Numerical sensitivity analysis of welding-induced residual stress depending on variations in continuous cooling transformation behavior

NASA Astrophysics Data System (ADS)

Heinze, C.; Schwenk, C.; Rethmeier, M.; Caron, J.

2011-06-01

The usage of continuous cooling transformation (CCT) diagrams in numerical welding simulations is state of the art. Nevertheless, specifications provide limits in chemical composition of materials which result in different CCT behavior and CCT diagrams, respectively. Therefore, it is necessary to analyze the influence of variations in CCT diagrams on the developing residual stresses. In the present paper, four CCT diagrams and their effect on numerical calculation of residual stresses are investigated for the widely used structural steel S355J2 + N welded by the gas metal arc welding (GMAW) process. Rather than performing an arbitrary adjustment of CCT behavior, four justifiable data sets were used as input to the numerical calculation: data available in the Sysweld database, experimental data acquired through Gleeble dilatometry tests, and TTT/CCT predictions calculated from the JMatPro and Edison Welding Institute (EWI) Virtual Joining Portal software. The performed numerical analyses resulted in noticeable deviations in residual stresses considering the different CCT diagrams. Furthermore, possibilities to improve the prediction of distortions and residual stress based on CCT behavior are discussed.

Optimization of Regression Models of Experimental Data Using Confirmation Points

NASA Technical Reports Server (NTRS)

Ulbrich, N.

2010-01-01

A new search metric is discussed that may be used to better assess the predictive capability of different math term combinations during the optimization of a regression model of experimental data. The new search metric can be determined for each tested math term combination if the given experimental data set is split into two subsets. The first subset consists of data points that are only used to determine the coefficients of the regression model. The second subset consists of confirmation points that are exclusively used to test the regression model. The new search metric value is assigned after comparing two values that describe the quality of the fit of each subset. The first value is the standard deviation of the PRESS residuals of the data points. The second value is the standard deviation of the response residuals of the confirmation points. The greater of the two values is used as the new search metric value. This choice guarantees that both standard deviations are always less or equal to the value that is used during the optimization. Experimental data from the calibration of a wind tunnel strain-gage balance is used to illustrate the application of the new search metric. The new search metric ultimately generates an optimized regression model that was already tested at regression model independent confirmation points before it is ever used to predict an unknown response from a set of regressors.

Prediction of protein tertiary structure to low resolution: performance for a large and structurally diverse test set.

PubMed

Eyrich, V A; Standley, D M; Friesner, R A

1999-05-14

We report the tertiary structure predictions for 95 proteins ranging in size from 17 to 160 residues starting from known secondary structure. Predictions are obtained from global minimization of an empirical potential function followed by the application of a refined atomic overlap potential. The minimization strategy employed represents a variant of the Monte Carlo plus minimization scheme of Li and Scheraga applied to a reduced model of the protein chain. For all of the cases except beta-proteins larger than 75 residues, a native-like structure, usually 4-6 A root-mean-square deviation from the native, is located. For beta-proteins larger than 75 residues, the energy gap between native-like structures and the lowest energy structures produced in the simulation is large, so that low RMSD structures are not generated starting from an unfolded state. This is attributed to the lack of an explicit hydrogen bond term in the potential function, which we hypothesize is necessary to stabilize large assemblies of beta-strands. Copyright 1999 Academic Press.

Development of variable pathlength UV-vis spectroscopy combined with partial-least-squares regression for wastewater chemical oxygen demand (COD) monitoring.

PubMed

Chen, Baisheng; Wu, Huanan; Li, Sam Fong Yau

2014-03-01

To overcome the challenging task to select an appropriate pathlength for wastewater chemical oxygen demand (COD) monitoring with high accuracy by UV-vis spectroscopy in wastewater treatment process, a variable pathlength approach combined with partial-least squares regression (PLSR) was developed in this study. Two new strategies were proposed to extract relevant information of UV-vis spectral data from variable pathlength measurements. The first strategy was by data fusion with two data fusion levels: low-level data fusion (LLDF) and mid-level data fusion (MLDF). Predictive accuracy was found to improve, indicated by the lower root-mean-square errors of prediction (RMSEP) compared with those obtained for single pathlength measurements. Both fusion levels were found to deliver very robust PLSR models with residual predictive deviations (RPD) greater than 3 (i.e. 3.22 and 3.29, respectively). The second strategy involved calculating the slopes of absorbance against pathlength at each wavelength to generate slope-derived spectra. Without the requirement to select the optimal pathlength, the predictive accuracy (RMSEP) was improved by 20-43% as compared to single pathlength spectroscopy. Comparing to nine-factor models from fusion strategy, the PLSR model from slope-derived spectroscopy was found to be more parsimonious with only five factors and more robust with residual predictive deviation (RPD) of 3.72. It also offered excellent correlation of predicted and measured COD values with R(2) of 0.936. In sum, variable pathlength spectroscopy with the two proposed data analysis strategies proved to be successful in enhancing prediction performance of COD in wastewater and showed high potential to be applied in on-line water quality monitoring. Copyright © 2013 Elsevier B.V. All rights reserved.

Molecular dynamics of bacteriorhodopsin.

PubMed

Lupo, J A; Pachter, R

1997-02-01

A model of bacteriorhodopsin (bR), with a retinal chromophore attached, has been derived for a molecular dynamics simulation. A method for determining atomic coordinates of several ill-defined strands was developed using a structure prediction algorithm based on a sequential Kalman filter technique. The completed structure was minimized using the GROMOS force field. The structure was then heated to 293 K and run for 500 ps at constant temperature. A comparison with the energy-minimized structure showed a slow increase in the all-atom RMS deviation over the first 200 ps, leveling off to approximately 2.4 A relative to the starting structure. The final structure yielded a backbone-atom RMS deviation from the crystallographic structure of 2.8 A. The residue neighbors of the chromophore atoms were followed as a function of time. The set of persistent near-residue neighbors supports the theory that differences in pKa values control access to the Schiff base proton, rather than formation of a counterion complex.

Toward accurate prediction of pKa values for internal protein residues: the importance of conformational relaxation and desolvation energy.

PubMed

Wallace, Jason A; Wang, Yuhang; Shi, Chuanyin; Pastoor, Kevin J; Nguyen, Bao-Linh; Xia, Kai; Shen, Jana K

2011-12-01

Proton uptake or release controls many important biological processes, such as energy transduction, virus replication, and catalysis. Accurate pK(a) prediction informs about proton pathways, thereby revealing detailed acid-base mechanisms. Physics-based methods in the framework of molecular dynamics simulations not only offer pK(a) predictions but also inform about the physical origins of pK(a) shifts and provide details of ionization-induced conformational relaxation and large-scale transitions. One such method is the recently developed continuous constant pH molecular dynamics (CPHMD) method, which has been shown to be an accurate and robust pK(a) prediction tool for naturally occurring titratable residues. To further examine the accuracy and limitations of CPHMD, we blindly predicted the pK(a) values for 87 titratable residues introduced in various hydrophobic regions of staphylococcal nuclease and variants. The predictions gave a root-mean-square deviation of 1.69 pK units from experiment, and there were only two pK(a)'s with errors greater than 3.5 pK units. Analysis of the conformational fluctuation of titrating side-chains in the context of the errors of calculated pK(a) values indicate that explicit treatment of conformational flexibility and the associated dielectric relaxation gives CPHMD a distinct advantage. Analysis of the sources of errors suggests that more accurate pK(a) predictions can be obtained for the most deeply buried residues by improving the accuracy in calculating desolvation energies. Furthermore, it is found that the generalized Born implicit-solvent model underlying the current CPHMD implementation slightly distorts the local conformational environment such that the inclusion of an explicit-solvent representation may offer improvement of accuracy. Copyright © 2011 Wiley-Liss, Inc.

Interpretation and estimation for dynamic mobility of chlorpyrifos in soils containing different organic matters.

PubMed

Hwang, Jeong-In; Lee, Sung-Eun; Kim, Jang-Eok

2015-12-01

The adsorption and removal behaviors of the organophosphate insecticide chlorpyrifos in two soils (AS and GW soils) with different organic matter contents were investigated to predict the dynamic residues in the soil environment. The adsorption test showed that the chlorpyrifos adsorptive power for the AS soil containing high organic matter content was greater than that for the GW soil. The extent of the time-dependent removal of chlorpyrifos in the tested soils was not significantly different except at 90 days after the treatment. The availability of a chemical-specific residue model developed in this study was statistically assessed to estimate the chlorpyrifos residue in soil solutions that could be absorbed into plants. The values modeled using the soil experimental data were satisfactory, having a mean deviation of 32% from the measured data. The correlation between the modeled and measured data was acceptable, with mean coefficients of correlation (R(2)) of 0.89. Furthermore, the average of the residual error was low at 0.43, which corresponded to a mean factor of -1.9. The developed model could be used as a critical tool to predict the subsequent plant uptake of chlorpyrifos.

POOL server: machine learning application for functional site prediction in proteins.

PubMed

Somarowthu, Srinivas; Ondrechen, Mary Jo

2012-08-01

We present an automated web server for partial order optimum likelihood (POOL), a machine learning application that combines computed electrostatic and geometric information for high-performance prediction of catalytic residues from 3D structures. Input features consist of THEMATICS electrostatics data and pocket information from ConCavity. THEMATICS measures deviation from typical, sigmoidal titration behavior to identify functionally important residues and ConCavity identifies binding pockets by analyzing the surface geometry of protein structures. Both THEMATICS and ConCavity (structure only) do not require the query protein to have any sequence or structure similarity to other proteins. Hence, POOL is applicable to proteins with novel folds and engineered proteins. As an additional option for cases where sequence homologues are available, users can include evolutionary information from INTREPID for enhanced accuracy in site prediction. The web site is free and open to all users with no login requirements at http://www.pool.neu.edu. m.ondrechen@neu.edu Supplementary data are available at Bioinformatics online.

Single-Station Sigma for the Iranian Strong Motion Stations

NASA Astrophysics Data System (ADS)

Zafarani, H.; Soghrat, M. R.

2017-11-01

In development of ground motion prediction equations (GMPEs), the residuals are assumed to have a log-normal distribution with a zero mean and a standard deviation, designated as sigma. Sigma has significant effect on evaluation of seismic hazard for designing important infrastructures such as nuclear power plants and dams. Both aleatory and epistemic uncertainties are involved in the sigma parameter. However, ground-motion observations over long time periods are not available at specific sites and the GMPEs have been derived using observed data from multiple sites for a small number of well-recorded earthquakes. Therefore, sigma is dominantly related to the statistics of the spatial variability of ground motion instead of temporal variability at a single point (ergodic assumption). The main purpose of this study is to reduce the variability of the residuals so as to handle it as epistemic uncertainty. In this regard, it is tried to partially apply the non-ergodic assumption by removing repeatable site effects from total variability of six GMPEs driven from the local, Europe-Middle East and worldwide data. For this purpose, we used 1837 acceleration time histories from 374 shallow earthquakes with moment magnitudes ranging from M w 4.0 to 7.3 recorded at 370 stations with at least two recordings per station. According to estimated single-station sigma for the Iranian strong motion stations, the ratio of event-corrected single-station standard deviation ( Φ ss) to within-event standard deviation ( Φ) is about 0.75. In other words, removing the ergodic assumption on site response resulted in 25% reduction of the within-event standard deviation that reduced the total standard deviation by about 15%.

Inter-technique validation of tropospheric slant total delays

NASA Astrophysics Data System (ADS)

Kačmařík, Michal; Douša, Jan; Dick, Galina; Zus, Florian; Brenot, Hugues; Möller, Gregor; Pottiaux, Eric; Kapłon, Jan; Hordyniec, Paweł; Václavovic, Pavel; Morel, Laurent

2017-06-01

An extensive validation of line-of-sight tropospheric slant total delays (STD) from Global Navigation Satellite Systems (GNSS), ray tracing in numerical weather prediction model (NWM) fields and microwave water vapour radiometer (WVR) is presented. Ten GNSS reference stations, including collocated sites, and almost 2 months of data from 2013, including severe weather events were used for comparison. Seven institutions delivered their STDs based on GNSS observations processed using 5 software programs and 11 strategies enabling to compare rather different solutions and to assess the impact of several aspects of the processing strategy. STDs from NWM ray tracing came from three institutions using three different NWMs and ray-tracing software. Inter-techniques evaluations demonstrated a good mutual agreement of various GNSS STD solutions compared to NWM and WVR STDs. The mean bias among GNSS solutions not considering post-fit residuals in STDs was -0.6 mm for STDs scaled in the zenith direction and the mean standard deviation was 3.7 mm. Standard deviations of comparisons between GNSS and NWM ray-tracing solutions were typically 10 mm ± 2 mm (scaled in the zenith direction), depending on the NWM model and the GNSS station. Comparing GNSS versus WVR STDs reached standard deviations of 12 mm ± 2 mm also scaled in the zenith direction. Impacts of raw GNSS post-fit residuals and cleaned residuals on optimal reconstructing of GNSS STDs were evaluated at inter-technique comparison and for GNSS at collocated sites. The use of raw post-fit residuals is not generally recommended as they might contain strong systematic effects, as demonstrated in the case of station LDB0. Simplified STDs reconstructed only from estimated GNSS tropospheric parameters, i.e. without applying post-fit residuals, performed the best in all the comparisons; however, it obviously missed part of tropospheric signals due to non-linear temporal and spatial variations in the troposphere. Although the post-fit residuals cleaned of visible systematic errors generally showed a slightly worse performance, they contained significant tropospheric signal on top of the simplified model. They are thus recommended for the reconstruction of STDs, particularly during high variability in the troposphere. Cleaned residuals also showed a stable performance during ordinary days while containing promising information about the troposphere at low-elevation angles.

High-Throughput Analytical Techniques for Determination of Residues of 653 Multiclass Pesticides and Chemical Pollutants in Tea, Part VI: Study of the Degradation of 271 Pesticide Residues in Aged Oolong Tea by Gas Chromatography-Tandem Mass Spectrometry and Its Application in Predicting the Residue Concentrations of Target Pesticides.

PubMed

Chang, Qiao-Ying; Pang, Guo-Fang; Fan, Chun-Lin; Chen, Hui; Wang, Zhi-Bin

2016-07-01

The degradation rate of 271 pesticide residues in aged Oolong tea at two spray concentrations, named a and b (a < b), were monitored for 120 days using GC-tandem MS (GC-MS/MS). To research the degradation trends and establish regression equations, determination days were plotted as horizontal ordinates and the residue concentrations of pesticide were plotted as vertical ordinates. Here, we consider the degradation equations of 271 pesticides over 40 and 120 days, summarize the degradation rates in six aspects (A-F), and discuss the degradation trends of the 271 pesticides in aged Oolong tea in detail. The results indicate that >70% of the determined pesticides coincide with the degradation regularity of trends A, B, and E, i.e., the concentration of pesticide will decrease within 4 months. Next, 20 representative pesticides were selected for further study at higher spray concentrations, named c and d (d > c > b > a), in aged Oolong tea over another 90 days. The determination days were plotted on the x-axis, and the differences between each determined result and first-time-determined value of target pesticides were plotted on the y-axis. The logarithmic function was obtained by fitting the 90-day determination results, allowing the degradation value of a target pesticide on a specific day to be calculated. These logarithmic functions at d concentration were applied to predict the residue concentrations of pesticides at c concentration. Results revealed that 70% of the 20 pesticides had the lower deviation ratios of predicted and measured results.

A machine learning approach for predicting methionine oxidation sites.

PubMed

Aledo, Juan C; Cantón, Francisco R; Veredas, Francisco J

2017-09-29

The oxidation of protein-bound methionine to form methionine sulfoxide, has traditionally been regarded as an oxidative damage. However, recent evidences support the view of this reversible reaction as a regulatory post-translational modification. The perception that methionine sulfoxidation may provide a mechanism to the redox regulation of a wide range of cellular processes, has stimulated some proteomic studies. However, these experimental approaches are expensive and time-consuming. Therefore, computational methods designed to predict methionine oxidation sites are an attractive alternative. As a first approach to this matter, we have developed models based on random forests, support vector machines and neural networks, aimed at accurate prediction of sites of methionine oxidation. Starting from published proteomic data regarding oxidized methionines, we created a hand-curated dataset formed by 113 unique polypeptides of known structure, containing 975 methionyl residues, 122 of which were oxidation-prone (positive dataset) and 853 were oxidation-resistant (negative dataset). We use a machine learning approach to generate predictive models from these datasets. Among the multiple features used in the classification task, some of them contributed substantially to the performance of the predictive models. Thus, (i) the solvent accessible area of the methionine residue, (ii) the number of residues between the analyzed methionine and the next methionine found towards the N-terminus and (iii) the spatial distance between the atom of sulfur from the analyzed methionine and the closest aromatic residue, were among the most relevant features. Compared to the other classifiers we also evaluated, random forests provided the best performance, with accuracy, sensitivity and specificity of 0.7468±0.0567, 0.6817±0.0982 and 0.7557±0.0721, respectively (mean ± standard deviation). We present the first predictive models aimed to computationally detect methionine sites that may become oxidized in vivo in response to oxidative signals. These models provide insights into the structural context in which a methionine residue become either oxidation-resistant or oxidation-prone. Furthermore, these models should be useful in prioritizing methinonyl residues for further studies to determine their potential as regulatory post-translational modification sites.

Active Site Detection by Spatial Conformity and Electrostatic Analysis—Unravelling a Proteolytic Function in Shrimp Alkaline Phosphatase

PubMed Central

Chakraborty, Sandeep; Minda, Renu; Salaye, Lipika; Bhattacharjee, Swapan K.; Rao, Basuthkar J.

2011-01-01

Computational methods are increasingly gaining importance as an aid in identifying active sites. Mostly these methods tend to have structural information that supplement sequence conservation based analyses. Development of tools that compute electrostatic potentials has further improved our ability to better characterize the active site residues in proteins. We have described a computational methodology for detecting active sites based on structural and electrostatic conformity - C ata L ytic A ctive S ite P rediction (CLASP). In our pipelined model, physical 3D signature of any particular enzymatic function as defined by its active sites is used to obtain spatially congruent matches. While previous work has revealed that catalytic residues have large pKa deviations from standard values, we show that for a given enzymatic activity, electrostatic potential difference (PD) between analogous residue pairs in an active site taken from different proteins of the same family are similar. False positives in spatially congruent matches are further pruned by PD analysis where cognate pairs with large deviations are rejected. We first present the results of active site prediction by CLASP for two enzymatic activities - β-lactamases and serine proteases, two of the most extensively investigated enzymes. The results of CLASP analysis on motifs extracted from Catalytic Site Atlas (CSA) are also presented in order to demonstrate its ability to accurately classify any protein, putative or otherwise, with known structure. The source code and database is made available at www.sanchak.com/clasp/. Subsequently, we probed alkaline phosphatases (AP), one of the well known promiscuous enzymes, for additional activities. Such a search has led us to predict a hitherto unknown function of shrimp alkaline phosphatase (SAP), where the protein acts as a protease. Finally, we present experimental evidence of the prediction by CLASP by showing that SAP indeed has protease activity in vitro. PMID:22174814

Detection of novel coupled mutations in the katG gene (His276Met, Gln295His and Ser315Thr) in a multidrug-resistant Mycobacterium tuberculosis strain from Chennai, India, and insight into the molecular mechanism of isoniazid resistance using structural bioinformatics approaches.

PubMed

Ramasubban, Gayathri; Therese, Kulandai Lily; Vetrivel, Umashankar; Sivashanmugam, Muthukumaran; Rajan, Parvathy; Sridhar, R; Madhavan, Hajib N; Meenakshi, N

2011-04-01

This study reports on the structural basis of drug resistance targeting the katG gene in a multidrug-resistant Mycobacterium tuberculosis (MDR-TB) strain with two novel mutations (His276Met and Gln295His) in addition to the most commonly reported mutation (Ser315Thr). A structural bioinformatics approach was used to predict the structure of the mutant KatG enzyme (MT). Subsequent molecular dynamics and docking studies were performed to explain the mechanism of isoniazid (INH) resistance. The results show significant conformational changes in the structure of MT leading to a change in INH binding residues at the active site, with a significant increase in the inhibition constant (Ki) of 5.67 μm in the mutant KatG-isoniazid complex (MT-INH) compared with the wild-type KatG-isoniazid complex (WT-INH). In the case of molecular dynamics studies, root mean square deviation (RMSD) analysis of the protein backbone in simulated biological conditions revealed an unstable trajectory with higher deviations in MT throughout the simulation process (1 ns). Moreover, root mean square fluctuation (RMSF) analysis revealed an overall increase in residual fluctuations in MT compared with the wild-type KatG enzyme (WT), whilst the INH binding residues of MT showed a decreased fluctuation that can be observed as peak deviations. Hence, the present study suggests that His276Met, Gln295His and Ser315Thr mutations targeting the katG gene result in decreased stability and flexibility of the protein at INH binding residues leading to impaired enzyme function. Copyright © 2010 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved.

Botulinum toxin type A as treatment of partially accommodative esotropia.

PubMed

Flores-Reyes, E M; Castillo-López, M G; Toledo-Silva, R; Vargas-Ortega, J; Murillo-Correa, C E; Aguilar-Ruiz, A

2016-03-01

To determine the effectiveness of a botulinum toxin type A injection in both medial rectus muscles in patients with partially accommodative esotropia. Residual deviation and stability of strabismus were evaluated at 18 months follow up. A prospective, analytical, quasi-experimental study was conducted on a cohort of 21 patients who underwent total cycloplegic refraction and with a residual deviation of at least 14 DP. A botulinum toxin type A dose of 5 IU was injected into each medial rectus muscle for a residual deviation greater than 18 DP, with a dose of 2.5 IU being used for a deviation between 14 and 18 DP. Multivariate logistic regression analyses were performed to relate residual deviation to variables recorded as potential predictors. A total of 21 patients were included, 33.3% (n=7) males and 66.6% (n=14) females. Mean visual acuity was -.28±.25 logMAR for right eye (range 0 to -1) and -.42±.31 logMAR for left eye (range 0 to -1.3). Mean angle of residual deviation before application of botulinum toxin was 40.95±8.6DP without spectacles correction, and 22.3±7.99 DP with full cycloplegic refraction. Adverse effects were ptosis in 14.2% (n=3), diplopia 23.8% (n=5), and vertical deviation in 33% (n=7). One patient had a poor outcome, therefore required surgical treatment. At one year follow up, 85.71% of patients showed good results with esotropia of 12 DP or less, dropping to 71.43% at 18 months of follow up. Botulinum toxin type A is an effective long-term treatment with a good response in 71.43% of patients. No predictors of good response were demonstrated. Copyright © 2015 Sociedad Española de Oftalmología. Published by Elsevier España, S.L.U. All rights reserved.

INDIVIDUALIZED FETAL GROWTH ASSESSMENT: CRITICAL EVALUATION OF KEY CONCEPTS IN THE SPECIFICATION OF THIRD TRIMESTER GROWTH TRAJECTORIES

PubMed Central

Deter, Russell L.; Lee, Wesley; Yeo, Lami; Romero, Roberto

2012-01-01

Objectives To characterize 2nd and 3rd trimester fetal growth using Individualized Growth Assessment in a large cohort of fetuses with normal growth outcomes. Methods A prospective longitudinal study of 119 pregnancies was carried out from 18 weeks, MA, to delivery. Measurements of eleven fetal growth parameters were obtained from 3D scans at 3–4 week intervals. Regression analyses were used to determine Start Points [SP] and Rossavik model [P = c (t) k + st] coefficients c, k and s for each parameter in each fetus. Second trimester growth model specification functions were re-established. These functions were used to generate individual growth models and determine predicted s and s-residual [s = pred s + s-resid] values. Actual measurements were compared to predicted growth trajectories obtained from the growth models and Percent Deviations [% Dev = {{actual − predicted}/predicted} × 100] calculated. Age-specific reference standards for this statistic were defined using 2-level statistical modeling for the nine directly measured parameters and estimated weight. Results Rossavik models fit the data for all parameters very well [R2: 99%], with SP’s and k values similar to those found in a much smaller cohort. The c values were strongly related to the 2nd trimester slope [R2: 97%] as was predicted s to estimated c [R2: 95%]. The latter was negative for skeletal parameters and positive for soft tissue parameters. The s-residuals were unrelated to estimated c’s [R2: 0%], and had mean values of zero. Rossavik models predicted 3rd trimester growth with systematic errors close to 0% and random errors [95% range] of 5.7 – 10.9% and 20.0 – 24.3% for one and three dimensional parameters, respectively. Moderate changes in age-specific variability were seen in the 3rd trimester.. Conclusions IGA procedures for evaluating 2nd and 3rd trimester growth are now established based on a large cohort [4–6 fold larger than those used previously], thus permitting more reliable growth assessment with each fetus acting as its own control. New, more rigorously defined, age-specific standards for the evaluation of 3rd trimester growth deviations are now available for 10 anatomical parameters. Our results are also consistent with the predicted s and s-residual being representatives of growth controllers operating through the insulin-like growth factor [IGF] axis. PMID:23962305

Empirical Corrections to Nutation Amplitudes and Precession Computed from a Global VLBI Solution

NASA Astrophysics Data System (ADS)

Schuh, H.; Ferrandiz, J. M.; Belda-Palazón, S.; Heinkelmann, R.; Karbon, M.; Nilsson, T.

2017-12-01

The IAU2000A nutation and IAU2006 precession models were adopted to provide accurate estimations and predictions of the Celestial Intermediate Pole (CIP). However, they are not fully accurate and VLBI (Very Long Baseline Interferometry) observations show that the CIP deviates from the position resulting from the application of the IAU2006/2000A model. Currently, those deviations or offsets of the CIP (Celestial Pole Offsets - CPO), can only be obtained by the VLBI technique. The accuracy of the order of 0.1 milliseconds of arc (mas) allows to compare the observed nutation with theoretical prediction model for a rigid Earth and constrain geophysical parameters describing the Earth's interior. In this study, we empirically evaluate the consistency, systematics and deviations of the IAU 2006/2000A precession-nutation model using several CPO time series derived from the global analysis of VLBI sessions. The final objective is the reassessment of the precession offset and rate, and the amplitudes of the principal terms of nutation, trying to empirically improve the conventional values derived from the precession/nutation theories. The statistical analysis of the residuals after re-fitting the main nutation terms demonstrates that our empirical corrections attain an error reduction by almost 15 micro arc seconds.

The natural abundance of 13C with different agricultural management by NIRS with fibre optic probe technology.

PubMed

Fuentes, Mariela; González-Martín, Inmaculada; Hernández-Hierro, Jose Miguel; Hidalgo, Claudia; Govaerts, Bram; Etchevers, Jorge; Sayre, Ken D; Dendooven, Luc

2009-06-30

In the present study the natural abundance of (13)C is quantified in agricultural soils in Mexico which have been submitted to different agronomic practices, zero and conventional tillage, retention of crop residues (with and without) and rotation of crops (wheat and maize) for 17 years, which have influenced the physical, chemical and biological characteristics of the soil. The natural abundance of C13 is quantified by near infrared spectra (NIRS) with a remote reflectance fibre optic probe, applying the probe directly to the soil samples. Discriminate partial least squares analysis of the near infrared spectra allowed to classify soils with and without residues, regardless of the type of tillage or rotation systems used with a prediction rate of 90% in the internal validation and 94% in the external validation. The NIRS calibration model using a modified partial least squares regression allowed to determine the delta(13)C in soils with or without residues, with multiple correlation coefficients 0.81 and standard error prediction 0.5 per thousand in soils with residues and 0.92 and 0.2 per thousand in soils without residues. The ratio performance deviation for the quantification of delta(13)C in soil was 2.5 in soil with residues and 3.8 without residues. This indicated that the model was adequate to determine the delta(13)C of unknown soils in the -16.2 per thousand to -20.4 per thousand range. The development of the NIR calibration permits analytic determinations of the values of delta(13)C in unknown agricultural soils in less time, employing a non-destructive method, by the application of the fibre optic probe of remote reflectance to the soil sample.

Methodology for the development of normative data for Spanish-speaking pediatric populations.

PubMed

Rivera, D; Arango-Lasprilla, J C

2017-01-01

To describe the methodology utilized to calculate reliability and the generation of norms for 10 neuropsychological tests for children in Spanish-speaking countries. The study sample consisted of over 4,373 healthy children from nine countries in Latin America (Chile, Cuba, Ecuador, Guatemala, Honduras, Mexico, Paraguay, Peru, and Puerto Rico) and Spain. Inclusion criteria for all countries were to have between 6 to 17 years of age, an Intelligence Quotient of≥80 on the Test of Non-Verbal Intelligence (TONI-2), and score of <19 on the Children's Depression Inventory. Participants completed 10 neuropsychological tests. Reliability and norms were calculated for all tests. Test-retest analysis showed excellent or good- reliability on all tests (r's>0.55; p's<0.001) except M-WCST perseverative errors whose coefficient magnitude was fair. All scores were normed using multiple linear regressions and standard deviations of residual values. Age, age2, sex, and mean level of parental education (MLPE) were included as predictors in the models by country. The non-significant variables (p > 0.05) were removed and the analysis were run again. This is the largest Spanish-speaking children and adolescents normative study in the world. For the generation of normative data, the method based on linear regression models and the standard deviation of residual values was used. This method allows determination of the specific variables that predict test scores, helps identify and control for collinearity of predictive variables, and generates continuous and more reliable norms than those of traditional methods.

Determination of total phenolic compounds in compost by infrared spectroscopy.

PubMed

Cascant, M M; Sisouane, M; Tahiri, S; Krati, M El; Cervera, M L; Garrigues, S; de la Guardia, M

2016-06-01

Middle and near infrared (MIR and NIR) were applied to determine the total phenolic compounds (TPC) content in compost samples based on models built by using partial least squares (PLS) regression. The multiplicative scatter correction, standard normal variate and first derivative were employed as spectra pretreatment, and the number of latent variable were optimized by leave-one-out cross-validation. The performance of PLS-ATR-MIR and PLS-DR-NIR models was evaluated according to root mean square error of cross validation and prediction (RMSECV and RMSEP), the coefficient of determination for prediction (Rpred(2)) and residual predictive deviation (RPD) being obtained for this latter values of 5.83 and 8.26 for MIR and NIR, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

Capillary pressure - saturation relations for supercritical CO2 and brine: Implications for capillary/residual trapping in carbonate reservoirs during geologic carbon sequestration

NASA Astrophysics Data System (ADS)

Wang, S.; Tokunaga, T. K.

2014-12-01

In geologic carbon sequestration (GCS), data on capillary pressure (Pc) - saturation (Sw) relations are routinely needed to appraise reservoir processes. Capillarity and its hysteresis have been often experimentally studied in oil-water, gas-water and three phase gas-oil-water systems, but fewer works have been reported on scCO2-water under in-situ reservoir conditions. Here, Pc-Sw relations of supercritical (sc) CO2 displacing brine, and brine rewetting the porous medium to trap scCO2 were studied to understand CO2 transport and trapping behavior in carbonate reservoirs under representative reservoir conditions. High-quality drainage and imbibition (and associated capillary pressure hysteresis) curves were measured under elevated temperature and pressure (45 ºC, 8.5 and 12 MPa) for scCO2-brine as well as at room temperature and pressure (23 ºC, 0.1 MPa) for air-brine in unconsolidated limestone and dolomite sand columns using newly developed semi-automated multistep outflow-inflow porous plate apparatus. Drainage and imbibition curves for scCO2-brine deviated from the universal scaling curves for hydrophilic interactions (with greater deviation under higher pressure) and shifted to lower Pc than predicted based on interfacial tension (IFT) changes. Augmented scaling incorporating differences in IFT and contact angle improved the scaling results but the scaled curves still did not converge onto the universal curves. Equilibrium residual trapping of the nonwetting phase was determined at Pc =0 during imbibition. The capillary-trapped amounts of scCO2 were significantly larger than for air. It is concluded that the deviations from the universal capillary scaling curves are caused by scCO2-induced wettability alteration, given the fact that pore geometry remained constant and IFT is well constrained. In-situ wettability alteration by reactive scCO2 is of critical importance and must be accounted for to achieve reliable predictions of CO2 behavior in GCS reservoirs.

Packing of sidechains in low-resolution models for proteins.

PubMed

Keskin, O; Bahar, I

1998-01-01

Atomic level rotamer libraries for sidechains in proteins have been proposed by several groups. Conformations of side groups in coarse-grained models, on the other hand, have not yet been analyzed, although low resolution approaches are the only efficient way to explore global structural features. A residue-specific backbone-dependent library for sidechain isomers, compatible with a coarse-grained model, is proposed. The isomeric states are utilized in packing sidechains of known backbone structures. Sidechain positions are predicted with a root-mean-square deviation (r.m.s.d.) of 2.40 A with respect to crystal structure for 50 test proteins. The rmsd for core residues is 1.60 A and decreases to 1.35 A when conformational correlations and directional effects in inter-residue couplings are considered. An automated method for assigning sidechain positions in coarse-grained model proteins is proposed and made available on the internet; the method accounts satisfactorily for sidechain packing, particularly in the core.

Fast and simultaneous prediction of animal feed nutritive values using near infrared reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Samadi; Wajizah, S.; Munawar, A. A.

2018-02-01

Feed plays an important factor in animal production. The purpose of this study is to apply NIRS method in determining feed values. NIRS spectra data were acquired for feed samples in wavelength range of 1000 - 2500 nm with 32 scans and 0.2 nm wavelength. Spectral data were corrected by de-trending (DT) and standard normal variate (SNV) methods. Prediction of in vitro dry matter digestibility (IVDMD) and in vitro organic matter digestibility (IVOMD) were established as model by using principal component regression (PCR) and validated using leave one out cross validation (LOOCV). Prediction performance was quantified using coefficient correlation (r) and residual predictive deviation (RPD) index. The results showed that IVDMD and IVOMD can be predicted by using SNV spectra data with r and RPD index: 0.93 and 2.78 for IVDMD ; 0.90 and 2.35 for IVOMD respectively. In conclusion, NIRS technique appears feasible to predict animal feed nutritive values.

Microstructural Modeling of Brittle Materials for Enhanced Performance and Reliability.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Teague, Melissa Christine; Teague, Melissa Christine; Rodgers, Theron

Brittle failure is often influenced by difficult to measure and variable microstructure-scale stresses. Recent advances in photoluminescence spectroscopy (PLS), including improved confocal laser measurement and rapid spectroscopic data collection have established the potential to map stresses with microscale spatial resolution (%3C2 microns). Advanced PLS was successfully used to investigate both residual and externally applied stresses in polycrystalline alumina at the microstructure scale. The measured average stresses matched those estimated from beam theory to within one standard deviation, validating the technique. Modeling the residual stresses within the microstructure produced general agreement in comparison with the experimentally measured results. Microstructure scale modelingmore » is primed to take advantage of advanced PLS to enable its refinement and validation, eventually enabling microstructure modeling to become a predictive tool for brittle materials.« less

Pushing the size limit of de novo structure ensemble prediction guided by sparse SDSL-EPR restraints to 200 residues: The monomeric and homodimeric forms of BAX

PubMed Central

Fischer, Axel W.; Bordignon, Enrica; Bleicken, Stephanie; García-Sáez, Ana J.; Jeschke, Gunnar; Meiler, Jens

2016-01-01

Structure determination remains a challenge for many biologically important proteins. In particular, proteins that adopt multiple conformations often evade crystallization in all biologically relevant states. Although computational de novo protein folding approaches often sample biologically relevant conformations, the selection of the most accurate model for different functional states remains a formidable challenge, in particular, for proteins with more than about 150 residues. Electron paramagnetic resonance (EPR) spectroscopy can obtain limited structural information for proteins in well-defined biological states and thereby assist in selecting biologically relevant conformations. The present study demonstrates that de novo folding methods are able to accurately sample the folds of 192-residue long soluble monomeric Bcl-2-associated X protein (BAX). The tertiary structures of the monomeric and homodimeric forms of BAX were predicted using the primary structure as well as 25 and 11 EPR distance restraints, respectively. The predicted models were subsequently compared to respective NMR/X-ray structures of BAX. EPR restraints improve the protein-size normalized root-mean-square-deviation (RMSD100) of the most accurate models with respect to the NMR/crystal structure from 5.9 Å to 3.9 Å and from 5.7 Å to 3.3 Å, respectively. Additionally, the model discrimination is improved, which is demonstrated by an improvement of the enrichment from 5% to 15% and from 13% to 21%, respectively. PMID:27129417

Uncertainty, variability, and earthquake physics in ground‐motion prediction equations

USGS Publications Warehouse

Baltay, Annemarie S.; Hanks, Thomas C.; Abrahamson, Norm A.

2017-01-01

Residuals between ground‐motion data and ground‐motion prediction equations (GMPEs) can be decomposed into terms representing earthquake source, path, and site effects. These terms can be cast in terms of repeatable (epistemic) residuals and the random (aleatory) components. Identifying the repeatable residuals leads to a GMPE with reduced uncertainty for a specific source, site, or path location, which in turn can yield a lower hazard level at small probabilities of exceedance. We illustrate a schematic framework for this residual partitioning with a dataset from the ANZA network, which straddles the central San Jacinto fault in southern California. The dataset consists of more than 3200 1.15≤M≤3 earthquakes and their peak ground accelerations (PGAs), recorded at close distances (R≤20  km). We construct a small‐magnitude GMPE for these PGA data, incorporating VS30 site conditions and geometrical spreading. Identification and removal of the repeatable source, path, and site terms yield an overall reduction in the standard deviation from 0.97 (in ln units) to 0.44, for a nonergodic assumption, that is, for a single‐source location, single site, and single path. We give examples of relationships between independent seismological observables and the repeatable terms. We find a correlation between location‐based source terms and stress drops in the San Jacinto fault zone region; an explanation of the site term as a function of kappa, the near‐site attenuation parameter; and a suggestion that the path component can be related directly to elastic structure. These correlations allow the repeatable source location, site, and path terms to be determined a priori using independent geophysical relationships. Those terms could be incorporated into location‐specific GMPEs for more accurate and precise ground‐motion prediction.

Parameterization models for pesticide exposure via crop consumption.

PubMed

Fantke, Peter; Wieland, Peter; Juraske, Ronnie; Shaddick, Gavin; Itoiz, Eva Sevigné; Friedrich, Rainer; Jolliet, Olivier

2012-12-04

An approach for estimating human exposure to pesticides via consumption of six important food crops is presented that can be used to extend multimedia models applied in health risk and life cycle impact assessment. We first assessed the variation of model output (pesticide residues per kg applied) as a function of model input variables (substance, crop, and environmental properties) including their possible correlations using matrix algebra. We identified five key parameters responsible for between 80% and 93% of the variation in pesticide residues, namely time between substance application and crop harvest, degradation half-lives in crops and on crop surfaces, overall residence times in soil, and substance molecular weight. Partition coefficients also play an important role for fruit trees and tomato (Kow), potato (Koc), and lettuce (Kaw, Kow). Focusing on these parameters, we develop crop-specific models by parametrizing a complex fate and exposure assessment framework. The parametric models thereby reflect the framework's physical and chemical mechanisms and predict pesticide residues in harvest using linear combinations of crop, crop surface, and soil compartments. Parametric model results correspond well with results from the complex framework for 1540 substance-crop combinations with total deviations between a factor 4 (potato) and a factor 66 (lettuce). Predicted residues also correspond well with experimental data previously used to evaluate the complex framework. Pesticide mass in harvest can finally be combined with reduction factors accounting for food processing to estimate human exposure from crop consumption. All parametric models can be easily implemented into existing assessment frameworks.

Quantitative features in the computed tomography of healthy lungs.

PubMed Central

Fromson, B H; Denison, D M

1988-01-01

This study set out to determine whether quantitative features of lung computed tomography scans could be identified that would lead to a tightly defined normal range for use in assessing patients. Fourteen normal subjects with apparently healthy lungs were studied. A technique was developed for rapid and automatic extraction of lung field data from the computed tomography scans. The Hounsfield unit histograms were constructed and, when normalised for predicted lung volumes, shown to be consistent in shape for all the subjects. A three dimensional presentation of the data in the form of a "net plot" was devised, and from this a logarithmic relationship between the area of each lung slice and its mean density was derived (r = 0.9, n = 545, p less than 0.0001). The residual density, calculated as the difference between measured density and density predicted from the relationship with area, was shown to be normally distributed with a mean of 0 and a standard deviation of 25 Hounsfield units (chi 2 test: p less than 0.05). A presentation combining this residual density with the net plot is described. PMID:3353883

Development of a hybrid proximal sensing method for rapid identification of petroleum contaminated soils.

PubMed

Chakraborty, Somsubhra; Weindorf, David C; Li, Bin; Ali Aldabaa, Abdalsamad Abdalsatar; Ghosh, Rakesh Kumar; Paul, Sathi; Nasim Ali, Md

2015-05-01

Using 108 petroleum contaminated soil samples, this pilot study proposed a new analytical approach of combining visible near-infrared diffuse reflectance spectroscopy (VisNIR DRS) and portable X-ray fluorescence spectrometry (PXRF) for rapid and improved quantification of soil petroleum contamination. Results indicated that an advanced fused model where VisNIR DRS spectra-based penalized spline regression (PSR) was used to predict total petroleum hydrocarbon followed by PXRF elemental data-based random forest regression was used to model the PSR residuals, it outperformed (R(2)=0.78, residual prediction deviation (RPD)=2.19) all other models tested, even producing better generalization than using VisNIR DRS alone (RPD's of 1.64, 1.86, and 1.96 for random forest, penalized spline regression, and partial least squares regression, respectively). Additionally, unsupervised principal component analysis using the PXRF+VisNIR DRS system qualitatively separated contaminated soils from control samples. Fusion of PXRF elemental data and VisNIR derivative spectra produced an optimized model for total petroleum hydrocarbon quantification in soils. Copyright © 2015 Elsevier B.V. All rights reserved.

Nonlinear structure-composition relationships in the Ge 1-ySn y/Si(100) (y<0.15) system

DOE PAGES

Beeler, R.; Roucka, R.; Chizmeshya, A. V. G.; ...

2011-07-26

The compositional dependence of the cubic lattice parameter in Ge 1-ySn y alloys has been revisited. Large 1000-atom supercell ab initio simulations confirm earlier theoretical predictions that indicate a positive quadratic deviation from Vegard's law, albeit with a somewhat smaller bowing coefficient, θ = 0.047 Å, than found from 64-atom cell simulations (θ = 0.063 Å). On the other hand, measurements from an extensive set of alloy samples with compositions y < 0.15 reveal a negative deviation from Vegard's law. The discrepancy with earlier experimental data, which supported the theoretical results, is traced back to an unexpected compositional dependence ofmore » the residual strain after growth on Si substrates. The experimental bowing parameter for the relaxed lattice constant of the alloys is found to be θ = -0.066 Å. Possible reasons for the disagreement between theory and experiment are discussed in detail.« less

Springback effects during single point incremental forming: Optimization of the tool path

NASA Astrophysics Data System (ADS)

Giraud-Moreau, Laurence; Belchior, Jérémy; Lafon, Pascal; Lotoing, Lionel; Cherouat, Abel; Courtielle, Eric; Guines, Dominique; Maurine, Patrick

2018-05-01

Incremental sheet forming is an emerging process to manufacture sheet metal parts. This process is more flexible than conventional one and well suited for small batch production or prototyping. During the process, the sheet metal blank is clamped by a blank-holder and a small-size smooth-end hemispherical tool moves along a user-specified path to deform the sheet incrementally. Classical three-axis CNC milling machines, dedicated structure or serial robots can be used to perform the forming operation. Whatever the considered machine, large deviations between the theoretical shape and the real shape can be observed after the part unclamping. These deviations are due to both the lack of stiffness of the machine and residual stresses in the part at the end of the forming stage. In this paper, an optimization strategy of the tool path is proposed in order to minimize the elastic springback induced by residual stresses after unclamping. A finite element model of the SPIF process allowing the shape prediction of the formed part with a good accuracy is defined. This model, based on appropriated assumptions, leads to calculation times which remain compatible with an optimization procedure. The proposed optimization method is based on an iterative correction of the tool path. The efficiency of the method is shown by an improvement of the final shape.

Impact of Nocturnal Low-Level Jets on Near-Surface Turbulence Kinetic Energy

NASA Astrophysics Data System (ADS)

Duarte, Henrique F.; Leclerc, Monique Y.; Zhang, Gengsheng; Durden, David; Kurzeja, Robert; Parker, Matthew; Werth, David

2015-09-01

We report on the role of low-level jets (LLJs) on the modulation of near-surface turbulence in the stable boundary layer, focusing on the behaviour of the transport terms of the turbulence kinetic energy (TKE) budget. We also examine the applicability of Monin-Obukhov similarity theory (MOST) in light of these terms. Using coincident near-surface turbulence and LLJ data collected over a three-month period in South Carolina, USA, we found that turbulence during LLJ periods was typically stronger and more well-developed in comparison with periods without a LLJ. We found a local imbalance in the near-surface TKE budget, in which the imbalance (residual) term was typically positive (i.e., energy gain) and nearly in equilibrium with buoyant consumption. Based on a comparison with previous studies, we assume that this residual term represents mostly pressure transport. We found the behaviour of the residual term to be better delineated in the presence of LLJs. We found shear production to adhere to MOST remarkably well during LLJs, except under very stable conditions. Gain of non-local TKE via pressure transport, likely consisting of large-scale fluctuations, could be the cause of the observed deviation from the MOST -less prediction. The fact that this deviation was observed for periods with well-developed turbulence with an inertial subrange slope close to indicates that such Kolmogorov turbulence is not a sufficient condition to guarantee the applicability of the MOST -less concept, as recently suggested in the literature. The implications of these results are discussed.

Sci-Fri AM: Quality, Safety, and Professional Issues 04: Predicting waiting times in Radiation Oncology using machine learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joseph, Ackeem; Herrera, David; Hijal, Tarek

We describe a method for predicting waiting times in radiation oncology. Machine learning is a powerful predictive modelling tool that benefits from large, potentially complex, datasets. The essence of machine learning is to predict future outcomes by learning from previous experience. The patient waiting experience remains one of the most vexing challenges facing healthcare. Waiting time uncertainty can cause patients, who are already sick and in pain, to worry about when they will receive the care they need. In radiation oncology, patients typically experience three types of waiting: Waiting at home for their treatment plan to be prepared Waiting inmore » the waiting room for daily radiotherapy Waiting in the waiting room to see a physician in consultation or follow-up These waiting periods are difficult for staff to predict and only rough estimates are typically provided, based on personal experience. In the present era of electronic health records, waiting times need not be so uncertain. At our centre, we have incorporated the electronic treatment records of all previously-treated patients into our machine learning model. We found that the Random Forest Regression model provides the best predictions for daily radiotherapy treatment waiting times (type 2). Using this model, we achieved a median residual (actual minus predicted value) of 0.25 minutes and a standard deviation residual of 6.5 minutes. The main features that generated the best fit model (from most to least significant) are: Allocated time, median past duration, fraction number and the number of treatment fields.« less

Visible and Near-Infrared Spectroscopy Analysis of a Polycyclic Aromatic Hydrocarbon in Soils

PubMed Central

Okparanma, Reuben N.; Mouazen, Abdul M.

2013-01-01

Visible and near-infrared (VisNIR) spectroscopy is becoming recognised by soil scientists as a rapid and cost-effective measurement method for hydrocarbons in petroleum-contaminated soils. This study investigated the potential application of VisNIR spectroscopy (350–2500 nm) for the prediction of phenanthrene, a polycyclic aromatic hydrocarbon (PAH), in soils. A total of 150 diesel-contaminated soil samples were used in the investigation. Partial least-squares (PLS) regression analysis with full cross-validation was used to develop models to predict the PAH compound. Results showed that the PAH compound was predicted well with residual prediction deviation of 2.0–2.32, root-mean-square error of prediction of 0.21–0.25 mg kg−1, and coefficient of determination (r 2) of 0.75–0.83. The mechanism of prediction was attributed to covariation of the PAH with clay and soil organic carbon. Overall, the results demonstrated that the methodology may be used for predicting phenanthrene in soils utilizing the interrelationship between clay and soil organic carbon. PMID:24453798

Ranking and validation of spallation models for isotopic production cross sections of heavy residua

NASA Astrophysics Data System (ADS)

Sharma, Sushil K.; Kamys, Bogusław; Goldenbaum, Frank; Filges, Detlef

2017-07-01

The production cross sections of isotopically identified residual nuclei of spallation reactions induced by 136Xe projectiles at 500AMeV on hydrogen target were analyzed in a two-step model. The first stage of the reaction was described by the INCL4.6 model of an intranuclear cascade of nucleon-nucleon and pion-nucleon collisions whereas the second stage was analyzed by means of four different models; ABLA07, GEM2, GEMINI++ and SMM. The quality of the data description was judged quantitatively using two statistical deviation factors; the H-factor and the M-factor. It was found that the present analysis leads to a different ranking of models as compared to that obtained from the qualitative inspection of the data reproduction. The disagreement was caused by sensitivity of the deviation factors to large statistical errors present in some of the data. A new deviation factor, the A factor, was proposed, that is not sensitive to the statistical errors of the cross sections. The quantitative ranking of models performed using the A-factor agreed well with the qualitative analysis of the data. It was concluded that using the deviation factors weighted by statistical errors may lead to erroneous conclusions in the case when the data cover a large range of values. The quality of data reproduction by the theoretical models is discussed. Some systematic deviations of the theoretical predictions from the experimental results are observed.

Comprehensive Analysis of Mandibular Residual Asymmetry after Bilateral Sagittal Split Ramus Osteotomy Correction of Menton Point Deviation

PubMed Central

Lin, Qiuping; Huang, Xiaoqiong; Xu, Yue; Yang, Xiaoping

2016-01-01

Purpose Facial asymmetry often persists even after mandibular deviation corrected by the bilateral sagittal split ramus osteotomy (BSSRO) operation, since the reference facial sagittal plane for the asymmetry analysis is usually set up before the mandibular menton (Me) point correction. Our aim is to develop a predictive and quantitative method to assess the true asymmetry of the mandible after a midline correction performed by a virtual BSSRO, and to verify its availability by evaluation of the post-surgical improvement. Patients and Methods A retrospective cohort study was conducted at the Hospital of Stomatology, Sun Yat-sen University (China) of patients with pure hemi-mandibular elongation (HE) from September 2010 through May 2014. Mandibular models were reconstructed from CBCT images of patients with pre-surgical orthodontic treatment. After mandibular de-rotation and midline alignment with virtual BSSRO, the elongation hemi-mandible was virtually mirrored along the facial sagittal plane. The residual asymmetry, defined as the superimposition and boolean operation of the mirrored elongation side on the normal side, was calculated, including the volumetric differences and the length of transversal and vertical asymmetry discrepancy. For more specific evaluation, both sides of the hemi-mandible were divided into the symphysis and parasymphysis (SP), mandibular body (MB), and mandibular angle (MA) regions. Other clinical variables include deviation of Me point, dental midline and molar relationship. The measurement of volumetric discrepancy between the two sides of post-surgical hemi-mandible were also calculated to verify the availability of virtual surgery. Paired t-tests were computed and the P value was set at .05. Results This study included 45 patients. The volume differences were 407.8±64.8 mm3, 2139.1±72.5 mm3, and 422.5±36.9 mm3; residual average transversal discrepancy, 1.9 mm, 1.0 mm, and 2.2 mm; average vertical discrepancy, 1.1 mm, 2.2 mm, and 2.2 mm (before virtual surgery). The post-surgical volumetric measurement showed no statistical differences between bilateral mandibular regions. Conclusions Mandibular asymmetry persists after Me point correction. A 3D quantification of mandibular residual asymmetry after Me point correction and mandible de-rotation with virtual BSSRO sets up a true reference mirror plane for comprehensive asymmetry assessment of bilateral mandibular structure, thereby providing an accurate guidance for orthognathic surgical planning. PMID:27571364

Comprehensive Analysis of Mandibular Residual Asymmetry after Bilateral Sagittal Split Ramus Osteotomy Correction of Menton Point Deviation.

PubMed

Lin, Han; Zhu, Ping; Lin, Qiuping; Huang, Xiaoqiong; Xu, Yue; Yang, Xiaoping

2016-01-01

Facial asymmetry often persists even after mandibular deviation corrected by the bilateral sagittal split ramus osteotomy (BSSRO) operation, since the reference facial sagittal plane for the asymmetry analysis is usually set up before the mandibular menton (Me) point correction. Our aim is to develop a predictive and quantitative method to assess the true asymmetry of the mandible after a midline correction performed by a virtual BSSRO, and to verify its availability by evaluation of the post-surgical improvement. A retrospective cohort study was conducted at the Hospital of Stomatology, Sun Yat-sen University (China) of patients with pure hemi-mandibular elongation (HE) from September 2010 through May 2014. Mandibular models were reconstructed from CBCT images of patients with pre-surgical orthodontic treatment. After mandibular de-rotation and midline alignment with virtual BSSRO, the elongation hemi-mandible was virtually mirrored along the facial sagittal plane. The residual asymmetry, defined as the superimposition and boolean operation of the mirrored elongation side on the normal side, was calculated, including the volumetric differences and the length of transversal and vertical asymmetry discrepancy. For more specific evaluation, both sides of the hemi-mandible were divided into the symphysis and parasymphysis (SP), mandibular body (MB), and mandibular angle (MA) regions. Other clinical variables include deviation of Me point, dental midline and molar relationship. The measurement of volumetric discrepancy between the two sides of post-surgical hemi-mandible were also calculated to verify the availability of virtual surgery. Paired t-tests were computed and the P value was set at .05. This study included 45 patients. The volume differences were 407.8±64.8 mm3, 2139.1±72.5 mm3, and 422.5±36.9 mm3; residual average transversal discrepancy, 1.9 mm, 1.0 mm, and 2.2 mm; average vertical discrepancy, 1.1 mm, 2.2 mm, and 2.2 mm (before virtual surgery). The post-surgical volumetric measurement showed no statistical differences between bilateral mandibular regions. Mandibular asymmetry persists after Me point correction. A 3D quantification of mandibular residual asymmetry after Me point correction and mandible de-rotation with virtual BSSRO sets up a true reference mirror plane for comprehensive asymmetry assessment of bilateral mandibular structure, thereby providing an accurate guidance for orthognathic surgical planning.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levegruen, Sabine, E-mail: sabine.levegruen@uni-due.de; Poettgen, Christoph; Abu Jawad, Jehad

Purpose: To evaluate megavoltage computed tomography (MVCT)-based image guidance with helical tomotherapy in patients with vertebral tumors by analyzing factors influencing interobserver variability, considered as quality criterion of image guidance. Methods and Materials: Five radiation oncologists retrospectively registered 103 MVCTs in 10 patients to planning kilovoltage CTs by rigid transformations in 4 df. Interobserver variabilities were quantified using the standard deviations (SDs) of the distributions of the correction vector components about the observers' fraction mean. To assess intraobserver variabilities, registrations were repeated after {>=}4 weeks. Residual deviations after setup correction due to uncorrectable rotational errors and elastic deformations were determinedmore » at 3 craniocaudal target positions. To differentiate observer-related variations in minimizing these residual deviations across the 3-dimensional MVCT from image resolution effects, 2-dimensional registrations were performed in 30 single transverse and sagittal MVCT slices. Axial and longitudinal MVCT image resolutions were quantified. For comparison, image resolution of kilovoltage cone-beam CTs (CBCTs) and interobserver variability in registrations of 43 CBCTs were determined. Results: Axial MVCT image resolution is 3.9 lp/cm. Longitudinal MVCT resolution amounts to 6.3 mm, assessed as full-width at half-maximum of thin objects in MVCTs with finest pitch. Longitudinal CBCT resolution is better (full-width at half-maximum, 2.5 mm for CBCTs with 1-mm slices). In MVCT registrations, interobserver variability in the craniocaudal direction (SD 1.23 mm) is significantly larger than in the lateral and ventrodorsal directions (SD 0.84 and 0.91 mm, respectively) and significantly larger compared with CBCT alignments (SD 1.04 mm). Intraobserver variabilities are significantly smaller than corresponding interobserver variabilities (variance ratio [VR] 1.8-3.1). Compared with 3-dimensional registrations, 2-dimensional registrations have significantly smaller interobserver variability in the lateral and ventrodorsal directions (VR 3.8 and 2.8, respectively) but not in the craniocaudal direction (VR 0.75). Conclusion: Tomotherapy image guidance precision is affected by image resolution and residual deviations after setup correction. Eliminating the effect of residual deviations yields small interobserver variabilities with submillimeter precision in the axial plane. In contrast, interobserver variability in the craniocaudal direction is dominated by the poorer longitudinal MVCT image resolution. Residual deviations after image guidance exist and need to be considered when dose gradients ultimately achievable with image guided radiation therapy techniques are analyzed.« less

Megavoltage computed tomography image guidance with helical tomotherapy in patients with vertebral tumors: analysis of factors influencing interobserver variability.

PubMed

Levegrün, Sabine; Pöttgen, Christoph; Jawad, Jehad Abu; Berkovic, Katharina; Hepp, Rodrigo; Stuschke, Martin

2013-02-01

To evaluate megavoltage computed tomography (MVCT)-based image guidance with helical tomotherapy in patients with vertebral tumors by analyzing factors influencing interobserver variability, considered as quality criterion of image guidance. Five radiation oncologists retrospectively registered 103 MVCTs in 10 patients to planning kilovoltage CTs by rigid transformations in 4 df. Interobserver variabilities were quantified using the standard deviations (SDs) of the distributions of the correction vector components about the observers' fraction mean. To assess intraobserver variabilities, registrations were repeated after ≥4 weeks. Residual deviations after setup correction due to uncorrectable rotational errors and elastic deformations were determined at 3 craniocaudal target positions. To differentiate observer-related variations in minimizing these residual deviations across the 3-dimensional MVCT from image resolution effects, 2-dimensional registrations were performed in 30 single transverse and sagittal MVCT slices. Axial and longitudinal MVCT image resolutions were quantified. For comparison, image resolution of kilovoltage cone-beam CTs (CBCTs) and interobserver variability in registrations of 43 CBCTs were determined. Axial MVCT image resolution is 3.9 lp/cm. Longitudinal MVCT resolution amounts to 6.3 mm, assessed as full-width at half-maximum of thin objects in MVCTs with finest pitch. Longitudinal CBCT resolution is better (full-width at half-maximum, 2.5 mm for CBCTs with 1-mm slices). In MVCT registrations, interobserver variability in the craniocaudal direction (SD 1.23 mm) is significantly larger than in the lateral and ventrodorsal directions (SD 0.84 and 0.91 mm, respectively) and significantly larger compared with CBCT alignments (SD 1.04 mm). Intraobserver variabilities are significantly smaller than corresponding interobserver variabilities (variance ratio [VR] 1.8-3.1). Compared with 3-dimensional registrations, 2-dimensional registrations have significantly smaller interobserver variability in the lateral and ventrodorsal directions (VR 3.8 and 2.8, respectively) but not in the craniocaudal direction (VR 0.75). Tomotherapy image guidance precision is affected by image resolution and residual deviations after setup correction. Eliminating the effect of residual deviations yields small interobserver variabilities with submillimeter precision in the axial plane. In contrast, interobserver variability in the craniocaudal direction is dominated by the poorer longitudinal MVCT image resolution. Residual deviations after image guidance exist and need to be considered when dose gradients ultimately achievable with image guided radiation therapy techniques are analyzed. Copyright © 2013 Elsevier Inc. All rights reserved.

Feasibility in multispectral imaging for predicting the content of bioactive compounds in intact tomato fruit.

PubMed

Liu, Changhong; Liu, Wei; Chen, Wei; Yang, Jianbo; Zheng, Lei

2015-04-15

Tomato is an important health-stimulating fruit because of the antioxidant properties of its main bioactive compounds, dominantly lycopene and phenolic compounds. Nowadays, product differentiation in the fruit market requires an accurate evaluation of these value-added compounds. An experiment was conducted to simultaneously and non-destructively measure lycopene and phenolic compounds content in intact tomatoes using multispectral imaging combined with chemometric methods. Partial least squares (PLS), least squares-support vector machines (LS-SVM) and back propagation neural network (BPNN) were applied to develop quantitative models. Compared with PLS and LS-SVM, BPNN model considerably improved the performance with coefficient of determination in prediction (RP(2))=0.938 and 0.965, residual predictive deviation (RPD)=4.590 and 9.335 for lycopene and total phenolics content prediction, respectively. It is concluded that multispectral imaging is an attractive alternative to the standard methods for determination of bioactive compounds content in intact tomatoes, providing a useful platform for infield fruit sorting/grading. Copyright © 2014 Elsevier Ltd. All rights reserved.

Geostatistical estimation of forest biomass in interior Alaska combining Landsat-derived tree cover, sampled airborne lidar and field observations

NASA Astrophysics Data System (ADS)

Babcock, Chad; Finley, Andrew O.; Andersen, Hans-Erik; Pattison, Robert; Cook, Bruce D.; Morton, Douglas C.; Alonzo, Michael; Nelson, Ross; Gregoire, Timothy; Ene, Liviu; Gobakken, Terje; Næsset, Erik

2018-06-01

The goal of this research was to develop and examine the performance of a geostatistical coregionalization modeling approach for combining field inventory measurements, strip samples of airborne lidar and Landsat-based remote sensing data products to predict aboveground biomass (AGB) in interior Alaska's Tanana Valley. The proposed modeling strategy facilitates pixel-level mapping of AGB density predictions across the entire spatial domain. Additionally, the coregionalization framework allows for statistically sound estimation of total AGB for arbitrary areal units within the study area---a key advance to support diverse management objectives in interior Alaska. This research focuses on appropriate characterization of prediction uncertainty in the form of posterior predictive coverage intervals and standard deviations. Using the framework detailed here, it is possible to quantify estimation uncertainty for any spatial extent, ranging from pixel-level predictions of AGB density to estimates of AGB stocks for the full domain. The lidar-informed coregionalization models consistently outperformed their counterpart lidar-free models in terms of point-level predictive performance and total AGB precision. Additionally, the inclusion of Landsat-derived forest cover as a covariate further improved estimation precision in regions with lower lidar sampling intensity. Our findings also demonstrate that model-based approaches that do not explicitly account for residual spatial dependence can grossly underestimate uncertainty, resulting in falsely precise estimates of AGB. On the other hand, in a geostatistical setting, residual spatial structure can be modeled within a Bayesian hierarchical framework to obtain statistically defensible assessments of uncertainty for AGB estimates.

THE EFFECTS OF BODY MASS, PHYLOGENY, HABITAT, AND TROPHIC LEVEL ON MAMMALIAN AGE AT FIRST REPRODUCTION.

PubMed

Wootton, J Timothy

1987-07-01

I examined age at first reproduction of 547 mammalian species to determine the influence of diet and habitat on the evolution of life-history traits. Body mass correlated positively with age at first reproduction, explaining 56% of the variance. Habitat and trophic groups deviated significantly from the allometric curve in a pattern generally consistent with predictions from r/K selection theory and its modifications. However, mammalian orders also deviated significantly from the allometric curve, and different habitat and diet groups contained different ratios of mammalian orders. When the effects of orders were removed, residual deviations did not differ among ecological groups. Adjusting for ecological differences did not eliminate the differences between orders. These results suggest that body mass (or some correlated factor) and phylogeny strongly constrain age at first reproduction. Ecological factors appear to have little effect on the evolution of age at first reproduction. Apparent differences in weight-specific ages at first reproduction within habitats and trophic groups may be the result of ecological selection of order composition in the present, rather than ecologically driven evolution of life history in the past. © 1987 The Society for the Study of Evolution.

StralSV: assessment of sequence variability within similar 3D structures and application to polio RNA-dependent RNA polymerase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zemla, A; Lang, D; Kostova, T

2010-11-29

Most of the currently used methods for protein function prediction rely on sequence-based comparisons between a query protein and those for which a functional annotation is provided. A serious limitation of sequence similarity-based approaches for identifying residue conservation among proteins is the low confidence in assigning residue-residue correspondences among proteins when the level of sequence identity between the compared proteins is poor. Multiple sequence alignment methods are more satisfactory - still, they cannot provide reliable results at low levels of sequence identity. Our goal in the current work was to develop an algorithm that could overcome these difficulties and facilitatemore » the identification of structurally (and possibly functionally) relevant residue-residue correspondences between compared protein structures. Here we present StralSV, a new algorithm for detecting closely related structure fragments and quantifying residue frequency from tight local structure alignments. We apply StralSV in a study of the RNA-dependent RNA polymerase of poliovirus and demonstrate that the algorithm can be used to determine regions of the protein that are relatively unique or that shared structural similarity with structures that are distantly related. By quantifying residue frequencies among many residue-residue pairs extracted from local alignments, one can infer potential structural or functional importance of specific residues that are determined to be highly conserved or that deviate from a consensus. We further demonstrate that considerable detailed structural and phylogenetic information can be derived from StralSV analyses. StralSV is a new structure-based algorithm for identifying and aligning structure fragments that have similarity to a reference protein. StralSV analysis can be used to quantify residue-residue correspondences and identify residues that may be of particular structural or functional importance, as well as unusual or unexpected residues at a given sequence position.« less

StralSV: assessment of sequence variability within similar 3D structures and application to polio RNA-dependent RNA polymerase.

PubMed

Zemla, Adam T; Lang, Dorothy M; Kostova, Tanya; Andino, Raul; Ecale Zhou, Carol L

2011-06-02

Most of the currently used methods for protein function prediction rely on sequence-based comparisons between a query protein and those for which a functional annotation is provided. A serious limitation of sequence similarity-based approaches for identifying residue conservation among proteins is the low confidence in assigning residue-residue correspondences among proteins when the level of sequence identity between the compared proteins is poor. Multiple sequence alignment methods are more satisfactory--still, they cannot provide reliable results at low levels of sequence identity. Our goal in the current work was to develop an algorithm that could help overcome these difficulties by facilitating the identification of structurally (and possibly functionally) relevant residue-residue correspondences between compared protein structures. Here we present StralSV (structure-alignment sequence variability), a new algorithm for detecting closely related structure fragments and quantifying residue frequency from tight local structure alignments. We apply StralSV in a study of the RNA-dependent RNA polymerase of poliovirus, and we demonstrate that the algorithm can be used to determine regions of the protein that are relatively unique, or that share structural similarity with proteins that would be considered distantly related. By quantifying residue frequencies among many residue-residue pairs extracted from local structural alignments, one can infer potential structural or functional importance of specific residues that are determined to be highly conserved or that deviate from a consensus. We further demonstrate that considerable detailed structural and phylogenetic information can be derived from StralSV analyses. StralSV is a new structure-based algorithm for identifying and aligning structure fragments that have similarity to a reference protein. StralSV analysis can be used to quantify residue-residue correspondences and identify residues that may be of particular structural or functional importance, as well as unusual or unexpected residues at a given sequence position. StralSV is provided as a web service at http://proteinmodel.org/AS2TS/STRALSV/.

Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials.

PubMed

Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A; Burgueño, Juan; Bandeira E Sousa, Massaine; Crossa, José

2018-03-28

In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines ([Formula: see text]) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. Copyright © 2018 Cuevas et al.

Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials

PubMed Central

Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A.; Burgueño, Juan; Bandeira e Sousa, Massaine; Crossa, José

2018-01-01

In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines (l) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. PMID:29476023

Accurate measurement in the field of the earth of the general-relativistic precession of the LAGEOS II pericenter and new constraints on non-newtonian gravity.

PubMed

Lucchesi, David M; Peron, Roberto

2010-12-03

The pericenter shift of a binary system represents a suitable observable to test for possible deviations from the newtonian inverse-square law in favor of new weak interactions between macroscopic objects. We analyzed 13 years of tracking data of the LAGEOS satellites with GEODYN II software but with no models for general relativity. From the fit of LAGEOS II pericenter residuals we have been able to obtain a 99.8% agreement with the predictions of Einstein's theory. This result may be considered as a 99.8% measurement in the field of the Earth of the combination of the γ and β parameters of general relativity, and it may be used to constrain possible deviations from the inverse-square law in favor of new weak interactions parametrized by a Yukawa-like potential with strength α and range λ. We obtained |α| ≲ 1 × 10(-11), a huge improvement at a range of about 1 Earth radius.

Evolution of Residual Stress and Distortion of Cold-Rolled Bearing Ring from Annealing to Quenched-Tempered Heat Treatment

NASA Astrophysics Data System (ADS)

Lu, Bohan; Lu, Xiaohui

2018-02-01

This study investigates the correlation between the residual stress and distortion behavior of a cold-rolled ring from the annealing to quenching-tempering (QT) process. Due to the cold-rolled process, the external periphery of the bearing ring experiences a compressive residual stress. To relieve the residual stress, cold-rolled rings are annealed at 700 °C which is higher than the starting temperature of recrystallization. When cold-rolled rings are annealed at 700 °C for 15 min, the compressive residual stress is reduced to zero and the outer diameter of the annealed ring becomes larger than that of a non-annealed sample, which is unrelated to annealing time. Simultaneously, the roundness and taper deviation do not obviously change compared with those of non-annealed sample. The stress relaxation during the annealing process was attributed to the recovery and recrystallization of ferrite. Annealing has a genetic influence on the following QT heat treatment, wherein the lowest residual stress is in the non-annealed cold-rolled ring. From the annealing to QT process, the deviation of the outer diameter, roundness, and taper increased with annealing time, a large extend than that of non-annealed samples.

High accuracy prediction of beta-turns and their types using propensities and multiple alignments.

PubMed

Fuchs, Patrick F J; Alix, Alain J P

2005-06-01

We have developed a method that predicts both the presence and the type of beta-turns, using a straightforward approach based on propensities and multiple alignments. The propensities were calculated classically, but the way to use them for prediction was completely new: starting from a tetrapeptide sequence on which one wants to evaluate the presence of a beta-turn, the propensity for a given residue is modified by taking into account all the residues present in the multiple alignment at this position. The evaluation of a score is then done by weighting these propensities by the use of Position-specific score matrices generated by PSI-BLAST. The introduction of secondary structure information predicted by PSIPRED or SSPRO2 as well as taking into account the flanking residues around the tetrapeptide improved the accuracy greatly. This latter evaluated on a database of 426 reference proteins (previously used on other studies) by a sevenfold crossvalidation gave very good results with a Matthews Correlation Coefficient (MCC) of 0.42 and an overall prediction accuracy of 74.8%; this places our method among the best ones. A jackknife test was also done, which gave results within the same range. This shows that it is possible to reach neural networks accuracy with considerably less computional cost and complexity. Furthermore, propensities remain excellent descriptors of amino acid tendencies to belong to beta-turns, which can be useful for peptide or protein engineering and design. For beta-turn type prediction, we reached the best accuracy ever published in terms of MCC (except for the irregular type IV) in the range of 0.25-0.30 for types I, II, and I' and 0.13-0.15 for types VIII, II', and IV. To our knowledge, our method is the only one available on the Web that predicts types I' and II'. The accuracy evaluated on two larger databases of 547 and 823 proteins was not improved significantly. All of this was implemented into a Web server called COUDES (French acronym for: Chercher Ou Une Deviation Existe Surement), which is available at the following URL: http://bioserv.rpbs.jussieu.fr/Coudes/index.html within the new bioinformatics platform RPBS.

Revealing Hidden Conformational Space of LOV Protein VIVID Through Rigid Residue Scan Simulations

NASA Astrophysics Data System (ADS)

Zhou, Hongyu; Zoltowski, Brian D.; Tao, Peng

2017-04-01

VIVID(VVD) protein is a Light-Oxygen-Voltage(LOV) domain in circadian clock system. Upon blue light activation, a covalent bond is formed between VVD residue Cys108 and its cofactor flavin adenine dinucleotide(FAD), and prompts VVD switching from Dark state to Light state with significant conformational deviation. However, the mechanism of this local environment initiated global protein conformational change remains elusive. We employed a recently developed computational approach, rigid residue scan(RRS), to systematically probe the impact of the internal degrees of freedom in each amino acid residue of VVD on its overall dynamics by applying rigid body constraint on each residue in molecular dynamics simulations. Key residues were identified with distinctive impacts on Dark and Light states, respectively. All the simulations display wide range of distribution on a two-dimensional(2D) plot upon structural root-mean-square deviations(RMSD) from either Dark or Light state. Clustering analysis of the 2D RMSD distribution leads to 15 representative structures with drastically different conformation of N-terminus, which is also a key difference between Dark and Light states of VVD. Further principle component analyses(PCA) of RRS simulations agree with the observation of distinctive impact from individual residues on Dark and Light states.

Revealing Hidden Conformational Space of LOV Protein VIVID Through Rigid Residue Scan Simulations

PubMed Central

Zhou, Hongyu; Zoltowski, Brian D.; Tao, Peng

2017-01-01

VIVID(VVD) protein is a Light-Oxygen-Voltage(LOV) domain in circadian clock system. Upon blue light activation, a covalent bond is formed between VVD residue Cys108 and its cofactor flavin adenine dinucleotide(FAD), and prompts VVD switching from Dark state to Light state with significant conformational deviation. However, the mechanism of this local environment initiated global protein conformational change remains elusive. We employed a recently developed computational approach, rigid residue scan(RRS), to systematically probe the impact of the internal degrees of freedom in each amino acid residue of VVD on its overall dynamics by applying rigid body constraint on each residue in molecular dynamics simulations. Key residues were identified with distinctive impacts on Dark and Light states, respectively. All the simulations display wide range of distribution on a two-dimensional(2D) plot upon structural root-mean-square deviations(RMSD) from either Dark or Light state. Clustering analysis of the 2D RMSD distribution leads to 15 representative structures with drastically different conformation of N-terminus, which is also a key difference between Dark and Light states of VVD. Further principle component analyses(PCA) of RRS simulations agree with the observation of distinctive impact from individual residues on Dark and Light states. PMID:28425502

The disappearance rate and risk assessment of thiacloprid residues in Asian pear using liquid chromatography confirmed with tandem mass spectrometry.

PubMed

Kabir, Md Humayun; Abd El-Aty, A M; Rahman, Md Musfiqur; Kim, Sung-Woo; Choi, Jeong-Heui; Lee, Young-Jun; Truong, Lieu T B; Lee, Kang-Bong; Kim, Mi-Ra; Shin, Ho-Chul; Shim, Jae-Han

2017-05-01

This study was undertaken to quantify the residue levels and propose the dissipation kinetics of thiacloprid formulated as suspension concentrate in field-incurred Asian pears grown under two different open-field conditions. Samples were extracted with 20% distilled water in acetonitrile; partitioned with brine water and dichloromethane; and purified with a Florisil solid phase extraction cartridge. The analyte was identified with an LC ultraviolet detector, and field-incurred samples were confirmed using LC-MS/MS. The calibration curve was linear over the range 0.05-5.0 mg/L with a satisfactory coefficient of determination (R 2  = 0.9994). The limits of detection and limits of quantification (LOQ) were 0.003 and 0.01 mg/kg, respectively. The recovery rate fortified to blank samples at LOQ, 10× LOQ, and the maximum residue limit (MRL) were between 73.7 and 86.2% with relative standard deviation ≤9.0%. The residual concentrations at both sites were considerably lower than the MRL (0.7 mg/kg) set by the Korean Ministry of Food Drug Safety, with biological half-lives of 5.0 and 7.4 days, for sites 1 and 2, respectively. From the pre-harvest residue limit curve, it was predicted that if the residues were <1.13 or 1.40 mg/kg 10 days before harvest, the residue level would be lower than the MRL during harvest. Risk assessment on day 0 showed an acceptable daily intake (%) of 13.0% and 11.0% for sites 1 and site 2, respectively, which indicates that the residual amounts are not hazardous to the Korean population. Copyright © 2016 John Wiley & Sons, Ltd.

Deposition and residues of azoxystrobin and imidacloprid on greenhouse lettuce with implications for human consumption.

PubMed

Itoiz, Eva Sevigné; Fantke, Peter; Juraske, Ronnie; Kounina, Anna; Vallejo, Assumpció Antón

2012-11-01

Lettuce greenhouse experiments were carried out from March to June 2011 in order to analyze how pesticides behave from the time of application until their intake via human consumption taking into account the primary distribution of pesticides, field dissipation, and post-harvest processing. In addition, experimental conditions were used to evaluate a new dynamic plant uptake model comparing its results with the experimentally derived residues. One application of imidacloprid and two of azoxystrobin were conducted. For evaluating primary pesticide distribution, two approaches based on leaf area index and vegetation cover were used and results were compared with those obtained from a tracer test. High influence of lettuce density, growth stage and type of sprayer was observed in primary distribution showing that low densities or early growth stages implied high losses of pesticides on soil. Washed and unwashed samples of lettuce were taken and analyzed from application to harvest to evaluate removal of pesticides by food processing. Results show that residues found on the Spanish preharvest interval days were in all cases below officially set maximum residue limits, although it was observed that time between application and harvest is as important for residues as application amounts. An overall reduction of 40-60% of pesticides residues was obtained from washing lettuce. Experimentally derived residues were compared with modeled residues and deviate from 1.2 to 1.4 for imidacloprid and azoxystrobin, respectively, presenting good model predictions. Resulting human intake fractions range from 0.045 kg(intake) kg(applied)(-1) for imidacloprid to 0.14 kg(intake) kg(applied)(-1) for azoxystrobin. Copyright © 2012 Elsevier Ltd. All rights reserved.

Isolating the cow-specific part of residual energy intake in lactating dairy cows using random regressions.

PubMed

Fischer, A; Friggens, N C; Berry, D P; Faverdin, P

2018-07-01

The ability to properly assess and accurately phenotype true differences in feed efficiency among dairy cows is key to the development of breeding programs for improving feed efficiency. The variability among individuals in feed efficiency is commonly characterised by the residual intake approach. Residual feed intake is represented by the residuals of a linear regression of intake on the corresponding quantities of the biological functions that consume (or release) energy. However, the residuals include both, model fitting and measurement errors as well as any variability in cow efficiency. The objective of this study was to isolate the individual animal variability in feed efficiency from the residual component. Two separate models were fitted, in one the standard residual energy intake (REI) was calculated as the residual of a multiple linear regression of lactation average net energy intake (NEI) on lactation average milk energy output, average metabolic BW, as well as lactation loss and gain of body condition score. In the other, a linear mixed model was used to simultaneously fit fixed linear regressions and random cow levels on the biological traits and intercept using fortnight repeated measures for the variables. This method split the predicted NEI in two parts: one quantifying the population mean intercept and coefficients, and one quantifying cow-specific deviations in the intercept and coefficients. The cow-specific part of predicted NEI was assumed to isolate true differences in feed efficiency among cows. NEI and associated energy expenditure phenotypes were available for the first 17 fortnights of lactation from 119 Holstein cows; all fed a constant energy-rich diet. Mixed models fitting cow-specific intercept and coefficients to different combinations of the aforementioned energy expenditure traits, calculated on a fortnightly basis, were compared. The variance of REI estimated with the lactation average model represented only 8% of the variance of measured NEI. Among all compared mixed models, the variance of the cow-specific part of predicted NEI represented between 53% and 59% of the variance of REI estimated from the lactation average model or between 4% and 5% of the variance of measured NEI. The remaining 41% to 47% of the variance of REI estimated with the lactation average model may therefore reflect model fitting errors or measurement errors. In conclusion, the use of a mixed model framework with cow-specific random regressions seems to be a promising method to isolate the cow-specific component of REI in dairy cows.

[Predictability of residual astigmatism after implantation of posterior chamber toric lenses].

PubMed

Mies, D; Klink, T; Eisenbarth, W; Meyer, L M

2018-01-01

The objective of the study was to examine the predictability of residual astigmatism after cataract surgery and implantation of the posterior chamber aspheric toric lens TECNIS® ZCT, Abott Medical Optic (Ettlingen, Deutschland). The retrospective study included a total of 88 patient eyes undergoing a cataract operation with a toric lens implantation between March 2014 and October 2015. The inclusion criteria were a regular astigmatism of at least 0.75 dpt. Posterior chamber toric lenses (model Tecnis ZCT) were exclusively implanted. Post-surgery check-ups were performed after 1 day, 1 month and 2 months. Main study outcome was best-corrected visual acuity (BCVA), spherical and astigmatic aberration and the difference between expected and actual residual astigmatism after cataract surgery. The median reduction of corneal astigmatism was from -2.50 dpt (±1.06 dpt) to -0.75 dpt (±0.51 dpt) (p ≤ 0.05). The median BCVA increased from 0.37 logMAR (±0.25 logMAR) before surgery to 0.09 logMAR (±0.10 logMAR) after surgery. The spherical equivalent was reduced from +3.50 dpt (±1.11 dpt) (presurgery) to -0.56 dpt (±0.51 dpt) (postsurgery) in hyperopic patients and from -2.44 dpt (±3.03 dpt) to -0.69 dpt (±0.81 dpt) in myopic patients. By using the power vector analysis no significant deviation from the expected target values was observed; however, the median discrepancy between the expected and actual residual astigmatism was -0.50 dpt despite a surgical orientation of the intraocular lens (IOL) within 5° of the desired axis. The IOL showed a median rotation of 3.00° (±4.46°). Implantation of the aspheric toric intraocular lens Tecnis ZCT is a predictable, effective and reproducible tool in cataract surgery to account for regular corneal astigmatis; however, despite an optimal surgical orientation of the toric IOL, a small and rarely a large discrepancy might occur between expected and actual residual astigmatism.

Hot topic: Definition and implementation of a breeding value for feed efficiency in dairy cows.

PubMed

Pryce, J E; Gonzalez-Recio, O; Nieuwhof, G; Wales, W J; Coffey, M P; Hayes, B J; Goddard, M E

2015-10-01

A new breeding value that combines the amount of feed saved through improved metabolic efficiency with predicted maintenance requirements is described. The breeding value includes a genomic component for residual feed intake (RFI) combined with maintenance requirements calculated from either a genomic or pedigree estimated breeding value (EBV) for body weight (BW) predicted using conformation traits. Residual feed intake is only available for genotyped Holsteins; however, BW is available for all breeds. The RFI component of the "feed saved" EBV has 2 parts: Australian calf RFI and Australian lactating cow RFI. Genomic breeding values for RFI were estimated from a reference population of 2,036 individuals in a multi-trait analysis including Australian calf RFI (n=843), Australian lactating cow RFI (n=234), and UK and Dutch lactating cow RFI (n=958). In all cases, the RFI phenotypes were deviations from a mean of 0, calculated by correcting dry matter intake for BW, growth, and milk yield (in the case of lactating cows). Single nucleotide polymorphism effects were calculated from the output of genomic BLUP and used to predict breeding values of 4,106 Holstein sires that were genotyped but did not have RFI phenotypes themselves. These bulls already had BW breeding values calculated from type traits, from which maintenance requirements in kilograms of feed per year were inferred. Finally, RFI and the feed required for maintenance (through BW) were used to calculate a feed saved breeding value and expressed as the predicted amount of feed saved per year. Animals that were 1 standard deviation above the mean were predicted to eat 66 kg dry matter less per year at the same level of milk production. In a data set of genotyped Holstein sires, the mean reliability of the feed saved breeding value was 0.37. For Holsteins that are not genotyped and for breeds other than Holsteins, feed saved is calculated using BW only. From April 2015, feed saved has been included as part of the Australian national selection index, the Balanced Performance Index (BPI). Selection on the BPI is expected to lead to modest gains in feed efficiency. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Microplate model for the present-day deformation of Tibet

USGS Publications Warehouse

Thatcher, W.

2007-01-01

Site velocities from 349 Global Positioning System (GPS) stations are used to construct an 11-element quasi-rigid block model of the Tibetan Plateau and its surroundings. Rigid rotations of five major blocks are well determined, and average translation velocities of six smaller blocks can be constrained. Where data are well distributed the velocity field can be explained well by rigid block motion and fault slip across block boundaries. Residual misfits average 1.6 mm/yr compared to typical one standard deviation velocity uncertainties of 1.3 mm/yr. Any residual internal straining of the blocks is small and heterogeneous. However, residual substructure might well represent currently unresolved motions of smaller blocks. Although any smaller blocks must move at nearly the same rate as the larger blocks within which they lie, undetected relative motions between them could be significant, particularly where there are gaps in GPS coverage. Predicted relative motions between major blocks agree with the observed sense of slip and along-strike partitioning of motion across major faults. However, predicted slip rates across Tibet's major strike-slip faults are low, only 5-12 mm/yr, a factor of 2-3 smaller than most rates estimated from fault offset features dated by radiometric methods as ???2000 to ???100,000 year old. Previous work has suggested that both GPS data and low fault slip rates are incompatible with rigid block motions of Tibet. The results reported here overcome these objections.

Mitigating cutting-induced plasticity in the contour method, Part 2: Numerical analysis

DOE PAGES

Muránsky, O.; Hamelin, C. J.; Hosseinzadeh, F.; ...

2016-02-10

Cutting-induced plasticity can have a significant effect on the measurement accuracy of the contour method. The present study examines the benefit of a double-embedded cutting configuration that relies on self-restraint of the specimen, relative to conventional edge-crack cutting configurations. A series of finite element analyses are used to simulate the planar sectioning performed during double-embedded and conventional edge-crack contour cutting configurations. The results of numerical analyses are first compared to measured results to validate the cutting simulations. The simulations are then used to compare the efficacy of different cutting configurations by predicting the deviation of the residual stress profile frommore » an original (pre-cutting) reference stress field, and the extent of cutting-induced plasticity. Comparisons reveal that while the double-embedded cutting configuration produces the most accurate residual stress measurements, the highest levels of plastic flow are generated in this process. As a result, this cutting-induced plastic deformation is, however, largely confined to small ligaments formed as a consequence of the sample sectioning process, and as such it does not significantly affect the back-calculated residual stress field.« less

Mitigating cutting-induced plasticity in the contour method, Part 2: Numerical analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Muránsky, O.; Hamelin, C. J.; Hosseinzadeh, F.

Cutting-induced plasticity can have a significant effect on the measurement accuracy of the contour method. The present study examines the benefit of a double-embedded cutting configuration that relies on self-restraint of the specimen, relative to conventional edge-crack cutting configurations. A series of finite element analyses are used to simulate the planar sectioning performed during double-embedded and conventional edge-crack contour cutting configurations. The results of numerical analyses are first compared to measured results to validate the cutting simulations. The simulations are then used to compare the efficacy of different cutting configurations by predicting the deviation of the residual stress profile frommore » an original (pre-cutting) reference stress field, and the extent of cutting-induced plasticity. Comparisons reveal that while the double-embedded cutting configuration produces the most accurate residual stress measurements, the highest levels of plastic flow are generated in this process. As a result, this cutting-induced plastic deformation is, however, largely confined to small ligaments formed as a consequence of the sample sectioning process, and as such it does not significantly affect the back-calculated residual stress field.« less

Analysis of target wavefront error for secondary mirror of a spaceborne telescope

NASA Astrophysics Data System (ADS)

Chang, Shenq-Tsong; Lin, Wei-Cheng; Kuo, Ching-Hsiang; Chan, Chia-Yen; Lin, Yu-Chuan; Huang, Ting-Ming

2014-09-01

During the fabrication of an aspherical mirror, the inspection of the residual wavefront error is critical. In the program of a spaceborne telescope development, primary mirror is made of ZERODUR with clear aperture of 450 mm. The mass is 10 kg after lightweighting. Deformation of mirror due to gravity is expected; hence uniform supporting measured by load cells has been applied to reduce the gravity effect. Inspection has been taken to determine the residual wavefront error at the configuration of mirror face upwards. Correction polishing has been performed according to the measurement. However, after comparing with the data measured by bench test while the primary mirror is at a configuration of mirror face horizontal, deviations have been found for the two measurements. Optical system that is not able to meet the requirement is predicted according to the measured wavefront error by bench test. A target wavefront error of secondary mirror is therefore analyzed to correct that of primary mirror. Optical performance accordingly is presented.

Photonic Doppler velocimetry probe designed with stereo imaging

NASA Astrophysics Data System (ADS)

Malone, Robert M.; Cata, Brian M.; Daykin, Edward P.; Esquibel, David L.; Frogget, Brent C.; Holtkamp, David B.; Kaufman, Morris I.; McGillivray, Kevin D.; Palagi, Martin J.; Pazuchanics, Peter; Romero, Vincent T.; Sorenson, Danny S.

2014-09-01

During the fabrication of an aspherical mirror, the inspection of the residual wavefront error is critical. In the program of a spaceborne telescope development, primary mirror is made of ZERODUR with clear aperture of 450 mm. The mass is 10 kg after lightweighting. Deformation of mirror due to gravity is expected; hence uniform supporting measured by load cells has been applied to reduce the gravity effect. Inspection has been taken to determine the residual wavefront error at the configuration of mirror face upwards. Correction polishing has been performed according to the measurement. However, after comparing with the data measured by bench test while the primary mirror is at a configuration of mirror face horizontal, deviations have been found for the two measurements. Optical system that is not able to meet the requirement is predicted according to the measured wavefront error by bench test. A target wavefront error of secondary mirror is therefore analyzed to correct that of primary mirror. Optical performance accordingly is presented.

Developing a NIR multispectral imaging for prediction and visualization of peanut protein content using variable selection algorithms

NASA Astrophysics Data System (ADS)

Cheng, Jun-Hu; Jin, Huali; Liu, Zhiwei

2018-01-01

The feasibility of developing a multispectral imaging method using important wavelengths from hyperspectral images selected by genetic algorithm (GA), successive projection algorithm (SPA) and regression coefficient (RC) methods for modeling and predicting protein content in peanut kernel was investigated for the first time. Partial least squares regression (PLSR) calibration model was established between the spectral data from the selected optimal wavelengths and the reference measured protein content ranged from 23.46% to 28.43%. The RC-PLSR model established using eight key wavelengths (1153, 1567, 1972, 2143, 2288, 2339, 2389 and 2446 nm) showed the best predictive results with the coefficient of determination of prediction (R2P) of 0.901, and root mean square error of prediction (RMSEP) of 0.108 and residual predictive deviation (RPD) of 2.32. Based on the obtained best model and image processing algorithms, the distribution maps of protein content were generated. The overall results of this study indicated that developing a rapid and online multispectral imaging system using the feature wavelengths and PLSR analysis is potential and feasible for determination of the protein content in peanut kernels.

Autocorrelated residuals in inverse modelling of soil hydrological processes: a reason for concern or something that can safely be ignored?

NASA Astrophysics Data System (ADS)

Scharnagl, Benedikt; Durner, Wolfgang

2013-04-01

Models are inherently imperfect because they simplify processes that are themselves imperfectly known and understood. Moreover, the input variables and parameters needed to run a model are typically subject to various sources of error. As a consequence of these imperfections, model predictions will always deviate from corresponding observations. In most applications in soil hydrology, these deviations are clearly not random but rather show a systematic structure. From a statistical point of view, this systematic mismatch may be a reason for concern because it violates one of the basic assumptions made in inverse parameter estimation: the assumption of independence of the residuals. But what are the consequences of simply ignoring the autocorrelation in the residuals, as it is current practice in soil hydrology? Are the parameter estimates still valid even though the statistical foundation they are based on is partially collapsed? Theory and practical experience from other fields of science have shown that violation of the independence assumption will result in overconfident uncertainty bounds and that in some cases it may lead to significantly different optimal parameter values. In our contribution, we present three soil hydrological case studies, in which the effect of autocorrelated residuals on the estimated parameters was investigated in detail. We explicitly accounted for autocorrelated residuals using a formal likelihood function that incorporates an autoregressive model. The inverse problem was posed in a Bayesian framework, and the posterior probability density function of the parameters was estimated using Markov chain Monte Carlo simulation. In contrast to many other studies in related fields of science, and quite surprisingly, we found that the first-order autoregressive model, often abbreviated as AR(1), did not work well in the soil hydrological setting. We showed that a second-order autoregressive, or AR(2), model performs much better in these applications, leading to parameter and uncertainty estimates that satisfy all the underlying statistical assumptions. For theoretical reasons, these estimates are deemed more reliable than those estimates based on the neglect of autocorrelation in the residuals. In compliance with theory and results reported in the literature, our results showed that parameter uncertainty bounds were substantially wider if autocorrelation in the residuals was explicitly accounted for, and also the optimal parameter vales were slightly different in this case. We argue that the autoregressive model presented here should be used as a matter of routine in inverse modeling of soil hydrological processes.

A QSAR study of integrase strand transfer inhibitors based on a large set of pyrimidine, pyrimidone, and pyridopyrazine carboxamide derivatives

NASA Astrophysics Data System (ADS)

de Campos, Luana Janaína; de Melo, Eduardo Borges

2017-08-01

In the present study, 199 compounds derived from pyrimidine, pyrimidone and pyridopyrazine carboxamides with inhibitory activity against HIV-1 integrase were modeled. Subsequently, a multivariate QSAR study was conducted with 54 molecules employed by Ordered Predictors Selection (OPS) and Partial Least Squares (PLS) for the selection of variables and model construction, respectively. Topological, electrotopological, geometric, and molecular descriptors were used. The selected real model was robust and free from chance correlation; in addition, it demonstrated favorable internal and external statistical quality. Once statistically validated, the training model was used to predict the activity of a second data set (n = 145). The root mean square deviation (RMSD) between observed and predicted values was 0.698. Although it is a value outside of the standards, only 15 (10.34%) of the samples exhibited higher residual values than 1 log unit, a result considered acceptable. Results of Williams and Euclidean applicability domains relative to the prediction showed that the predictions did not occur by extrapolation and that the model is representative of the chemical space of test compounds.

Enhancing interacting residue prediction with integrated contact matrix prediction in protein-protein interaction.

PubMed

Du, Tianchuan; Liao, Li; Wu, Cathy H

2016-12-01

Identifying the residues in a protein that are involved in protein-protein interaction and identifying the contact matrix for a pair of interacting proteins are two computational tasks at different levels of an in-depth analysis of protein-protein interaction. Various methods for solving these two problems have been reported in the literature. However, the interacting residue prediction and contact matrix prediction were handled by and large independently in those existing methods, though intuitively good prediction of interacting residues will help with predicting the contact matrix. In this work, we developed a novel protein interacting residue prediction system, contact matrix-interaction profile hidden Markov model (CM-ipHMM), with the integration of contact matrix prediction and the ipHMM interaction residue prediction. We propose to leverage what is learned from the contact matrix prediction and utilize the predicted contact matrix as "feedback" to enhance the interaction residue prediction. The CM-ipHMM model showed significant improvement over the previous method that uses the ipHMM for predicting interaction residues only. It indicates that the downstream contact matrix prediction could help the interaction site prediction.

Prediction uncertainty and optimal experimental design for learning dynamical systems.

PubMed

Letham, Benjamin; Letham, Portia A; Rudin, Cynthia; Browne, Edward P

2016-06-01

Dynamical systems are frequently used to model biological systems. When these models are fit to data, it is necessary to ascertain the uncertainty in the model fit. Here, we present prediction deviation, a metric of uncertainty that determines the extent to which observed data have constrained the model's predictions. This is accomplished by solving an optimization problem that searches for a pair of models that each provides a good fit for the observed data, yet has maximally different predictions. We develop a method for estimating a priori the impact that additional experiments would have on the prediction deviation, allowing the experimenter to design a set of experiments that would most reduce uncertainty. We use prediction deviation to assess uncertainty in a model of interferon-alpha inhibition of viral infection, and to select a sequence of experiments that reduces this uncertainty. Finally, we prove a theoretical result which shows that prediction deviation provides bounds on the trajectories of the underlying true model. These results show that prediction deviation is a meaningful metric of uncertainty that can be used for optimal experimental design.

Evaluating the Performance of a New Model for Predicting the Growth of Clostridium perfringens in Cooked, Uncured Meat and Poultry Products under Isothermal, Heating, and Dynamically Cooling Conditions.

PubMed

Huang, Lihan

2016-07-01

Clostridium perfringens type A is a significant public health threat and its spores may germinate, outgrow, and multiply during cooling of cooked meats. This study applies a new C. perfringens growth model in the USDA Integrated Pathogen Modeling Program-Dynamic Prediction (IPMP Dynamic Prediction) Dynamic Prediction to predict the growth from spores of C. perfringens in cooked uncured meat and poultry products using isothermal, dynamic heating, and cooling data reported in the literature. The residual errors of predictions (observation-prediction) are analyzed, and the root-mean-square error (RMSE) calculated. For isothermal and heating profiles, each data point in growth curves is compared. The mean residual errors (MRE) of predictions range from -0.40 to 0.02 Log colony forming units (CFU)/g, with a RMSE of approximately 0.6 Log CFU/g. For cooling, the end point predictions are conservative in nature, with an MRE of -1.16 Log CFU/g for single-rate cooling and -0.66 Log CFU/g for dual-rate cooling. The RMSE is between 0.6 and 0.7 Log CFU/g. Compared with other models reported in the literature, this model makes more accurate and fail-safe predictions. For cooling, the percentage for accurate and fail-safe predictions is between 97.6% and 100%. Under criterion 1, the percentage of accurate predictions is 47.5% for single-rate cooling and 66.7% for dual-rate cooling, while the fail-dangerous predictions are between 0% and 2.4%. This study demonstrates that IPMP Dynamic Prediction can be used by food processors and regulatory agencies as a tool to predict the growth of C. perfringens in uncured cooked meats and evaluate the safety of cooked or heat-treated uncured meat and poultry products exposed to cooling deviations or to develop customized cooling schedules. This study also demonstrates the need for more accurate data collection during cooling. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

CSmetaPred: a consensus method for prediction of catalytic residues.

PubMed

Choudhary, Preeti; Kumar, Shailesh; Bachhawat, Anand Kumar; Pandit, Shashi Bhushan

2017-12-22

Knowledge of catalytic residues can play an essential role in elucidating mechanistic details of an enzyme. However, experimental identification of catalytic residues is a tedious and time-consuming task, which can be expedited by computational predictions. Despite significant development in active-site prediction methods, one of the remaining issues is ranked positions of putative catalytic residues among all ranked residues. In order to improve ranking of catalytic residues and their prediction accuracy, we have developed a meta-approach based method CSmetaPred. In this approach, residues are ranked based on the mean of normalized residue scores derived from four well-known catalytic residue predictors. The mean residue score of CSmetaPred is combined with predicted pocket information to improve prediction performance in meta-predictor, CSmetaPred_poc. Both meta-predictors are evaluated on two comprehensive benchmark datasets and three legacy datasets using Receiver Operating Characteristic (ROC) and Precision Recall (PR) curves. The visual and quantitative analysis of ROC and PR curves shows that meta-predictors outperform their constituent methods and CSmetaPred_poc is the best of evaluated methods. For instance, on CSAMAC dataset CSmetaPred_poc (CSmetaPred) achieves highest Mean Average Specificity (MAS), a scalar measure for ROC curve, of 0.97 (0.96). Importantly, median predicted rank of catalytic residues is the lowest (best) for CSmetaPred_poc. Considering residues ranked ≤20 classified as true positive in binary classification, CSmetaPred_poc achieves prediction accuracy of 0.94 on CSAMAC dataset. Moreover, on the same dataset CSmetaPred_poc predicts all catalytic residues within top 20 ranks for ~73% of enzymes. Furthermore, benchmarking of prediction on comparative modelled structures showed that models result in better prediction than only sequence based predictions. These analyses suggest that CSmetaPred_poc is able to rank putative catalytic residues at lower (better) ranked positions, which can facilitate and expedite their experimental characterization. The benchmarking studies showed that employing meta-approach in combining residue-level scores derived from well-known catalytic residue predictors can improve prediction accuracy as well as provide improved ranked positions of known catalytic residues. Hence, such predictions can assist experimentalist to prioritize residues for mutational studies in their efforts to characterize catalytic residues. Both meta-predictors are available as webserver at: http://14.139.227.206/csmetapred/ .

Sweat loss prediction using a multi-model approach

NASA Astrophysics Data System (ADS)

Xu, Xiaojiang; Santee, William R.

2011-07-01

A new multi-model approach (MMA) for sweat loss prediction is proposed to improve prediction accuracy. MMA was computed as the average of sweat loss predicted by two existing thermoregulation models: i.e., the rational model SCENARIO and the empirical model Heat Strain Decision Aid (HSDA). Three independent physiological datasets, a total of 44 trials, were used to compare predictions by MMA, SCENARIO, and HSDA. The observed sweat losses were collected under different combinations of uniform ensembles, environmental conditions (15-40°C, RH 25-75%), and exercise intensities (250-600 W). Root mean square deviation (RMSD), residual plots, and paired t tests were used to compare predictions with observations. Overall, MMA reduced RMSD by 30-39% in comparison with either SCENARIO or HSDA, and increased the prediction accuracy to 66% from 34% or 55%. Of the MMA predictions, 70% fell within the range of mean observed value ± SD, while only 43% of SCENARIO and 50% of HSDA predictions fell within the same range. Paired t tests showed that differences between observations and MMA predictions were not significant, but differences between observations and SCENARIO or HSDA predictions were significantly different for two datasets. Thus, MMA predicted sweat loss more accurately than either of the two single models for the three datasets used. Future work will be to evaluate MMA using additional physiological data to expand the scope of populations and conditions.

Control of deviations and prediction of surface roughness from micro machining of THz waveguides using acoustic emission signals

NASA Astrophysics Data System (ADS)

Griffin, James M.; Diaz, Fernanda; Geerling, Edgar; Clasing, Matias; Ponce, Vicente; Taylor, Chris; Turner, Sam; Michael, Ernest A.; Patricio Mena, F.; Bronfman, Leonardo

2017-02-01

By using acoustic emission (AE) it is possible to control deviations and surface quality during micro milling operations. The method of micro milling is used to manufacture a submillimetre waveguide where micro machining is employed to achieve the required superior finish and geometrical tolerances. Submillimetre waveguide technology is used in deep space signal retrieval where highest detection efficiencies are needed and therefore every possible signal loss in the receiver has to be avoided and stringent tolerances achieved. With a sub-standard surface finish the signals travelling along the waveguides dissipate away faster than with perfect surfaces where the residual roughness becomes comparable with the electromagnetic skin depth. Therefore, the higher the radio frequency the more critical this becomes. The method of time-frequency analysis (STFT) is used to transfer raw AE into more meaningful salient signal features (SF). This information was then correlated against the measured geometrical deviations and, the onset of catastrophic tool wear. Such deviations can be offset from different AE signals (different deviations from subsequent tests) and feedback for a final spring cut ensuring the geometrical accuracies are met. Geometrical differences can impact on the required transfer of AE signals (change in cut off frequencies and diminished SNR at the interface) and therefore errors have to be minimised to within 1 μm. Rules based on both Classification and Regression Trees (CART) and Neural Networks (NN) were used to implement a simulation displaying how such a control regime could be used as a real time controller, be it corrective measures (via spring cuts) over several initial machining passes or, with a micron cut introducing a level plain measure for allowing setup corrective measures (similar to a spirit level).

An Evaluation of the Automated Cost Estimating Integrated Tools (ACEIT) System

DTIC Science & Technology

1989-09-01

residual and it is described as the residual divided by its standard deviation (13:App A,17). Neter, Wasserman, and Kutner, in Applied Linear Regression Models...others. Applied Linear Regression Models. Homewood IL: Irwin, 1983. 19. Raduchel, William J. "A Professional’s Perspective on User-Friendliness," Byte

Using FT-NIR spectroscopy technique to determine arginine content in fermented Cordyceps sinensis mycelium.

PubMed

Xie, Chuanqi; Xu, Ning; Shao, Yongni; He, Yong

2015-01-01

This research investigated the feasibility of using Fourier transform near-infrared (FT-NIR) spectral technique for determining arginine content in fermented Cordyceps sinensis (C. sinensis) mycelium. Three different models were carried out to predict the arginine content. Wavenumber selection methods such as competitive adaptive reweighted sampling (CARS) and successive projections algorithm (SPA) were used to identify the most important wavenumbers and reduce the high dimensionality of the raw spectral data. Only a few wavenumbers were selected by CARS and CARS-SPA as the optimal wavenumbers, respectively. Among the prediction models, CARS-least squares-support vector machine (CARS-LS-SVM) model performed best with the highest values of the coefficient of determination of prediction (Rp(2)=0.8370) and residual predictive deviation (RPD=2.4741), the lowest value of root mean square error of prediction (RMSEP=0.0841). Moreover, the number of the input variables was forty-five, which only accounts for 2.04% of that of the full wavenumbers. The results showed that FT-NIR spectral technique has the potential to be an objective and non-destructive method to detect arginine content in fermented C. sinensis mycelium. Copyright © 2015 Elsevier B.V. All rights reserved.

Tests of a habitat suitability model for black-capped chickadees

USGS Publications Warehouse

Schroeder, Richard L.

1990-01-01

The black-capped chickadee (Parus atricapillus) Habitat Suitability Index (HSI) model provides a quantitative rating of the capability of a habitat to support breeding, based on measures related to food and nest site availability. The model assumption that tree canopy volume can be predicted from measures of tree height and canopy closure was tested using data from foliage volume studies conducted in the riparian cottonwood habitat along the South Platte River in Colorado. Least absolute deviations (LAD) regression showed that canopy cover and over story tree height yielded volume predictions significantly lower than volume estimated by more direct methods. Revisions to these model relations resulted in improved predictions of foliage volume. The relation between the HSI and estimates of black-capped chickadee population densities was examined using LAD regression for both the original model and the model with the foliage volume revisions. Residuals from these models were compared to residuals from both a zero slope model and an ideal model. The fit model for the original HSI differed significantly from the ideal model, whereas the fit model for the original HSI did not differ significantly from the ideal model. However, both the fit model for the original HSI and the fit model for the revised HSI did not differ significantly from a model with a zero slope. Although further testing of the revised model is needed, its use is recommended for more realistic estimates of tree canopy volume and habitat suitability.

Active laser ranging with frequency transfer using frequency comb

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Hongyuan; Wei, Haoyun; Yang, Honglei

2016-05-02

A comb-based active laser ranging scheme is proposed for enhanced distance resolution and a common time standard for the entire system. Three frequency combs with different repetition rates are used as light sources at the two ends where the distance is measured. Pulse positions are determined through asynchronous optical sampling and type II second harmonic generation. Results show that the system achieves a maximum residual of 379.6 nm and a standard deviation of 92.9 nm with 2000 averages over 23.6 m. Moreover, as for the frequency transfer, an atom clock and an adjustable signal generator, synchronized to the atom clock, are used asmore » time standards for the two ends to appraise the frequency deviation introduced by the proposed system. The system achieves a residual fractional deviation of 1.3 × 10{sup −16} for 1 s, allowing precise frequency transfer between the two clocks at the two ends.« less

The tectonic fabric of the ocean basins

NASA Astrophysics Data System (ADS)

Matthews, Kara J.; Müller, R. Dietmar; Wessel, Paul; Whittaker, Joanne M.

2011-12-01

We present a global community data set of fracture zones (FZs), discordant zones, propagating ridges, V-shaped structures and extinct ridges, digitized from vertical gravity gradient (VGG) maps. We use a new semi-automatic FZ tracking program to test the precision of our hand-digitized traces and find a Mean Absolute Deviation of less than 3.4 km from the raw VGG minima that most clearly delineate each feature, and less than 5.4 km from the FZ location predicted by fitting model profiles to the VGG data that represent the morphology of the individual FZs. These offsets are small considering gravity data only provide an approximation for the underlying basement morphology. We further investigate the origin of non-FZ seafloor fabric by combining published abyssal hill heights computed from gravity anomalies with global half-spreading rates. A residual abyssal hill height grid, with spreading rate effects removed, combined with our interpreted tectonic fabric reveals several types of seafloor fabric distinct from typical abyssal hills. Where discordant zones do not overprint abyssal hill signals, residual abyssal hill height anomalies correspond to seafloor that accreted near mantle thermal anomalies or zones of melt-depletion. Our analysis reveals several areas where residual abyssal hill height anomalies reflect pseudo-faults and extinct ridges associated with ridge propagation and/or microplate formation in the southern Pacific Ocean.

Measurement of Enzyme Isotope Effects.

PubMed

Kholodar, Svetlana A; Ghosh, Ananda K; Kohen, Amnon

2017-01-01

Enzyme isotope effects, or the kinetic effects of "heavy" enzymes, refer to the effect of isotopically labeled protein residues on the enzyme's activity or physical properties. These effects are increasingly employed in the examination of the possible contributions of protein dynamics to enzyme catalysis. One hypothesis assumed that isotopic substitution of all 12 C, 14 N, and nonexchangeable 1 H by 13 C, 15 N, and 2 H, would slow down protein picosecond to femtosecond dynamics without any effect on the system's electrostatics following the Born-Oppenheimer approximation. It was suggested that reduced reaction rates reported for several "heavy" enzymes accords with that hypothesis. However, numerous deviations from the predictions of that hypothesis were also reported. Current studies also attempt to test the role of individual residues by site-specific labeling or by labeling a pattern of residues on activity. It appears that in several systems the protein's fast dynamics are indeed reduced in "heavy" enzymes in a way that reduces the probability of barrier crossing of its chemical step. Other observations, however, indicated that slower protein dynamics are electrostatically altered in isotopically labeled enzymes. Interestingly, these effects appear to be system dependent, thus it might be premature to suggest a general role of "heavy" enzymes' effect on catalysis. © 2017 Elsevier Inc. All rights reserved.

Evaluation of the QuEChERS Method and Gas Chromatography–Mass Spectrometry for the Analysis Pesticide Residues in Water and Sediment

PubMed Central

de Macedo, A. N.; Vicente, G. H. L.; Nogueira, A. R. A.

2010-01-01

A method for the determination of pesticide residues in water and sediment was developed using the QuEChERS method followed by gas chromatography – mass spectrometry. The method was validated in terms of accuracy, specificity, linearity, detection and quantification limits. The recovery percentages obtained for the pesticides in water at different concentrations ranged from 63 to 116%, with relative standard deviations below 12%. The corresponding results from the sediment ranged from 48 to 115% with relative standard deviations below 16%. The limits of detection for the pesticides in water and sediment were below 0.003 mg L−1 and 0.02 mg kg−1, respectively. PMID:21165598

Free flux flow in two single crystals of V3Si with slightly different pinning strengths

NASA Astrophysics Data System (ADS)

Gafarov, O.; Gapud, A. A.; Moraes, S.; Thompson, J. R.; Christen, D. K.; Reyes, A. P.

2010-10-01

Results of recent measurements on two very clean, single-crystal samples of the A15 superconductor V3Si are presented. Magnetization and transport data already confirmed the ``clean'' quality of both samples, as manifested by: (i) high residual resistivity ratio, (ii) very low critical current densities, and (iii) a ``peak'' effect in the field dependence of critical current. The (H,T) phase line for this peak effect is shifted in the slightly ``dirtier'' sample, which consequently also has higher critical current density Jc(H). High-current Lorentz forces are applied on mixed-state vortices in order to induce the highly ordered free flux flow (FFF) phase, using the same methods as in previous work. A traditional model by Bardeen and Stephen (BS) predicts a simple field dependence of flux flow resistivity ρf(H), presuming a field-independent flux core size. A model by Kogan and Zelezhina (KZ) takes core size into account, and predict a clear deviation from BS. In this study, ρf(H) is confirmed to be consistent with predictions of KZ, as will be discussed.

Numerical analysis of residual stresses in preforms of stress applying part for PANDA-type polarization maintaining optical fibers in view of technological imperfections of the doped zone geometry

NASA Astrophysics Data System (ADS)

Trufanov, Aleksandr N.; Trufanov, Nikolay A.; Semenov, Nikita V.

2016-09-01

The experimental data analysis of the stress applying rod section geometry for the PANDA-type polarization maintaining optical fiber has been performed. The dependencies of the change in the radial dimensions of the preform and the doping boundary on the angular coordinate have been obtained. The original algorithm of experimental data statistic analysis, which enables determination of the specimens' characteristic form of section, has been described. The influence of actual doped zone geometry on the residual stress fields formed during the stress rod preform fabrication has been investigated. It has been established that the deviation of the boundary between pure silica and the doped zone from the circular shape results in dissymmetry and local concentrations of the residual stress fields along the section, which can cause preforms destruction at high degrees of doping. The observed geometry deviations of up to 10% lead to the increase of the maximum stress intensity value by over 20%.

[Rapid determination of componential contents and calorific value of selected agricultural biomass feedstocks using spectroscopic technology].

PubMed

Sheng, Kui-Chuan; Shen, Ying-Ying; Yang, Hai-Qing; Wang, Wen-Jin; Luo, Wei-Qiang

2012-10-01

Rapid determination of biomass feedstock properties is of value for the production of biomass densification briquetting fuel with high quality. In the present study, visible and near-infrared (Vis-NIR) spectroscopy was employed to build prediction models of componential contents, i. e. moisture, ash, volatile matter and fixed-carbon, and calorific value of three selected species of agricultural biomass feedstock, i. e. pine wood, cedar wood, and cotton stalk. The partial least squares (PLS) cross validation results showed that compared with original reflection spectra, PLS regression models developed for first derivative spectra produced higher prediction accuracy with coefficients of determination (R2) of 0.97, 0.94 and 0.90, and residual prediction deviation (RPD) of 6.57, 4.00 and 3.01 for ash, volatile matter and moisture, respectively. Good prediction accuracy was achieved with R2 of 0.85 and RPD of 2.55 for fixed carbon, and R2 of 0.87 and RPD of 2.73 for calorific value. It is concluded that the Vis-NIR spectroscopy is promising as an alternative of traditional proximate analysis for rapid determination of componential contents and calorific value of agricultural biomass feedstock

Single-Point Mutation with a Rotamer Library Toolkit: Toward Protein Engineering.

PubMed

Pottel, Joshua; Moitessier, Nicolas

2015-12-28

Protein engineers have long been hard at work to harness biocatalysts as a natural source of regio-, stereo-, and chemoselectivity in order to carry out chemistry (reactions and/or substrates) not previously achieved with these enzymes. The extreme labor demands and exponential number of mutation combinations have induced computational advances in this domain. The first step in our virtual approach is to predict the correct conformations upon mutation of residues (i.e., rebuilding side chains). For this purpose, we opted for a combination of molecular mechanics and statistical data. In this work, we have developed automated computational tools to extract protein structural information and created conformational libraries for each amino acid dependent on a variable number of parameters (e.g., resolution, flexibility, secondary structure). We have also developed the necessary tool to apply the mutation and optimize the conformation accordingly. For side-chain conformation prediction, we obtained overall average root-mean-square deviations (RMSDs) of 0.91 and 1.01 Å for the 18 flexible natural amino acids within two distinct sets of over 3000 and 1500 side-chain residues, respectively. The commonly used dihedral angle differences were also evaluated and performed worse than the state of the art. These two metrics are also compared. Furthermore, we generated a family-specific library for kinases that produced an average 2% lower RMSD upon side-chain reconstruction and a residue-specific library that yielded a 17% improvement. Ultimately, since our protein engineering outlook involves using our docking software, Fitted/Impacts, we applied our mutation protocol to a benchmarked data set for self- and cross-docking. Our side-chain reconstruction does not hinder our docking software, demonstrating differences in pose prediction accuracy of approximately 2% (RMSD cutoff metric) for a set of over 200 protein/ligand structures. Similarly, when docking to a set of over 100 kinases, side-chain reconstruction (using both general and biased conformation libraries) had minimal detriment to the docking accuracy.

Developing and Applying Control Charts to Detect Change Water Chemistry Parameters Measured in the Athabasca River Near the Oil Sands: A Tool for Surveillance Monitoring.

PubMed

Arciszewski, Tim J; Hazewinkel, Rod R; Munkittrick, Kelly R; Kilgour, Bruce W

2018-05-10

Control charting is a simple technique to identify change and is well-suited for use in water quality programs. Control charts accounting for co-variation associated with discharge and time were used to explore example and representative variables routinely measured in the Athabasca River near the oil sands area for indications of change, including 5 major ions (chloride, sodium, sulphate, calcium, magnesium), 5 total metals (aluminum, iron, thallium, molybdenum, vanadium) and total suspended solids (TSS). Regression equations developed from reference data (1988-2009) were used to predict observations and calculate residuals from later test observations (2010-2016). Evidence of change was sought in the deviation of residual errors from the test period compared to the patterns expected and defined from probability distributions of the reference residuals using the Odds Ratio. In most cases, the patterns in test residuals were not statistically different from those expected from the reference period, especially when data was examined annually. However, some differences were apparent and more differences were apparent as data accumulated and was analysed over time. In sum, the analyses suggest higher concentrations than predicted in most major ions, but the source of the changes is uncertain. In contrast, most metals were lower than expected and may be related to changing deposition patterns of materials or weathering of minerals during construction activities of the 2000's which influence the reference data used. The analyses also suggest alternative approaches may be necessary to understand change in some variables. Despite this, the results support the use of control charts to detect changes in water chemistry parameters and the value of the tool in surveillance phases of long-term and adaptive monitoring programs. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

TOUCHSTONE II: a new approach to ab initio protein structure prediction.

PubMed

Zhang, Yang; Kolinski, Andrzej; Skolnick, Jeffrey

2003-08-01

We have developed a new combined approach for ab initio protein structure prediction. The protein conformation is described as a lattice chain connecting C(alpha) atoms, with attached C(beta) atoms and side-chain centers of mass. The model force field includes various short-range and long-range knowledge-based potentials derived from a statistical analysis of the regularities of protein structures. The combination of these energy terms is optimized through the maximization of correlation for 30 x 60,000 decoys between the root mean square deviation (RMSD) to native and energies, as well as the energy gap between native and the decoy ensemble. To accelerate the conformational search, a newly developed parallel hyperbolic sampling algorithm with a composite movement set is used in the Monte Carlo simulation processes. We exploit this strategy to successfully fold 41/100 small proteins (36 approximately 120 residues) with predicted structures having a RMSD from native below 6.5 A in the top five cluster centroids. To fold larger-size proteins as well as to improve the folding yield of small proteins, we incorporate into the basic force field side-chain contact predictions from our threading program PROSPECTOR where homologous proteins were excluded from the data base. With these threading-based restraints, the program can fold 83/125 test proteins (36 approximately 174 residues) with structures having a RMSD to native below 6.5 A in the top five cluster centroids. This shows the significant improvement of folding by using predicted tertiary restraints, especially when the accuracy of side-chain contact prediction is >20%. For native fold selection, we introduce quantities dependent on the cluster density and the combination of energy and free energy, which show a higher discriminative power to select the native structure than the previously used cluster energy or cluster size, and which can be used in native structure identification in blind simulations. These procedures are readily automated and are being implemented on a genomic scale.

Qualitative Fault Isolation of Hybrid Systems: A Structural Model Decomposition-Based Approach

NASA Technical Reports Server (NTRS)

Bregon, Anibal; Daigle, Matthew; Roychoudhury, Indranil

2016-01-01

Quick and robust fault diagnosis is critical to ensuring safe operation of complex engineering systems. A large number of techniques are available to provide fault diagnosis in systems with continuous dynamics. However, many systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete behavioral modes, each with its own continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task computationally more complex due to the large number of possible system modes and the existence of autonomous mode transitions. This paper presents a qualitative fault isolation framework for hybrid systems based on structural model decomposition. The fault isolation is performed by analyzing the qualitative information of the residual deviations. However, in hybrid systems this process becomes complex due to possible existence of observation delays, which can cause observed deviations to be inconsistent with the expected deviations for the current mode in the system. The great advantage of structural model decomposition is that (i) it allows to design residuals that respond to only a subset of the faults, and (ii) every time a mode change occurs, only a subset of the residuals will need to be reconfigured, thus reducing the complexity of the reasoning process for isolation purposes. To demonstrate and test the validity of our approach, we use an electric circuit simulation as the case study.

Capillary pressure-saturation relations in quartz and carbonate sands: Limitations for correlating capillary and wettability influences on air, oil, and supercritical CO2 trapping

NASA Astrophysics Data System (ADS)

Wang, Shibo; Tokunaga, Tetsu K.; Wan, Jiamin; Dong, Wenming; Kim, Yongman

2016-08-01

Capillary pressure (Pc)-saturation (Sw) relations are essential for predicting equilibrium and flow of immiscible fluid pairs in soils and deeper geologic formations. In systems that are difficult to measure, behavior is often estimated based on capillary scaling of easily measured Pc-Sw relations (e.g., air-water, and oil-water), yet the reliability of such approximations needs to be examined. In this study, 17 sets of brine drainage and imbibition curves were measured with air-brine, decane-brine, and supercritical (sc) CO2-brine in homogeneous quartz and carbonate sands, using porous plate systems under ambient (0.1 MPa, 23°C) and reservoir (12.0 MPa, 45°C) conditions. Comparisons between these measurements showed significant differences in residual nonwetting phase saturation, Snw,r. Through applying capillary scaling, changes in interfacial properties were indicated, particularly wettability. With respect to the residual trapping of the nonwetting phases, Snwr, CO2 > Snwr, decane > Snwr, air. Decane-brine and scCO2-brine Pc-Sw curves deviated significantly from predictions assuming hydrophilic interactions. Moreover, neither the scaled capillary behavior nor Snw,r for scCO2-brine were well represented by decane-brine, apparently because of differences in wettability and viscosities, indicating limitations for using decane (and other organic liquids) as a surrogate fluid in studies intended to apply to geological carbon sequestration. Thus, challenges remain in applying scaling for predicting capillary trapping and multiphase displacement processes across such diverse fields as vadose zone hydrology, enhanced oil recovery, and geologic carbon sequestration.

Capillary pressure - saturation relations in quartz and carbonate sands: Limitations for correlating capillary and wettability influences on air, oil, and supercritical CO2 trapping

NASA Astrophysics Data System (ADS)

Tokunaga, T. K.; Wang, S.; Wan, J.; Dong, W.; Kim, Y.

2016-12-01

Capillary pressure (Pc) - saturation (Sw) relations are essential for predicting equilibrium and flow of immiscible fluid pairs in soils and deeper geologic formations. In systems that are difficult to measure, behavior is often estimated based on capillary scaling of easily measured Pc-Sw relations (e.g., air-water, and oil-water), yet the reliability of such approximations needs to be examined. In this study, seventeen sets of brine drainage and imbibition curves were measured with air-brine, decane-brine, and supercritical (sc) CO2-brine in homogeneous quartz and carbonate sands, using porous plate systems under ambient (0.1 MPa, 23 °C) and reservoir (12.0 MPa, 45 °C) conditions. Comparisons between these measurements showed significant differences in residual nonwetting phase saturation, Snw,r. Through applying capillary scaling, changes in interfacial properties were indicated, particularly wettability. With respect to the residual trapping of the nonwetting phases, Snwr, CO2 > Snwr, decane > Snwr, air. Decane-brine and scCO2-brine Pc-Sw curves deviated significantly from predictions assuming hydrophilic interactions. Moreover, neither the scaled capillary behavior nor Snw,r for scCO2-brine were well represented by decane-brine, apparently because of differences in wettability and viscosities, indicating limitations for using decane (and other organic liquids) as a surrogate fluid in studies intended to apply to geological carbon sequestration. Thus, challenges remain in applying scaling for predicting capillary trapping and multiphase displacement processes across such diverse fields as vadose zone hydrology, enhanced oil recovery, and geologic carbon sequestration.

Physicochemical characterization of Lavandula spp. honey with FT-Raman spectroscopy.

PubMed

Anjos, Ofélia; Santos, António J A; Paixão, Vasco; Estevinho, Letícia M

2018-02-01

This study aimed to evaluate the potential of FT-Raman spectroscopy in the prediction of the chemical composition of Lavandula spp. monofloral honey. Partial Least Squares (PLS) regression models were performed for the quantitative estimation and the results were correlated with those obtained using reference methods. Good calibration models were obtained for electrical conductivity, ash, total acidity, pH, reducing sugars, hydroxymethylfurfural (HMF), proline, diastase index, apparent sucrose, total flavonoids content and total phenol content. On the other hand, the model was less accurate for pH determination. The calibration models had high r 2 (ranging between 92.8% and 99.9%), high residual prediction deviation - RPD (ranging between 4.2 and 26.8) and low root mean square errors. These results confirm the hypothesis that FT-Raman is a useful technique for the quality control and chemical properties' evaluation of Lavandula spp honey. Its application may allow improving the efficiency, speed and cost of the current laboratory analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

NGA-West 2 Equations for predicting PGA, PGV, and 5%-Damped PSA for shallow crustal earthquakes

USGS Publications Warehouse

Boore, David M.; Stewart, Jon P.; Seyhan, Emel; Atkinson, Gail M.

2013-01-01

We provide ground-motion prediction equations for computing medians and standard deviations of average horizontal component intensity measures (IMs) for shallow crustal earthquakes in active tectonic regions. The equations were derived from a global database with M 3.0–7.9 events. We derived equations for the primary M- and distance-dependence of the IMs after fixing the VS30-based nonlinear site term from a parallel NGA-West 2 study. We then evaluated additional effects using mixed effects residuals analysis, which revealed no trends with source depth over the M range of interest, indistinct Class 1 and 2 event IMs, and basin depth effects that increase and decrease long-period IMs for depths larger and smaller, respectively, than means from regional VS30-depth relations. Our aleatory variability model captures decreasing between-event variability with M, as well as within-event variability that increases or decreases with M depending on period, increases with distance, and decreases for soft sites.

Sarcopenia-related parameters and incident disability in older persons: results from the "invecchiare in Chianti" study.

PubMed

Cesari, Matteo; Rolland, Yves; Abellan Van Kan, Gabor; Bandinelli, Stefania; Vellas, Bruno; Ferrucci, Luigi

2015-04-01

Current operational definitions of sarcopenia are based on algorithms' simultaneous considering measures of skeletal muscle mass and muscle-specific as well as global function. We hypothesize that quantitative and qualitative sarcopenia-related parameters may not be equally predictive of incident disability, thus presenting different clinical relevance. Data are from 922 elder adults (mean age = 73.9 years) with no activities of daily living (ADL) impairment recruited in the "Invecchiare in Chianti" study. Incident disability in ≥1 ADL defined the outcome of interest. The specific capacities of following sarcopenia-related parameters at predicting incident ADL disability were compared: residuals of skeletal muscle mass, fat-adjusted residuals of skeletal muscle mass, muscle density, ankle extension strength, ratio ankle extension strength/muscle mass, gait speed, and handgrip strength. During the follow-up (median = 9.1 years), 188 (20.4%) incident ADL disability events were reported. Adjusted models showed that only gait speed was significantly associated with the outcome in both men (per standard deviation [SD] = 0.23 m/s increase, hazard ratio [HR] = 0.46, 95% confidence interval [CI] = 0.33-0.63; p < .001) and women (per SD = 0.24 m/s increase, HR = 0.64, 95% CI = 0.50-0.82; p < .001). In women, the fat-adjusted lean mass residual (per SD = 4.41 increase, HR = 0.79, 95% CI = 0.65-0.96; p = .02) and muscle density (per SD = 3.60 increase, HR = 0.76, 95% CI = 0.61-0.93; p = .01) were the only other parameters that predicted disability. In men, several of the tested variables (except muscle mass measures) reported significant results. Gender strongly influences which sarcopenia-related parameters predict disability. Gait speed was a powerful predictor of disability in both men and women, but its nonmuscle-specific nature should impose caution about its inclusion in definitions of sarcopenia. © The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Identification of residue pairing in interacting β-strands from a predicted residue contact map.

PubMed

Mao, Wenzhi; Wang, Tong; Zhang, Wenxuan; Gong, Haipeng

2018-04-19

Despite the rapid progress of protein residue contact prediction, predicted residue contact maps frequently contain many errors. However, information of residue pairing in β strands could be extracted from a noisy contact map, due to the presence of characteristic contact patterns in β-β interactions. This information may benefit the tertiary structure prediction of mainly β proteins. In this work, we propose a novel ridge-detection-based β-β contact predictor to identify residue pairing in β strands from any predicted residue contact map. Our algorithm RDb 2 C adopts ridge detection, a well-developed technique in computer image processing, to capture consecutive residue contacts, and then utilizes a novel multi-stage random forest framework to integrate the ridge information and additional features for prediction. Starting from the predicted contact map of CCMpred, RDb 2 C remarkably outperforms all state-of-the-art methods on two conventional test sets of β proteins (BetaSheet916 and BetaSheet1452), and achieves F1-scores of ~ 62% and ~ 76% at the residue level and strand level, respectively. Taking the prediction of the more advanced RaptorX-Contact as input, RDb 2 C achieves impressively higher performance, with F1-scores reaching ~ 76% and ~ 86% at the residue level and strand level, respectively. In a test of structural modeling using the top 1 L predicted contacts as constraints, for 61 mainly β proteins, the average TM-score achieves 0.442 when using the raw RaptorX-Contact prediction, but increases to 0.506 when using the improved prediction by RDb 2 C. Our method can significantly improve the prediction of β-β contacts from any predicted residue contact maps. Prediction results of our algorithm could be directly applied to effectively facilitate the practical structure prediction of mainly β proteins. All source data and codes are available at http://166.111.152.91/Downloads.html or the GitHub address of https://github.com/wzmao/RDb2C .

Prediction of Protein Modification Sites of Pyrrolidone Carboxylic Acid Using mRMR Feature Selection and Analysis

PubMed Central

Zheng, Lu-Lu; Niu, Shen; Hao, Pei; Feng, KaiYan; Cai, Yu-Dong; Li, Yixue

2011-01-01

Pyrrolidone carboxylic acid (PCA) is formed during a common post-translational modification (PTM) of extracellular and multi-pass membrane proteins. In this study, we developed a new predictor to predict the modification sites of PCA based on maximum relevance minimum redundancy (mRMR) and incremental feature selection (IFS). We incorporated 727 features that belonged to 7 kinds of protein properties to predict the modification sites, including sequence conservation, residual disorder, amino acid factor, secondary structure and solvent accessibility, gain/loss of amino acid during evolution, propensity of amino acid to be conserved at protein-protein interface and protein surface, and deviation of side chain carbon atom number. Among these 727 features, 244 features were selected by mRMR and IFS as the optimized features for the prediction, with which the prediction model achieved a maximum of MCC of 0.7812. Feature analysis showed that all feature types contributed to the modification process. Further site-specific feature analysis showed that the features derived from PCA's surrounding sites contributed more to the determination of PCA sites than other sites. The detailed feature analysis in this paper might provide important clues for understanding the mechanism of the PCA formation and guide relevant experimental validations. PMID:22174779

RRCRank: a fusion method using rank strategy for residue-residue contact prediction.

PubMed

Jing, Xiaoyang; Dong, Qiwen; Lu, Ruqian

2017-09-02

In structural biology area, protein residue-residue contacts play a crucial role in protein structure prediction. Some researchers have found that the predicted residue-residue contacts could effectively constrain the conformational search space, which is significant for de novo protein structure prediction. In the last few decades, related researchers have developed various methods to predict residue-residue contacts, especially, significant performance has been achieved by using fusion methods in recent years. In this work, a novel fusion method based on rank strategy has been proposed to predict contacts. Unlike the traditional regression or classification strategies, the contact prediction task is regarded as a ranking task. First, two kinds of features are extracted from correlated mutations methods and ensemble machine-learning classifiers, and then the proposed method uses the learning-to-rank algorithm to predict contact probability of each residue pair. First, we perform two benchmark tests for the proposed fusion method (RRCRank) on CASP11 dataset and CASP12 dataset respectively. The test results show that the RRCRank method outperforms other well-developed methods, especially for medium and short range contacts. Second, in order to verify the superiority of ranking strategy, we predict contacts by using the traditional regression and classification strategies based on the same features as ranking strategy. Compared with these two traditional strategies, the proposed ranking strategy shows better performance for three contact types, in particular for long range contacts. Third, the proposed RRCRank has been compared with several state-of-the-art methods in CASP11 and CASP12. The results show that the RRCRank could achieve comparable prediction precisions and is better than three methods in most assessment metrics. The learning-to-rank algorithm is introduced to develop a novel rank-based method for the residue-residue contact prediction of proteins, which achieves state-of-the-art performance based on the extensive assessment.

Residual symptoms after surgery for unilateral congenital superior oblique palsy.

PubMed

Caca, Ihsan; Sahin, Alparslan; Cingu, Abdullah; Ari, Seyhmus; Akbas, Umut

2012-01-01

To establish the surgical results and residual symptoms in 48 cases with unilateral congenital superior oblique muscle palsy that had surgical intervention to the vertical muscles alone. Myectomy and concomitant disinsertion of the inferior oblique (IO) muscle was performed in 38 cases and myectomy and concomitant IO disinsertion and recession of the superior rectus muscle in the ipsilateral eye was performed in 10 cases. The preoperative and postoperative vertical deviation values and surgical results were compared. Of the patients who had myectomy and concomitant IO disinsertion, 74% achieved an "excellent" result, 21% a "good" result, and 5% a "poor" result postoperatively. The difference in deviation between preoperative and postoperative values was statistically significant (P < .001). Of the patients who had myectomy and concomitant inferior oblique disinsertion and ipsilateral superior rectus recession, 50% achieved an "excellent" result, 20% a "good" result, and 30% a "poor" result postoperatively. The difference in deviation between preoperative and postoperative values was statistically significant (P < .001). Both procedures are effective and successful in patients with superior oblique muscle palsy, but a secondary surgery may be required. Copyright 2012, SLACK Incorporated.

Incremental Sampling Methodology (ISM) for Metallic Residues

DTIC Science & Technology

2013-08-01

Deviation (also %RSD) Sb Antimony Sn Tin Sr Strontium STD Standard Deviation ERDC TR-13-5 x SU Sampling Unit Ti Titanium UCL Upper Confidence Limit...Ce), chromium (Cr), Cu, Fe, Pb, mag- nesium (Mg), Mn, potassium (K), sodium (Na), strontium (Sr), titanium (Ti), W, zirconium (Zr), and Zn (Clausen...wastes. A proposed alternative to EPA SW 846 Method 3050. Environmental Science and Technology 23: 89 −900. Matzke, B., N. Hassig, J. Wilson, R. Gilber

Spin distributions and cross sections of evaporation residues in the 28Si+176Yb reaction

NASA Astrophysics Data System (ADS)

Sudarshan, K.; Tripathi, R.; Sodaye, S.; Sharma, S. K.; Pujari, P. K.; Gehlot, J.; Madhavan, N.; Nath, S.; Mohanto, G.; Mukul, I.; Jhingan, A.; Mazumdar, I.

2017-02-01

Background: Non-compound-nucleus fission in the preactinide region has been an active area of investigation in the recent past. Based on the measurements of fission-fragment mass distributions in the fission of 202Po, populated by reactions with varying entrance channel mass asymmetry, the onset of non-compound-nucleus fission was proposed to be around ZpZt˜1000 [Phys. Rev. C 77, 024606 (2008), 10.1103/PhysRevC.77.024606], where Zp and Zt are the projectile and target proton numbers, respectively. Purpose: The present paper is aimed at the measurement of cross sections and spin distributions of evaporation residues in the 28Si+176Yb reaction (ZpZt=980 ) to investigate the fusion hindrance which, in turn, would give information about the contribution from non-compound-nucleus fission in this reaction. Method: Evaporation-residue cross sections were measured in the beam energy range of 129-166 MeV using the hybrid recoil mass analyzer (HYRA) operated in the gas-filled mode. Evaporation-residue cross sections were also measured by the recoil catcher technique followed by off-line γ -ray spectrometry at few intermediate energies. γ -ray multiplicities of evaporation residues were measured to infer about their spin distribution. The measurements were carried out using NaI(Tl) detector-based 4π-spin spectrometer from the Tata Institute of Fundamental Research, Mumbai, coupled to the HYRA. Results: Evaporation-residue cross sections were significantly lower compared to those calculated using the statistical model code pace2 [Phys. Rev. C 21, 230 (1980), 10.1103/PhysRevC.21.230] with the coupled-channel fusion model code ccfus [Comput. Phys. Commun. 46, 187 (1987), 10.1016/0010-4655(87)90045-2] at beam energies close to the entrance channel Coulomb barrier. At higher beam energies, experimental cross sections were close to those predicted by the model. Average γ -ray multiplicities or angular momentum values of evaporation residues were in agreement with the calculations of the code ccfus + pace2 within the experimental uncertainties at all the beam energies. Conclusions: Deviation of evaporation-residue cross sections from the "fusion + statistical model" predictions at beam energies close to the entrance channel Coulomb barrier indicates fusion hindrance at these beam energies which would lead to non-compound-nucleus fission. However, reasonable agreement of average angular momentum values of evaporation residues at these beam energies with those calculated using the coupled-channel fusion model with the statistical model codes ccfus + pace2 suggests that fusion suppression at beam energies close to the entrance channel Coulomb barrier where populated l waves are low is not l dependent.

Pulmonary Hyperinflation and Left Ventricular Mass

PubMed Central

Smith, Benjamin M; Kawut, Steven M.; Bluemke, David A; Basner, Robert C; Gomes, Antoinette S; Hoffman, Eric; Kalhan, Ravi; Lima, João AC; Liu, Chia-Ying; Michos, Erin D; Prince, Martin R; Rabbani, LeRoy; Rabinowitz, Daniel; Shimbo, Daichi; Shea, Steven; Barr, R Graham

2013-01-01

Background Left ventricular (LV) mass is an important predictor of heart failure and cardiovascular mortality, yet determinants of LV mass are incompletely understood. Pulmonary hyperinflation in chronic obstructive pulmonary disease (COPD) may contribute to changes in intrathoracic pressure that increase LV wall stress. We therefore hypothesized that residual lung volume in COPD would be associated with greater LV mass. Methods and results The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study recruited smokers aged 50–79 years who were free of clinical cardiovascular disease. LV mass was measured by cardiac magnetic resonance. Pulmonary function testing was performed according to guidelines. Regression models were used to adjust for age, sex, body size, blood pressure and other cardiac risk factors. Among 119 MESA COPD Study participants, mean age was 69±6 years, 55% were male and 65% had COPD, mostly of mild or moderate severity. Mean LV mass was 128±34 grams. Residual lung volume was independently associated with greater LV mass (7.2 grams per standard deviation increase in residual volume; 95% CI 2.2 to 12; P=0.004), and was similar in magnitude to that of systolic blood pressure (7.6 grams per standard deviation increase in systolic blood pressure, 95% CI 4.3 to 11 grams; p<0.001). Similar results were observed for LV mass to end-diastolic volume ratio (p=0.02) and with hyperinflation measured as residual volume to total lung capacity ratio (P=0.009). Conclusions Pulmonary hyperinflation, as measured by residual lung volume or residual lung volume to total lung capacity ratio, is associated with greater LV mass. PMID:23493320

Determination of cyflumetofen residue in water, soil, and fruits by modified quick, easy, cheap, effective, rugged, and safe method coupled to gas chromatography/tandem mass spectrometry.

PubMed

Li, Minmin; Liu, Xingang; Dong, Fengshou; Xu, Jun; Qin, Dongmei; Zheng, Yongquan

2012-10-01

A new, highly sensitive, and selective method was developed for the determination of the cyflumetofen residue in water, soil, and fruits by using gas chromatography quadruple mass spectrometry. The target compound was extracted using acetonitrile and then cleaned up using dispersive solid-phase extraction with primary and secondary amine and graphitized carbon black, and optionally by a freezing-out cleanup step. The matrix-matched standards gave satisfactory recoveries and relative standard deviation values in different matrices at three fortified levels (0.05, 0.5, and 1.0 mg kg(-1) ). The overall average recoveries for this method in water, soil, and all fruits matrix at three fortified levels ranged from 76.3 to 101.5% with relative standard deviations in the range of 1.2-11.8% (n = 5). The calculated limits of detection and quantification were typically below 0.005 and 0.015 μg kg(-1), which were much lower than the maximum residue levels established by Japanese Positive List. This study provides a theoretical basis for China to draw up maximum residue level and analytical method for cyflumetofen acaricide in different fruits. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Residual standard deviation: Validation of a new measure of dual-task cost in below-knee prosthesis users.

PubMed

Howard, Charla L; Wallace, Chris; Abbas, James; Stokic, Dobrivoje S

2017-01-01

We developed and evaluated properties of a new measure of variability in stride length and cadence, termed residual standard deviation (RSD). To calculate RSD, stride length and cadence are regressed against velocity to derive the best fit line from which the variability (SD) of the distance between the actual and predicted data points is calculated. We examined construct, concurrent, and discriminative validity of RSD using dual-task paradigm in 14 below-knee prosthesis users and 13 age- and education-matched controls. Subjects walked first over an electronic walkway while performing separately a serial subtraction and backwards spelling task, and then at self-selected slow, normal, and fast speeds used to derive the best fit line for stride length and cadence against velocity. Construct validity was demonstrated by significantly greater increase in RSD during dual-task gait in prosthesis users than controls (group-by-condition interaction, stride length p=0.0006, cadence p=0.009). Concurrent validity was established against coefficient of variation (CV) by moderate-to-high correlations (r=0.50-0.87) between dual-task cost RSD and dual-task cost CV for both stride length and cadence in prosthesis users and controls. Discriminative validity was documented by the ability of dual-task cost calculated from RSD to effectively differentiate prosthesis users from controls (area under the receiver operating characteristic curve, stride length 0.863, p=0.001, cadence 0.808, p=0.007), which was better than the ability of dual-task cost CV (0.692, 0.648, respectively, not significant). These results validate RSD as a new measure of variability in below-knee prosthesis users. Future studies should include larger cohorts and other populations to ascertain its generalizability. Copyright © 2016 Elsevier B.V. All rights reserved.

Residual oxygen time model for oxygen partial pressure near 130 kPa (1.3 atm).

PubMed

Shykoff, Barbara E

2015-01-01

A two-part residual oxygen time model predicts the probability of detectible pulmonary oxygen toxicity P(P[O2tox]) after dives with oxygen partial pressure (PO2) approximately 130 kPa, and provides a tool to plan dive series with selected risk of P[O2tox]. Data suggest that pulmonary oxygen injury at this PO2 is additive between dives. Recovery begins after a delay and continues during any following dive. A logistic relation expresses P(P[O2tox]) as a function of dive duration (T(dur)) [hours]: P(P[O2tox]) = 100/[1+exp (3.586-0.49 x T(dur))] This expression maps T(dur) to P(P[O2tox]) or, in the linear mid-portion of the curve, P(P[O2tox]) usefully to T(dur). For multiple dives or during recovery, it maps to an equivalent dive duration, T(eq). T(eq) was found after second dives of duration T(dur 2). Residual time from the first dive t(r) = T(eq) - T(dur2). With known t(r), t and T(dur) a recovery model was fitted. t(r) = T(dur) x exp [-k x((t-5)/T(dur)2], where t = t - 5 hours, k = 0.149 for resting, and 0.047 for exercising divers, and t represents time after surfacing. The fits were assessed for 1,352 man-dives. Standard deviations of the residuals were 8.5% and 18.3% probability for resting or exercise dives, respectively.

Prediction of the Possibility a Right-Turn Driving Behavior at Intersection Leads to an Accident by Detecting Deviation of the Situation from Usual when the Behavior is Observed

NASA Astrophysics Data System (ADS)

Hayashi, Toshinori; Yamada, Keiichi

Deviation of driving behavior from usual could be a sign of human error that increases the risk of traffic accidents. This paper proposes a novel method for predicting the possibility a driving behavior leads to an accident from the information on the driving behavior and the situation. In a previous work, a method of predicting the possibility by detecting the deviation of driving behavior from usual one in that situation has been proposed. In contrast, the method proposed in this paper predicts the possibility by detecting the deviation of the situation from usual one when the behavior is observed. An advantage of the proposed method is the number of the required models is independent of the variety of the situations. The method was applied to a problem of predicting accidents by right-turn driving behavior at an intersection, and the performance of the method was evaluated by experiments on a driving simulator.

Research on wind field algorithm of wind lidar based on BP neural network and grey prediction

NASA Astrophysics Data System (ADS)

Chen, Yong; Chen, Chun-Li; Luo, Xiong; Zhang, Yan; Yang, Ze-hou; Zhou, Jie; Shi, Xiao-ding; Wang, Lei

2018-01-01

This paper uses the BP neural network and grey algorithm to forecast and study radar wind field. In order to reduce the residual error in the wind field prediction which uses BP neural network and grey algorithm, calculating the minimum value of residual error function, adopting the residuals of the gray algorithm trained by BP neural network, using the trained network model to forecast the residual sequence, using the predicted residual error sequence to modify the forecast sequence of the grey algorithm. The test data show that using the grey algorithm modified by BP neural network can effectively reduce the residual value and improve the prediction precision.

Prediction of Ba, Co and Ni for tropical soils using diffuse reflectance spectroscopy and X-ray fluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Arantes Camargo, Livia; Marques Júnior, José; Reynaldo Ferracciú Alleoni, Luís; Tadeu Pereira, Gener; De Bortoli Teixeira, Daniel; Santos Rabelo de Souza Bahia, Angélica

2017-04-01

Environmental impact assessments may be assisted by spatial characterization of potentially toxic elements (PTEs). Diffuse reflectance spectroscopy (DRS) and X-ray fluorescence spectroscopy (XRF) are rapid, non-destructive, low-cost, prediction tools for a simultaneous characterization of different soil attributes. Although low concentrations of PTEs might preclude the observation of spectral features, their contents can be predicted using spectroscopy by exploring the existing relationship between the PTEs and soil attributes with spectral features. This study aimed to evaluate, in three geomorphic surfaces of Oxisols, the capacity for predicting PTEs (Ba, Co, and Ni) and their spatial variability by means of diffuse reflectance spectroscopy (DRS) and X-ray fluorescence spectroscopy (XRF). For that, soil samples were collected from three geomorphic surfaces and analyzed for chemical, physical, and mineralogical properties, and then analyzed in DRS (visible + near infrared - VIS+NIR and medium infrared - MIR) and XRF equipment. PTE prediction models were calibrated using partial least squares regression (PLSR). PTE spatial distribution maps were built using the values calculated by the calibrated models that reached the best accuracy using geostatistics. PTE prediction models were satisfactorily calibrated using MIR DRS for Ba, and Co (residual prediction deviation - RPD > 3.0), Vis DRS for Ni (RPD > 2.0) and FRX for all the studied PTEs (RPD > 1.8). DRS- and XRF-predicted values allowed the characterization and the understanding of spatial variability of the studied PTEs.

ST-segment resolution with bivalirudin versus heparin and routine glycoprotein IIb/IIIa inhibitors started in the ambulance in ST-segment elevation myocardial infarction patients transported for primary percutaneous coronary intervention: The EUROMAX ST-segment resolution substudy.

PubMed

Van't Hof, Arnoud; Giannini, Francesco; Ten Berg, Jurrien; Tolsma, Rudolf; Clemmensen, Peter; Bernstein, Debra; Coste, Pierre; Goldstein, Patrick; Zeymer, Uwe; Hamm, Christian; Deliargyris, Efthymios; Steg, Philippe G

2017-08-01

Myocardial reperfusion after primary percutaneous coronary intervention (PCI) can be assessed by the extent of post-procedural ST-segment resolution. The European Ambulance Acute Coronary Syndrome Angiography (EUROMAX) trial compared pre-hospital bivalirudin and pre-hospital heparin or enoxaparin with or without GPIIb/IIIa inhibitors (GPIs) in primary PCI. This nested substudy was performed in centres routinely using pre-hospital GPI in order to compare the impact of randomized treatments on ST-resolution after primary PCI. Residual cumulative ST-segment deviation on the single one hour post-procedure electrocardiogram (ECG) was assessed by an independent core laboratory and was the primary endpoint. It was calculated that 762 evaluable patients were needed to show non-inferiority (85% power, alpha 2.5%) between randomized treatments. A total of 871 participated with electrocardiographic data available in 824 patients (95%). Residual ST-segment deviation one hour after PCI was 3.8±4.9 mm versus 3.9±5.2 mm for bivalirudin and heparin+GPI, respectively ( p=0.0019 for non-inferiority). Overall, there were no differences between randomized treatments in any measures of ST-segment resolution either before or after the index procedure. Pre-hospital treatment with bivalirudin is non-inferior to pre-hospital heparin + GPI with regard to residual ST-segment deviation or ST-segment resolution, reflecting comparable myocardial reperfusion with the two strategies.

A study of respiration-correlated cone-beam CT scans to correct target positioning errors in radiotherapy of thoracic cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Santoro, J. P.; McNamara, J.; Yorke, E.

2012-10-15

Purpose: There is increasingly widespread usage of cone-beam CT (CBCT) for guiding radiation treatment in advanced-stage lung tumors, but difficulties associated with daily CBCT in conventionally fractionated treatments include imaging dose to the patient, increased workload and longer treatment times. Respiration-correlated cone-beam CT (RC-CBCT) can improve localization accuracy in mobile lung tumors, but further increases the time and workload for conventionally fractionated treatments. This study investigates whether RC-CBCT-guided correction of systematic tumor deviations in standard fractionated lung tumor radiation treatments is more effective than 2D image-based correction of skeletal deviations alone. A second study goal compares respiration-correlated vs respiration-averaged imagesmore » for determining tumor deviations. Methods: Eleven stage II-IV nonsmall cell lung cancer patients are enrolled in an IRB-approved prospective off-line protocol using RC-CBCT guidance to correct for systematic errors in GTV position. Patients receive a respiration-correlated planning CT (RCCT) at simulation, daily kilovoltage RC-CBCT scans during the first week of treatment and weekly scans thereafter. Four types of correction methods are compared: (1) systematic error in gross tumor volume (GTV) position, (2) systematic error in skeletal anatomy, (3) daily skeletal corrections, and (4) weekly skeletal corrections. The comparison is in terms of weighted average of the residual GTV deviations measured from the RC-CBCT scans and representing the estimated residual deviation over the treatment course. In the second study goal, GTV deviations computed from matching RCCT and RC-CBCT are compared to deviations computed from matching respiration-averaged images consisting of a CBCT reconstructed using all projections and an average-intensity-projection CT computed from the RCCT. Results: Of the eleven patients in the GTV-based systematic correction protocol, two required no correction, seven required a single correction, one required two corrections, and one required three corrections. Mean residual GTV deviation (3D distance) following GTV-based systematic correction (mean {+-} 1 standard deviation 4.8 {+-} 1.5 mm) is significantly lower than for systematic skeletal-based (6.5 {+-} 2.9 mm, p= 0.015), and weekly skeletal-based correction (7.2 {+-} 3.0 mm, p= 0.001), but is not significantly lower than daily skeletal-based correction (5.4 {+-} 2.6 mm, p= 0.34). In two cases, first-day CBCT images reveal tumor changes-one showing tumor growth, the other showing large tumor displacement-that are not readily observed in radiographs. Differences in computed GTV deviations between respiration-correlated and respiration-averaged images are 0.2 {+-} 1.8 mm in the superior-inferior direction and are of similar magnitude in the other directions. Conclusions: An off-line protocol to correct GTV-based systematic error in locally advanced lung tumor cases can be effective at reducing tumor deviations, although the findings need confirmation with larger patient statistics. In some cases, a single cone-beam CT can be useful for assessing tumor changes early in treatment, if more than a few days elapse between simulation and the start of treatment. Tumor deviations measured with respiration-averaged CT and CBCT images are consistent with those measured with respiration-correlated images; the respiration-averaged method is more easily implemented in the clinic.« less

EL_PSSM-RT: DNA-binding residue prediction by integrating ensemble learning with PSSM Relation Transformation.

PubMed

Zhou, Jiyun; Lu, Qin; Xu, Ruifeng; He, Yulan; Wang, Hongpeng

2017-08-29

Prediction of DNA-binding residue is important for understanding the protein-DNA recognition mechanism. Many computational methods have been proposed for the prediction, but most of them do not consider the relationships of evolutionary information between residues. In this paper, we first propose a novel residue encoding method, referred to as the Position Specific Score Matrix (PSSM) Relation Transformation (PSSM-RT), to encode residues by utilizing the relationships of evolutionary information between residues. PDNA-62 and PDNA-224 are used to evaluate PSSM-RT and two existing PSSM encoding methods by five-fold cross-validation. Performance evaluations indicate that PSSM-RT is more effective than previous methods. This validates the point that the relationship of evolutionary information between residues is indeed useful in DNA-binding residue prediction. An ensemble learning classifier (EL_PSSM-RT) is also proposed by combining ensemble learning model and PSSM-RT to better handle the imbalance between binding and non-binding residues in datasets. EL_PSSM-RT is evaluated by five-fold cross-validation using PDNA-62 and PDNA-224 as well as two independent datasets TS-72 and TS-61. Performance comparisons with existing predictors on the four datasets demonstrate that EL_PSSM-RT is the best-performing method among all the predicting methods with improvement between 0.02-0.07 for MCC, 4.18-21.47% for ST and 0.013-0.131 for AUC. Furthermore, we analyze the importance of the pair-relationships extracted by PSSM-RT and the results validates the usefulness of PSSM-RT for encoding DNA-binding residues. We propose a novel prediction method for the prediction of DNA-binding residue with the inclusion of relationship of evolutionary information and ensemble learning. Performance evaluation shows that the relationship of evolutionary information between residues is indeed useful in DNA-binding residue prediction and ensemble learning can be used to address the data imbalance issue between binding and non-binding residues. A web service of EL_PSSM-RT ( http://hlt.hitsz.edu.cn:8080/PSSM-RT_SVM/ ) is provided for free access to the biological research community.

Next-day residual effects of gabapentin, diphenhydramine, and triazolam on simulated driving performance in healthy volunteers: a phase 3, randomized, double-blind, placebo-controlled, crossover trial.

PubMed

Kay, Gary G; Schwartz, Howard I; Wingertzahn, Mark A; Jayawardena, Shyamalie; Rosenberg, Russell P

2016-05-01

Next-day residual effects of a nighttime dose of gabapentin 250 mg were evaluated on simulated driving performance in healthy participants in a randomized, placebo-controlled, double-blind, multicenter, four-period crossover study that included diphenhydramine citrate 76 mg and triazolam 0.5 mg. At treatment visits, participants (n = 59) were dosed at ~23:30, went to bed immediately, and awakened 6.5 h postdose for evaluation. The primary endpoint was the standard deviation of lateral position for the 100-km driving scenario. Additional measures of driving, sleepiness, and cognition were included. Study sensitivity was established with triazolam, which demonstrated significant next-day impairment on all driving endpoints, relative to placebo (p < 0.001). Gabapentin demonstrated noninferiority to placebo on standard deviation of lateral position and speed deviation but not for lane excursions. Diphenhydramine citrate demonstrated significant impairment relative to gabapentin and placebo on speed deviation (p < 0.05). Other comparisons were either nonsignificant or statistically ineligible per planned, sequential comparisons. Secondary endpoints for sleepiness and cognitive performance were supportive of these conclusions. Together, these data suggest that low-dose gabapentin had no appreciable next-day effects on simulated driving performance or cognitive functioning. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Structure of the Bacillus subtilis phage SPO1-encoded type II DNA-binding protein TF1 in solution.

PubMed

Jia, X; Grove, A; Ivancic, M; Hsu, V L; Geiduscheck, E P; Kearns, D R

1996-10-25

The solution structure of a type II DNA-binding protein, the bacteriophage SPO1-encoded transcription factor 1 (TF1), was determined using NMR spectroscopy. Selective 2H-labeling, 13C-labeling and isotopic heterodimers were used to distinguish contacts between and within monomers of the dimeric protein. A total of 1914 distance and dihedral angle constraints derived from NMR experiments were used in structure calculations using restrained molecular dynamics and simulated annealing protocols. The ensemble of 30 calculated structures has a root-mean-square deviation (r.m.s.d.) of 0.9 A, about the average structure for the backbone atoms, and 1.2 A for all heavy-atoms of the dimeric core (helices 1 and 2) and the beta-sheets. A severe helix distortion at residues 92-93 in the middle of helix 3 is associated with r.m.s.d. of approximately 1.5 A for the helix 3 backbone. Deviations of approximately 5 A or larger are noted for the very flexible beta-ribbon arms that constitute part of a proposed DNA-binding region. A structural model of TF1 has been calculated based on the previously reported crystal structure of the homologous HU protein and this model was used as the starting structure for calculations. A comparison between the calculated average solution structure of TF1 and a solution structure of HU indicates a similarity in the dimeric core (excluding the nine amino acid residue tail) with pairwise deviations of 2 to 3 A. The largest deviations between the average structure and the HU solution structure were found in the beta-ribbon arms, as expected. A 4 A deviation is found at residue 15 of TF1 which is in a loop connecting two helical segments; it has been reported that substitution of Glu15 by Gly increases the thermostability of TF1. The homology between TF1 and other proteins of this family leads us to anticipate similar tertiary structures.

Is the Spatial Distribution of Mankind's Most Basic Economic Traits Determined by Climate and Soil Alone?

PubMed Central

Beck, Jan; Sieber, Andrea

2010-01-01

Background Several authors, most prominently Jared Diamond (1997, Guns, Germs and Steel), have investigated biogeographic determinants of human history and civilization. The timing of the transition to an agricultural lifestyle, associated with steep population growth and consequent societal change, has been suggested to be affected by the availability of suitable organisms for domestication. These factors were shown to quantitatively explain some of the current global inequalities of economy and political power. Here, we advance this approach one step further by looking at climate and soil as sole determining factors. Methodology/Principal Findings As a simplistic ‘null model’, we assume that only climate and soil conditions affect the suitability of four basic landuse types – agriculture, sedentary animal husbandry, nomadic pastoralism and hunting-and-gathering. Using ecological niche modelling (ENM), we derive spatial predictions of the suitability for these four landuse traits and apply these to the Old World and Australia. We explore two aspects of the properties of these predictions, conflict potential and population density. In a calculation of overlap of landuse suitability, we map regions of potential conflict between landuse types. Results are congruent with a number of real, present or historical, regions of conflict between ethnic groups associated with different landuse traditions. Furthermore, we found that our model of agricultural suitability explains a considerable portion of population density variability. We mapped residuals from this correlation, finding geographically highly structured deviations that invite further investigation. We also found that ENM of agricultural suitability correlates with a metric of local wealth generation (Gross Domestic Product, Purchasing Power Parity). Conclusions/Significance From simplified assumptions on the links between climate, soil and landuse we are able to provide good predictions on complex features of human geography. The spatial distribution of deviations from ENM predictions identifies those regions requiring further investigation of potential explanations. Our findings and methodological approaches may be of applied interest, e.g., in the context of climate change. PMID:20463959

Is the spatial distribution of mankind's most basic economic traits determined by climate and soil alone?

PubMed

Beck, Jan; Sieber, Andrea

2010-05-05

Several authors, most prominently Jared Diamond (1997, Guns, Germs and Steel), have investigated biogeographic determinants of human history and civilization. The timing of the transition to an agricultural lifestyle, associated with steep population growth and consequent societal change, has been suggested to be affected by the availability of suitable organisms for domestication. These factors were shown to quantitatively explain some of the current global inequalities of economy and political power. Here, we advance this approach one step further by looking at climate and soil as sole determining factors. As a simplistic 'null model', we assume that only climate and soil conditions affect the suitability of four basic landuse types - agriculture, sedentary animal husbandry, nomadic pastoralism and hunting-and-gathering. Using ecological niche modelling (ENM), we derive spatial predictions of the suitability for these four landuse traits and apply these to the Old World and Australia. We explore two aspects of the properties of these predictions, conflict potential and population density. In a calculation of overlap of landuse suitability, we map regions of potential conflict between landuse types. Results are congruent with a number of real, present or historical, regions of conflict between ethnic groups associated with different landuse traditions. Furthermore, we found that our model of agricultural suitability explains a considerable portion of population density variability. We mapped residuals from this correlation, finding geographically highly structured deviations that invite further investigation. We also found that ENM of agricultural suitability correlates with a metric of local wealth generation (Gross Domestic Product, Purchasing Power Parity). From simplified assumptions on the links between climate, soil and landuse we are able to provide good predictions on complex features of human geography. The spatial distribution of deviations from ENM predictions identifies those regions requiring further investigation of potential explanations. Our findings and methodological approaches may be of applied interest, e.g., in the context of climate change.

Comparison of free flux flow in two single crystals of V3Si with slightly different pinning strengths

NASA Astrophysics Data System (ADS)

Gafarov, Ozarfar; Gapud, Albert A.; Moraes, Sunhee; Thompson, James R.; Christen, David K.; Reyes, Arneil P.

2011-03-01

Results of recent measurements on two very clean, single-crystal samples of the A15 superconductor V3 Si are presented. Magnetization and transport data confirm the ``clean'' quality of both samples, as manifested by: (i) high residual resistivity ratio, (ii) low critical current densities, and (iii) a ``peak'' effect in the field dependence of critical current. The (H,T) phase line for this peak effect is shifted in the slightly ``dirtier'' sample, which also has higher critical current density Jc (H). High-current Lorentz forces are applied on mixed-state vortices in order to induce the highly ordered free flux flow (FFF) phase, using the same methods as in previous work. A traditional model by Bardeen and Stephen (BS) predicts a simple field dependence of flux flow resistivity ρf (H), presuming a field-independent flux core size. A model by Kogan and Zelezhina (KZ) takes core size into account, and predicts a deviation from BS. In this study, ρf (H) is confirmed to be consistent with predictions of KZ, as will be discussed. Funded by Research Corporation and the National Science Foundation.

Near infrared spectroscopy (NIRS) for on-line determination of quality parameters in intact olives.

PubMed

Salguero-Chaparro, Lourdes; Baeten, Vincent; Fernández-Pierna, Juan A; Peña-Rodríguez, Francisco

2013-08-15

The acidity, moisture and fat content in intact olive fruits were determined on-line using a NIR diode array instrument, operating on a conveyor belt. Four sets of calibrations models were obtained by means of different combinations from samples collected during 2009-2010 and 2010-2011, using full-cross and external validation. Several preprocessing treatments such as derivatives and scatter correction were investigated by using the root mean square error of cross-validation (RMSECV) and prediction (RMSEP), as control parameters. The results obtained showed RMSECV values of 2.54-3.26 for moisture, 2.35-2.71 for fat content and 2.50-3.26 for acidity parameters, depending on the calibration model developed. Calibrations for moisture, fat content and acidity gave residual predictive deviation (RPD) values of 2.76, 2.37 and 1.60, respectively. Although, it is concluded that the on-line NIRS prediction results were acceptable for the three parameters measured in intact olive samples in movement, the models developed must be improved in order to increase their accuracy before final NIRS implementation at mills. Copyright © 2013 Elsevier Ltd. All rights reserved.

Three-Dimensional Molecular Modeling of a Diverse Range of SC Clan Serine Proteases

PubMed Central

Laskar, Aparna; Chatterjee, Aniruddha; Chatterjee, Somnath; Rodger, Euan J.

2012-01-01

Serine proteases are involved in a variety of biological processes and are classified into clans sharing structural homology. Although various three-dimensional structures of SC clan proteases have been experimentally determined, they are mostly bacterial and animal proteases, with some from archaea, plants, and fungi, and as yet no structures have been determined for protozoa. To bridge this gap, we have used molecular modeling techniques to investigate the structural properties of different SC clan serine proteases from a diverse range of taxa. Either SWISS-MODEL was used for homology-based structure prediction or the LOOPP server was used for threading-based structure prediction. The predicted models were refined using Insight II and SCRWL and validated against experimental structures. Investigation of secondary structures and electrostatic surface potential was performed using MOLMOL. The structural geometry of the catalytic core shows clear deviations between taxa, but the relative positions of the catalytic triad residues were conserved. Evolutionary divergence was also exhibited by large variation in secondary structure features outside the core, differences in overall amino acid distribution, and unique surface electrostatic potential patterns between species. Encompassing a wide range of taxa, our structural analysis provides an evolutionary perspective on SC clan serine proteases. PMID:23213528

Free flux flow in two single crystals of V3Si with differing pinning strengths

NASA Astrophysics Data System (ADS)

Gafarov, O.; Gapud, A. A.; Moraes, S.; Thompson, J. R.; Christen, D. K.; Reyes, A. P.

2011-10-01

Results of measurements on two very clean, single-crystal samples of the A15 superconductor V3Si are presented. Magnetization and transport data have confirmed the ``clean'' quality of both samples, as manifested by: (i) high residual electrical resistivity ratio, (ii) very low critical current densities Jc, and (iii) a ``peak'' effect in the field dependence of critical current. The (H,T) phase line for this peak effect is shifted down for the slightly ``dirtier'' sample, which consequently also has higher critical current density Jc(H). Large Lorentz forces are applied on mixed-state vortices via large currents, in order to induce the highly ordered free flux flow (FFF) phase, using experimental methods developed previously. The traditional model by Bardeen and Stephen (BS) predicts a simple field dependence of flux flow resistivity ρf(H) ˜ H/Hc2, presuming a field-independent flux core size. A model by Kogan and Zelezhina (KZ) takes into account the effects of magnetic field on core size, and predict a clear deviation from the linear BS dependence. In this study, ρf(H) is confirmed to be consistent with predictions of KZ.

Visual Field Defects and Retinal Ganglion Cell Losses in Human Glaucoma Patients

PubMed Central

Harwerth, Ronald S.; Quigley, Harry A.

2007-01-01

Objective The depth of visual field defects are correlated with retinal ganglion cell densities in experimental glaucoma. This study was to determine whether a similar structure-function relationship holds for human glaucoma. Methods The study was based on retinal ganglion cell densities and visual thresholds of patients with documented glaucoma (Kerrigan-Baumrind, et al.) The data were analyzed by a model that predicted ganglion cell densities from standard clinical perimetry, which were then compared to histologic cell counts. Results The model, without free parameters, produced accurate and relatively precise quantification of ganglion cell densities associated with visual field defects. For 437 sets of data, the unity correlation for predicted vs. measured cell densities had a coefficient of determination of 0.39. The mean absolute deviation of the predicted vs. measured values was 2.59 dB, the mean and SD of the distribution of residual errors of prediction was -0.26 ± 3.22 dB. Conclusions Visual field defects by standard clinical perimetry are proportional to neural losses caused by glaucoma. Clinical Relevance The evidence for quantitative structure-function relationships provides a scientific basis of interpreting glaucomatous neuropathy from visual thresholds and supports the application of standard perimetry to establish the stage of the disease. PMID:16769839

Dissipation and residue of myclobutanil in lychee.

PubMed

Liu, Yanping; Sun, Haibin; Liu, Fengmao; Wang, Siwei

2012-06-01

The dissipation and residue of myclobutanil in lychee under field conditions were studied. To determine myclobutanil residue in samples, an analytical method with a florisil column clean-up and detected by gas chromatography-electron capture detector (GC-ECD) was developed. Recoveries were found in the range of 83.24 %-89.00 % with relative standard deviations of 2.67 %-9.88 %. This method was successfully applied to analyze the dissipation and residue of myclobutanil in lychee in Guangdong and Guangxi Province, China. The half lives in lychee were from 2.2 to 3.4 days. The residues of myclobutanil in lychee flesh were all below the limit of quantification (LOQ) value (0.01 mg/kg), and most of the residues were concentrated in the peel. The terminal residues of myclobutanil were all bellow the maximum residue limit (MRL) value set by European Union (EU) (0.02 mg/kg). Hence it was safe for the use of this pesticide and the results also could give a reference for MRL setting of myclobutanil in lychee in China.

Prediction limits of mobile phone activity modelling

NASA Astrophysics Data System (ADS)

Kondor, Dániel; Grauwin, Sebastian; Kallus, Zsófia; Gódor, István; Sobolevsky, Stanislav; Ratti, Carlo

2017-02-01

Thanks to their widespread usage, mobile devices have become one of the main sensors of human behaviour and digital traces left behind can be used as a proxy to study urban environments. Exploring the nature of the spatio-temporal patterns of mobile phone activity could thus be a crucial step towards understanding the full spectrum of human activities. Using 10 months of mobile phone records from Greater London resolved in both space and time, we investigate the regularity of human telecommunication activity on urban scales. We evaluate several options for decomposing activity timelines into typical and residual patterns, accounting for the strong periodic and seasonal components. We carry out our analysis on various spatial scales, showing that regularity increases as we look at aggregated activity in larger spatial units with more activity in them. We examine the statistical properties of the residuals and show that it can be explained by noise and specific outliers. Also, we look at sources of deviations from the general trends, which we find to be explainable based on knowledge of the city structure and places of attractions. We show examples how some of the outliers can be related to external factors such as specific social events.

Prediction limits of mobile phone activity modelling.

PubMed

Kondor, Dániel; Grauwin, Sebastian; Kallus, Zsófia; Gódor, István; Sobolevsky, Stanislav; Ratti, Carlo

2017-02-01

Thanks to their widespread usage, mobile devices have become one of the main sensors of human behaviour and digital traces left behind can be used as a proxy to study urban environments. Exploring the nature of the spatio-temporal patterns of mobile phone activity could thus be a crucial step towards understanding the full spectrum of human activities. Using 10 months of mobile phone records from Greater London resolved in both space and time, we investigate the regularity of human telecommunication activity on urban scales. We evaluate several options for decomposing activity timelines into typical and residual patterns, accounting for the strong periodic and seasonal components. We carry out our analysis on various spatial scales, showing that regularity increases as we look at aggregated activity in larger spatial units with more activity in them. We examine the statistical properties of the residuals and show that it can be explained by noise and specific outliers. Also, we look at sources of deviations from the general trends, which we find to be explainable based on knowledge of the city structure and places of attractions. We show examples how some of the outliers can be related to external factors such as specific social events.

Tidal dynamics in a changing lagoon: Flooding or not flooding the marginal regions

NASA Astrophysics Data System (ADS)

Lopes, Carina L.; Dias, João M.

2015-12-01

Coastal lagoons are low-lying systems under permanent changes motivated by natural and anthropogenic factors. Ria de Aveiro is such an example with its margins currently threatened by the advance of the lagoonal waters recorded during the last decades. This work aims to study the tidal modifications found between 1987 and 2012 in this lagoon, motivated by the main channels deepening which induce higher inland tidal levels. Additionally it aims to study the impact that protective walls designed to protect the margins against flooding may have in those modifications under sea level rise predictions. The hydrodynamic model ELCIRC previously calibrated for Ria de Aveiro was used and tidal asymmetry, tidal ellipses and residual currents were analyzed for different scenarios, considering the mean sea level rise predicted for 2100 and the implementation of probable flood protection walls. Results evidenced that lagoon dominance remained unchanged between 1987 and 2012, but distortion decreased/increased in the deeper/shallower channels. The same trend was found under mean sea level rise conditions. Tidal currents increased over this period inducing an amplification of the water properties exchange within the lagoon, which will be stronger under mean sea level rise conditions. The deviations between scenarios with or without flood protection walls can achieve 60% for the tidal distortion and residual currents and 20% for the tidal currents, highlighting that tidal properties are extremely sensitive to the lagoon geometry. In summary, the development of numerical modelling applications dedicated to study the influence of mean sea level rise on coastal low-lying systems subjected to human influence should include structural measures designed for flood defence in order to accurately predict changes in the local tidal properties.

Predicting logging residue volumes in the Pacific Northwest

Treesearch

Erik C. Berg; Todd A. Morgan; Eric A. Simmons; Stan Zarnoch; Micah G. Scudder

2016-01-01

Pacific Northwest forest managers seek estimates of post-timber-harvest woody residue volumes and biomass that can be related to readily available site- and tree-level attributes. To better predict residue production, researchers investigated variability in residue ratios, growing-stock residue volume per mill-delivered volume, across Idaho, Montana, Oregon, and...

ComplexContact: a web server for inter-protein contact prediction using deep learning.

PubMed

Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo

2018-05-22

ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

An experimental and theoretical study to relate uncommon rock/fluid properties to oil recovery. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Watson, R.

Waterflooding is the most commonly used secondary oil recovery technique. One of the requirements for understanding waterflood performance is a good knowledge of the basic properties of the reservoir rocks. This study is aimed at correlating rock-pore characteristics to oil recovery from various reservoir rock types and incorporating these properties into empirical models for Predicting oil recovery. For that reason, this report deals with the analyses and interpretation of experimental data collected from core floods and correlated against measurements of absolute permeability, porosity. wettability index, mercury porosimetry properties and irreducible water saturation. The results of the radial-core the radial-core andmore » linear-core flow investigations and the other associated experimental analyses are presented and incorporated into empirical models to improve the predictions of oil recovery resulting from waterflooding, for sandstone and limestone reservoirs. For the radial-core case, the standardized regression model selected, based on a subset of the variables, predicted oil recovery by waterflooding with a standard deviation of 7%. For the linear-core case, separate models are developed using common, uncommon and combination of both types of rock properties. It was observed that residual oil saturation and oil recovery are better predicted with the inclusion of both common and uncommon rock/fluid properties into the predictive models.« less

Comparison on effectiveness of trans-septal suturing versus nasal packing after septoplasty: a systematic review and meta-analysis.

PubMed

Wang, Wei-Wei; Dong, Bao-Cheng

2017-11-01

This systematic review applied meta-analytic procedures to evaluate the curative effect of trans-septal suturing versus nasal packing after septoplasty. Computerized search of the published literature in PubMed, EMBASE, CENTRAL, Cochrane Database of Systematic Reviews, WANFANG, CNKI databases. Randomized trials investigating trans-septal suturing versus nasal packing following septoplasty in patients with deviated nasal septum. Adhesion, septal hematoma, bleeding, septal perforation, infection, pain, headache, or residual septal deviation per randomized patients. 19 randomized controlled trials of 1845 subjects were included. Meta-analysis showed that postoperative pain, headache, and adhesion were significantly lower in trans-septal suturing group. Nasal packing and trans-septal suturing technique appear to be equivalent with regard to postoperative bleeding, hematoma, septal perforation, infection, and residual septal deviation. Trans-septal suturing technology is not only associated with less patient pain, headache, and lower occurrence rate of adhesion after septoplasty but it also relates to higher patient satisfaction and an improved quality of life. The suturing technology can be used as a substitute for traditional nasal packing of the first-line treatment. More well-designed studies are needed to confirm the effect of trans-septal suturing following septoplasty.

A computational tool to predict the evolutionarily conserved protein-protein interaction hot-spot residues from the structure of the unbound protein.

PubMed

Agrawal, Neeraj J; Helk, Bernhard; Trout, Bernhardt L

2014-01-21

Identifying hot-spot residues - residues that are critical to protein-protein binding - can help to elucidate a protein's function and assist in designing therapeutic molecules to target those residues. We present a novel computational tool, termed spatial-interaction-map (SIM), to predict the hot-spot residues of an evolutionarily conserved protein-protein interaction from the structure of an unbound protein alone. SIM can predict the protein hot-spot residues with an accuracy of 36-57%. Thus, the SIM tool can be used to predict the yet unknown hot-spot residues for many proteins for which the structure of the protein-protein complexes are not available, thereby providing a clue to their functions and an opportunity to design therapeutic molecules to target these proteins. Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Application of Mean of Absolute Deviation Method for the Selection of Best Nonlinear Component Based on Video Encryption

NASA Astrophysics Data System (ADS)

Anees, Amir; Khan, Waqar Ahmad; Gondal, Muhammad Asif; Hussain, Iqtadar

2013-07-01

The aim of this work is to make use of the mean of absolute deviation (MAD) method for the evaluation process of substitution boxes used in the advanced encryption standard. In this paper, we use the MAD technique to analyze some popular and prevailing substitution boxes used in encryption processes. In particular, MAD is applied to advanced encryption standard (AES), affine power affine (APA), Gray, Lui J., Residue Prime, S8 AES, SKIPJACK, and Xyi substitution boxes.

Kappa Distribution in a Homogeneous Medium: Adiabatic Limit of a Super-diffusive Process?

NASA Astrophysics Data System (ADS)

Roth, I.

2015-12-01

The classical statistical theory predicts that an ergodic, weakly interacting system like charged particles in the presence of electromagnetic fields, performing Brownian motions (characterized by small range deviations in phase space and short-term microscopic memory), converges into the Gibbs-Boltzmann statistics. Observation of distributions with a kappa-power-law tails in homogeneous systems contradicts this prediction and necessitates a renewed analysis of the basic axioms of the diffusion process: characteristics of the transition probability density function (pdf) for a single interaction, with a possibility of non-Markovian process and non-local interaction. The non-local, Levy walk deviation is related to the non-extensive statistical framework. Particles bouncing along (solar) magnetic field with evolving pitch angles, phases and velocities, as they interact resonantly with waves, undergo energy changes at undetermined time intervals, satisfying these postulates. The dynamic evolution of a general continuous time random walk is determined by pdf of jumps and waiting times resulting in a fractional Fokker-Planck equation with non-integer derivatives whose solution is given by a Fox H-function. The resulting procedure involves the known, although not frequently used in physics fractional calculus, while the local, Markovian process recasts the evolution into the standard Fokker-Planck equation. Solution of the fractional Fokker-Planck equation with the help of Mellin transform and evaluation of its residues at the poles of its Gamma functions results in a slowly converging sum with power laws. It is suggested that these tails form the Kappa function. Gradual vs impulsive solar electron distributions serve as prototypes of this description.

Liquid chromatographic determination of acriflavine and proflavine residues in channel catfish muscle.

PubMed

Plakas, S M; el Said, K R; Jester, E L; Bencsath, F A; Hayton, W L

1997-01-01

A liquid chromatographic (LC) method was developed for determination of acriflavine (ACR) and proflavine (PRO) residues in channel catfish muscle. Residues were extracted with acidified methanol solution, and extracts were cleaned up with C18 solid-phase extraction columns. Residue concentrations were determined on an LC cyano column, with spectrophotometric detection at 454 nm. Catfish muscle was individually fortified with ACR (purified from commercial product) and PRO at concentrations of 5, 10, 20, 40, and 80 ppb (5 replicates per level). Mean recoveries from fortified muscle at each level ranged from 86 to 95%, with relative standard deviations (RSDs) of 2.5 to 5.7%. The method was applied to incurred residues of ACR and PRO in muscle after waterborne exposure of channel catfish to commercial acriflavine (10 ppm total dye for 4 h). RSDs for incurred residues of ACR and PRO were in the same range as those for fortified muscle. Low residue concentrations (< 1% of exposure water concentration) suggested poor absorption of ACR and PRO in catfish.

Selective Weighted Least Squares Method for Fourier Transform Infrared Quantitative Analysis.

PubMed

Wang, Xin; Li, Yan; Wei, Haoyun; Chen, Xia

2017-06-01

Classical least squares (CLS) regression is a popular multivariate statistical method used frequently for quantitative analysis using Fourier transform infrared (FT-IR) spectrometry. Classical least squares provides the best unbiased estimator for uncorrelated residual errors with zero mean and equal variance. However, the noise in FT-IR spectra, which accounts for a large portion of the residual errors, is heteroscedastic. Thus, if this noise with zero mean dominates in the residual errors, the weighted least squares (WLS) regression method described in this paper is a better estimator than CLS. However, if bias errors, such as the residual baseline error, are significant, WLS may perform worse than CLS. In this paper, we compare the effect of noise and bias error in using CLS and WLS in quantitative analysis. Results indicated that for wavenumbers with low absorbance, the bias error significantly affected the error, such that the performance of CLS is better than that of WLS. However, for wavenumbers with high absorbance, the noise significantly affected the error, and WLS proves to be better than CLS. Thus, we propose a selective weighted least squares (SWLS) regression that processes data with different wavenumbers using either CLS or WLS based on a selection criterion, i.e., lower or higher than an absorbance threshold. The effects of various factors on the optimal threshold value (OTV) for SWLS have been studied through numerical simulations. These studies reported that: (1) the concentration and the analyte type had minimal effect on OTV; and (2) the major factor that influences OTV is the ratio between the bias error and the standard deviation of the noise. The last part of this paper is dedicated to quantitative analysis of methane gas spectra, and methane/toluene mixtures gas spectra as measured using FT-IR spectrometry and CLS, WLS, and SWLS. The standard error of prediction (SEP), bias of prediction (bias), and the residual sum of squares of the errors (RSS) from the three quantitative analyses were compared. In methane gas analysis, SWLS yielded the lowest SEP and RSS among the three methods. In methane/toluene mixture gas analysis, a modification of the SWLS has been presented to tackle the bias error from other components. The SWLS without modification presents the lowest SEP in all cases but not bias and RSS. The modification of SWLS reduced the bias, which showed a lower RSS than CLS, especially for small components.

Most outdoor malaria transmission by behaviourally-resistant Anopheles arabiensis is mediated by mosquitoes that have previously been inside houses.

PubMed

Killeen, Gerry F; Govella, Nicodem J; Lwetoijera, Dickson W; Okumu, Fredros O

2016-04-19

Anopheles arabiensis is stereotypical of diverse vectors that mediate residual malaria transmission globally, because it can feed outdoors upon humans or cattle, or enter but then rapidly exit houses without fatal exposure to insecticidal nets or sprays. Life histories of a well-characterized An. arabiensis population were simulated with a simple but process-explicit deterministic model and relevance to other vectors examined through sensitivity analysis. Where most humans use bed nets, two thirds of An. arabiensis blood feeds and half of malaria transmission events were estimated to occur outdoors. However, it was also estimated that most successful feeds and almost all (>98 %) transmission events are preceded by unsuccessful attempts to attack humans indoors. The estimated proportion of vector blood meals ultimately obtained from humans indoors is dramatically attenuated by availability of alternative hosts, or partial ability to attack humans outdoors. However, the estimated proportion of mosquitoes old enough to transmit malaria, and which have previously entered a house at least once, is far less sensitive to both variables. For vectors with similarly modest preference for cattle over humans and similar ability to evade fatal indoor insecticide exposure once indoors, >80 % of predicted feeding events by mosquitoes old enough to transmit malaria are preceded by at least one house entry event, so long as ≥40 % of attempts to attack humans occur indoors and humans outnumber cattle ≥4-fold. While the exact numerical results predicted by such a simple deterministic model should be considered only approximate and illustrative, the derived conclusions are remarkably insensitive to substantive deviations from the input parameter values measured for this particular An. arabiensis population. This life-history analysis, therefore, identifies a clear, broadly-important opportunity for more effective suppression of residual malaria transmission by An. arabiensis in Africa and other important vectors of residual transmission across the tropics. Improved control of predominantly outdoor residual transmission by An. arabiensis, and other modestly zoophagic vectors like Anopheles darlingi, which frequently enter but then rapidly exit from houses, may be readily achieved by improving existing technology for killing mosquitoes indoors.

Near-infrared spectroscopy (NIRS) for a real time monitoring of the biogas process.

PubMed

Stockl, Andrea; Lichti, Fabian

2018-01-01

In this research project Near-infrared spectroscopy (NIRS) was applied to monitor the content of specific process parameters in anaerobic digestion. A laboratory scaled biogas digester was constantly fed every four hours with maize- and grass silage to keep a base load with an organic loading rate (OLR) of 2.5 kg oDM/m 3  ∗ d. Daily impact loads with shredded wheat up to an OLR of 8 kg oDM/m 3  ∗ d were added in order to generate peaks at the parameters tested. The developed calibration models are capable to show changes in process parameters like volatile fatty acids (VFA), propionic acid, total inorganic carbon (TIC) and the ratio of the volatile fatty acids to the carbonate buffer (VFA/TIC). Based on the calibration of the models for VFA and TIC, the values could be predicted with an R 2 of 0.94 and 0.97, respectively. Moreover, the residual prediction deviations were 4.0 and 6.0 for VFA and TIC, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Thermal anomaly mapping from night MODIS imagery of USA, a tool for environmental assessment.

PubMed

Miliaresis, George Ch

2013-02-01

A method is presented for elevation, latitude and longitude decorrelation stretch of multi-temporal MODIS MYD11C3 imagery (monthly average night land surface temperature (LST) across USA and Mexico). Multiple linear regression analysis of principal components images (PCAs) quantifies the variance explained by elevation (H), latitude (LAT), and longitude (LON). The multi-temporal LST imagery is reconstructed from the residual images and selected PCAs by taking into account the portion of variance that is not related to H, LAT, LON. The reconstructed imagery presents the magnitude the standardized LST value per pixel deviates from the H, LAT, LON predicted. LST anomaly is defined as a region that presents either positive or negative reconstructed LST value. The environmental assessment of USA indicated that only for the 25 % of the study area (Mississippi drainage basin), the LST is predicted by the H, LAT, LON. Regions with milled climatic pattern were identified in the West Coast while the coldest climatic pattern is observed for Mid USA. Positive season invariant LST anomalies are identified in SW (Arizona, Sierra Nevada, etc.) and NE USA.

Prediction of distal residue participation in enzyme catalysis

PubMed Central

Brodkin, Heather R; DeLateur, Nicholas A; Somarowthu, Srinivas; Mills, Caitlyn L; Novak, Walter R; Beuning, Penny J; Ringe, Dagmar; Ondrechen, Mary Jo

2015-01-01

A scoring method for the prediction of catalytically important residues in enzyme structures is presented and used to examine the participation of distal residues in enzyme catalysis. Scores are based on the Partial Order Optimum Likelihood (POOL) machine learning method, using computed electrostatic properties, surface geometric features, and information obtained from the phylogenetic tree as input features. Predictions of distal residue participation in catalysis are compared with experimental kinetics data from the literature on variants of the featured enzymes; some additional kinetics measurements are reported for variants of Pseudomonas putida nitrile hydratase (ppNH) and for Escherichia coli alkaline phosphatase (AP). The multilayer active sites of P. putida nitrile hydratase and of human phosphoglucose isomerase are predicted by the POOL log ZP scores, as is the single-layer active site of P. putida ketosteroid isomerase. The log ZP score cutoff utilized here results in over-prediction of distal residue involvement in E. coli alkaline phosphatase. While fewer experimental data points are available for P. putida mandelate racemase and for human carbonic anhydrase II, the POOL log ZP scores properly predict the previously reported participation of distal residues. PMID:25627867

Evaluation of CROES Nephrolithometry Nomogram as a Preoperative Predictive System for Percutaneous Nephrolithotomy Outcomes.

PubMed

Kumar, Sumit; Sreenivas, Jayaram; Karthikeyan, Vilvapathy Senguttuvan; Mallya, Ashwin; Keshavamurthy, Ramaiah

2016-10-01

Scoring systems have been devised to predict outcomes of percutaneous nephrolithotomy (PCNL). CROES nephrolithometry nomogram (CNN) is the latest tool devised to predict stone-free rate (SFR). We aim to compare predictive accuracy of CNN against Guy stone score (GSS) for SFR and postoperative outcomes. Between January 2013 and December 2015, 313 patients undergoing PCNL were analyzed for predictive accuracy of GSS, CNN, and stone burden (SB) for SFR, complications, operation time (OT), and length of hospitalization (LOH). We further stratified patients into risk groups based on CNN and GSS. Mean ± standard deviation (SD) SB was 298.8 ± 235.75 mm 2 . SB, GSS, and CNN (area under curve [AUC]: 0.662, 0.660, 0.673) were found to be predictors of SFR. However, predictability for complications was not as good (AUC: SB 0.583, GSS 0.554, CNN 0.580). Single implicated calix (Adj. OR 3.644; p = 0.027), absence of staghorn calculus (Adj. OR 3.091; p = 0.044), single stone (Adj. OR 3.855; p = 0.002), and single puncture (Adj. OR 2.309; p = 0.048) significantly predicted SFR on multivariate analysis. Charlson comorbidity index (CCI; p = 0.020) and staghorn calculus (p = 0.002) were independent predictors for complications on linear regression. SB and GSS independently predicted OT on multivariate analysis. SB and complications significantly predicted LOH, while GSS and CNN did not predict LOH. CNN offered better risk stratification for residual stones than GSS. CNN and GSS have good preoperative predictive accuracy for SFR. Number of implicated calices may affect SFR, and CCI affects complications. Studies should incorporate these factors in scoring systems and assess if predictability of PCNL outcomes improves.

Retrieval of Aerosol Optical Properties from Ground-Based Remote Sensing Measurements: Aerosol Asymmetry Factor and Single Scattering Albedo

NASA Astrophysics Data System (ADS)

Qie, L.; Li, Z.; Li, L.; Li, K.; Li, D.; Xu, H.

2018-04-01

The Devaux-Vermeulen-Li method (DVL method) is a simple approach to retrieve aerosol optical parameters from the Sun-sky radiance measurements. This study inherited the previous works of retrieving aerosol single scattering albedo (SSA) and scattering phase function, the DVL method was modified to derive aerosol asymmetric factor (g). To assess the algorithm performance at various atmospheric aerosol conditions, retrievals from AERONET observations were implemented, and the results are compared with AERONET official products. The comparison shows that both the DVL SSA and g were well correlated with those of AERONET. The RMSD and the absolute value of MBD deviations between the SSAs are 0.025 and 0.015 respectively, well below the AERONET declared SSA uncertainty of 0.03 for all wavelengths. For asymmetry factor g, the RMSD deviations are smaller than 0.02 and the absolute values of MBDs smaller than 0.01 at 675, 870 and 1020 nm bands. Then, considering several factors probably affecting retrieval quality (i.e. the aerosol optical depth (AOD), the solar zenith angle, and the sky residual error, sphericity proportion and Ångström exponent), the deviations for SSA and g of these two algorithms were calculated at varying value intervals. Both the SSA and g deviations were found decrease with the AOD and the solar zenith angle, and increase with sky residual error. However, the deviations do not show clear sensitivity to the sphericity proportion and Ångström exponent. This indicated that the DVL algorithm is available for both large, non-spherical particles and spherical particles. The DVL results are suitable for the evaluation of aerosol direct radiative effects of different aerosol types.

Crystal structure and magnetic properties of '{alpha} Prime Prime -Fe{sub 16}N{sub 2}' containing residual {alpha}-Fe prepared by low-temperature ammonia nitridation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yamashita, S.; Masubuchi, Y.; Nakazawa, Y.

2012-10-15

Slight enhancement of saturation magnetization to 219 A m{sup 2} kg{sup -1} was observed from 199 A m{sup 2} kg{sup -1} for the original {alpha}-Fe on the intermediate nitrided mixture of '{alpha} Prime Prime -Fe{sub 16}N{sub 2}' with residual {alpha}-Fe among the low temperature ammonia nitridation products under 5 T magnetic field at room temperature. The value changed not linearly against the yield as had been expected. Crystal structure refinement indicated that the phase similar to {alpha} Prime Prime -Fe{sub 16}N{sub 2} had deviations on its lattice constants and positional parameters, compared to previously reported values for {alpha} Prime Primemore » -Fe{sub 16}N{sub 2}. Spin-polarized total energy calculations were performed using the projector-augmented wave method as implemented in the Vienna ab-initio simulation package (VASP) to calculate magnetic moment on the refined crystal structure of the intermediate '{alpha} Prime Prime -Fe{sub 16}N{sub 2}'. The calculations supported the observed magnetization enhancement in the intermediate nitridation product. - Graphical abstract: Crystal structural parameters slightly change in the intermediate nitrided '{alpha} Prime Prime -Fe{sub 16}N{sub 2}' from those in {alpha} Prime Prime -Fe{sub 16}N{sub 2} to show the magnetization maxima in the mixture of '{alpha} Prime Prime -Fe{sub 16}N{sub 2}' and the residual {alpha}-F. Highlights: Black-Right-Pointing-Pointer Larger magnetization was observed than the value of Fe{sub 16}N{sub 2} on its intermediate nitrided mixture with residual {alpha}-Fe. Black-Right-Pointing-Pointer The enhancement was related to the crystal structural deviation from Fe{sub 16}N{sub 2} on the intermediate nitride. Black-Right-Pointing-Pointer It was supported by spin-polarized total energy calculation using the deviated structure.« less

Assembling Precise Truss Structures With Minimal Stresses

NASA Technical Reports Server (NTRS)

Sword, Lee F.

1996-01-01

Improved method of assembling precise truss structures involves use of simple devices. Tapered pins that fit in tapered holes indicate deviations from prescribed lengths. Method both helps to ensure precision of finished structures and minimizes residual stresses within structures.

Reduction of deviation angle during occlusion therapy: in partially accommodative esotropia with moderate amblyopia.

PubMed

Chun, Bo Young; Kwon, Soon Jae; Chae, Sun Hwa; Kwon, Jung Yoon

2007-09-01

To evaluate changes in ocular alignment in partially accommodative esotropic children age ranged from 3 to 8 years during occlusion therapy for amblyopia. Angle measurements of twenty-two partially accommodative esotropic patients with moderate amblyopia were evaluated before and at 2 years after occlusion therapy. Mean deviation angle with glasses at the start of occlusion treatment was 19.45+/-5.97 PD and decreased to 12.14+/-12.96 PD at 2 years after occlusion therapy (p<0.01). After occlusion therapy, 9 (41%) cases were indications of surgery for residual deviation but if we had planned surgery before occlusion treatment, 18 (82%) of patients would have had surgery. There was a statistical relationship between increase of visual acuity ratio and decrease of deviation angle (r=-0.479, p=0.024). There was a significant reduction of deviation angle of partially accommodative esotropic patients at 2 years after occlusion therapy. Our results suggest that occlusion therapy has an influence on ocular alignment in partially accommodative esotropic patients with amblyopia.

Dietary intake and human milk residues of hexachlorocyclohexane isomers in two Chinese cities.

PubMed

Yu, Yanxin; Tao, Shu; Liu, Wenxin; Lu, Xiaoxia; Wang, Xuejun; Wong, Minghung

2009-07-01

Residues of hexachlorocyclohexane isomers (HCHs, including alpha-HCH, beta-HCH, gamma-HCH, and delta-HCH) in human milk of two populations from Beijing and Shenyang, China were studied. In addition to human milk samples from 76 women, 271 composite food samples covering major food categories were also collected for HCH analysis. The food consumption and social-demographic characteristics of the studied populations were investigated and dietary intakes of HCHs of the milk donors on an individual basis were calculated. The dependences of HCH concentration in the human milk on food consumption, dietary intake of HCHs, and demographic characteristics were studied. It was found that beta-HCH dominated the HCHs detected in the human milk. Although there were dramatic declines in HCHs in the human milk compared to historical data, the current levels (312 +/- 377 ng/g fat and 360 +/- 235 ng/g fat as the means and standard deviations for Beijing and Shenyang, respectively) were still much higher than those reported in other cities within China and around the world. It was revealed that the residual level of HCHs in the human milk was positively correlated (p < 0.001) to the quantities of food consumption. Milk, oil, vegetables, and fruits contributed a large portion of HCHs intake in Beijing, while cereals, milk, vegetables, oil, and meat were the most important dietary intake sources of HCHs in Shenyang. Both daily dietary intake of HCHs (p < 0.001) and body mass index (BMI, body weight divided by the squared height) (p < 0.01) were significantly correlated with human milk HCHs. A nonlinear model was developed to predict the residues of HCHs in human milk using both dietary intake and BMI as independent variables. Potential risk of the HCH exposure of breastfed infants is discussed.

Molecular dynamics simulations reveal a disorder-to-order transition on phosphorylation of smooth muscle myosin.

PubMed

Espinoza-Fonseca, L Michel; Kast, David; Thomas, David D

2007-09-15

We have performed molecular dynamics simulations of the phosphorylated (at S-19) and the unphosphorylated 25-residue N-terminal phosphorylation domain of the regulatory light chain (RLC) of smooth muscle myosin to provide insight into the structural basis of regulation. This domain does not appear in any crystal structure, so these simulations were combined with site-directed spin labeling to define its structure and dynamics. Simulations were carried out in explicit water at 310 K, starting with an ideal alpha-helix. In the absence of phosphorylation, large portions of the domain (residues S-2 to K-11 and R-16 through Y-21) were metastable throughout the simulation, undergoing rapid transitions among alpha-helix, pi-helix, and turn, whereas residues K-12 to Q-15 remained highly disordered, displaying a turn motif from 1 to 22.5 ns and a random coil pattern from 22.5 to 50 ns. Phosphorylation increased alpha-helical order dramatically in residues K-11 to A-17 but caused relatively little change in the immediate vicinity of the phosphorylation site (S-19). Phosphorylation also increased the overall dynamic stability, as evidenced by smaller temporal fluctuations in the root mean-square deviation. These results on the isolated phosphorylation domain, predicting a disorder-to-order transition induced by phosphorylation, are remarkably consistent with published experimental data involving site-directed spin labeling of the intact RLC bound to the two-headed heavy meromyosin. The simulations provide new insight into structural details not revealed by experiment, allowing us to propose a refined model for the mechanism by which phosphorylation affects the N-terminal domain of the RLC of smooth muscle myosin.

Constraints on the shear speed, crust thickness and residual topography of western Tibet from surface wave tomography and virtual deep seismic sounding

NASA Astrophysics Data System (ADS)

Matchette-Downes, H.; van der Hilst, R. D.; Priestley, K. F.

2017-12-01

We have estimated the thickness of the crust in western Tibet by measuring the time delays between the direct S and the SsPmp seismic phases. We find that the thickness of the crust increases from around 50 km beneath the Tethyan Himalayas to around 80 km beneath the Lhasa block, and then decreases to around 70 km beneath the Qiangtang terrane.This method, virtual deep seismic sounding (VDSS), also yields robust estimates of the contribution of crust buoyancy to elevation. By subtracting the predicted elevation from the real topography, we find there is no observable deviation from hydrostatic topography beneath the Tethyan Himalaya, but there is negative residual topography of 1.5 to 2.0 km beneath the Lhasa and Qiangtang terranes. It is also known that the interior of the Plateau is isostatically compensated, as it has small free air gravity anomalies.Additionally, we have estimated the 3D shear speed structure of the crust and upper mantle. This model is derived from maps of the fundamental mode Rayleigh wave phase speed dispersion in the period range from 20 to 140 s, obtained from a standard two-plane-wave inversion constrained with receiver functions and group speeds from ambient noise. The observations agree with previous observations of a low-wavespeed zone in the mid-crust and a gradual Moho. Furthermore, the long-period Rayleigh waves detect a high-wavespeed upper mantle.Together, the observations of high upper mantle wavespeeds, negative residual topography, and small free air gravity anomalies support the hypothesis that cold, dense Indian lithosphere has underthrust the Plateau in this region. However, in the presentation we also consider contributions to residual topography from plate flexure, lower crustal flow, or deeper mantle flow (dynamic topography).

Phytoremediation of palm oil mill secondary effluent (POMSE) by Chrysopogon zizanioides (L.) using artificial neural networks.

PubMed

Darajeh, Negisa; Idris, Azni; Fard Masoumi, Hamid Reza; Nourani, Abolfazl; Truong, Paul; Rezania, Shahabaldin

2017-05-04

Artificial neural networks (ANNs) have been widely used to solve the problems because of their reliable, robust, and salient characteristics in capturing the nonlinear relationships between variables in complex systems. In this study, ANN was applied for modeling of Chemical Oxygen Demand (COD) and biodegradable organic matter (BOD) removal from palm oil mill secondary effluent (POMSE) by vetiver system. The independent variable, including POMSE concentration, vetiver slips density, and removal time, has been considered as input parameters to optimize the network, while the removal percentage of COD and BOD were selected as output. To determine the number of hidden layer nodes, the root mean squared error of testing set was minimized, and the topologies of the algorithms were compared by coefficient of determination and absolute average deviation. The comparison indicated that the quick propagation (QP) algorithm had minimum root mean squared error and absolute average deviation, and maximum coefficient of determination. The importance values of the variables was included vetiver slips density with 42.41%, time with 29.8%, and the POMSE concentration with 27.79%, which showed none of them, is negligible. Results show that the ANN has great potential ability in prediction of COD and BOD removal from POMSE with residual standard error (RSE) of less than 0.45%.

Genomic Prediction Accounting for Residual Heteroskedasticity

PubMed Central

Ou, Zhining; Tempelman, Robert J.; Steibel, Juan P.; Ernst, Catherine W.; Bates, Ronald O.; Bello, Nora M.

2015-01-01

Whole-genome prediction (WGP) models that use single-nucleotide polymorphism marker information to predict genetic merit of animals and plants typically assume homogeneous residual variance. However, variability is often heterogeneous across agricultural production systems and may subsequently bias WGP-based inferences. This study extends classical WGP models based on normality, heavy-tailed specifications and variable selection to explicitly account for environmentally-driven residual heteroskedasticity under a hierarchical Bayesian mixed-models framework. WGP models assuming homogeneous or heterogeneous residual variances were fitted to training data generated under simulation scenarios reflecting a gradient of increasing heteroskedasticity. Model fit was based on pseudo-Bayes factors and also on prediction accuracy of genomic breeding values computed on a validation data subset one generation removed from the simulated training dataset. Homogeneous vs. heterogeneous residual variance WGP models were also fitted to two quantitative traits, namely 45-min postmortem carcass temperature and loin muscle pH, recorded in a swine resource population dataset prescreened for high and mild residual heteroskedasticity, respectively. Fit of competing WGP models was compared using pseudo-Bayes factors. Predictive ability, defined as the correlation between predicted and observed phenotypes in validation sets of a five-fold cross-validation was also computed. Heteroskedastic error WGP models showed improved model fit and enhanced prediction accuracy compared to homoskedastic error WGP models although the magnitude of the improvement was small (less than two percentage points net gain in prediction accuracy). Nevertheless, accounting for residual heteroskedasticity did improve accuracy of selection, especially on individuals of extreme genetic merit. PMID:26564950

Computational prediction of protein hot spot residues.

PubMed

Morrow, John Kenneth; Zhang, Shuxing

2012-01-01

Most biological processes involve multiple proteins interacting with each other. It has been recently discovered that certain residues in these protein-protein interactions, which are called hot spots, contribute more significantly to binding affinity than others. Hot spot residues have unique and diverse energetic properties that make them challenging yet important targets in the modulation of protein-protein complexes. Design of therapeutic agents that interact with hot spot residues has proven to be a valid methodology in disrupting unwanted protein-protein interactions. Using biological methods to determine which residues are hot spots can be costly and time consuming. Recent advances in computational approaches to predict hot spots have incorporated a myriad of features, and have shown increasing predictive successes. Here we review the state of knowledge around protein-protein interactions, hot spots, and give an overview of multiple in silico prediction techniques of hot spot residues.

Computational Prediction of Hot Spot Residues

PubMed Central

Morrow, John Kenneth; Zhang, Shuxing

2013-01-01

Most biological processes involve multiple proteins interacting with each other. It has been recently discovered that certain residues in these protein-protein interactions, which are called hot spots, contribute more significantly to binding affinity than others. Hot spot residues have unique and diverse energetic properties that make them challenging yet important targets in the modulation of protein-protein complexes. Design of therapeutic agents that interact with hot spot residues has proven to be a valid methodology in disrupting unwanted protein-protein interactions. Using biological methods to determine which residues are hot spots can be costly and time consuming. Recent advances in computational approaches to predict hot spots have incorporated a myriad of features, and have shown increasing predictive successes. Here we review the state of knowledge around protein-protein interactions, hot spots, and give an overview of multiple in silico prediction techniques of hot spot residues. PMID:22316154

Empirical parameterization of a model for predicting peptide helix/coil equilibrium populations.

PubMed Central

Andersen, N. H.; Tong, H.

1997-01-01

A modification of the Lifson-Roig formulation of helix/coil transitions is presented; it (1) incorporates end-capping and coulombic (salt bridges, hydrogen bonding, and side-chain interactions with charged termini and the helix dipole) effects, (2) helix-stabilizing hydrophobic clustering, (3) allows for different inherent termination probabilities of individual residues, and (4) differentiates helix elongation in the first versus subsequent turns of a helix. Each residue is characterized by six parameters governing helix formation. The formulation of the conditional probability of helix initiation and termination that we developed is essentially the same as one presented previously (Shalongo W, Stellwagen, E. 1995. Protein Sci 4:1161-1166) and nearly the mathematical equivalent of the new capping formulation incorporated in the model presented by Rohl et al. (1996. Protein Sci 5:2623-2637). Side-chain/side-chain interactions are, in most cases, incorporated as context dependent modifications of propagation rather than nucleation parameters. An alternative procedure for converting [theta]221 values to experimental fractional helicities () is presented. Tests of the program predictions suggest this method may have some advantages both for designed peptides and for the analysis of secondary structure preferences that could drive the formation of molten-globule intermediates on protein folding pathways. The model predicts the fractional helicity of 385 peptides with a root-mean-square deviation (RMSD) of 0.050 and locates (with precise definition of the termini in many cases) helices in proteins as well as competing methods. The propagation and nucleation parameters were derived from NMR data and from the CD data for a 79 peptide "learning set" for which an excellent fit resulted (RMSD = 0.0295). The current set of parameter corrections for capping boxes, helix dipole interactions, and side-chain/side-chain interactions (coulombic, hydrogen bonding and hydrophobic clustering), although still under development provide a significant improvement in both helix/coil equilibrium prediction for peptides and helix location in protein sequences. This is clearly evident in the rms deviations between CD measures and calculated values of fractional helicity for different classes of peptides before and after applying the corrections: for peptides lacking capping boxes and i/i + 3 and i/i + 4 side-chain/side-chain interactions RMSD = 0.044 (n = 164) versus RMSD = 0.054 (0.172 without the corrections, n = 221) for peptides that required context-dependent corrections of the parameters. If we restrict the analysis to N-acylated peptides with helix stabilizing side-chain/side-chain interactions (including N-capping boxes), the degree to which our corrections account for the stabilizing interaction can be judged from the change in helicity underestimation, (calc-CD): -0.15 +/- 0.10, which is reduced to -0.018 +/- 0.048 (n = 191) upon applying the corrections. PMID:9300492

In silico designing of hyper-glycosylated analogs for the human coagulation factor IX.

PubMed

Ghasemi, Fahimeh; Zomorodipour, Alireza; Karkhane, Ali Asghar; Khorramizadeh, M Reza

2016-07-01

N-glycosylation is a process during which a glycan moiety attaches to the asparagine residue in the N-glycosylation consensus sequence (Asn-Xxx-Ser/Thr), where Xxx can be any amino acid except proline. Introduction of a new N-glycosylation site into a protein backbone leads to its hyper-glycosylation, and may improve the protein properties such as solubility, folding, stability, and secretion. Glyco-engineering is an approach to facilitate the hyper-glycosylation of recombinant proteins by application of the site-directed mutagenesis methods. In this regard, selection of a suitable location on the surface of a protein for introduction of a new N-glycosylation site is a main concern. In this work, a computational approach was conducted to select suitable location(s) for introducing new N-glycosylation sites into the human coagulation factor IX (hFIX). With this aim, the first 45 residues of mature hFIX were explored to find out suitable positions for introducing either Asn or Ser/Thr residues, to create new N-glycosylation site(s). Our exploration lead to detection of five potential positions, for hyper-glycosylation. For each suggested position, an analog was defined and subjected for N-glycosylation efficiency prediction. After generation of three-dimensional structures, by homology-based modeling, the five designed analogs were examined by molecular dynamic (MD) simulations, to predict their stability levels and probable structural distortions caused by amino acid substitutions, relative to the native counterpart. Three out of five suggested analogs, namely; E15T, K22N, and R37N, reached equilibration state with relatively constant Root Mean Square Deviation values. Additional analysis on the data obtained during MD simulations, lead us to conclude that, R37N is the only qualified analog with the most similar structure and dynamic behavior to that of the native counterpart, to be considered for further experimental investigations. Copyright © 2016 Elsevier Inc. All rights reserved.

Prediction of Soil pH Hyperspectral Spectrum in Guanzhong Area of Shaanxi Province Based on PLS

NASA Astrophysics Data System (ADS)

Liu, Jinbao; Zhang, Yang; Wang, Huanyuan; Cheng, Jie; Tong, Wei; Wei, Jing

2017-12-01

The soil pH of Fufeng County, Yangling County and Wugong County in Shaanxi Province was studied. The spectral reflectance was measured by ASD Field Spec HR portable terrain spectrum, and its spectral characteristics were analyzed. The first deviation of the original spectral reflectance of the soil, the second deviation, the logarithm of the reciprocal logarithm, the first order differential of the reciprocal logarithm and the second order differential of the reciprocal logarithm were used to establish the soil pH Spectral prediction model. The results showed that the correlation between the reflectance spectra after SNV pre-treatment and the soil pH was significantly improved. The optimal prediction model of soil pH established by partial least squares method was a prediction model based on the first order differential of the reciprocal logarithm of spectral reflectance. The principal component factor was 10, the decision coefficient Rc2 = 0.9959, the model root means square error RMSEC = 0.0076, the correction deviation SEC = 0.0077; the verification decision coefficient Rv2 = 0.9893, the predicted root mean square error RMSEP = 0.0157, The deviation of SEP = 0.0160, the model was stable, the fitting ability and the prediction ability were high, and the soil pH can be measured quickly.

[Development of residual voltage testing equipment].

PubMed

Zeng, Xiaohui; Wu, Mingjun; Cao, Li; He, Jinyi; Deng, Zhensheng

2014-07-01

For the existing measurement methods of residual voltage which can't turn the power off at peak voltage exactly and simultaneously display waveforms, a new residual voltage detection method is put forward in this paper. First, the zero point of the power supply is detected with zero cross detection circuit and is inputted to a single-chip microcomputer in the form of pulse signal. Secend, when the zero point delays to the peak voltage, the single-chip microcomputer sends control signal to power off the relay. At last, the waveform of the residual voltage is displayed on a principal computer or oscilloscope. The experimental results show that the device designed in this paper can turn the power off at peak voltage and is able to accurately display the voltage waveform immediately after power off and the standard deviation of the residual voltage is less than 0.2 V at exactly one second and later.

Method and apparatus for in-situ detection and isolation of aircraft engine faults

NASA Technical Reports Server (NTRS)

Bonanni, Pierino Gianni (Inventor); Brunell, Brent Jerome (Inventor)

2007-01-01

A method for performing a fault estimation based on residuals of detected signals includes determining an operating regime based on a plurality of parameters, extracting predetermined noise standard deviations of the residuals corresponding to the operating regime and scaling the residuals, calculating a magnitude of a measurement vector of the scaled residuals and comparing the magnitude to a decision threshold value, extracting an average, or mean direction and a fault level mapping for each of a plurality of fault types, based on the operating regime, calculating a projection of the measurement vector onto the average direction of each of the plurality of fault types, determining a fault type based on which projection is maximum, and mapping the projection to a continuous-valued fault level using a lookup table.

Cosmological implications of a large complete quasar sample.

PubMed

Segal, I E; Nicoll, J F

1998-04-28

Objective and reproducible determinations of the probabilistic significance levels of the deviations between theoretical cosmological prediction and direct model-independent observation are made for the Large Bright Quasar Sample [Foltz, C., Chaffee, F. H., Hewett, P. C., MacAlpine, G. M., Turnshek, D. A., et al. (1987) Astron. J. 94, 1423-1460]. The Expanding Universe model as represented by the Friedman-Lemaitre cosmology with parameters qo = 0, Lambda = 0 denoted as C1 and chronometric cosmology (no relevant adjustable parameters) denoted as C2 are the cosmologies considered. The mean and the dispersion of the apparent magnitudes and the slope of the apparent magnitude-redshift relation are the directly observed statistics predicted. The C1 predictions of these cosmology-independent quantities are deviant by as much as 11sigma from direct observation; none of the C2 predictions deviate by >2sigma. The C1 deviations may be reconciled with theory by the hypothesis of quasar "evolution," which, however, appears incapable of being substantiated through direct observation. The excellent quantitative agreement of the C1 deviations with those predicted by C2 without adjustable parameters for the results of analysis predicated on C1 indicates that the evolution hypothesis may well be a theoretical artifact.

HomPPI: a class of sequence homology based protein-protein interface prediction methods

PubMed Central

2011-01-01

Background Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins, the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces has been a subject of debate. Results We studied more than 300,000 pair-wise alignments of protein sequences from structurally characterized protein complexes, including both obligate and transient complexes. We identified sequence similarity criteria required for accurate homology-based inference of interface residues in a query protein sequence. Based on these analyses, we developed HomPPI, a class of sequence homology-based methods for predicting protein-protein interface residues. We present two variants of HomPPI: (i) NPS-HomPPI (Non partner-specific HomPPI), which can be used to predict interface residues of a query protein in the absence of knowledge of the interaction partner; and (ii) PS-HomPPI (Partner-specific HomPPI), which can be used to predict the interface residues of a query protein with a specific target protein. Our experiments on a benchmark dataset of obligate homodimeric complexes show that NPS-HomPPI can reliably predict protein-protein interface residues in a given protein, with an average correlation coefficient (CC) of 0.76, sensitivity of 0.83, and specificity of 0.78, when sequence homologs of the query protein can be reliably identified. NPS-HomPPI also reliably predicts the interface residues of intrinsically disordered proteins. Our experiments suggest that NPS-HomPPI is competitive with several state-of-the-art interface prediction servers including those that exploit the structure of the query proteins. The partner-specific classifier, PS-HomPPI can, on a large dataset of transient complexes, predict the interface residues of a query protein with a specific target, with a CC of 0.65, sensitivity of 0.69, and specificity of 0.70, when homologs of both the query and the target can be reliably identified. The HomPPI web server is available at http://homppi.cs.iastate.edu/. Conclusions Sequence homology-based methods offer a class of computationally efficient and reliable approaches for predicting the protein-protein interface residues that participate in either obligate or transient interactions. For query proteins involved in transient interactions, the reliability of interface residue prediction can be improved by exploiting knowledge of putative interaction partners. PMID:21682895

Prediction of distal residue participation in enzyme catalysis.

PubMed

Brodkin, Heather R; DeLateur, Nicholas A; Somarowthu, Srinivas; Mills, Caitlyn L; Novak, Walter R; Beuning, Penny J; Ringe, Dagmar; Ondrechen, Mary Jo

2015-05-01

A scoring method for the prediction of catalytically important residues in enzyme structures is presented and used to examine the participation of distal residues in enzyme catalysis. Scores are based on the Partial Order Optimum Likelihood (POOL) machine learning method, using computed electrostatic properties, surface geometric features, and information obtained from the phylogenetic tree as input features. Predictions of distal residue participation in catalysis are compared with experimental kinetics data from the literature on variants of the featured enzymes; some additional kinetics measurements are reported for variants of Pseudomonas putida nitrile hydratase (ppNH) and for Escherichia coli alkaline phosphatase (AP). The multilayer active sites of P. putida nitrile hydratase and of human phosphoglucose isomerase are predicted by the POOL log ZP scores, as is the single-layer active site of P. putida ketosteroid isomerase. The log ZP score cutoff utilized here results in over-prediction of distal residue involvement in E. coli alkaline phosphatase. While fewer experimental data points are available for P. putida mandelate racemase and for human carbonic anhydrase II, the POOL log ZP scores properly predict the previously reported participation of distal residues. 2015 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Experimentally observed conformation-dependent geometry and hidden strain in proteins.

PubMed Central

Karplus, P. A.

1996-01-01

A database has been compiled documenting the peptide conformations and geometries from 70 diverse proteins refined at 1.75 A or better. Analysis of the well-ordered residues within the database shows phi, psi-distributions that have more fine structure than is generally observed. Also, clear evidence is presented that the peptide covalent geometry depends on conformation, with the interpeptide N-C alpha-C bond angle varying by nearly +/-5 degrees from its standard value. The observed deviations from standard peptide geometry are greatest near the edges of well-populated regions, consistent with strain occurring in these conformations. Minimization of such hidden strain could be an important factor in thermostability of proteins. These empirical data describing how equilibrium peptide geometry varies as a function of conformation confirm and extend quantum mechanics calculations, and have predictive value that will aid both theoretical and experimental analyses of protein structure. PMID:8819173

Generalized Majority Logic Criterion to Analyze the Statistical Strength of S-Boxes

NASA Astrophysics Data System (ADS)

Hussain, Iqtadar; Shah, Tariq; Gondal, Muhammad Asif; Mahmood, Hasan

2012-05-01

The majority logic criterion is applicable in the evaluation process of substitution boxes used in the advanced encryption standard (AES). The performance of modified or advanced substitution boxes is predicted by processing the results of statistical analysis by the majority logic criteria. In this paper, we use the majority logic criteria to analyze some popular and prevailing substitution boxes used in encryption processes. In particular, the majority logic criterion is applied to AES, affine power affine (APA), Gray, Lui J, residue prime, S8 AES, Skipjack, and Xyi substitution boxes. The majority logic criterion is further extended into a generalized majority logic criterion which has a broader spectrum of analyzing the effectiveness of substitution boxes in image encryption applications. The integral components of the statistical analyses used for the generalized majority logic criterion are derived from results of entropy analysis, contrast analysis, correlation analysis, homogeneity analysis, energy analysis, and mean of absolute deviation (MAD) analysis.

Transcriptome mining and in silico structural and functional analysis of ascorbic acid and tartaric acid biosynthesis pathway enzymes in rose-scanted geranium.

PubMed

Narnoliya, Lokesh K; Sangwan, Rajender S; Singh, Sudhir P

2018-06-01

Rose-scented geranium (Pelargonium sp.) is widely known as aromatic and medicinal herb, accumulating specialized metabolites of high economic importance, such as essential oils, ascorbic acid, and tartaric acid. Ascorbic acid and tartaric acid are multifunctional metabolites of human value to be used as vital antioxidants and flavor enhancing agents in food products. No information is available related to the structural and functional properties of the enzymes involved in ascorbic acid and tartaric acid biosynthesis in rose-scented geranium. In the present study, transcriptome mining was done to identify full-length genes, followed by their bioinformatic and molecular modeling investigations and understanding of in silico structural and functional properties of these enzymes. Evolutionary conserved domains were identified in the pathway enzymes. In silico physicochemical characterization of the catalytic enzymes revealed isoelectric point (pI), instability index, aliphatic index, and grand average hydropathy (GRAVY) values of the enzymes. Secondary structural prediction revealed abundant proportion of alpha helix and random coil confirmations in the pathway enzymes. Three-dimensional homology models were developed for these enzymes. The predicted structures showed significant structural similarity with their respective templates in root mean square deviation analysis. Ramachandran plot analysis of the modeled enzymes revealed that more than 84% of the amino acid residues were within the favored regions. Further, functionally important residues were identified corresponding to catalytic sites located in the enzymes. To, our best knowledge, this is the first report which provides a foundation on functional annotation and structural determination of ascorbic acid and tartaric acid pathway enzymes in rose-scanted geranium.

Residue depletion of tilmicosin in chicken tissues.

PubMed

Zhang, Yue; Jiang, Haiyang; Jin, Xingjun; Shen, Zhangqi; Shen, Jianzhong; Fu, Caixia; Guo, Junlin

2004-05-05

A high-performance liquid chromatography (HPLC) method with detection at 290 nm was modified and validated for the determination of tilmicosin residues in broiler chicken tissues. The limits of detection (LOD) of the method were 0.01 microg/g for muscle and 0.025 microg/g for liver and kidney. Average recoveries ranged from 80.4 to 88.3%. Relative standard deviation values ranged from 5.2 to 12.1%. Residue depletion of tilmicosin in broiler chickens was examined after dosing over a 5-day period by incorporation of the drug into drinking water at 37.5 and 75.0 mg/L. Tilmicosin concentrations in liver and kidney were highest on day 3 of medication and on day 5 in muscle, in both low- and high-dose groups. The residue levels in both groups were significantly higher in liver than in kidney or muscle. A minimum withdrawal time of 9 days was indicated for residue levels in muscle, liver, and kidney tissues below the maximum residue level (MRL).

Genomic Prediction Accounting for Residual Heteroskedasticity.

PubMed

Ou, Zhining; Tempelman, Robert J; Steibel, Juan P; Ernst, Catherine W; Bates, Ronald O; Bello, Nora M

2015-11-12

Whole-genome prediction (WGP) models that use single-nucleotide polymorphism marker information to predict genetic merit of animals and plants typically assume homogeneous residual variance. However, variability is often heterogeneous across agricultural production systems and may subsequently bias WGP-based inferences. This study extends classical WGP models based on normality, heavy-tailed specifications and variable selection to explicitly account for environmentally-driven residual heteroskedasticity under a hierarchical Bayesian mixed-models framework. WGP models assuming homogeneous or heterogeneous residual variances were fitted to training data generated under simulation scenarios reflecting a gradient of increasing heteroskedasticity. Model fit was based on pseudo-Bayes factors and also on prediction accuracy of genomic breeding values computed on a validation data subset one generation removed from the simulated training dataset. Homogeneous vs. heterogeneous residual variance WGP models were also fitted to two quantitative traits, namely 45-min postmortem carcass temperature and loin muscle pH, recorded in a swine resource population dataset prescreened for high and mild residual heteroskedasticity, respectively. Fit of competing WGP models was compared using pseudo-Bayes factors. Predictive ability, defined as the correlation between predicted and observed phenotypes in validation sets of a five-fold cross-validation was also computed. Heteroskedastic error WGP models showed improved model fit and enhanced prediction accuracy compared to homoskedastic error WGP models although the magnitude of the improvement was small (less than two percentage points net gain in prediction accuracy). Nevertheless, accounting for residual heteroskedasticity did improve accuracy of selection, especially on individuals of extreme genetic merit. Copyright © 2016 Ou et al.

Improve the prediction of RNA-binding residues using structural neighbours.

PubMed

Li, Quan; Cao, Zanxia; Liu, Haiyan

2010-03-01

The interactions between RNA-binding proteins (RBPs) with RNA play key roles in managing some of the cell's basic functions. The identification and prediction of RNA binding sites is important for understanding the RNA-binding mechanism. Computational approaches are being developed to predict RNA-binding residues based on the sequence- or structure-derived features. To achieve higher prediction accuracy, improvements on current prediction methods are necessary. We identified that the structural neighbors of RNA-binding and non-RNA-binding residues have different amino acid compositions. Combining this structure-derived feature with evolutionary (PSSM) and other structural information (secondary structure and solvent accessibility) significantly improves the predictions over existing methods. Using a multiple linear regression approach and 6-fold cross validation, our best model can achieve an overall correct rate of 87.8% and MCC of 0.47, with a specificity of 93.4%, correctly predict 52.4% of the RNA-binding residues for a dataset containing 107 non-homologous RNA-binding proteins. Compared with existing methods, including the amino acid compositions of structure neighbors lead to clearly improvement. A web server was developed for predicting RNA binding residues in a protein sequence (or structure),which is available at http://mcgill.3322.org/RNA/.

Search for Functional Flexible Regions in the G-protein Family: New Reading of the FoldUnfold Program.

PubMed

Galzitskaya, Oxana; Deryusheva, Eugenia; Machulin, Andrey; Nemashkalova, Ekaterina; Glyakina, Anna

2018-06-21

High prediction accuracy of flexible loops in different protein families is a challenge because of the crucial functions associated with these regions. Results of the currently available programs for prediction of loops vary from protein to protein. For prediction of flexible regions in the G-domain for 23 representatives of G-proteins with the known 3D structure we have used eight programs. The results of predictions demonstrate that the FoldUnfold program predicts better loop positions than the PONDR, RОNN, DisEMBL, IUPred, GlobPlot 2, FoldIndex, and MobiDB programs. When classifying the predicted loops (rigid/flexible) according to the Debye-Waller fluctuation factors, our data reveal the existing weak correlation between the B-factors and the average number of closed residues according to the FoldUnfold program; the percentage of overlapping characteristics (residue fold/unfold status) of the protein residues from the two methods is about 60-70%. According to the FoldUnfold program, for G-proteins with the posttranslational modifications, the surrounding binding site residues by disordered-promoting glycine and alanine residues conduces to a more flexible position of the binding sites for fatty acid, while methionine, cysteine and isoleucine residues provide more rigid binding sites. Thus, our research demonstrates additional possibilities of the FoldUnfold program for prediction of flexible regions and characteristics of individual residues in a different protein family. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Genetic variance in micro-environmental sensitivity for milk and milk quality in Walloon Holstein cattle.

PubMed

Vandenplas, J; Bastin, C; Gengler, N; Mulder, H A

2013-09-01

Animals that are robust to environmental changes are desirable in the current dairy industry. Genetic differences in micro-environmental sensitivity can be studied through heterogeneity of residual variance between animals. However, residual variance between animals is usually assumed to be homogeneous in traditional genetic evaluations. The aim of this study was to investigate genetic heterogeneity of residual variance by estimating variance components in residual variance for milk yield, somatic cell score, contents in milk (g/dL) of 2 groups of milk fatty acids (i.e., saturated and unsaturated fatty acids), and the content in milk of one individual fatty acid (i.e., oleic acid, C18:1 cis-9), for first-parity Holstein cows in the Walloon Region of Belgium. A total of 146,027 test-day records from 26,887 cows in 747 herds were available. All cows had at least 3 records and a known sire. These sires had at least 10 cows with records and each herd × test-day had at least 5 cows. The 5 traits were analyzed separately based on fixed lactation curve and random regression test-day models for the mean. Estimation of variance components was performed by running iteratively expectation maximization-REML algorithm by the implementation of double hierarchical generalized linear models. Based on fixed lactation curve test-day mean models, heritability for residual variances ranged between 1.01×10(-3) and 4.17×10(-3) for all traits. The genetic standard deviation in residual variance (i.e., approximately the genetic coefficient of variation of residual variance) ranged between 0.12 and 0.17. Therefore, some genetic variance in micro-environmental sensitivity existed in the Walloon Holstein dairy cattle for the 5 studied traits. The standard deviations due to herd × test-day and permanent environment in residual variance ranged between 0.36 and 0.45 for herd × test-day effect and between 0.55 and 0.97 for permanent environmental effect. Therefore, nongenetic effects also contributed substantially to micro-environmental sensitivity. Addition of random regressions to the mean model did not reduce heterogeneity in residual variance and that genetic heterogeneity of residual variance was not simply an effect of an incomplete mean model. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Deviations from Newton's law in supersymmetric large extra dimensions

NASA Astrophysics Data System (ADS)

Callin, P.; Burgess, C. P.

2006-09-01

Deviations from Newton's inverse-squared law at the micron length scale are smoking-gun signals for models containing supersymmetric large extra dimensions (SLEDs), which have been proposed as approaches for resolving the cosmological constant problem. Just like their non-supersymmetric counterparts, SLED models predict gravity to deviate from the inverse-square law because of the advent of new dimensions at sub-millimeter scales. However SLED models differ from their non-supersymmetric counterparts in three important ways: (i) the size of the extra dimensions is fixed by the observed value of the dark energy density, making it impossible to shorten the range over which new deviations from Newton's law must be seen; (ii) supersymmetry predicts there to be more fields in the extra dimensions than just gravity, implying different types of couplings to matter and the possibility of repulsive as well as attractive interactions; and (iii) the same mechanism which is purported to keep the cosmological constant naturally small also keeps the extra-dimensional moduli effectively massless, leading to deviations from general relativity in the far infrared of the scalar-tensor form. We here explore the deviations from Newton's law which are predicted over micron distances, and show the ways in which they differ and resemble those in the non-supersymmetric case.

Accuracy of near infrared spectroscopy for prediction of chemical composition, salt content and free amino acids in dry-cured ham.

PubMed

Prevolnik, Maja; Škrlep, Martin; Janeš, Lucija; Velikonja-Bolta, Spela; Škorjanc, Dejan; Čandek-Potokar, Marjeta

2011-06-01

The capability of near infrared (NIR) spectroscopy was examined for the purposes of quality control of the traditional Slovenian dry-cured ham "Kraški pršut." Predictive models were developed for moisture, salt, protein, non-protein nitrogen, intramuscular fat and free amino acids in biceps femoris muscle (n = 135). The models' quality was assessed using statistical parameters: coefficient of determination (R(2)) and standard error (se) of cross-validation (CV) and external validation (EV). Residual predictive deviation (RPD) was also assessed. Best results were obtained for salt content and salt percentage in moisture/dry matter (R(CV)(2)>0.90, RPD>3.0), it was satisfactory for moisture, non-protein nitrogen, intramuscular fat and total free amino acids (R(CV)(2) = 0.75-0.90, RPD = 2.0-3.0), while not so for protein content and proteolysis index (R(CV)(2) = 0.65-0.75, RPD<2.0). Calibrations for individual free amino acids yielded R(CV)(2) from 0.40 to 0.90 and RPD from 1.3 to 2.9. Additional external validation of models on independent samples yielded comparable results. Based on the results, NIR spectroscopy can replace chemical methods in quality control of dry-cured ham. Copyright © 2011 Elsevier Ltd. All rights reserved.

Logging utilization research in the Pacific Northwest: residue prediction and unique research challenges

Treesearch

Erik C. Berg; Todd A. Morgan; Eric A. Simmons; Stanley J. Zarnoch

2015-01-01

Logging utilization research results have informed land managers of changes in utilization of forest growing stock for more than 40 years. The logging utilization residue ratio- growing stock residue volume/mill delivered volume- can be applied to historic or projected timber harvest volumes to predict woody residue volumes at varied spatial scales. Researchers at the...

New Approach To Hour-By-Hour Weather Forecast

NASA Astrophysics Data System (ADS)

Liao, Q. Q.; Wang, B.

2017-12-01

Fine hourly forecast in single station weather forecast is required in many human production and life application situations. Most previous MOS (Model Output Statistics) which used a linear regression model are hard to solve nonlinear natures of the weather prediction and forecast accuracy has not been sufficient at high temporal resolution. This study is to predict the future meteorological elements including temperature, precipitation, relative humidity and wind speed in a local region over a relatively short period of time at hourly level. By means of hour-to-hour NWP (Numeral Weather Prediction)meteorological field from Forcastio (https://darksky.net/dev/docs/forecast) and real-time instrumental observation including 29 stations in Yunnan and 3 stations in Tianjin of China from June to October 2016, predictions are made of the 24-hour hour-by-hour ahead. This study presents an ensemble approach to combine the information of instrumental observation itself and NWP. Use autoregressive-moving-average (ARMA) model to predict future values of the observation time series. Put newest NWP products into the equations derived from the multiple linear regression MOS technique. Handle residual series of MOS outputs with autoregressive (AR) model for the linear property presented in time series. Due to the complexity of non-linear property of atmospheric flow, support vector machine (SVM) is also introduced . Therefore basic data quality control and cross validation makes it able to optimize the model function parameters , and do 24 hours ahead residual reduction with AR/SVM model. Results show that AR model technique is better than corresponding multi-variant MOS regression method especially at the early 4 hours when the predictor is temperature. MOS-AR combined model which is comparable to MOS-SVM model outperform than MOS. Both of their root mean square error and correlation coefficients for 2 m temperature are reduced to 1.6 degree Celsius and 0.91 respectively. The forecast accuracy of 24- hour forecast deviation no more than 2 degree Celsius is 78.75 % for MOS-AR model and 81.23 % for AR model.

Text Mining Improves Prediction of Protein Functional Sites

PubMed Central

Cohn, Judith D.; Ravikumar, Komandur E.

2012-01-01

We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions. PMID:22393388

Through-Thickness Residual Stress Profiles in Austenitic Stainless Steel Welds: A Combined Experimental and Prediction Study

NASA Astrophysics Data System (ADS)

Mathew, J.; Moat, R. J.; Paddea, S.; Francis, J. A.; Fitzpatrick, M. E.; Bouchard, P. J.

2017-12-01

Economic and safe management of nuclear plant components relies on accurate prediction of welding-induced residual stresses. In this study, the distribution of residual stress through the thickness of austenitic stainless steel welds has been measured using neutron diffraction and the contour method. The measured data are used to validate residual stress profiles predicted by an artificial neural network approach (ANN) as a function of welding heat input and geometry. Maximum tensile stresses with magnitude close to the yield strength of the material were observed near the weld cap in both axial and hoop direction of the welds. Significant scatter of more than 200 MPa was found within the residual stress measurements at the weld center line and are associated with the geometry and welding conditions of individual weld passes. The ANN prediction is developed in an attempt to effectively quantify this phenomenon of `innate scatter' and to learn the non-linear patterns in the weld residual stress profiles. Furthermore, the efficacy of the ANN method for defining through-thickness residual stress profiles in welds for application in structural integrity assessments is evaluated.

A simple extension to the CMASA method for the prediction of catalytic residues in the presence of single point mutations.

PubMed

Flores, David I; Sotelo-Mundo, Rogerio R; Brizuela, Carlos A

2014-01-01

The automatic identification of catalytic residues still remains an important challenge in structural bioinformatics. Sequence-based methods are good alternatives when the query shares a high percentage of identity with a well-annotated enzyme. However, when the homology is not apparent, which occurs with many structures from the structural genome initiative, structural information should be exploited. A local structural comparison is preferred to a global structural comparison when predicting functional residues. CMASA is a recently proposed method for predicting catalytic residues based on a local structure comparison. The method achieves high accuracy and a high value for the Matthews correlation coefficient. However, point substitutions or a lack of relevant data strongly affect the performance of the method. In the present study, we propose a simple extension to the CMASA method to overcome this difficulty. Extensive computational experiments are shown as proof of concept instances, as well as for a few real cases. The results show that the extension performs well when the catalytic site contains mutated residues or when some residues are missing. The proposed modification could correctly predict the catalytic residues of a mutant thymidylate synthase, 1EVF. It also successfully predicted the catalytic residues for 3HRC despite the lack of information for a relevant side chain atom in the PDB file.

Contact Prediction for Beta and Alpha-Beta Proteins Using Integer Linear Optimization and its Impact on the First Principles 3D Structure Prediction Method ASTRO-FOLD

PubMed Central

Rajgaria, R.; Wei, Y.; Floudas, C. A.

2010-01-01

An integer linear optimization model is presented to predict residue contacts in β, α + β, and α/β proteins. The total energy of a protein is expressed as sum of a Cα – Cα distance dependent contact energy contribution and a hydrophobic contribution. The model selects contacts that assign lowest energy to the protein structure while satisfying a set of constraints that are included to enforce certain physically observed topological information. A new method based on hydrophobicity is proposed to find the β-sheet alignments. These β-sheet alignments are used as constraints for contacts between residues of β-sheets. This model was tested on three independent protein test sets and CASP8 test proteins consisting of β, α + β, α/β proteins and was found to perform very well. The average accuracy of the predictions (separated by at least six residues) was approximately 61%. The average true positive and false positive distances were also calculated for each of the test sets and they are 7.58 Å and 15.88 Å, respectively. Residue contact prediction can be directly used to facilitate the protein tertiary structure prediction. This proposed residue contact prediction model is incorporated into the first principles protein tertiary structure prediction approach, ASTRO-FOLD. The effectiveness of the contact prediction model was further demonstrated by the improvement in the quality of the protein structure ensemble generated using the predicted residue contacts for a test set of 10 proteins. PMID:20225257

Selective Radiofrequency Stimulation of the Dorsal Root Ganglion (DRG) as a Method for Predicting Targets for Neuromodulation in Patients With Post Amputation Pain: A Case Series.

PubMed

Hunter, Corey W; Yang, Ajax; Davis, Tim

2017-10-01

While spinal cord stimulation (SCS) has established itself as an accepted and validated treatment for neuropathic pain, there are a number of conditions where it has experienced less, long-term success: post amputee pain (PAP) being one of them. Dorsal root ganglion (DRG) stimulation has shown great promise, particularly in conditions where traditional SCS has fallen short. One major difference between DRG stimulation and traditional SCS is the ability to provide focal stimulation over targeted areas. While this may be a contributing factor to its superiority, it can also be a limitation insofar stimulating the wrong DRG(s) can lead to failure. This is particularly relevant in conditions like PAP where neuroplastic maladaptation occurs causing the pain to deviate from expected patterns, thus creating uncertainty and variability in predicting targets for stimulation. We propose selective radiofrequency (RF) stimulation of the DRG as a method for preoperatively predicting targets for neuromodulation in patients with PAP. We present four patients with PAP of the lower extremities. RF stimulation was used to selectively stimulate individual DRG's, creating areas of paresthesias to see which most closely correlated/overlapped with the painful area(s). RF stimulation to the DRG's that resulted in the desirable paresthesia coverage in the residual or the missing limb(s) was recorded as "positive." Trial DRG leads were placed based on the positive RF stimulation findings. In each patient, stimulating one or more DRG(s) produced paresthesias patterns that were contradictory to know dermatomal patterns. Upon completion of a one-week trial all four patients reported 60-90% pain relief, with coverage over the painful areas, and opted for permanent implant. Mapping the DRG via RF stimulation appears to provide improved accuracy for determining lead placement in the setting of PAP where pain patterns are known to deviate from conventional dermatomal mapping. © 2017 International Neuromodulation Society.

Dissipation dynamic, residue distribution and processing factor of hexythiazox in strawberry fruits under open field condition.

PubMed

Saber, Ayman N; Malhat, Farag M; Badawy, Hany M A; Barakat, Dalia A

2016-04-01

Two independent field trials were performed to investigate the dissipation and residue levels of hexythiazox in strawberry. The study presents a method validation for extraction and quantitative analysis of hexythiazox residues in strawberry using HPLC-DAD. The results shown that the mean recoveries ranged from 85% to 93%, furthermore the intra- and inter-day relative standard deviations were less than 10%. The results suggest that the hexythiazox dissipation curves followed the first-order kinetic and its half-life ranged from 3.43 to 3.81 days. The final residues in strawberry were below the Codex maximum residue limit (MRL) (6 mg/kg) after three days of the application. The effects of household processing and storage on the levels of hexythiazox residues were quantified, and it's useful for reducing the dietary exposure. The processing factor after each stage were generally less than 1, indicating that the whole process can reduce the residues of hexythiazox in strawberry. The results could provide guidance to safe and reasonable use of hexythiazox in agriculture. Copyright © 2015 Elsevier Ltd. All rights reserved.

Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions

NASA Technical Reports Server (NTRS)

Spear, Ashley D.; Priest, Amanda R.; Veilleux, Michael G.; Ingraffea, Anthony R.; Hochhalter, Jacob D.

2011-01-01

A surrogate model methodology is described for predicting in real time the residual strength of flight structures with discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. A residual strength test of a metallic, integrally-stiffened panel is simulated to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data would, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high-fidelity fracture simulation framework provide useful tools for adaptive flight technology.

Passive correlation ranging of a geostationary satellite using DVB-S payload signals.

NASA Astrophysics Data System (ADS)

Shakun, Leonid; Shulga, Alexandr; Sybiryakova, Yevgeniya; Bushuev, Felix; Kaliuzhnyi, Mykola; Bezrukovs, Vladislavs; Moskalenko, Sergiy; Kulishenko, Vladislav; Balagura, Oleg

2016-07-01

Passive correlation ranging (PaCoRa) for geostationary satellites is now considered as an alternate to tone-ranging (https://artes.esa.int/search/node/PaCoRa). The PaCoRa method has been employed in the Research Institute "Nikolaev astronomical observatory" since the first experiment in August 2011 with two stations spatially separated on 150 km. The PaCoRa has been considered as an independent method for tracking the future Ukrainian geostationary satellite "Lybid'. Now a radio engineering complex (RC) for passive ranging consists of five spatially separated stations of receiving digital satellite television and a data processing center located in Mykolaiv. The stations are located in Kyiv, Kharkiv, Mukacheve, Mykolaiv (Ukraine) and in Ventspils (Latvia). Each station has identical equipment. The equipment allows making synchronous recording of fragments of the DVB-S signal from the quadrature detector output of a satellite television receiver. The fragments are recorded every second. Synchronization of the stations is performed using GPS receivers. Samples of the complex signal obtained in this way are archived and are sent to the data processing center over the Internet. Here the time differences of arrival (TDOA) for pairs of the stations are determined as a result of correlation processing of received signals. The values of the TDOA that measured every second are used for orbit determination (OD) of the satellite. The results of orbit determination of the geostationary telecommunication satellite "Eutelsat-13B" (13º East) obtained during about four months of observations in 2015 are presented in the report. The TDOA and OD accuracies are also given. Single-measurement error (1 sigma) of the TDOA is equal about 8.7 ns for all pairs of the stations. Standard deviations and average values of the residuals between the observed TDOA and the TDOA computed using the orbit elements obtained from optical measurements are estimated for the pairs Kharkiv-Mykolaiv and Mukacheve-Mykolaiv. The standard deviations do not exceed 10 ns for the both pairs and the average values are equal +10 ns and -106 ns respectively for Kharkiv-Mykolaiv and Mukacheve-Mykolaiv. We discuss the residuals between the observed TDOA and estimates of the TDOA that are calculated by fitted models of satellite motion: the SGP4/SDP4 model and the model based on the numerical integration of the equations of motion taking into account the geopotential, and the perturbation from the Moon and the Sun. We note that residuals from the model SGP4/SDP4 have periodic deviations due to the inaccuracy of the SGP4/SDP4 model. As a result, estimation of the standard deviation of the satellite position is about 60 m for the epoch of the SGP4/SDP4 orbit elements. The residuals for the numerical model in the interval of one day do not show low-frequency deviation. In this case, the estimate of the standard deviation of the satellite position is about 12 m for the epoch of the numerical orbit elements. Keywords. DVB-S, geostationary satellite, orbit determination, passive ranging.

Forty-five degree cutting septoplasty.

PubMed

Hsiao, Yen-Chang; Chang, Chun-Shin; Chuang, Shiow-Shuh; Kolios, Georgios; Abdelrahman, Mohamed

2016-01-01

The crooked nose represents a challenge for rhinoplasty surgeons, and many methods have been proposed for management; however, there is no ideal method for treatment. Accordingly, the 45° cutting septoplasty technique, which involves a 45° cut at the junction of the L-shaped strut and repositioning it to achieve a straight septum is proposed. From October 2010 to September 2014, 43 patients underwent the 45° cutting septoplasty technique. There were 28 men and 15 women, with ages ranging from 20 to 58 years (mean, 33 years). Standardized photographs were obtained at every visit. Established photogrammetric parameters were used to describe the degree of correction: Correction rate = (preoperative total deviation - postoperative residual deviation)/preoperative total deviation × 100% was proposed. The mean follow-up period for all patients was 12.3 months. The mean preoperative deviation was 64.3° and the mean postoperative deviation was 2.7°; the overall correction rate was 95.8%. One patient experienced composite implant deviation two weeks postoperatively and underwent revision rhinoplasty. There were no infections, hematomas or postoperative bleeding. Based on the clinical observation of all patients during the follow-up period, the 45° cutting septoplasty technique was shown to be effective for the treatment of crooked nose.

Distribution of kriging errors, the implications and how to communicate them

NASA Astrophysics Data System (ADS)

Li, Hong Yi; Milne, Alice; Webster, Richard

2016-04-01

Kriging in one form or another has become perhaps the most popular method for spatial prediction in environmental science. Each prediction is unbiased and of minimum variance, which itself is estimated. The kriging variances depend on the mathematical model chosen to describe the spatial variation; different models, however plausible, give rise to different minimized variances. Practitioners often compare models by so-called cross-validation before finally choosing the most appropriate for their kriging. One proceeds as follows. One removes a unit (a sampling point) from the whole set, kriges the value there and compares the kriged value with the value observed to obtain the deviation or error. One repeats the process for each and every point in turn and for all plausible models. One then computes the mean errors (MEs) and the mean of the squared errors (MSEs). Ideally a squared error should equal the corresponding kriging variance (σK2), and so one is advised to choose the model for which on average the squared errors most nearly equal the kriging variances, i.e. the ratio MSDR = MSE/σK2 ≈ 1. Maximum likelihood estimation of models almost guarantees that the MSDR equals 1, and so the kriging variances are unbiased predictors of the squared error across the region. The method is based on the assumption that the errors have a normal distribution. The squared deviation ratio (SDR) should therefore be distributed as χ2 with one degree of freedom with a median of 0.455. We have found that often the median of the SDR (MedSDR) is less, in some instances much less, than 0.455 even though the mean of the SDR is close to 1. It seems that in these cases the distributions of the errors are leptokurtic, i.e. they have an excess of predictions close to the true values, excesses near the extremes and a dearth of predictions in between. In these cases the kriging variances are poor measures of the uncertainty at individual sites. The uncertainty is typically under-estimated for the extreme observations and compensated for by over estimating for other observations. Statisticians must tell users when they present maps of predictions. We illustrate the situation with results from mapping salinity in land reclaimed from the Yangtze delta in the Gulf of Hangzhou, China. There the apparent electrical conductivity (ECa) of the topsoil was measured at 525 points in a field of 2.3 ha. The marginal distribution of the observations was strongly positively skewed, and so the observed ECas were transformed to their logarithms to give an approximately symmetric distribution. That distribution was strongly platykurtic with short tails and no evident outliers. The logarithms were analysed as a mixed model of quadratic drift plus correlated random residuals with a spherical variogram. The kriged predictions that deviated from their true values with an MSDR of 0.993, but with a medSDR=0.324. The coefficient of kurtosis of the deviations was 1.45, i.e. substantially larger than 0 for a normal distribution. The reasons for this behaviour are being sought. The most likely explanation is that there are spatial outliers, i.e. points at which the observed values that differ markedly from those at their their closest neighbours.

Distribution of kriging errors, the implications and how to communicate them

NASA Astrophysics Data System (ADS)

Li, HongYi; Milne, Alice; Webster, Richard

2015-04-01

Kriging in one form or another has become perhaps the most popular method for spatial prediction in environmental science. Each prediction is unbiased and of minimum variance, which itself is estimated. The kriging variances depend on the mathematical model chosen to describe the spatial variation; different models, however plausible, give rise to different minimized variances. Practitioners often compare models by so-called cross-validation before finally choosing the most appropriate for their kriging. One proceeds as follows. One removes a unit (a sampling point) from the whole set, kriges the value there and compares the kriged value with the value observed to obtain the deviation or error. One repeats the process for each and every point in turn and for all plausible models. One then computes the mean errors (MEs) and the mean of the squared errors (MSEs). Ideally a squared error should equal the corresponding kriging variance (σ_K^2), and so one is advised to choose the model for which on average the squared errors most nearly equal the kriging variances, i.e. the ratio MSDR=MSE/ σ_K2 ≈1. Maximum likelihood estimation of models almost guarantees that the MSDR equals 1, and so the kriging variances are unbiased predictors of the squared error across the region. The method is based on the assumption that the errors have a normal distribution. The squared deviation ratio (SDR) should therefore be distributed as χ2 with one degree of freedom with a median of 0.455. We have found that often the median of the SDR (MedSDR) is less, in some instances much less, than 0.455 even though the mean of the SDR is close to 1. It seems that in these cases the distributions of the errors are leptokurtic, i.e. they have an excess of predictions close to the true values, excesses near the extremes and a dearth of predictions in between. In these cases the kriging variances are poor measures of the uncertainty at individual sites. The uncertainty is typically under-estimated for the extreme observations and compensated for by over estimating for other observations. Statisticians must tell users when they present maps of predictions. We illustrate the situation with results from mapping salinity in land reclaimed from the Yangtze delta in the Gulf of Hangzhou, China. There the apparent electrical conductivity (EC_a) of the topsoil was measured at 525 points in a field of 2.3~ha. The marginal distribution of the observations was strongly positively skewed, and so the observed EC_as were transformed to their logarithms to give an approximately symmetric distribution. That distribution was strongly platykurtic with short tails and no evident outliers. The logarithms were analysed as a mixed model of quadratic drift plus correlated random residuals with a spherical variogram. The kriged predictions that deviated from their true values with an MSDR of 0.993, but with a medSDR=0.324. The coefficient of kurtosis of the deviations was 1.45, i.e. substantially larger than 0 for a normal distribution. The reasons for this behaviour are being sought. The most likely explanation is that there are spatial outliers, i.e. points at which the observed values that differ markedly from those at their their closest neighbours.

Hurricane track forecast cones from fluctuations

PubMed Central

Meuel, T.; Prado, G.; Seychelles, F.; Bessafi, M.; Kellay, H.

2012-01-01

Trajectories of tropical cyclones may show large deviations from predicted tracks leading to uncertainty as to their landfall location for example. Prediction schemes usually render this uncertainty by showing track forecast cones representing the most probable region for the location of a cyclone during a period of time. By using the statistical properties of these deviations, we propose a simple method to predict possible corridors for the future trajectory of a cyclone. Examples of this scheme are implemented for hurricane Ike and hurricane Jimena. The corridors include the future trajectory up to at least 50 h before landfall. The cones proposed here shed new light on known track forecast cones as they link them directly to the statistics of these deviations. PMID:22701776

On-line determination of transient stability status using multilayer perceptron neural network

NASA Astrophysics Data System (ADS)

Frimpong, Emmanuel Asuming; Okyere, Philip Yaw; Asumadu, Johnson

2018-01-01

A scheme to predict transient stability status following a disturbance is presented. The scheme is activated upon the tripping of a line or bus and operates as follows: Two samples of frequency deviation values at all generator buses are obtained. At each generator bus, the maximum frequency deviation within the two samples is extracted. A vector is then constructed from the extracted maximum frequency deviations. The Euclidean norm of the constructed vector is calculated and then fed as input to a trained multilayer perceptron neural network which predicts the stability status of the system. The scheme was tested using data generated from the New England test system. The scheme successfully predicted the stability status of all two hundred and five disturbance test cases.

A model of curved saccade trajectories: spike rate adaptation in the brainstem as the cause of deviation away.

PubMed

Kruijne, Wouter; Van der Stigchel, Stefan; Meeter, Martijn

2014-03-01

The trajectory of saccades to a target is often affected whenever there is a distractor in the visual field. Distractors can cause a saccade to deviate towards their location or away from it. The oculomotor mechanisms that produce deviation towards distractors have been thoroughly explored in behavioral, neurophysiological and computational studies. The mechanisms underlying deviation away, on the other hand, remain unclear. Behavioral findings suggest a mechanism of spatially focused, top-down inhibition in a saccade map, and deviation away has become a tool to investigate such inhibition. However, this inhibition hypothesis has little neuroanatomical or neurophysiological support, and recent findings go against it. Here, we propose that deviation away results from an unbalanced saccade drive from the brainstem, caused by spike rate adaptation in brainstem long-lead burst neurons. Adaptation to stimulation in the direction of the distractor results in an unbalanced drive away from it. An existing model of the saccade system was extended with this theory. The resulting model simulates a wide range of findings on saccade trajectories, including findings that have classically been interpreted to support inhibition views. Furthermore, the model replicated the effect of saccade latency on deviation away, but predicted this effect would be absent with large (400 ms) distractor-target onset asynchrony. This prediction was confirmed in an experiment, which demonstrates that the theory both explains classical findings on saccade trajectories and predicts new findings. Copyright © 2014 Elsevier Inc. All rights reserved.

PREDICTING CHEMICAL RESIDUES IN AQUATIC FOOD CHAINS

EPA Science Inventory

The need to accurately predict chemical accumulation in aquatic organisms is critical for a variety of environmental applications including the assessment of contaminated sediments. Approaches for predicting chemical residues can be divided into two general classes, empirical an...

Bio-knowledge based filters improve residue-residue contact prediction accuracy.

PubMed

Wozniak, P P; Pelc, J; Skrzypecki, M; Vriend, G; Kotulska, M

2018-05-29

Residue-residue contact prediction through direct coupling analysis has reached impressive accuracy, but yet higher accuracy will be needed to allow for routine modelling of protein structures. One way to improve the prediction accuracy is to filter predicted contacts using knowledge about the particular protein of interest or knowledge about protein structures in general. We focus on the latter and discuss a set of filters that can be used to remove false positive contact predictions. Each filter depends on one or a few cut-off parameters for which the filter performance was investigated. Combining all filters while using default parameters resulted for a test-set of 851 protein domains in the removal of 29% of the predictions of which 92% were indeed false positives. All data and scripts are available from http://comprec-lin.iiar.pwr.edu.pl/FPfilter/. malgorzata.kotulska@pwr.edu.pl. Supplementary data are available at Bioinformatics online.

Effect of polymer residues on the electrical properties of large-area graphene–hexagonal boron nitride planar heterostructures

DOE PAGES

Voyloy, Dimitry; Lassiter, Matthew G.; Sokolov, Alexei P.; ...

2017-06-19

Polymer residue plays an important role in the performance of 2D heterostructured materials. Herein, we study the effect of polymer residual impurities on the electrical properties of graphene–boron nitride planar heterostructures. Large-area graphene (Gr) and hexagonal boron nitride (h-BN) monolayers were synthesized using chemical vapor deposition techniques. Atomic van-der-Waals heterostructure layers based on varied configurations of Gr and h-BN layers were assembled. The average interlayer resistance of the heterojunctions over a 1 cm 2 area for several planar heterostructure configurations was assessed by impedance spectroscopy and modeled by equivalent electrical circuits. As a result, conductive AFM measurements showed that themore » presence of polymer residues on the surface of the Gr and h-BN monolayers resulted in significant resistance deviations over nanoscale regions.« less

Effect of polymer residues on the electrical properties of large-area graphene–hexagonal boron nitride planar heterostructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Voyloy, Dimitry; Lassiter, Matthew G.; Sokolov, Alexei P.

Polymer residue plays an important role in the performance of 2D heterostructured materials. Herein, we study the effect of polymer residual impurities on the electrical properties of graphene–boron nitride planar heterostructures. Large-area graphene (Gr) and hexagonal boron nitride (h-BN) monolayers were synthesized using chemical vapor deposition techniques. Atomic van-der-Waals heterostructure layers based on varied configurations of Gr and h-BN layers were assembled. The average interlayer resistance of the heterojunctions over a 1 cm 2 area for several planar heterostructure configurations was assessed by impedance spectroscopy and modeled by equivalent electrical circuits. As a result, conductive AFM measurements showed that themore » presence of polymer residues on the surface of the Gr and h-BN monolayers resulted in significant resistance deviations over nanoscale regions.« less

Modeling and monitoring of tooth fillet crack growth in dynamic simulation of spur gear set

NASA Astrophysics Data System (ADS)

Guilbault, Raynald; Lalonde, Sébastien; Thomas, Marc

2015-05-01

This study integrates a linear elastic fracture mechanics analysis of the tooth fillet crack propagation into a nonlinear dynamic model of spur gear sets. An original formulation establishes the rigidity of sound and damaged teeth. The formula incorporates the contribution of the flexible gear body and real crack trajectories in the fillet zone. The work also develops a KI prediction formula. A validation of the equation estimates shows that the predicted KI are in close agreement with published numerical and experimental values. The representation also relies on the Paris-Erdogan equation completed with crack closure effects. The analysis considers that during dN fatigue cycles, a harmonic mean of ΔK assures optimal evaluations. The paper evaluates the influence of the mesh frequency distance from the resonances of the system. The obtained results indicate that while the dependence may demonstrate obvious nonlinearities, the crack progression rate increases with a mesh frequency augmentation. The study develops a tooth fillet crack propagation detection procedure based on residual signals (RS) prepared in the frequency domain. The proposed approach accepts any gear conditions as reference signature. The standard deviation and mean values of the RS are evaluated as gear condition descriptors. A trend tracking of their responses obtained from a moving linear regression completes the analysis. Globally, the results show that, regardless of the reference signal, both descriptors are sensitive to the tooth fillet crack and sharply react to tooth breakage. On average, the mean value detected the crack propagation after a size increase of 3.69 percent as compared to the reference condition, whereas the standard deviation required crack progressions of 12.24 percent. Moreover, the mean descriptor shows evolutions closer to the crack size progression.

Residual Stresses in 21-6-9 Stainless Steel Warm Forgings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Everhart, Wesley A.; Lee, Jordan D.; Broecker, Daniel J.

Forging residual stresses are detrimental to the production and performance of derived machined parts due to machining distortions, corrosion drivers and fatigue crack drivers. Residual strains in a 21-6-9 stainless steel warm High Energy Rate Forging (HERF) were measured via neutron diffraction. The finite element analysis (FEA) method was used to predict the residual stresses that occur during forging and water quenching. The experimentally measured residual strains were used to calibrate simulations of the three-dimensional residual stress state of the forging. ABAQUS simulation tools predicted residual strains that tend to match with experimental results when varying yield strength is considered.

Design and Evaluation of a Dynamic Programming Flight Routing Algorithm Using the Convective Weather Avoidance Model

NASA Technical Reports Server (NTRS)

Ng, Hok K.; Grabbe, Shon; Mukherjee, Avijit

2010-01-01

The optimization of traffic flows in congested airspace with varying convective weather is a challenging problem. One approach is to generate shortest routes between origins and destinations while meeting airspace capacity constraint in the presence of uncertainties, such as weather and airspace demand. This study focuses on development of an optimal flight path search algorithm that optimizes national airspace system throughput and efficiency in the presence of uncertainties. The algorithm is based on dynamic programming and utilizes the predicted probability that an aircraft will deviate around convective weather. It is shown that the running time of the algorithm increases linearly with the total number of links between all stages. The optimal routes minimize a combination of fuel cost and expected cost of route deviation due to convective weather. They are considered as alternatives to the set of coded departure routes which are predefined by FAA to reroute pre-departure flights around weather or air traffic constraints. A formula, which calculates predicted probability of deviation from a given flight path, is also derived. The predicted probability of deviation is calculated for all path candidates. Routes with the best probability are selected as optimal. The predicted probability of deviation serves as a computable measure of reliability in pre-departure rerouting. The algorithm can also be extended to automatically adjust its design parameters to satisfy the desired level of reliability.

Cosmological implications of a large complete quasar sample

PubMed Central

Segal, I. E.; Nicoll, J. F.

1998-01-01

Objective and reproducible determinations of the probabilistic significance levels of the deviations between theoretical cosmological prediction and direct model-independent observation are made for the Large Bright Quasar Sample [Foltz, C., Chaffee, F. H., Hewett, P. C., MacAlpine, G. M., Turnshek, D. A., et al. (1987) Astron. J. 94, 1423–1460]. The Expanding Universe model as represented by the Friedman–Lemaitre cosmology with parameters qo = 0, Λ = 0 denoted as C1 and chronometric cosmology (no relevant adjustable parameters) denoted as C2 are the cosmologies considered. The mean and the dispersion of the apparent magnitudes and the slope of the apparent magnitude–redshift relation are the directly observed statistics predicted. The C1 predictions of these cosmology-independent quantities are deviant by as much as 11σ from direct observation; none of the C2 predictions deviate by >2σ. The C1 deviations may be reconciled with theory by the hypothesis of quasar “evolution,” which, however, appears incapable of being substantiated through direct observation. The excellent quantitative agreement of the C1 deviations with those predicted by C2 without adjustable parameters for the results of analysis predicated on C1 indicates that the evolution hypothesis may well be a theoretical artifact. PMID:9560182

Reduction of Deviation Angle During Occlusion Therapy: In Partially Accommodative Esotropia with Moderate Amblyopia

PubMed Central

Chun, Bo Young; Kwon, Soon Jae; Chae, Sun Hwa

2007-01-01

Purpose To evaluate changes in ocular alignment in partially accommodative esotropic children age ranged from 3 to 8 years during occlusion therapy for amblyopia. Methods Angle measurements of twenty-two partially accommodative esotropic patients with moderate amblyopia were evaluated before and at 2 years after occlusion therapy. Results Mean deviation angle with glasses at the start of occlusion treatment was 19.45±5.97 PD and decreased to 12.14±12.96 PD at 2 years after occlusion therapy (p<0.01). After occlusion therapy, 9 (41%) cases were indications of surgery for residual deviation but if we had planned surgery before occlusion treatment, 18 (82%) of patients would have had surgery. There was a statistical relationship between increase of visual acuity ratio and decrease of deviation angle (r=-0.479, p=0.024). Conclusions There was a significant reduction of deviation angle of partially accommodative esotropic patients at 2 years after occlusion therapy. Our results suggest that occlusion therapy has an influence on ocular alignment in partially accommodative esotropic patients with amblyopia. PMID:17804922

Clumped isotope effects during OH and Cl oxidation of methane

NASA Astrophysics Data System (ADS)

Whitehill, Andrew R.; Joelsson, Lars Magnus T.; Schmidt, Johan A.; Wang, David T.; Johnson, Matthew S.; Ono, Shuhei

2017-01-01

A series of experiments were carried out to determine the clumped (13CH3D) methane kinetic isotope effects during oxidation of methane by OH and Cl radicals, the major sink reactions for atmospheric methane. Experiments were performed in a 100 L quartz photochemical reactor, in which OH was produced from the reaction of O(1D) (from O3 photolysis) with H2O, and Cl was from photolysis of Cl2. Samples were taken from the reaction cell and analyzed for methane (12CH4, 12CH3D, 13CH4, 13CH3D) isotopologue ratios using tunable infrared laser direct absorption spectroscopy. Measured kinetic isotope effects for singly substituted species were consistent with previous experimental studies. For doubly substituted methane, 13CH3D, the observed kinetic isotope effects closely follow the product of the kinetic isotope effects for the 13C and deuterium substituted species (i.e., 13,2KIE = 13KIE × 2KIE). The deviation from this relationship is 0.3‰ ± 1.2‰ and 3.5‰ ± 0.7‰ for OH and Cl oxidation, respectively. This is consistent with model calculations performed using quantum chemistry and transition state theory. The OH and Cl reactions enrich the residual methane in the clumped isotopologue in open system reactions. In a closed system, however, this effect is overtaken by the large D/H isotope effect, which causes the residual methane to become anti-clumped relative to the initial methane. Based on these results, we demonstrate that oxidation of methane by OH, the predominant oxidant for tropospheric methane, will only have a minor (∼0.3‰) impact on the clumped isotope signature (Δ13CH3D, measured as a deviation from a stochastic distribution of isotopes) of tropospheric methane. This paper shows that Δ13CH3D will provide constraints on methane source strengths, and predicts that Δ12CH2D2 can provide information on methane sink strengths.

Distribution of pesticide residues in soil and uncertainty of sampling.

PubMed

Suszter, Gabriela K; Ambrus, Árpád

2017-08-03

Pesticide residues were determined in about 120 soil cores taken randomly from the top 15 cm layer of two sunflower fields about 30 days after preemergence herbicide treatments. Samples were extracted with acetone-ethyl acetate mixture and the residues were determined with GC-TSD. Residues of dimethenamid, pendimethalin, and prometryn ranged from 0.005 to 2.97 mg/kg. Their relative standard deviations (CV) were between 0.66 and 1.13. The relative frequency distributions of residues in soil cores were very similar to those observed in root and tuber vegetables grown in pesticide treated soils. Based on all available information, a typical CV of 1.00 was estimated for pesticide residues in primary soil samples (soil cores). The corresponding expectable relative uncertainty of sampling is 20% when composite samples of size 25 are taken. To obtain a reliable estimate of the average residues in the top 15 cm layer of soil of a field up to 8 independent replicate random samples should be taken. To obtain better estimate of the actual residue level of the sampled filed would be marginal if larger number of samples were taken.

Prediction of interface residue based on the features of residue interaction network.

PubMed

Jiao, Xiong; Ranganathan, Shoba

2017-11-07

Protein-protein interaction plays a crucial role in the cellular biological processes. Interface prediction can improve our understanding of the molecular mechanisms of the related processes and functions. In this work, we propose a classification method to recognize the interface residue based on the features of a weighted residue interaction network. The random forest algorithm is used for the prediction and 16 network parameters and the B-factor are acting as the element of the input feature vector. Compared with other similar work, the method is feasible and effective. The relative importance of these features also be analyzed to identify the key feature for the prediction. Some biological meaning of the important feature is explained. The results of this work can be used for the related work about the structure-function relationship analysis via a residue interaction network model. Copyright © 2017 Elsevier Ltd. All rights reserved.

Variability and rapid increase in body mass index during childhood are associated with adult obesity.

PubMed

Li, Shengxu; Chen, Wei; Sun, Dianjianyi; Fernandez, Camilo; Li, Jian; Kelly, Tanika; He, Jiang; Krousel-Wood, Marie; Whelton, Paul K

2015-12-01

Body mass index (BMI) in childhood predicts obesity in adults, but it is unknown whether rapid increase and variability in BMI during childhood are independent predictors of adult obesity. The study cohort consisted of 1622 Bogalusa Heart Study participants (aged 20 to 51 years at follow-up) who had been screened at least four times during childhood (aged 4-19 years). BMI rate of change during childhood for each individual was assessed by mixed models; BMI residual standard deviation (RSD) during childhoodwas used as a measure of variability. The average follow-up period was 20.9 years. One standard deviation increase in rate of change in BMI during childhood was associated with 1.39 [95% confidence interval (CI): 1.17-1.61] kg/m(2) increase in adult BMI and 2.98 (95% CI: 2.42-3.56) cm increase in adult waist circumference, independently of childhood mean BMI. Similarly, one standard deviation increase in RSD in BMI during childhood was associated with 0.46 (95% CI: 0.23-0.69) kg/m(2) increase in adult BMI and 1.42 (95% CI: 0.82-2.02) cm increase in adult waist circumference. Odds ratio for adult obesity progressively increased from the lowest to the highest quartile of BMI rate of change or RSD during childhood (P for trend < 0.05 for both). Rapid increase and greater variability in BMI during childhood appear to be independent risk factors for adult obesity. Our findings have implications for understanding body weight regulation and obesity development from childhood to adulthood. © The Author 2015; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

Fatigue Life Variability in Large Aluminum Forgings with Residual Stress

DTIC Science & Technology

2011-07-01

been conducted. A detailed finite element analysis of the forge/ quench /coldwork/machine process was performed in order to predict the bulk residual...forge/ quench /coldwork/machine process was performed in order to predict the bulk residual stresses in a fictitious aluminum bulkhead. The residual...continues to develop the capability for computational simulation of the forge, quench , cold work and machining processes. In order to handle the

InterProSurf: a web server for predicting interacting sites on protein surfaces

PubMed Central

Negi, Surendra S.; Schein, Catherine H.; Oezguen, Numan; Power, Trevor D.; Braun, Werner

2009-01-01

Summary A new web server, InterProSurf, predicts interacting amino acid residues in proteins that are most likely to interact with other proteins, given the 3D structures of subunits of a protein complex. The prediction method is based on solvent accessible surface area of residues in the isolated subunits, a propensity scale for interface residues and a clustering algorithm to identify surface regions with residues of high interface propensities. Here we illustrate the application of InterProSurf to determine which areas of Bacillus anthracis toxins and measles virus hemagglutinin protein interact with their respective cell surface receptors. The computationally predicted regions overlap with those regions previously identified as interface regions by sequence analysis and mutagenesis experiments. PMID:17933856

Tree morphologic plasticity explains deviation from metabolic scaling theory in semi-arid conifer forests, southwestern USA

Treesearch

Tyson L. Swetnam; Christopher D. O' Connor; Ann M. Lynch

2016-01-01

A significant concern about Metabolic Scaling Theory (MST) in real forests relates to consistent differences between the values of power law scaling exponents of tree primary size measures used to estimate mass and those predicted by MST. Here we consider why observed scaling exponents for diameter and height relationships deviate from MST predictions across...

Slash prediction: a test in commercial thinnings in northeasrern California

Treesearch

C. Phillip Weatherspoon; Gary O. Fiddler

1984-01-01

Two slash prediction handbooks commonly used in California do not use data from California. To test predictions of the handbooks in northeastern California, logging residues from commercially thinned young-growth stands were surveyed. Measured residues were compared to handbook predictions. Species represented were ponderosa pine, California white fir, California red...

Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model.

PubMed

Wang, Sheng; Sun, Siqi; Li, Zhen; Zhang, Renyu; Xu, Jinbo

2017-01-01

Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predicted contacts for proteins without many sequence homologs is still of low quality and not very useful for de novo structure prediction. This paper presents a new deep learning method that predicts contacts by integrating both evolutionary coupling (EC) and sequence conservation information through an ultra-deep neural network formed by two deep residual neural networks. The first residual network conducts a series of 1-dimensional convolutional transformation of sequential features; the second residual network conducts a series of 2-dimensional convolutional transformation of pairwise information including output of the first residual network, EC information and pairwise potential. By using very deep residual networks, we can accurately model contact occurrence patterns and complex sequence-structure relationship and thus, obtain higher-quality contact prediction regardless of how many sequence homologs are available for proteins in question. Our method greatly outperforms existing methods and leads to much more accurate contact-assisted folding. Tested on 105 CASP11 targets, 76 past CAMEO hard targets, and 398 membrane proteins, the average top L long-range prediction accuracy obtained by our method, one representative EC method CCMpred and the CASP11 winner MetaPSICOV is 0.47, 0.21 and 0.30, respectively; the average top L/10 long-range accuracy of our method, CCMpred and MetaPSICOV is 0.77, 0.47 and 0.59, respectively. Ab initio folding using our predicted contacts as restraints but without any force fields can yield correct folds (i.e., TMscore>0.6) for 203 of the 579 test proteins, while that using MetaPSICOV- and CCMpred-predicted contacts can do so for only 79 and 62 of them, respectively. Our contact-assisted models also have much better quality than template-based models especially for membrane proteins. The 3D models built from our contact prediction have TMscore>0.5 for 208 of the 398 membrane proteins, while those from homology modeling have TMscore>0.5 for only 10 of them. Further, even if trained mostly by soluble proteins, our deep learning method works very well on membrane proteins. In the recent blind CAMEO benchmark, our fully-automated web server implementing this method successfully folded 6 targets with a new fold and only 0.3L-2.3L effective sequence homologs, including one β protein of 182 residues, one α+β protein of 125 residues, one α protein of 140 residues, one α protein of 217 residues, one α/β of 260 residues and one α protein of 462 residues. Our method also achieved the highest F1 score on free-modeling targets in the latest CASP (Critical Assessment of Structure Prediction), although it was not fully implemented back then. http://raptorx.uchicago.edu/ContactMap/.

Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model

PubMed Central

Li, Zhen; Zhang, Renyu

2017-01-01

Motivation Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predicted contacts for proteins without many sequence homologs is still of low quality and not very useful for de novo structure prediction. Method This paper presents a new deep learning method that predicts contacts by integrating both evolutionary coupling (EC) and sequence conservation information through an ultra-deep neural network formed by two deep residual neural networks. The first residual network conducts a series of 1-dimensional convolutional transformation of sequential features; the second residual network conducts a series of 2-dimensional convolutional transformation of pairwise information including output of the first residual network, EC information and pairwise potential. By using very deep residual networks, we can accurately model contact occurrence patterns and complex sequence-structure relationship and thus, obtain higher-quality contact prediction regardless of how many sequence homologs are available for proteins in question. Results Our method greatly outperforms existing methods and leads to much more accurate contact-assisted folding. Tested on 105 CASP11 targets, 76 past CAMEO hard targets, and 398 membrane proteins, the average top L long-range prediction accuracy obtained by our method, one representative EC method CCMpred and the CASP11 winner MetaPSICOV is 0.47, 0.21 and 0.30, respectively; the average top L/10 long-range accuracy of our method, CCMpred and MetaPSICOV is 0.77, 0.47 and 0.59, respectively. Ab initio folding using our predicted contacts as restraints but without any force fields can yield correct folds (i.e., TMscore>0.6) for 203 of the 579 test proteins, while that using MetaPSICOV- and CCMpred-predicted contacts can do so for only 79 and 62 of them, respectively. Our contact-assisted models also have much better quality than template-based models especially for membrane proteins. The 3D models built from our contact prediction have TMscore>0.5 for 208 of the 398 membrane proteins, while those from homology modeling have TMscore>0.5 for only 10 of them. Further, even if trained mostly by soluble proteins, our deep learning method works very well on membrane proteins. In the recent blind CAMEO benchmark, our fully-automated web server implementing this method successfully folded 6 targets with a new fold and only 0.3L-2.3L effective sequence homologs, including one β protein of 182 residues, one α+β protein of 125 residues, one α protein of 140 residues, one α protein of 217 residues, one α/β of 260 residues and one α protein of 462 residues. Our method also achieved the highest F1 score on free-modeling targets in the latest CASP (Critical Assessment of Structure Prediction), although it was not fully implemented back then. Availability http://raptorx.uchicago.edu/ContactMap/ PMID:28056090

Application of Visible and Near-Infrared Hyperspectral Imaging to Determine Soluble Protein Content in Oilseed Rape Leaves

PubMed Central

Zhang, Chu; Liu, Fei; Kong, Wenwen; He, Yong

2015-01-01

Visible and near-infrared hyperspectral imaging covering spectral range of 380–1030 nm as a rapid and non-destructive method was applied to estimate the soluble protein content of oilseed rape leaves. Average spectrum (500–900 nm) of the region of interest (ROI) of each sample was extracted, and four samples out of 128 samples were defined as outliers by Monte Carlo-partial least squares (MCPLS). Partial least squares (PLS) model using full spectra obtained dependable performance with the correlation coefficient (rp) of 0.9441, root mean square error of prediction (RMSEP) of 0.1658 mg/g and residual prediction deviation (RPD) of 2.98. The weighted regression coefficient (Bw), successive projections algorithm (SPA) and genetic algorithm-partial least squares (GAPLS) selected 18, 15, and 16 sensitive wavelengths, respectively. SPA-PLS model obtained the best performance with rp of 0.9554, RMSEP of 0.1538 mg/g and RPD of 3.25. Distribution of protein content within the rape leaves were visualized and mapped on the basis of the SPA-PLS model. The overall results indicated that hyperspectral imaging could be used to determine and visualize the soluble protein content of rape leaves. PMID:26184198

Emission of hydrogen sulfide (H2S) at a waterfall in a sewer: study of main factors affecting H2S emission and modeling approaches.

PubMed

Jung, Daniel; Hatrait, Laetitia; Gouello, Julien; Ponthieux, Arnaud; Parez, Vincent; Renner, Christophe

2017-11-01

Hydrogen sulfide (H 2 S) represents one of the main odorant gases emitted from sewer networks. A mathematical model can be a fast and low-cost tool for estimating its emission. This study investigates two approaches to modeling H 2 S gas transfer at a waterfall in a discharge manhole. The first approach is based on an adaptation of oxygen models for H 2 S emission at a waterfall and the second consists of a new model. An experimental set-up and a statistical data analysis allowed the main factors affecting H 2 S emission to be studied. A new model of the emission kinetics was developed using linear regression and taking into account H 2 S liquid concentration, waterfall height and fluid velocity at the outlet pipe of a rising main. Its prediction interval was estimated by the residual standard deviation (15.6%) up to a rate of 2.3 g H 2 S·h -1 . Finally, data coming from four sampling campaigns on sewer networks were used to perform simulations and compare predictions of all developed models.

Replica exchange Monte-Carlo simulations of helix bundle membrane proteins: rotational parameters of helices

NASA Astrophysics Data System (ADS)

Wu, H.-H.; Chen, C.-C.; Chen, C.-M.

2012-03-01

We propose a united-residue model of membrane proteins to investigate the structures of helix bundle membrane proteins (HBMPs) using coarse-grained (CG) replica exchange Monte-Carlo (REMC) simulations. To demonstrate the method, it is used to identify the ground state of HBMPs in a CG model, including bacteriorhodopsin (BR), halorhodopsin (HR), and their subdomains. The rotational parameters of transmembrane helices (TMHs) are extracted directly from the simulations, which can be compared with their experimental measurements from site-directed dichroism. In particular, the effects of amphiphilic interaction among the surfaces of TMHs on the rotational angles of helices are discussed. The proposed CG model gives a reasonably good structure prediction of HBMPs, as well as a clear physical picture for the packing, tilting, orientation, and rotation of TMHs. The root mean square deviation (RMSD) in coordinates of Cα atoms of the ground state CG structure from the X-ray structure is 5.03 Å for BR and 6.70 Å for HR. The final structure of HBMPs is obtained from the all-atom molecular dynamics simulations by refining the predicted CG structure, whose RMSD is 4.38 Å for BR and 5.70 Å for HR.

Weizsäcker-Skyrme-type nuclear mass formula incorporating two combinatorial radial basis function prescriptions and their application

NASA Astrophysics Data System (ADS)

Ma, Na Na; Zhang, Hai Fei; Yin, Peng; Bao, Xiao Jun; Zhang, Hong Fei

2017-08-01

Within the improved Weizsäcker-Skyrme (WS)-type nuclear mass formulas, we systematically calculated one-nucleon and two-nucleon separated energy, α-decay and β-decay energies, and the odd-even staggering (OES) of nuclear binding energies. As a result, the root-mean-square (rms) deviations of 2267 nuclei within the new improved WS-type mass formula are dropped from 493 to 167 keV, where 2267 nuclei are extracted from the atomic mass evaluation of 2012. Simultaneously, all the rms deviations of one-nucleon and two-nucleon separation energies and decay energies Qα,Qβ-,Qβ+, and QEC for more than 3000 nuclei are cut down by about 100-400 keV. Further, some basic physical observations of 988 boundary nuclei are predicted for providing reference to experiments. Finally, the overall neutron OESs and proton OESs have been systemically investigated and the residual error satisfies a normal distribution. The pairing gaps Δn and Δp of the isotopes of O, Ca, Ni, Zr, Sn, Gd, Qs, Pb, Pa, Ds and the isotonic magic chains of N =28 ,50 ,82 ,126 and even-even nuclei are also studied with dramatic improvements obtained. Especially, the rms of Δn and Δp in these nuclei have been reduced by about 200 keV. The above physical quantities show important information for nuclear charts and the features of nuclear structure.

Deviation of Long-Period Tides from Equilibrium: Kinematics and Geostrophy

NASA Technical Reports Server (NTRS)

Egbert, Gary D.; Ray, Richard D.

2003-01-01

New empirical estimates of the long-period fortnightly (Mf) tide obtained from TOPEX/Poseidon (T/P) altimeter data confirm significant basin-scale deviations from equilibrium. Elevations in the low-latitude Pacific have reduced amplitude and lag those in the Atlantic by 30 deg or more. These interbasin amplitude and phase variations are robust features that are reproduced by numerical solutions of the shallow-water equations, even for a constant-depth ocean with schematic interconnected rectangular basins. A simplified analytical model for cooscillating connected basins also reproduces the principal features observed in the empirical solutions. This simple model is largely kinematic. Zonally averaged elevations within a simple closed basin would be nearly in equilibrium with the gravitational potential, except for a constant offset required to conserve mass. With connected basins these offsets are mostly eliminated by interbasin mass flux. Because of rotation, this flux occurs mostly in a narrow boundary layer across the mouth and at the western edge of each basin, and geostrophic balance in this zone supports small residual offsets (and phase shifts) between basins. The simple model predicts that this effect should decrease roughly linearly with frequency, a result that is confirmed by numerical modeling and empirical T/P estimates of the monthly (Mm) tidal constituent. This model also explains some aspects of the anomalous nonisostatic response of the ocean to atmospheric pressure forcing at periods of around 5 days.

A deep learning framework for improving long-range residue-residue contact prediction using a hierarchical strategy.

PubMed

Xiong, Dapeng; Zeng, Jianyang; Gong, Haipeng

2017-09-01

Residue-residue contacts are of great value for protein structure prediction, since contact information, especially from those long-range residue pairs, can significantly reduce the complexity of conformational sampling for protein structure prediction in practice. Despite progresses in the past decade on protein targets with abundant homologous sequences, accurate contact prediction for proteins with limited sequence information is still far from satisfaction. Methodologies for these hard targets still need further improvement. We presented a computational program DeepConPred, which includes a pipeline of two novel deep-learning-based methods (DeepCCon and DeepRCon) as well as a contact refinement step, to improve the prediction of long-range residue contacts from primary sequences. When compared with previous prediction approaches, our framework employed an effective scheme to identify optimal and important features for contact prediction, and was only trained with coevolutionary information derived from a limited number of homologous sequences to ensure robustness and usefulness for hard targets. Independent tests showed that 59.33%/49.97%, 64.39%/54.01% and 70.00%/59.81% of the top L/5, top L/10 and top 5 predictions were correct for CASP10/CASP11 proteins, respectively. In general, our algorithm ranked as one of the best methods for CASP targets. All source data and codes are available at http://166.111.152.91/Downloads.html . hgong@tsinghua.edu.cn or zengjy321@tsinghua.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

High performance computation of residual stress and distortion in laser welded 301L stainless sheets

DOE PAGES

Huang, Hui; Tsutsumi, Seiichiro; Wang, Jiandong; ...

2017-07-11

Transient thermo-mechanical simulation of stainless plate laser welding process was performed by a highly efficient and accurate approach-hybrid iterative substructure and adaptive mesh method. Especially, residual stress prediction was enhanced by considering various heat effects in the numerical model. The influence of laser welding heat input on residual stress and welding distortion of stainless thin sheets were investigated by experiment and simulation. X-ray diffraction (XRD) and contour method were used to measure the surficial and internal residual stress respectively. Effect of strain hardening, annealing and melting on residual stress prediction was clarified through a parametric study. It was shown thatmore » these heat effects must be taken into account for accurate prediction of residual stresses in laser welded stainless sheets. Reasonable agreement among residual stresses by numerical method, XRD and contour method was obtained. Buckling type welding distortion was also well reproduced by the developed thermo-mechanical FEM.« less

High performance computation of residual stress and distortion in laser welded 301L stainless sheets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Hui; Tsutsumi, Seiichiro; Wang, Jiandong

Transient thermo-mechanical simulation of stainless plate laser welding process was performed by a highly efficient and accurate approach-hybrid iterative substructure and adaptive mesh method. Especially, residual stress prediction was enhanced by considering various heat effects in the numerical model. The influence of laser welding heat input on residual stress and welding distortion of stainless thin sheets were investigated by experiment and simulation. X-ray diffraction (XRD) and contour method were used to measure the surficial and internal residual stress respectively. Effect of strain hardening, annealing and melting on residual stress prediction was clarified through a parametric study. It was shown thatmore » these heat effects must be taken into account for accurate prediction of residual stresses in laser welded stainless sheets. Reasonable agreement among residual stresses by numerical method, XRD and contour method was obtained. Buckling type welding distortion was also well reproduced by the developed thermo-mechanical FEM.« less

Residual Strength Prediction of Fuselage Structures with Multiple Site Damage

NASA Technical Reports Server (NTRS)

Chen, Chuin-Shan; Wawrzynek, Paul A.; Ingraffea, Anthony R.

1999-01-01

This paper summarizes recent results on simulating full-scale pressure tests of wide body, lap-jointed fuselage panels with multiple site damage (MSD). The crack tip opening angle (CTOA) fracture criterion and the FRANC3D/STAGS software program were used to analyze stable crack growth under conditions of general yielding. The link-up of multiple cracks and residual strength of damaged structures were predicted. Elastic-plastic finite element analysis based on the von Mises yield criterion and incremental flow theory with small strain assumption was used. A global-local modeling procedure was employed in the numerical analyses. Stress distributions from the numerical simulations are compared with strain gage measurements. Analysis results show that accurate representation of the load transfer through the rivets is crucial for the model to predict the stress distribution accurately. Predicted crack growth and residual strength are compared with test data. Observed and predicted results both indicate that the occurrence of small MSD cracks substantially reduces the residual strength. Modeling fatigue closure is essential to capture the fracture behavior during the early stable crack growth. Breakage of a tear strap can have a major influence on residual strength prediction.

Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions

NASA Technical Reports Server (NTRS)

Spear, Ashley D.; Priest, Amanda R.; Veilleux, Michael G.; Ingraffea, Anthony R.; Hochhalter, Jacob D.

2011-01-01

A surrogate model methodology is described for predicting, during flight, the residual strength of aircraft structures that sustain discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. Two ductile fracture simulations are presented to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data does, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high fidelity fracture simulation framework provide useful tools for adaptive flight technology.

Measures of Residual Risk with Connections to Regression, Risk Tracking, Surrogate Models, and Ambiguity

DTIC Science & Technology

2015-04-15

manage , predict, and mitigate the risk in the original variable. Residual risk can be exemplified as a quantification of the improved... the random variable of interest is viewed in concert with a related random vector that helps to manage , predict, and mitigate the risk in the original... manage , predict and mitigate the risk in the original variable. Residual risk can be exemplified as a quantification of the improved situation faced

Accurate prediction of RNA-binding protein residues with two discriminative structural descriptors.

PubMed

Sun, Meijian; Wang, Xia; Zou, Chuanxin; He, Zenghui; Liu, Wei; Li, Honglin

2016-06-07

RNA-binding proteins participate in many important biological processes concerning RNA-mediated gene regulation, and several computational methods have been recently developed to predict the protein-RNA interactions of RNA-binding proteins. Newly developed discriminative descriptors will help to improve the prediction accuracy of these prediction methods and provide further meaningful information for researchers. In this work, we designed two structural features (residue electrostatic surface potential and triplet interface propensity) and according to the statistical and structural analysis of protein-RNA complexes, the two features were powerful for identifying RNA-binding protein residues. Using these two features and other excellent structure- and sequence-based features, a random forest classifier was constructed to predict RNA-binding residues. The area under the receiver operating characteristic curve (AUC) of five-fold cross-validation for our method on training set RBP195 was 0.900, and when applied to the test set RBP68, the prediction accuracy (ACC) was 0.868, and the F-score was 0.631. The good prediction performance of our method revealed that the two newly designed descriptors could be discriminative for inferring protein residues interacting with RNAs. To facilitate the use of our method, a web-server called RNAProSite, which implements the proposed method, was constructed and is freely available at http://lilab.ecust.edu.cn/NABind .

Three key residues form a critical contact network in a protein folding transition state

NASA Astrophysics Data System (ADS)

Vendruscolo, Michele; Paci, Emanuele; Dobson, Christopher M.; Karplus, Martin

2001-02-01

Determining how a protein folds is a central problem in structural biology. The rate of folding of many proteins is determined by the transition state, so that a knowledge of its structure is essential for understanding the protein folding reaction. Here we use mutation measurements-which determine the role of individual residues in stabilizing the transition state-as restraints in a Monte Carlo sampling procedure to determine the ensemble of structures that make up the transition state. We apply this approach to the experimental data for the 98-residue protein acylphosphatase, and obtain a transition-state ensemble with the native-state topology and an average root-mean-square deviation of 6Å from the native structure. Although about 20 residues with small positional fluctuations form the structural core of this transition state, the native-like contact network of only three of these residues is sufficient to determine the overall fold of the protein. This result reveals how a nucleation mechanism involving a small number of key residues can lead to folding of a polypeptide chain to its unique native-state structure.

Prediction of Detailed Enzyme Functions and Identification of Specificity Determining Residues by Random Forests

PubMed Central

Nagao, Chioko; Nagano, Nozomi; Mizuguchi, Kenji

2014-01-01

Determining enzyme functions is essential for a thorough understanding of cellular processes. Although many prediction methods have been developed, it remains a significant challenge to predict enzyme functions at the fourth-digit level of the Enzyme Commission numbers. Functional specificity of enzymes often changes drastically by mutations of a small number of residues and therefore, information about these critical residues can potentially help discriminate detailed functions. However, because these residues must be identified by mutagenesis experiments, the available information is limited, and the lack of experimentally verified specificity determining residues (SDRs) has hindered the development of detailed function prediction methods and computational identification of SDRs. Here we present a novel method for predicting enzyme functions by random forests, EFPrf, along with a set of putative SDRs, the random forests derived SDRs (rf-SDRs). EFPrf consists of a set of binary predictors for enzymes in each CATH superfamily and the rf-SDRs are the residue positions corresponding to the most highly contributing attributes obtained from each predictor. EFPrf showed a precision of 0.98 and a recall of 0.89 in a cross-validated benchmark assessment. The rf-SDRs included many residues, whose importance for specificity had been validated experimentally. The analysis of the rf-SDRs revealed both a general tendency that functionally diverged superfamilies tend to include more active site residues in their rf-SDRs than in less diverged superfamilies, and superfamily-specific conservation patterns of each functional residue. EFPrf and the rf-SDRs will be an effective tool for annotating enzyme functions and for understanding how enzyme functions have diverged within each superfamily. PMID:24416252

Improved ambiguity resolution for URTK with dynamic atmosphere constraints

NASA Astrophysics Data System (ADS)

Tang, Weiming; Liu, Wenjian; Zou, Xuan; Li, Zongnan; Chen, Liang; Deng, Chenlong; Shi, Chuang

2016-12-01

Raw observation processing method with prior knowledge of ionospheric delay could strengthen the ambiguity resolution (AR), but it does not make full use of the relatively longer wavelength of wide-lane (WL) observation. Furthermore, the accuracy of calculated atmospheric delays from the regional augmentation information has quite different in quality, while the atmospheric constraint used in the current methods is usually set to an empirical value. A proper constraint, which matches the accuracy of calculated atmospheric delays, can most effectively compensate the residual systematic biases caused by large inter-station distances. Therefore, the standard deviation of the residual atmospheric parameters should be fine-tuned. This paper presents an atmosphere-constrained AR method for undifferenced network RTK (URTK) rover, whose ambiguities are sequentially fixed according to their wavelengths. Furthermore, this research systematically analyzes the residual atmospheric error and finds that it mainly varies along the positional relationship between the rover and the chosen reference stations. More importantly, its ionospheric part of certain location will also be cyclically influenced every day. Therefore, the standard deviation of residual ionospheric error can be modeled by a daily repeated cosine or other functions with the help of data one day before, and applied by rovers as pseudo-observation. With the data collected at 29 stations from a continuously operating reference station network in Guangdong Province (GDCORS) in China, the efficiency of the proposed approach is confirmed by improving the success and error rates of AR for 10-20 % compared to that of the WL-L1-IF one, as well as making much better positioning accuracy.

R2C: improving ab initio residue contact map prediction using dynamic fusion strategy and Gaussian noise filter.

PubMed

Yang, Jing; Jin, Qi-Yu; Zhang, Biao; Shen, Hong-Bin

2016-08-15

Inter-residue contacts in proteins dictate the topology of protein structures. They are crucial for protein folding and structural stability. Accurate prediction of residue contacts especially for long-range contacts is important to the quality of ab inito structure modeling since they can enforce strong restraints to structure assembly. In this paper, we present a new Residue-Residue Contact predictor called R2C that combines machine learning-based and correlated mutation analysis-based methods, together with a two-dimensional Gaussian noise filter to enhance the long-range residue contact prediction. Our results show that the outputs from the machine learning-based method are concentrated with better performance on short-range contacts; while for correlated mutation analysis-based approach, the predictions are widespread with higher accuracy on long-range contacts. An effective query-driven dynamic fusion strategy proposed here takes full advantages of the two different methods, resulting in an impressive overall accuracy improvement. We also show that the contact map directly from the prediction model contains the interesting Gaussian noise, which has not been discovered before. Different from recent studies that tried to further enhance the quality of contact map by removing its transitive noise, we designed a new two-dimensional Gaussian noise filter, which was especially helpful for reinforcing the long-range residue contact prediction. Tested on recent CASP10/11 datasets, the overall top L/5 accuracy of our final R2C predictor is 17.6%/15.5% higher than the pure machine learning-based method and 7.8%/8.3% higher than the correlated mutation analysis-based approach for the long-range residue contact prediction. http://www.csbio.sjtu.edu.cn/bioinf/R2C/Contact:hbshen@sjtu.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Modeling helical proteins using residual dipolar couplings, sparse long-range distance constraints and a simple residue-based force field

PubMed Central

Eggimann, Becky L.; Vostrikov, Vitaly V.; Veglia, Gianluigi; Siepmann, J. Ilja

2013-01-01

We present a fast and simple protocol to obtain moderate-resolution backbone structures of helical proteins. This approach utilizes a combination of sparse backbone NMR data (residual dipolar couplings and paramagnetic relaxation enhancements) or EPR data with a residue-based force field and Monte Carlo/simulated annealing protocol to explore the folding energy landscape of helical proteins. By using only backbone NMR data, which are relatively easy to collect and analyze, and strategically placed spin relaxation probes, we show that it is possible to obtain protein structures with correct helical topology and backbone RMS deviations well below 4 Å. This approach offers promising alternatives for the structural determination of proteins in which nuclear Overha-user effect data are difficult or impossible to assign and produces initial models that will speed up the high-resolution structure determination by NMR spectroscopy. PMID:24639619

Determination of residual solvents in bulk pharmaceuticals by thermal desorption/gas chromatography/mass spectrometry.

PubMed

Urakami, K; Saito, Y; Fujiwara, Y; Watanabe, C; Umemoto, K; Godo, M; Hashimoto, K

2000-12-01

Thermal desorption (TD) techniques followed by capillary GC/MS were applied for the analysis of residual solvents in bulk pharmaceuticals. Solvents desorbed from samples by heating were cryofocused at the head of a capillary column prior to GC/MS analysis. This method requires a very small amount of sample and no sample pretreatment. Desorption temperature was set at the point about 20 degrees C higher than the melting point of each sample individually. The relative standard deviations of this method tested by performing six consecutive analyses of 8 different samples were 1.1 to 3.1%, and analytical results of residual solvents were in agreement with those obtained by direct injection of N,N-dimethylformamide solution of the samples into the GC. This novel TD/GC/MS method was demonstrated to be very useful for the identification and quantification of residual solvents in bulk pharmaceuticals.

Dissipation and residue of azoxystrobin in banana under field condition.

PubMed

Wang, Siwei; Sun, Haibin; Liu, Yanping

2013-09-01

A method was developed for determining azoxystrobin in banana and cultivation soil using gas chromatography. The dissipation and residue of azoxystrobin in banana fields at GAP conditions were investigated. The average recoveries ranged from 80.3 to 96.0 % with relative standard deviations of 2.9 to 7.2 % at three different spiking levels for each matrix. The results indicated that the half-life of azoxystrobin in bananas and soil ranged from 7.5 to 13.5 days in Guangdong and from 8.7 to 12.7 days in Fujian. The dissipation rates of azoxystrobin in banana and soil were almost the same. Terminal residues in banana and banana flesh (0.01 mg/kg) were all below the maximum residue limit (2 mg/kg by Codex Alimentarius Commission and China). The results demonstrated that the safety of using azoxystrobin at the recommended agriculture dosage to protect bananas from diseases.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Myronakis, M; Cai, W; Dhou, S

Purpose: To determine if 4DCT-based motion modeling and external surrogate motion measured during treatment simulation can enhance prediction of residual tumor motion and duty cycle during treatment delivery. Methods: This experiment was conducted using simultaneously recorded tumor and external surrogate motion acquired over multiple fractions of lung cancer radiotherapy. These breathing traces were combined with the XCAT phantom to simulate CT images. Data from the first day was used to estimate the residual tumor motion and duty cycle both directly from the 4DCT (the current clinical standard), and from external-surrogate based motion modeling. The accuracy of these estimated residual tumormore » motions and duty cycles are evaluated by comparing to the measured internal/external motions from other treatment days. Results: All calculations were done for 25% and 50% duty cycles. The results indicated that duty cycle derived from 4DCT information alone is not enough to accurately predict duty cycles during treatment. Residual tumor motion was determined from the recorded data and compared with the estimated residual tumor motion from 4DCT. Relative differences in residual tumor motion varied from −30% to 55%, suggesting that more information is required to properly predict residual tumor motion. Compared to estimations made from 4DCT, in three out of four patients examined, the 30 seconds of motion modeling data was able to predict the duty cycle with better accuracy than 4DCT. No improvement was observed in prediction of residual tumor motion for this dataset. Conclusion: Motion modeling during simulation has the potential to enhance 4DCT and provide more information about target motion, duty cycles, and delivered dose. Based on these four patients, 30 seconds of motion modeling data produced improve duty cycle estimations but showed no measurable improvement in residual tumor motion prediction. More patient data is needed to verify this Result. I would like to acknowledge funding from MRA, VARIAN Medical Systems, Inc.« less

Deviation from a preoperative surgical and anaesthetic care plan is associated with increased risk of adverse intraoperative events in major abdominal surgery.

PubMed

Gauss, T; Merckx, P; Brasher, C; Kavafyan, J; Le Bihan, E; Aussilhou, B; Belghiti, J; Mantz, J

2013-02-01

Perioperative coordination facilitates team communication and planning. The aim of this study was to determine how often deviation from predicted surgical conditions and a pre-established anaesthetic care plan in major abdominal surgery occurred, and whether this was associated with an increase in adverse clinical events. In this prospective observational study, weekly preoperative interdisciplinary team meetings were conducted according to a joint care plan checklist in a tertiary care centre in France. Any discordance with preoperative predictions and deviation from the care plan were noted. A link to the incidence of predetermined adverse intraoperative events was investigated. Intraoperative adverse clinical events (ACEs) occurred in 15 % of all cases and were associated with postoperative complications [relative risk (RR) = 1.5; 95 % confidence interval (1.1; 2.2)]. Quality of prediction of surgical procedural items was modest, with one in five to six items not correctly predicted. Discordant surgical prediction was associated with an increased incidence of ACE. Deviation from the anaesthetic care plan occurred in around 13 %, which was more frequent when surgical prediction was inaccurate (RR > 3) and independently associated with ACE (odds ratio 6). Surgery was more difficult than expected in up to one out of five cases. In a similar proportion, disagreement between preoperative care plans and observed clinical management was independently associated with an increased risk of adverse clinical events.

On the structural context and identification of enzyme catalytic residues.

PubMed

Chien, Yu-Tung; Huang, Shao-Wei

2013-01-01

Enzymes play important roles in most of the biological processes. Although only a small fraction of residues are directly involved in catalytic reactions, these catalytic residues are the most crucial parts in enzymes. The study of the fundamental and unique features of catalytic residues benefits the understanding of enzyme functions and catalytic mechanisms. In this work, we analyze the structural context of catalytic residues based on theoretical and experimental structure flexibility. The results show that catalytic residues have distinct structural features and context. Their neighboring residues, whether sequence or structure neighbors within specific range, are usually structurally more rigid than those of noncatalytic residues. The structural context feature is combined with support vector machine to identify catalytic residues from enzyme structure. The prediction results are better or comparable to those of recent structure-based prediction methods.

Predicting protein β-sheet contacts using a maximum entropy-based correlated mutation measure.

PubMed

Burkoff, Nikolas S; Várnai, Csilla; Wild, David L

2013-03-01

The problem of ab initio protein folding is one of the most difficult in modern computational biology. The prediction of residue contacts within a protein provides a more tractable immediate step. Recently introduced maximum entropy-based correlated mutation measures (CMMs), such as direct information, have been successful in predicting residue contacts. However, most correlated mutation studies focus on proteins that have large good-quality multiple sequence alignments (MSA) because the power of correlated mutation analysis falls as the size of the MSA decreases. However, even with small autogenerated MSAs, maximum entropy-based CMMs contain information. To make use of this information, in this article, we focus not on general residue contacts but contacts between residues in β-sheets. The strong constraints and prior knowledge associated with β-contacts are ideally suited for prediction using a method that incorporates an often noisy CMM. Using contrastive divergence, a statistical machine learning technique, we have calculated a maximum entropy-based CMM. We have integrated this measure with a new probabilistic model for β-contact prediction, which is used to predict both residue- and strand-level contacts. Using our model on a standard non-redundant dataset, we significantly outperform a 2D recurrent neural network architecture, achieving a 5% improvement in true positives at the 5% false-positive rate at the residue level. At the strand level, our approach is competitive with the state-of-the-art single methods achieving precision of 61.0% and recall of 55.4%, while not requiring residue solvent accessibility as an input. http://www2.warwick.ac.uk/fac/sci/systemsbiology/research/software/

A web server for analysis, comparison and prediction of protein ligand binding sites.

PubMed

Singh, Harinder; Srivastava, Hemant Kumar; Raghava, Gajendra P S

2016-03-25

One of the major challenges in the field of system biology is to understand the interaction between a wide range of proteins and ligands. In the past, methods have been developed for predicting binding sites in a protein for a limited number of ligands. In order to address this problem, we developed a web server named 'LPIcom' to facilitate users in understanding protein-ligand interaction. Analysis, comparison and prediction modules are available in the "LPIcom' server to predict protein-ligand interacting residues for 824 ligands. Each ligand must have at least 30 protein binding sites in PDB. Analysis module of the server can identify residues preferred in interaction and binding motif for a given ligand; for example residues glycine, lysine and arginine are preferred in ATP binding sites. Comparison module of the server allows comparing protein-binding sites of multiple ligands to understand the similarity between ligands based on their binding site. This module indicates that ATP, ADP and GTP ligands are in the same cluster and thus their binding sites or interacting residues exhibit a high level of similarity. Propensity-based prediction module has been developed for predicting ligand-interacting residues in a protein for more than 800 ligands. In addition, a number of web-based tools have been integrated to facilitate users in creating web logo and two-sample between ligand interacting and non-interacting residues. In summary, this manuscript presents a web-server for analysis of ligand interacting residue. This server is available for public use from URL http://crdd.osdd.net/raghava/lpicom .

Template‐based field map prediction for rapid whole brain B0 shimming

PubMed Central

Shi, Yuhang; Vannesjo, S. Johanna; Miller, Karla L.

2017-01-01

Purpose In typical MRI protocols, time is spent acquiring a field map to calculate the shim settings for best image quality. We propose a fast template‐based field map prediction method that yields near‐optimal shims without measuring the field. Methods The template‐based prediction method uses prior knowledge of the B0 distribution in the human brain, based on a large database of field maps acquired from different subjects, together with subject‐specific structural information from a quick localizer scan. The shimming performance of using the template‐based prediction is evaluated in comparison to a range of potential fast shimming methods. Results Static B0 shimming based on predicted field maps performed almost as well as shimming based on individually measured field maps. In experimental evaluations at 7 T, the proposed approach yielded a residual field standard deviation in the brain of on average 59 Hz, compared with 50 Hz using measured field maps and 176 Hz using no subject‐specific shim. Conclusions This work demonstrates that shimming based on predicted field maps is feasible. The field map prediction accuracy could potentially be further improved by generating the template from a subset of subjects, based on parameters such as head rotation and body mass index. Magn Reson Med 80:171–180, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. PMID:29193340

The prediction of the residual life of electromechanical equipment based on the artificial neural network

NASA Astrophysics Data System (ADS)

Zhukovskiy, Yu L.; Korolev, N. A.; Babanova, I. S.; Boikov, A. V.

2017-10-01

This article is devoted to the prediction of the residual life based on an estimate of the technical state of the induction motor. The proposed system allows to increase the accuracy and completeness of diagnostics by using an artificial neural network (ANN), and also identify and predict faulty states of an electrical equipment in dynamics. The results of the proposed system for estimation the technical condition are probability technical state diagrams and a quantitative evaluation of the residual life, taking into account electrical, vibrational, indirect parameters and detected defects. Based on the evaluation of the technical condition and the prediction of the residual life, a decision is made to change the control of the operating and maintenance modes of the electric motors.

Comparison of Predictive Modeling Methods of Aircraft Landing Speed

NASA Technical Reports Server (NTRS)

Diallo, Ousmane H.

2012-01-01

Expected increases in air traffic demand have stimulated the development of air traffic control tools intended to assist the air traffic controller in accurately and precisely spacing aircraft landing at congested airports. Such tools will require an accurate landing-speed prediction to increase throughput while decreasing necessary controller interventions for avoiding separation violations. There are many practical challenges to developing an accurate landing-speed model that has acceptable prediction errors. This paper discusses the development of a near-term implementation, using readily available information, to estimate/model final approach speed from the top of the descent phase of flight to the landing runway. As a first approach, all variables found to contribute directly to the landing-speed prediction model are used to build a multi-regression technique of the response surface equation (RSE). Data obtained from operations of a major airlines for a passenger transport aircraft type to the Dallas/Fort Worth International Airport are used to predict the landing speed. The approach was promising because it decreased the standard deviation of the landing-speed error prediction by at least 18% from the standard deviation of the baseline error, depending on the gust condition at the airport. However, when the number of variables is reduced to the most likely obtainable at other major airports, the RSE model shows little improvement over the existing methods. Consequently, a neural network that relies on a nonlinear regression technique is utilized as an alternative modeling approach. For the reduced number of variables cases, the standard deviation of the neural network models errors represent over 5% reduction compared to the RSE model errors, and at least 10% reduction over the baseline predicted landing-speed error standard deviation. Overall, the constructed models predict the landing-speed more accurately and precisely than the current state-of-the-art.

Residue-Specific α-Helix Propensities from Molecular Simulation

PubMed Central

Best, Robert B.; de Sancho, David; Mittal, Jeetain

2012-01-01

Formation of α-helices is a fundamental process in protein folding and assembly. By studying helix formation in molecular simulations of a series of alanine-based peptides, we obtain the temperature-dependent α-helix propensities of all 20 naturally occurring residues with two recent additive force fields, Amber ff03w and Amber ff99SB∗. Encouragingly, we find that the overall helix propensity of many residues is captured well by both energy functions, with Amber ff99SB∗ being more accurate. Nonetheless, there are some residues that deviate considerably from experiment, which can be attributed to two aspects of the energy function: i), variations of the charge model used to determine the atomic partial charges, with residues whose backbone charges differ most from alanine tending to have the largest error; ii), side-chain torsion potentials, as illustrated by the effect of modifications to the torsion angles of I, L, D, N. We find that constrained refitting of residue charges for charged residues in Amber ff99SB∗ significantly improves their helix propensity. The resulting parameters should more faithfully reproduce helix propensities in simulations of protein folding and disordered proteins. PMID:22455930

Prediction of hot spots in protein interfaces using a random forest model with hybrid features.

PubMed

Wang, Lin; Liu, Zhi-Ping; Zhang, Xiang-Sun; Chen, Luonan

2012-03-01

Prediction of hot spots in protein interfaces provides crucial information for the research on protein-protein interaction and drug design. Existing machine learning methods generally judge whether a given residue is likely to be a hot spot by extracting features only from the target residue. However, hot spots usually form a small cluster of residues which are tightly packed together at the center of protein interface. With this in mind, we present a novel method to extract hybrid features which incorporate a wide range of information of the target residue and its spatially neighboring residues, i.e. the nearest contact residue in the other face (mirror-contact residue) and the nearest contact residue in the same face (intra-contact residue). We provide a novel random forest (RF) model to effectively integrate these hybrid features for predicting hot spots in protein interfaces. Our method can achieve accuracy (ACC) of 82.4% and Matthew's correlation coefficient (MCC) of 0.482 in Alanine Scanning Energetics Database, and ACC of 77.6% and MCC of 0.429 in Binding Interface Database. In a comparison study, performance of our RF model exceeds other existing methods, such as Robetta, FOLDEF, KFC, KFC2, MINERVA and HotPoint. Of our hybrid features, three physicochemical features of target residues (mass, polarizability and isoelectric point), the relative side-chain accessible surface area and the average depth index of mirror-contact residues are found to be the main discriminative features in hot spots prediction. We also confirm that hot spots tend to form large contact surface areas between two interacting proteins. Source data and code are available at: http://www.aporc.org/doc/wiki/HotSpot.

Frame prediction using recurrent convolutional encoder with residual learning

NASA Astrophysics Data System (ADS)

Yue, Boxuan; Liang, Jun

2018-05-01

The prediction for the frame of a video is difficult but in urgent need in auto-driving. Conventional methods can only predict some abstract trends of the region of interest. The boom of deep learning makes the prediction for frames possible. In this paper, we propose a novel recurrent convolutional encoder and DE convolutional decoder structure to predict frames. We introduce the residual learning in the convolution encoder structure to solve the gradient issues. The residual learning can transform the gradient back propagation to an identity mapping. It can reserve the whole gradient information and overcome the gradient issues in Recurrent Neural Networks (RNN) and Convolutional Neural Networks (CNN). Besides, compared with the branches in CNNs and the gated structures in RNNs, the residual learning can save the training time significantly. In the experiments, we use UCF101 dataset to train our networks, the predictions are compared with some state-of-the-art methods. The results show that our networks can predict frames fast and efficiently. Furthermore, our networks are used for the driving video to verify the practicability.

A high precision instrument to measure angular and binocular deviation introduced by aircraft windscreens by using a shadow casting technique

NASA Astrophysics Data System (ADS)

Shivananju, B. N.; Yamdagni, S.; Vasu, R. M.; Asokan, S.

2012-12-01

Objects viewed through transparent sheets with residual non-parallelism and irregularity appear shifted and distorted. This distortion is measured in terms of angular and binocular deviation of an object viewed through the transparent sheet. The angular and binocular deviations introduced are particularly important in the context of aircraft windscreens and canopies as they can interfere with decision making of pilots especially while landing, leading to accidents. In this work, we have developed an instrument to measure both the angular and binocular deviations introduced by transparent sheets. This instrument is especially useful in the qualification of aircraft windscreens and canopies. It measures the deviation in the geometrical shadow cast by a periodic dot pattern trans-illuminated by the distorted light beam from the transparent test specimen compared to the reference pattern. Accurate quantification of the shift in the pattern is obtained by cross-correlating the reference shadow pattern with the specimen shadow pattern and measuring the location of the correlation peak. The developed instrument is handy to use and computes both angular and binocular deviation with an accuracy of less than ±0.1 mrad (≈0.036 mrad) and has an excellent repeatability with an error of less than 2%.

Non-"g" Residuals of the SAT and ACT Predict Specific Abilities

ERIC Educational Resources Information Center

Coyle, Thomas R.; Purcell, Jason M.; Snyder, Anissa C.; Kochunov, Peter

2013-01-01

This research examined whether non-"g" residuals of the SAT and ACT subtests, obtained after removing g, predicted specific abilities. Non-"g" residuals of the verbal and math subtests of the SAT and ACT were correlated with academic (verbal and math) and non-academic abilities (speed and shop), both based on the Armed Services…

Low-Complexity Lossless and Near-Lossless Data Compression Technique for Multispectral Imagery

NASA Technical Reports Server (NTRS)

Xie, Hua; Klimesh, Matthew A.

2009-01-01

This work extends the lossless data compression technique described in Fast Lossless Compression of Multispectral- Image Data, (NPO-42517) NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26. The original technique was extended to include a near-lossless compression option, allowing substantially smaller compressed file sizes when a small amount of distortion can be tolerated. Near-lossless compression is obtained by including a quantization step prior to encoding of prediction residuals. The original technique uses lossless predictive compression and is designed for use on multispectral imagery. A lossless predictive data compression algorithm compresses a digitized signal one sample at a time as follows: First, a sample value is predicted from previously encoded samples. The difference between the actual sample value and the prediction is called the prediction residual. The prediction residual is encoded into the compressed file. The decompressor can form the same predicted sample and can decode the prediction residual from the compressed file, and so can reconstruct the original sample. A lossless predictive compression algorithm can generally be converted to a near-lossless compression algorithm by quantizing the prediction residuals prior to encoding them. In this case, since the reconstructed sample values will not be identical to the original sample values, the encoder must determine the values that will be reconstructed and use these values for predicting later sample values. The technique described here uses this method, starting with the original technique, to allow near-lossless compression. The extension to allow near-lossless compression adds the ability to achieve much more compression when small amounts of distortion are tolerable, while retaining the low complexity and good overall compression effectiveness of the original algorithm.

SU-F-P-20: Predicting Waiting Times in Radiation Oncology Using Machine Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joseph, A; Herrera, D; Hijal, T

Purpose: Waiting times remain one of the most vexing patient satisfaction challenges facing healthcare. Waiting time uncertainty can cause patients, who are already sick or in pain, to worry about when they will receive the care they need. These waiting periods are often difficult for staff to predict and only rough estimates are typically provided based on personal experience. This level of uncertainty leaves most patients unable to plan their calendar, making the waiting experience uncomfortable, even painful. In the present era of electronic health records (EHRs), waiting times need not be so uncertain. Extensive EHRs provide unprecedented amounts ofmore » data that can statistically cluster towards representative values when appropriate patient cohorts are selected. Predictive modelling, such as machine learning, is a powerful approach that benefits from large, potentially complex, datasets. The essence of machine learning is to predict future outcomes by learning from previous experience. The application of a machine learning algorithm to waiting time data has the potential to produce personalized waiting time predictions such that the uncertainty may be removed from the patient’s waiting experience. Methods: In radiation oncology, patients typically experience several types of waiting (eg waiting at home for treatment planning, waiting in the waiting room for oncologist appointments and daily waiting in the waiting room for radiotherapy treatments). A daily treatment wait time model is discussed in this report. To develop a prediction model using our large dataset (with more than 100k sample points) a variety of machine learning algorithms from the Python package sklearn were tested. Results: We found that the Random Forest Regressor model provides the best predictions for daily radiotherapy treatment waiting times. Using this model, we achieved a median residual (actual value minus predicted value) of 0.25 minutes and a standard deviation residual of 6.5 minutes. This means that the majority of our estimates are within 6.5 minutes of the actual wait time. Conclusion: The goal of this project was to define an appropriate machine learning algorithm to estimate waiting times based on the collective knowledge and experience learned from previous patients. Our results offer an opportunity to improve the information that is provided to patients and family members regarding the amount of time they can expect to wait for radiotherapy treatment at our centre. AJ acknowledges support by the CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council (Grant number: 432290) and from the 2014 Q+ Initiative of the McGill University Health Centre.« less

Counter measures to effectively reduce end flare

NASA Astrophysics Data System (ADS)

Moneke, Matthias; Groche, Peter

2017-10-01

Roll forming is a manufacturing process, whose profitability is predicated on its high output. When roll formed profiles are cut to length, process related residual stresses are released and increased deformation at the profile ends at the cut-off occurs, also known as end flare. U-profiles typically show a flaring in at the lead end and a flaring out at the tail end. Due to this deformation, deviations from the dimensional accuracy can occur, which cause problems during further processing of the parts. Additional operations are necessary to compensate for the end flare, thereby increasing plant deployment time and production costs. Recent research focused on the cause of the residual stresses and it was shown, that a combination of residual longitudinal stresses and residual shear stresses are responsible for end flare. By exploiting this knowledge, it is possible to determine, depending on the flaring of the profile, in which part of the profile residual longitudinal or residual shear stresses are prevalent and which counter measures can specifically counteract the responsible residual stresses. For this purpose numerical and experimental investigations on a U-, Hat- and C-Profile were conducted. It could be shown that overbending and bending back of the profile is most effective in reducing end flare. Another developed method is lowering and elevating the profile to reduce residual longitudinal stresses.

Crop/weed discrimination using near-infrared reflectance spectroscopy (NIRS)

NASA Astrophysics Data System (ADS)

Zhang, Yun; He, Yong

2006-09-01

The traditional uniform herbicide application often results in an over chemical residues on soil, crop plants and agriculture produce, which have imperiled the environment and food security. Near-infrared reflectance spectroscopy (NIRS) offers a promising means for weed detection and site-specific herbicide application. In laboratory, a total of 90 samples (30 for each species) of the detached leaves of two weeds, i.e., threeseeded mercury (Acalypha australis L.) and fourleafed duckweed (Marsilea quadrfolia L.), and one crop soybean (Glycine max) was investigated for NIRS on 325- 1075 nm using a field spectroradiometer. 20 absorbance samples of each species after pretreatment were exported and the lacked Y variables were assigned independent values for partial least squares (PLS) analysis. During the combined principle component analysis (PCA) on 400-1000 nm, the PC1 and PC2 could together explain over 91% of the total variance and detect the three plant species with 98.3% accuracy. The full-cross validation results of PLS, i.e., standard error of prediction (SEP) 0.247, correlation coefficient (r) 0.954 and root mean square error of prediction (RMSEP) 0.245, indicated an optimum model for weed identification. By predicting the remaining 10 samples of each species in the PLS model, the results with deviation presented a 100% crop/weed detection rate. Thus, it could be concluded that PLS was an available alternative of for qualitative weed discrimination on NTRS.

Residual stress effects on the impact resistance and strength of fiber composites

NASA Technical Reports Server (NTRS)

Chamis, C. C.

1973-01-01

Equations have been derived to predict degradation effects of microresidual stresses on impact resistance of unidirectional fiber composites. Equations also predict lamination residual stresses in multilayered angle ply composites.

Crack prediction in EB-PVD thermal barrier coatings based on the simulation of residual stresses

NASA Astrophysics Data System (ADS)

Chen, J. W.; Zhao, Y.; Liu, S.; Zhang, Z. Z.; Ma, J.

2016-07-01

Thermal barrier coatings systems (TBCs) are widely used in the field of aerospace. The durability and insulating ability of TBCs are highly dependent on the residual stresses of top coatings, thus the investigation of the residual stresses is helpful to understand the failure mechanisms of TBCs. The simulation of residual stresses evolution in electron beam physical vapor deposition (EB-PVD) TBCs is described in this work. The interface morphology of TBCs subjected to cyclic heating and cooling is observed using scanning electron microscope (SEM). An interface model of TBCs is established based on thermal elastic-plastic finite method. Residual stress distributions in TBCs are obtained to reflect the influence of interfacial roughness. Both experimental and simulation results show that it is feasible to predict the crack location by stress analysis, which is crucial to failure prediction.

Investigation of Diesel’s Residual Noise on Predictive Vehicles Noise Cancelling using LMS Adaptive Algorithm

NASA Astrophysics Data System (ADS)

Arttini Dwi Prasetyowati, Sri; Susanto, Adhi; Widihastuti, Ida

2017-04-01

Every noise problems require different solution. In this research, the noise that must be cancelled comes from roadway. Least Mean Square (LMS) adaptive is one of the algorithm that can be used to cancel that noise. Residual noise always appears and could not be erased completely. This research aims to know the characteristic of residual noise from vehicle’s noise and analysis so that it is no longer appearing as a problem. LMS algorithm was used to predict the vehicle’s noise and minimize the error. The distribution of the residual noise could be observed to determine the specificity of the residual noise. The statistic of the residual noise close to normal distribution with = 0,0435, = 1,13 and the autocorrelation of the residual noise forming impulse. As a conclusion the residual noise is insignificant.

Temperature effect on the structure and conformational fluctuations in two zinc knuckles from the mouse mammary tumor virus.

PubMed

Nedjoua, Drici; Krallafa, Abdelghani Mohamed

2018-06-01

Zinc fingers are small protein domains in which zinc plays a structural role, contributing to the stability of the zinc-peptide complex. Zinc fingers are structurally diverse and are present in proteins that perform a broad range of functions in various cellular processes, such as replication and repair, transcription and translation, metabolism and signaling, cell proliferation, and apoptosis. Zinc fingers typically function as interaction modules and bind to a wide variety of compounds, such as nucleic acids, proteins, and small molecules. In this study, we investigated the structural properties, in solution, of the proximal and distal zinc knuckles of the nucleocapsid (NC) protein from the mouse mammary tumor virus (MMTV) (MMTV NC). For this purpose, we performed a series of molecular dynamics simulations in aqueous solution at 300 K, 333 K, and 348 K. The temperature effect was evaluated in terms of root mean square deviation of the backbone atoms and root mean square fluctuation of the coordinating residue atoms. The stability of the zinc coordination sphere was analyzed based upon the time profile of the interatomic distances between the zinc ions and the chelator atoms. The results indicate that the hydrophobic character of the proximal zinc finger is dominant at 333 K. The low mobility of the coordinating residues suggests that the strong electrostatic effect exerted by the zinc ion on its coordinating residues is not influenced by the increase in temperature. The evolution of the structural parameters of the coordination sphere of the distal zinc finger at 300 K gives us a reasonable picture of the unfolding pathway, as proposed by Bombarda and coworkers (Bombarda et al., 2005), which can predict the binding order of the four conserved ligand-binding residues. Our results support the conclusion that the structural features can vary significantly between the two zinc knuckles of MMTV NC. Copyright © 2018 Elsevier Ltd. All rights reserved.

Prediction of residue-residue contact matrix for protein-protein interaction with Fisher score features and deep learning.

PubMed

Du, Tianchuan; Liao, Li; Wu, Cathy H; Sun, Bilin

2016-11-01

Protein-protein interactions play essential roles in many biological processes. Acquiring knowledge of the residue-residue contact information of two interacting proteins is not only helpful in annotating functions for proteins, but also critical for structure-based drug design. The prediction of the protein residue-residue contact matrix of the interfacial regions is challenging. In this work, we introduced deep learning techniques (specifically, stacked autoencoders) to build deep neural network models to tackled the residue-residue contact prediction problem. In tandem with interaction profile Hidden Markov Models, which was used first to extract Fisher score features from protein sequences, stacked autoencoders were deployed to extract and learn hidden abstract features. The deep learning model showed significant improvement over the traditional machine learning model, Support Vector Machines (SVM), with the overall accuracy increased by 15% from 65.40% to 80.82%. We showed that the stacked autoencoders could extract novel features, which can be utilized by deep neural networks and other classifiers to enhance learning, out of the Fisher score features. It is further shown that deep neural networks have significant advantages over SVM in making use of the newly extracted features. Copyright © 2016. Published by Elsevier Inc.

Simultaneous determination of flubendiamide its metabolite desiodo flubendiamide residues in cabbage, tomato and pigeon pea by HPLC.

PubMed

Paramasivam, M; Banerjee, Hemanta

2011-10-01

A sensitive and simple method for simultaneous analysis of flubendiamide and its metabolite desiodo flubendiamide in cabbage, tomato and pigeon pea has been developed. The residues were extracted with QuEChERS method followed by dispersive solid-phase extraction with primary secondary amine sorbent to remove co extractives, prior to analysis by HPLC coupled with UV-Vis detector. The recoveries of flubendiamide and desiodo flubendiamide were ranged from 85.1 to 98.5% and 85.9 to 97.1% respectively with relative standard deviations (RSD) less than 5% and sensitivity of 0.01 μg g(-1). The method offers a less expensive and safer alternative to the existing residue analysis methods for vegetables. © Springer Science+Business Media, LLC 2011

[Determination of buprofezin, methamidophos, acephate, and triazophos residues in Chinese tea samples by gas chromatography].

PubMed

Zhang, Shuiba; Yi, Jun; Ye, Jianglei; Zheng, Wenhui; Cai, Xueqin; Gong, Zhenbin

2004-03-01

A method has been developed for the simultaneous determination of buprofezin, methamidophos, acephate and triazophos residues in Chinese tea samples. The pesticide residues were extracted from tea samples with a mixture of ethyl acetate and n-hexane (50:50, v/v) at 45 degrees C. The extracts were subsequently treated with a column packed with 40 mg of active carbon by gradient elution with ethyl acetate and n-hexane. Buprofenzin and the three organophosphorus pesticides were analyzed by gas chromatography using a DB-210 capillary column and a nitrogen-phosphorus detector. The recoveries for spiked standards were 73.4%-96.9%. The relative standard deviations were all within 4.63%. The limits of quantitation (3sigma) in the tea samples were about 7.0-12.0 microg/kg.

Detection of pesticides in active and depopulated beehives in Uruguay.

PubMed

Pareja, Lucía; Colazzo, Marcos; Pérez-Parada, Andrés; Niell, Silvina; Carrasco-Letelier, Leonidas; Besil, Natalia; Cesio, María Verónica; Heinzen, Horacio

2011-10-01

The influence of insecticides commonly used for agricultural purposes on beehive depopulation in Uruguay was investigated. Honeycombs, bees, honey and propolis from depopulated hives were analyzed for pesticide residues, whereas from active beehives only honey and propolis were evaluated. A total of 37 samples were analyzed, representing 14,800 beehives. In depopulated beehives only imidacloprid and fipronil were detected and in active beehives endosulfan, coumaphos, cypermethrin, ethion and chlorpyrifos were found. Coumaphos was present in the highest concentrations, around 1,000 μg/kg, in all the propolis samples from active beehives. Regarding depopulated beehives, the mean levels of imidacloprid found in honeycomb (377 μg/kg, Standard Deviation: 118) and propolis (60 μg/kg, Standard Deviation: 57) are higher than those described to produce bee disorientation and fipronil levels detected in bees (150 and 170 μg/kg) are toxic per se. The other insecticides found can affect the global fitness of the bees causing weakness and a decrease in their overall productivity. These preliminary results suggest that bees exposed to pesticides or its residues can lead them in different ways to the beehive.

From Principal Component to Direct Coupling Analysis of Coevolution in Proteins: Low-Eigenvalue Modes are Needed for Structure Prediction

PubMed Central

Cocco, Simona; Monasson, Remi; Weigt, Martin

2013-01-01

Various approaches have explored the covariation of residues in multiple-sequence alignments of homologous proteins to extract functional and structural information. Among those are principal component analysis (PCA), which identifies the most correlated groups of residues, and direct coupling analysis (DCA), a global inference method based on the maximum entropy principle, which aims at predicting residue-residue contacts. In this paper, inspired by the statistical physics of disordered systems, we introduce the Hopfield-Potts model to naturally interpolate between these two approaches. The Hopfield-Potts model allows us to identify relevant ‘patterns’ of residues from the knowledge of the eigenmodes and eigenvalues of the residue-residue correlation matrix. We show how the computation of such statistical patterns makes it possible to accurately predict residue-residue contacts with a much smaller number of parameters than DCA. This dimensional reduction allows us to avoid overfitting and to extract contact information from multiple-sequence alignments of reduced size. In addition, we show that low-eigenvalue correlation modes, discarded by PCA, are important to recover structural information: the corresponding patterns are highly localized, that is, they are concentrated in few sites, which we find to be in close contact in the three-dimensional protein fold. PMID:23990764

[Determination of strobilurin fungicides in fruits and their mass fragmentation routes by ultra performance liquid chromatography-tandem mass spectrometry].

PubMed

Zhou, Yao; Yang, Huiqin; Shi, Yiyin; Chen, Jiaxian; Zhu, Jian; Deng, Xiaojun; Guo, Dehua

2017-09-08

A method was developed for the simultaneous determination of six strobilurin fungicide ( E -metominostrobin, azoxystrobin, kresoxim-methyl, picoxystrobin, pyraclostrobin and trifloxystrobin) residues in orange, banana, apple and pineapple samples by ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The fragmentation routes of all the compounds were explained by the aid of a fragment predicting software ACD Lab/MS Fragmenter. The samples were extracted by acetonitrile, then cleaned up by amino solid phase extraction cartridges (SupelClean LC-NH 2 ). The extracts were separated on a ACQUITY UPLC BEH C 18 column (50 mm×2.1 mm, 1.7 μm) with gradient elution. Acetonitrile containing 0.1% (v/v) formic acid and 10 mmol/L ammonium acetate containing 0.1% (v/v) formic acid were used as mobile phases. The samples were detected by electrospray ionization (ESI)-MS/MS in positive ion and multiple reaction monitoring (MRM) mode, quantified by external standard method. Good linearities were obtained in the range of 5-100 μg/L (for pyraclostrobin, 1-20 μg/L) with correlation coefficients ( r 2 ) greater than 0.999. The recoveries ranged from 60.4% to 120% with the relative standard deviations between 2.15% and 15.1% ( n =6). The developed method can meet the inspection of the six strobilurin residues in the orange, banana, apple and pineapple samples.

Conformational Dynamics of Titin PEVK Explored with FRET Spectroscopy

PubMed Central

Huber, Tamás; Grama, László; Hetényi, Csaba; Schay, Gusztáv; Fülöp, Lívia; Penke, Botond; Kellermayer, Miklós S.Z.

2012-01-01

The proline-, glutamate-, valine-, and lysine-rich (PEVK) domain of the giant muscle protein titin is thought to be an intrinsically unstructured random-coil segment. Various observations suggest, however, that the domain may not be completely devoid of internal interactions and structural features. To test the validity of random polymer models for PEVK, we determined the mean end-to-end distances of an 11- and a 21-residue synthetic PEVK peptide, calculated from the efficiency of the fluorescence resonance energy transfer (FRET) between an N-terminal intrinsic tryptophan donor and a synthetically added C-terminal IAEDANS acceptor obtained in steady-state and time-resolved experiments. We find that the contour-length scaling of mean end-to-end distance deviates from predictions of a purely statistical polymer chain. Furthermore, the addition of guanidine hydrochloride decreased, whereas the addition of salt increased the FRET efficiency, pointing at the disruption of structure-stabilizing interactions. Increasing temperature between 10 and 50°C increased the normalized FRET efficiency in both peptides but with different trajectories, indicating that their elasticity and conformational stability are different. Simulations suggest that whereas the short PEVK peptide displays an overall random structure, the long PEVK peptide retains residual, loose helical configurations. Transitions in the local structure and dynamics of the PEVK domain may play a role in the modulation of passive muscle mechanics. PMID:23062340

Recovery and its correlates among patients with bipolar disorder: A study from a tertiary care centre in North India.

PubMed

Grover, Sandeep; Hazari, Nandita; Aneja, Jitender; Chakrabarti, Subho; Sharma, Sunil; Avasthi, Ajit

2016-12-01

The goal of treatment in mental illness has evolved from a symptom-based approach to a personal recovery-based approach. The aim of this study was to evaluate the predictors of personal recovery among patients with bipolar disorder. A total of 185 patients with bipolar disorder, currently in remission, were evaluated on Recovery Assessment Scale (RAS), Internalized Stigma of Mental Illness Scale (ISMIS), Brief Religious coping scale (RCOPE), Duke University Religiosity Index (DUREL), Religiousness Measures Scale, Hamilton depression rating scale (HDRS), Young Mania rating scale (YMRS) and Global Assessment of Functioning (GAF) scale. The mean age of the sample was 40.5 (standard deviation (SD), 11.26) years. Majority of the participants were male, married, working, Hindu by religion and belonged to extended/joint families of urban background. In the regression analysis, RAS scores were predicted significantly by discrimination experience, stereotype endorsement and alienation domains of ISMIS, level of functioning as assessed by GAF, residual depressive symptoms as assessed by HDRS and occupational status. The level of variance explained for total RAS score and various RAS domains ranged from 36.2% to 46.9%. This study suggests that personal recovery among patients with bipolar disorder is affected by stigma, level of functioning, residual depressive symptoms and employment status of patients with bipolar disorder. © The Author(s) 2016.

Accurate Prediction of Protein Contact Maps by Coupling Residual Two-Dimensional Bidirectional Long Short-Term Memory with Convolutional Neural Networks.

PubMed

Hanson, Jack; Paliwal, Kuldip; Litfin, Thomas; Yang, Yuedong; Zhou, Yaoqi

2018-06-19

Accurate prediction of a protein contact map depends greatly on capturing as much contextual information as possible from surrounding residues for a target residue pair. Recently, ultra-deep residual convolutional networks were found to be state-of-the-art in the latest Critical Assessment of Structure Prediction techniques (CASP12, (Schaarschmidt et al., 2018)) for protein contact map prediction by attempting to provide a protein-wide context at each residue pair. Recurrent neural networks have seen great success in recent protein residue classification problems due to their ability to propagate information through long protein sequences, especially Long Short-Term Memory (LSTM) cells. Here we propose a novel protein contact map prediction method by stacking residual convolutional networks with two-dimensional residual bidirectional recurrent LSTM networks, and using both one-dimensional sequence-based and two-dimensional evolutionary coupling-based information. We show that the proposed method achieves a robust performance over validation and independent test sets with the Area Under the receiver operating characteristic Curve (AUC)>0.95 in all tests. When compared to several state-of-the-art methods for independent testing of 228 proteins, the method yields an AUC value of 0.958, whereas the next-best method obtains an AUC of 0.909. More importantly, the improvement is over contacts at all sequence-position separations. Specifically, a 8.95%, 5.65% and 2.84% increase in precision were observed for the top L∕10 predictions over the next best for short, medium and long-range contacts, respectively. This confirms the usefulness of ResNets to congregate the short-range relations and 2D-BRLSTM to propagate the long-range dependencies throughout the entire protein contact map 'image'. SPOT-Contact server url: http://sparks-lab.org/jack/server/SPOT-Contact/. Supplementary data is available at Bioinformatics online.

Dynameomics: data-driven methods and models for utilizing large-scale protein structure repositories for improving fragment-based loop prediction.

PubMed

Rysavy, Steven J; Beck, David A C; Daggett, Valerie

2014-11-01

Protein function is intimately linked to protein structure and dynamics yet experimentally determined structures frequently omit regions within a protein due to indeterminate data, which is often due protein dynamics. We propose that atomistic molecular dynamics simulations provide a diverse sampling of biologically relevant structures for these missing segments (and beyond) to improve structural modeling and structure prediction. Here we make use of the Dynameomics data warehouse, which contains simulations of representatives of essentially all known protein folds. We developed novel computational methods to efficiently identify, rank and retrieve small peptide structures, or fragments, from this database. We also created a novel data model to analyze and compare large repositories of structural data, such as contained within the Protein Data Bank and the Dynameomics data warehouse. Our evaluation compares these structural repositories for improving loop predictions and analyzes the utility of our methods and models. Using a standard set of loop structures, containing 510 loops, 30 for each loop length from 4 to 20 residues, we find that the inclusion of Dynameomics structures in fragment-based methods improves the quality of the loop predictions without being dependent on sequence homology. Depending on loop length, ∼ 25-75% of the best predictions came from the Dynameomics set, resulting in lower main chain root-mean-square deviations for all fragment lengths using the combined fragment library. We also provide specific cases where Dynameomics fragments provide better predictions for NMR loop structures than fragments from crystal structures. Online access to these fragment libraries is available at http://www.dynameomics.org/fragments. © 2014 The Protein Society.

In silico prediction of nematic transition temperature for liquid crystals using quantitative structure-property relationship approaches.

PubMed

Fatemi, Mohammad Hossein; Ghorbanzad'e, Mehdi

2009-11-01

Quantitative structure-property relationship models for the prediction of the nematic transition temperature (T (N)) were developed by using multilinear regression analysis and a feedforward artificial neural network (ANN). A collection of 42 thermotropic liquid crystals was chosen as the data set. The data set was divided into three sets: for training, and an internal and external test set. Training and internal test sets were used for ANN model development, and the external test set was used for evaluation of the predictive power of the model. In order to build the models, a set of six descriptors were selected by the best multilinear regression procedure of the CODESSA program. These descriptors were: atomic charge weighted partial negatively charged surface area, relative negative charged surface area, polarity parameter/square distance, minimum most negative atomic partial charge, molecular volume, and the A component of moment of inertia, which encode geometrical and electronic characteristics of molecules. These descriptors were used as inputs to ANN. The optimized ANN model had 6:6:1 topology. The standard errors in the calculation of T (N) for the training, internal, and external test sets using the ANN model were 1.012, 4.910, and 4.070, respectively. To further evaluate the ANN model, a crossvalidation test was performed, which produced the statistic Q (2) = 0.9796 and standard deviation of 2.67 based on predicted residual sum of square. Also, the diversity test was performed to ensure the model's stability and prove its predictive capability. The obtained results reveal the suitability of ANN for the prediction of T (N) for liquid crystals using molecular structural descriptors.

Dynameomics: Data-driven methods and models for utilizing large-scale protein structure repositories for improving fragment-based loop prediction

PubMed Central

Rysavy, Steven J; Beck, David AC; Daggett, Valerie

2014-01-01

Protein function is intimately linked to protein structure and dynamics yet experimentally determined structures frequently omit regions within a protein due to indeterminate data, which is often due protein dynamics. We propose that atomistic molecular dynamics simulations provide a diverse sampling of biologically relevant structures for these missing segments (and beyond) to improve structural modeling and structure prediction. Here we make use of the Dynameomics data warehouse, which contains simulations of representatives of essentially all known protein folds. We developed novel computational methods to efficiently identify, rank and retrieve small peptide structures, or fragments, from this database. We also created a novel data model to analyze and compare large repositories of structural data, such as contained within the Protein Data Bank and the Dynameomics data warehouse. Our evaluation compares these structural repositories for improving loop predictions and analyzes the utility of our methods and models. Using a standard set of loop structures, containing 510 loops, 30 for each loop length from 4 to 20 residues, we find that the inclusion of Dynameomics structures in fragment-based methods improves the quality of the loop predictions without being dependent on sequence homology. Depending on loop length, ∼25–75% of the best predictions came from the Dynameomics set, resulting in lower main chain root-mean-square deviations for all fragment lengths using the combined fragment library. We also provide specific cases where Dynameomics fragments provide better predictions for NMR loop structures than fragments from crystal structures. Online access to these fragment libraries is available at http://www.dynameomics.org/fragments. PMID:25142412

A Progressive Damage Methodology for Residual Strength Predictions of Notched Composite Panels

NASA Technical Reports Server (NTRS)

Coats, Timothy W.; Harris, Charles E.

1998-01-01

The translaminate fracture behavior of carbon/epoxy structural laminates with through-penetration notches was investigated to develop a residual strength prediction methodology for composite structures. An experimental characterization of several composite materials systems revealed a fracture resistance behavior that was very similar to the R-curve behavior exhibited by ductile metals. Fractographic examinations led to the postulate that the damage growth resistance was primarily due to fractured fibers in the principal load-carrying plies being bridged by intact fibers of the adjacent plies. The load transfer associated with this bridging mechanism suggests that a progressive damage analysis methodology will be appropriate for predicting the residual strength of laminates with through-penetration notches. A progressive damage methodology developed by the authors was used to predict the initiation and growth of matrix cracks and fiber fracture. Most of the residual strength predictions for different panel widths, notch lengths, and material systems were within about 10% of the experimental failure loads.

A new criterion for predicting rolling-element fatigue lives of through-hardened steels

NASA Technical Reports Server (NTRS)

Chevalier, J. L.; Zaretsky, E. V.; Parker, R. J.

1972-01-01

A carbide factor was derived based upon a statistical analysis which related rolling-element fatigue life to the total number of residual carbide particles per unit area, median residual carbide size, and percent residual carbide area. An equation was experimentally determined which predicts material hardness as a function of temperature. The limiting temperatures of all of the materials studied were dependent on initial room temperature hardness and tempering temperature. An equation was derived combining the effects of material hardness, carbide factor, and bearing temperature to predict rolling-element bearing life.

A Quantitative Proxy for Sea-Ice Based on Diatoms: A Cautionary Tale.

NASA Astrophysics Data System (ADS)

Nesterovich, A.; Caissie, B.

2016-12-01

Sea ice in the Polar Regions supports unique and productive ecosystems, but the current decline in the Arctic sea ice extent prompts questions about previous sea ice declines and the response of ice related ecosystems. Since satellite data only extend back to 1978, the study of sea ice before this time requires a proxy. Being one of the most productive, diatom-dominated regions in the world and having a wide range of sea ice concentrations, the Bering and Chukchi seas are a perfect place to find a relationship between the presence of sea ice and diatom community composition. The aim of this work is to develop a diatom-based proxy for the sea ice extent. A total of 473 species have been identified in 104 sediment samples, most of which were collected on board the US Coast Guard Cutter Healy ice breaker (2006, 2007) and the Norseman II (2008). The study also included some of the archived diatom smear slides made from sediments collected in 1969. The assemblages were compared to satellite-derived sea ice extent data averaged over the 10 years preceding the sampling. Previous studies in the Arctic and Antarctic regions demonstrated that the Generalized Additive Model (GAM) is one of the best choices for proxy construction. It has the advantage of using only several species instead of the whole assemblage, thus including only sea ice-associated species and minimizing the noise created by species responding to other environmental factors. Our GAM on three species (Connia compita, Fragilariopsis reginae-jahniae, and Neodenticula seminae) has low standard deviation, high level of explained variation, and holds under the ten-fold cross-validation; the standard residual analysis is acceptable. However, a spatial residual analysis revealed that the model consistently over predicts in the Chukchi Sea and under predicts in the Bering Sea. Including a spatial model into the GAM didn't improve the situation. This has led us to test other methods, including a non-parametric model Random Forests. All models showed the same consistent pattern in the residuals. We conclude that ecosystems of the Bering and Chukchi seas respond differently to sea ice concentration and an integrated proxy must take it into account.

The Folding Energy Landscape and Free Energy Excitations of Cytochrome c

PubMed Central

Weinkam, Patrick; Zimmermann, Jörg; Romesberg, Floyd E.

2014-01-01

The covalently bound heme cofactor plays a dominant role in the folding of cytochrome c. Due to the complicated inorganic chemistry of the heme, some might consider the folding of cytochrome c to be a special case that follows different principles than those used to describe folding of proteins without cofactors. Recent investigations, however, demonstrate that models which are commonly used to describe folding for many proteins work well for cytochrome c when heme is explicitly introduced and generally provide results that agree with experimental observations. We will first discuss results from simple native structure-based models. These models include attractive interactions between nonadjacent residues only if they are present in the crystal structure at pH 7. Since attractive nonnative contacts are not included in native structure-based models, their energy landscapes can be described as “perfectly funneled.” In other words, native structure-based models are energetically guided towards the native state and contain no energetic traps that would hinder folding. Energetic traps are sources of frustration which cause specific transient intermediates to be populated. Native structure-based models do include repulsion between residues due to excluded volume. Nonenergetic traps can therefore exist if the chain, which cannot cross over itself, must partially unfold in order for folding to proceed. The ability of native structure-based models to capture these type of motions is in part responsible for their successful predictions of folding pathways for many types of proteins. Models without frustration describe well the sequence of folding events for cytochrome c inferred from hydrogen exchange experiments thereby justifying their use as a starting point. At low pH, the folding sequence of cytochrome c deviates from that at pH 7 and from those predicted from models with perfectly funneled energy landscapes. Alternate folding pathways are a result of “chemical frustration.” This frustration arises because some regions of the protein are destabilized more than others due to the heterogeneous distribution of titratable residues that are protonated at low pH. We construct more complex models that include chemical frustration, in addition to the native structure-based terms. These more complex models only modestly perturb the energy landscape which remains overall well funneled. These perturbed models can accurately describe how alternative folding pathways are used at low pH. At alkaline pH, cytochrome c populates distinctly different structural ensembles. For instance, lysine residues are deprotonated and compete for the heme ligation site. The same models that can describe folding at low pH also predict well the structures and relative stabilities of intermediates populated at alkaline pH. PMID:20143816

NMR and SAXS characterization of the denatured state of the chemotactic protein Che Y: Implications for protein folding initiation

PubMed Central

Garcia, Pascal; Serrano, Luis; Durand, Dominique; Rico, Manuel; Bruix, Marta

2001-01-01

The denatured state of a double mutant of the chemotactic protein CheY (F14N/V83T) has been analyzed in the presence of 5 M urea, using small angle X-ray scattering (SAXS) and heteronuclear magnetic resonance. SAXS studies show that the denatured protein follows a wormlike chain model. Its backbone can be described as a chain composed of rigid elements connected by flexible links. A comparison of the contour length obtained for the chain at 5 M urea with the one expected for a fully expanded chain suggests that ∼25% of the residues are involved in residual structures. Conformational shifts of the α-protons, heteronuclear 15N-{1H} NOEs and 15N relaxation properties have been used to identify some regions in the protein that deviate from a random coil behavior. According to these NMR data, the protein can be divided into two subdomains, which largely coincide with the two folding subunits identified in a previous kinetic study of the folding of the protein. The first of these subdomains, spanning residues 1–70, is shown here to exhibit a restricted mobility as compared to the rest of the protein. Two regions, one in each subdomain, were identified as deviating from the random coil chemical shifts. Peptides corresponding to these sequences were characterized by NMR and their backbone 1H chemical shifts were compared to those in the intact protein under identical denaturing conditions. For the region located in the first subdomain, this comparison shows that the observed deviation from random coil parameters is caused by interactions with the rest of the molecule. The restricted flexibility of the first subdomain and the transient collapse detected in that subunit are consistent with the conclusions obtained by applying the protein engineering method to the characterization of the folding reaction transition state. PMID:11369848

Structural analysis of B-cell epitopes in antibody:protein complexes

PubMed Central

Kringelum, Jens Vindahl; Nielsen, Morten; Padkjær, Søren Berg; Lund, Ole

2012-01-01

The binding of antigens to antibodies is one of the key events in an immune response against foreign molecules and is a critical element of several biomedical applications including vaccines and immunotherapeutics. For development of such applications, the identification of antibody binding sites (B-cell epitopes) is essential. However experimental epitope mapping is highly cost-intensive and computer-aided methods do in general have moderate performance. One major reason for this moderate performance is an incomplete understanding of what characterizes an epitope. To fill this gap, we here developed a novel framework for comparing and superimposing B-cell epitopes and applied it on a dataset of 107 non-similar antigen:antibody structures extracted from the PDB database. With the presented framework, we were able to describe the general B-cell epitope as a flat, oblong, oval shaped volume consisting of predominantly hydrophobic amino acids in the center flanked by charged residues. The average epitope was found to be made up of ~15 residues with one linear stretch of 5 or more residues constituting more than half of the epitope size. Furthermore, the epitope area is predominantly constrained to a plane above the antibody tip, in which the epitope is orientated in a −30 to 60 degree angle relative to the light to heavy chain antibody direction. Contrary to previously findings, we did not find a significant deviation between the amino acid composition in epitopes and the composition of equally exposed parts of the antigen surface. Our results, in combination with previously findings, give a detailed picture of the B-cell epitope that may be used in development of improved B-cell prediction methods. PMID:22784991

Early warning of changing drinking water quality by trend analysis.

PubMed

Tomperi, Jani; Juuso, Esko; Leiviskä, Kauko

2016-06-01

Monitoring and control of water treatment plants play an essential role in ensuring high quality drinking water and avoiding health-related problems or economic losses. The most common quality variables, which can be used also for assessing the efficiency of the water treatment process, are turbidity and residual levels of coagulation and disinfection chemicals. In the present study, the trend indices are developed from scaled measurements to detect warning signs of changes in the quality variables of drinking water and some operating condition variables that strongly affect water quality. The scaling is based on monotonically increasing nonlinear functions, which are generated with generalized norms and moments. Triangular episodes are classified with the trend index and its derivative. Deviation indices are used to assess the severity of situations. The study shows the potential of the described trend analysis as a predictive monitoring tool, as it provides an advantage over the traditional manual inspection of variables by detecting changes in water quality and giving early warnings.

α-Cyclodextrin dimer complexes of dopamine and levodopa derivatives to assess drug delivery to the central nervous system: ADME and molecular docking studies

PubMed Central

Shityakov, Sergey; Broscheit, Jens; Förster, Carola

2012-01-01

This paper attempts to predict and emphasize molecular interactions of dopamine, levodopa, and their derivatives (Dopimid compounds) containing 2-phenyl-imidazopyridine moiety with the α-cyclodextrin dimer in order to assess and improve drug delivery to the central nervous system. The molecular docking method is used to determine the energetic profiles, hydrogen bond formation, and hydrophobic effect of 14 host–guest complexes. The results show that the “chemical branching” represented by additional ethyl-acetate residue is energetically unfavorable and promotes a conformational shift due to the high root mean square deviation levels. This phenomenon is characterized by a low number of H-bonds and a significant decrease of the host–guest hydrophobic potential surface. Finally, the overall docking procedure presents a powerful rationale for screening and analyzing various sets of promising drug-like chemical compounds in the fields of supramolecular chemistry, molecular sensing, synthetic receptors, and nanobiotechnology. PMID:22811606

Sustained modelling ability of artificial neural networks in the analysis of two pharmaceuticals (dextropropoxyphene and dipyrone) present in unequal concentrations.

PubMed

Cámara, María S; Ferroni, Félix M; De Zan, Mercedes; Goicoechea, Héctor C

2003-07-01

An improvement is presented on the simultaneous determination of two active ingredients present in unequal concentrations in injections. The analysis was carried out with spectrophotometric data and non-linear multivariate calibration methods, in particular artificial neural networks (ANNs). The presence of non-linearities caused by the major analyte concentrations which deviate from Beer's law was confirmed by plotting actual vs. predicted concentrations, and observing curvatures in the residuals for the estimated concentrations with linear methods. Mixtures of dextropropoxyphene and dipyrone have been analysed by using linear and non-linear partial least-squares (PLS and NPLSs) and ANNs. Notwithstanding the high degree of spectral overlap and the occurrence of non-linearities, rapid and simultaneous analysis has been achieved, with reasonably good accuracy and precision. A commercial sample was analysed by using the present methodology, and the obtained results show reasonably good agreement with those obtained by using high-performance liquid chromatography (HPLC) and a UV-spectrophotometric comparative methods.

Protein asparagine deamidation prediction based on structures with machine learning methods.

PubMed

Jia, Lei; Sun, Yaxiong

2017-01-01

Chemical stability is a major concern in the development of protein therapeutics due to its impact on both efficacy and safety. Protein "hotspots" are amino acid residues that are subject to various chemical modifications, including deamidation, isomerization, glycosylation, oxidation etc. A more accurate prediction method for potential hotspot residues would allow their elimination or reduction as early as possible in the drug discovery process. In this work, we focus on prediction models for asparagine (Asn) deamidation. Sequence-based prediction method simply identifies the NG motif (amino acid asparagine followed by a glycine) to be liable to deamidation. It still dominates deamidation evaluation process in most pharmaceutical setup due to its convenience. However, the simple sequence-based method is less accurate and often causes over-engineering a protein. We introduce structure-based prediction models by mining available experimental and structural data of deamidated proteins. Our training set contains 194 Asn residues from 25 proteins that all have available high-resolution crystal structures. Experimentally measured deamidation half-life of Asn in penta-peptides as well as 3D structure-based properties, such as solvent exposure, crystallographic B-factors, local secondary structure and dihedral angles etc., were used to train prediction models with several machine learning algorithms. The prediction tools were cross-validated as well as tested with an external test data set. The random forest model had high enrichment in ranking deamidated residues higher than non-deamidated residues while effectively eliminated false positive predictions. It is possible that such quantitative protein structure-function relationship tools can also be applied to other protein hotspot predictions. In addition, we extensively discussed metrics being used to evaluate the performance of predicting unbalanced data sets such as the deamidation case.

DockRank: Ranking docked conformations using partner-specific sequence homology-based protein interface prediction

PubMed Central

Xue, Li C.; Jordan, Rafael A.; EL-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2015-01-01

Selecting near-native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. Dock-Rank uses interface residues predicted by partner-specific sequence homology-based protein–protein interface predictor (PS-HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state-of-the-art docking scoring functions using Success Rate (the percentage of cases that have at least one near-native conformation among the top m conformations) and Hit Rate (the percentage of near-native conformations that are included among the top m conformations). In cases where it is possible to obtain partner-specific (PS) interface predictions from PS-HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state-of-the-art energy-based scoring functions (improving Success Rate by up to 4-fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39-fold). The latter result underscores the importance of using partner-specific interface residues in scoring docked conformations. We show that DockRank, when used to re-rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/. PMID:23873600

DockRank: ranking docked conformations using partner-specific sequence homology-based protein interface prediction.

PubMed

Xue, Li C; Jordan, Rafael A; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2014-02-01

Selecting near-native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. DockRank uses interface residues predicted by partner-specific sequence homology-based protein-protein interface predictor (PS-HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state-of-the-art docking scoring functions using Success Rate (the percentage of cases that have at least one near-native conformation among the top m conformations) and Hit Rate (the percentage of near-native conformations that are included among the top m conformations). In cases where it is possible to obtain partner-specific (PS) interface predictions from PS-HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state-of-the-art energy-based scoring functions (improving Success Rate by up to 4-fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39-fold). The latter result underscores the importance of using partner-specific interface residues in scoring docked conformations. We show that DockRank, when used to re-rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/. Copyright © 2013 Wiley Periodicals, Inc.

Influence of Convective Effect of Solar Winds on the CME Transit Time

NASA Astrophysics Data System (ADS)

Sun, Lu-yuan

2017-10-01

Based on an empirical model for predicting the transit time of coronal mass ejections (CMEs) proposed by Gopalswamy, 52 CME events which are related to the geomagnetic storms of Dst < -50 nT, and 10 CME events which caused extremely strong geomagnetic storms (Dst < -200 nT) in 1996- 2007 are selected, and combined with the observational data of the interplanetary solar winds that collected by the ACE satellite at 1AU, to analyze the influence of convective effect of ambient solar winds on the prediction of the CME transit time when it arrives at a place of 1 AU. After taking the convective effect of ambient solar winds into account, the standard deviation of predictions is reduced from 16.5 to 11.4 hours for the 52 CME events, and the prediction error is less than 15 hours for 68% of these events; while the standard deviation of predictions is reduced from 10.6 to 6.5 hours for the 10 CME events that caused extremely strong geomagnetic storms, and the prediction error is less than 5 hours for 6 of the 10 events. These results show that taking the convective effect of ambient solar winds into account can reduce the standard deviation of the predicted CME transit time, hence the convective effect of solar winds plays an important role for predicting the transit times of CME events.

A simple and efficient method for predicting protein-protein interaction sites.

PubMed

Higa, R H; Tozzi, C L

2008-09-23

Computational methods for predicting protein-protein interaction sites based on structural data are characterized by an accuracy between 70 and 80%. Some experimental studies indicate that only a fraction of the residues, forming clusters in the center of the interaction site, are energetically important for binding. In addition, the analysis of amino acid composition has shown that residues located in the center of the interaction site can be better discriminated from the residues in other parts of the protein surface. In the present study, we implement a simple method to predict interaction site residues exploiting this fact and show that it achieves a very competitive performance compared to other methods using the same dataset and criteria for performance evaluation (success rate of 82.1%).

Bioinformatic prediction and in vivo validation of residue-residue interactions in human proteins

NASA Astrophysics Data System (ADS)

Jordan, Daniel; Davis, Erica; Katsanis, Nicholas; Sunyaev, Shamil

2014-03-01

Identifying residue-residue interactions in protein molecules is important for understanding both protein structure and function in the context of evolutionary dynamics and medical genetics. Such interactions can be difficult to predict using existing empirical or physical potentials, especially when residues are far from each other in sequence space. Using a multiple sequence alignment of 46 diverse vertebrate species we explore the space of allowed sequences for orthologous protein families. Amino acid changes that are known to damage protein function allow us to identify specific changes that are likely to have interacting partners. We fit the parameters of the continuous-time Markov process used in the alignment to conclude that these interactions are primarily pairwise, rather than higher order. Candidates for sites under pairwise epistasis are predicted, which can then be tested by experiment. We report the results of an initial round of in vivo experiments in a zebrafish model that verify the presence of multiple pairwise interactions predicted by our model. These experimentally validated interactions are novel, distant in sequence, and are not readily explained by known biochemical or biophysical features.

Influence of Noncompliance With Radiation Therapy Protocol Guidelines and Operative Bed Recurrences for Children With Rhabdomyosarcoma and Microscopic Residual Disease: A Report From the Children's Oncology Group

DOE Office of Scientific and Technical Information (OSTI.GOV)

Million, Lynn, E-mail: lynn.million@hci.utah.ed; Anderson, James; Breneman, John

2011-06-01

Purpose: Postoperative radiation therapy (RT) is recommended for patients with rhabdomyosarcoma having microscopic disease. Sometimes RT dose/volume is reduced or omitted in an attempt to avoid late effects, particularly in young children. We reviewed operative bed recurrences to determine if noncompliance with RT protocol guidelines influenced local-regional control. Methods and Materials: All operative bed recurrences among 695 Group II rhabdomyosarcoma patients in Intergroup Rhabdomyosarcoma Study Group (IRS) I through IV were reviewed for deviation from RT protocol. Major/minor dose deviation was defined as >10% or 6-10% of the prescribed dose (40-60 Gy), respectively. Major/minor volume deviation was defined as tumormore » excluded from the RT field or treatment volume not covered by the specified margin (preoperative tumor volume and 2- to 5-cm margin), respectively. No RT was a major deviation. Results: Forty-six of 83 (55%) patients with operative bed recurrences did not receive the intended RT (39 major and 7 minor deviations). RT omission was the most frequent RT protocol deviation (19/46, 41%), followed by dose (17/46, 37%), volume (9/46, 20%), and dose and volume deviation (1/46, 2%). Only 7 operative bed recurrences occurred in IRS IV (5% local-regional failure) with only 3 RT protocol deviations. Sixty-three (76%) patients with recurrence died of disease despite retrieval therapy, including 13 of 19 nonirradiated children. Conclusion: Over half of the operative bed recurrences were associated with noncompliance; omission of RT was the most common protocol deviation. Three fourths of children die when local-regional disease is not controlled, emphasizing the importance of RT in Group II rhabdomyosarcoma.« less

[Simultaneous determination of seven residual solvents in bovis calculus artifactus by headspace gas chromatography].

PubMed

Chi, Shuyao; Wu, Dike; Sun, Jinhong; Ye, Ruhan; Wang, Xiaoyan

2014-05-01

A headspace gas chromatography (HS-GC) method was developed for the simultaneous determination of seven residual solvents (petroleum ether (60-90 degrees C), acetone, ethyl acetate, methanol, methylene chloride, ethanol and butyl acetate) in bovis calculus artifactus. The DB-WAX capillary column and flame ionization detector (FID) were used for the separation and detection of the residual solvents, and the internal standard method was used for the quantification. The chromatographic conditions, such as equilibrium temperature and equilibrium time, were optimized. Under the optimized conditions, all of the seven residual solvents showed good linear relationships with good correlation coefficients (not less than 0.999 3) in the prescribed concentration range. At three spiked levels, the recoveries for the seven residual solvents were 94.7%-105.2% with the relative standard deviations (RSDs) less than 3.5%. The limits of detection (LODs) of the method were 0.43-5.23 mg/L, and the limits of quantification (LOQs) were 1.25-16.67 mg/L. The method is simple, rapid, sensitive and accurate, and is suitable for the simultaneous determination of the seven residual solvents in bovis calculus artifactus.

Residue behavior and dietary intake risk assessment of three fungicides in tomatoes (Lycopersicon esculentum Mill.) under greenhouse conditions.

PubMed

Zhu, Xiaodan; Jia, Chunhong; Duan, Lifang; Zhang, Wei; Yu, Pingzhong; He, Min; Chen, Li; Zhao, Ercheng

2016-11-01

The residue behavior and dietary intake risk of three fungicides (pyrimethanil, iprodione, kresoxim-methyl) in tomatoes (Lycopersicon esculentum Mill.) grown in greenhouse were investigated. A simple, rapid analytical method for the quantification of fungicide residues in tomatoes was developed using gas chromatography coupled with mass spectrum detection (GC-MSD). The fortified recoveries were ranged from 87% to 103% with relative standard deviations (RSDs) varied from 4.7% to 12.1%. The results indicated that the dissipation rate of the studied fungicides in tomatoes followed first order kinetics with half lives in the range of 8.6-11.5 days. The final residues of all the fungicides in tomatoes were varied from 0.241 to 0.944 mg/kg. The results of dietary intake assessment indicated that the dietary intake of the three fungicides from tomatoes consumption for Chinese consumers were acceptable. This study would provide more understanding of residue behavior and dietary intake risk by these fungicides used under greenhouse conditions. Copyright © 2016 Elsevier Inc. All rights reserved.

Determination of benazolin-ethyl residues in soil and rape seed by SPE clean-up and GC with electron capture detection.

PubMed

Liu, Xiaolu; Yang, Tao; Hu, Jiye

2013-01-01

A method has been developed and established for residue determination of benazolin-ethyl in soil and rape seed samples by gas chromatography with electron capture detection (GC-ECD). Limits of quantification of the method are 0.005 mg/kg for both soil and rape seed, which are sufficiently below the maximum residue limit, and the limit of detection is 0.0023 ng. The average recoveries of the analyte range from 85.89 to 105.84% with relative standard deviations (coefficient of variation) less than 5.53% at the three spike levels (0.005, 0.1 and 0.5 mg/kg). The half-life of benazolin-ethyl in soil from the experimental field is 4.62 days. The final residues of benazolin-ethyl in soil and rape seed samples are lower than 0.005 mg/kg at harvest time. Direct confirmation of the analyte in real samples is achieved by GC-mass spectrometry. It is demonstrated that the proposed method is simple, rapid and efficient, and reliable to detect benazolin-ethyl residues in soil and rape seed samples.

Crack Growth Simulation and Residual Strength Prediction in Airplane Fuselages

NASA Technical Reports Server (NTRS)

Chen, Chuin-Shan; Wawrzynek, Paul A.; Ingraffea, Anthony R.

1999-01-01

The objectives were to create a capability to simulate curvilinear crack growth and ductile tearing in aircraft fuselages subjected to widespread fatigue damage and to validate with tests. Analysis methodology and software program (FRANC3D/STAGS) developed herein allows engineers to maintain aging aircraft economically, while insuring continuous airworthiness, and to design more damage-tolerant aircraft for the next generation. Simulations of crack growth in fuselages were described. The crack tip opening angle (CTOA) fracture criterion, obtained from laboratory tests, was used to predict fracture behavior of fuselage panel tests. Geometrically nonlinear, elastic-plastic, thin shell finite element crack growth analyses were conducted. Comparisons of stress distributions, multiple stable crack growth history, and residual strength between measured and predicted results were made to assess the validity of the methodology. Incorporation of residual plastic deformations and tear strap failure was essential for accurate residual strength predictions. Issue related to predicting crack trajectory in fuselages were also discussed. A directional criterion, including T-stress and fracture toughness orthotropy, was developed. Curvilinear crack growth was simulated in coupon and fuselage panel tests. Both T-stress and fracture toughness orthotropy were essential to predict the observed crack paths. Flapping of fuselages were predicted. Measured and predicted results agreed reasonable well.

Estimates of diet selection in cattle grazing cornstalk residues by measurement of chemical composition and near infrared reflectance spectroscopy of diet samples collected by ruminal evacuation.

PubMed

Petzel, Emily A; Smart, Alexander J; St-Pierre, Benoit; Selman, Susan L; Bailey, Eric A; Beck, Erin E; Walker, Julie A; Wright, Cody L; Held, Jeffrey E; Brake, Derek W

2018-05-04

Six ruminally cannulated cows (570 ± 73 kg) fed corn residues were placed in a 6 × 6 Latin square to evaluate predictions of diet composition from ruminally collected diet samples. After complete ruminal evacuation, cows were fed 1-kg meals (dry matter [DM]-basis) containing different combinations of cornstalk and leaf and husk (LH) residues in ratios of 0:100, 20:80, 40:60, 60:40, 80:20, and 100:0. Diet samples from each meal were collected by removal of ruminal contents after 1-h and were either unrinsed, hand-rinsed or machine-rinsed to evaluate effects of endogenous compounds on predictions of diet composition. Diet samples were analyzed for neutral (NDF) and acid (ADF) detergent fiber, acid detergent insoluble ash (ADIA), acid detergent lignin (ADL), crude protein (CP), and near infrared reflectance spectroscopy (NIRS) to calculate diet composition. Rinsing type increased NDF and ADF content and decreased ADIA and CP content of diet samples (P < 0.01). Rinsing tended to increase (P < 0.06) ADL content of diet samples. Differences in concentration between cornstalk and LH residues within each chemical component were standardized by calculating a coefficient of variation (CV). Accuracy and precision of estimates of diet composition were analyzed by regressing predicted diet composition and known diet composition. Predictions of diet composition were improved by increasing differences in concentration of chemical components between cornstalk and LH residues up to a CV of 22.6 ± 5.4%. Predictions of diet composition from unrinsed ADIA and machine-rinsed NIRS had the greatest accuracy (slope = 0.98 and 0.95, respectively) and large coefficients of determination (r2 = 0.86 and 0.74, respectively). Subsequently, a field study (Exp. 2) was performed to evaluate predictions of diet composition in cattle (646 ± 89 kg) grazing corn residue. Five cows were placed in 1 of 10 paddocks and allowed to graze continuously or to strip-graze corn residues. Predictions of diet composition from ADIA, ADL, and NIRS did not differ (P = 0.99), and estimates of cornstalk intake tended to be greater (P = 0.09) in strip-grazed compared to continuously grazed cows. These data indicate that diet composition can be predicted by chemical components or NIRS by ruminal collection of diet samples among cattle grazing corn residues.

Combined proportional and additive residual error models in population pharmacokinetic modelling.

PubMed

Proost, Johannes H

2017-11-15

In pharmacokinetic modelling, a combined proportional and additive residual error model is often preferred over a proportional or additive residual error model. Different approaches have been proposed, but a comparison between approaches is still lacking. The theoretical background of the methods is described. Method VAR assumes that the variance of the residual error is the sum of the statistically independent proportional and additive components; this method can be coded in three ways. Method SD assumes that the standard deviation of the residual error is the sum of the proportional and additive components. Using datasets from literature and simulations based on these datasets, the methods are compared using NONMEM. The different coding of methods VAR yield identical results. Using method SD, the values of the parameters describing residual error are lower than for method VAR, but the values of the structural parameters and their inter-individual variability are hardly affected by the choice of the method. Both methods are valid approaches in combined proportional and additive residual error modelling, and selection may be based on OFV. When the result of an analysis is used for simulation purposes, it is essential that the simulation tool uses the same method as used during analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Residue level and dissipation of carbendazim in/on pomegranate fruits and soil.

PubMed

Mohapatra, Soudamini; S, Lekha

2016-07-01

Carbendazim is widely used on pomegranate for control of a large number of fungal diseases. Its residue levels in/on pomegranate fruits and soil were evaluated under field conditions. The quick, easy, cheap, effective, rugged, and safe (QuEChERS) method in conjunction with liquid-chromatography mass spectrometry was used for analysis of carbendazim. Recovery of carbendazim was within 78.92-96.28 % and relative standard deviation within 3.8-10.9 % (n = 6). Carbendazim residues on pomegranate fruits dissipated at the half lives of 17.3 and 22.8 days from treatments at 500 and 1000 g active ingredient (a.i.) ha(-1), respectively. Its residues in pomegranate aril were highest on the tenth day and reduced thereafter. The residue level of carbendazim on pomegranate whole fruits from standard dose treatment was less than the EU maximum residue limit (MRL) of 0.1 mg kg(-1) at harvest. The carbendazim residues were

Pesticide residues in Portuguese strawberries grown in 2009-2010 using integrated pest management and organic farming.

PubMed

Fernandes, Virgínia C; Domingues, Valentina F; Mateus, Nuno; Delerue-Matos, Cristina

2012-11-01

Pesticides are among the most widely used chemicals in the world. Because of the widespread use of agricultural chemicals in food production, people are exposed to low levels of pesticide residues through their diets. Scientists do not yet have a total understanding of the health effects of these pesticide residues. This work aims to determine differences in terms of pesticide residue content in Portuguese strawberries grown using different agriculture practices. The Quick, Easy, Cheap, Effective, Rugged, and Safe sample preparation method was conducted and shown to have good performance for multiclass pesticides extraction in strawberries. The screening of 25 pesticides residue was performed by gas chromatography-tandem mass spectrometry. In quantitative validation, acceptable performances were achieved with recoveries of 70-120 and <12 % residual standard deviation for 25 pesticides. Good linearity was obtained for all the target compounds, with highly satisfactory repeatability. The limits of detection were in the range of 0.1-28 μg/kg. The method was applied to analyze strawberry samples from organic and integrated pest management (IPM) practices harvested in 2009-2010. The results showed the presence of fludioxonil, bifenthrin, mepanipyrim, tolylfluanid, cyprodinil, tetraconazole, and malathion when using IPM below the maximum residue levels.

Triangular Resection of the Upper Lateral Cartilage for Middle Vault Deviation.

PubMed

Ryu, Gwanghui; Seo, Min Young; Lee, Kyung Eun; Hong, Sang Duk; Chung, Seung-Kyu; Dhong, Hun-Jong; Kim, Hyo Yeol

2018-06-02

Middle vault deviation has a significant effect on the aesthetic and functional aspects of the nose, and its management continues to be a challenge. Spreader graft and its modification techniques have been focused, but there has been scarce consideration for removing surplus portion and balancing the upper lateral cartilage (ULC). This study aimed to report the newly invented triangular-shaped resection technique ("triangular resection") of the ULC and to evaluate its efficacy for correcting middle vault deviation. A retrospective study included 17 consecutive patients who presented with middle vault deviation and underwent septorhinoplasty by using triangular resection at a tertiary academic hospital from February 2014 and March 2016. Their outcomes were evaluated pre- and postoperatively including medical photographs, acoustic rhinometry and subjective nasal obstruction using a 7-point Likert scale. The immediate outcomes were evaluated around 1 month after surgery, and long-term outcomes were available in 12 patients; the mean follow-up period was 9.1 months. Nasal tip deviation angle was reduced from 5.66º to 2.37º immediately (P<0.001). Middle vault deviation also improved from 169.50º to 177.24º (P<0.001). Long-term results were 2.49º (P=0.015) for nasal tip deviation and 178.68º (P=0.002) for middle vault deviation. The aesthetic outcome involved a complete correction in eight patients (47.1%), a minimally visible deviation in seven patients (41.2%) and a remaining residual deviation in two patients (11.8%). Pre- and postoperative minimal cross-sectional areas (summation of the right and left sides) were 0.86 and 1.07, respectively (P=0.021). Fifteen patients answered about their nasal obstruction symptoms and the median symptom score had alleviated from 6.0 to 3.0 (P=0.004). Triangular resection of the ULC is a simple and effective method for correcting middle vault deviation and balancing the ULCs without complications as internal nasal valve narrowing.

SU-F-T-57: Delivered Activity Accuracy of Radium 223 Dichloride Injections, When Being Administrated for Castration Resistant Prostate Cancer, Symptomatic Bone Metastases. The Impact of Residual Activity in the Spent Syringe and Dispensing Accuracy of Ra 223

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jennings, G

Purpose: To quantify the delivered activity accuracy of Radium 223 dichloride injections, when being administrated for castration – resistant prostate cancer, symptomatic bone metastases. The impact of residual activity in the spent syringe and dispensing accuracy of Ra 223. Methods: The administration is by slow intravenous injection over 1 minute followed by double flushing of the 10 mL syringe and IV with saline. Eighty (80) procedures was used to investigate variations in the activity from the amount prescribed (µCi) = 1.35 × Patient weight Kg. The Activity dispensed into a 10mL syringe using a NIST traceable Capintec CRC-25R Chamber andmore » a cross calibrated capintec CRC-15R to measure activity in the syringe immediately before and after administration Results: The patients weight range from 121Ib to 235lb and doses ranging 74.25 µCi to 144.2 µCi. The deviation of dispensed dose vs Prescribed dose average +2.1% with a range of −1.1% to +5.7%. The Dose measured before administration ranges 79.3 µCi to 154.9 µCi. Deviation from the dispensed dose was show to average +2.9% with a range of −0.8% to +7.3%. The average residual dose post injection was 2.5 µCi or 2.2% of the pre injection activity. Ranging from 0.9 µCi to 6.2 µCi, 0.7% to 5.4% respectively. Subtracting the residual activity from that measured activity before injection and comparing it to prescription dose was shown to have an average variation of +2.7% with a range of −0.8% to 7.4%. Conclusion: The case resulted in the 6.2 µCi maximum residual dose had two syringes. A small, 82.8 µCi activity, case resulted in the 7.4% maximum variation in measures less residual verses prescription dose. The average +2.1 % dispenses activity of Ra 223 over the prescription dosage was seen to counteract the average 2.2% residual dosage found to remain in the syringe.« less

Rapid ion-pair liquid chromatographic method for the determination of fenbendazole marker residue in fermented dairy products.

PubMed

Vousdouka, Venetia I; Papapanagiotou, Elias P; Angelidis, Apostolos S; Fletouris, Dimitrios J

2017-04-15

A simple, rapid and sensitive liquid chromatographic method that allows for the quantitative determination of fenbendazole residues in fermented dairy products is described. Samples were extracted with a mixture of acetonitrile-phosphoric acid and the extracts were defatted with hexane to be further partitioned into ethyl acetate. The organic layer was evaporated to dryness and the residue was reconstituted in mobile phase. Separation of fenbendazole and its sulphoxide, sulphone, and p-hydroxylated metabolites was carried out isocratically with a mobile phase containing both positively and negatively charged pairing ions. Overall recoveries ranged from 79.8 to 88.8%, while precision data, based on within and between days variations, suggested an overall relative standard deviation of 6.3-11.0%. The detection and quantification limits were lower than 9 and 21μg/kg, respectively. The method has been successfully applied to quantitate fenbendazole residues in Feta cheese and yoghurt made from spiked and incurred ovine milk. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analysis of deep learning methods for blind protein contact prediction in CASP12.

PubMed

Wang, Sheng; Sun, Siqi; Xu, Jinbo

2018-03-01

Here we present the results of protein contact prediction achieved in CASP12 by our RaptorX-Contact server, which is an early implementation of our deep learning method for contact prediction. On a set of 38 free-modeling target domains with a median family size of around 58 effective sequences, our server obtained an average top L/5 long- and medium-range contact accuracy of 47% and 44%, respectively (L = length). A complete implementation has an average accuracy of 59% and 57%, respectively. Our deep learning method formulates contact prediction as a pixel-level image labeling problem and simultaneously predicts all residue pairs of a protein using a combination of two deep residual neural networks, taking as input the residue conservation information, predicted secondary structure and solvent accessibility, contact potential, and coevolution information. Our approach differs from existing methods mainly in (1) formulating contact prediction as a pixel-level image labeling problem instead of an image-level classification problem; (2) simultaneously predicting all contacts of an individual protein to make effective use of contact occurrence patterns; and (3) integrating both one-dimensional and two-dimensional deep convolutional neural networks to effectively learn complex sequence-structure relationship including high-order residue correlation. This paper discusses the RaptorX-Contact pipeline, both contact prediction and contact-based folding results, and finally the strength and weakness of our method. © 2017 Wiley Periodicals, Inc.

Ensemble Architecture for Prediction of Enzyme-ligand Binding Residues Using Evolutionary Information.

PubMed

Pai, Priyadarshini P; Dattatreya, Rohit Kadam; Mondal, Sukanta

2017-11-01

Enzyme interactions with ligands are crucial for various biochemical reactions governing life. Over many years attempts to identify these residues for biotechnological manipulations have been made using experimental and computational techniques. The computational approaches have gathered impetus with the accruing availability of sequence and structure information, broadly classified into template-based and de novo methods. One of the predominant de novo methods using sequence information involves application of biological properties for supervised machine learning. Here, we propose a support vector machines-based ensemble for prediction of protein-ligand interacting residues using one of the most important discriminative contributing properties in the interacting residue neighbourhood, i. e., evolutionary information in the form of position-specific- scoring matrix (PSSM). The study has been performed on a non-redundant dataset comprising of 9269 interacting and 91773 non-interacting residues for prediction model generation and further evaluation. Of the various PSSM-based models explored, the proposed method named ROBBY (pRediction Of Biologically relevant small molecule Binding residues on enzYmes) shows an accuracy of 84.0 %, Matthews Correlation Coefficient of 0.343 and F-measure of 39.0 % on 78 test enzymes. Further, scope of adding domain knowledge such as pocket information has also been investigated; results showed significant enhancement in method precision. Findings are hoped to boost the reliability of small-molecule ligand interaction prediction for enzyme applications and drug design. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Accuracy of Physical Examination, Ultrasonography, and Mammography in Predicting Residual Pathologic Tumor Size in Patients Treated With Neoadjuvant Chemotherapy

PubMed Central

Chagpar, Anees B.; Middleton, Lavinia P.; Sahin, Aysegul A.; Dempsey, Peter; Buzdar, Aman U.; Mirza, Attiqa N.; Ames, Fredrick C.; Babiera, Gildy V.; Feig, Barry W.; Hunt, Kelly K.; Kuerer, Henry M.; Meric-Bernstam, Funda; Ross, Merrick I.; Singletary, S Eva

2006-01-01

Objective: To assess the accuracy of physical examination, ultrasonography, and mammography in predicting residual size of breast tumors following neoadjuvant chemotherapy. Background: Neoadjuvant chemotherapy is an accepted part of the management of stage II and III breast cancer. Accurate prediction of residual pathologic tumor size after neoadjuvant chemotherapy is critical in guiding surgical therapy. Although physical examination, ultrasonography, and mammography have all been used to predict residual tumor size, there have been conflicting reports about the accuracy of these methods in the neoadjuvant setting. Methods: We reviewed the records of 189 patients who participated in 1 of 2 protocols using doxorubicin-containing neoadjuvant chemotherapy, and who had assessment by physical examination, ultrasonography, and/or mammography no more than 60 days before their surgical resection. Size correlations were performed using Spearman rho analysis. Clinical and pathologic measurements were also compared categorically using the weighted kappa statistic. Results: Size estimates by physical examination, ultrasonography, and mammography were only moderately correlated with residual pathologic tumor size after neoadjuvant chemotherapy (correlation coefficients: 0.42, 0.42, and 0.41, respectively), with an accuracy of ±1 cm in 66% of patients by physical examination, 75% by ultrasonography, and 70% by mammography. Kappa values (0.24–0.35) indicated poor agreement between clinical and pathologic measurements. Conclusion: Physical examination, ultrasonography, and mammography were only moderately useful for predicting residual pathologic tumor size after neoadjuvant chemotherapy. PMID:16432360

Stress transfer mechanisms at the submicron level for graphene/polymer systems.

PubMed

Anagnostopoulos, George; Androulidakis, Charalampos; Koukaras, Emmanuel N; Tsoukleri, Georgia; Polyzos, Ioannis; Parthenios, John; Papagelis, Konstantinos; Galiotis, Costas

2015-02-25

The stress transfer mechanism from a polymer substrate to a nanoinclusion, such as a graphene flake, is of extreme interest for the production of effective nanocomposites. Previous work conducted mainly at the micron scale has shown that the intrinsic mechanism of stress transfer is shear at the interface. However, since the interfacial shear takes its maximum value at the very edge of the nanoinclusion it is of extreme interest to assess the effect of edge integrity upon axial stress transfer at the submicron scale. Here, we conduct a detailed Raman line mapping near the edges of a monolayer graphene flake that is simply supported onto an epoxy-based photoresist (SU8)/poly(methyl methacrylate) matrix at steps as small as 100 nm. We show for the first time that the distribution of axial strain (stress) along the flake deviates somewhat from the classical shear-lag prediction for a region of ∼ 2 μm from the edge. This behavior is mainly attributed to the presence of residual stresses, unintentional doping, and/or edge effects (deviation from the equilibrium values of bond lengths and angles, as well as different edge chiralities). By considering a simple balance of shear-to-normal stresses at the interface we are able to directly convert the strain (stress) gradient to values of interfacial shear stress for all the applied tensile levels without assuming classical shear-lag behavior. For large flakes a maximum value of interfacial shear stress of 0.4 MPa is obtained prior to flake slipping.

OPR-PPR, a Computer Program for Assessing Data Importance to Model Predictions Using Linear Statistics

USGS Publications Warehouse

Tonkin, Matthew J.; Tiedeman, Claire; Ely, D. Matthew; Hill, Mary C.

2007-01-01

The OPR-PPR program calculates the Observation-Prediction (OPR) and Parameter-Prediction (PPR) statistics that can be used to evaluate the relative importance of various kinds of data to simulated predictions. The data considered fall into three categories: (1) existing observations, (2) potential observations, and (3) potential information about parameters. The first two are addressed by the OPR statistic; the third is addressed by the PPR statistic. The statistics are based on linear theory and measure the leverage of the data, which depends on the location, the type, and possibly the time of the data being considered. For example, in a ground-water system the type of data might be a head measurement at a particular location and time. As a measure of leverage, the statistics do not take into account the value of the measurement. As linear measures, the OPR and PPR statistics require minimal computational effort once sensitivities have been calculated. Sensitivities need to be calculated for only one set of parameter values; commonly these are the values estimated through model calibration. OPR-PPR can calculate the OPR and PPR statistics for any mathematical model that produces the necessary OPR-PPR input files. In this report, OPR-PPR capabilities are presented in the context of using the ground-water model MODFLOW-2000 and the universal inverse program UCODE_2005. The method used to calculate the OPR and PPR statistics is based on the linear equation for prediction standard deviation. Using sensitivities and other information, OPR-PPR calculates (a) the percent increase in the prediction standard deviation that results when one or more existing observations are omitted from the calibration data set; (b) the percent decrease in the prediction standard deviation that results when one or more potential observations are added to the calibration data set; or (c) the percent decrease in the prediction standard deviation that results when potential information on one or more parameters is added.

Analysis on Experimental Investigation and Mathematical Modeling of Incompressible Flow Through Ceramic Foam Filters

NASA Astrophysics Data System (ADS)

Akbarnejad, Shahin; Jonsson, Lage Tord Ingemar; Kennedy, Mark William; Aune, Ragnhild Elizabeth; Jönsson, Pӓr Göran

2016-08-01

This paper presents experimental results of pressure drop measurements on 30, 50, and 80 pores per inch (PPI) commercial alumina ceramic foam filters (CFF) and compares the obtained pressure drop profiles to numerically modeled values. In addition, it is aimed at investigating the adequacy of the mathematical correlations used in the analytical and the computational fluid dynamics (CFD) simulations. It is shown that the widely used correlations for predicting pressure drop in porous media continuously under-predict the experimentally obtained pressure drop profiles. For analytical predictions, the negative deviations from the experimentally obtained pressure drop using the unmodified Ergun and Dietrich equations could be as high as 95 and 74 pct, respectively. For the CFD predictions, the deviation to experimental results is in the range of 84.3 to 88.5 pct depending on filter PPI. Better results can be achieved by applying the Forchheimer second-order drag term instead of the Brinkman-Forchheimer drag term. Thus, the final deviation of the CFD model estimates lie in the range of 0.3 to 5.5 pct compared to the measured values.

Sink fast and swim harder! Round-trip cost-of-transport for buoyant divers.

PubMed

Miller, Patrick J O; Biuw, Martin; Watanabe, Yuuki Y; Thompson, Dave; Fedak, Mike A

2012-10-15

Efficient locomotion between prey resources at depth and oxygen at the surface is crucial for breath-hold divers to maximize time spent in the foraging layer, and thereby net energy intake rates. The body density of divers, which changes with body condition, determines the apparent weight (buoyancy) of divers, which may affect round-trip cost-of-transport (COT) between the surface and depth. We evaluated alternative predictions from external-work and actuator-disc theory of how non-neutral buoyancy affects round-trip COT to depth, and the minimum COT speed for steady-state vertical transit. Not surprisingly, the models predict that one-way COT decreases (increases) when buoyancy aids (hinders) one-way transit. At extreme deviations from neutral buoyancy, gliding at terminal velocity is the minimum COT strategy in the direction aided by buoyancy. In the transit direction hindered by buoyancy, the external-work model predicted that minimum COT speeds would not change at greater deviations from neutral buoyancy, but minimum COT speeds were predicted to increase under the actuator disc model. As previously documented for grey seals, we found that vertical transit rates of 36 elephant seals increased in both directions as body density deviated from neutral buoyancy, indicating that actuator disc theory may more closely predict the power requirements of divers affected by gravity than an external work model. For both models, minor deviations from neutral buoyancy did not affect minimum COT speed or round-trip COT itself. However, at body-density extremes, both models predict that savings in the aided direction do not fully offset the increased COT imposed by the greater thrusting required in the hindered direction.

CFD analysis of temperature imbalance in superheater/reheater region of tangentially coal-fired boiler

NASA Astrophysics Data System (ADS)

Zainudin, A. F.; Hasini, H.; Fadhil, S. S. A.

2017-10-01

This paper presents a CFD analysis of the flow, velocity and temperature distribution in a 700 MW tangentially coal-fired boiler operating in Malaysia. The main objective of the analysis is to gain insights on the occurrences in the boiler so as to understand the inherent steam temperature imbalance problem. The results show that the root cause of the problem comes from the residual swirl in the horizontal pass. The deflection of the residual swirl due to the sudden reduction and expansion of the flow cross-sectional area causes velocity deviation between the left and right side of the boiler. This consequently results in flue gas temperature imbalance which has often caused tube leaks in the superheater/reheater region. Therefore, eliminating the residual swirl or restraining it from being diverted might help to alleviate the problem.

HotRegion: a database of predicted hot spot clusters.

PubMed

Cukuroglu, Engin; Gursoy, Attila; Keskin, Ozlem

2012-01-01

Hot spots are energetically important residues at protein interfaces and they are not randomly distributed across the interface but rather clustered. These clustered hot spots form hot regions. Hot regions are important for the stability of protein complexes, as well as providing specificity to binding sites. We propose a database called HotRegion, which provides the hot region information of the interfaces by using predicted hot spot residues, and structural properties of these interface residues such as pair potentials of interface residues, accessible surface area (ASA) and relative ASA values of interface residues of both monomer and complex forms of proteins. Also, the 3D visualization of the interface and interactions among hot spot residues are provided. HotRegion is accessible at http://prism.ccbb.ku.edu.tr/hotregion.

Two States Mapping Based Time Series Neural Network Model for Compensation Prediction Residual Error

NASA Astrophysics Data System (ADS)

Jung, Insung; Koo, Lockjo; Wang, Gi-Nam

2008-11-01

The objective of this paper was to design a model of human bio signal data prediction system for decreasing of prediction error using two states mapping based time series neural network BP (back-propagation) model. Normally, a lot of the industry has been applied neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has got a residual error between real value and prediction result. Therefore, we designed two states of neural network model for compensation residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We determined that most of the simulation cases were satisfied by the two states mapping based time series prediction model. In particular, small sample size of times series were more accurate than the standard MLP model.

An object programming based environment for protein secondary structure prediction.

PubMed

Giacomini, M; Ruggiero, C; Sacile, R

1996-01-01

The most frequently used methods for protein secondary structure prediction are empirical statistical methods and rule based methods. A consensus system based on object-oriented programming is presented, which integrates the two approaches with the aim of improving the prediction quality. This system uses an object-oriented knowledge representation based on the concepts of conformation, residue and protein, where the conformation class is the basis, the residue class derives from it and the protein class derives from the residue class. The system has been tested with satisfactory results on several proteins of the Brookhaven Protein Data Bank. Its results have been compared with the results of the most widely used prediction methods, and they show a higher prediction capability and greater stability. Moreover, the system itself provides an index of the reliability of its current prediction. This system can also be regarded as a basis structure for programs of this kind.

A Progressive Damage Methodology for Residual Strength Predictions of Center-Crack Tension Composite Panels

NASA Technical Reports Server (NTRS)

Coats, Timothy William

1996-01-01

An investigation of translaminate fracture and a progressive damage methodology was conducted to evaluate and develop a residual strength prediction capability for laminated composites with through penetration notches. This is relevant to the damage tolerance of an aircraft fuselage that might suffer an in-flight accident such as an uncontained engine failure. An experimental characterization of several composite materials systems revealed an R-curve type of behavior. Fractographic examinations led to the postulate that this crack growth resistance could be due to fiber bridging, defined here as fractured fibers of one ply bridged by intact fibers of an adjacent ply. The progressive damage methodology is currently capable of predicting the initiation and growth of matrix cracks and fiber fracture. Using two difference fiber failure criteria, residual strength was predicted for different size panel widths and notch lengths. A ply discount fiber failure criterion yielded extremely conservative results while an elastic-perfectly plastic fiber failure criterion showed that the fiber bridging concept is valid for predicting residual strength for tensile dominated failure loads. Furthermore, the R-curves predicted by the model using the elastic-perfectly plastic fiber criterion compared very well with the experimental R-curves.

Development of QuEChERS-based extraction and liquid chromatography-tandem mass spectrometry method for quantifying flumethasone residues in beef muscle.

PubMed

Park, Ki Hun; Choi, Jeong-Heui; Abd El-Aty, A M; Cho, Soon-Kil; Park, Jong-Hyouk; Kwon, Ki Sung; Park, Hee Ra; Kim, Hyung Soo; Shin, Ho-Chul; Kim, Mi Ra; Shim, Jae-Han

2012-12-01

A rapid, specific, and sensitive method based on liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) in the positive ion mode using multiple reaction monitoring (MRM) was developed and validated to quantify flumethasone residues in beef muscle. Methods were compared between the original as well as the EN quick, easy, cheap, effective, rugged, and safe (QuEChERS)-based extraction. Good linearity was achieved at concentration levels of 5-30 μg/kg. Estimated recovery rates at spiking levels of 5 and 10 μg/kg ranged from 72.1 to 84.6%, with relative standard deviations (RSDs)<7%. The results of the inter-day study, which was performed by fortifying beef muscle samples (n=18) on 3 separate days, showed an accuracy of 93.4-94.4%. The precision (expressed as relative standard deviation values) for the inter-day variation at two levels of fortification (10 and 20 μg/kg) was 1.9-5.2%. The limit of detection (LOD) and limit of quantitation (LOQ) were 1.7 and 5 μg/kg, at signal-to-noise ratios (S/Ns) of 3 and 10, respectively. The method was successfully applied to analyze real samples obtained from large markets throughout the Korean Peninsula. The method proved to be sensitive and reliable and, thus, rendered an appropriate means for residue analysis studies. Copyright © 2012 Elsevier Ltd. All rights reserved.

Laser frequency stabilization using a commercial wavelength meter

NASA Astrophysics Data System (ADS)

Couturier, Luc; Nosske, Ingo; Hu, Fachao; Tan, Canzhu; Qiao, Chang; Jiang, Y. H.; Chen, Peng; Weidemüller, Matthias

2018-04-01

We present the characterization of a laser frequency stabilization scheme using a state-of-the-art wavelength meter based on solid Fizeau interferometers. For a frequency-doubled Ti-sapphire laser operated at 461 nm, an absolute Allan deviation below 10-9 with a standard deviation of 1 MHz over 10 h is achieved. Using this laser for cooling and trapping of strontium atoms, the wavemeter scheme provides excellent stability in single-channel operation. Multi-channel operation with a multimode fiber switch results in fluctuations of the atomic fluorescence correlated to residual frequency excursions of the laser. The wavemeter-based frequency stabilization scheme can be applied to a wide range of atoms and molecules for laser spectroscopy, cooling, and trapping.

Global empirical model of TEC response to geomagnetic activity

NASA Astrophysics Data System (ADS)

Mukhtarov, P.; Andonov, B.; Pancheva, D.

2013-10-01

global total electron content (TEC) model response to geomagnetic activity described by the Kp index is built by using the Center for Orbit Determination of Europe (CODE) TEC data for a full 13 years, January 1999 to December 2011. The model describes the most probable spatial distribution and temporal variability of the geomagnetically forced TEC anomalies assuming that these anomalies at a given modified dip latitude depend mainly on the Kp index, local time (LT), and longitude. The geomagnetic anomalies are expressed by the relative deviation of TEC from its 15 day median and are denoted as rTEC. The rTEC response to the geomagnetic activity is presented by a sum of two responses with different time delay constants and different signs of the cross-correlation function. It has been found that the mean dependence of rTEC on Kp index can be expressed by a cubic function. The LT dependence of rTEC is described by Fourier time series which includes the contribution of four diurnal components with periods 24, 12, 8, and 6 h. The rTEC dependence on longitude is presented by Fourier series which includes the contribution of zonal waves with zonal wave numbers up to 6. In order to demonstrate how the model is able to reproduce the rTEC response to geomagnetic activity, three geomagnetic storms at different seasons and solar activity conditions are presented. The model residuals clearly reveal two types of the model deviation from the data: some underestimation of the largest TEC response to the geomagnetic activity and randomly distributed errors which are the data noise or anomalies generated by other sources. The presented TEC model fits to the CODE TEC input data with small negative bias of -0.204, root mean squares error RMSE = 4.592, and standard deviation error STDE = 4.588. The model offers TEC maps which depend on geographic coordinates (5° × 5° in latitude and longitude) and universal time (UT) at given geomagnetic activity and day of the year. It could be used for both science and possible service (nowcasting and short-term prediction); for the latter, a detailed validation of the model at different geophysical conditions has to be performed in order to clarify the model predicting quality.

In silico platform for predicting and initiating β-turns in a protein at desired locations.

PubMed

Singh, Harinder; Singh, Sandeep; Raghava, Gajendra P S

2015-05-01

Numerous studies have been performed for analysis and prediction of β-turns in a protein. This study focuses on analyzing, predicting, and designing of β-turns to understand the preference of amino acids in β-turn formation. We analyzed around 20,000 PDB chains to understand the preference of residues or pair of residues at different positions in β-turns. Based on the results, a propensity-based method has been developed for predicting β-turns with an accuracy of 82%. We introduced a new approach entitled "Turn level prediction method," which predicts the complete β-turn rather than focusing on the residues in a β-turn. Finally, we developed BetaTPred3, a Random forest based method for predicting β-turns by utilizing various features of four residues present in β-turns. The BetaTPred3 achieved an accuracy of 79% with 0.51 MCC that is comparable or better than existing methods on BT426 dataset. Additionally, models were developed to predict β-turn types with better performance than other methods available in the literature. In order to improve the quality of prediction of turns, we developed prediction models on a large and latest dataset of 6376 nonredundant protein chains. Based on this study, a web server has been developed for prediction of β-turns and their types in proteins. This web server also predicts minimum number of mutations required to initiate or break a β-turn in a protein at specified location of a protein. © 2015 Wiley Periodicals, Inc.

Evaluation of Acoustic Doppler Current Profiler measurements of river discharge

USGS Publications Warehouse

Morlock, S.E.

1996-01-01

The standard deviations of the ADCP measurements ranged from approximately 1 to 6 percent and were generally higher than the measurement errors predicted by error-propagation analysis of ADCP instrument performance. These error-prediction methods assume that the largest component of ADCP discharge measurement error is instrument related. The larger standard deviations indicate that substantial portions of measurement error may be attributable to sources unrelated to ADCP electronics or signal processing and are functions of the field environment.

COUSCOus: improved protein contact prediction using an empirical Bayes covariance estimator.

PubMed

Rawi, Reda; Mall, Raghvendra; Kunji, Khalid; El Anbari, Mohammed; Aupetit, Michael; Ullah, Ehsan; Bensmail, Halima

2016-12-15

The post-genomic era with its wealth of sequences gave rise to a broad range of protein residue-residue contact detecting methods. Although various coevolution methods such as PSICOV, DCA and plmDCA provide correct contact predictions, they do not completely overlap. Hence, new approaches and improvements of existing methods are needed to motivate further development and progress in the field. We present a new contact detecting method, COUSCOus, by combining the best shrinkage approach, the empirical Bayes covariance estimator and GLasso. Using the original PSICOV benchmark dataset, COUSCOus achieves mean accuracies of 0.74, 0.62 and 0.55 for the top L/10 predicted long, medium and short range contacts, respectively. In addition, COUSCOus attains mean areas under the precision-recall curves of 0.25, 0.29 and 0.30 for long, medium and short contacts and outperforms PSICOV. We also observed that COUSCOus outperforms PSICOV w.r.t. Matthew's correlation coefficient criterion on full list of residue contacts. Furthermore, COUSCOus achieves on average 10% more gain in prediction accuracy compared to PSICOV on an independent test set composed of CASP11 protein targets. Finally, we showed that when using a simple random forest meta-classifier, by combining contact detecting techniques and sequence derived features, PSICOV predictions should be replaced by the more accurate COUSCOus predictions. We conclude that the consideration of superior covariance shrinkage approaches will boost several research fields that apply the GLasso procedure, amongst the presented one of residue-residue contact prediction as well as fields such as gene network reconstruction.

Assessment of Protein Side-Chain Conformation Prediction Methods in Different Residue Environments

PubMed Central

Peterson, Lenna X.; Kang, Xuejiao; Kihara, Daisuke

2016-01-01

Computational prediction of side-chain conformation is an important component of protein structure prediction. Accurate side-chain prediction is crucial for practical applications of protein structure models that need atomic detailed resolution such as protein and ligand design. We evaluated the accuracy of eight side-chain prediction methods in reproducing the side-chain conformations of experimentally solved structures deposited to the Protein Data Bank. Prediction accuracy was evaluated for a total of four different structural environments (buried, surface, interface, and membrane-spanning) in three different protein types (monomeric, multimeric, and membrane). Overall, the highest accuracy was observed for buried residues in monomeric and multimeric proteins. Notably, side-chains at protein interfaces and membrane-spanning regions were better predicted than surface residues even though the methods did not all use multimeric and membrane proteins for training. Thus, we conclude that the current methods are as practically useful for modeling protein docking interfaces and membrane-spanning regions as for modeling monomers. PMID:24619909

A Multifeatures Fusion and Discrete Firefly Optimization Method for Prediction of Protein Tyrosine Sulfation Residues.

PubMed

Guo, Song; Liu, Chunhua; Zhou, Peng; Li, Yanling

2016-01-01

Tyrosine sulfation is one of the ubiquitous protein posttranslational modifications, where some sulfate groups are added to the tyrosine residues. It plays significant roles in various physiological processes in eukaryotic cells. To explore the molecular mechanism of tyrosine sulfation, one of the prerequisites is to correctly identify possible protein tyrosine sulfation residues. In this paper, a novel method was presented to predict protein tyrosine sulfation residues from primary sequences. By means of informative feature construction and elaborate feature selection and parameter optimization scheme, the proposed predictor achieved promising results and outperformed many other state-of-the-art predictors. Using the optimal features subset, the proposed method achieved mean MCC of 94.41% on the benchmark dataset, and a MCC of 90.09% on the independent dataset. The experimental performance indicated that our new proposed method could be effective in identifying the important protein posttranslational modifications and the feature selection scheme would be powerful in protein functional residues prediction research fields.

A Multifeatures Fusion and Discrete Firefly Optimization Method for Prediction of Protein Tyrosine Sulfation Residues

PubMed Central

Liu, Chunhua; Zhou, Peng; Li, Yanling

2016-01-01

Tyrosine sulfation is one of the ubiquitous protein posttranslational modifications, where some sulfate groups are added to the tyrosine residues. It plays significant roles in various physiological processes in eukaryotic cells. To explore the molecular mechanism of tyrosine sulfation, one of the prerequisites is to correctly identify possible protein tyrosine sulfation residues. In this paper, a novel method was presented to predict protein tyrosine sulfation residues from primary sequences. By means of informative feature construction and elaborate feature selection and parameter optimization scheme, the proposed predictor achieved promising results and outperformed many other state-of-the-art predictors. Using the optimal features subset, the proposed method achieved mean MCC of 94.41% on the benchmark dataset, and a MCC of 90.09% on the independent dataset. The experimental performance indicated that our new proposed method could be effective in identifying the important protein posttranslational modifications and the feature selection scheme would be powerful in protein functional residues prediction research fields. PMID:27034949

Sequence-Based Prediction of RNA-Binding Residues in Proteins.

PubMed

Walia, Rasna R; El-Manzalawy, Yasser; Honavar, Vasant G; Dobbs, Drena

2017-01-01

Identifying individual residues in the interfaces of protein-RNA complexes is important for understanding the molecular determinants of protein-RNA recognition and has many potential applications. Recent technical advances have led to several high-throughput experimental methods for identifying partners in protein-RNA complexes, but determining RNA-binding residues in proteins is still expensive and time-consuming. This chapter focuses on available computational methods for identifying which amino acids in an RNA-binding protein participate directly in contacting RNA. Step-by-step protocols for using three different web-based servers to predict RNA-binding residues are described. In addition, currently available web servers and software tools for predicting RNA-binding sites, as well as databases that contain valuable information about known protein-RNA complexes, RNA-binding motifs in proteins, and protein-binding recognition sites in RNA are provided. We emphasize sequence-based methods that can reliably identify interfacial residues without the requirement for structural information regarding either the RNA-binding protein or its RNA partner.

Sequence-Based Prediction of RNA-Binding Residues in Proteins

PubMed Central

Walia, Rasna R.; EL-Manzalawy, Yasser; Honavar, Vasant G.; Dobbs, Drena

2017-01-01

Identifying individual residues in the interfaces of protein–RNA complexes is important for understanding the molecular determinants of protein–RNA recognition and has many potential applications. Recent technical advances have led to several high-throughput experimental methods for identifying partners in protein–RNA complexes, but determining RNA-binding residues in proteins is still expensive and time-consuming. This chapter focuses on available computational methods for identifying which amino acids in an RNA-binding protein participate directly in contacting RNA. Step-by-step protocols for using three different web-based servers to predict RNA-binding residues are described. In addition, currently available web servers and software tools for predicting RNA-binding sites, as well as databases that contain valuable information about known protein–RNA complexes, RNA-binding motifs in proteins, and protein-binding recognition sites in RNA are provided. We emphasize sequence-based methods that can reliably identify interfacial residues without the requirement for structural information regarding either the RNA-binding protein or its RNA partner. PMID:27787829

Residual Stress Assessment in Thin Angle Ply Tubes

NASA Astrophysics Data System (ADS)

Kaddour, A. S.; Al-Hassani, S. T. S.; Hinton, M. J.

2003-05-01

This preliminary study aims to investigate the residual stresses developed in hot cured thin-walled angle-ply filament wound tubes made of E-glass/epoxy, Kevlar/epoxy and carbon/epoxy materials. The residual stresses were estimated from change in geometry of these tubes when axially slitted at ambient temperature. Three basic deformation modes; namely opening up, closing-in and twisting, were observed and these depended on the winding angle, material and wall thickness. The residual stresses were also determined from hoop and axial strain gauges mounted on both the inner and outer surfaces at various locations around the tube. The stresses were compared with theoretical prediction based upon a linear thermo-elastic analysis. Both the predicted and measured values were found to increase with increasing hoop stiffness but there was a large discrepancy between the predicted and measured data, reaching a factor of 5 for the thinnest case. When compared with predicted failure stresses, the experimentally determined stresses were some 15% of the computed compressive strength.

Using weighted power mean for equivalent square estimation.

PubMed

Zhou, Sumin; Wu, Qiuwen; Li, Xiaobo; Ma, Rongtao; Zheng, Dandan; Wang, Shuo; Zhang, Mutian; Li, Sicong; Lei, Yu; Fan, Qiyong; Hyun, Megan; Diener, Tyler; Enke, Charles

2017-11-01

Equivalent Square (ES) enables the calculation of many radiation quantities for rectangular treatment fields, based only on measurements from square fields. While it is widely applied in radiotherapy, its accuracy, especially for extremely elongated fields, still leaves room for improvement. In this study, we introduce a novel explicit ES formula based on Weighted Power Mean (WPM) function and compare its performance with the Sterling formula and Vadash/Bjärngard's formula. The proposed WPM formula is ESWPMa,b=waα+1-wbα1/α for a rectangular photon field with sides a and b. The formula performance was evaluated by three methods: standard deviation of model fitting residual error, maximum relative model prediction error, and model's Akaike Information Criterion (AIC). Testing datasets included the ES table from British Journal of Radiology (BJR), photon output factors (S cp ) from the Varian TrueBeam Representative Beam Data (Med Phys. 2012;39:6981-7018), and published S cp data for Varian TrueBeam Edge (J Appl Clin Med Phys. 2015;16:125-148). For the BJR dataset, the best-fit parameter value α = -1.25 achieved a 20% reduction in standard deviation in ES estimation residual error compared with the two established formulae. For the two Varian datasets, employing WPM reduced the maximum relative error from 3.5% (Sterling) or 2% (Vadash/Bjärngard) to 0.7% for open field sizes ranging from 3 cm to 40 cm, and the reduction was even more prominent for 1 cm field sizes on Edge (J Appl Clin Med Phys. 2015;16:125-148). The AIC value of the WPM formula was consistently lower than its counterparts from the traditional formulae on photon output factors, most prominent on very elongated small fields. The WPM formula outperformed the traditional formulae on three testing datasets. With increasing utilization of very elongated, small rectangular fields in modern radiotherapy, improved photon output factor estimation is expected by adopting the WPM formula in treatment planning and secondary MU check. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Prediction of flunixin tissue residue concentrations in livers from diseased cattle.

PubMed

Wu, H; Baynes, R E; Tell, L A; Riviere, J E

2013-12-01

Flunixin, a widely used non-steroidal anti-inflammatory drug, was a leading cause of violative residues in cattle. The objective of this analysis was to explore how the changes in pharmacokinetic (PK) parameters that may be associated with diseased animals affect the predicted liver residue of flunixin in cattle. Monte Carlo simulations for liver residues of flunixin were performed using the PK model structure and relevant PK parameter estimates from a previously published population PK model for flunixin in cattle. The magnitude of a change in the PK parameter value that resulted in a violative residue issue in more than one percent of a cattle population was compared. In this regard, elimination clearance and volume of distribution affected withdrawal times. Pathophysiological factors that can change these parameters may contribute to the occurrence of violative residues of flunixin.

Secondary flow spanwise deviation model for the stators of NASA middle compressor stages

NASA Technical Reports Server (NTRS)

Roberts, W. B.; Sandercock, D. M.

1984-01-01

A model of the spanwise variation of deviation for stator blades is presented. Deviation is defined as the difference between the passage mean flow angle and the metal angle at the outlet of a blade element of an axial compressor stage. The variation of deviation is taken as the difference above or below that predicted by blade element, (i.e., two-dimensional) theory at any spanwise location. The variation of deviation is dependent upon the blade camber, solidity and inlet boundary layer thickness at the hub or tip end-wall, and the blade channel aspect ratio. If these parameters are known or can be calculated, the model provides a reasonable approximation of the spanwise variation of deviation for most compressor middle stage stators operating at subsonic inlet Mach numbers.

A mechanical analysis of conduit arteries accounting for longitudinal residual strains.

PubMed

Wang, Ruoya; Gleason, Rudolph L

2010-04-01

Identification of an appropriate stress-free reference configuration is critically important in providing a reasonable prediction of the intramural stress distribution when performing biomechanical analyses on arteries. The stress-free state is commonly approximated as a radially cut ring that typically opens into a nearly circular sector, relieving much of the circumferential residual strains that exist in the traction-free configuration. An opening angle is often used to characterize this sector. In this study, we first present experimental results showing significant residual deformations in the longitudinal direction of two commonly studied arteries in the pig: the common carotid artery and the left anterior descending coronary artery. We concluded that a radially cut ring cannot completely describe the stress-free state of the arteries. Instead, we propose the use of a longitudinal opening angle, in conjunction with the traditional circumferential opening angle, to experimentally quantify the stress-free state of an artery. Secondly, we propose a new kinematic model to account for the addition of longitudinal residual strains through employing the longitudinal opening angle and performed a stress analysis. We found that with the inclusion of longitudinal residual strains in the stress analysis, the predicted circumferential stress gradient was decreased by 3-fold and the predicted longitudinal stress gradient was increased by 5.7-fold. Thus, inclusion of longitudinal residual strains has a significant effect on the predicted stress distribution in arteries.

Analyses of a 426-Day Record of Seafloor Gravity and Pressure Time Series in the North Sea

NASA Astrophysics Data System (ADS)

Rosat, S.; Escot, B.; Hinderer, J.; Boy, J.-P.

2017-04-01

Continuous gravity observations of ocean and solid tides are usually done with land-based gravimeters. In this study, we analyze a 426-day record of time-varying gravity acquired by an ocean-bottom Scintrex spring gravimeter between August 2005 and November 2006 at the Troll A site located in the North Sea at a depth of 303 m. Sea-bottom pressure changes were also recorded in parallel with a Paroscientific quartz pressure sensor. From these data, we show a comparison of the noise level of the seafloor gravimeter with respect to two standard land-based relative gravimeters: a Scintrex CG5 and a GWR Superconducting Gravimeter that were recording at the J9 gravimetric observatory of Strasbourg (France). We also compare the analyzed gravity records with the predicted solid and oceanic tides. The oceanic tides recorded by the seafloor barometer are also analyzed and compared to the predicted ones using FES2014b ocean model. Observed diurnal and semi-diurnal components are in good agreement with FES2014b predictions. Smallest constituents reflect some differences that may be attributed to non-linearity occurring at the Troll A site. Using the barotropic TUGO-m dynamic model of sea-level response to ECMWF atmospheric pressure and winds forcing, we show a good agreement with the detided ocean-bottom pressure residuals. About 4 hPa of standard deviation of remaining sea-bottom pressure are, however, not explained by the TUGO-m dynamic model.

A molecular dynamics study of Beta-Glucosidase B upon small substrate binding.

PubMed

Mazlan, Nur Shima Fadhilah; Ahmad Khairudin, Nurul Bahiyah

2016-07-01

Paenibacillus polymyxa β-glucosidase B (BglB), belongs to a GH family 1, is a monomeric enzyme that acts as an exo-β-glucosidase hydrolysing cellobiose and cellodextrins of higher degree of polymerization using retaining mechanism. A molecular dynamics (MD) simulation was performed at 300 K under periodic boundary condition for 5 ns using the complexes structure obtained from previous docking study, namely BglB-Beta-d-glucose and BglB-Cellobiose. From the root-mean-square deviation analysis, both enzyme complexes were reported to deviate from the initial structure in the early part of the simulation but it was stable afterwards. The root-mean-square fluctuation analysis revealed that the most flexible regions comprised of the residues from 26 to 29, 43 to 53, 272 to 276, 306 to 325 and 364 to 367. The radius of gyration analysis had shown the structure of BglB without substrate became more compact towards the end of the simulation compare to other two complexes. The residues His122 and Trp410 were observed to form stable hydrogen bond with occupancy higher than 10%. In conclusion, the behaviour of BglB enzyme towards the substrate binding was successfully explored via MD simulation approaches.

An analysis of Landsat-4 Thematic Mapper geometric properties

NASA Technical Reports Server (NTRS)

Walker, R. E.; Zobrist, A. L.; Bryant, N. A.; Gohkman, B.; Friedman, S. Z.; Logan, T. L.

1984-01-01

Landsat-4 Thematic Mapper data of Washington, DC, Harrisburg, PA, and Salton Sea, CA were analyzed to determine geometric integrity and conformity of the data to known earth surface geometry. Several tests were performed. Intraband correlation and interband registration were investigated. No problems were observed in the intraband analysis, and aside from indications of slight misregistration between bands of the primary versus bands of the secondary focal planes, interband registration was well within the specified tolerances. A substantial number of ground control points were found and used to check the images' conformity to the Space Oblique Mercator (SOM) projection of their respective areas. The means of the residual offsets, which included nonprocessing related measurement errors, were close to the one pixel level in the two scenes examined. The Harrisburg scene residual mean was 28.38 m (0.95 pixels) with a standard deviation of 19.82 m (0.66 pixels), while the mean and standard deviation for the Salton Sea scene were 40.46 (1.35 pixels) and 30.57 m (1.02 pixels), respectively. Overall, the data were judged to be a high geometric quality with errors close to those targeted by the TM sensor design specifications.

Steric interactions determine side-chain conformations in protein cores.

PubMed

Caballero, D; Virrueta, A; O'Hern, C S; Regan, L

2016-09-01

We investigate the role of steric interactions in defining side-chain conformations in protein cores. Previously, we explored the strengths and limitations of hard-sphere dipeptide models in defining sterically allowed side-chain conformations and recapitulating key features of the side-chain dihedral angle distributions observed in high-resolution protein structures. Here, we show that modeling residues in the context of a particular protein environment, with both intra- and inter-residue steric interactions, is sufficient to specify which of the allowed side-chain conformations is adopted. This model predicts 97% of the side-chain conformations of Leu, Ile, Val, Phe, Tyr, Trp and Thr core residues to within 20°. Although the hard-sphere dipeptide model predicts the observed side-chain dihedral angle distributions for both Thr and Ser, the model including the protein environment predicts side-chain conformations to within 20° for only 60% of core Ser residues. Thus, this approach can identify the amino acids for which hard-sphere interactions alone are sufficient and those for which additional interactions are necessary to accurately predict side-chain conformations in protein cores. We also show that our approach can predict alternate side-chain conformations of core residues, which are supported by the observed electron density. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Deviation characteristics of specular reflectivity of micro-rough surface from Fresnel's equation

NASA Astrophysics Data System (ADS)

Zhang, W. J.; Qiu, J.; Liu, L. H.

2015-07-01

Specular reflectivity is an important radiative property in thermal engineering applications and reflection-based optical constant determinations, yet it will be influenced by surface micro-roughness which cannot be completely removed during the polishing process. In this work, we examined the deviation characteristics of the specular reflectivity of micro-rough surfaces from that predicted by the Fresnel's equation under the assumption of smooth surface. The effects of incident angle and relative roughness were numerically investigated for both 1D and 2D micro randomly rough surfaces using full wave analysis under the condition that the relative roughness is smaller than 0.05. For transverse magnetic (TM) wave incidence, it is observed that the deviation of specular reflectivity dramatically rises as the incident angle approaches to the pseudo Brewster's angle, which violates the prediction based on Rayleigh criterion. While for the transverse electric (TE) wave incidence, the deviation of the specular reflectivity is much smaller and decreases monotonically with the increase of incident angle, which agrees with the predication from Rayleigh criterion. Generally, the deviation of specular reflectivity for both TM and TE increases with the relative roughness as commonly expected.

Effect of Spring-in Deviation on Fatigue Life of Composite Elevator Assembly

NASA Astrophysics Data System (ADS)

Wang, Hua

2017-12-01

The spring-in deviation results in the extra stresses around the joints of the composite C-beam and metallic parts when they are assembled together. These extra stresses affect the composite elevator's fatigue life, which should be explored with the fatigue experimentation. The paper presents the experimental investigation on the effect of spring-in deviation on the fatigue life of the composite elevator assembly. The investigation seeks to build the relationship between the spring-in and the fatigue life in order to determine the spring-in threshold during the course of assembling. The phenomenological model of the composite C-beam is constructed to predict the stresses around the joints. Based on the predicted spring-in induced stresses around the joints, pre-stresses are precisely added to the fatigue specimen when conducting the fatigue experiment. At last, the relationship curve of the spring-in on the composite C-beam's fatigue life is obtained from the experimental data. Giving the fatigue life accepting limits, the maximum accepting spring-in deviation during the course of assembling could be obtained from the relationship curve. The reported work will enhance the understanding of assembling the composites with spring-in deviation in the civil aircraft industry.

Improved crop residue cover estimates by coupling spectral indices for residue and moisture

USDA-ARS?s Scientific Manuscript database

Remote sensing assessment of soil residue cover (fR) and tillage intensity will improve our predictions of the impact of agricultural practices and promote sustainable management. Spectral indices for estimating fR are sensitive to soil and residue water content, therefore, the uncertainty of estima...

Quantitative modeling of peptide binding to TAP using support vector machine.

PubMed

Diez-Rivero, Carmen M; Chenlo, Bernardo; Zuluaga, Pilar; Reche, Pedro A

2010-01-01

The transport of peptides to the endoplasmic reticulum by the transporter associated with antigen processing (TAP) is a necessary step towards determining CD8 T cell epitopes. In this work, we have studied the predictive performance of support vector machine models trained on single residue positions and residue combinations drawn from a large dataset consisting of 613 nonamer peptides of known affinity to TAP. Predictive performance of these TAP affinity models was evaluated under 10-fold cross-validation experiments and measured using Pearson's correlation coefficients (R(p)). Our results show that every peptide position (P1-P9) contributes to TAP binding (minimum R(p) of 0.26 +/- 0.11 was achieved by a model trained on the P6 residue), although the largest contributions to binding correspond to the C-terminal end (R(p) = 0.68 +/- 0.06) and the P1 (R(p) = 0.51 +/- 0.09) and P2 (0.57 +/- 0.08) residues of the peptide. Training the models on additional peptide residues generally improved their predictive performance and a maximum correlation (R(p) = 0.89 +/- 0.03) was achieved by a model trained on the full-length sequences or a residue selection consisting of the first 5 N- and last 3 C-terminal residues of the peptides included in the training set. A system for predicting the binding affinity of peptides to TAP using the methods described here is readily available for free public use at http://imed.med.ucm.es/Tools/tapreg/. (c) 2009 Wiley-Liss, Inc.

Impact of interannual variability (1979-1986) of transport and temperature on ozone as computed using a two-dimensional photochemical model

NASA Technical Reports Server (NTRS)

Jackman, Charles H.; Douglass, Anne R.; Chandra, Sushil; Stolarski, Richard S.; Rosenfield, Joan E.; Kaye, Jack A.

1991-01-01

Values of the monthly mean heating rates and the residual circulation characteristics were calculated using NMC data for temperature and the solar backscattered UV ozone for the period between 1979 and 1986. The results were used in a two-dimensional photochemical model in order to examine the effects of temperature and residual circulation on the interannual variability of ozone. It was found that the calculated total ozone was more sensitive to variations in interannual residual circulation than in the interannual temperature. The magnitude of the modeled ozone variability was found to be similar to the observed variability, but the observed and modeled year-to-year deviations were, for the most part, uncorrelated, due to the fact that the model did not account for most of the QBO forcing and for some of the observed tropospheric changes.

Tweaked residual convolutional network for face alignment

NASA Astrophysics Data System (ADS)

Du, Wenchao; Li, Ke; Zhao, Qijun; Zhang, Yi; Chen, Hu

2017-08-01

We propose a novel Tweaked Residual Convolutional Network approach for face alignment with two-level convolutional networks architecture. Specifically, the first-level Tweaked Convolutional Network (TCN) module predicts the landmark quickly but accurately enough as a preliminary, by taking low-resolution version of the detected face holistically as the input. The following Residual Convolutional Networks (RCN) module progressively refines the landmark by taking as input the local patch extracted around the predicted landmark, particularly, which allows the Convolutional Neural Network (CNN) to extract local shape-indexed features to fine tune landmark position. Extensive evaluations show that the proposed Tweaked Residual Convolutional Network approach outperforms existing methods.

A General Method for Predicting Amino Acid Residues Experiencing Hydrogen Exchange

PubMed Central

Wang, Boshen; Perez-Rathke, Alan; Li, Renhao; Liang, Jie

2018-01-01

Information on protein hydrogen exchange can help delineate key regions involved in protein-protein interactions and provides important insight towards determining functional roles of genetic variants and their possible mechanisms in disease processes. Previous studies have shown that the degree of hydrogen exchange is affected by hydrogen bond formations, solvent accessibility, proximity to other residues, and experimental conditions. However, a general predictive method for identifying residues capable of hydrogen exchange transferable to a broad set of proteins is lacking. We have developed a machine learning method based on random forest that can predict whether a residue experiences hydrogen exchange. Using data from the Start2Fold database, which contains information on 13,306 residues (3,790 of which experience hydrogen exchange and 9,516 which do not exchange), our method achieves good performance. Specifically, we achieve an overall out-of-bag (OOB) error, an unbiased estimate of the test set error, of 20.3 percent. Using a randomly selected test data set consisting of 500 residues experiencing hydrogen exchange and 500 which do not, our method achieves an accuracy of 0.79, a recall of 0.74, a precision of 0.82, and an F1 score of 0.78.

Deep learning methods for protein torsion angle prediction.

PubMed

Li, Haiou; Hou, Jie; Adhikari, Badri; Lyu, Qiang; Cheng, Jianlin

2017-09-18

Deep learning is one of the most powerful machine learning methods that has achieved the state-of-the-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition. In this work, we developed deep learning methods to improve the prediction of torsion (dihedral) angles of proteins. We design four different deep learning architectures to predict protein torsion angles. The architectures including deep neural network (DNN) and deep restricted Boltzmann machine (DRBN), deep recurrent neural network (DRNN) and deep recurrent restricted Boltzmann machine (DReRBM) since the protein torsion angle prediction is a sequence related problem. In addition to existing protein features, two new features (predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments) are used as input to each of the four deep learning architectures to predict phi and psi angles of protein backbone. The mean absolute error (MAE) of phi and psi angles predicted by DRNN, DReRBM, DRBM and DNN is about 20-21° and 29-30° on an independent dataset. The MAE of phi angle is comparable to the existing methods, but the MAE of psi angle is 29°, 2° lower than the existing methods. On the latest CASP12 targets, our methods also achieved the performance better than or comparable to a state-of-the art method. Our experiment demonstrates that deep learning is a valuable method for predicting protein torsion angles. The deep recurrent network architecture performs slightly better than deep feed-forward architecture, and the predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments are useful features for improving prediction accuracy.

Optimization of processing parameters for the preparation of phytosterol microemulsions by the solvent displacement method.

PubMed

Leong, Wai Fun; Che Man, Yaakob B; Lai, Oi Ming; Long, Kamariah; Misran, Misni; Tan, Chin Ping

2009-09-23

The purpose of this study was to optimize the parameters involved in the production of water-soluble phytosterol microemulsions for use in the food industry. In this study, response surface methodology (RSM) was employed to model and optimize four of the processing parameters, namely, the number of cycles of high-pressure homogenization (1-9 cycles), the pressure used for high-pressure homogenization (100-500 bar), the evaporation temperature (30-70 degrees C), and the concentration ratio of microemulsions (1-5). All responses-particle size (PS), polydispersity index (PDI), and percent ethanol residual (%ER)-were well fit by a reduced cubic model obtained by multiple regression after manual elimination. The coefficient of determination (R(2)) and absolute average deviation (AAD) value for PS, PDI, and %ER were 0.9628 and 0.5398%, 0.9953 and 0.7077%, and 0.9989 and 1.0457%, respectively. The optimized processing parameters were 4.88 (approximately 5) homogenization cycles, homogenization pressure of 400 bar, evaporation temperature of 44.5 degrees C, and concentration ratio of microemulsions of 2.34 cycles (approximately 2 cycles) of high-pressure homogenization. The corresponding responses for the optimized preparation condition were a minimal particle size of 328 nm, minimal polydispersity index of 0.159, and <0.1% of ethanol residual. The chi-square test verified the model, whereby the experimental values of PS, PDI, and %ER agreed with the predicted values at a 0.05 level of significance.

Trp-cage: folding free energy landscape in explicit water.

PubMed

Zhou, Ruhong

2003-11-11

Trp-cage is a 20-residue miniprotein, which is believed to be the fastest folder known so far. In this study, the folding free energy landscape of Trp-cage has been explored in explicit solvent by using an OPLSAA force field with periodic boundary condition. A highly parallel replica exchange molecular dynamics method is used for the conformation space sampling, with the help of a recently developed efficient molecular dynamics algorithm P3ME/RESPA (particle-particle particle-mesh Ewald/reference system propagator algorithm). A two-step folding mechanism is proposed that involves an intermediate state where two correctly formed partial hydrophobic cores are separated by an essential salt-bridge between residues Asp-9 and Arg-16 near the center of the peptide. This metastable intermediate state provides an explanation for the superfast folding process. The free energy landscape is found to be rugged at low temperatures, and then becomes smooth and funnel-like above 340 K. The lowest free energy structure at 300 K is only 1.50 A Calpha-RMSD (Calpha-rms deviation) from the NMR structures. The simulated nuclear Overhauser effect pair distances are in excellent agreement with the raw NMR data. The temperature dependence of the Trp-cage population, however, is found to be significantly different from experiment, with a much higher melting transition temperature above 400 K (experimental 315 K), indicating that the current force fields, parameterized at room temperature, need to be improved to correctly predict the temperature dependence.

Trp-cage: Folding free energy landscape in explicit water

NASA Astrophysics Data System (ADS)

Zhou, Ruhong

2003-11-01

Trp-cage is a 20-residue miniprotein, which is believed to be the fastest folder known so far. In this study, the folding free energy landscape of Trp-cage has been explored in explicit solvent by using an OPLSAA force field with periodic boundary condition. A highly parallel replica exchange molecular dynamics method is used for the conformation space sampling, with the help of a recently developed efficient molecular dynamics algorithm P3ME/RESPA (particle-particle particle-mesh Ewald/reference system propagator algorithm). A two-step folding mechanism is proposed that involves an intermediate state where two correctly formed partial hydrophobic cores are separated by an essential salt-bridge between residues Asp-9 and Arg-16 near the center of the peptide. This metastable intermediate state provides an explanation for the superfast folding process. The free energy landscape is found to be rugged at low temperatures, and then becomes smooth and funnel-like above 340 K. The lowest free energy structure at 300 K is only 1.50 Å C-RMSD (C-rms deviation) from the NMR structures. The simulated nuclear Overhauser effect pair distances are in excellent agreement with the raw NMR data. The temperature dependence of the Trp-cage population, however, is found to be significantly different from experiment, with a much higher melting transition temperature above 400 K (experimental 315 K), indicating that the current force fields, parameterized at room temperature, need to be improved to correctly predict the temperature dependence.

Trp-cage: Folding free energy landscape in explicit water

PubMed Central

Zhou, Ruhong

2003-01-01

Trp-cage is a 20-residue miniprotein, which is believed to be the fastest folder known so far. In this study, the folding free energy landscape of Trp-cage has been explored in explicit solvent by using an OPLSAA force field with periodic boundary condition. A highly parallel replica exchange molecular dynamics method is used for the conformation space sampling, with the help of a recently developed efficient molecular dynamics algorithm P3ME/RESPA (particle–particle particle–mesh Ewald/reference system propagator algorithm). A two-step folding mechanism is proposed that involves an intermediate state where two correctly formed partial hydrophobic cores are separated by an essential salt-bridge between residues Asp-9 and Arg-16 near the center of the peptide. This metastable intermediate state provides an explanation for the superfast folding process. The free energy landscape is found to be rugged at low temperatures, and then becomes smooth and funnel-like above 340 K. The lowest free energy structure at 300 K is only 1.50 Å Cα-RMSD (Cα-rms deviation) from the NMR structures. The simulated nuclear Overhauser effect pair distances are in excellent agreement with the raw NMR data. The temperature dependence of the Trp-cage population, however, is found to be significantly different from experiment, with a much higher melting transition temperature above 400 K (experimental 315 K), indicating that the current force fields, parameterized at room temperature, need to be improved to correctly predict the temperature dependence. PMID:14581616

Determination of etoxazole residues in fruits and vegetables by SPE clean-up and HPLC-DAD.

PubMed

Malhat, Farag; Badawy, Hany; Barakat, Dalia; Saber, Ayman

2013-01-01

A method for determination of etoxazole residues in apples, strawberries and green beans was developed and validated. The analyte was extracted with acetonitrile from foodstuff and a charcoal-celite cartridge was used for clean-up of raw extracts. Reversed phase high performance liquid chromatography with photodiode array detector (HPLC-DAD) was used for the determination and quantification of etoxazole residues in the studied samples. The calibration graphs of etoxazole in a solvent or three blank matrixes were linear within the tested intervals 0.01-2 mg L(-1), with correlation coefficient of determination >0.999. The combined solid phase extraction (SPE) clean-up and the chromatographic method steps were sensitive and reliable for simultaneous determination of etoxazole residues in the studied samples. The average recoveries of etoxazole in the tested foodstuffs were between 93.4 to 102% at spiking levels of 0.01, 0.10, and 0.50 mg kg(-1), with relative standard deviations ranging from 2.8 to 4.7%, in agreement with directives for method validation in residue analyses. The limit of detection (LOD) of the HPLC-DAD system was 100 pg. The limit of quantification of the entire method was 0.01 mg kg(-1).

Dissipation of Flonicamid in Honeysuckle and Its Transfer during Brewing Process.

PubMed

Wang, Yujie; Xue, Jian; Jin, Hongyu; Ma, Shuangcheng

2017-05-01

The dissipation of flonicamid in Honeysuckle and transfer pattern from Honeysuckle to its tea infusion were investigated. Flonicamid was applied on Honeysuckle crop at two dosages, 60 g of active gradient per hectare (g a.i. hm -2 ) and 180 g a.i. hm -2 (recommended and triple the recommended) in Fenqiu, Henan Province in 2015 and 2016. Gas Chromatography-Electron Capture Detector (GC-ECD) detection methods were developed for the analysis of flonicamid residues in honeysuckles and its infusion. The recoveries in both honeysuckles and its infusion ranged from 81.5 to 101.7% with relative standard deviations (RSDs) of 3.2-9.1%. The dissipations of flonicamid in Honeysuckle were found to follow the first order kinetics with half-life ranging between 2.8 and 3.2 d. After recommended dose pesticide application, contents of flonicamid residues were lower than theoretical maximum residue limit (tMRL). Flonicamid residues can easily transfer from Honeysuckle to its tea infusion and transfer rates of flonicamid decrease with the brewing temperature reduction or the brewing times increase. These results are helpful to establish maximum residue limit and develop guidance on the appropriate and secure use of flonicamid in Honeysuckle.

Dissipation and Residues of Pyrethrins in Leaf Lettuce under Greenhouse and Open Field Conditions.

PubMed

Pan, Lixiang; Feng, Xiaoxiao; Zhang, Hongyan

2017-07-21

Pyrethrins are nowadays widely used for prevention and control of insects in leaf lettuce. However, there is a concern about the pesticide residue in leaf lettuce. A reliable analytical method for determination of pyrethrins (pyrethrin-and П, cinerin І and П, and jasmolin І and П) in leaf lettuce was developed by using gas chromatography-mass spectrometry (GC-MS). Recoveries of pyrethrins in leaf lettuce at three spiking levels were 99.4-104.0% with relative standard deviations of 0.9-3.1% ( n = 5). Evaluation of dissipation and final residues of pyrethrins in leaf lettuce were determined at six different locations, including the open field, as well as under greenhouse conditions. The initial concentration of pyrethrins in greenhouse (0.57 mg/kg) was higher than in open field (0.25 mg/kg) and the half-life for pyrethrins disappearance in field lettuce (0.7 days) was less than that greenhouse lettuce (1.1 days). Factors such as rainfall, solar radiation, wind speed, and crop growth rate are likely to have caused these results. The final residue in leaf lettuce was far below the maximum residue limits (MRLs) (1 mg/kg established by the European Union (EU), Australia, Korea, Japan).

Morphology of residually stressed tubular tissues: Beyond the elastic multiplicative decomposition

NASA Astrophysics Data System (ADS)

Ciarletta, P.; Destrade, M.; Gower, A. L.; Taffetani, M.

2016-05-01

Many interesting shapes appearing in the biological world are formed by the onset of mechanical instability. In this work we consider how the build-up of residual stress can cause a solid to buckle. In all past studies a fictitious (virtual) stress-free state was required to calculate the residual stress. In contrast, we use a model which is simple and allows the prescription of any residual stress field. We specialize the analysis to an elastic tube subject to a two-dimensional residual stress, and find that incremental wrinkles can appear on its inner or its outer face, depending on the location of the highest value of the residual hoop stress. We further validate the predictions of the incremental theory with finite element simulations, which allow us to go beyond this threshold and predict the shape, number and amplitude of the resulting creases.

Conditional Entropy-Constrained Residual VQ with Application to Image Coding

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Chung, Wilson C.; Smith, Mark J. T.

1996-01-01

This paper introduces an extension of entropy-constrained residual vector quantization (VQ) where intervector dependencies are exploited. The method, which we call conditional entropy-constrained residual VQ, employs a high-order entropy conditioning strategy that captures local information in the neighboring vectors. When applied to coding images, the proposed method is shown to achieve better rate-distortion performance than that of entropy-constrained residual vector quantization with less computational complexity and lower memory requirements. Moreover, it can be designed to support progressive transmission in a natural way. It is also shown to outperform some of the best predictive and finite-state VQ techniques reported in the literature. This is due partly to the joint optimization between the residual vector quantizer and a high-order conditional entropy coder as well as the efficiency of the multistage residual VQ structure and the dynamic nature of the prediction.

High-Level Prediction Signals in a Low-Level Area of the Macaque Face-Processing Hierarchy.

PubMed

Schwiedrzik, Caspar M; Freiwald, Winrich A

2017-09-27

Theories like predictive coding propose that lower-order brain areas compare their inputs to predictions derived from higher-order representations and signal their deviation as a prediction error. Here, we investigate whether the macaque face-processing system, a three-level hierarchy in the ventral stream, employs such a coding strategy. We show that after statistical learning of specific face sequences, the lower-level face area ML computes the deviation of actual from predicted stimuli. But these signals do not reflect the tuning characteristic of ML. Rather, they exhibit identity specificity and view invariance, the tuning properties of higher-level face areas AL and AM. Thus, learning appears to endow lower-level areas with the capability to test predictions at a higher level of abstraction than what is afforded by the feedforward sweep. These results provide evidence for computational architectures like predictive coding and suggest a new quality of functional organization of information-processing hierarchies beyond pure feedforward schemes. Copyright © 2017 Elsevier Inc. All rights reserved.

Template CoMFA Generates Single 3D-QSAR Models that, for Twelve of Twelve Biological Targets, Predict All ChEMBL-Tabulated Affinities

PubMed Central

Cramer, Richard D.

2015-01-01

The possible applicability of the new template CoMFA methodology to the prediction of unknown biological affinities was explored. For twelve selected targets, all ChEMBL binding affinities were used as training and/or prediction sets, making these 3D-QSAR models the most structurally diverse and among the largest ever. For six of the targets, X-ray crystallographic structures provided the aligned templates required as input (BACE, cdk1, chk2, carbonic anhydrase-II, factor Xa, PTP1B). For all targets including the other six (hERG, cyp3A4 binding, endocrine receptor, COX2, D2, and GABAa), six modeling protocols applied to only three familiar ligands provided six alternate sets of aligned templates. The statistical qualities of the six or seven models thus resulting for each individual target were remarkably similar. Also, perhaps unexpectedly, the standard deviations of the errors of cross-validation predictions accompanying model derivations were indistinguishable from the standard deviations of the errors of truly prospective predictions. These standard deviations of prediction ranged from 0.70 to 1.14 log units and averaged 0.89 (8x in concentration units) over the twelve targets, representing an average reduction of almost 50% in uncertainty, compared to the null hypothesis of “predicting” an unknown affinity to be the average of known affinities. These errors of prediction are similar to those from Tanimoto coefficients of fragment occurrence frequencies, the predominant approach to side effect prediction, which template CoMFA can augment by identifying additional active structural classes, by improving Tanimoto-only predictions, by yielding quantitative predictions of potency, and by providing interpretable guidance for avoiding or enhancing any specific target response. PMID:26065424

Propeller aircraft interior noise model. II - Scale-model and flight-test comparisons

NASA Technical Reports Server (NTRS)

Willis, C. M.; Mayes, W. H.

1987-01-01

A program for predicting the sound levels inside propeller driven aircraft arising from sidewall transmission of airborne exterior noise is validated through comparisons of predictions with both scale-model test results and measurements obtained in flight tests on a turboprop aircraft. The program produced unbiased predictions for the case of the scale-model tests, with a standard deviation of errors of about 4 dB. For the case of the flight tests, the predictions revealed a bias of 2.62-4.28 dB (depending upon whether or not the data for the fourth harmonic were included) and the standard deviation of the errors ranged between 2.43 and 4.12 dB. The analytical model is shown to be capable of taking changes in the flight environment into account.

Resolution in partially accomodative esotropia during occlusion treatment for amblyopia.

PubMed

Koc, F; Ozal, H; Yasar, H; Firat, E

2006-03-01

To evaluate alignment changes in partially accommodative esotropia during occlusion treatment for amblyopia. Changes at the deviation angles of 63 partially accommodative esotropia patients, who had occlusion treatment for amblyopia, were evaluated retrospectively. Mean deviation angle at the start of therapy without glasses was 45 PD (10-90 PD) and became 27 PD (5-70 PD) after at least 2 months with glasses. During 12 (2-36) months of occlusion period, mean manifest deviation angle with glasses decreased to 11 PD (0-50) (P < 0.001) and amblyopia resolved in 71.5% of the cases. After termination of amblyopia treatment 24 (38%) cases had surgery for the residual deviation but if we had planned surgery before amblyopia treatment, 81% of the patients would have had surgery. Should amblyopia be treated initially or should we operate first in patients with strabismus and amblyopia together? Our research suggests that we should not hurry to operate in high hypermetropic partially accommodative cases, which have amblyopia and a long-term history of strabismus. Initial amblyopia treatment in these cases allows time for resolution of the nonaccomodative component in strabismus and can significantly decrease the necessity for surgery.

Gradient Magnitude Similarity Deviation: A Highly Efficient Perceptual Image Quality Index.

PubMed

Xue, Wufeng; Zhang, Lei; Mou, Xuanqin; Bovik, Alan C

2014-02-01

It is an important task to faithfully evaluate the perceptual quality of output images in many applications, such as image compression, image restoration, and multimedia streaming. A good image quality assessment (IQA) model should not only deliver high quality prediction accuracy, but also be computationally efficient. The efficiency of IQA metrics is becoming particularly important due to the increasing proliferation of high-volume visual data in high-speed networks. We present a new effective and efficient IQA model, called gradient magnitude similarity deviation (GMSD). The image gradients are sensitive to image distortions, while different local structures in a distorted image suffer different degrees of degradations. This motivates us to explore the use of global variation of gradient based local quality map for overall image quality prediction. We find that the pixel-wise gradient magnitude similarity (GMS) between the reference and distorted images combined with a novel pooling strategy-the standard deviation of the GMS map-can predict accurately perceptual image quality. The resulting GMSD algorithm is much faster than most state-of-the-art IQA methods, and delivers highly competitive prediction accuracy. MATLAB source code of GMSD can be downloaded at http://www4.comp.polyu.edu.hk/~cslzhang/IQA/GMSD/GMSD.htm.

Validating a Model for Welding Induced Residual Stress Using High-Energy X-ray Diffraction

NASA Astrophysics Data System (ADS)

Mach, J. C.; Budrow, C. J.; Pagan, D. C.; Ruff, J. P. C.; Park, J.-S.; Okasinski, J.; Beaudoin, A. J.; Miller, M. P.

2017-05-01

Integrated computational materials engineering (ICME) provides a pathway to advance performance in structures through the use of physically-based models to better understand how manufacturing processes influence product performance. As one particular challenge, consider that residual stresses induced in fabrication are pervasive and directly impact the life of structures. For ICME to be an effective strategy, it is essential that predictive capability be developed in conjunction with critical experiments. In the present work, simulation results from a multi-physics model for gas metal arc welding are evaluated through x-ray diffraction using synchrotron radiation. A test component was designed with intent to develop significant gradients in residual stress, be representative of real-world engineering application, yet remain tractable for finely spaced strain measurements with positioning equipment available at synchrotron facilities. The experimental validation lends confidence to model predictions, facilitating the explicit consideration of residual stress distribution in prediction of fatigue life.

Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network.

PubMed

Lyons, James; Dehzangi, Abdollah; Heffernan, Rhys; Sharma, Alok; Paliwal, Kuldip; Sattar, Abdul; Zhou, Yaoqi; Yang, Yuedong

2014-10-30

Because a nearly constant distance between two neighbouring Cα atoms, local backbone structure of proteins can be represented accurately by the angle between C(αi-1)-C(αi)-C(αi+1) (θ) and a dihedral angle rotated about the C(αi)-C(αi+1) bond (τ). θ and τ angles, as the representative of structural properties of three to four amino-acid residues, offer a description of backbone conformations that is complementary to φ and ψ angles (single residue) and secondary structures (>3 residues). Here, we report the first machine-learning technique for sequence-based prediction of θ and τ angles. Predicted angles based on an independent test have a mean absolute error of 9° for θ and 34° for τ with a distribution on the θ-τ plane close to that of native values. The average root-mean-square distance of 10-residue fragment structures constructed from predicted θ and τ angles is only 1.9Å from their corresponding native structures. Predicted θ and τ angles are expected to be complementary to predicted ϕ and ψ angles and secondary structures for using in model validation and template-based as well as template-free structure prediction. The deep neural network learning technique is available as an on-line server called Structural Property prediction with Integrated DEep neuRal network (SPIDER) at http://sparks-lab.org. Copyright © 2014 Wiley Periodicals, Inc.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lewis, John R.; Brooks, Dusty Marie

In pressurized water reactors, the prevention, detection, and repair of cracks within dissimilar metal welds is essential to ensure proper plant functionality and safety. Weld residual stresses, which are difficult to model and cannot be directly measured, contribute to the formation and growth of cracks due to primary water stress corrosion cracking. Additionally, the uncertainty in weld residual stress measurements and modeling predictions is not well understood, further complicating the prediction of crack evolution. The purpose of this document is to develop methodology to quantify the uncertainty associated with weld residual stress that can be applied to modeling predictions andmore » experimental measurements. Ultimately, the results can be used to assess the current state of uncertainty and to build confidence in both modeling and experimental procedures. The methodology consists of statistically modeling the variation in the weld residual stress profiles using functional data analysis techniques. Uncertainty is quantified using statistical bounds (e.g. confidence and tolerance bounds) constructed with a semi-parametric bootstrap procedure. Such bounds describe the range in which quantities of interest, such as means, are expected to lie as evidenced by the data. The methodology is extended to provide direct comparisons between experimental measurements and modeling predictions by constructing statistical confidence bounds for the average difference between the two quantities. The statistical bounds on the average difference can be used to assess the level of agreement between measurements and predictions. The methodology is applied to experimental measurements of residual stress obtained using two strain relief measurement methods and predictions from seven finite element models developed by different organizations during a round robin study.« less

Modeling the Zeeman effect in high altitude SSMIS channels for numerical weather prediction profiles: comparing a fast model and a line-by-line model

NASA Astrophysics Data System (ADS)

Larsson, R.; Milz, M.; Rayer, P.; Saunders, R.; Bell, W.; Booton, A.; Buehler, S. A.; Eriksson, P.; John, V.

2015-10-01

We present a comparison of a reference and a fast radiative transfer model using numerical weather prediction profiles for the Zeeman-affected high altitude Special Sensor Microwave Imager/Sounder channels 19-22. We find that the models agree well for channels 21 and 22 compared to the channels' system noise temperatures (1.9 and 1.3 K, respectively) and the expected profile errors at the affected altitudes (estimated to be around 5 K). For channel 22 there is a 0.5 K average difference between the models, with a standard deviation of 0.24 K for the full set of atmospheric profiles. Same channel, there is 1.2 K in average between the fast model and the sensor measurement, with 1.4 K standard deviation. For channel 21 there is a 0.9 K average difference between the models, with a standard deviation of 0.56 K. Same channel, there is 1.3 K in average between the fast model and the sensor measurement, with 2.4 K standard deviation. We consider the relatively small model differences as a validation of the fast Zeeman effect scheme for these channels. Both channels 19 and 20 have smaller average differences between the models (at below 0.2 K) and smaller standard deviations (at below 0.4 K) when both models use a two-dimensional magnetic field profile. However, when the reference model is switched to using a full three-dimensional magnetic field profile, the standard deviation to the fast model is increased to almost 2 K due to viewing geometry dependencies causing up to ± 7 K differences near the equator. The average differences between the two models remain small despite changing magnetic field configurations. We are unable to compare channels 19 and 20 to sensor measurements due to limited altitude range of the numerical weather prediction profiles. We recommended that numerical weather prediction software using the fast model takes the available fast Zeeman scheme into account for data assimilation of the affected sensor channels to better constrain the upper atmospheric temperatures.

Modeling the Zeeman effect in high-altitude SSMIS channels for numerical weather prediction profiles: comparing a fast model and a line-by-line model

NASA Astrophysics Data System (ADS)

Larsson, Richard; Milz, Mathias; Rayer, Peter; Saunders, Roger; Bell, William; Booton, Anna; Buehler, Stefan A.; Eriksson, Patrick; John, Viju O.

2016-03-01

We present a comparison of a reference and a fast radiative transfer model using numerical weather prediction profiles for the Zeeman-affected high-altitude Special Sensor Microwave Imager/Sounder channels 19-22. We find that the models agree well for channels 21 and 22 compared to the channels' system noise temperatures (1.9 and 1.3 K, respectively) and the expected profile errors at the affected altitudes (estimated to be around 5 K). For channel 22 there is a 0.5 K average difference between the models, with a standard deviation of 0.24 K for the full set of atmospheric profiles. Concerning the same channel, there is 1.2 K on average between the fast model and the sensor measurement, with 1.4 K standard deviation. For channel 21 there is a 0.9 K average difference between the models, with a standard deviation of 0.56 K. Regarding the same channel, there is 1.3 K on average between the fast model and the sensor measurement, with 2.4 K standard deviation. We consider the relatively small model differences as a validation of the fast Zeeman effect scheme for these channels. Both channels 19 and 20 have smaller average differences between the models (at below 0.2 K) and smaller standard deviations (at below 0.4 K) when both models use a two-dimensional magnetic field profile. However, when the reference model is switched to using a full three-dimensional magnetic field profile, the standard deviation to the fast model is increased to almost 2 K due to viewing geometry dependencies, causing up to ±7 K differences near the equator. The average differences between the two models remain small despite changing magnetic field configurations. We are unable to compare channels 19 and 20 to sensor measurements due to limited altitude range of the numerical weather prediction profiles. We recommended that numerical weather prediction software using the fast model takes the available fast Zeeman scheme into account for data assimilation of the affected sensor channels to better constrain the upper atmospheric temperatures.

Predictors of Residual Disease after Unplanned Excision of Soft Tissue Sarcomas

PubMed Central

Gingrich, Alicia A.; Elias, Alexandra; Michael Lee, Chia-Yuan; Nakache, Yves-Paul N.; Li, Chin-Shang; Shah, Dhruvil R.; Boutin, Robert D.; Canter, Robert J.

2016-01-01

Background Unplanned excision of soft tissue sarcomas (STS) is an important quality of care issue given the morbidity related to tumor bed excision. Since not all patients harbor residual disease at the time of re-excision, we sought to determine predictors of residual STS following unplanned excision. Methods We identified 76 patients from a prospective database (1/1/2008 – 9/30/2014) who received a diagnosis of primary STS following unplanned excision on the trunk or extremities. We used univariable and multivariable analyses to evaluate predictors of residual STS as the primary endpoint. We calculated the sensitivity/specificity and accuracy of interval magnetic resonance imaging (MRI) to predict residual sarcoma at re-excision. Results Mean age was 52 years, and 63.2% were male. 50% had fragmented unplanned excision. Among patients undergoing re-excision, residual STS was identified in 70%. On univariable analysis, MRI showing gross disease and fragmented excision were significant predictors of residual STS (OR 10.59, 95% CI 2.14–52.49, P=0.004 and OR 3.61, 95% CI 1.09–11.94, P=0.035, respectively). On multivariable analysis, tumor size predicted distant recurrence and overall survival. When we combined equivocal and positive MRI, the sensitivity and specificity of MRI for predicting residual STS were 86.7% (95% CI 73.2–95.0%) and 57.9% (95% CI 33.5–79.8%), with an overall accuracy of 78.1% (95% CI 66.0–87.5%). Conclusions 70% of patients undergoing repeat excision after unplanned excision of STS harbor residual sarcoma. Although interval MRI and fragmented excision appear to be the most significant predictors of residual STS, the accuracy of MRI remains modest, especially given the incidence of equivocal MRI. PMID:27993214

Effect of stress on energy flux deviation of ultrasonic waves in GR/EP composites

NASA Technical Reports Server (NTRS)

Prosser, William H.; Kriz, R. D.; Fitting, Dale W.

1990-01-01

Ultrasonic waves suffer energy flux deviation in graphite/epoxy because of the large anisotropy. The angle of deviation is a function of the elastic coefficients. For nonlinear solids, these coefficients and thus the angle of deviation is a function of stress. Acoustoelastic theory was used to model the effect of stress on flux deviation for unidirectional T300/5208 using previously measured elastic coefficients. Computations were made for uniaxial stress along the x3 axis (fiber axis) and the x1 for waves propagating in the x1x3 plane. These results predict a shift as large as three degrees for the quasi-transverse wave. The shift in energy flux offers a new nondestructive technique of evaluating stress in composites.

Intensity stabilisation of optical pulse sequences for coherent control of laser-driven qubits

NASA Astrophysics Data System (ADS)

Thom, Joseph; Yuen, Ben; Wilpers, Guido; Riis, Erling; Sinclair, Alastair G.

2018-05-01

We demonstrate a system for intensity stabilisation of optical pulse sequences used in laser-driven quantum control of trapped ions. Intensity instability is minimised by active stabilisation of the power (over a dynamic range of > 104) and position of the focused beam at the ion. The fractional Allan deviations in power were found to be <2.2 × 10^{-4} for averaging times from 1 to 16,384 s. Over similar times, the absolute Allan deviation of the beam position is <0.1 μm for a 45 {μ }m beam diameter. Using these residual power and position instabilities, we estimate the associated contributions to infidelity in example qubit logic gates to be below 10^{-6} per gate.

A two-component rain model for the prediction of attenuation and diversity improvement

NASA Technical Reports Server (NTRS)

Crane, R. K.

1982-01-01

A new model was developed to predict attenuation statistics for a single Earth-satellite or terrestrial propagation path. The model was extended to provide predictions of the joint occurrences of specified or higher attenuation values on two closely spaced Earth-satellite paths. The joint statistics provide the information required to obtain diversity gain or diversity advantage estimates. The new model is meteorologically based. It was tested against available Earth-satellite beacon observations and terrestrial path measurements. The model employs the rain climate region descriptions of the Global rain model. The rms deviation between the predicted and observed attenuation values for the terrestrial path data was 35 percent, a result consistent with the expectations of the Global model when the rain rate distribution for the path is not used in the calculation. Within the United States the rms deviation between measurement and prediction was 36 percent but worldwide it was 79 percent.

Calibration of strong motion models for Central America region and its use in seismic hazard assessment

NASA Astrophysics Data System (ADS)

Climent, A.; Benito, M. B.; Piedra, R.; Lindholm, C.; Gaspar-Escribano, J.

2013-05-01

We present the results of a study aimed at choosing the more suitable strong-motion models for seismic hazard analysis in the Central America (CA) Region. After a careful revision of the state of the art, different models developed for subduction and volcanic crustal zones, in tectonic environment similar to those of CA, were selected. These models were calibrated with accelerograms recorded in Costa Rica, Nicaragua and El Salvador. The peak ground acceleration PGA and Spectral Acceleration SA (T) derived from the records were compared with the ones predicted by the models in similar conditions of magnitude, distance and soil. The type of magnitude (Ms, Mb, MW), distance (Rhyp, Rrup, etc) and ground motion parameter (maximum horizontal component, geometrical mean, etc ) was taken into account in the comparison with the real data. As results of the analysis, the models which present a best fit with the local data were identified. These models have been applied for carrying out seismic hazard analysis in the region, in the frame of the RESIS II project financed by the Norwegian Foreign Department and also by the Spanish project SISMOCAES. The methodology followed is based on the direct comparison between PGA and SA 5 % damped response values extracted from actual records with the corresponding acceleration values predicted by the selected ground-motion models for similar magnitude, distance and soil conditions. Residuals between observed and predicted values for PGA, and SA (1sec) are calculated and plotted as a function of distance and magnitude, analyzing their deviation from the mean value. Besides and most important, a statistical analysis of the normalized residuals was carry out using the criteria proposed by Scherbaum et al. (2004), which consists in categorizing ground motion models based in a likelihood parameter that reflects the goodness-of-fit of the median values as well as the shape of the underlying distribution of ground motion residuals. Considering the results of the both analysis the conclusions can be drawn in the following paragraphs. Analyses of residuals show that in some cases the best adjustments of PGA and SA values do not always favor the same equation. Consequently, the following equations that present reasonable adjustments for both parameters are finally selected: Schmidt (2010) and Zhao et al (2006) for shallow crustal sources; Schmidt (2010), Zhao et al (2006), Youngs et al. (1997) and Lin & Lee (2008) for subduction interface and Schmidt (2010), Youngs et al (1997), Zhao et al (2006) and Garcia et al (2005) for inslab subduction sources. Finally, to improve the development of proper models of attenuation of the region, it is recommended to the governmental and private institutions, to support the implementation of permanent strong ground motion networks in all Central America countries, especially in Guatemala, Honduras, Nicaragua and Panama, including free field stations. In case of Costa Rica and El Salvador to strengthen the networks that already they operate.

Revision of earthquake hypocenter locations in GEOFON bulletin data using global source-specific station terms technique

NASA Astrophysics Data System (ADS)

Nooshiri, N.; Saul, J.; Heimann, S.; Tilmann, F. J.; Dahm, T.

2015-12-01

The use of a 1D velocity model for seismic event location is often associated with significant travel-time residuals. Particularly for regional stations in subduction zones, where the velocity structure strongly deviates from the assumed 1D model, residuals of up to ±10 seconds are observed even for clear arrivals, which leads to strongly biased locations. In fact, due to mostly regional travel-time anomalies, arrival times at regional stations do not match the location obtained with teleseismic picks, and vice versa. If the earthquake is weak and only recorded regionally, or if fast locations based on regional stations are needed, the location may be far off the corresponding teleseismic location. In this case, implementation of travel-time corrections may leads to a reduction of the travel-time residuals at regional stations and, in consequence, significantly improve the relative location accuracy. Here, we have extended the source-specific station terms (SSST) technique to regional and teleseismic distances and adopted the algorithm for probabilistic, non-linear, global-search earthquake location. The method has been applied to specific test regions using P and pP phases from the GEOFON bulletin data for all available station networks. By using this method, a set of timing corrections has been calculated for each station varying as a function of source position. In this way, an attempt is made to correct for the systematic errors, introduced by limitations and inaccuracies in the assumed velocity structure, without solving for a new earth model itself. In this presentation, we draw on examples of the application of this global SSST technique to relocate earthquakes from the Tonga-Fiji subduction zone and from the Chilean margin. Our results have been showing a considerable decrease of the root-mean-square (RMS) residual in earthquake location final catalogs, a major reduction of the median absolute deviation (MAD) of the travel-time residuals at regional stations and sharper images of the seismicity compared to the initial locations.

Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modelling heteroscedastic residual errors

NASA Astrophysics Data System (ADS)

David, McInerney; Mark, Thyer; Dmitri, Kavetski; George, Kuczera

2017-04-01

This study provides guidance to hydrological researchers which enables them to provide probabilistic predictions of daily streamflow with the best reliability and precision for different catchment types (e.g. high/low degree of ephemerality). Reliable and precise probabilistic prediction of daily catchment-scale streamflow requires statistical characterization of residual errors of hydrological models. It is commonly known that hydrological model residual errors are heteroscedastic, i.e. there is a pattern of larger errors in higher streamflow predictions. Although multiple approaches exist for representing this heteroscedasticity, few studies have undertaken a comprehensive evaluation and comparison of these approaches. This study fills this research gap by evaluating 8 common residual error schemes, including standard and weighted least squares, the Box-Cox transformation (with fixed and calibrated power parameter, lambda) and the log-sinh transformation. Case studies include 17 perennial and 6 ephemeral catchments in Australia and USA, and two lumped hydrological models. We find the choice of heteroscedastic error modelling approach significantly impacts on predictive performance, though no single scheme simultaneously optimizes all performance metrics. The set of Pareto optimal schemes, reflecting performance trade-offs, comprises Box-Cox schemes with lambda of 0.2 and 0.5, and the log scheme (lambda=0, perennial catchments only). These schemes significantly outperform even the average-performing remaining schemes (e.g., across ephemeral catchments, median precision tightens from 105% to 40% of observed streamflow, and median biases decrease from 25% to 4%). Theoretical interpretations of empirical results highlight the importance of capturing the skew/kurtosis of raw residuals and reproducing zero flows. Recommendations for researchers and practitioners seeking robust residual error schemes for practical work are provided.

Residue contacts predicted by evolutionary covariance extend the application of ab initio molecular replacement to larger and more challenging protein folds.

PubMed

Simkovic, Felix; Thomas, Jens M H; Keegan, Ronan M; Winn, Martyn D; Mayans, Olga; Rigden, Daniel J

2016-07-01

For many protein families, the deluge of new sequence information together with new statistical protocols now allow the accurate prediction of contacting residues from sequence information alone. This offers the possibility of more accurate ab initio (non-homology-based) structure prediction. Such models can be used in structure solution by molecular replacement (MR) where the target fold is novel or is only distantly related to known structures. Here, AMPLE, an MR pipeline that assembles search-model ensembles from ab initio structure predictions ('decoys'), is employed to assess the value of contact-assisted ab initio models to the crystallographer. It is demonstrated that evolutionary covariance-derived residue-residue contact predictions improve the quality of ab initio models and, consequently, the success rate of MR using search models derived from them. For targets containing β-structure, decoy quality and MR performance were further improved by the use of a β-strand contact-filtering protocol. Such contact-guided decoys achieved 14 structure solutions from 21 attempted protein targets, compared with nine for simple Rosetta decoys. Previously encountered limitations were superseded in two key respects. Firstly, much larger targets of up to 221 residues in length were solved, which is far larger than the previously benchmarked threshold of 120 residues. Secondly, contact-guided decoys significantly improved success with β-sheet-rich proteins. Overall, the improved performance of contact-guided decoys suggests that MR is now applicable to a significantly wider range of protein targets than were previously tractable, and points to a direct benefit to structural biology from the recent remarkable advances in sequencing.

Detection of minimal residual disease following induction immunochemotherapy predicts progression free survival in mantle cell lymphoma: final results of CALGB 59909

PubMed Central

Liu, Hongtao; Johnson, Jeffrey L.; Koval, Greg; Malnassy, Greg; Sher, Dorie; Damon, Lloyd E.; Hsi, Eric D.; Bucci, Donna Marie; Linker, Charles A.; Cheson, Bruce D.; Stock, Wendy

2012-01-01

Background In the present study, the prognostic impact of minimal residual disease during treatment on time to progression and overall survival was analyzed prospectively in patients with mantle cell lymphoma treated on the Cancer and Leukemia Group B 59909 clinical trial. Design and Methods Peripheral blood and bone marrow samples were collected during different phases of the Cancer and Leukemia Group B 59909 study for minimal residual disease analysis. Minimal residual disease status was determined by quantitative polymerase chain reaction of IgH and/or BCL-1/JH gene rearrangement. Correlation of minimal residual disease status with time to progression and overall survival was determined. In multivariable analysis, minimal residual disease, and other risk factors were correlated with time to progression. Results Thirty-nine patients had evaluable, sequential peripheral blood and bone marrow samples for minimal residual disease analysis. Using peripheral blood monitoring, 18 of 39 (46%) achieved molecular remission following induction therapy. The molecular remission rate increased from 46 to 74% after one course of intensification therapy. Twelve of 21 minimal residual disease positive patients (57%) progressed within three years of follow up compared to 4 of 18 (22%) molecular remission patients (P=0.049). Detection of minimal residual disease following induction therapy predicted disease progression with a hazard ratio of 3.7 (P=0.016). The 3-year probability of time to progression among those who were in molecular remission after induction chemotherapy was 82% compared to 48% in patients with detectable minimal residual disease. The prediction of time to progression by post-induction minimal residual disease was independent of other prognostic factors in multivariable analysis. Conclusions Detection of minimal residual disease following induction immunochemotherapy was an independent predictor of time to progression following immunochemotherapy and autologous stem cell transplantation for mantle cell lymphoma. The clinical trial was registered at ClinicalTrials.gov: NCT00020943. PMID:22102709

All-atom 3D structure prediction of transmembrane β-barrel proteins from sequences.

PubMed

Hayat, Sikander; Sander, Chris; Marks, Debora S; Elofsson, Arne

2015-04-28

Transmembrane β-barrels (TMBs) carry out major functions in substrate transport and protein biogenesis but experimental determination of their 3D structure is challenging. Encouraged by successful de novo 3D structure prediction of globular and α-helical membrane proteins from sequence alignments alone, we developed an approach to predict the 3D structure of TMBs. The approach combines the maximum-entropy evolutionary coupling method for predicting residue contacts (EVfold) with a machine-learning approach (boctopus2) for predicting β-strands in the barrel. In a blinded test for 19 TMB proteins of known structure that have a sufficient number of diverse homologous sequences available, this combined method (EVfold_bb) predicts hydrogen-bonded residue pairs between adjacent β-strands at an accuracy of ∼70%. This accuracy is sufficient for the generation of all-atom 3D models. In the transmembrane barrel region, the average 3D structure accuracy [template-modeling (TM) score] of top-ranked models is 0.54 (ranging from 0.36 to 0.85), with a higher (44%) number of residue pairs in correct strand-strand registration than in earlier methods (18%). Although the nonbarrel regions are predicted less accurately overall, the evolutionary couplings identify some highly constrained loop residues and, for FecA protein, the barrel including the structure of a plug domain can be accurately modeled (TM score = 0.68). Lower prediction accuracy tends to be associated with insufficient sequence information and we therefore expect increasing numbers of β-barrel families to become accessible to accurate 3D structure prediction as the number of available sequences increases.

Thermodynamic Predictions vs. Measured Fluid Chemistry: Lessons from Low-Temperature, Serpentinizing Fluids

NASA Astrophysics Data System (ADS)

Leong, J. M.; Howells, A. H.; Robinson, K. J.; Shock, E. L.

2018-05-01

A combination of reaction-path, mixing, and sensitivity calculations was used to reconcile deviations between thermodynamic predictions and actual measurements of low-temperature serpentinizing fluid chemistry.

Numerical Prediction of Residual Stresses in an Autofrettaged Tube of Compressible Material

DTIC Science & Technology

1981-05-01

2 LEVEL TECHNICAL REPORT ARLCB-TR- 81019 NUMERICAL PREDICTION OF RESIDUAL STRESSES IN AN AUTOFRETTAGED TUBE OF COMPRESSIBLE MATERIAL 7 P. C. T. Chen...DOCUMENTATION PAGE READ INSTRUCTIONS BEFORE COMPLETING FORM I. REPORT NUMBER 2. GOVT ACCESSION NO. 3. RECIPIENT’S CATALOG NUMBER ARLCB-TR- 81019 At

SODa: an Mn/Fe superoxide dismutase prediction and design server.

PubMed

Kwasigroch, Jean Marc; Wintjens, René; Gilis, Dimitri; Rooman, Marianne

2008-06-02

Superoxide dismutases (SODs) are ubiquitous metalloenzymes that play an important role in the defense of aerobic organisms against oxidative stress, by converting reactive oxygen species into nontoxic molecules. We focus here on the SOD family that uses Fe or Mn as cofactor. The SODa webtool http://babylone.ulb.ac.be/soda predicts if a target sequence corresponds to an Fe/Mn SOD. If so, it predicts the metal ion specificity (Fe, Mn or cambialistic) and the oligomerization mode (dimer or tetramer) of the target. In addition, SODa proposes a list of residue substitutions likely to improve the predicted preferences for the metal cofactor and oligomerization mode. The method is based on residue fingerprints, consisting of residues conserved in SOD sequences or typical of SOD subgroups, and of interaction fingerprints, containing residue pairs that are in contact in SOD structures. SODa is shown to outperform and to be more discriminative than traditional techniques based on pairwise sequence alignments. Moreover, the fact that it proposes selected mutations makes it a valuable tool for rational protein design.

High variation subarctic topsoil pollutant concentration prediction using neural network residual kriging

NASA Astrophysics Data System (ADS)

Sergeev, A. P.; Tarasov, D. A.; Buevich, A. G.; Subbotina, I. E.; Shichkin, A. V.; Sergeeva, M. V.; Lvova, O. A.

2017-06-01

The work deals with the application of neural networks residual kriging (NNRK) to the spatial prediction of the abnormally distributed soil pollutant (Cr). It is known that combination of geostatistical interpolation approaches (kriging) and neural networks leads to significantly better prediction accuracy and productivity. Generalized regression neural networks and multilayer perceptrons are classes of neural networks widely used for the continuous function mapping. Each network has its own pros and cons; however both demonstrated fast training and good mapping possibilities. In the work, we examined and compared two combined techniques: generalized regression neural network residual kriging (GRNNRK) and multilayer perceptron residual kriging (MLPRK). The case study is based on the real data sets on surface contamination by chromium at a particular location of the subarctic Novy Urengoy, Russia, obtained during the previously conducted screening. The proposed models have been built, implemented and validated using ArcGIS and MATLAB environments. The networks structures have been chosen during a computer simulation based on the minimization of the RMSE. MLRPK showed the best predictive accuracy comparing to the geostatistical approach (kriging) and even to GRNNRK.

ANALYTICAL METHOD FOR THE DETERMINATION OF BORON IN PURIFIED AND NATURAL WATERS (EXCLUDING SEA-WATER)

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

1964-01-01

An aliquot of the sample is evaporated to dryness with sodium hydroxide, and the boron is determined absorptiometrically on the residue as the curcumin complex. The method is applicable to water containing 0.065 to 0.05 ppm boron. The standard deviation obtained from 12 recoveries at the 0.25 mu g level was 0.014 mu g. (auth)

Characterization of Residual Stress Effects on Fatigue Crack Growth of a Friction Stir Welded Aluminum Alloy

NASA Technical Reports Server (NTRS)

Newman, John A.; Smith, Stephen W.; Seshadri, Banavara R.; James, Mark A.; Brazill, Richard L.; Schultz, Robert W.; Donald, J. Keith; Blair, Amy

2015-01-01

An on-line compliance-based method to account for residual stress effects in stress-intensity factor and fatigue crack growth property determinations has been evaluated. Residual stress intensity factor results determined from specimens containing friction stir weld induced residual stresses are presented, and the on-line method results were found to be in excellent agreement with residual stress-intensity factor data obtained using the cut compliance method. Variable stress-intensity factor tests were designed to demonstrate that a simple superposition model, summing the applied stress-intensity factor with the residual stress-intensity factor, can be used to determine the total crack-tip stress-intensity factor. Finite element, VCCT (virtual crack closure technique), and J-integral analysis methods have been used to characterize weld-induced residual stress using thermal expansion/contraction in the form of an equivalent delta T (change in local temperature during welding) to simulate the welding process. This equivalent delta T was established and applied to analyze different specimen configurations to predict residual stress distributions and associated residual stress-intensity factor values. The predictions were found to agree well with experimental results obtained using the crack- and cut-compliance methods.

The effect of the environment on the structure, morphology and star formation history of intermediate-redshift galaxies

NASA Astrophysics Data System (ADS)

Kelkar, Kshitija; Gray, Meghan E.; Aragón-Salamanca, Alfonso; Rudnick, Gregory; Milvang-Jensen, Bo; Jablonka, Pascale; Schrabback, Tim

2017-08-01

With the aim of understanding the effect of the environment on the star formation history and morphological transformation of galaxies, we present a detailed analysis of the colour, morphology and internal structure of cluster and field galaxies at 0.4 ≤ z ≤ 0.8. We use the Hubble Space Telescope data for over 500 galaxies from the ESO Distant Cluster Survey to quantify how the galaxies' light distribution deviate from symmetric smooth profiles. We visually inspect the galaxies' images to identify the likely causes for such deviations. We find that the residual flux fraction (RFF), which measures the fractional contribution to the galaxy light of the residuals left after subtracting a symmetric and smooth model, is very sensitive to the degree of structural disturbance but not the causes of such disturbance. On the other hand, the asymmetry of these residuals (Ares) is more sensitive to the causes of the disturbance, with merging galaxies having the highest values of Ares. Using these quantitative parameters, we find that, at a fixed morphology, cluster and field galaxies show statistically similar degrees of disturbance. However, there is a higher fraction of symmetric and passive spirals in the cluster than in the field. These galaxies have smoother light distributions than their star-forming counterparts. We also find that while almost all field and cluster S0s appear undisturbed, there is a relatively small population of star-forming S0s in clusters but not in the field. These findings are consistent with relatively gentle environmental processes acting on galaxies infalling on to clusters.

WE-G-204-06: Grid-Line Artifact Minimization for High Resolution Detectors Using Iterative Residual Scatter Correction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rana, R; Bednarek, D; Rudin, S

2015-06-15

Purpose: Anti-scatter grid-line artifacts are more prominent for high-resolution x-ray detectors since the fraction of a pixel blocked by the grid septa is large. Direct logarithmic subtraction of the artifact pattern is limited by residual scattered radiation and we investigate an iterative method for scatter correction. Methods: A stationary Smit-Rοntgen anti-scatter grid was used with a high resolution Dexela 1207 CMOS X-ray detector (75 µm pixel size) to image an artery block (Nuclear Associates, Model 76-705) placed within a uniform head equivalent phantom as the scattering source. The image of the phantom was divided by a flat-field image obtained withoutmore » scatter but with the grid to eliminate grid-line artifacts. Constant scatter values were subtracted from the phantom image before dividing by the averaged flat-field-with-grid image. The standard deviation of pixel values for a fixed region of the resultant images with different subtracted scatter values provided a measure of the remaining grid-line artifacts. Results: A plot of the standard deviation of image pixel values versus the subtracted scatter value shows that the image structure noise reaches a minimum before going up again as the scatter value is increased. This minimum corresponds to a minimization of the grid-line artifacts as demonstrated in line profile plots obtained through each of the images perpendicular to the grid lines. Artifact-free images of the artery block were obtained with the optimal scatter value obtained by this iterative approach. Conclusion: Residual scatter subtraction can provide improved grid-line artifact elimination when using the flat-field with grid “subtraction” technique. The standard deviation of image pixel values can be used to determine the optimal scatter value to subtract to obtain a minimization of grid line artifacts with high resolution x-ray imaging detectors. This study was supported by NIH Grant R01EB002873 and an equipment grant from Toshiba Medical Systems Corp.« less

Dissipation, transfer and safety evaluation of emamectin benzoate in tea.

PubMed

Zhou, Li; Luo, Fengjian; Zhang, Xinzhong; Jiang, Yaping; Lou, Zhengyun; Chen, Zongmao

2016-07-01

The dissipation and residue of emamectin benzoate in tea leaves and the residue transfer from tea leaves to tea brew were investigated by modified QuEChERS (quick, easy, cheap, effective, rugged and safe) combined with ultra performance liquid chromatography tandem mass (UPLC-MS/MS). The average recoveries ranged 85.3-101.3% with relative standard deviation (RSD) less than 15%. The limits of quantification (LOQ) were 0.005mgkg(-1) in tea leaves and 0.0004mgL(-1) in brew. Emamectin benzoate dissipated rapidly in tea with half-life (t1/2) of 1.0-1.3days. The terminal residues of emamectin benzoate were less than 0.062mgkg(-1). The leaching rate of emamectin benzoate from freshly-made tea to brew was <5%. The risk of emamectin benzoate at the recommended dosage was negligible to humans depending on risk quotient (RQ) value, that was lower than 1 significantly. This study could provide guidance for the safe use of emamectin benzoate and serve as a reference for the establishment of maximum residue limits (MRLs) in China. Copyright © 2016. Published by Elsevier Ltd.

Chip-scale pattern modification method for equalizing residual layer thickness in nanoimprint lithography

NASA Astrophysics Data System (ADS)

Youn, Sung-Won; Suzuki, Kenta; Hiroshima, Hiroshi

2018-06-01

A software program for modifying a mold design to obtain a uniform residual layer thickness (RLT) distribution has been developed and its validity was verified by UV-nanoimprint lithography (UV-NIL) simulation. First, the effects of granularity (G) on both residual layer uniformity and filling characteristics were characterized. For a constant complementary pattern depth and a granularity that was sufficiently larger than the minimum pattern width, filling time decreased with the decrease in granularity. For a pattern design with a wide density range and an irregular distribution, the choice of a small granularity was not always a good strategy since the etching depth required for a complementary pattern occasionally exceptionally increased with the decrease in granularity. On basis of the results obtained, the automated method was applied to a chip-scale pattern modification. Simulation results showed a marked improvement in residual layer thickness uniformity for a capacity-equalized (CE) mold. For the given conditions, the standard deviation of RLT decreased in the range from 1/3 to 1/5 in accordance with pattern designs.

SCC of 2304 Duplex Stainless Steel—Microstructure, Residual Stress and Surface Grinding Effects

PubMed Central

Zhou, Nian; Peng, Ru Lin; Schönning, Mikael; Pettersson, Rachel

2017-01-01

The influence of surface grinding and microstructure on chloride induced stress corrosion cracking (SCC) behavior of 2304 duplex stainless steel has been investigated. Grinding operations were performed both parallel and perpendicular to the rolling direction of the material. SCC tests were conducted in boiling magnesium chloride according to ASTM G36; specimens were exposed both without external loading and with varied levels of four-point bend loading. Residual stresses were measured on selected specimens before and after exposure using the X-ray diffraction technique. In addition, in-situ surface stress measurements subjected to four-point bend loading were performed to evaluate the deviation between the actual applied loading and the calculated values according to ASTM G39. Micro-cracks, initiated by grinding induced surface tensile residual stresses, were observed for all the ground specimens but not on the as-delivered surfaces. Loading transverse to the rolling direction of the material increased the susceptibility to chloride induced SCC. Grinding induced tensile residual stresses and micro-notches in the as-ground surface topography were also detrimental. PMID:28772582

SCC of 2304 Duplex Stainless Steel-Microstructure, Residual Stress and Surface Grinding Effects.

PubMed

Zhou, Nian; Peng, Ru Lin; Schönning, Mikael; Pettersson, Rachel

2017-02-23

The influence of surface grinding and microstructure on chloride induced stress corrosion cracking (SCC) behavior of 2304 duplex stainless steel has been investigated. Grinding operations were performed both parallel and perpendicular to the rolling direction of the material. SCC tests were conducted in boiling magnesium chloride according to ASTM G36; specimens were exposed both without external loading and with varied levels of four-point bend loading. Residual stresses were measured on selected specimens before and after exposure using the X-ray diffraction technique. In addition, in-situ surface stress measurements subjected to four-point bend loading were performed to evaluate the deviation between the actual applied loading and the calculated values according to ASTM G39. Micro-cracks, initiated by grinding induced surface tensile residual stresses, were observed for all the ground specimens but not on the as-delivered surfaces. Loading transverse to the rolling direction of the material increased the susceptibility to chloride induced SCC. Grinding induced tensile residual stresses and micro-notches in the as-ground surface topography were also detrimental.

The neural basis of financial risk taking.

PubMed

Kuhnen, Camelia M; Knutson, Brian

2005-09-01

Investors systematically deviate from rationality when making financial decisions, yet the mechanisms responsible for these deviations have not been identified. Using event-related fMRI, we examined whether anticipatory neural activity would predict optimal and suboptimal choices in a financial decision-making task. We characterized two types of deviations from the optimal investment strategy of a rational risk-neutral agent as risk-seeking mistakes and risk-aversion mistakes. Nucleus accumbens activation preceded risky choices as well as risk-seeking mistakes, while anterior insula activation preceded riskless choices as well as risk-aversion mistakes. These findings suggest that distinct neural circuits linked to anticipatory affect promote different types of financial choices and indicate that excessive activation of these circuits may lead to investing mistakes. Thus, consideration of anticipatory neural mechanisms may add predictive power to the rational actor model of economic decision making.

Composite Cure Process Modeling and Simulations using COMPRO(Registered Trademark) and Validation of Residual Strains using Fiber Optics Sensors

NASA Technical Reports Server (NTRS)

Sreekantamurthy, Thammaiah; Hudson, Tyler B.; Hou, Tan-Hung; Grimsley, Brian W.

2016-01-01

Composite cure process induced residual strains and warping deformations in composite components present significant challenges in the manufacturing of advanced composite structure. As a part of the Manufacturing Process and Simulation initiative of the NASA Advanced Composite Project (ACP), research is being conducted on the composite cure process by developing an understanding of the fundamental mechanisms by which the process induced factors influence the residual responses. In this regard, analytical studies have been conducted on the cure process modeling of composite structural parts with varied physical, thermal, and resin flow process characteristics. The cure process simulation results were analyzed to interpret the cure response predictions based on the underlying physics incorporated into the modeling tool. In the cure-kinetic analysis, the model predictions on the degree of cure, resin viscosity and modulus were interpreted with reference to the temperature distribution in the composite panel part and tool setup during autoclave or hot-press curing cycles. In the fiber-bed compaction simulation, the pore pressure and resin flow velocity in the porous media models, and the compaction strain responses under applied pressure were studied to interpret the fiber volume fraction distribution predictions. In the structural simulation, the effect of temperature on the resin and ply modulus, and thermal coefficient changes during curing on predicted mechanical strains and chemical cure shrinkage strains were studied to understand the residual strains and stress response predictions. In addition to computational analysis, experimental studies were conducted to measure strains during the curing of laminated panels by means of optical fiber Bragg grating sensors (FBGs) embedded in the resin impregnated panels. The residual strain measurements from laboratory tests were then compared with the analytical model predictions. The paper describes the cure process procedures and residual strain predications, and discusses pertinent experimental results from the validation studies.

Alternate approach for calculating hardness based on residual indentation depth: Comparison with experiments

NASA Astrophysics Data System (ADS)

Ananthakrishna, G.; K, Srikanth

2018-03-01

It is well known that plastic deformation is a highly nonlinear dissipative irreversible phenomenon of considerable complexity. As a consequence, little progress has been made in modeling some well-known size-dependent properties of plastic deformation, for instance, calculating hardness as a function of indentation depth independently. Here, we devise a method of calculating hardness by calculating the residual indentation depth and then calculate the hardness as the ratio of the load to the residual imprint area. Recognizing the fact that dislocations are the basic defects controlling the plastic component of the indentation depth, we set up a system of coupled nonlinear time evolution equations for the mobile, forest, and geometrically necessary dislocation densities. Within our approach, we consider the geometrically necessary dislocations to be immobile since they contribute to additional hardness. The model includes dislocation multiplication, storage, and recovery mechanisms. The growth of the geometrically necessary dislocation density is controlled by the number of loops that can be activated under the contact area and the mean strain gradient. The equations are then coupled to the load rate equation. Our approach has the ability to adopt experimental parameters such as the indentation rates, the geometrical parameters defining the Berkovich indenter, including the nominal tip radius. The residual indentation depth is obtained by integrating the Orowan expression for the plastic strain rate, which is then used to calculate the hardness. Consistent with the experimental observations, the increasing hardness with decreasing indentation depth in our model arises from limited dislocation sources at small indentation depths and therefore avoids divergence in the limit of small depths reported in the Nix-Gao model. We demonstrate that for a range of parameter values that physically represent different materials, the model predicts the three characteristic features of hardness, namely, increase in the hardness with decreasing indentation depth, and the linear relation between the square of the hardness and the inverse of the indentation depth, for all but 150 nm, deviating for smaller depths. In addition, we also show that it is straightforward to obtain optimized parameter values that give good fit to the hardness data for polycrystalline cold worked copper and single crystals of silver.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aristophanous, M; Court, L

Purpose: Despite daily image guidance setup uncertainties can be high when treating large areas of the body. The aim of this study was to measure local uncertainties inside the PTV for patients receiving IMRT to the mediastinum region. Methods: Eleven lymphoma patients that received radiotherapy (breath-hold) to the mediastinum were included in this study. The treated region could range all the way from the neck to the diaphragm. Each patient had a CT scan with a CT-on-rails system prior to every treatment. The entire PTV region was matched to the planning CT using automatic rigid registration. The PTV was thenmore » split into 5 regions: neck, supraclavicular, superior mediastinum, upper heart, lower heart. Additional auto-registrations for each of the 5 local PTV regions were performed. The residual local setup errors were calculated as the difference between the final global PTV position and the individual final local PTV positions for the AP, SI and RL directions. For each patient 4 CT scans were analyzed (1 per week of treatment). Results: The residual mean group error (M) and standard deviation of the inter-patient (or systematic) error (Σ) were lowest in the RL direction of the superior mediastinum (0.0mm and 0.5mm) and highest in the RL direction of the lower heart (3.5mm and 2.9mm). The standard deviation of the inter-fraction (or random) error (σ) was lowest in the RL direction of the superior mediastinum (0.5mm) and highest in the SI direction of the lower heart (3.9mm) The directionality of local uncertainties is important; a superior residual error in the lower heart for example keeps it in the global PTV. Conclusion: There is a complex relationship between breath-holding and positioning uncertainties that needs further investigation. Residual setup uncertainties can be significant even under daily CT image guidance when treating large regions of the body.« less

Absolute Magnitude Calibration for Dwarfs Based on the Colour-Magnitude Diagrams of Galactic Clusters

NASA Astrophysics Data System (ADS)

Karaali, S.; Gökçe, E. Yaz; Bilir, S.; Güçtekin, S. Tunçel

2014-07-01

We present two absolute magnitude calibrations for dwarfs based on colour-magnitude diagrams of Galactic clusters. The combination of the Mg absolute magnitudes of the dwarf fiducial sequences of the clusters M92, M13, M5, NGC 2420, M67, and NGC 6791 with the corresponding metallicities provides absolute magnitude calibration for a given (g - r)0 colour. The calibration is defined in the colour interval 0.25 ≤ (g - r)0 ≤ 1.25 mag and it covers the metallicity interval - 2.15 ≤ [Fe/H] ≤ +0.37 dex. The absolute magnitude residuals obtained by the application of the procedure to another set of Galactic clusters lie in the interval - 0.15 ≤ ΔMg ≤ +0.12 mag. The mean and standard deviation of the residuals are < ΔMg > = - 0.002 and σ = 0.065 mag, respectively. The calibration of the MJ absolute magnitude in terms of metallicity is carried out by using the fiducial sequences of the clusters M92, M13, 47 Tuc, NGC 2158, and NGC 6791. It is defined in the colour interval 0.90 ≤ (V - J)0 ≤ 1.75 mag and it covers the same metallicity interval of the Mg calibration. The absolute magnitude residuals obtained by the application of the procedure to the cluster M5 ([Fe/H] = -1.40 dex) and 46 solar metallicity, - 0.45 ≤ [Fe/H] ≤ +0.35 dex, field stars lie in the interval - 0.29 and + 0.35 mag. However, the range of 87% of them is rather shorter, - 0.20 ≤ ΔMJ ≤ +0.20 mag. The mean and standard deviation of all residuals are < ΔMJ > =0.05 and σ = 0.13 mag, respectively. The derived relations are applicable to stars older than 4 Gyr for the Mg calibration, and older than 2 Gyr for the MJ calibration. The cited limits are the ages of the youngest calibration clusters in the two systems.

Stress Transfer Mechanisms at the Submicron Level for Graphene/Polymer Systems

PubMed Central

2015-01-01

The stress transfer mechanism from a polymer substrate to a nanoinclusion, such as a graphene flake, is of extreme interest for the production of effective nanocomposites. Previous work conducted mainly at the micron scale has shown that the intrinsic mechanism of stress transfer is shear at the interface. However, since the interfacial shear takes its maximum value at the very edge of the nanoinclusion it is of extreme interest to assess the effect of edge integrity upon axial stress transfer at the submicron scale. Here, we conduct a detailed Raman line mapping near the edges of a monolayer graphene flake that is simply supported onto an epoxy-based photoresist (SU8)/poly(methyl methacrylate) matrix at steps as small as 100 nm. We show for the first time that the distribution of axial strain (stress) along the flake deviates somewhat from the classical shear-lag prediction for a region of ∼2 μm from the edge. This behavior is mainly attributed to the presence of residual stresses, unintentional doping, and/or edge effects (deviation from the equilibrium values of bond lengths and angles, as well as different edge chiralities). By considering a simple balance of shear-to-normal stresses at the interface we are able to directly convert the strain (stress) gradient to values of interfacial shear stress for all the applied tensile levels without assuming classical shear-lag behavior. For large flakes a maximum value of interfacial shear stress of 0.4 MPa is obtained prior to flake slipping. PMID:25644121

Thermal Expansion of Vacuum Plasma Sprayed Coatings

NASA Technical Reports Server (NTRS)

Raj, S V.; Palczer, A. R.

2010-01-01

Metallic Cu-8%Cr, Cu-26%Cr, Cu-8%Cr-1%Al, NiAl and NiCrAlY monolithic coatings were fabricated by vacuum plasma spray deposition processes for thermal expansion property measurements between 293 and 1223 K. The corrected thermal expansion, (DL/L(sub 0) varies with the absolute temperature, T, as (DL/L(sub 0) = A(T - 293)(sup 3) + BIT - 293)(sup 2) + C(T - 293) + D, where, A, B, C and D are thermal, regression constants. Excellent reproducibility was observed for all of the coatings except for data obtained on the Cu-8%Cr and Cu-26%Cr coatings in the first heat-up cycle, which deviated from those determined in the subsequent cycles. This deviation is attributed to the presence of residual stresses developed during the spraying of the coatings, which are relieved after the first heat-up cycle. In the cases of Cu-8%Cr and NiAl, the thermal expansion data were observed to be reproducible for three specimens. The linear expansion data for Cu-8% Cr and Cu-26%Cr agree extremely well with rule of mixture (ROM) predictions. Comparison of the data for the Cu-8%Cr coating with literature data for Cr and Cu revealed that the thermal expansion behavior of this alloy is determined by the Cu-rich matrix. The data for NiAl and NiCrAlY are in excellent agreement with published results irrespective of composition and the methods used for processing the materials. The implications of these results on coating GRCop-84 copper alloy combustor liners for reusable launch vehicles are discussed.

Analysis of consequences of non-synonymous SNP in feed conversion ratio associated TGF-β receptor type 3 gene in chicken.

PubMed

Rasal, Kiran D; Shah, Tejas M; Vaidya, Megha; Jakhesara, Subhash J; Joshi, Chaitanya G

2015-06-01

The recent advances in high throughput sequencing technology accelerate possible ways for the study of genome wide variation in several organisms and associated consequences. In the present study, mutations in TGFBR3 showing significant association with FCR trait in chicken during exome sequencing were further analyzed. Out of four SNPs, one nsSNP p.Val451Leu was found in the coding region of TGFBR3. In silico tools such as SnpSift and PANTHER predicted it as deleterious (0.04) and to be tolerated, respectively, while I-Mutant revealed that protein stability decreased. The TGFBR3 I-TASSER model has a C-score of 0.85, which was validated using PROCHECK. Based on MD simulation, mutant protein structure deviated from native with RMSD 0.08 Å due to change in the H-bonding distances of mutant residue. The docking of TGFBR3 with interacting TGFBR2 inferred that mutant required more global energy. Therefore, the present study will provide useful information about functional SNPs that have an impact on FCR traits.

Analysis and Design of Fuselage Structures Including Residual Strength Prediction Methodology

NASA Technical Reports Server (NTRS)

Knight, Norman F.

1998-01-01

The goal of this research project is to develop and assess methodologies for the design and analysis of fuselage structures accounting for residual strength. Two primary objectives are included in this research activity: development of structural analysis methodology for predicting residual strength of fuselage shell-type structures; and the development of accurate, efficient analysis, design and optimization tool for fuselage shell structures. Assessment of these tools for robustness, efficient, and usage in a fuselage shell design environment will be integrated with these two primary research objectives.

Underwater EIT Follow-on Project

DTIC Science & Technology

2009-01-01

correlation value of 0.2. (White pixels indicate zero deviation from predicted transimpedance ; blue represents high deviation...34 Figure 50. Sample transimpedance measurements for high turbidity (top) and low turbidity (bottom) conditions. (These measurements...magnitudes of the transimpedance measurements. ... 40 Figure 67. A reconstruction image of rust level 0. The true target position is 2cm below the

A QSPR model for prediction of diffusion coefficient of non-electrolyte organic compounds in air at ambient condition.

PubMed

Mirkhani, Seyyed Alireza; Gharagheizi, Farhad; Sattari, Mehdi

2012-03-01

Evaluation of diffusion coefficients of pure compounds in air is of great interest for many diverse industrial and air quality control applications. In this communication, a QSPR method is applied to predict the molecular diffusivity of chemical compounds in air at 298.15K and atmospheric pressure. Four thousand five hundred and seventy nine organic compounds from broad spectrum of chemical families have been investigated to propose a comprehensive and predictive model. The final model is derived by Genetic Function Approximation (GFA) and contains five descriptors. Using this dedicated model, we obtain satisfactory results quantified by the following statistical results: Squared Correlation Coefficient=0.9723, Standard Deviation Error=0.003 and Average Absolute Relative Deviation=0.3% for the predicted properties from existing experimental values. Copyright © 2011 Elsevier Ltd. All rights reserved.

Transmembrane Domains of Attraction on the TSH Receptor

PubMed Central

Ali, M. Rejwan; Mezei, Mihaly; Davies, Terry F.

2015-01-01

The TSH receptor (TSHR) has the propensity to form dimers and oligomers. Our data using ectodomain-truncated TSHRs indicated that the predominant interfaces for oligomerization reside in the transmembrane (TM) domain. To map the potentially interacting residues, we first performed in silico studies of the TSHR transmembrane domain using a homology model and using Brownian dynamics (BD). The cluster of dimer conformations obtained from BD analysis indicated that TM1 made contact with TM4 and two residues in TM2 made contact with TM5. To confirm the proximity of these contact residues, we then generated cysteine mutants at all six contact residues predicted by the BD analysis and performed cysteine cross-linking studies. These results showed that the predicted helices in the protomer were indeed involved in proximity interactions. Furthermore, an alternative experimental approach, receptor truncation experiments and LH receptor sequence substitution experiments, identified TM1 harboring a major region involved in TSHR oligomerization, in agreement with the conclusion from the cross-linking studies. Point mutations of the predicted interacting residues did not yield a substantial decrease in oligomerization, unlike the truncation of the TM1, so we concluded that constitutive oligomerization must involve interfaces forming domains of attraction in a cooperative manner that is not dominated by interactions between specific residues. PMID:25406938

Predictions for Proteins, RNAs and DNAs with the Gaussian Dielectric Function Using DelPhiPKa

PubMed Central

Wang, Lin; Li, Lin; Alexov, Emil

2015-01-01

We developed a Poisson-Boltzmann based approach to calculate the PKa values of protein ionizable residues (Glu, Asp, His, Lys and Arg), nucleotides of RNA and single stranded DNA. Two novel features were utilized: the dielectric properties of the macromolecules and water phase were modeled via the smooth Gaussian-based dielectric function in DelPhi and the corresponding electrostatic energies were calculated without defining the molecular surface. We tested the algorithm by calculating PKa values for more than 300 residues from 32 proteins from the PPD dataset and achieved an overall RMSD of 0.77. Particularly, the RMSD of 0.55 was achieved for surface residues, while the RMSD of 1.1 for buried residues. The approach was also found capable of capturing the large PKa shifts of various single point mutations in staphylococcal nuclease (SNase) from PKa -cooperative dataset, resulting in an overall RMSD of 1.6 for this set of pKa’s. Investigations showed that predictions for most of buried mutant residues of SNase could be improved by using higher dielectric constant values. Furthermore, an option to generate different hydrogen positions also improves PKa predictions for buried carboxyl residues. Finally, the PKa calculations on two RNAs demonstrated the capability of this approach for other types of biomolecules. PMID:26408449

Assessing the Utility of Seasonal SST Forecasts to the Fisheries Management Process: a Pacific Sardine Case Study

NASA Astrophysics Data System (ADS)

Tommasi, D.; Stock, C. A.

2016-02-01

It is well established that environmental fluctuations affect the productivity of numerous fish stocks. Recent advances in prediction capability of dynamical global forecast systems, such as the state of the art NOAA Geophysical Fluid dynamics Laboratory (GFDL) 2.5-FLOR model, allow for climate predictions of fisheries-relevant variables at temporal scales relevant to the fishery management decision making process. We demonstrate that the GFDL FLOR model produces skillful seasonal SST anomaly predictions over the continental shelf , where most of the global fish yield is generated. The availability of skillful SST projections at this "fishery relevant" scale raises the potential for better constrained estimates of future fish biomass and improved harvest decisions. We assessed the utility of seasonal SST coastal shelf predictions for fisheries management using the case study of Pacific sardine. This fishery was selected because it is one of the few to already incorporate SST into its harvest guideline, and show a robust recruitment-SST relationship. We quantified the effectiveness of management under the status quo harvest guideline (HG) and under alternative HGs including future information at different levels of uncertainty. Usefulness of forecast SST to management was dependent on forecast uncertainty. If the standard deviation of the SST anomaly forecast residuals was less than 0.65, the alternative HG produced higher long-term yield and stock biomass, and reduced the probability of either catch or stock biomass falling below management-set threshold values as compared to the status quo. By contrast, probability of biomass falling to extremely low values increased as compared to the status quo for all alternative HGs except for a perfectly known future SST case. To safeguard against occurrence of such low probability but costly events, a harvest cutoff biomass also has to be implemented into the HG.

Summary of the GK15 ground‐motion prediction equation for horizontal PGA and 5% damped PSA from shallow crustal continental earthquakes

USGS Publications Warehouse

Graizer, Vladimir;; Kalkan, Erol

2016-01-01

We present a revised ground‐motion prediction equation (GMPE) for computing medians and standard deviations of peak ground acceleration (PGA) and 5% damped pseudospectral acceleration (PSA) response ordinates of the horizontal component of randomly oriented ground motions to be used for seismic‐hazard analyses and engineering applications. This GMPE is derived from the expanded Next Generation Attenuation (NGA)‐West 1 database (see Data and Resources; Chiou et al., 2008). The revised model includes an anelastic attenuation term as a function of quality factor (Q0) to capture regional differences in far‐source (beyond 150 km) attenuation, and a new frequency‐dependent sedimentary‐basin scaling term as a function of depth to the 1.5  km/s shear‐wave velocity isosurface to improve ground‐motion predictions at sites located on deep sedimentary basins. The new Graizer–Kalkan 2015 (GK15) model, developed to be simple, is applicable for the western United States and other similar shallow crustal continental regions in active tectonic environments for earthquakes with moment magnitudes (M) 5.0–8.0, distances 0–250 km, average shear‐wave velocities in the upper 30 m (VS30) 200–1300  m/s, and spectral periods (T) 0.01–5 s. Our aleatory variability model captures interevent (between‐event) variability, which decreases with magnitude and increases with distance. The mixed‐effect residuals analysis reveals that the GK15 has no trend with respect to the independent predictor parameters. Compared to our 2007–2009 GMPE, the PGA values are very similar, whereas spectral ordinates predicted are larger at T<0.2  s and they are smaller at longer periods.

Residue decomposition of submodel of WEPS

USDA-ARS?s Scientific Manuscript database

The Residue Decomposition submodel of the Wind Erosion Prediction System (WEPS) simulates the decrease in crop residue biomass due to microbial activity. The decomposition process is modeled as a first-order reaction with temperature and moisture as driving variables. Decomposition is a function of ...

Finite element estimation of the residual stresses in roller-straightened rail

DOT National Transportation Integrated Search

2004-11-13

The purpose of this paper is to develop models to accurately predict : the residual stresses due to the roller straightening of railroad rails. : Several aspects of residual stress creation in rail due to roller : straightening are addressed. The eff...

Lid opening and conformational stability of T1 Lipase is mediated by increasing chain length polar solvents

PubMed Central

Mohamad Ali, Mohd Shukuri; Salleh, Abu Bakar; Rahman, Raja Noor Zaliha Raja Abd; Normi, Yahaya M.; Mohd Shariff, Fairolniza

2017-01-01

The dynamics and conformational landscape of proteins in organic solvents are events of potential interest in nonaqueous process catalysis. Conformational changes, folding transitions, and stability often correspond to structural rearrangements that alter contacts between solvent molecules and amino acid residues. However, in nonaqueous enzymology, organic solvents limit stability and further application of proteins. In the present study, molecular dynamics (MD) of a thermostable Geobacillus zalihae T1 lipase was performed in different chain length polar organic solvents (methanol, ethanol, propanol, butanol, and pentanol) and water mixture systems to a concentration of 50%. On the basis of the MD results, the structural deviations of the backbone atoms elucidated the dynamic effects of water/organic solvent mixtures on the equilibrium state of the protein simulations in decreasing solvent polarity. The results show that the solvent mixture gives rise to deviations in enzyme structure from the native one simulated in water. The drop in the flexibility in H2O, MtOH, EtOH and PrOH simulation mixtures shows that greater motions of residues were influenced in BtOH and PtOH simulation mixtures. Comparing the root mean square fluctuations value with the accessible solvent area (SASA) for every residue showed an almost correspondingly high SASA value of residues to high flexibility and low SASA value to low flexibility. The study further revealed that the organic solvents influenced the formation of more hydrogen bonds in MtOH, EtOH and PrOH and thus, it is assumed that increased intraprotein hydrogen bonding is ultimately correlated to the stability of the protein. However, the solvent accessibility analysis showed that in all solvent systems, hydrophobic residues were exposed and polar residues tended to be buried away from the solvent. Distance variation of the tetrahedral intermediate packing of the active pocket was not conserved in organic solvent systems, which could lead to weaknesses in the catalytic H-bond network and most likely a drop in catalytic activity. The conformational variation of the lid domain caused by the solvent molecules influenced its gradual opening. Formation of additional hydrogen bonds and hydrophobic interactions indicates that the contribution of the cooperative network of interactions could retain the stability of the protein in some solvent systems. Time-correlated atomic motions were used to characterize the correlations between the motions of the atoms from atomic coordinates. The resulting cross-correlation map revealed that the organic solvent mixtures performed functional, concerted, correlated motions in regions of residues of the lid domain to other residues. These observations suggest that varying lengths of polar organic solvents play a significant role in introducing dynamic conformational diversity in proteins in a decreasing order of polarity. PMID:28533982

Clinical assessment is an accurate predictor of which patients will need septoplasty.

PubMed

Sedaghat, Ahmad R; Busaba, Nicolas Y; Cunningham, Michael J; Kieff, David A

2013-01-01

Septoplasty is a frequently performed surgical procedure with the most common indication being nasal airway obstruction. Almost universally, health insurance companies mandate a trial of medical therapy consisting of intranasal corticosteroids prior to performance of septoplasty regardless of clinical assessment. Evidence for this requirement is lacking. We sought to evaluate the initial clinical assessment as a predictor of response to this mandated trial of medical treatment. Retrospective review of prospectively collected data on 137 consecutive patients who presented with symptoms of nasal obstruction and a deviated nasal septum on physical examination. Patients were placed into one of three cohorts based on prediction of 1) failure of medical therapy with subsequent septoplasty, 2) success of medical therapy without subsequent septoplasty, or 3) unable to make a prediction. Patients from each cohort were assessed for subsequent response to medical therapy and ultimate need for septoplasty. Overall clinical assessment had a sensitivity of 86.9%, specificity of 91.8%, positive predictive value of 93.6%, and negative predictive value of 96.4% for detecting/predicting need for septoplasty. The accuracy of the overall clinical assessment is considerably better than severe deviation at any one septal anatomical site. Of patients whose response to medical therapy could not be predicted, 61.3% failed medical therapy and needed surgery; this is statistically equivalent to a 50/50 distribution between either needing septoplasty or not. Clinical assessment at initial presentation of patients with nasal obstruction and deviated septum is highly accurate in predicting which patients will need septoplasty. Copyright © 2012 The American Laryngological, Rhinological, and Otological Society, Inc.

[Study of building quantitative analysis model for chlorophyll in winter wheat with reflective spectrum using MSC-ANN algorithm].

PubMed

Liang, Xue; Ji, Hai-yan; Wang, Peng-xin; Rao, Zhen-hong; Shen, Bing-hui

2010-01-01

Preprocess method of multiplicative scatter correction (MSC) was used to reject noises in the original spectra produced by the environmental physical factor effectively, then the principal components of near-infrared spectroscopy were calculated by nonlinear iterative partial least squares (NIPALS) before building the back propagation artificial neural networks method (BP-ANN), and the numbers of principal components were calculated by the method of cross validation. The calculated principal components were used as the inputs of the artificial neural networks model, and the artificial neural networks model was used to find the relation between chlorophyll in winter wheat and reflective spectrum, which can predict the content of chlorophyll in winter wheat. The correlation coefficient (r) of calibration set was 0.9604, while the standard deviation (SD) and relative standard deviation (RSD) was 0.187 and 5.18% respectively. The correlation coefficient (r) of predicted set was 0.9600, and the standard deviation (SD) and relative standard deviation (RSD) was 0.145 and 4.21% respectively. It means that the MSC-ANN algorithm can reject noises in the original spectra produced by the environmental physical factor effectively and set up an exact model to predict the contents of chlorophyll in living leaves veraciously to replace the classical method and meet the needs of fast analysis of agricultural products.

Predicting logging residues: an interim equation for Appalachian oak sawtimber

Treesearch

A. Jeff Martin

1975-01-01

An equation, using dbh, dbh², bole length, and sawlog height to predict the cubic-foot volume of logging residue per tree, was developed from data collected on 36 mixed oaks in southwestern Virginia. The equation produced reliable results for small sawtimber trees, but additional research is needed for other species, sites, and utilization practices.

Effect of Stress on Energy Flux Deviation of Ultrasonic Waves in Ultrasonic Waves in GR/EP Composites

NASA Technical Reports Server (NTRS)

Prosser, William H.; Kriz, R. D.; Fitting, Dale W.

1990-01-01

Ultrasonic waves suffer energy flux deviation in graphite/epoxy because of the large anisotropy. The angle of deviation is a function of the elastic coefficients. For nonlinear solids, these coefficients and thus the angle of deviation is a function of stress. Acoustoelastic theory was used to model the effect of stress on flux deviation for unidirectional T300/5208 using previously measured elastic coefficients. Computations were made for uniaxial stress along the x3 axis fiber axis) and the x1 axis for waves propagating in the x1x3 plane. These results predict a shift as large as three degrees for the quasi-transverse wave. The shift in energy flux offers new nondestructive technique of evaluating stress in composites.

Predicting Transmembrane Helix Packing Arrangements using Residue Contacts and a Force-Directed Algorithm

PubMed Central

Nugent, Timothy; Jones, David T.

2010-01-01

Alpha-helical transmembrane proteins constitute roughly 30% of a typical genome and are involved in a wide variety of important biological processes including cell signalling, transport of membrane-impermeable molecules and cell recognition. Despite significant efforts to predict transmembrane protein topology, comparatively little attention has been directed toward developing a method to pack the helices together. Here, we present a novel approach to predict lipid exposure, residue contacts, helix-helix interactions and finally the optimal helical packing arrangement of transmembrane proteins. Using molecular dynamics data, we have trained and cross-validated a support vector machine (SVM) classifier to predict per residue lipid exposure with 69% accuracy. This information is combined with additional features to train a second SVM to predict residue contacts which are then used to determine helix-helix interaction with up to 65% accuracy under stringent cross-validation on a non-redundant test set. Our method is also able to discriminate native from decoy helical packing arrangements with up to 70% accuracy. Finally, we employ a force-directed algorithm to construct the optimal helical packing arrangement which demonstrates success for proteins containing up to 13 transmembrane helices. This software is freely available as source code from http://bioinf.cs.ucl.ac.uk/memsat/mempack/. PMID:20333233

Peridynamics for failure and residual strength prediction of fiber-reinforced composites

NASA Astrophysics Data System (ADS)

Colavito, Kyle

Peridynamics is a reformulation of classical continuum mechanics that utilizes integral equations in place of partial differential equations to remove the difficulty in handling discontinuities, such as cracks or interfaces, within a body. Damage is included within the constitutive model; initiation and propagation can occur without resorting to special crack growth criteria necessary in other commonly utilized approaches. Predicting damage and residual strengths of composite materials involves capturing complex, distinct and progressive failure modes. The peridynamic laminate theory correctly predicts the load redistribution in general laminate layups in the presence of complex failure modes through the use of multiple interaction types. This study presents two approaches to obtain the critical peridynamic failure parameters necessary to capture the residual strength of a composite structure. The validity of both approaches is first demonstrated by considering the residual strength of isotropic materials. The peridynamic theory is used to predict the crack growth and final failure load in both a diagonally loaded square plate with a center crack, as well as a four-point shear specimen subjected to asymmetric loading. This study also establishes the validity of each approach by considering composite laminate specimens in which each failure mode is isolated. Finally, the failure loads and final failure modes are predicted in a laminate with various hole diameters subjected to tensile and compressive loads.

Accurate prediction of interfacial residues in two-domain proteins using evolutionary information: implications for three-dimensional modeling.

PubMed

Bhaskara, Ramachandra M; Padhi, Amrita; Srinivasan, Narayanaswamy

2014-07-01

With the preponderance of multidomain proteins in eukaryotic genomes, it is essential to recognize the constituent domains and their functions. Often function involves communications across the domain interfaces, and the knowledge of the interacting sites is essential to our understanding of the structure-function relationship. Using evolutionary information extracted from homologous domains in at least two diverse domain architectures (single and multidomain), we predict the interface residues corresponding to domains from the two-domain proteins. We also use information from the three-dimensional structures of individual domains of two-domain proteins to train naïve Bayes classifier model to predict the interfacial residues. Our predictions are highly accurate (∼85%) and specific (∼95%) to the domain-domain interfaces. This method is specific to multidomain proteins which contain domains in at least more than one protein architectural context. Using predicted residues to constrain domain-domain interaction, rigid-body docking was able to provide us with accurate full-length protein structures with correct orientation of domains. We believe that these results can be of considerable interest toward rational protein and interaction design, apart from providing us with valuable information on the nature of interactions. © 2013 Wiley Periodicals, Inc.

Robust Ultraviolet-Visible (UV-Vis) Partial Least-Squares (PLS) Models for Tannin Quantification in Red Wine.

PubMed

Aleixandre-Tudo, José Luis; Nieuwoudt, Helené; Aleixandre, José Luis; Du Toit, Wessel J

2015-02-04

The validation of ultraviolet-visible (UV-vis) spectroscopy combined with partial least-squares (PLS) regression to quantify red wine tannins is reported. The methylcellulose precipitable (MCP) tannin assay and the bovine serum albumin (BSA) tannin assay were used as reference methods. To take the high variability of wine tannins into account when the calibration models were built, a diverse data set was collected from samples of South African red wines that consisted of 18 different cultivars, from regions spanning the wine grape-growing areas of South Africa with their various sites, climates, and soils, ranging in vintage from 2000 to 2012. A total of 240 wine samples were analyzed, and these were divided into a calibration set (n = 120) and a validation set (n = 120) to evaluate the predictive ability of the models. To test the robustness of the PLS calibration models, the predictive ability of the classifying variables cultivar, vintage year, and experimental versus commercial wines was also tested. In general, the statistics obtained when BSA was used as a reference method were slightly better than those obtained with MCP. Despite this, the MCP tannin assay should also be considered as a valid reference method for developing PLS calibrations. The best calibration statistics for the prediction of new samples were coefficient of correlation (R 2 val) = 0.89, root mean standard error of prediction (RMSEP) = 0.16, and residual predictive deviation (RPD) = 3.49 for MCP and R 2 val = 0.93, RMSEP = 0.08, and RPD = 4.07 for BSA, when only the UV region (260-310 nm) was selected, which also led to a faster analysis time. In addition, a difference in the results obtained when the predictive ability of the classifying variables vintage, cultivar, or commercial versus experimental wines was studied suggests that tannin composition is highly affected by many factors. This study also discusses the correlations in tannin values between the methylcellulose and protein precipitation methods.

Prediction of iron oxide contents using diffuse reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Marques, José, Jr.; Arantes Camargo, Livia

2015-04-01

Determining soil iron oxides using conventional analysis is relatively unfeasible when large areas are mapped, with the aim of characterizing spatial variability. Diffuse reflectance spectroscopy (DRS) is rapid, less expensive, non-destructive and sometimes more accurate than conventional analysis. Furthermore, this technique allows the simultaneous characterization of many soil attributes with agronomic and environmental relevance. This study aims to assess the DRS capability to predict iron oxides content -hematite and goethite - , characterizing their spatial variability in soils of Brazil. Soil samples collected from an 800-hectare area were scanned in the visible and near-infrared spectral range. Moreover, chemometric calibration was obtained through partial least-squares regression (PLSR). Then, spatial distribution maps of the attributes were constructed using predicted values from calibrated models through geostatistical methods. The studied area presented soils with varied contents of iron oxides as examples for the Oxisols and Entisols. In the spectra of each soil is observed that the reflectance decreases with the content of iron oxides present in the soil. In soils with a high content of iron oxides can be observed more pronounced concavities between 380 and 1100 nm which are characteristic of the presence of these oxides. In soils with higher reflectance it were observed concavity characteristics due to the presence of kaolinite, in agreement with the low iron contents of those soils. The best accuracy of prediction models [residual prediction deviation (RPD) = 1.7] was obtained for goethite within the visible region (380-800 nm), and for hematite (RPD = 2.0) within the visible near infrared (380-2300 nm). The maps of goethite and hematite predicted showed the spatial distribution pattern similar to the maps of clay and iron extracted by dithionite-citrate-bicarbonate, being consistent with the iron oxide contents of soils present in the study area. These results confirm the value of DRS in the mapping of iron oxides in large areas at detailed scale.

Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks

PubMed Central

Shen, Yang; Bax, Ad

2013-01-01

A new program, TALOS-N, is introduced for predicting protein backbone torsion angles from NMR chemical shifts. The program relies far more extensively on the use of trained artificial neural networks than its predecessor, TALOS+. Validation on an independent set of proteins indicates that backbone torsion angles can be predicted for a larger, ≥ 90% fraction of the residues, with an error rate smaller than ca 3.5%, using an acceptance criterion that is nearly two-fold tighter than that used previously, and a root mean square difference between predicted and crystallographically observed (φ,ψ) torsion angles of ca 12°. TALOS-N also reports sidechain χ1 rotameric states for about 50% of the residues, and a consistency with reference structures of 89%. The program includes a neural network trained to identify secondary structure from residue sequence and chemical shifts. PMID:23728592

KFC Server: interactive forecasting of protein interaction hot spots.

PubMed

Darnell, Steven J; LeGault, Laura; Mitchell, Julie C

2008-07-01

The KFC Server is a web-based implementation of the KFC (Knowledge-based FADE and Contacts) model-a machine learning approach for the prediction of binding hot spots, or the subset of residues that account for most of a protein interface's; binding free energy. The server facilitates the automated analysis of a user submitted protein-protein or protein-DNA interface and the visualization of its hot spot predictions. For each residue in the interface, the KFC Server characterizes its local structural environment, compares that environment to the environments of experimentally determined hot spots and predicts if the interface residue is a hot spot. After the computational analysis, the user can visualize the results using an interactive job viewer able to quickly highlight predicted hot spots and surrounding structural features within the protein structure. The KFC Server is accessible at http://kfc.mitchell-lab.org.

KFC Server: interactive forecasting of protein interaction hot spots

PubMed Central

Darnell, Steven J.; LeGault, Laura; Mitchell, Julie C.

2008-01-01

The KFC Server is a web-based implementation of the KFC (Knowledge-based FADE and Contacts) model—a machine learning approach for the prediction of binding hot spots, or the subset of residues that account for most of a protein interface's; binding free energy. The server facilitates the automated analysis of a user submitted protein–protein or protein–DNA interface and the visualization of its hot spot predictions. For each residue in the interface, the KFC Server characterizes its local structural environment, compares that environment to the environments of experimentally determined hot spots and predicts if the interface residue is a hot spot. After the computational analysis, the user can visualize the results using an interactive job viewer able to quickly highlight predicted hot spots and surrounding structural features within the protein structure. The KFC Server is accessible at http://kfc.mitchell-lab.org. PMID:18539611

Accounting for epistatic interactions improves the functional analysis of protein structures.

PubMed

Wilkins, Angela D; Venner, Eric; Marciano, David C; Erdin, Serkan; Atri, Benu; Lua, Rhonald C; Lichtarge, Olivier

2013-11-01

The constraints under which sequence, structure and function coevolve are not fully understood. Bringing this mutual relationship to light can reveal the molecular basis of binding, catalysis and allostery, thereby identifying function and rationally guiding protein redesign. Underlying these relationships are the epistatic interactions that occur when the consequences of a mutation to a protein are determined by the genetic background in which it occurs. Based on prior data, we hypothesize that epistatic forces operate most strongly between residues nearby in the structure, resulting in smooth evolutionary importance across the structure. We find that when residue scores of evolutionary importance are distributed smoothly between nearby residues, functional site prediction accuracy improves. Accordingly, we designed a novel measure of evolutionary importance that focuses on the interaction between pairs of structurally neighboring residues. This measure that we term pair-interaction Evolutionary Trace yields greater functional site overlap and better structure-based proteome-wide functional predictions. Our data show that the structural smoothness of evolutionary importance is a fundamental feature of the coevolution of sequence, structure and function. Mutations operate on individual residues, but selective pressure depends in part on the extent to which a mutation perturbs interactions with neighboring residues. In practice, this principle led us to redefine the importance of a residue in terms of the importance of its epistatic interactions with neighbors, yielding better annotation of functional residues, motivating experimental validation of a novel functional site in LexA and refining protein function prediction. lichtarge@bcm.edu. Supplementary data are available at Bioinformatics online.

Heterodimer Binding Scaffolds Recognition via the Analysis of Kinetically Hot Residues.

PubMed

Perišić, Ognjen

2018-03-16

Physical interactions between proteins are often difficult to decipher. The aim of this paper is to present an algorithm that is designed to recognize binding patches and supporting structural scaffolds of interacting heterodimer proteins using the Gaussian Network Model (GNM). The recognition is based on the (self) adjustable identification of kinetically hot residues and their connection to possible binding scaffolds. The kinetically hot residues are residues with the lowest entropy, i.e., the highest contribution to the weighted sum of the fastest modes per chain extracted via GNM. The algorithm adjusts the number of fast modes in the GNM's weighted sum calculation using the ratio of predicted and expected numbers of target residues (contact and the neighboring first-layer residues). This approach produces very good results when applied to dimers with high protein sequence length ratios. The protocol's ability to recognize near native decoys was compared to the ability of the residue-level statistical potential of Lu and Skolnick using the Sternberg and Vakser decoy dimers sets. The statistical potential produced better overall results, but in a number of cases its predicting ability was comparable, or even inferior, to the prediction ability of the adjustable GNM approach. The results presented in this paper suggest that in heterodimers at least one protein has interacting scaffold determined by the immovable, kinetically hot residues. In many cases, interacting proteins (especially if being of noticeably different sizes) either behave as a rigid lock and key or, presumably, exhibit the opposite dynamic behavior. While the binding surface of one protein is rigid and stable, its partner's interacting scaffold is more flexible and adaptable.

Accounting for epistatic interactions improves the functional analysis of protein structures

PubMed Central

Wilkins, Angela D.; Venner, Eric; Marciano, David C.; Erdin, Serkan; Atri, Benu; Lua, Rhonald C.; Lichtarge, Olivier

2013-01-01

Motivation: The constraints under which sequence, structure and function coevolve are not fully understood. Bringing this mutual relationship to light can reveal the molecular basis of binding, catalysis and allostery, thereby identifying function and rationally guiding protein redesign. Underlying these relationships are the epistatic interactions that occur when the consequences of a mutation to a protein are determined by the genetic background in which it occurs. Based on prior data, we hypothesize that epistatic forces operate most strongly between residues nearby in the structure, resulting in smooth evolutionary importance across the structure. Methods and Results: We find that when residue scores of evolutionary importance are distributed smoothly between nearby residues, functional site prediction accuracy improves. Accordingly, we designed a novel measure of evolutionary importance that focuses on the interaction between pairs of structurally neighboring residues. This measure that we term pair-interaction Evolutionary Trace yields greater functional site overlap and better structure-based proteome-wide functional predictions. Conclusions: Our data show that the structural smoothness of evolutionary importance is a fundamental feature of the coevolution of sequence, structure and function. Mutations operate on individual residues, but selective pressure depends in part on the extent to which a mutation perturbs interactions with neighboring residues. In practice, this principle led us to redefine the importance of a residue in terms of the importance of its epistatic interactions with neighbors, yielding better annotation of functional residues, motivating experimental validation of a novel functional site in LexA and refining protein function prediction. Contact: lichtarge@bcm.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24021383

Audio-visual biofeedback for respiratory-gated radiotherapy: Impact of audio instruction and audio-visual biofeedback on respiratory-gated radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

George, Rohini; Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, VA; Chung, Theodore D.

2006-07-01

Purpose: Respiratory gating is a commercially available technology for reducing the deleterious effects of motion during imaging and treatment. The efficacy of gating is dependent on the reproducibility within and between respiratory cycles during imaging and treatment. The aim of this study was to determine whether audio-visual biofeedback can improve respiratory reproducibility by decreasing residual motion and therefore increasing the accuracy of gated radiotherapy. Methods and Materials: A total of 331 respiratory traces were collected from 24 lung cancer patients. The protocol consisted of five breathing training sessions spaced about a week apart. Within each session the patients initially breathedmore » without any instruction (free breathing), with audio instructions and with audio-visual biofeedback. Residual motion was quantified by the standard deviation of the respiratory signal within the gating window. Results: Audio-visual biofeedback significantly reduced residual motion compared with free breathing and audio instruction. Displacement-based gating has lower residual motion than phase-based gating. Little reduction in residual motion was found for duty cycles less than 30%; for duty cycles above 50% there was a sharp increase in residual motion. Conclusions: The efficiency and reproducibility of gating can be improved by: incorporating audio-visual biofeedback, using a 30-50% duty cycle, gating during exhalation, and using displacement-based gating.« less

Residual determination and risk assessment of buprofezin in plum (Prunus domestica) grown in open-field conditions following the application of three different formulations.

PubMed

Kabir, Md Humayun; Abd El-Aty, A M; Kim, Sung-Woo; Lee, Han Sol; Rahman, Md Musfiqur; Lee, Young-Jun; Chung, Hyung Suk; Lieu, Truong; Choi, Jeong-Heui; Shin, Ho-Chul; Im, Geon-Jae; Hong, Su Myeong; Shim, Jae-Han

2016-11-01

This study was conducted to characterize the residual level and perform a risk assessment on buprofezin formulated as an emulsifiable concentrate, wettable powder, and suspension concentrate over various treatment schedules in plum (Prunus domestica). The samples were extracted with an AOAC quick, easy, cheap, effective, rugged, and safe, 'QuEChERS', method after major modifications. As intrinsic interferences were observed in blank plum samples following dispersive-solid phase extraction (consisting of primary secondary amine and C 18 sorbents), amino cartridges were used for solid-phase extraction. Analysis was carried out using liquid chromatography with diode array detection and confirmed by liquid chromatography-tandem mass spectrometry. The method showed excellent linearity with determination coefficient (R 2  = 1) and satisfactory recoveries (at two spiking levels, 0.5 and 2.5 mg/kg) between 90.98 and 94.74% with relative standard deviation (RSD) ≤8%. The limit of quantification (0.05 mg/kg) was considerably lower than the maximum residue limit (2 mg/kg) set by the Codex Alimentarius. Absolute residue levels for emulsifiable concentrates were highest, perhaps owing to the dilution rate and adjuvant. Notably, all formulation residues were lower than the maximum residue limit, and safety data proved that the fruits are safe for consumers. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

An analytical model to predict and minimize the residual stress of laser cladding process

NASA Astrophysics Data System (ADS)

Tamanna, N.; Crouch, R.; Kabir, I. R.; Naher, S.

2018-02-01

Laser cladding is one of the advanced thermal techniques used to repair or modify the surface properties of high-value components such as tools, military and aerospace parts. Unfortunately, tensile residual stresses generate in the thermally treated area of this process. This work focuses on to investigate the key factors for the formation of tensile residual stress and how to minimize it in the clad when using dissimilar substrate and clad materials. To predict the tensile residual stress, a one-dimensional analytical model has been adopted. Four cladding materials (Al2O3, TiC, TiO2, ZrO2) on the H13 tool steel substrate and a range of preheating temperatures of the substrate, from 300 to 1200 K, have been investigated. Thermal strain and Young's modulus are found to be the key factors of formation of tensile residual stresses. Additionally, it is found that using a preheating temperature of the substrate immediately before laser cladding showed the reduction of residual stress.

RCD+: Fast loop modeling server.

PubMed

López-Blanco, José Ramón; Canosa-Valls, Alejandro Jesús; Li, Yaohang; Chacón, Pablo

2016-07-08

Modeling loops is a critical and challenging step in protein modeling and prediction. We have developed a quick online service (http://rcd.chaconlab.org) for ab initio loop modeling combining a coarse-grained conformational search with a full-atom refinement. Our original Random Coordinate Descent (RCD) loop closure algorithm has been greatly improved to enrich the sampling distribution towards near-native conformations. These improvements include a new workflow optimization, MPI-parallelization and fast backbone angle sampling based on neighbor-dependent Ramachandran probability distributions. The server starts by efficiently searching the vast conformational space from only the loop sequence information and the environment atomic coordinates. The generated closed loop models are subsequently ranked using a fast distance-orientation dependent energy filter. Top ranked loops are refined with the Rosetta energy function to obtain accurate all-atom predictions that can be interactively inspected in an user-friendly web interface. Using standard benchmarks, the average root mean squared deviation (RMSD) is 0.8 and 1.4 Å for 8 and 12 residues loops, respectively, in the challenging modeling scenario in where the side chains of the loop environment are fully remodeled. These results are not only very competitive compared to those obtained with public state of the art methods, but also they are obtained ∼10-fold faster. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

A Malaria Ecology Index Predicted Spatial and Temporal Variation of Malaria Burden and Efficacy of Antimalarial Interventions Based on African Serological Data.

PubMed

McCord, Gordon C; Anttila-Hughes, Jesse K

2017-03-01

Reducing the global health burden of malaria is complicated by weak reporting systems for infectious diseases and a paucity of vital statistics registration. This limits our ability to predict changes in malaria health burden intensity, target antimalarial resources where needed, and identify malaria impacts in retrospective data. We refined and deployed a temporally and spatially varying Malaria Ecology Index (MEI) incorporating climatological and ecological data to estimate malaria transmission strength and validate it against cross-sectional serology data from 39,875 children from seven sub-Saharan African countries. The MEI is strongly associated with malaria burden; a 1 standard deviation higher MEI is associated with a 50-117% increase in malaria risk and a 3-5 g/dL lower level of Hg. Results show that the relationship between malaria ecology and disease burden is attenuated with sufficient coverage of insecticide treated nets (ITNs) or indoor residual spraying (IRS). Having both ITNs and IRS reduce the added risk from adverse malaria ecology conditions by half. Readily available climate and ecology data can be used to estimate the spatial and temporal variation in malaria disease burden, providing a feasible alternative to direct surveillance. This will help target resources for malaria programs in the absence of national coverage of active case detection systems, and facilitate malaria research using retrospective health data.

Liquid paraffin as new dilution medium for the analysis of high boiling point residual solvents with static headspace-gas chromatography.

PubMed

D'Autry, Ward; Zheng, Chao; Bugalama, John; Wolfs, Kris; Hoogmartens, Jos; Adams, Erwin; Wang, Bochu; Van Schepdael, Ann

2011-07-15

Residual solvents are volatile organic compounds which can be present in pharmaceutical substances. A generic static headspace-gas chromatography analysis method for the identification and control of residual solvents is described in the European Pharmacopoeia. Although this method is proved to be suitable for the majority of samples and residual solvents, the method may lack sensitivity for high boiling point residual solvents such as N,N-dimethylformamide, N,N-dimethylacetamide, dimethyl sulfoxide and benzyl alcohol. In this study, liquid paraffin was investigated as new dilution medium for the analysis of these residual solvents. The headspace-gas chromatography method was developed and optimized taking the official Pharmacopoeia method as a starting point. The optimized method was validated according to ICH criteria. It was found that the detection limits were below 1μg/vial for each compound, indicating a drastically increased sensitivity compared to the Pharmacopoeia method, which failed to detect the compounds at their respective limit concentrations. Linearity was evaluated based on the R(2) values, which were above 0.997 for all compounds, and inspection of residual plots. Instrument and method precision were examined by calculating the relative standard deviations (RSD) of repeated analyses within the linearity and accuracy experiments, respectively. It was found that all RSD values were below 10%. Accuracy was checked by a recovery experiment at three different levels. Mean recovery values were all in the range 95-105%. Finally, the optimized method was applied to residual DMSO analysis in four different Kollicoat(®) sample batches. Copyright © 2011 Elsevier B.V. All rights reserved.

SERS strategy based on the modified Au nanoparticles for highly sensitive detection of bisphenol A residues in milk.

PubMed

Yang, Libin; Chen, Yongliang; Shen, Yu; Yang, Ming; Li, Xiuling; Han, Xiaoxia; Jiang, Xin; Zhao, Bing

2018-03-01

Bisphenol A (BPA) is a highly toxic chemical, and its residue in milk product is threatening people's health due to its possible leaching from the packagings and cans with BPA coating. In this work, halides modified Au nanoparticles (NPs) as the modification substrates were first designed for rapid and sensitive determination of BPA residue in real milk by SERS method with the assistance of aggregation agents (Zn 2+ ). It can be concluded that Au NPs modification substrate with assistance of the aggregation agent can remarkably improve the detection sensitivity of BPA residue, which can significantly enhance the SERS signal of BPA and achieve the trace-level detection of BPA residue. Under the optimal conditions, the limit of detection of BPA residue can be as low as to 4.3 × 10 -9 mol/L (equal to 0.98 × 10 -3 mg/kg), which is much less than the standard of European Union (0.6mg/kg). And, there is a good linear relationship (R 2 = 0.990) between the intensity of SERS signal and the logarithm of BPA concentration in the range of 1.0 × 10 -8 -1.0 × 10 -3 mol/L. By this method, the recovery of BPA residue ranges from 89.5% to 100.2% with relative standard deviation between 4.6% and 2.7%. The proposed SERS method proves to be reliable, highly sensitive and possesses good reproducibility, which is very promising for sensitive detection of bisphenols residue in foodstuff. Copyright © 2017 Elsevier B.V. All rights reserved.

Bioinformatics analysis reveals biophysical and evolutionary insights into the 3-nitrotyrosine post-translational modification in the human proteome

PubMed Central

Ng, John Y.; Boelen, Lies; Wong, Jason W. H.

2013-01-01

Protein 3-nitrotyrosine is a post-translational modification that commonly arises from the nitration of tyrosine residues. This modification has been detected under a wide range of pathological conditions and has been shown to alter protein function. Whether 3-nitrotyrosine is important in normal cellular processes or is likely to affect specific biological pathways remains unclear. Using GPS-YNO2, a recently described 3-nitrotyrosine prediction algorithm, a set of predictions for nitrated residues in the human proteome was generated. In total, 9.27 per cent of the proteome was predicted to be nitratable (27 922/301 091). By matching the predictions against a set of curated and experimentally validated 3-nitrotyrosine sites in human proteins, it was found that GPS-YNO2 is able to predict 73.1 per cent (404/553) of these sites. Furthermore, of these sites, 42 have been shown to be nitrated endogenously, with 85.7 per cent (36/42) of these predicted to be nitrated. This demonstrates the feasibility of using the predicted dataset for a whole proteome analysis. A comprehensive bioinformatics analysis was subsequently performed on predicted and all experimentally validated nitrated tyrosine. This found mild but specific biophysical constraints that affect the susceptibility of tyrosine to nitration, and these may play a role in increasing the likelihood of 3-nitrotyrosine to affect processes, including phosphorylation and DNA binding. Furthermore, examining the evolutionary conservation of predicted 3-nitrotyrosine showed that, relative to non-nitrated tyrosine residues, 3-nitrotyrosine residues are generally less conserved. This suggests that, at least in the majority of cases, 3-nitrotyrosine is likely to have a deleterious effect on protein function and less likely to be important in normal cellular function. PMID:23389939

Development and application of a population physiologically based pharmacokinetic model for penicillin G in swine and cattle for food safety assessment.

PubMed

Li, Miao; Gehring, Ronette; Riviere, Jim E; Lin, Zhoumeng

2017-09-01

Penicillin G is a widely used antimicrobial in food-producing animals, and one of the most predominant drug residues in animal-derived food products. Due to reduced sensitivity of bacteria to penicillin, extralabel use of penicillin G is common, which may lead to violative residues in edible tissues and cause adverse reactions in consumers. This study aimed to develop a physiologically based pharmacokinetic (PBPK) model to predict drug residues in edible tissues and estimate extended withdrawal intervals for penicillin G in swine and cattle. A flow-limited PBPK model was developed with data from Food Animal Residue Avoidance Databank using Berkeley Madonna. The model predicted observed drug concentrations in edible tissues, including liver, muscle, and kidney for penicillin G both in swine and cattle well, including data not used in model calibration. For extralabel use (5× and 10× label dose) of penicillin G, Monte Carlo sampling technique was applied to predict times needed for tissue concentrations to fall below established tolerances for the 99th percentile of the population. This model provides a useful tool to predict tissue residues of penicillin G in swine and cattle to aid food safety assessment, and also provide a framework for extrapolation to other food animal species. Copyright © 2017 Elsevier Ltd. All rights reserved.

Incorporating a prediction of postgrazing herbage mass into a whole-farm model for pasture-based dairy systems.

PubMed

Gregorini, P; Galli, J; Romera, A J; Levy, G; Macdonald, K A; Fernandez, H H; Beukes, P C

2014-07-01

The DairyNZ whole-farm model (WFM; DairyNZ, Hamilton, New Zealand) consists of a framework that links component models for animal, pastures, crops, and soils. The model was developed to assist with analysis and design of pasture-based farm systems. New (this work) and revised (e.g., cow, pasture, crops) component models can be added to the WFM, keeping the model flexible and up to date. Nevertheless, the WFM does not account for plant-animal relationships determining herbage-depletion dynamics. The user has to preset the maximum allowable level of herbage depletion [i.e., postgrazing herbage mass (residuals)] throughout the year. Because residuals have a direct effect on herbage regrowth, the WFM in its current form does not dynamically simulate the effect of grazing pressure on herbage depletion and consequent effect on herbage regrowth. The management of grazing pressure is a key component of pasture-based dairy systems. Thus, the main objective of the present work was to develop a new version of the WFM able to predict residuals, and thereby simulate related effects of grazing pressure dynamically at the farm scale. This objective was accomplished by incorporating a new component model into the WFM. This model represents plant-animal relationships, for example sward structure and herbage intake rate, and resulting level of herbage depletion. The sensitivity of the new version of the WFM was evaluated and then the new WFM was tested against an experimental data set previously used to evaluate the WFM and to illustrate the adequacy and improvement of the model development. Key outputs variables of the new version pertinent to this work (milk production, herbage dry matter intake, intake rate, harvesting efficiency, and residuals) responded acceptably to a range of input variables. The relative prediction errors for monthly and mean annual residual predictions were 20 and 5%, respectively. Monthly predictions of residuals had a line bias (1.5%), with a proportion of square root of mean square prediction error (RMSPE) due to random error of 97.5%. Predicted monthly herbage growth rates had a line bias of 2%, a proportion of RMSPE due to random error of 96%, and a concordance correlation coefficient of 0.87. Annual herbage production was predicted with an RMSPE of 531 (kg of herbage dry matter/ha per year), a line bias of 11%, a proportion of RMSPE due to random error of 80%, and relative prediction errors of 2%. Annual herbage dry matter intake per cow and hectare, both per year, were predicted with RMSPE, relative prediction error, and concordance correlation coefficient of 169 and 692kg of dry matter, 3 and 4%, and 0.91 and 0.87, respectively. These results indicate that predictions of the new WFM are relatively accurate and precise, with a conclusion that incorporating a plant-animal relationship model into the WFM allows for dynamic predictions of residuals and more realistic simulations of the effect of grazing pressure on herbage production and intake at the farm level without the intervention from the user. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Turbulent current drive mechanisms

NASA Astrophysics Data System (ADS)

McDevitt, Christopher J.; Tang, Xian-Zhu; Guo, Zehua

2017-08-01

Mechanisms through which plasma microturbulence can drive a mean electron plasma current are derived. The efficiency through which these turbulent contributions can drive deviations from neoclassical predictions of the electron current profile is computed by employing a linearized Coulomb collision operator. It is found that a non-diffusive contribution to the electron momentum flux as well as an anomalous electron-ion momentum exchange term provide the most efficient means through which turbulence can modify the mean electron current for the cases considered. Such turbulent contributions appear as an effective EMF within Ohm's law and hence provide an ideal means for driving deviations from neoclassical predictions.

Measures of Residual Risk with Connections to Regression, Risk Tracking, Surrogate Models, and Ambiguity

DTIC Science & Technology

2015-01-07

vector that helps to manage , predict, and mitigate the risk in the original variable. Residual risk can be exemplified as a quantification of the improved... the random variable of interest is viewed in concert with a related random vector that helps to manage , predict, and mitigate the risk in the original...measures of risk. They view a random variable of interest in concert with an auxiliary random vector that helps to manage , predict and mitigate the risk

Design for the optical retardation in broadband zero-order half-wave plates.

PubMed

Liu, Jin; Cai, Yi; Chen, Hongyi; Zeng, Xuanke; Zou, Da; Xu, Shixiang

2011-04-25

This paper presents a novel design for broadband zero-order half-wave plates to eliminate the first-order or up to second-order wavelength-dependent birefringent phase retardation (BPR) with 2 or 3 different birefringent materials. The residual BPRs of the plates increase monotonously with the wavelength deviation from a selected wavelength, so the plates are applicable to the broadband light pulses which gather most of the light energy around their central wavelengths. The model chooses the materials by the birefringent dispersion coefficient and evaluates the performances of the plates by the weighted average of the absolute value of residual BPR in order to emphasize the contributions of the incident spectral components whose possess higher energies.

CCD observations of Phoebe

NASA Astrophysics Data System (ADS)

Veiga, C. H.; Vieira Martins, R.; Andrei, A. H.

2000-02-01

Astromeric CCD positions of the Saturnian satellite Phoebe obtained from 60 frames taken in 10 nights are presented. The observations were distributed between 5 missions in the years 1995 to 1997. For the astrometric calibration the USNO-A2.0 Catalogue is used. All positions are compared with those calculated by Jacobson (1998a) and Bec-Borsenberger & Rocher (1982). The residuals have mean and standard deviation smaller than 0farcs 5, in the x and y directions. The distribution of residuals is suggestive of the need of an improvement for the orbit calculations. Based on observations made at Laboratório Nacional de Astrofísica/CNPq/MCT-Itajubá-Brazil. Please send offprint requests to C.H. Veiga. Table 1 is only available at http://www.edpsciences.org

Validating a Model for Welding Induced Residual Stress Using High-Energy X-ray Diffraction

DOE PAGES

Mach, J. C.; Budrow, C. J.; Pagan, D. C.; ...

2017-03-15

Integrated computational materials engineering (ICME) provides a pathway to advance performance in structures through the use of physically-based models to better understand how manufacturing processes influence product performance. As one particular challenge, consider that residual stresses induced in fabrication are pervasive and directly impact the life of structures. For ICME to be an effective strategy, it is essential that predictive capability be developed in conjunction with critical experiments. In the present paper, simulation results from a multi-physics model for gas metal arc welding are evaluated through x-ray diffraction using synchrotron radiation. A test component was designed with intent to developmore » significant gradients in residual stress, be representative of real-world engineering application, yet remain tractable for finely spaced strain measurements with positioning equipment available at synchrotron facilities. Finally, the experimental validation lends confidence to model predictions, facilitating the explicit consideration of residual stress distribution in prediction of fatigue life.« less

Validating a Model for Welding Induced Residual Stress Using High-Energy X-ray Diffraction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mach, J. C.; Budrow, C. J.; Pagan, D. C.

Integrated computational materials engineering (ICME) provides a pathway to advance performance in structures through the use of physically-based models to better understand how manufacturing processes influence product performance. As one particular challenge, consider that residual stresses induced in fabrication are pervasive and directly impact the life of structures. For ICME to be an effective strategy, it is essential that predictive capability be developed in conjunction with critical experiments. In the present paper, simulation results from a multi-physics model for gas metal arc welding are evaluated through x-ray diffraction using synchrotron radiation. A test component was designed with intent to developmore » significant gradients in residual stress, be representative of real-world engineering application, yet remain tractable for finely spaced strain measurements with positioning equipment available at synchrotron facilities. Finally, the experimental validation lends confidence to model predictions, facilitating the explicit consideration of residual stress distribution in prediction of fatigue life.« less

A New Hybrid Spatio-temporal Model for Estimating Daily Multi-year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

NASA Technical Reports Server (NTRS)

Kloog, Itai; Chudnovsky, Alexandra A.; Just, Allan C.; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A.; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

2014-01-01

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter PM(sub 2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data.We developed and cross validated models to predict daily PM(sub 2.5) at a 1X 1 km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1 X 1 km grid predictions. We used mixed models regressing PM(sub 2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R(sup 2) = 0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R(sup 2) = 0.87, R(sup)2 = 0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

A New Hybrid Spatio-Temporal Model For Estimating Daily Multi-Year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data.

PubMed

Kloog, Itai; Chudnovsky, Alexandra A; Just, Allan C; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

2014-10-01

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter (PM 2.5 ) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data. We developed and cross validated models to predict daily PM 2.5 at a 1×1km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1×1 km grid predictions. We used mixed models regressing PM 2.5 measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R 2 =0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R 2 =0.87, R 2 =0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

A New Hybrid Spatio-Temporal Model For Estimating Daily Multi-Year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

PubMed Central

Kloog, Itai; Chudnovsky, Alexandra A.; Just, Allan C.; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A.; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

2017-01-01

Background The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter (PM2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. Methods We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data. We developed and cross validated models to predict daily PM2.5 at a 1×1km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003–2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1×1 km grid predictions. We used mixed models regressing PM2.5 measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Results Our model performance was excellent (mean out-of-sample R2=0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R2=0.87, R2=0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Conclusion Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region. PMID:28966552

Prediction of Carcass Composition Using Carcass Grading Traits in Hanwoo Steers.

PubMed

Lee, Jooyoung; Won, Seunggun; Lee, Jeongkoo; Kim, Jongbok

2016-09-01

The prediction of carcass composition in Hanwoo steers is very important for value-based marketing, and the improvement of prediction accuracy and precision can be achieved through the analyses of independent variables using a prediction equation with a sufficient dataset. The present study was conducted to develop a prediction equation for Hanwoo carcass composition for which data was collected from 7,907 Hanwoo steers raised at a private farm in Gangwon Province, South Korea, and slaughtered in the period between January 2009 and September 2014. Carcass traits such as carcass weight (CWT), back fat thickness (BFT), eye-muscle area (EMA), and marbling score (MAR) were used as independent variables for the development of a prediction equation for carcass composition, such as retail cut weight and percentage (RC, and %RC, respectively), trimmed fat weight and percentage (FAT, and %FAT, respectively), and separated bone weight and percentage (BONE, and %BONE), and its feasibility for practical use was evaluated using the estimated retail yield percentage (ELP) currently used in Korea. The equations were functions of all the variables, and the significance was estimated via stepwise regression analyses. Further, the model equations were verified by means of the residual standard deviation and the coefficient of determination (R(2)) between the predicted and observed values. As the results of stepwise analyses, CWT was the most important single variable in the equation for RC and FAT, and BFT was the most important variable for the equation of %RC and %FAT. The precision and accuracy of three variable equation consisting CWT, BFT, and EMA were very similar to those of four variable equation that included all for independent variables (CWT, BFT, EMA, and MAR) in RC and FAT, while the three variable equations provided a more accurate prediction for %RC. Consequently, the three-variable equation might be more appropriate for practical use than the four-variable equation based on its easy and cost-effective measurement. However, a relatively high average difference for the ELP in absolute value implies a revision of the official equation may be required, although the current official equation for predicting RC with three variables is still valid.

Protein contact prediction using patterns of correlation.

PubMed

Hamilton, Nicholas; Burrage, Kevin; Ragan, Mark A; Huber, Thomas

2004-09-01

We describe a new method for using neural networks to predict residue contact pairs in a protein. The main inputs to the neural network are a set of 25 measures of correlated mutation between all pairs of residues in two "windows" of size 5 centered on the residues of interest. While the individual pair-wise correlations are a relatively weak predictor of contact, by training the network on windows of correlation the accuracy of prediction is significantly improved. The neural network is trained on a set of 100 proteins and then tested on a disjoint set of 1033 proteins of known structure. An average predictive accuracy of 21.7% is obtained taking the best L/2 predictions for each protein, where L is the sequence length. Taking the best L/10 predictions gives an average accuracy of 30.7%. The predictor is also tested on a set of 59 proteins from the CASP5 experiment. The accuracy is found to be relatively consistent across different sequence lengths, but to vary widely according to the secondary structure. Predictive accuracy is also found to improve by using multiple sequence alignments containing many sequences to calculate the correlations. Copyright 2004 Wiley-Liss, Inc.

Functional region prediction with a set of appropriate homologous sequences-an index for sequence selection by integrating structure and sequence information with spatial statistics

PubMed Central

2012-01-01

Background The detection of conserved residue clusters on a protein structure is one of the effective strategies for the prediction of functional protein regions. Various methods, such as Evolutionary Trace, have been developed based on this strategy. In such approaches, the conserved residues are identified through comparisons of homologous amino acid sequences. Therefore, the selection of homologous sequences is a critical step. It is empirically known that a certain degree of sequence divergence in the set of homologous sequences is required for the identification of conserved residues. However, the development of a method to select homologous sequences appropriate for the identification of conserved residues has not been sufficiently addressed. An objective and general method to select appropriate homologous sequences is desired for the efficient prediction of functional regions. Results We have developed a novel index to select the sequences appropriate for the identification of conserved residues, and implemented the index within our method to predict the functional regions of a protein. The implementation of the index improved the performance of the functional region prediction. The index represents the degree of conserved residue clustering on the tertiary structure of the protein. For this purpose, the structure and sequence information were integrated within the index by the application of spatial statistics. Spatial statistics is a field of statistics in which not only the attributes but also the geometrical coordinates of the data are considered simultaneously. Higher degrees of clustering generate larger index scores. We adopted the set of homologous sequences with the highest index score, under the assumption that the best prediction accuracy is obtained when the degree of clustering is the maximum. The set of sequences selected by the index led to higher functional region prediction performance than the sets of sequences selected by other sequence-based methods. Conclusions Appropriate homologous sequences are selected automatically and objectively by the index. Such sequence selection improved the performance of functional region prediction. As far as we know, this is the first approach in which spatial statistics have been applied to protein analyses. Such integration of structure and sequence information would be useful for other bioinformatics problems. PMID:22643026

Testing long-period ground-motion simulations of scenario earthquakes using the Mw 7.2 El Mayor-Cucapah mainshock: Evaluation of finite-fault rupture characterization and 3D seismic velocity models

USGS Publications Warehouse

Graves, Robert W.; Aagaard, Brad T.

2011-01-01

Using a suite of five hypothetical finite-fault rupture models, we test the ability of long-period (T>2.0 s) ground-motion simulations of scenario earthquakes to produce waveforms throughout southern California consistent with those recorded during the 4 April 2010 Mw 7.2 El Mayor-Cucapah earthquake. The hypothetical ruptures are generated using the methodology proposed by Graves and Pitarka (2010) and require, as inputs, only a general description of the fault location and geometry, event magnitude, and hypocenter, as would be done for a scenario event. For each rupture model, two Southern California Earthquake Center three-dimensional community seismic velocity models (CVM-4m and CVM-H62) are used, resulting in a total of 10 ground-motion simulations, which we compare with recorded ground motions. While the details of the motions vary across the simulations, the median levels match the observed peak ground velocities reasonably well, with the standard deviation of the residuals generally within 50% of the median. Simulations with the CVM-4m model yield somewhat lower variance than those with the CVM-H62 model. Both models tend to overpredict motions in the San Diego region and underpredict motions in the Mojave desert. Within the greater Los Angeles basin, the CVM-4m model generally matches the level of observed motions, whereas the CVM-H62 model tends to overpredict the motions, particularly in the southern portion of the basin. The variance in the peak velocity residuals is lowest for a rupture that has significant shallow slip (<5 km depth), whereas the variance in the residuals is greatest for ruptures with large asperities below 10 km depth. Overall, these results are encouraging and provide confidence in the predictive capabilities of the simulation methodology, while also suggesting some regions in which the seismic velocity models may need improvement.

Sample preparation for total reflection X-ray fluorescence analysis using resist pattern technique

NASA Astrophysics Data System (ADS)

Tsuji, K.; Yomogita, N.; Konyuba, Y.

2018-06-01

A circular resist pattern layer with a diameter of 9 mm was prepared on a glass substrate (26 mm × 76 mm; 1.5 mm thick) for total reflection X-ray fluorescence (TXRF) analysis. The parallel cross pattern was designed with a wall thickness of 10 μm, an interval of 20 μm, and a height of 1.4 or 0.8 μm. This additional resist layer did not significantly increase background intensity on the XRF peaks in TXRF spectra. Dotted residue was obtained from a standard solution (10 μL) containing Ti, Cr, Ni, Pb, and Ga, each at a final concentration of 10 ppm, on a normal glass substrate with a silicone coating layer. The height of the residue was more than 100 μm, where self-absorption in the large residue affected TXRF quantification (intensity relative standard deviation (RSD): 12-20%). In contrast, from a droplet composed of a small volume of solution dropped and cast on the resist pattern structure, the obtained residue was not completely film but a film-like residue with a thickness less than 1 μm, where self-absorption was not a serious problem. In the end, this sample preparation was demonstrated to improve TXRF quantification (intensity RSD: 2-4%).

Dissipation and Residues of Pyrethrins in Leaf Lettuce under Greenhouse and Open Field Conditions

PubMed Central

Pan, Lixiang; Feng, Xiaoxiao; Zhang, Hongyan

2017-01-01

Pyrethrins are nowadays widely used for prevention and control of insects in leaf lettuce. However, there is a concern about the pesticide residue in leaf lettuce. A reliable analytical method for determination of pyrethrins (pyrethrin—and П, cinerin І and П, and jasmolin І and П) in leaf lettuce was developed by using gas chromatography–mass spectrometry (GC–MS). Recoveries of pyrethrins in leaf lettuce at three spiking levels were 99.4–104.0% with relative standard deviations of 0.9–3.1% (n = 5). Evaluation of dissipation and final residues of pyrethrins in leaf lettuce were determined at six different locations, including the open field, as well as under greenhouse conditions. The initial concentration of pyrethrins in greenhouse (0.57 mg/kg) was higher than in open field (0.25 mg/kg) and the half-life for pyrethrins disappearance in field lettuce (0.7 days) was less than that greenhouse lettuce (1.1 days). Factors such as rainfall, solar radiation, wind speed, and crop growth rate are likely to have caused these results. The final residue in leaf lettuce was far below the maximum residue limits (MRLs) (1 mg/kg established by the European Union (EU), Australia, Korea, Japan). PMID:28754023

Prediction of vitamin interacting residues in a vitamin binding protein using evolutionary information

PubMed Central

2013-01-01

Background The vitamins are important cofactors in various enzymatic-reactions. In past, many inhibitors have been designed against vitamin binding pockets in order to inhibit vitamin-protein interactions. Thus, it is important to identify vitamin interacting residues in a protein. It is possible to detect vitamin-binding pockets on a protein, if its tertiary structure is known. Unfortunately tertiary structures of limited proteins are available. Therefore, it is important to develop in-silico models for predicting vitamin interacting residues in protein from its primary structure. Results In this study, first we compared protein-interacting residues of vitamins with other ligands using Two Sample Logo (TSL). It was observed that ATP, GTP, NAD, FAD and mannose preferred {G,R,K,S,H}, {G,K,T,S,D,N}, {T,G,Y}, {G,Y,W} and {Y,D,W,N,E} residues respectively, whereas vitamins preferred {Y,F,S,W,T,G,H} residues for the interaction with proteins. Furthermore, compositional information of preferred and non-preferred residues along with patterns-specificity was also observed within different vitamin-classes. Vitamins A, B and B6 preferred {F,I,W,Y,L,V}, {S,Y,G,T,H,W,N,E} and {S,T,G,H,Y,N} interacting residues respectively. It suggested that protein-binding patterns of vitamins are different from other ligands, and motivated us to develop separate predictor for vitamins and their sub-classes. The four different prediction modules, (i) vitamin interacting residues (VIRs), (ii) vitamin-A interacting residues (VAIRs), (iii) vitamin-B interacting residues (VBIRs) and (iv) pyridoxal-5-phosphate (vitamin B6) interacting residues (PLPIRs) have been developed. We applied various classifiers of SVM, BayesNet, NaiveBayes, ComplementNaiveBayes, NaiveBayesMultinomial, RandomForest and IBk etc., as machine learning techniques, using binary and Position-Specific Scoring Matrix (PSSM) features of protein sequences. Finally, we selected best performing SVM modules and obtained highest MCC of 0.53, 0.48, 0.61, 0.81 for VIRs, VAIRs, VBIRs, PLPIRs respectively, using PSSM-based evolutionary information. All the modules developed in this study have been trained and tested on non-redundant datasets and evaluated using five-fold cross-validation technique. The performances were also evaluated on the balanced and different independent datasets. Conclusions This study demonstrates that it is possible to predict VIRs, VAIRs, VBIRs and PLPIRs from evolutionary information of protein sequence. In order to provide service to the scientific community, we have developed web-server and standalone software VitaPred (http://crdd.osdd.net/raghava/vitapred/). PMID:23387468

Prediction of vitamin interacting residues in a vitamin binding protein using evolutionary information.

PubMed

Panwar, Bharat; Gupta, Sudheer; Raghava, Gajendra P S

2013-02-07

The vitamins are important cofactors in various enzymatic-reactions. In past, many inhibitors have been designed against vitamin binding pockets in order to inhibit vitamin-protein interactions. Thus, it is important to identify vitamin interacting residues in a protein. It is possible to detect vitamin-binding pockets on a protein, if its tertiary structure is known. Unfortunately tertiary structures of limited proteins are available. Therefore, it is important to develop in-silico models for predicting vitamin interacting residues in protein from its primary structure. In this study, first we compared protein-interacting residues of vitamins with other ligands using Two Sample Logo (TSL). It was observed that ATP, GTP, NAD, FAD and mannose preferred {G,R,K,S,H}, {G,K,T,S,D,N}, {T,G,Y}, {G,Y,W} and {Y,D,W,N,E} residues respectively, whereas vitamins preferred {Y,F,S,W,T,G,H} residues for the interaction with proteins. Furthermore, compositional information of preferred and non-preferred residues along with patterns-specificity was also observed within different vitamin-classes. Vitamins A, B and B6 preferred {F,I,W,Y,L,V}, {S,Y,G,T,H,W,N,E} and {S,T,G,H,Y,N} interacting residues respectively. It suggested that protein-binding patterns of vitamins are different from other ligands, and motivated us to develop separate predictor for vitamins and their sub-classes. The four different prediction modules, (i) vitamin interacting residues (VIRs), (ii) vitamin-A interacting residues (VAIRs), (iii) vitamin-B interacting residues (VBIRs) and (iv) pyridoxal-5-phosphate (vitamin B6) interacting residues (PLPIRs) have been developed. We applied various classifiers of SVM, BayesNet, NaiveBayes, ComplementNaiveBayes, NaiveBayesMultinomial, RandomForest and IBk etc., as machine learning techniques, using binary and Position-Specific Scoring Matrix (PSSM) features of protein sequences. Finally, we selected best performing SVM modules and obtained highest MCC of 0.53, 0.48, 0.61, 0.81 for VIRs, VAIRs, VBIRs, PLPIRs respectively, using PSSM-based evolutionary information. All the modules developed in this study have been trained and tested on non-redundant datasets and evaluated using five-fold cross-validation technique. The performances were also evaluated on the balanced and different independent datasets. This study demonstrates that it is possible to predict VIRs, VAIRs, VBIRs and PLPIRs from evolutionary information of protein sequence. In order to provide service to the scientific community, we have developed web-server and standalone software VitaPred (http://crdd.osdd.net/raghava/vitapred/).

Use of Standard Deviations as Predictors in Models Using Large-Scale International Data Sets

ERIC Educational Resources Information Center

Austin, Bruce; French, Brian; Adesope, Olusola; Gotch, Chad

2017-01-01

Measures of variability are successfully used in predictive modeling in research areas outside of education. This study examined how standard deviations can be used to address research questions not easily addressed using traditional measures such as group means based on index variables. Student survey data were obtained from the Organisation for…

Screen Twice, Cut Once: Assessing the Predictive Validity of Teacher Selection Tools

ERIC Educational Resources Information Center

Goldhaber, Dan; Grout, Cyrus; Huntington-Klein, Nick

2015-01-01

It is well documented that teachers can have profound effects on student outcomes. Empirical estimates find that a one standard deviation increase in teacher quality raises student test achievement by 10 to 25 percent of a standard deviation. More recent evidence shows that the effectiveness of teachers can affect long-term student outcomes, such…

Chemometric quality inspection control of pyrantel pamoate, febantel and praziquantel in veterinary tablets by mid infrared spectroscopy

NASA Astrophysics Data System (ADS)

Piantavini, Mário S.; Pontes, Flávia L. D.; Uber, Caroline P.; Stremel, Dile P.; Sena, Marcelo M.; Pontarolo, Roberto

This paper describes the development and validation of a new multivariate calibration method based on diffuse reflectance mid infrared spectroscopy for direct and simultaneous determination of three veterinary pharmaceutical drugs, pyrantel pamoate, praziquantel and febantel, in commercial tablets. The best synergy interval partial least squares (siPLS) model was obtained by selecting three spectral regions, 3715-3150, 2865-2583, and 2298-1733 cm-1, preprocessed by first derivative and Savitzky-Golay smoothing followed by mean centering. This model was built with five latent variables and provided root mean square errors of prediction (RMSEP) equal or lower than 0.69 mg per 100 mg of powder for the three analytes. The method was validated according the appropriate regulations through the estimate of figures of merit, such as trueness, precision, linearity, analytical sensitivity, bias and residual prediction deviation (RPD). Then, it was applied to three different veterinary pharmaceutical formulations found in the Brazilian market, in a situation of multi-product calibration, since the excipient composition of these commercial products, which was not known a priori, was modeled by an experimental design that scanned the likely content range of the possible constituents. The results were verified with high performance liquid chromatography with diode array detection (HPLC-DAD) and high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) and were in agreement with the predicted values at 95% confidence level. The developed method presented the advantages of being simple, rapid, solvent free, and about ten times faster than the HPLC ones.

Variations in toxicity of semi-coking wastewater treatment processes and their toxicity prediction.

PubMed

Ma, Xiaoyan; Wang, Xiaochang; Liu, Yongjun; Gao, Jian; Wang, Yongkun

2017-04-01

Chemical analyses and bioassays using Vibrio fischeri and Daphnia magna were conducted to evaluate comprehensively the variation of biotoxicity caused by contaminants in wastewater from a semi-coking wastewater treatment plant (WWTP). Pretreatment units (including an oil-water separator, a phenols extraction tower, an ammonia stripping tower, and a regulation tank) followed by treatment units (including anaerobic-oxic treatment units, coagulation-sedimentation treatment units, and an active carbon adsorption column) were employed in the semi-coking WWTP. Five benzenes, 11 phenols, and five polycyclic aromatic hydrocarbons (PAHs) were investigated as the dominant contaminants in semi-coking wastewater. Because of residual extractant, the phenols extraction process increased acute toxicity to V. fischeri and immobilization and lethal toxicity to D. magna. The acute toxicity of pretreated wastewater to V. fischeri was still higher than that of raw semi-coking wastewater, even though 90.0% of benzenes, 94.8% of phenols, and 81.0% of PAHs were removed. After wastewater pretreatment, phenols and PAHs were mainly removed by anaerobic-oxic and coagulation-sedimentation treatment processes respectively, and a subsequent active carbon adsorption process further reduced the concentrations of all target chemicals to below detection limits. An effective biotoxicity reduction was found during the coagulation-sedimentation and active carbon adsorption treatment processes. The concentration addition model can be applied for toxicity prediction of wastewater from the semi-coking WWTP. The deviation between the measured and predicted toxicity results may result from the effects of compounds not detectable by instrumental analyses, the synergistic effect of detected contaminants, or possible transformation products. Copyright © 2016. Published by Elsevier Inc.

Modeling global macroclimatic constraints on ectotherm energy budgets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grant, B.W.; Porter, W.P.

1992-12-31

The authors describe a mechanistic individual-based model of how global macroclimatic constraints affect the energy budgets of ectothermic animals. The model uses macroclimatic and biophysical characters of the habitat and organism and tenets of heat transfer theory to calculate hourly temperature availabilities over a year. Data on the temperature dependence of activity rate, metabolism, food consumption and food processing capacity are used to estimate the net rate of resource assimilation which is then integrated over time. They present a new test of this model in which they show that the predicted energy budget sizes for 11 populations of the lizardmore » Sceloporus undulates are in close agreement with observed results from previous field studies. This demonstrates that model tests rae feasible and the results are reasonable. Further, since the model represents an upper bound to the size of the energy budget, observed residual deviations form explicit predictions about the effects of environmental constraints on the bioenergetics of the study lizards within each site that may be tested by future field and laboratory studies. Three major new improvements to the modeling are discussed. They present a means to estimate microclimate thermal heterogeneity more realistically and include its effects on field rates of individual activity and food consumption. Second, they describe an improved model of digestive function involving batch processing of consumed food. Third, they show how optimality methods (specifically the methods of stochastic dynamic programming) may be included to model the fitness consequences of energy allocation decisions subject to food consumption and processing constraints which are predicted from the microclimate and physiological modeling.« less

Chemometric quality inspection control of pyrantel pamoate, febantel and praziquantel in veterinary tablets by mid infrared spectroscopy.

PubMed

Piantavini, Mário S; Pontes, Flávia L D; Uber, Caroline P; Stremel, Dile P; Sena, Marcelo M; Pontarolo, Roberto

2014-05-05

This paper describes the development and validation of a new multivariate calibration method based on diffuse reflectance mid infrared spectroscopy for direct and simultaneous determination of three veterinary pharmaceutical drugs, pyrantel pamoate, praziquantel and febantel, in commercial tablets. The best synergy interval partial least squares (siPLS) model was obtained by selecting three spectral regions, 3715-3150, 2865-2583, and 2298-1733 cm(-1), preprocessed by first derivative and Savitzky-Golay smoothing followed by mean centering. This model was built with five latent variables and provided root mean square errors of prediction (RMSEP) equal or lower than 0.69 mg per 100 mg of powder for the three analytes. The method was validated according the appropriate regulations through the estimate of figures of merit, such as trueness, precision, linearity, analytical sensitivity, bias and residual prediction deviation (RPD). Then, it was applied to three different veterinary pharmaceutical formulations found in the Brazilian market, in a situation of multi-product calibration, since the excipient composition of these commercial products, which was not known a priori, was modeled by an experimental design that scanned the likely content range of the possible constituents. The results were verified with high performance liquid chromatography with diode array detection (HPLC-DAD) and high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) and were in agreement with the predicted values at 95% confidence level. The developed method presented the advantages of being simple, rapid, solvent free, and about ten times faster than the HPLC ones. Copyright © 2014 Elsevier B.V. All rights reserved.

A methodology to predict damage initiation, damage growth and residual strength in titanium matrix composites

NASA Technical Reports Server (NTRS)

Bakuckas, J. G., Jr.; Johnson, W. S.

1994-01-01

In this research, a methodology to predict damage initiation, damage growth, fatigue life, and residual strength in titanium matrix composites (TMC) is outlined. Emphasis was placed on micromechanics-based engineering approaches. Damage initiation was predicted using a local effective strain approach. A finite element analysis verified the prevailing assumptions made in the formulation of this model. Damage growth, namely, fiber-bridged matrix crack growth, was evaluated using a fiber bridging (FB) model which accounts for thermal residual stresses. This model combines continuum fracture mechanics and micromechanics analyses yielding stress-intensity factor solutions for fiber-bridged matrix cracks. It is assumed in the FB model that fibers in the wake of the matrix crack are idealized as a closure pressure, and an unknown constant frictional shear stress is assumed to act along the debond length of the bridging fibers. This frictional shear stress was used as a curve fitting parameter to the available experimental data. Fatigue life and post-fatigue residual strength were predicted based on the axial stress in the first intact 0 degree fiber calculated using the FB model and a three-dimensional finite element analysis.

Practical guidance on representing the heteroscedasticity of residual errors of hydrological predictions

NASA Astrophysics Data System (ADS)

McInerney, David; Thyer, Mark; Kavetski, Dmitri; Kuczera, George

2016-04-01

Appropriate representation of residual errors in hydrological modelling is essential for accurate and reliable probabilistic streamflow predictions. In particular, residual errors of hydrological predictions are often heteroscedastic, with large errors associated with high runoff events. Although multiple approaches exist for representing this heteroscedasticity, few if any studies have undertaken a comprehensive evaluation and comparison of these approaches. This study fills this research gap by evaluating a range of approaches for representing heteroscedasticity in residual errors. These approaches include the 'direct' weighted least squares approach and 'transformational' approaches, such as logarithmic, Box-Cox (with and without fitting the transformation parameter), logsinh and the inverse transformation. The study reports (1) theoretical comparison of heteroscedasticity approaches, (2) empirical evaluation of heteroscedasticity approaches using a range of multiple catchments / hydrological models / performance metrics and (3) interpretation of empirical results using theory to provide practical guidance on the selection of heteroscedasticity approaches. Importantly, for hydrological practitioners, the results will simplify the choice of approaches to represent heteroscedasticity. This will enhance their ability to provide hydrological probabilistic predictions with the best reliability and precision for different catchment types (e.g. high/low degree of ephemerality).

A perturbative approach for enhancing the performance of time series forecasting.

PubMed

de Mattos Neto, Paulo S G; Ferreira, Tiago A E; Lima, Aranildo R; Vasconcelos, Germano C; Cavalcanti, George D C

2017-04-01

This paper proposes a method to perform time series prediction based on perturbation theory. The approach is based on continuously adjusting an initial forecasting model to asymptotically approximate a desired time series model. First, a predictive model generates an initial forecasting for a time series. Second, a residual time series is calculated as the difference between the original time series and the initial forecasting. If that residual series is not white noise, then it can be used to improve the accuracy of the initial model and a new predictive model is adjusted using residual series. The whole process is repeated until convergence or the residual series becomes white noise. The output of the method is then given by summing up the outputs of all trained predictive models in a perturbative sense. To test the method, an experimental investigation was conducted on six real world time series. A comparison was made with six other methods experimented and ten other results found in the literature. Results show that not only the performance of the initial model is significantly improved but also the proposed method outperforms the other results previously published. Copyright © 2017 Elsevier Ltd. All rights reserved.

figure1.nc

EPA Pesticide Factsheets

NetCDF file of the SREF standard deviation of wind speed and direction that was used to inject variability in the FDDA input.variable U_NDG_OLD contains standard deviation of wind speed (m/s)variable V_NDG_OLD contains the standard deviation of wind direction (deg)This dataset is associated with the following publication:Gilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259–12,280, (2015).

Prediction of moisture variation during composting process: A comparison of mathematical models.

PubMed

Wang, Yongjiang; Ai, Ping; Cao, Hongliang; Liu, Zhigang

2015-10-01

This study was carried out to develop and compare three models for simulating the moisture content during composting. Model 1 described changes in water content using mass balance, while Model 2 introduced a liquid-gas transferred water term. Model 3 predicted changes in moisture content without complex degradation kinetics. Average deviations for Model 1-3 were 8.909, 7.422 and 5.374 kg m(-3) while standard deviations were 10.299, 8.374 and 6.095, respectively. The results showed that Model 1 is complex and involves more state variables, but can be used to reveal the effect of humidity on moisture content. Model 2 tested the hypothesis of liquid-gas transfer and was shown to be capable of predicting moisture content during composting. Model 3 could predict water content well without considering degradation kinetics. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fatigue of graphite/epoxy /0/90/45/-45/s laminates under dual stress levels

NASA Technical Reports Server (NTRS)

Yang, J. N.; Jones, D. L.

1982-01-01

A model for the prediction of loading sequence effects on the statistical distribution of fatigue life and residual strength in composite materials is generalized and applied to (0/90/45/-45)s graphite/epoxy laminates. Load sequence effects are found to be caused by both the difference in residual strength when failure occurs (boundary effect) and the effect of previously applied loads (memory effect). The model allows the isolation of these two effects, and the estimation of memory effect magnitudes under dual fatigue loading levels. It is shown that the material memory effect is insignificant, and that correlations between predictions of the number of early failures agree with the verification tests, as do predictions of fatigue life and residual strength degradation under dual stress levels.

Body Composition Predicts Growth in Infants and Toddlers With Chronic Liver Disease.

PubMed

Hurtado-López, Erika F; Vásquez-Garibay, Edgar M; Trujillo, Xóchitl; Larrosa-Haro, Alfredo

2017-12-01

This cross-sectional study was conducted on 15 infants and toddlers with chronic liver disease to validate arm anthropometry as an accurate measure of body composition (BC) compared to dual-energy x-ray absorptiometry and to predict growth from BC. The z score means of the anthropometric indicators were <-2 standard deviation, except for body fat index and subscapular skinfold, which were between -2 and +2 standard deviation. Fat mass was predicted by arm adiposity indicators and fat-free mass by arm muscle area. Bone mineral content explained 87% of variation in length. Two multiple regression models predicted length: 1 with fat mass plus fat-free mass; and the second with fat mass and bone mineral content. These observations suggest that arm anthropometry is a useful tool to estimate BC and the nutritional status in infants and toddlers with chronic liver disease. Length and head circumference can be predicted by fat mass, fat-free mass, and bone mineral content.

Mass predictions of atomic nuclei in the infinite nuclear matter model

NASA Astrophysics Data System (ADS)

Nayak, R. C.; Satpathy, L.

2012-07-01

We present here the mass excesses, binding energies, one- and two-neutron, one- and two-proton and α-particle separation energies of 6727 nuclei in the ranges 4≤Z≤120 and 8≤A≤303 calculated in the infinite nuclear matter model. Compared to our predictions of 1999 mass table, the present ones are obtained using larger data base of 2003 mass table of Wapstra and Audi and resorting to higher accuracy in the solutions of the η-differential equations of the INM model. The local energy η's supposed to carry signature of the characteristic properties of nuclei are found to possess the predictive capability. In fact η-systematics reveal new magic numbers in the drip-line regions giving rise to new islands of stability supported by relativistic mean field theoretic calculations. This is a manifestation of a new phenomenon where shell-effect overcomes the instability due to repulsive components of the nucleon-nucleon force broadening the stability peninsula. The two-neutron separation energy-systematics derived from the present mass predictions reveal a general new feature for the existence of islands of inversion in the exotic neutron-rich regions of nuclear landscape, apart from supporting the presently known islands around 31Na and 62Ti. The five global parameters representing the properties of infinite nuclear matter, the surface, the Coulomb and the pairing terms are retained as per our 1999 mass table. The root-mean-square deviation of the present mass-fit to 2198 known masses is 342 keV, while the mean deviation is 1.3 keV, reminiscent of no left-over systematic effects. This is a substantive improvement over our 1999 mass table having rms deviation of 401 keV and mean deviation of 9 keV for 1884 data nuclei.

Forced Expiratory Volume in 1 Second Variability Helps Identify Patients with Cystic Fibrosis at Risk of Greater Loss of Lung Function.

PubMed

Morgan, Wayne J; VanDevanter, Donald R; Pasta, David J; Foreman, Aimee J; Wagener, Jeffrey S; Konstan, Michael W

2016-02-01

To evaluate several alternative measures of forced expiratory volume in 1 second percent predicted (FEV1 %pred) variability as potential predictors of future FEV1 %pred decline in patients with cystic fibrosis. We included 13,827 patients age ≥6 years from the Epidemiologic Study of Cystic Fibrosis 1994-2002 with ≥4 FEV1 %pred measurements spanning ≥366 days in both a 2-year baseline period and a 2-year follow-up period. We predicted change from best baseline FEV1 %pred to best follow-up FEV1 %pred and change from baseline to best in the second follow-up year by using multivariable regression stratified by 4 lung-disease stages. We assessed 5 measures of variability (some as deviations from the best and some as deviations from the trend line) both alone and after controlling for demographic and clinical factors and for the slope and level of FEV1 %pred. All 5 measures of FEV1 %pred variability were predictive, but the strongest predictor was median deviation from the best FEV1 %pred in the baseline period. The contribution to explanatory power (R(2)) was substantial and exceeded the total contribution of all other factors excluding the FEV1 %pred rate of decline. Adding the other variability measures provided minimal additional value. Median deviation from the best FEV1 %pred is a simple metric that markedly improves prediction of FEV1 %pred decline even after the inclusion of demographic and clinical characteristics and the FEV1 %pred rate of decline. The routine calculation of this variability measure could allow clinicians to better identify patients at risk and therefore in need of increased intervention. Copyright © 2016 Elsevier Inc. All rights reserved.

pKa predictions for proteins, RNAs, and DNAs with the Gaussian dielectric function using DelPhi pKa.

PubMed

Wang, Lin; Li, Lin; Alexov, Emil

2015-12-01

We developed a Poisson-Boltzmann based approach to calculate the pKa values of protein ionizable residues (Glu, Asp, His, Lys and Arg), nucleotides of RNA and single stranded DNA. Two novel features were utilized: the dielectric properties of the macromolecules and water phase were modeled via the smooth Gaussian-based dielectric function in DelPhi and the corresponding electrostatic energies were calculated without defining the molecular surface. We tested the algorithm by calculating pKa values for more than 300 residues from 32 proteins from the PPD dataset and achieved an overall RMSD of 0.77. Particularly, the RMSD of 0.55 was achieved for surface residues, while the RMSD of 1.1 for buried residues. The approach was also found capable of capturing the large pKa shifts of various single point mutations in staphylococcal nuclease (SNase) from pKa-cooperative dataset, resulting in an overall RMSD of 1.6 for this set of pKa's. Investigations showed that predictions for most of buried mutant residues of SNase could be improved by using higher dielectric constant values. Furthermore, an option to generate different hydrogen positions also improves pKa predictions for buried carboxyl residues. Finally, the pKa calculations on two RNAs demonstrated the capability of this approach for other types of biomolecules. © 2015 Wiley Periodicals, Inc.

Bio-energy conversion performance, biodegradability, and kinetic analysis of different fruit residues during discontinuous anaerobic digestion.

PubMed

Zhao, Chen; Yan, Hu; Liu, Yan; Huang, Yan; Zhang, Ruihong; Chen, Chang; Liu, Guangqing

2016-06-01

Huge amounts of fruit residues are produced and abandoned annually. The high moisture and organic contents of these residues makes them a big problem to the environment. Conversely, they are a potential resource to the world. Anaerobic digestion is a good way to utilize these organic wastes. In this study, the biomethane conversion performances of a large number of fruit residues were determined and compared using batch anaerobic digestion, a reliable and easily accessible method. The results showed that some fruit residues containing high contents of lipids and carbohydrates, such as loquat peels and rambutan seeds, were well fit for anaerobic digestion. Contrarily, residues with high lignin content were strongly recommended not to be used as a single substrate for methane production. Multiple linear regression model was adopted to simulate the correlation between the organic component of these fruit residues and their experimental methane yield, through which the experimental methane yield could probably be predicted for any other fruit residues. Four kinetic models were used to predict the batch anaerobic digestion process of different fruit residues. It was shown that the modified Gompertz and Cone models were better fit for the fruit residues compared to the first-order and Fitzhugh models. The first findings of this study could provide useful reference and guidance for future studies regarding the applications and potential utilization of fruit residues. Copyright © 2016 Elsevier Ltd. All rights reserved.

Development, validation and determination of multiclass pesticide residues in cocoa beans using gas chromatography and liquid chromatography tandem mass spectrometry.

PubMed

Zainudin, Badrul Hisyam; Salleh, Salsazali; Mohamed, Rahmat; Yap, Ken Choy; Muhamad, Halimah

2015-04-01

An efficient and rapid method for the analysis of pesticide residues in cocoa beans using gas and liquid chromatography-tandem mass spectrometry was developed, validated and applied to imported and domestic cocoa beans samples collected over 2 years from smallholders and Malaysian ports. The method was based on solvent extraction method and covers 26 pesticides (insecticides, fungicides, and herbicides) of different chemical classes. The recoveries for all pesticides at 10 and 50 μg/kg were in the range of 70-120% with relative standard deviations of less than 20%. Good selectivity and sensitivity were obtained with method limit of quantification of 10 μg/kg. The expanded uncertainty measurements were in the range of 4-25%. Finally, the proposed method was successfully applied for the routine analysis of pesticide residues in cocoa beans via a monitoring study where 10% of them was found positive for chlorpyrifos, ametryn and metalaxyl. Copyright © 2014 Elsevier Ltd. All rights reserved.

DECONV-TOOL: An IDL based deconvolution software package

NASA Technical Reports Server (NTRS)

Varosi, F.; Landsman, W. B.

1992-01-01

There are a variety of algorithms for deconvolution of blurred images, each having its own criteria or statistic to be optimized in order to estimate the original image data. Using the Interactive Data Language (IDL), we have implemented the Maximum Likelihood, Maximum Entropy, Maximum Residual Likelihood, and sigma-CLEAN algorithms in a unified environment called DeConv_Tool. Most of the algorithms have as their goal the optimization of statistics such as standard deviation and mean of residuals. Shannon entropy, log-likelihood, and chi-square of the residual auto-correlation are computed by DeConv_Tool for the purpose of determining the performance and convergence of any particular method and comparisons between methods. DeConv_Tool allows interactive monitoring of the statistics and the deconvolved image during computation. The final results, and optionally, the intermediate results, are stored in a structure convenient for comparison between methods and review of the deconvolution computation. The routines comprising DeConv_Tool are available via anonymous FTP through the IDL Astronomy User's Library.

[Determination of azoxystrobin residues in fruits and vegetables by gas chromatography/mass spectrometry with solid-phase extraction].

PubMed

Bo, Haibo

2007-11-01

A method was developed for the determination of azoxystrobin residues in fruits and vegetables by gas chromatography/mass spectrometry (GC/MS). Azoxystrobin residues were extracted with ethyl acetate-cyclohexane (1 : 1, v/v) by ultrasonication and then they were cleaned up on a silica solid-phase extraction (SPE) column to obtain an extract suitable for analysis by GC/MS in the selective ion monitoring (SIM) mode (the selected ion: m/z 344, 372, 388 and 403). The calibration curves were linear between area and concentration of azoxystrobin from 0.01 to 1.0 mg/kg with the correlation coefficient greater than 0.99. The average recoveries from spiked fruit and vegetable matrixes at three concentrations of 0.01, 0.1, 1.0 mg/kg ranged from 85.2% to 98.2% with relative standard deviation less than 21.5%. The limit of detection was 0.01 mg/kg and the limit of quantity was 0.05 mg/kg in fruit and vegetable matrixes, respectively.

High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features.

PubMed

Jones, David T; Kandathil, Shaun M

2018-04-26

In addition to substitution frequency data from protein sequence alignments, many state-of-the-art methods for contact prediction rely on additional sources of information, or features, of protein sequences in order to predict residue-residue contacts, such as solvent accessibility, predicted secondary structure, and scores from other contact prediction methods. It is unclear how much of this information is needed to achieve state-of-the-art results. Here, we show that using deep neural network models, simple alignment statistics contain sufficient information to achieve state-of-the-art precision. Our prediction method, DeepCov, uses fully convolutional neural networks operating on amino-acid pair frequency or covariance data derived directly from sequence alignments, without using global statistical methods such as sparse inverse covariance or pseudolikelihood estimation. Comparisons against CCMpred and MetaPSICOV2 show that using pairwise covariance data calculated from raw alignments as input allows us to match or exceed the performance of both of these methods. Almost all of the achieved precision is obtained when considering relatively local windows (around 15 residues) around any member of a given residue pairing; larger window sizes have comparable performance. Assessment on a set of shallow sequence alignments (fewer than 160 effective sequences) indicates that the new method is substantially more precise than CCMpred and MetaPSICOV2 in this regime, suggesting that improved precision is attainable on smaller sequence families. Overall, the performance of DeepCov is competitive with the state of the art, and our results demonstrate that global models, which employ features from all parts of the input alignment when predicting individual contacts, are not strictly needed in order to attain precise contact predictions. DeepCov is freely available at https://github.com/psipred/DeepCov. d.t.jones@ucl.ac.uk.

Protocol deviations before and after IV tPA in community hospitals

PubMed Central

Adelman, Eric E.; Scott, Phillip A.; Skolarus, Lesli E.; Fox, Allison K.; Frederiksen, Shirley M.; Meurer, William J.

2015-01-01

Background Protocol deviations before and after tPA treatment for ischemic stroke are common. It is unclear if patient or hospital factors predict protocol deviations. We examined predictors of protocol deviations and the effects of protocol violations on symptomatic intracerebral hemorrhage. Methods We used data from the INSTINCT trial, a cluster-randomized, controlled trial evaluating the efficacy of a barrier assessment and educational intervention to increase appropriate tPA use in 24 Michigan community hospitals, to review tPA treatments between 2007 and 2010. Protocol violations were defined as deviations from the standard tPA protocol, both before and after treatment. Multi-level logistic regression models were fitted to determine if patient and hospital variables were associated with pre-treatment or post-treatment protocol deviations. Results During the study, 557 patients (mean age 70; 52% male; median NIHSS 12) were treated with tPA. Protocol deviations occurred in 233 (42%) patients: 16% had pre-treatment deviations, 35% had post-treatment deviations, and 9% had both. The most common protocol deviations included elevated post-treatment blood pressure, antithrombotic agent use within 24 hours of treatment, and elevated pre-treatment blood pressure. Protocol deviations were not associated with symptomatic intracerebral hemorrhage, stroke severity, or hospital factors. Older age was associated with pre-treatment protocol deviations (adjusted OR 0.52; 95% confidence interval 0.30-0.92). Pre-treatment deviations were associated with post-treatment deviations (adjusted OR 3.20; 95% confidence interval 1.91-5.35). Conclusions Protocol deviations were not associated with symptomatic intracerebral hemorrhage. Aside from age, patient and hospital factors were not associated with protocol deviations. PMID:26419527

Next-day residual effects of hypnotics in DSM-IV primary insomnia: a driving simulator study with simultaneous electroencephalogram monitoring.

PubMed

Staner, Luc; Ertlé, Stéphane; Boeijinga, Peter; Rinaudo, Gilbert; Arnal, Marie Agnès; Muzet, Alain; Luthringer, Rémy

2005-10-01

Most studies that investigated the next-day residual effects of hypnotic drugs on daytime driving performances were performed on healthy subjects and after a single drug administration. In the present study, we further examine whether the results of these studies could be generalised to insomniac patients and after repeated drug administration. Single and repeated (7 day) doses of zolpidem (10 mg), zopiclone (7.5 mg), lormetazepam (1 mg) or placebo were administered at bedtime in a crossover design to 23 patients (9 men and 14 women aged 38.8+/-2.0 years) with Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) primary insomnia. Driving tests were performed 9-11 h post-dose. Results showed that treatment effects were evidenced for subjective sleep, for driving abilities, and for electroencephalogram (EEG) recorded before (resting EEG) and during the driving simulation test (driving EEG). Compared to placebo, zopiclone increased the number of collisions and lormetazepam increased deviation from speed limit and deviation from absolute speed, whereas zolpidem did not differentiate from placebo on these analyses. EEG recordings showed that in contrast to zolpidem, lormetazepam and zopiclone induced typical benzodiazepine-like alterations, suggesting that next-day poor driving performance could relate to a prolonged central nervous system effect of these two hypnotics. The present results corroborate studies on healthy volunteers showing that residual effects of hypnotics increase with their half-lives. The results further suggest that drugs preserving physiological EEG rhythms before and during the driving simulation test 9-11 h post-dose, such as zolpidem, do not influence next-day driving abilities.

Resolution of the COBE Earth sensor anomaly

NASA Technical Reports Server (NTRS)

Sedler, J.

1993-01-01

Since its launch on November 18, 1989, the Earth sensors on the Cosmic Background Explorer (COBE) have shown much greater noise than expected. The problem was traced to an error in Earth horizon acquisition-of-signal (AOS) times. Due to this error, the AOS timing correction was ignored, causing Earth sensor split-to-index (SI) angles to be incorrectly time-tagged to minor frame synchronization times. Resulting Earth sensor residuals, based on gyro-propagated fine attitude solutions, were as large as plus or minus 0.45 deg (much greater than plus or minus 0.10 deg from scanner specifications (Reference 1)). Also, discontinuities in single-frame coarse attitude pitch and roll angles (as large as 0.80 and 0.30 deg, respectively) were noted several times during each orbit. However, over the course of the mission, each Earth sensor was observed to independently and unexpectedly reset and then reactivate into a new configuration. Although the telemetered AOS timing corrections are still in error, a procedure has been developed to approximate and apply these corrections. This paper describes the approach, analysis, and results of approximating and applying AOS timing adjustments to correct Earth scanner data. Furthermore, due to the continuing degradation of COBE's gyroscopes, gyro-propagated fine attitude solutions may soon become unavailable, requiring an alternative method for attitude determination. By correcting Earth scanner AOS telemetry, as described in this paper, more accurate single-frame attitude solutions are obtained. All aforementioned pitch and roll discontinuities are removed. When proper AOS corrections are applied, the standard deviation of pitch residuals between coarse attitude and gyro-propagated fine attitude solutions decrease by a factor of 3. Also, the overall standard deviation of SI residuals from fine attitude solutions decrease by a factor of 4 (meeting sensor specifications) when AOS corrections are applied.

Bupivacaine injection remodels extraocular muscles and corrects comitant strabismus.

PubMed

Miller, Joel M; Scott, Alan B; Danh, Kenneth K; Strasser, Dirk; Sane, Mona

2013-12-01

To evaluate the clinical effectiveness and anatomic changes resulting from bupivacaine injection into extraocular muscles to treat comitant horizontal strabismus. Prospective, observational clinical series. Thirty-one comitant horizontal strabismus patients. Nineteen patients with esotropia received bupivacaine injections in the lateral rectus muscle, and 12 patients with exotropia received bupivacaine injections in the medial rectus. Sixteen of these, with large strabismus angles, also received botulinum type A toxin injections in the antagonist muscle at the same treatment session. A second treatment was given to 13 patients who had residual strabismus after the first treatment. Clinical alignment measures and muscle volume, maximum cross-sectional area, and shape derived from magnetic resonance imaging, with follow-up examinations for up to 3 years. At an average of 15.3 months after the final treatment, original misalignment was reduced by 10.5 prism diopters (Δ; 6.0°) with residual deviations of 10Δ or less in 53% of patients. A single treatment with bupivacaine alone reduced misalignment at 11.3 months by 4.7Δ (2.7°) with residual deviations of 10Δ or less in 50% of patients. Alignment corrections were remarkably stable over follow-ups for as long as 3 years. Six months after bupivacaine injection, muscle volume had increased by 6.6%, and maximum cross-sectional area had increased by 8.5%, gradually relaxing toward pretreatment values thereafter. Computer modeling with Orbit 1.8 (Eidactics, San Francisco, CA) suggested that changes in agonist and antagonist muscle lengths were responsible for the enduring changes in eye alignment. Bupivacaine injection alone or together with botulinum toxin injection in the antagonist muscle improves eye alignment in comitant horizontal strabismus by inducing changes in rectus muscle structure and length. Copyright © 2013 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Ruminal pH predictions for beef cattle: Comparative evaluation of current models.

PubMed

Sarhan, M A; Beauchemin, K A

2015-04-01

This study evaluated 8 empirical models for their ability to accurately predict mean ruminal pH in beef cattle fed a wide range of diets. Models tested that use physically effective fiber (peNDF) as a dependent variable were Pitt et al. (1996, PIT), Mertens (1997, MER), Fox et al. (2004, FOX), Zebeli et al. (2006, ZB6), and Zebeli et al. (2008, ZB8), and those that use rumen VFA were Tamminga and Van Vuuren (1988, TAM), Lescoat and Sauvant (1995, LES), and Allen (1997, ALL). A data set of 65 published papers (231 treatment means) for beef cattle was assembled that included information on animal characteristics, diet composition, and ruminal fermentation and mean pH. Model evaluations were based on mean square prediction error (MSPE), concordance correlation coefficient (CCC), and regression analysis. The prediction potential of the models varied with low root MSPE (RMSPE) values of 4.94% and 5.37% for PIT and FOX, RMSPE values of 9.66% and 12.55% for ZB6 and MER, and intermediate RMSPE values of 5.66% to 6.26% for the other models. For PIT and FOX, with the lowest RMSPE, approximately 96% of MSPE was due to random error, whereas for ZB6 and MER, with the highest RMSPE, 15.85% and 23.42% of MSPE, respectively, was due to linear bias, and 37.19% and 60.12% of the error, respectively, was due to deviation of the regression slope from unity. The CCC was greatest for PIT (0.67) and FOX (0.62), followed by 0.60 for LES and TAM, 0.52 for ZB8, 0.39 for MER, 0.34 for ALL, and 0.22 for ZB6. Residuals plotted against model-predicted values showed linear bias (P < 0.001) for all models except PIT (P = 0.976) and FOX (P = 0.054) and mean bias (P < 0.001) except for FOX (P = 0.293), LES (P = 0.215), and TAM (P = 0.119). The study showed that the empirical models PIT and FOX, based on peNDF, and LES and TAM, based on VFA, are preferred over the others for prediction of mean ruminal pH in beef cattle fed a wide range of diets. Several animal (BW and intake), diet (forage and OM contents), and ruminal (ammonia and acetate concentrations) factors were (P < 0.001) related to the residuals for each model. We conclude that the accuracy of prediction of mean ruminal pH was relatively low for all extant models. Consideration of factors in addition to peNDF and total VFA, as well as the use of data from studies with continuous measurement of ruminal pH over 24 h or more, would be useful in the development of improved models for predicting ruminal pH in beef cattle.

Experimental and theoretical studies of the crystal structures of bis-isoxazole-bis-methylene dinitrate (BIDN) and bis-isoxazole tetramethylene tetranitrate (BITN) by x-ray crystallography and density functional theory

NASA Astrophysics Data System (ADS)

Taylor, Decarlos E.; Sausa, Rosario C.

2018-06-01

The determination of crystal structures plays an important role for model testing and validation, and understanding intra and intermolecular interactions that influence crystal packing. Here, we report the molecular structure of two recently synthesized energetic molecules, 3,3-bis-isoxazole-5,5‧-bis-methylene dinitrate (C8H6N4O8, BIDN) and bis-isoxazole tetramethylene tetranitrate (C10H8N6O14, BITN) determined by single crystal x-ray diffraction and solid state density functional theory (DFT). BIDN is composed of two planar alkyl nitrate groups (r.m.s deviation = 0.0004 (1) Å) bonded to two planar azole rings (r.m.s deviation = 0.001 (1) Å, whereas BITN is composed of four planar alkyl nitrate groups (average r.m.s deviation = 0.002 (1) Å) bonded to two planar azole rings (average r.m.s deviation = 0.002 (1) Å). The theoretical calculations predict very well the planarity of both the alkyl nitrate groups and rings for both compounds. Furthermore, they predict well the bond lengths and angles of both molecules with mean deviation values of 0.018 Å (BIDN) and 0.017 Å (BITN) and 0.481° (BIDN) and 0.747° (BITN). Overall, the DFT determined torsion angles agree well with those determined experimentally for both BIDN (average deviation = 1.139°) and BITN (average deviation = 0.604°). The theoretical cell constant values are in excellent agreement with those determined experimentally for both molecules, with the BIDN a cell value and β angle showing the largest deviation, 2.1% and -1.3%, respectively. Contacts between the atoms N and H dominate the intermolecular interactions of BIDN, whereas contacts involving the atoms O and H dominate the BITN intermolecular interactions. Electrostatic potential calculations at the B3LYP/6-31G* level reveal BIDN exhibits a lower sensitivity to impact compared to BITN.

Contribution to the Prediction of the Fold Code: Application to Immunoglobulin and Flavodoxin Cases

PubMed Central

Banach, Mateusz; Prudhomme, Nicolas; Carpentier, Mathilde; Duprat, Elodie; Papandreou, Nikolaos; Kalinowska, Barbara; Chomilier, Jacques; Roterman, Irena

2015-01-01

Background Folding nucleus of globular proteins formation starts by the mutual interaction of a group of hydrophobic amino acids whose close contacts allow subsequent formation and stability of the 3D structure. These early steps can be predicted by simulation of the folding process through a Monte Carlo (MC) coarse grain model in a discrete space. We previously defined MIRs (Most Interacting Residues), as the set of residues presenting a large number of non-covalent neighbour interactions during such simulation. MIRs are good candidates to define the minimal number of residues giving rise to a given fold instead of another one, although their proportion is rather high, typically [15-20]% of the sequences. Having in mind experiments with two sequences of very high levels of sequence identity (up to 90%) but different folds, we combined the MIR method, which takes sequence as single input, with the “fuzzy oil drop” (FOD) model that requires a 3D structure, in order to estimate the residues coding for the fold. FOD assumes that a globular protein follows an idealised 3D Gaussian distribution of hydrophobicity density, with the maximum in the centre and minima at the surface of the “drop”. If the actual local density of hydrophobicity around a given amino acid is as high as the ideal one, then this amino acid is assigned to the core of the globular protein, and it is assumed to follow the FOD model. Therefore one obtains a distribution of the amino acids of a protein according to their agreement or rejection with the FOD model. Results We compared and combined MIR and FOD methods to define the minimal nucleus, or keystone, of two populated folds: immunoglobulin-like (Ig) and flavodoxins (Flav). The combination of these two approaches defines some positions both predicted as a MIR and assigned as accordant with the FOD model. It is shown here that for these two folds, the intersection of the predicted sets of residues significantly differs from random selection. It reduces the number of selected residues by each individual method and allows a reasonable agreement with experimentally determined key residues coding for the particular fold. In addition, the intersection of the two methods significantly increases the specificity of the prediction, providing a robust set of residues that constitute the folding nucleus. PMID:25915049

Single-energy non-contrast hepatic steatosis criteria applied to virtual non-contrast images: is it still highly specific and positively predictive?

PubMed

Haji-Momenian, S; Parkinson, W; Khati, N; Brindle, K; Earls, J; Zeman, R K

2018-06-01

To determine the sensitivity, specificity, and predictive values of single-energy non-contrast hepatic steatosis criteria on dual-energy virtual non-contrast (VNC) images. Forty-eight computed tomography (CT) examinations, which included single-energy non-contrast (TNC) and contrast-enhanced dual-energy CT angiography (CTA) of the abdomen, were enrolled. VNC images were reconstructed from the CTA. Region of interest (ROI) attenuations were measured in the right and left hepatic lobes, spleen, and aorta on TNC and VNC images. The right and left hepatic lobes were treated as separate samples. Steatosis was diagnosed based on TNC liver attenuation of ≤40 HU or liver attenuation index (LAI) of ≤-10 HU, which are extremely specific and predictive for moderate to severe steatosis. The sensitivity, specificity, and predictive values of VNC images for steatosis were calculated. VNC-TNC deviations were correlated with aortic enhancement and patient water equivalent diameter (PWED). Thirty-two liver ROIs met steatosis criteria based on TNC attenuation; VNC attenuation had sensitivity, specificity, and a positive predictive value of 66.7%, 100%, and 100%, respectively. Twenty-one liver ROIs met steatosis criteria based on TNC LAI. VNC LAI had sensitivity, specificity, and positive predictive values of 61.9%, 90.7%, and 65%, respectively. Hepatic and splenic VNC-TNC deviations did not correlate with one another (R 2 =0.08), aortic enhancement (R 2 <0.06) or PWED (R 2 <0.09). Non-contrast hepatic attenuation criteria is extremely specific and positively predictive for moderate to severe steatosis on VNC reconstructions from the arterial phase. Hepatic attenuation performs better than LAI criteria. VNC deviations are independent of aortic enhancement and PWED. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Visuomotor adaptation needs a validation of prediction error by feedback error

PubMed Central

Gaveau, Valérie; Prablanc, Claude; Laurent, Damien; Rossetti, Yves; Priot, Anne-Emmanuelle

2014-01-01

The processes underlying short-term plasticity induced by visuomotor adaptation to a shifted visual field are still debated. Two main sources of error can induce motor adaptation: reaching feedback errors, which correspond to visually perceived discrepancies between hand and target positions, and errors between predicted and actual visual reafferences of the moving hand. These two sources of error are closely intertwined and difficult to disentangle, as both the target and the reaching limb are simultaneously visible. Accordingly, the goal of the present study was to clarify the relative contributions of these two types of errors during a pointing task under prism-displaced vision. In “terminal feedback error” condition, viewing of their hand by subjects was allowed only at movement end, simultaneously with viewing of the target. In “movement prediction error” condition, viewing of the hand was limited to movement duration, in the absence of any visual target, and error signals arose solely from comparisons between predicted and actual reafferences of the hand. In order to prevent intentional corrections of errors, a subthreshold, progressive stepwise increase in prism deviation was used, so that subjects remained unaware of the visual deviation applied in both conditions. An adaptive aftereffect was observed in the “terminal feedback error” condition only. As far as subjects remained unaware of the optical deviation and self-assigned pointing errors, prediction error alone was insufficient to induce adaptation. These results indicate a critical role of hand-to-target feedback error signals in visuomotor adaptation; consistent with recent neurophysiological findings, they suggest that a combination of feedback and prediction error signals is necessary for eliciting aftereffects. They also suggest that feedback error updates the prediction of reafferences when a visual perturbation is introduced gradually and cognitive factors are eliminated or strongly attenuated. PMID:25408644

Heterodimer Binding Scaffolds Recognition via the Analysis of Kinetically Hot Residues

PubMed Central

Perišić, Ognjen

2018-01-01

Physical interactions between proteins are often difficult to decipher. The aim of this paper is to present an algorithm that is designed to recognize binding patches and supporting structural scaffolds of interacting heterodimer proteins using the Gaussian Network Model (GNM). The recognition is based on the (self) adjustable identification of kinetically hot residues and their connection to possible binding scaffolds. The kinetically hot residues are residues with the lowest entropy, i.e., the highest contribution to the weighted sum of the fastest modes per chain extracted via GNM. The algorithm adjusts the number of fast modes in the GNM’s weighted sum calculation using the ratio of predicted and expected numbers of target residues (contact and the neighboring first-layer residues). This approach produces very good results when applied to dimers with high protein sequence length ratios. The protocol’s ability to recognize near native decoys was compared to the ability of the residue-level statistical potential of Lu and Skolnick using the Sternberg and Vakser decoy dimers sets. The statistical potential produced better overall results, but in a number of cases its predicting ability was comparable, or even inferior, to the prediction ability of the adjustable GNM approach. The results presented in this paper suggest that in heterodimers at least one protein has interacting scaffold determined by the immovable, kinetically hot residues. In many cases, interacting proteins (especially if being of noticeably different sizes) either behave as a rigid lock and key or, presumably, exhibit the opposite dynamic behavior. While the binding surface of one protein is rigid and stable, its partner’s interacting scaffold is more flexible and adaptable. PMID:29547506

Maximizing Selective Cleavages at Aspartic Acid and Proline Residues for the Identification of Intact Proteins

NASA Astrophysics Data System (ADS)

Foreman, David J.; Dziekonski, Eric T.; McLuckey, Scott A.

2018-04-01

A new approach for the identification of intact proteins has been developed that relies on the generation of relatively few abundant products from specific cleavage sites. This strategy is intended to complement standard approaches that seek to generate many fragments relatively non-selectively. Specifically, this strategy seeks to maximize selective cleavage at aspartic acid and proline residues via collisional activation of precursor ions formed via electrospray ionization (ESI) under denaturing conditions. A statistical analysis of the SWISS-PROT database was used to predict the number of arginine residues for a given intact protein mass and predict a m/z range where the protein carries a similar charge to the number of arginine residues thereby enhancing cleavage at aspartic acid residues by limiting proton mobility. Cleavage at aspartic acid residues is predicted to be most favorable in the m/z range of 1500-2500, a range higher than that normally generated by ESI at low pH. Gas-phase proton transfer ion/ion reactions are therefore used for precursor ion concentration from relatively high charge states followed by ion isolation and subsequent generation of precursor ions within the optimal m/z range via a second proton transfer reaction step. It is shown that the majority of product ion abundance is concentrated into cleavages C-terminal to aspartic acid residues and N-terminal to proline residues for ions generated by this process. Implementation of a scoring system that weights both ion fragment type and ion fragment area demonstrated identification of standard proteins, ranging in mass from 8.5 to 29.0 kDa. [Figure not available: see fulltext.

Maximizing Selective Cleavages at Aspartic Acid and Proline Residues for the Identification of Intact Proteins.

PubMed

Foreman, David J; Dziekonski, Eric T; McLuckey, Scott A

2018-04-30

A new approach for the identification of intact proteins has been developed that relies on the generation of relatively few abundant products from specific cleavage sites. This strategy is intended to complement standard approaches that seek to generate many fragments relatively non-selectively. Specifically, this strategy seeks to maximize selective cleavage at aspartic acid and proline residues via collisional activation of precursor ions formed via electrospray ionization (ESI) under denaturing conditions. A statistical analysis of the SWISS-PROT database was used to predict the number of arginine residues for a given intact protein mass and predict a m/z range where the protein carries a similar charge to the number of arginine residues thereby enhancing cleavage at aspartic acid residues by limiting proton mobility. Cleavage at aspartic acid residues is predicted to be most favorable in the m/z range of 1500-2500, a range higher than that normally generated by ESI at low pH. Gas-phase proton transfer ion/ion reactions are therefore used for precursor ion concentration from relatively high charge states followed by ion isolation and subsequent generation of precursor ions within the optimal m/z range via a second proton transfer reaction step. It is shown that the majority of product ion abundance is concentrated into cleavages C-terminal to aspartic acid residues and N-terminal to proline residues for ions generated by this process. Implementation of a scoring system that weights both ion fragment type and ion fragment area demonstrated identification of standard proteins, ranging in mass from 8.5 to 29.0 kDa. Graphical Abstract ᅟ.

Prediction of hip joint load and translation using musculoskeletal modelling with force-dependent kinematics and experimental validation.

PubMed

Zhang, Xuan; Chen, Zhenxian; Wang, Ling; Yang, Wenjian; Li, Dichen; Jin, Zhongmin

2015-07-01

Musculoskeletal lower limb models are widely used to predict the resultant contact force in the hip joint as a non-invasive alternative to instrumented implants. Previous musculoskeletal models based on rigid body assumptions treated the hip joint as an ideal sphere with only three rotational degrees of freedom. An musculoskeletal model that considered force-dependent kinematics with three additional translational degrees of freedom was developed and validated in this study by comparing it with a previous experimental measurement. A 32-mm femoral head against a polyethylene cup was considered in the musculoskeletal model for calculating the contact forces. The changes in the main modelling parameters were found to have little influence on the hip joint forces (relative deviation of peak value < 10 BW%, mean trial deviation < 20 BW%). The centre of the hip joint translation was more sensitive to the changes in the main modelling parameters, especially muscle recruitment type (relative deviation of peak value < 20%, mean trial deviation < 0.02 mm). The predicted hip contact forces showed consistent profiles, compared with the experimental measurements, except in the lateral-medial direction. The ratio-average analysis, based on the Bland-Altman's plots, showed better limits of agreement in climbing stairs (mean limits of agreement: -2.0 to 6.3 in walking, mean limits of agreement: -0.5 to 3.1 in climbing stairs). Better agreement of the predicted hip contact forces was also found during the stance phase. The force-dependent kinematics approach underestimated the maximum hip contact force by a mean value of 6.68 ± 1.75% BW compared with the experimental measurements. The predicted maximum translations of the hip joint centres were 0.125 ± 0.03 mm in level walking and 0.123 ± 0.005 mm in climbing stairs. © IMechE 2015.

Validation of the thermophysiological model by Fiala for prediction of local skin temperatures

NASA Astrophysics Data System (ADS)

Martínez, Natividad; Psikuta, Agnes; Kuklane, Kalev; Quesada, José Ignacio Priego; de Anda, Rosa María Cibrián Ortiz; Soriano, Pedro Pérez; Palmer, Rosario Salvador; Corberán, José Miguel; Rossi, René Michel; Annaheim, Simon

2016-12-01

The most complete and realistic physiological data are derived from direct measurements during human experiments; however, they present some limitations such as ethical concerns, time and cost burden. Thermophysiological models are able to predict human thermal response in a wide range of environmental conditions, but their use is limited due to lack of validation. The aim of this work was to validate the thermophysiological model by Fiala for prediction of local skin temperatures against a dedicated database containing 43 different human experiments representing a wide range of conditions. The validation was conducted based on root-mean-square deviation (rmsd) and bias. The thermophysiological model by Fiala showed a good precision when predicting core and mean skin temperature (rmsd 0.26 and 0.92 °C, respectively) and also local skin temperatures for most body sites (average rmsd for local skin temperatures 1.32 °C). However, an increased deviation of the predictions was observed for the forehead skin temperature (rmsd of 1.63 °C) and for the thigh during exercising exposures (rmsd of 1.41 °C). Possible reasons for the observed deviations are lack of information on measurement circumstances (hair, head coverage interference) or an overestimation of the sweat evaporative cooling capacity for the head and thigh, respectively. This work has highlighted the importance of collecting details about the clothing worn and how and where the sensors were attached to the skin for achieving more precise results in the simulations.

Predicting residue-wise contact orders in proteins by support vector regression.

PubMed

Song, Jiangning; Burrage, Kevin

2006-10-03

The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

SNBRFinder: A Sequence-Based Hybrid Algorithm for Enhanced Prediction of Nucleic Acid-Binding Residues.

PubMed

Yang, Xiaoxia; Wang, Jia; Sun, Jun; Liu, Rong

2015-01-01

Protein-nucleic acid interactions are central to various fundamental biological processes. Automated methods capable of reliably identifying DNA- and RNA-binding residues in protein sequence are assuming ever-increasing importance. The majority of current algorithms rely on feature-based prediction, but their accuracy remains to be further improved. Here we propose a sequence-based hybrid algorithm SNBRFinder (Sequence-based Nucleic acid-Binding Residue Finder) by merging a feature predictor SNBRFinderF and a template predictor SNBRFinderT. SNBRFinderF was established using the support vector machine whose inputs include sequence profile and other complementary sequence descriptors, while SNBRFinderT was implemented with the sequence alignment algorithm based on profile hidden Markov models to capture the weakly homologous template of query sequence. Experimental results show that SNBRFinderF was clearly superior to the commonly used sequence profile-based predictor and SNBRFinderT can achieve comparable performance to the structure-based template methods. Leveraging the complementary relationship between these two predictors, SNBRFinder reasonably improved the performance of both DNA- and RNA-binding residue predictions. More importantly, the sequence-based hybrid prediction reached competitive performance relative to our previous structure-based counterpart. Our extensive and stringent comparisons show that SNBRFinder has obvious advantages over the existing sequence-based prediction algorithms. The value of our algorithm is highlighted by establishing an easy-to-use web server that is freely accessible at http://ibi.hzau.edu.cn/SNBRFinder.

Protein Solvent-Accessibility Prediction by a Stacked Deep Bidirectional Recurrent Neural Network.

PubMed

Zhang, Buzhong; Li, Linqing; Lü, Qiang

2018-05-25

Residue solvent accessibility is closely related to the spatial arrangement and packing of residues. Predicting the solvent accessibility of a protein is an important step to understand its structure and function. In this work, we present a deep learning method to predict residue solvent accessibility, which is based on a stacked deep bidirectional recurrent neural network applied to sequence profiles. To capture more long-range sequence information, a merging operator was proposed when bidirectional information from hidden nodes was merged for outputs. Three types of merging operators were used in our improved model, with a long short-term memory network performing as a hidden computing node. The trained database was constructed from 7361 proteins extracted from the PISCES server using a cut-off of 25% sequence identity. Sequence-derived features including position-specific scoring matrix, physical properties, physicochemical characteristics, conservation score and protein coding were used to represent a residue. Using this method, predictive values of continuous relative solvent-accessible area were obtained, and then, these values were transformed into binary states with predefined thresholds. Our experimental results showed that our deep learning method improved prediction quality relative to current methods, with mean absolute error and Pearson's correlation coefficient values of 8.8% and 74.8%, respectively, on the CB502 dataset and 8.2% and 78%, respectively, on the Manesh215 dataset.

Finite Element Simulation of Shot Peening: Prediction of Residual Stresses and Surface Roughness

NASA Astrophysics Data System (ADS)

Gariépy, Alexandre; Perron, Claude; Bocher, Philippe; Lévesque, Martin

Shot peening is a surface treatment that consists of bombarding a ductile surface with numerous small and hard particles. Each impact creates localized plastic strains that permanently stretch the surface. Since the underlying material constrains this stretching, compressive residual stresses are generated near the surface. This process is commonly used in the automotive and aerospace industries to improve fatigue life. Finite element analyses can be used to predict residual stress profiles and surface roughness created by shot peening. This study investigates further the parameters and capabilities of a random impact model by evaluating the representative volume element and the calculated stress distribution. Using an isotropic-kinematic hardening constitutive law to describe the behaviour of AA2024-T351 aluminium alloy, promising results were achieved in terms of residual stresses.

Predicted Cubic-foot Yields of Lumber, Sawdust, and Sawmill Residue from the Sawtimber Portions of Hardwood Trees

Treesearch

Leland F. Hanks

1977-01-01

We have presented prediction equations and tables for estimating the gross cubic-foot volume of sawtimber for hardwood trees, and cubic-foot yields of lumber, sawdust, and sawmill residue that are produced during the sawing process. Yields are presented for northern red oak, black oak, white oak, chestnut oak, red maple, sugar maple, yellow-poplar, yellow birch, paper...

Pairwise contact energy statistical potentials can help to find probability of point mutations.

PubMed

Saravanan, K M; Suvaithenamudhan, S; Parthasarathy, S; Selvaraj, S

2017-01-01

To adopt a particular fold, a protein requires several interactions between its amino acid residues. The energetic contribution of these residue-residue interactions can be approximated by extracting statistical potentials from known high resolution structures. Several methods based on statistical potentials extracted from unrelated proteins are found to make a better prediction of probability of point mutations. We postulate that the statistical potentials extracted from known structures of similar folds with varying sequence identity can be a powerful tool to examine probability of point mutation. By keeping this in mind, we have derived pairwise residue and atomic contact energy potentials for the different functional families that adopt the (α/β) 8 TIM-Barrel fold. We carried out computational point mutations at various conserved residue positions in yeast Triose phosphate isomerase enzyme for which experimental results are already reported. We have also performed molecular dynamics simulations on a subset of point mutants to make a comparative study. The difference in pairwise residue and atomic contact energy of wildtype and various point mutations reveals probability of mutations at a particular position. Interestingly, we found that our computational prediction agrees with the experimental studies of Silverman et al. (Proc Natl Acad Sci 2001;98:3092-3097) and perform better prediction than i Mutant and Cologne University Protein Stability Analysis Tool. The present work thus suggests deriving pairwise contact energy potentials and molecular dynamics simulations of functionally important folds could help us to predict probability of point mutations which may ultimately reduce the time and cost of mutation experiments. Proteins 2016; 85:54-64. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Physiologically based pharmacokinetic model for quinocetone in pigs and extrapolation to mequindox.

PubMed

Zhu, Xudong; Huang, Lingli; Xu, Yamei; Xie, Shuyu; Pan, Yuanhu; Chen, Dongmei; Liu, Zhenli; Yuan, Zonghui

2017-02-01

Physiologically based pharmacokinetic (PBPK) models are scientific methods used to predict veterinary drug residues that may occur in food-producing animals, and which have powerful extrapolation ability. Quinocetone (QCT) and mequindox (MEQ) are widely used in China for the prevention of bacterial infections and promoting animal growth, but their abuse causes a potential threat to human health. In this study, a flow-limited PBPK model was developed to simulate simultaneously residue depletion of QCT and its marker residue dideoxyquinocetone (DQCT) in pigs. The model included compartments for blood, liver, kidney, muscle and fat and an extra compartment representing the other tissues. Physiological parameters were obtained from the literature. Plasma protein binding rates, renal clearances and tissue/plasma partition coefficients were determined by in vitro and in vivo experiments. The model was calibrated and validated with several pharmacokinetic and residue-depletion datasets from the literature. Sensitivity analysis and Monte Carlo simulations were incorporated into the PBPK model to estimate individual variation of residual concentrations. The PBPK model for MEQ, the congener compound of QCT, was built through cross-compound extrapolation based on the model for QCT. The QCT model accurately predicted the concentrations of QCT and DQCT in various tissues at most time points, especially the later time points. Correlation coefficients between predicted and measured values for all tissues were greater than 0.9. Monte Carlo simulations showed excellent consistency between estimated concentration distributions and measured data points. The extrapolation model also showed good predictive power. The present models contribute to improve the residue monitoring systems of QCT and MEQ, and provide evidence of the usefulness of PBPK model extrapolation for the same kinds of compounds.

Residual-Mean Analysis of the Air-Sea Fluxes and Associated Oceanic Meridional Overturning

DTIC Science & Technology

2006-12-01

the adiabatic component of the MOC which is based entirely on the sea surface data . The coordinate system introduced in this study is somewhat...heat capacity of water. The technique utilizes the observational data based on meteorological re- analysis (density flux at the sea surface) and...Figure 8. Annual mean and temporal standard deviation of the zonally-averaged mixed- layer depth. The plotted data are based on Levitus 94 climatology

Simultaneous determination of emamectin and ivermectin residues in Atlantic salmon muscle by liquid chromatography with fluorescence detection.

PubMed

van de Riet, J M; Brothers, N N; Pearce, J N; Burns, B G

2001-01-01

A liquid chromatographic (LC) method for determining residues of the antiparasitic drugs emamectin (EMA) and ivermectin (IVR) in fish tissues has been developed. EMA and IVR residues are extracted with acetonitrile and cleaned up on a C18 solid-phase extraction column. Extracts are derivatized with 1-methylimidazole and trifluoroacetic anhydride and the components are determined by LC on a C18 reversed-phase column with fluorescence detection (excitation: 365 nm, emission: 470 nm). The mobile phase is 94% acetonitrile-water run isocratically. Calibration curves were linear between 1 and 32 ng injected for both EMA and IVR. The limit of detection for both analytes was 0.5 ng/g, with a limit of quantitation of 1.5 ng/g. Recoveries of EMA and IVR added to salmon muscle averaged 96 +/- 9% and 86 +/- 6%, respectively, at levels between 5 and 80 ng/g. The percent relative standard deviation for the described method was less than 7% over the range of concentrations studied. The operational errors, interferences, and recoveries for fortified samples compare favorably with an established IVR method. The recommended method is simple, rapid, and specific for monitoring residues of EMA and IVR in Atlantic salmon muscle.

RECOVIR Software for Identifying Viruses

NASA Technical Reports Server (NTRS)

Chakravarty, Sugoto; Fox, George E.; Zhu, Dianhui

2013-01-01

Most single-stranded RNA (ssRNA) viruses mutate rapidly to generate a large number of strains with highly divergent capsid sequences. Determining the capsid residues or nucleotides that uniquely characterize these strains is critical in understanding the strain diversity of these viruses. RECOVIR (an acronym for "recognize viruses") software predicts the strains of some ssRNA viruses from their limited sequence data. Novel phylogenetic-tree-based databases of protein or nucleic acid residues that uniquely characterize these virus strains are created. Strains of input virus sequences (partial or complete) are predicted through residue-wise comparisons with the databases. RECOVIR uses unique characterizing residues to identify automatically strains of partial or complete capsid sequences of picorna and caliciviruses, two of the most highly diverse ssRNA virus families. Partition-wise comparisons of the database residues with the corresponding residues of more than 300 complete and partial sequences of these viruses resulted in correct strain identification for all of these sequences. This study shows the feasibility of creating databases of hitherto unknown residues uniquely characterizing the capsid sequences of two of the most highly divergent ssRNA virus families. These databases enable automated strain identification from partial or complete capsid sequences of these human and animal pathogens.

Prediction of active sites of enzymes by maximum relevance minimum redundancy (mRMR) feature selection.

PubMed

Gao, Yu-Fei; Li, Bi-Qing; Cai, Yu-Dong; Feng, Kai-Yan; Li, Zhan-Dong; Jiang, Yang

2013-01-27

Identification of catalytic residues plays a key role in understanding how enzymes work. Although numerous computational methods have been developed to predict catalytic residues and active sites, the prediction accuracy remains relatively low with high false positives. In this work, we developed a novel predictor based on the Random Forest algorithm (RF) aided by the maximum relevance minimum redundancy (mRMR) method and incremental feature selection (IFS). We incorporated features of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure and solvent accessibility to predict active sites of enzymes and achieved an overall accuracy of 0.885687 and MCC of 0.689226 on an independent test dataset. Feature analysis showed that every category of the features except disorder contributed to the identification of active sites. It was also shown via the site-specific feature analysis that the features derived from the active site itself contributed most to the active site determination. Our prediction method may become a useful tool for identifying the active sites and the key features identified by the paper may provide valuable insights into the mechanism of catalysis.

Predicting dementia using socio-demographic characteristics and the Free and Cued Selective Reminding Test in the general population.

PubMed

Mura, Thibault; Baramova, Marieta; Gabelle, Audrey; Artero, Sylvaine; Dartigues, Jean-François; Amieva, Hélène; Berr, Claudine

2017-03-23

Our study aimed to determine whether the consideration of socio-demographic features improves the prediction of Alzheimer's dementia (AD) at 5 years when using the Free and Cued Selective Reminding Test (FCSRT) in the general older population. Our analyses focused on 2558 subjects from the prospective Three-City Study, a cohort of community-dwelling individuals aged 65 years and over, with FCSRT scores. Four "residual scores" and "risk scores" were built that included the FCSRT scores and socio-demographic variables. The predictive performance of crude, residual and risk scores was analyzed by comparing the areas under the ROC curve (AUC). In total, 1750 subjects were seen 5 years after completing the FCSRT. AD was diagnosed in 116 of them. Compared with the crude free-recall score, the predictive performances of the residual score and of the risk score were not significantly improved (AUC: 0.83 vs 0.82 and 0.88 vs 0.89 respectively). Using socio-demographic features in addition to the FCSRT does not improve its predictive performance for dementia or AD.

Three-dimensional computed tomographic volumetry precisely predicts the postoperative pulmonary function.

PubMed

Kobayashi, Keisuke; Saeki, Yusuke; Kitazawa, Shinsuke; Kobayashi, Naohiro; Kikuchi, Shinji; Goto, Yukinobu; Sakai, Mitsuaki; Sato, Yukio

2017-11-01

It is important to accurately predict the patient's postoperative pulmonary function. The aim of this study was to compare the accuracy of predictions of the postoperative residual pulmonary function obtained with three-dimensional computed tomographic (3D-CT) volumetry with that of predictions obtained with the conventional segment-counting method. Fifty-three patients scheduled to undergo lung cancer resection, pulmonary function tests, and computed tomography were enrolled in this study. The postoperative residual pulmonary function was predicted based on the segment-counting and 3D-CT volumetry methods. The predicted postoperative values were compared with the results of postoperative pulmonary function tests. Regarding the linear correlation coefficients between the predicted postoperative values and the measured values, those obtained using the 3D-CT volumetry method tended to be higher than those acquired using the segment-counting method. In addition, the variations between the predicted and measured values were smaller with the 3D-CT volumetry method than with the segment-counting method. These results were more obvious in COPD patients than in non-COPD patients. Our findings suggested that the 3D-CT volumetry was able to predict the residual pulmonary function more accurately than the segment-counting method, especially in patients with COPD. This method might lead to the selection of appropriate candidates for surgery among patients with a marginal pulmonary function.

Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modeling heteroscedastic residual errors

NASA Astrophysics Data System (ADS)

McInerney, David; Thyer, Mark; Kavetski, Dmitri; Lerat, Julien; Kuczera, George

2017-03-01

Reliable and precise probabilistic prediction of daily catchment-scale streamflow requires statistical characterization of residual errors of hydrological models. This study focuses on approaches for representing error heteroscedasticity with respect to simulated streamflow, i.e., the pattern of larger errors in higher streamflow predictions. We evaluate eight common residual error schemes, including standard and weighted least squares, the Box-Cox transformation (with fixed and calibrated power parameter λ) and the log-sinh transformation. Case studies include 17 perennial and 6 ephemeral catchments in Australia and the United States, and two lumped hydrological models. Performance is quantified using predictive reliability, precision, and volumetric bias metrics. We find the choice of heteroscedastic error modeling approach significantly impacts on predictive performance, though no single scheme simultaneously optimizes all performance metrics. The set of Pareto optimal schemes, reflecting performance trade-offs, comprises Box-Cox schemes with λ of 0.2 and 0.5, and the log scheme (λ = 0, perennial catchments only). These schemes significantly outperform even the average-performing remaining schemes (e.g., across ephemeral catchments, median precision tightens from 105% to 40% of observed streamflow, and median biases decrease from 25% to 4%). Theoretical interpretations of empirical results highlight the importance of capturing the skew/kurtosis of raw residuals and reproducing zero flows. Paradoxically, calibration of λ is often counterproductive: in perennial catchments, it tends to overfit low flows at the expense of abysmal precision in high flows. The log-sinh transformation is dominated by the simpler Pareto optimal schemes listed above. Recommendations for researchers and practitioners seeking robust residual error schemes for practical work are provided.

Residue contacts predicted by evolutionary covariance extend the application of ab initio molecular replacement to larger and more challenging protein folds

PubMed Central

Simkovic, Felix; Thomas, Jens M. H.; Keegan, Ronan M.; Winn, Martyn D.; Mayans, Olga; Rigden, Daniel J.

2016-01-01

For many protein families, the deluge of new sequence information together with new statistical protocols now allow the accurate prediction of contacting residues from sequence information alone. This offers the possibility of more accurate ab initio (non-homology-based) structure prediction. Such models can be used in structure solution by molecular replacement (MR) where the target fold is novel or is only distantly related to known structures. Here, AMPLE, an MR pipeline that assembles search-model ensembles from ab initio structure predictions (‘decoys’), is employed to assess the value of contact-assisted ab initio models to the crystallographer. It is demonstrated that evolutionary covariance-derived residue–residue contact predictions improve the quality of ab initio models and, consequently, the success rate of MR using search models derived from them. For targets containing β-structure, decoy quality and MR performance were further improved by the use of a β-strand contact-filtering protocol. Such contact-guided decoys achieved 14 structure solutions from 21 attempted protein targets, compared with nine for simple Rosetta decoys. Previously encountered limitations were superseded in two key respects. Firstly, much larger targets of up to 221 residues in length were solved, which is far larger than the previously benchmarked threshold of 120 residues. Secondly, contact-guided decoys significantly improved success with β-sheet-rich proteins. Overall, the improved performance of contact-guided decoys suggests that MR is now applicable to a significantly wider range of protein targets than were previously tractable, and points to a direct benefit to structural biology from the recent remarkable advances in sequencing. PMID:27437113

Dissipation pattern of flubendiamide residues on capsicum fruit (Capsicum annuum L.) under field and controlled environmental conditions.

PubMed

Buddidathi, Radhika; Mohapatra, Soudamini; Siddamallaiah, Lekha; Manikrao, Gourishankar; Hebbar, Shibara Shankara

2016-01-01

This investigation was undertaken to compare the dissipation pattern of flubendiamide in capsicum fruits under poly-house and open field after giving spray applications at the recommended and double doses of 48 g a.i. ha(-1) and 96 g a.i. ha(-1). Extraction and purification of capsicum fruit samples were carried out by the QuEChERS method. Residues of flubendiamide and its metabolite, des-iodo flubendiamide, were analyzed by high-performance liquid chromatography-photodiode array, and confirmed by liquid chromatography-mass spectrometry/mass spectrometry. Limit of quantification of the method was 0.05 mg kg(-1), and recovery of the insecticides was in the range of 89.6-104.3%, with relative standard deviation being 4.5-11.5%. The measurement uncertainty of the analytical method was in the range of 10.7-15.7%. Initial residue deposits of flubendiamide on capsicum fruits grown under poly-house conditions were (0.977 and 1.834 mg kg(-1)) higher than that grown in the field (0.665 and 1.545 mg kg(-1)). Flubendiamide residues persisted for 15 days in field-grown and for 25 days in poly-house-grown capsicum fruits. The residues were degraded with the half-lives of 4.3-4.7 and 5.6-6.6 days in field and poly-house respectively. Des-iodo flubendiamide was not detected in capsicum fruits or soil. The residues of flubendiamide degraded to below the maximum residue limit notified by Codex Alimentarius Commission (FAO/WHO) after 1 and 6 days in open field, and 3 and 10 days in poly-house. The results of the study indicated that flubendiamide applied to capsicum under controlled environmental conditions required longer pre-harvest interval to allow its residues to dissipate to the safe level.

Left Atrial Appendage Eccentricity and Irregularity Are Associated With Residual Leaks After Percutaneous Closure.

PubMed

Rajwani, Adil; Shirazi, Masoumeh G; Disney, Patrick J S; Wong, Dennis T L; Teo, Karen S L; Delacroix, Sinny; Chokka, Ramesh G; Young, Glenn D; Worthley, Stephen G

2015-12-01

Predictors of residual leak following percutaneous LAA closure were evaluated. Left atrial appendage (LAA) closure aims to exclude this structure from the circulation, typically using a circular occluder. A noncircular orifice is frequently encountered however, and fibrous remodeling of the LAA in atrial fibrillation may restrict orifice deformation. Noncircularity may thus be implicated in the occurrence of residual leak despite an appropriately oversized device. Pre-procedural multislice computerized tomography was used to quantify LAA orifice eccentricity and irregularity. Univariate predictors of residual leak were identified with respect to the orifice, device, and relevant clinical variables, with the nature of any correlations then further evaluated. Eccentricity and irregularity indexes of the orifice in 31 individuals were correlated with residual leak even where the device was appropriately oversized. An eccentricity index of 0.15 predicted a residual leak with 85% sensitivity and 59% specificity. An irregularity index of 0.05 predicted a significant residual leak ≥3 mm with 100% sensitivity and 86% specificity. Orifice size, device size, degree of device oversize, left atrial volume, and pulmonary artery pressure were not predictors of residual leak. Eccentricity and irregularity of the LAA orifice are implicated in residual leak after percutaneous closure even where there is appropriate device over-size. Irregularity index in particular is a novel predictor of residual leak, supporting a closer consideration of orifice morphology before closure. Copyright © 2015 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

How do we assign punishment? The impact of minimal and maximal standards on the evaluation of deviants.

PubMed

Kessler, Thomas; Neumann, Jörg; Mummendey, Amélie; Berthold, Anne; Schubert, Thomas; Waldzus, Sven

2010-09-01

To explain the determinants of negative behavior toward deviants (e.g., punishment), this article examines how people evaluate others on the basis of two types of standards: minimal and maximal. Minimal standards focus on an absolute cutoff point for appropriate behavior; accordingly, the evaluation of others varies dichotomously between acceptable or unacceptable. Maximal standards focus on the degree of deviation from that standard; accordingly, the evaluation of others varies gradually from positive to less positive. This framework leads to the prediction that violation of minimal standards should elicit punishment regardless of the degree of deviation, whereas punishment in response to violations of maximal standards should depend on the degree of deviation. Four studies assessed or manipulated the type of standard and degree of deviation displayed by a target. Results consistently showed the expected interaction between type of standard (minimal and maximal) and degree of deviation on punishment behavior.

Application of a baseflow filter for evaluating model structure suitability of the IHACRES CMD

NASA Astrophysics Data System (ADS)

Kim, H. S.

2015-02-01

The main objective of this study was to assess the predictive uncertainty from the rainfall-runoff model structure coupling a conceptual module (non-linear module) with a metric transfer function module (linear module). The methodology was primarily based on the comparison between the outputs of the rainfall-runoff model and those from an alternative model approach. An alternative model approach was used to minimise uncertainties arising from data and the model structure. A baseflow filter was adopted to better understand deficiencies in the forms of the rainfall-runoff model by avoiding the uncertainties related to data and the model structure. The predictive uncertainty from the model structure was investigated for representative groups of catchments having similar hydrological response characteristics in the upper Murrumbidgee Catchment. In the assessment of model structure suitability, the consistency (or variability) of catchment response over time and space in model performance and parameter values has been investigated to detect problems related to the temporal and spatial variability of the model accuracy. The predictive error caused by model uncertainty was evaluated through analysis of the variability of the model performance and parameters. A graphical comparison of model residuals, effective rainfall estimates and hydrographs was used to determine a model's ability related to systematic model deviation between simulated and observed behaviours and general behavioural differences in the timing and magnitude of peak flows. The model's predictability was very sensitive to catchment response characteristics. The linear module performs reasonably well in the wetter catchments but has considerable difficulties when applied to the drier catchments where a hydrologic response is dominated by quick flow. The non-linear module has a potential limitation in its capacity to capture non-linear processes for converting observed rainfall into effective rainfall in both the wetter and drier catchments. The comparative study based on a better quantification of the accuracy and precision of hydrological modelling predictions yields a better understanding for the potential improvement of model deficiencies.

Research on the Effects of Drying Temperature on Nitrogen Detection of Different Soil Types by Near Infrared Sensors.

PubMed

Nie, Pengcheng; Dong, Tao; He, Yong; Xiao, Shupei

2018-01-29

Soil is a complicated system whose components and mechanisms are complex and difficult to be fully excavated and comprehended. Nitrogen is the key parameter supporting plant growth and development, and is the material basis of plant growth as well. An accurate grasp of soil nitrogen information is the premise of scientific fertilization in precision agriculture, where near infrared sensors are widely used for rapid detection of nutrients in soil. However, soil texture, soil moisture content and drying temperature all affect soil nitrogen detection using near infrared sensors. In order to investigate the effects of drying temperature on the nitrogen detection in black soil, loess and calcium soil, three kinds of soils were detected by near infrared sensors after 25 °C placement (ambient temperature), 50 °C drying (medium temperature), 80 °C drying (medium-high temperature) and 95 °C drying (high temperature). The successive projections algorithm based on multiple linear regression (SPA-MLR), partial least squares (PLS) and competitive adaptive reweighted squares (CARS) were used to model and analyze the spectral information of different soil types. The predictive abilities were assessed using the prediction correlation coefficients (R P ), the root mean squared error of prediction (RMSEP), and the residual predictive deviation (RPD). The results showed that the loess (R P = 0.9721, RMSEP = 0.067 g/kg, RPD = 4.34) and calcium soil (R P = 0.9588, RMSEP = 0.094 g/kg, RPD = 3.89) obtained the best prediction accuracy after 95 °C drying. The detection results of black soil (R P = 0.9486, RMSEP = 0.22 g/kg, RPD = 2.82) after 80 °C drying were the optimum. In conclusion, drying temperature does have an obvious influence on the detection of soil nitrogen by near infrared sensors, and the suitable drying temperature for different soil types was of great significance in enhancing the detection accuracy.

Diffusion-weighted magnetic resonance imaging of parotid glands before and after abatacept therapy in patients with Sjögren's syndrome associated with rheumatoid arthritis: Utility to evaluate and predict response to treatment.

PubMed

Takahashi, Hiroyuki; Tsuboi, Hiroto; Yokosawa, Masahiro; Asashima, Hiromitsu; Hirota, Tomoya; Kondo, Yuya; Matsumoto, Isao; Sumida, Takayuki

2018-03-01

To compare parotid diffusion-weighted images (DWIs) taken before and after abatacept therapy in patients with Sjögren's syndrome (SS) associated with rheumatoid arthritis (RA) and to examine the utility in evaluation and prediction of response to therapy. DWIs of the parotid glands taken at baseline and 52 weeks after initiation of abatacept were analyzed in nine SS patients with RA using relative standard deviation (RSD) of the entire glands and signal intensity ratio (SIR) within the residual parenchyma. The correlation between changes in RSD and SIR and changes in salivary secretion based on Saxon's test was examined. Furthermore, baseline characteristics were compared in patients with increased and decreased salivary secretion after treatment. The predictive power of the parameter at baseline was examined using receiver operating characteristic (ROC) analysis. Abatacept improved salivary secretion from 2076 ± 1535 at baseline to 2857 ± 1431 mg/2 min at 52 weeks (n = 9, p = .05). Increase of salivary secretion was significantly higher in patients with decreased RSD (n = 6) than increased RSD (n = 3) (1241 ± 713, -137 ± 142 mg/2 min, p = .02). The increase and decrease in RSD completely accorded with those of salivary secretion. Furthermore, SIR was the only parameter that was significantly different between patients with posttreatment increase and decrease in salivary secretion (p = .04). ROC analysis showed the sensitivity and specificity of SIR at baseline of ≥13.0 × 10 -2 for the prediction of the response to abatacept were 75.0% and 83.3%, respectively. Parotid DWI seems to be useful for evaluating and predicting the response in salivary secretion to abatacept in SS patients with RA.

How to Avoid Errors in Error Propagation: Prediction Intervals and Confidence Intervals in Forest Biomass

NASA Astrophysics Data System (ADS)

Lilly, P.; Yanai, R. D.; Buckley, H. L.; Case, B. S.; Woollons, R. C.; Holdaway, R. J.; Johnson, J.

2016-12-01

Calculations of forest biomass and elemental content require many measurements and models, each contributing uncertainty to the final estimates. While sampling error is commonly reported, based on replicate plots, error due to uncertainty in the regression used to estimate biomass from tree diameter is usually not quantified. Some published estimates of uncertainty due to the regression models have used the uncertainty in the prediction of individuals, ignoring uncertainty in the mean, while others have propagated uncertainty in the mean while ignoring individual variation. Using the simple case of the calcium concentration of sugar maple leaves, we compare the variation among individuals (the standard deviation) to the uncertainty in the mean (the standard error) and illustrate the declining importance in the prediction of individual concentrations as the number of individuals increases. For allometric models, the analogous statistics are the prediction interval (or the residual variation in the model fit) and the confidence interval (describing the uncertainty in the best fit model). The effect of propagating these two sources of error is illustrated using the mass of sugar maple foliage. The uncertainty in individual tree predictions was large for plots with few trees; for plots with 30 trees or more, the uncertainty in individuals was less important than the uncertainty in the mean. Authors of previously published analyses have reanalyzed their data to show the magnitude of these two sources of uncertainty in scales ranging from experimental plots to entire countries. The most correct analysis will take both sources of uncertainty into account, but for practical purposes, country-level reports of uncertainty in carbon stocks, as required by the IPCC, can ignore the uncertainty in individuals. Ignoring the uncertainty in the mean will lead to exaggerated estimates of confidence in estimates of forest biomass and carbon and nutrient contents.

Validation of an HPLC-UV method for the determination of ceftriaxone sodium residues on stainless steel surface of pharmaceutical manufacturing equipments.

PubMed

Akl, Magda A; Ahmed, Mona A; Ramadan, Ahmed

2011-05-15

In pharmaceutical industry, an important step consists in the removal of possible drug residues from the involved equipments and areas. The cleaning procedures must be validated and methods to determine trace amounts of drugs have, therefore, to be considered with special attention. An HPLC-UV method for the determination of ceftriaxone sodium residues on stainless steel surface was developed and validated in order to control a cleaning procedure. Cotton swabs, moistened with extraction solution (50% water and 50% mobile phase), were used to remove any residues of drugs from stainless steel surfaces, and give recoveries of 91.12, 93.8 and 98.7% for three concentration levels. The precision of the results, reported as the relative standard deviation (RSD), were below 1.5%. The method was validated over a concentration range of 1.15-6.92 μg ml(-1). Low quantities of drug residues were determined by HPLC-UV using a Hypersil ODS 5 μm (250×4.6 mm) at 50 °C with an acetonitrile:water:pH 7:pH 5 (39-55-5.5-0.5) mobile phase at flow rate of 1.5 ml min(-1), an injection volume of 20 μl and were detected at 254 nm. A simple, selective and sensitive HPLC-UV assay for the determination of ceftriaxone sodium residues on stainless steel surfaces was developed, validated and applied. Copyright © 2011 Elsevier B.V. All rights reserved.

A broadband Soleil-Babinet compensator for ultrashort light pulses

NASA Astrophysics Data System (ADS)

Xu, Shixiang; Ma, Yingkun; Cai, Yi; Lu, Xiaowei; Zeng, Xuanke; Chen, Hongyi; Li, Jingzhen

2013-12-01

This letter reports a novel design for a broadband Soleil-Babinet compensator including two pairs of optical wedges plus one plate. According to our birefringent dispersion compensation model, we can eliminate the first-order birefringent phase retardation (BPR) dispersion by using three different birefringent crystals. Our results show a Soleil-Babinet compensator based on a MgF2/ADP/KDP combination can work from 0° to 360° phase compensation with the maximal residual BPR less than 6° within the spectral region from 0.65 to 0.95 μm. The residual BPR of the compensator increases monotonically with the spectral deviation from the designed central wavelength, so our compensator is very suitable to be used for broadband laser pulses with most of their energies around the central wavelengths.

Residual strength assessment of low velocity impact damage of graphite-epoxy laminates

NASA Technical Reports Server (NTRS)

Lal, K. M.

1983-01-01

This report contains the study of Low Velocity Transverse Impact Damage of graphite-epoxy T300/5208 composite laminates. The specimen, 100 mm diameter clamped plates, were impact damaged by a cantilever-type instrumented 1-inch diameter steel ball. Study was limited to impact velocity 6 m/sec. Rectangular strips, 50 mm x 125 mm, were cut from the impact-damage specimens so that the impact damage zone was in the center of the strips. These strips were tested in tension to obtain their residual strength. An energy dissipation model was developed to predict the residual strength from fracture mechanics concepts. Net energy absorbed I(a) was evaluated from coefficient of restitution concepts based on shear dominated theory of fiber-reinforced materials, with the modification that during loading and unloading the shear deformation are respectively elastic-plastic and elastic. Delamination energy I(d) was predicted by assuming that the stiffness of the laminate dropped due to debonding. Fiber-breakage energy, assumed to be equal to the difference of I(a) and I(d), was used to determine the residual strength. Predictions were compared with test results.

The O'Connor cinch revisited.

PubMed Central

Williams, A. T.; Metz, H. S.; Jampolsky, A.

1978-01-01

The modified O'Connor cinch operation is a useful, but little used, adjustable resection operation. For increased understanding of its shortening and adjustment characteristics, a standard cinch was performed in animals and patients with strabismus. Animal studies showed that, as each strand of the cinch was removed, a small, relatively equal release of the cinch effect occurred. Measurement of the shortening obtained in patients with strabismus showed a consistent resection effect of about 4 mm. Review of 17 cases in which the cinch was used as part of the surgical treatment showed the technique to be adjustable by reducing the overcorrection in 6 cases. Ten to 20 prism dioptres of reduction in the deviation was obtained with adjustment of the cinch on the first postoperative day. All 17 cases had satisfactory adjustment. The largest residual deviation was 12 prism dioptres. Images PMID:718816

Effect of Measured Welding Residual Stresses on Crack Growth

NASA Technical Reports Server (NTRS)

Hampton, Roy W.; Nelson, Drew; Doty, Laura W. (Technical Monitor)

1998-01-01

Welding residual stresses in thin plate A516-70 steel and 2219-T87 aluminum butt weldments were measured by the strain-gage hole drilling and X-ray diffraction methods. The residual stress data were used to construct 3D strain fields which were modeled as thermally induced strains. These 3D strain fields were then analyzed with the WARP31) FEM fracture analysis code in order to predict their effect on fatigue and on fracture. For analyses of fatigue crack advance and subsequent verification testing, fatigue crack growth increments were simulated by successive saw-cuts and incremental loading to generate, as a function of crack length, effects on crack growth of the interaction between residual stresses and load induced stresses. The specimen experimental response was characterized and compared to the WARM linear elastic and elastic-plastic fracture mechanics analysis predictions. To perform the fracture analysis, the plate material's crack tearing resistance was determined by tests of thin plate M(T) specimens. Fracture analyses of these specimen were performed using WARP31D to determine the critical Crack Tip Opening Angle [CTOA] of each material. These critical CTOA values were used to predict crack tearing and fracture in the weldments. To verify the fracture predictions, weldment M(T) specimen were tested in monotonic loading to fracture while characterizing the fracture process.

The prediction of progression-free and overall survival in women with an advanced stage of epithelial ovarian carcinoma.

PubMed

Gerestein, C G; Eijkemans, M J C; de Jong, D; van der Burg, M E L; Dykgraaf, R H M; Kooi, G S; Baalbergen, A; Burger, C W; Ansink, A C

2009-02-01

Prognosis in women with ovarian cancer mainly depends on International Federation of Gynecology and Obstetrics stage and the ability to perform optimal cytoreductive surgery. Since ovarian cancer has a heterogeneous presentation and clinical course, predicting progression-free survival (PFS) and overall survival (OS) in the individual patient is difficult. The objective of this study was to determine predictors of PFS and OS in women with advanced stage epithelial ovarian cancer (EOC) after primary cytoreductive surgery and first-line platinum-based chemotherapy. Retrospective observational study. Two teaching hospitals and one university hospital in the south-western part of the Netherlands. Women with advanced stage EOC. All women who underwent primary cytoreductive surgery for advanced stage EOC followed by first-line platinum-based chemotherapy between January 1998 and October 2004 were identified. To investigate independent predictors of PFS and OS, a Cox' proportional hazard model was used. Nomograms were generated with the identified predictive parameters. The primary outcome measure was OS and the secondary outcome measures were response and PFS. A total of 118 women entered the study protocol. Median PFS and OS were 15 and 44 months, respectively. Preoperative platelet count (P = 0.007), and residual disease <1 cm (P = 0.004) predicted PFS with a optimism corrected c-statistic of 0.63. Predictive parameters for OS were preoperative haemoglobin serum concentration (P = 0.012), preoperative platelet counts (P = 0.031) and residual disease <1 cm (P = 0.028) with a optimism corrected c-statistic of 0.67. PFS could be predicted by postoperative residual disease and preoperative platelet counts, whereas residual disease, preoperative platelet counts and preoperative haemoglobin serum concentration were predictive for OS. The proposed nomograms need to be externally validated.

Methods of developing core collections based on the predicted genotypic value of rice ( Oryza sativa L.).

PubMed

Li, C T; Shi, C H; Wu, J G; Xu, H M; Zhang, H Z; Ren, Y L

2004-04-01

The selection of an appropriate sampling strategy and a clustering method is important in the construction of core collections based on predicted genotypic values in order to retain the greatest degree of genetic diversity of the initial collection. In this study, methods of developing rice core collections were evaluated based on the predicted genotypic values for 992 rice varieties with 13 quantitative traits. The genotypic values of the traits were predicted by the adjusted unbiased prediction (AUP) method. Based on the predicted genotypic values, Mahalanobis distances were calculated and employed to measure the genetic similarities among the rice varieties. Six hierarchical clustering methods, including the single linkage, median linkage, centroid, unweighted pair-group average, weighted pair-group average and flexible-beta methods, were combined with random, preferred and deviation sampling to develop 18 core collections of rice germplasm. The results show that the deviation sampling strategy in combination with the unweighted pair-group average method of hierarchical clustering retains the greatest degree of genetic diversities of the initial collection. The core collections sampled using predicted genotypic values had more genetic diversity than those based on phenotypic values.