock wave regions we are able to establish that it is essential to resolve the blast wave structure in order to make qualitatively correct predictions on the observed output and that the contribution from the reverse shock region will not stand out, even when the magnetic field is increased in this region by repeated shocks. This study resolves a controversy in the recent literature. [source] Ovarian reserve tests and their utility in predicting response to controlled ovarian stimulation in rhesus monkeysAMERICAN JOURNAL OF PRIMATOLOGY, Issue 8 2010Julie M. Wu Abstract Controlled ovarian stimulation (COS) is an alternative to natural breeding in nonhuman primates; however, these protocols are costly with no guarantee of success. Toward the objective of predicting COS outcome in rhesus monkeys, this study evaluated three clinically used ovarian reserve tests (ORTs): day 3 (d3) follicle-stimulating hormone (FSH) with d3 inhibin B (INHB), the clomiphene citrate challenge test (CCCT), and the exogenous FSH Ovarian Reserve Test. A COS was also performed and response was classified as either successful (COS+) or unsuccessful (COS,) and retrospectively compared with ORT predictions. FSH and INHB were assessed for best hormonal index in conjunction with the aforementioned tests. INHB was consistently more accurate than FSH in all the ORTs used. Overall, a modified version of the CCCT using INHB values yielded the best percentage of correct predictions. This is the first report of ORT evaluation in rhesus monkeys and may provide a useful diagnostic test before costly follicle stimulations, as well as predicting the onset of menopause. Am. J. Primatol. 72:672,680, 2010. © 2010 Wiley-Liss, Inc. [source] | ||||||||||||||||