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Sample records for accurately predict fluid

  1. A 3D-CFD code for accurate prediction of fluid flows and fluid forces in seals

    NASA Technical Reports Server (NTRS)

    Athavale, M. M.; Przekwas, A. J.; Hendricks, R. C.

    1994-01-01

    Current and future turbomachinery requires advanced seal configurations to control leakage, inhibit mixing of incompatible fluids and to control the rotodynamic response. In recognition of a deficiency in the existing predictive methodology for seals, a seven year effort was established in 1990 by NASA's Office of Aeronautics Exploration and Technology, under the Earth-to-Orbit Propulsion program, to develop validated Computational Fluid Dynamics (CFD) concepts, codes and analyses for seals. The effort will provide NASA and the U.S. Aerospace Industry with advanced CFD scientific codes and industrial codes for analyzing and designing turbomachinery seals. An advanced 3D CFD cylindrical seal code has been developed, incorporating state-of-the-art computational methodology for flow analysis in straight, tapered and stepped seals. Relevant computational features of the code include: stationary/rotating coordinates, cylindrical and general Body Fitted Coordinates (BFC) systems, high order differencing schemes, colocated variable arrangement, advanced turbulence models, incompressible/compressible flows, and moving grids. This paper presents the current status of code development, code demonstration for predicting rotordynamic coefficients, numerical parametric study of entrance loss coefficients for generic annular seals, and plans for code extensions to labyrinth, damping, and other seal configurations.

  2. Accurate measurement of unsteady state fluid temperature

    NASA Astrophysics Data System (ADS)

    Jaremkiewicz, Magdalena

    2017-03-01

    In this paper, two accurate methods for determining the transient fluid temperature were presented. Measurements were conducted for boiling water since its temperature is known. At the beginning the thermometers are at the ambient temperature and next they are immediately immersed into saturated water. The measurements were carried out with two thermometers of different construction but with the same housing outer diameter equal to 15 mm. One of them is a K-type industrial thermometer widely available commercially. The temperature indicated by the thermometer was corrected considering the thermometers as the first or second order inertia devices. The new design of a thermometer was proposed and also used to measure the temperature of boiling water. Its characteristic feature is a cylinder-shaped housing with the sheath thermocouple located in its center. The temperature of the fluid was determined based on measurements taken in the axis of the solid cylindrical element (housing) using the inverse space marching method. Measurements of the transient temperature of the air flowing through the wind tunnel using the same thermometers were also carried out. The proposed measurement technique provides more accurate results compared with measurements using industrial thermometers in conjunction with simple temperature correction using the inertial thermometer model of the first or second order. By comparing the results, it was demonstrated that the new thermometer allows obtaining the fluid temperature much faster and with higher accuracy in comparison to the industrial thermometer. Accurate measurements of the fast changing fluid temperature are possible due to the low inertia thermometer and fast space marching method applied for solving the inverse heat conduction problem.

  3. New model accurately predicts reformate composition

    SciTech Connect

    Ancheyta-Juarez, J.; Aguilar-Rodriguez, E. )

    1994-01-31

    Although naphtha reforming is a well-known process, the evolution of catalyst formulation, as well as new trends in gasoline specifications, have led to rapid evolution of the process, including: reactor design, regeneration mode, and operating conditions. Mathematical modeling of the reforming process is an increasingly important tool. It is fundamental to the proper design of new reactors and revamp of existing ones. Modeling can be used to optimize operating conditions, analyze the effects of process variables, and enhance unit performance. Instituto Mexicano del Petroleo has developed a model of the catalytic reforming process that accurately predicts reformate composition at the higher-severity conditions at which new reformers are being designed. The new AA model is more accurate than previous proposals because it takes into account the effects of temperature and pressure on the rate constants of each chemical reaction.

  4. An accurate equation of state for fluids and solids.

    PubMed

    Parsafar, G A; Spohr, H V; Patey, G N

    2009-09-03

    A simple functional form for a general equation of state based on an effective near-neighbor pair interaction of an extended Lennard-Jones (12,6,3) type is given and tested against experimental data for a wide variety of fluids and solids. Computer simulation results for ionic liquids are used for further evaluation. For fluids, there appears to be no upper density limitation on the equation of state. The lower density limit for isotherms near the critical temperature is the critical density. The equation of state gives a good description of all types of fluids, nonpolar (including long-chain hydrocarbons), polar, hydrogen-bonded, and metallic, at temperatures ranging from the triple point to the highest temperature for which there is experimental data. For solids, the equation of state is very accurate for all types considered, including covalent, molecular, metallic, and ionic systems. The experimental pvT data available for solids does not reveal any pressure or temperature limitations. An analysis of the importance and possible underlying physical significance of the terms in the equation of state is given.

  5. A gene expression biomarker accurately predicts estrogen ...

    EPA Pesticide Factsheets

    The EPA’s vision for the Endocrine Disruptor Screening Program (EDSP) in the 21st Century (EDSP21) includes utilization of high-throughput screening (HTS) assays coupled with computational modeling to prioritize chemicals with the goal of eventually replacing current Tier 1 screening tests. The ToxCast program currently includes 18 HTS in vitro assays that evaluate the ability of chemicals to modulate estrogen receptor α (ERα), an important endocrine target. We propose microarray-based gene expression profiling as a complementary approach to predict ERα modulation and have developed computational methods to identify ERα modulators in an existing database of whole-genome microarray data. The ERα biomarker consisted of 46 ERα-regulated genes with consistent expression patterns across 7 known ER agonists and 3 known ER antagonists. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression data sets from experiments in MCF-7 cells. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% or 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) OECD ER reference chemicals including “very weak” agonists and replicated predictions based on 18 in vitro ER-associated HTS assays. For 114 chemicals present in both the HTS data and the MCF-7 c

  6. You Can Accurately Predict Land Acquisition Costs.

    ERIC Educational Resources Information Center

    Garrigan, Richard

    1967-01-01

    Land acquisition costs were tested for predictability based upon the 1962 assessed valuations of privately held land acquired for campus expansion by the University of Wisconsin from 1963-1965. By correlating the land acquisition costs of 108 properties acquired during the 3 year period with--(1) the assessed value of the land, (2) the assessed…

  7. Towards more accurate vegetation mortality predictions

    DOE PAGES

    Sevanto, Sanna Annika; Xu, Chonggang

    2016-09-26

    Predicting the fate of vegetation under changing climate is one of the major challenges of the climate modeling community. Here, terrestrial vegetation dominates the carbon and water cycles over land areas, and dramatic changes in vegetation cover resulting from stressful environmental conditions such as drought feed directly back to local and regional climate, potentially leading to a vicious cycle where vegetation recovery after a disturbance is delayed or impossible.

  8. Accurate method for including solid-fluid boundary interactions in mesoscopic model fluids

    SciTech Connect

    Berkenbos, A. Lowe, C.P.

    2008-04-20

    Particle models are attractive methods for simulating the dynamics of complex mesoscopic fluids. Many practical applications of this methodology involve flow through a solid geometry. As the system is modeled using particles whose positions move continuously in space, one might expect that implementing the correct stick boundary condition exactly at the solid-fluid interface is straightforward. After all, unlike discrete methods there is no mapping onto a grid to contend with. In this article we describe a method that, for axisymmetric flows, imposes both the no-slip condition and continuity of stress at the interface. We show that the new method then accurately reproduces correct hydrodynamic behavior right up to the location of the interface. As such, computed flow profiles are correct even using a relatively small number of particles to model the fluid.

  9. A predictable and accurate technique with elastomeric impression materials.

    PubMed

    Barghi, N; Ontiveros, J C

    1999-08-01

    A method for obtaining more predictable and accurate final impressions with polyvinylsiloxane impression materials in conjunction with stock trays is proposed and tested. Heavy impression material is used in advance for construction of a modified custom tray, while extra-light material is used for obtaining a more accurate final impression.

  10. Accurate torque-speed performance prediction for brushless dc motors

    NASA Astrophysics Data System (ADS)

    Gipper, Patrick D.

    Desirable characteristics of the brushless dc motor (BLDCM) have resulted in their application for electrohydrostatic (EH) and electromechanical (EM) actuation systems. But to effectively apply the BLDCM requires accurate prediction of performance. The minimum necessary performance characteristics are motor torque versus speed, peak and average supply current and efficiency. BLDCM nonlinear simulation software specifically adapted for torque-speed prediction is presented. The capability of the software to quickly and accurately predict performance has been verified on fractional to integral HP motor sizes, and is presented. Additionally, the capability of torque-speed prediction with commutation angle advance is demonstrated.

  11. Fluid flow in nanopores: Accurate boundary conditions for carbon nanotubes

    NASA Astrophysics Data System (ADS)

    Sokhan, Vladimir P.; Nicholson, David; Quirke, Nicholas

    2002-11-01

    Steady-state Poiseuille flow of a simple fluid in carbon nanopores under a gravitylike force is simulated using a realistic empirical many-body potential model for carbon. Building on our previous study of slit carbon nanopores we show that fluid flow in a nanotube is also characterized by a large slip length. By analyzing temporal profiles of the velocity components of particles colliding with the wall we obtain values of the Maxwell coefficient defining the fraction of molecules thermalized by the wall and, for the first time, propose slip boundary conditions for smooth continuum surfaces such that they are equivalent in adsorption, diffusion, and fluid flow properties to fully dynamic atomistic models.

  12. On the Accurate Prediction of CME Arrival At the Earth

    NASA Astrophysics Data System (ADS)

    Zhang, Jie; Hess, Phillip

    2016-07-01

    We will discuss relevant issues regarding the accurate prediction of CME arrival at the Earth, from both observational and theoretical points of view. In particular, we clarify the importance of separating the study of CME ejecta from the ejecta-driven shock in interplanetary CMEs (ICMEs). For a number of CME-ICME events well observed by SOHO/LASCO, STEREO-A and STEREO-B, we carry out the 3-D measurements by superimposing geometries onto both the ejecta and sheath separately. These measurements are then used to constrain a Drag-Based Model, which is improved through a modification of including height dependence of the drag coefficient into the model. Combining all these factors allows us to create predictions for both fronts at 1 AU and compare with actual in-situ observations. We show an ability to predict the sheath arrival with an average error of under 4 hours, with an RMS error of about 1.5 hours. For the CME ejecta, the error is less than two hours with an RMS error within an hour. Through using the best observations of CMEs, we show the power of our method in accurately predicting CME arrival times. The limitation and implications of our accurate prediction method will be discussed.

  13. Predicting and measuring fluid responsiveness with echocardiography.

    PubMed

    Miller, Ashley; Mandeville, Justin

    2016-06-01

    Echocardiography is ideally suited to guide fluid resuscitation in critically ill patients. It can be used to assess fluid responsiveness by looking at the left ventricle, aortic outflow, inferior vena cava and right ventricle. Static measurements and dynamic variables based on heart-lung interactions all combine to predict and measure fluid responsiveness and assess response to intravenous fluid resuscitation. Thorough knowledge of these variables, the physiology behind them and the pitfalls in their use allows the echocardiographer to confidently assess these patients and in combination with clinical judgement manage them appropriately.

  14. Predicting and measuring fluid responsiveness with echocardiography

    PubMed Central

    Mandeville, Justin

    2016-01-01

    Echocardiography is ideally suited to guide fluid resuscitation in critically ill patients. It can be used to assess fluid responsiveness by looking at the left ventricle, aortic outflow, inferior vena cava and right ventricle. Static measurements and dynamic variables based on heart–lung interactions all combine to predict and measure fluid responsiveness and assess response to intravenous fluid resuscitation. Thorough knowledge of these variables, the physiology behind them and the pitfalls in their use allows the echocardiographer to confidently assess these patients and in combination with clinical judgement manage them appropriately. PMID:27249550

  15. Can numerical simulations accurately predict hydrodynamic instabilities in liquid films?

    NASA Astrophysics Data System (ADS)

    Denner, Fabian; Charogiannis, Alexandros; Pradas, Marc; van Wachem, Berend G. M.; Markides, Christos N.; Kalliadasis, Serafim

    2014-11-01

    Understanding the dynamics of hydrodynamic instabilities in liquid film flows is an active field of research in fluid dynamics and non-linear science in general. Numerical simulations offer a powerful tool to study hydrodynamic instabilities in film flows and can provide deep insights into the underlying physical phenomena. However, the direct comparison of numerical results and experimental results is often hampered by several reasons. For instance, in numerical simulations the interface representation is problematic and the governing equations and boundary conditions may be oversimplified, whereas in experiments it is often difficult to extract accurate information on the fluid and its behavior, e.g. determine the fluid properties when the liquid contains particles for PIV measurements. In this contribution we present the latest results of our on-going, extensive study on hydrodynamic instabilities in liquid film flows, which includes direct numerical simulations, low-dimensional modelling as well as experiments. The major focus is on wave regimes, wave height and wave celerity as a function of Reynolds number and forcing frequency of a falling liquid film. Specific attention is paid to the differences in numerical and experimental results and the reasons for these differences. The authors are grateful to the EPSRC for their financial support (Grant EP/K008595/1).

  16. Passive samplers accurately predict PAH levels in resident crayfish.

    PubMed

    Paulik, L Blair; Smith, Brian W; Bergmann, Alan J; Sower, Greg J; Forsberg, Norman D; Teeguarden, Justin G; Anderson, Kim A

    2016-02-15

    Contamination of resident aquatic organisms is a major concern for environmental risk assessors. However, collecting organisms to estimate risk is often prohibitively time and resource-intensive. Passive sampling accurately estimates resident organism contamination, and it saves time and resources. This study used low density polyethylene (LDPE) passive water samplers to predict polycyclic aromatic hydrocarbon (PAH) levels in signal crayfish, Pacifastacus leniusculus. Resident crayfish were collected at 5 sites within and outside of the Portland Harbor Superfund Megasite (PHSM) in the Willamette River in Portland, Oregon. LDPE deployment was spatially and temporally paired with crayfish collection. Crayfish visceral and tail tissue, as well as water-deployed LDPE, were extracted and analyzed for 62 PAHs using GC-MS/MS. Freely-dissolved concentrations (Cfree) of PAHs in water were calculated from concentrations in LDPE. Carcinogenic risks were estimated for all crayfish tissues, using benzo[a]pyrene equivalent concentrations (BaPeq). ∑PAH were 5-20 times higher in viscera than in tails, and ∑BaPeq were 6-70 times higher in viscera than in tails. Eating only tail tissue of crayfish would therefore significantly reduce carcinogenic risk compared to also eating viscera. Additionally, PAH levels in crayfish were compared to levels in crayfish collected 10 years earlier. PAH levels in crayfish were higher upriver of the PHSM and unchanged within the PHSM after the 10-year period. Finally, a linear regression model predicted levels of 34 PAHs in crayfish viscera with an associated R-squared value of 0.52 (and a correlation coefficient of 0.72), using only the Cfree PAHs in water. On average, the model predicted PAH concentrations in crayfish tissue within a factor of 2.4 ± 1.8 of measured concentrations. This affirms that passive water sampling accurately estimates PAH contamination in crayfish. Furthermore, the strong predictive ability of this simple model suggests

  17. Inverter Modeling For Accurate Energy Predictions Of Tracking HCPV Installations

    NASA Astrophysics Data System (ADS)

    Bowman, J.; Jensen, S.; McDonald, Mark

    2010-10-01

    High efficiency high concentration photovoltaic (HCPV) solar plants of megawatt scale are now operational, and opportunities for expanded adoption are plentiful. However, effective bidding for sites requires reliable prediction of energy production. HCPV module nameplate power is rated for specific test conditions; however, instantaneous HCPV power varies due to site specific irradiance and operating temperature, and is degraded by soiling, protective stowing, shading, and electrical connectivity. These factors interact with the selection of equipment typically supplied by third parties, e.g., wire gauge and inverters. We describe a time sequence model accurately accounting for these effects that predicts annual energy production, with specific reference to the impact of the inverter on energy output and interactions between system-level design decisions and the inverter. We will also show two examples, based on an actual field design, of inverter efficiency calculations and the interaction between string arrangements and inverter selection.

  18. Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates

    SciTech Connect

    Wang, Dong; Dasari, Surendra; Chambers, Matthew C.; Holman, Jerry D.; Chen, Kan; Liebler, Daniel; Orton, Daniel J.; Purvine, Samuel O.; Monroe, Matthew E.; Chung, Chang Y.; Rose, Kristie L.; Tabb, David L.

    2013-03-07

    In shotgun proteomics, database search algorithms rely on fragmentation models to predict fragment ions that should be observed for a given peptide sequence. The most widely used strategy (Naive model) is oversimplified, cleaving all peptide bonds with equal probability to produce fragments of all charges below that of the precursor ion. More accurate models, based on fragmentation simulation, are too computationally intensive for on-the-fly use in database search algorithms. We have created an ordinal-regression-based model called Basophile that takes fragment size and basic residue distribution into account when determining the charge retention during CID/higher-energy collision induced dissociation (HCD) of charged peptides. This model improves the accuracy of predictions by reducing the number of unnecessary fragments that are routinely predicted for highly-charged precursors. Basophile increased the identification rates by 26% (on average) over the Naive model, when analyzing triply-charged precursors from ion trap data. Basophile achieves simplicity and speed by solving the prediction problem with an ordinal regression equation, which can be incorporated into any database search software for shotgun proteomic identification.

  19. Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates

    DOE PAGES

    Wang, Dong; Dasari, Surendra; Chambers, Matthew C.; ...

    2013-03-07

    In shotgun proteomics, database search algorithms rely on fragmentation models to predict fragment ions that should be observed for a given peptide sequence. The most widely used strategy (Naive model) is oversimplified, cleaving all peptide bonds with equal probability to produce fragments of all charges below that of the precursor ion. More accurate models, based on fragmentation simulation, are too computationally intensive for on-the-fly use in database search algorithms. We have created an ordinal-regression-based model called Basophile that takes fragment size and basic residue distribution into account when determining the charge retention during CID/higher-energy collision induced dissociation (HCD) of chargedmore » peptides. This model improves the accuracy of predictions by reducing the number of unnecessary fragments that are routinely predicted for highly-charged precursors. Basophile increased the identification rates by 26% (on average) over the Naive model, when analyzing triply-charged precursors from ion trap data. Basophile achieves simplicity and speed by solving the prediction problem with an ordinal regression equation, which can be incorporated into any database search software for shotgun proteomic identification.« less

  20. Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates

    PubMed Central

    Wang, Dong; Dasari, Surendra; Chambers, Matthew C.; Holman, Jerry D.; Chen, Kan; Liebler, Daniel C.; Orton, Daniel J.; Purvine, Samuel O.; Monroe, Matthew E.; Chung, Chang Y.; Rose, Kristie L.; Tabb, David L.

    2013-01-01

    In shotgun proteomics, database search algorithms rely on fragmentation models to predict fragment ions that should be observed for a given peptide sequence. The most widely used strategy (Naive model) is oversimplified, cleaving all peptide bonds with equal probability to produce fragments of all charges below that of the precursor ion. More accurate models, based on fragmentation simulation, are too computationally intensive for on-the-fly use in database search algorithms. We have created an ordinal-regression-based model called Basophile that takes fragment size and basic residue distribution into account when determining the charge retention during CID/higher-energy collision induced dissociation (HCD) of charged peptides. This model improves the accuracy of predictions by reducing the number of unnecessary fragments that are routinely predicted for highly-charged precursors. Basophile increased the identification rates by 26% (on average) over the Naive model, when analyzing triply-charged precursors from ion trap data. Basophile achieves simplicity and speed by solving the prediction problem with an ordinal regression equation, which can be incorporated into any database search software for shotgun proteomic identification. PMID:23499924

  1. Rapid and Highly Accurate Prediction of Poor Loop Diuretic Natriuretic Response in Patients With Heart Failure

    PubMed Central

    Testani, Jeffrey M.; Hanberg, Jennifer S.; Cheng, Susan; Rao, Veena; Onyebeke, Chukwuma; Laur, Olga; Kula, Alexander; Chen, Michael; Wilson, F. Perry; Darlington, Andrew; Bellumkonda, Lavanya; Jacoby, Daniel; Tang, W. H. Wilson; Parikh, Chirag R.

    2015-01-01

    Background Removal of excess sodium and fluid is a primary therapeutic objective in acute decompensated heart failure (ADHF) and commonly monitored with fluid balance and weight loss. However, these parameters are frequently inaccurate or not collected and require a delay of several hours after diuretic administration before they are available. Accessible tools for rapid and accurate prediction of diuretic response are needed. Methods and Results Based on well-established renal physiologic principles an equation was derived to predict net sodium output using a spot urine sample obtained one or two hours following loop diuretic administration. This equation was then prospectively validated in 50 ADHF patients using meticulously obtained timed 6-hour urine collections to quantitate loop diuretic induced cumulative sodium output. Poor natriuretic response was defined as a cumulative sodium output of <50 mmol, a threshold that would result in a positive sodium balance with twice-daily diuretic dosing. Following a median dose of 3 mg (2–4 mg) of intravenous bumetanide, 40% of the population had a poor natriuretic response. The correlation between measured and predicted sodium output was excellent (r=0.91, p<0.0001). Poor natriuretic response could be accurately predicted with the sodium prediction equation (AUC=0.95, 95% CI 0.89–1.0, p<0.0001). Clinically recorded net fluid output had a weaker correlation (r=0.66, p<0.001) and lesser ability to predict poor natriuretic response (AUC=0.76, 95% CI 0.63–0.89, p=0.002). Conclusions In patients being treated for ADHF, poor natriuretic response can be predicted soon after diuretic administration with excellent accuracy using a spot urine sample. PMID:26721915

  2. Mouse models of human AML accurately predict chemotherapy response

    PubMed Central

    Zuber, Johannes; Radtke, Ina; Pardee, Timothy S.; Zhao, Zhen; Rappaport, Amy R.; Luo, Weijun; McCurrach, Mila E.; Yang, Miao-Miao; Dolan, M. Eileen; Kogan, Scott C.; Downing, James R.; Lowe, Scott W.

    2009-01-01

    The genetic heterogeneity of cancer influences the trajectory of tumor progression and may underlie clinical variation in therapy response. To model such heterogeneity, we produced genetically and pathologically accurate mouse models of common forms of human acute myeloid leukemia (AML) and developed methods to mimic standard induction chemotherapy and efficiently monitor therapy response. We see that murine AMLs harboring two common human AML genotypes show remarkably diverse responses to conventional therapy that mirror clinical experience. Specifically, murine leukemias expressing the AML1/ETO fusion oncoprotein, associated with a favorable prognosis in patients, show a dramatic response to induction chemotherapy owing to robust activation of the p53 tumor suppressor network. Conversely, murine leukemias expressing MLL fusion proteins, associated with a dismal prognosis in patients, are drug-resistant due to an attenuated p53 response. Our studies highlight the importance of genetic information in guiding the treatment of human AML, functionally establish the p53 network as a central determinant of chemotherapy response in AML, and demonstrate that genetically engineered mouse models of human cancer can accurately predict therapy response in patients. PMID:19339691

  3. Mouse models of human AML accurately predict chemotherapy response.

    PubMed

    Zuber, Johannes; Radtke, Ina; Pardee, Timothy S; Zhao, Zhen; Rappaport, Amy R; Luo, Weijun; McCurrach, Mila E; Yang, Miao-Miao; Dolan, M Eileen; Kogan, Scott C; Downing, James R; Lowe, Scott W

    2009-04-01

    The genetic heterogeneity of cancer influences the trajectory of tumor progression and may underlie clinical variation in therapy response. To model such heterogeneity, we produced genetically and pathologically accurate mouse models of common forms of human acute myeloid leukemia (AML) and developed methods to mimic standard induction chemotherapy and efficiently monitor therapy response. We see that murine AMLs harboring two common human AML genotypes show remarkably diverse responses to conventional therapy that mirror clinical experience. Specifically, murine leukemias expressing the AML1/ETO fusion oncoprotein, associated with a favorable prognosis in patients, show a dramatic response to induction chemotherapy owing to robust activation of the p53 tumor suppressor network. Conversely, murine leukemias expressing MLL fusion proteins, associated with a dismal prognosis in patients, are drug-resistant due to an attenuated p53 response. Our studies highlight the importance of genetic information in guiding the treatment of human AML, functionally establish the p53 network as a central determinant of chemotherapy response in AML, and demonstrate that genetically engineered mouse models of human cancer can accurately predict therapy response in patients.

  4. Turbulence Models for Accurate Aerothermal Prediction in Hypersonic Flows

    NASA Astrophysics Data System (ADS)

    Zhang, Xiang-Hong; Wu, Yi-Zao; Wang, Jiang-Feng

    Accurate description of the aerodynamic and aerothermal environment is crucial to the integrated design and optimization for high performance hypersonic vehicles. In the simulation of aerothermal environment, the effect of viscosity is crucial. The turbulence modeling remains a major source of uncertainty in the computational prediction of aerodynamic forces and heating. In this paper, three turbulent models were studied: the one-equation eddy viscosity transport model of Spalart-Allmaras, the Wilcox k-ω model and the Menter SST model. For the k-ω model and SST model, the compressibility correction, press dilatation and low Reynolds number correction were considered. The influence of these corrections for flow properties were discussed by comparing with the results without corrections. In this paper the emphasis is on the assessment and evaluation of the turbulence models in prediction of heat transfer as applied to a range of hypersonic flows with comparison to experimental data. This will enable establishing factor of safety for the design of thermal protection systems of hypersonic vehicle.

  5. Simple Mathematical Models Do Not Accurately Predict Early SIV Dynamics

    PubMed Central

    Noecker, Cecilia; Schaefer, Krista; Zaccheo, Kelly; Yang, Yiding; Day, Judy; Ganusov, Vitaly V.

    2015-01-01

    Upon infection of a new host, human immunodeficiency virus (HIV) replicates in the mucosal tissues and is generally undetectable in circulation for 1–2 weeks post-infection. Several interventions against HIV including vaccines and antiretroviral prophylaxis target virus replication at this earliest stage of infection. Mathematical models have been used to understand how HIV spreads from mucosal tissues systemically and what impact vaccination and/or antiretroviral prophylaxis has on viral eradication. Because predictions of such models have been rarely compared to experimental data, it remains unclear which processes included in these models are critical for predicting early HIV dynamics. Here we modified the “standard” mathematical model of HIV infection to include two populations of infected cells: cells that are actively producing the virus and cells that are transitioning into virus production mode. We evaluated the effects of several poorly known parameters on infection outcomes in this model and compared model predictions to experimental data on infection of non-human primates with variable doses of simian immunodifficiency virus (SIV). First, we found that the mode of virus production by infected cells (budding vs. bursting) has a minimal impact on the early virus dynamics for a wide range of model parameters, as long as the parameters are constrained to provide the observed rate of SIV load increase in the blood of infected animals. Interestingly and in contrast with previous results, we found that the bursting mode of virus production generally results in a higher probability of viral extinction than the budding mode of virus production. Second, this mathematical model was not able to accurately describe the change in experimentally determined probability of host infection with increasing viral doses. Third and finally, the model was also unable to accurately explain the decline in the time to virus detection with increasing viral dose. These results

  6. Prediction of viscosity of dense fluid mixtures

    NASA Astrophysics Data System (ADS)

    Royal, Damian D.; Vesovic, Velisa; Trusler, J. P. Martin; Wakeham, William. A.

    The Vesovic-Wakeham (VW) method of predicting the viscosity of dense fluid mixtures has been improved by implementing new mixing rules based on the rigid sphere formalism. The proposed mixing rules are based on both Lebowitz's solution of the Percus-Yevick equation and on the Carnahan-Starling equation. The predictions of the modified VW method have been compared with experimental viscosity data for a number of diverse fluid mixtures: natural gas, hexane + hheptane, hexane + octane, cyclopentane + toluene, and a ternary mixture of hydrofluorocarbons (R32 + R125 + R134a). The results indicate that the proposed improvements make possible the extension of the original VW method to liquid mixtures and to mixtures containing polar species, while retaining its original accuracy.

  7. Fast and Accurate Prediction of Stratified Steel Temperature During Holding Period of Ladle

    NASA Astrophysics Data System (ADS)

    Deodhar, Anirudh; Singh, Umesh; Shukla, Rishabh; Gautham, B. P.; Singh, Amarendra K.

    2017-04-01

    Thermal stratification of liquid steel in a ladle during the holding period and the teeming operation has a direct bearing on the superheat available at the caster and hence on the caster set points such as casting speed and cooling rates. The changes in the caster set points are typically carried out based on temperature measurements at the end of tundish outlet. Thermal prediction models provide advance knowledge of the influence of process and design parameters on the steel temperature at various stages. Therefore, they can be used in making accurate decisions about the caster set points in real time. However, this requires both fast and accurate thermal prediction models. In this work, we develop a surrogate model for the prediction of thermal stratification using data extracted from a set of computational fluid dynamics (CFD) simulations, pre-determined using design of experiments technique. Regression method is used for training the predictor. The model predicts the stratified temperature profile instantaneously, for a given set of process parameters such as initial steel temperature, refractory heat content, slag thickness, and holding time. More than 96 pct of the predicted values are within an error range of ±5 K (±5 °C), when compared against corresponding CFD results. Considering its accuracy and computational efficiency, the model can be extended for thermal control of casting operations. This work also sets a benchmark for developing similar thermal models for downstream processes such as tundish and caster.

  8. Fast and Accurate Prediction of Stratified Steel Temperature During Holding Period of Ladle

    NASA Astrophysics Data System (ADS)

    Deodhar, Anirudh; Singh, Umesh; Shukla, Rishabh; Gautham, B. P.; Singh, Amarendra K.

    2016-12-01

    Thermal stratification of liquid steel in a ladle during the holding period and the teeming operation has a direct bearing on the superheat available at the caster and hence on the caster set points such as casting speed and cooling rates. The changes in the caster set points are typically carried out based on temperature measurements at the end of tundish outlet. Thermal prediction models provide advance knowledge of the influence of process and design parameters on the steel temperature at various stages. Therefore, they can be used in making accurate decisions about the caster set points in real time. However, this requires both fast and accurate thermal prediction models. In this work, we develop a surrogate model for the prediction of thermal stratification using data extracted from a set of computational fluid dynamics (CFD) simulations, pre-determined using design of experiments technique. Regression method is used for training the predictor. The model predicts the stratified temperature profile instantaneously, for a given set of process parameters such as initial steel temperature, refractory heat content, slag thickness, and holding time. More than 96 pct of the predicted values are within an error range of ±5 K (±5 °C), when compared against corresponding CFD results. Considering its accuracy and computational efficiency, the model can be extended for thermal control of casting operations. This work also sets a benchmark for developing similar thermal models for downstream processes such as tundish and caster.

  9. Accurate prediction of wall shear stress in a stented artery: newtonian versus non-newtonian models.

    PubMed

    Mejia, Juan; Mongrain, Rosaire; Bertrand, Olivier F

    2011-07-01

    A significant amount of evidence linking wall shear stress to neointimal hyperplasia has been reported in the literature. As a result, numerical and experimental models have been created to study the influence of stent design on wall shear stress. Traditionally, blood has been assumed to behave as a Newtonian fluid, but recently that assumption has been challenged. The use of a linear model; however, can reduce computational cost, and allow the use of Newtonian fluids (e.g., glycerine and water) instead of a blood analog fluid in an experimental setup. Therefore, it is of interest whether a linear model can be used to accurately predict the wall shear stress caused by a non-Newtonian fluid such as blood within a stented arterial segment. The present work compares the resulting wall shear stress obtained using two linear and one nonlinear model under the same flow waveform. All numerical models are fully three-dimensional, transient, and incorporate a realistic stent geometry. It is shown that traditional linear models (based on blood's lowest viscosity limit, 3.5 Pa s) underestimate the wall shear stress within a stented arterial segment, which can lead to an overestimation of the risk of restenosis. The second linear model, which uses a characteristic viscosity (based on an average strain rate, 4.7 Pa s), results in higher wall shear stress levels, but which are still substantially below those of the nonlinear model. It is therefore shown that nonlinear models result in more accurate predictions of wall shear stress within a stented arterial segment.

  10. Fast and accurate predictions of covalent bonds in chemical space

    NASA Astrophysics Data System (ADS)

    Chang, K. Y. Samuel; Fias, Stijn; Ramakrishnan, Raghunathan; von Lilienfeld, O. Anatole

    2016-05-01

    We assess the predictive accuracy of perturbation theory based estimates of changes in covalent bonding due to linear alchemical interpolations among molecules. We have investigated σ bonding to hydrogen, as well as σ and π bonding between main-group elements, occurring in small sets of iso-valence-electronic molecules with elements drawn from second to fourth rows in the p-block of the periodic table. Numerical evidence suggests that first order Taylor expansions of covalent bonding potentials can achieve high accuracy if (i) the alchemical interpolation is vertical (fixed geometry), (ii) it involves elements from the third and fourth rows of the periodic table, and (iii) an optimal reference geometry is used. This leads to near linear changes in the bonding potential, resulting in analytical predictions with chemical accuracy (˜1 kcal/mol). Second order estimates deteriorate the prediction. If initial and final molecules differ not only in composition but also in geometry, all estimates become substantially worse, with second order being slightly more accurate than first order. The independent particle approximation based second order perturbation theory performs poorly when compared to the coupled perturbed or finite difference approach. Taylor series expansions up to fourth order of the potential energy curve of highly symmetric systems indicate a finite radius of convergence, as illustrated for the alchemical stretching of H 2+ . Results are presented for (i) covalent bonds to hydrogen in 12 molecules with 8 valence electrons (CH4, NH3, H2O, HF, SiH4, PH3, H2S, HCl, GeH4, AsH3, H2Se, HBr); (ii) main-group single bonds in 9 molecules with 14 valence electrons (CH3F, CH3Cl, CH3Br, SiH3F, SiH3Cl, SiH3Br, GeH3F, GeH3Cl, GeH3Br); (iii) main-group double bonds in 9 molecules with 12 valence electrons (CH2O, CH2S, CH2Se, SiH2O, SiH2S, SiH2Se, GeH2O, GeH2S, GeH2Se); (iv) main-group triple bonds in 9 molecules with 10 valence electrons (HCN, HCP, HCAs, HSiN, HSi

  11. Fast and accurate predictions of covalent bonds in chemical space.

    PubMed

    Chang, K Y Samuel; Fias, Stijn; Ramakrishnan, Raghunathan; von Lilienfeld, O Anatole

    2016-05-07

    We assess the predictive accuracy of perturbation theory based estimates of changes in covalent bonding due to linear alchemical interpolations among molecules. We have investigated σ bonding to hydrogen, as well as σ and π bonding between main-group elements, occurring in small sets of iso-valence-electronic molecules with elements drawn from second to fourth rows in the p-block of the periodic table. Numerical evidence suggests that first order Taylor expansions of covalent bonding potentials can achieve high accuracy if (i) the alchemical interpolation is vertical (fixed geometry), (ii) it involves elements from the third and fourth rows of the periodic table, and (iii) an optimal reference geometry is used. This leads to near linear changes in the bonding potential, resulting in analytical predictions with chemical accuracy (∼1 kcal/mol). Second order estimates deteriorate the prediction. If initial and final molecules differ not only in composition but also in geometry, all estimates become substantially worse, with second order being slightly more accurate than first order. The independent particle approximation based second order perturbation theory performs poorly when compared to the coupled perturbed or finite difference approach. Taylor series expansions up to fourth order of the potential energy curve of highly symmetric systems indicate a finite radius of convergence, as illustrated for the alchemical stretching of H2 (+). Results are presented for (i) covalent bonds to hydrogen in 12 molecules with 8 valence electrons (CH4, NH3, H2O, HF, SiH4, PH3, H2S, HCl, GeH4, AsH3, H2Se, HBr); (ii) main-group single bonds in 9 molecules with 14 valence electrons (CH3F, CH3Cl, CH3Br, SiH3F, SiH3Cl, SiH3Br, GeH3F, GeH3Cl, GeH3Br); (iii) main-group double bonds in 9 molecules with 12 valence electrons (CH2O, CH2S, CH2Se, SiH2O, SiH2S, SiH2Se, GeH2O, GeH2S, GeH2Se); (iv) main-group triple bonds in 9 molecules with 10 valence electrons (HCN, HCP, HCAs, HSiN, HSi

  12. An accurate equation of state for the exponential-6 fluid applied to dense supercritical nitrogen

    NASA Astrophysics Data System (ADS)

    Fried, Laurence E.; Howard, W. Michael

    1998-11-01

    The exponential-6 potential model is widely used in fluid equation of state studies. We have developed an accurate and efficient complete equation of state for the exponential-6 fluid based on HMSA integral equation theory and Monte Carlo calculations. Our equation of state has average fractional error of 0.2% in pV/NkBT and 0.3% in the excess energy Uex/NkBT. This is a substantial improvement in accuracy over perturbation methods, which are typically used in treatments of dense fluid equations of state. We have applied our equation of state to the problem of dense supercritical N2. We find that we are able to accurately reproduce a wide range of material properties with our model, over a range 0.01⩽P⩽100 GPa and 298⩽T⩽15 000 K.

  13. IRIS: Towards an Accurate and Fast Stage Weight Prediction Method

    NASA Astrophysics Data System (ADS)

    Taponier, V.; Balu, A.

    2002-01-01

    The knowledge of the structural mass fraction (or the mass ratio) of a given stage, which affects the performance of a rocket, is essential for the analysis of new or upgraded launchers or stages, whose need is increased by the quick evolution of the space programs and by the necessity of their adaptation to the market needs. The availability of this highly scattered variable, ranging between 0.05 and 0.15, is of primary importance at the early steps of the preliminary design studies. At the start of the staging and performance studies, the lack of frozen weight data (to be obtained later on from propulsion, trajectory and sizing studies) leads to rely on rough estimates, generally derived from printed sources and adapted. When needed, a consolidation can be acquired trough a specific analysis activity involving several techniques and implying additional effort and time. The present empirical approach allows thus to get approximated values (i.e. not necessarily accurate or consistent), inducing some result inaccuracy as well as, consequently, difficulties of performance ranking for a multiple option analysis, and an increase of the processing duration. This forms a classical harsh fact of the preliminary design system studies, insufficiently discussed to date. It appears therefore highly desirable to have, for all the evaluation activities, a reliable, fast and easy-to-use weight or mass fraction prediction method. Additionally, the latter should allow for a pre selection of the alternative preliminary configurations, making possible a global system approach. For that purpose, an attempt at modeling has been undertaken, whose objective was the determination of a parametric formulation of the mass fraction, to be expressed from a limited number of parameters available at the early steps of the project. It is based on the innovative use of a statistical method applicable to a variable as a function of several independent parameters. A specific polynomial generator

  14. An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions

    PubMed Central

    Deng, Xin; Gumm, Jordan; Karki, Suman; Eickholt, Jesse; Cheng, Jianlin

    2015-01-01

    Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale. PMID:26198229

  15. An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions.

    PubMed

    Deng, Xin; Gumm, Jordan; Karki, Suman; Eickholt, Jesse; Cheng, Jianlin

    2015-07-07

    Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale.

  16. Prediction of Preoperative Anxiety in Children: Who is Most Accurate?

    PubMed Central

    MacLaren, Jill E.; Thompson, Caitlin; Weinberg, Megan; Fortier, Michelle A.; Morrison, Debra E.; Perret, Danielle; Kain, Zeev N.

    2009-01-01

    Background In this investigation, we sought to assess the ability of pediatric attending anesthesiologists, resident anesthesiologists and mothers to predict anxiety during induction of anesthesia in 2 to 16-year-old children (n=125). Methods Anesthesiologists and mothers provided predictions using a visual analog scale and children's anxiety was assessed using a valid behavior observation tool the Modified Yale Preoperative Anxiety Scale (mYPAS). All mothers were present during anesthetic induction and no child received sedative premedication. Correlational analyses were conducted. Results A total of 125 children aged 2 to 16 years, their mothers, and their attending pediatric anesthesiologists and resident anesthesiologists were studied. Correlational analyses revealed significant associations between attending predictions and child anxiety at induction (rs= 0.38, p<0.001). Resident anesthesiologist and mother predictions were not significantly related to children's anxiety during induction (rs = 0.01 and 0.001, respectively). In terms of accuracy of prediction, 47.2% of predictions made by attending anesthesiologists were within one standard deviation of the observed anxiety exhibited by the child, and 70.4% of predictions were within 2 standard deviations. Conclusions We conclude that attending anesthesiologists who practice in pediatric settings are better than mothers in predicting the anxiety of children during induction of anesthesia. While this finding has significant clinical implications, it is unclear if it can be extended to attending anesthesiologists whose practice is not mostly pediatric anesthesia. PMID:19448201

  17. Development and Validation of a Multidisciplinary Tool for Accurate and Efficient Rotorcraft Noise Prediction (MUTE)

    NASA Technical Reports Server (NTRS)

    Liu, Yi; Anusonti-Inthra, Phuriwat; Diskin, Boris

    2011-01-01

    A physics-based, systematically coupled, multidisciplinary prediction tool (MUTE) for rotorcraft noise was developed and validated with a wide range of flight configurations and conditions. MUTE is an aggregation of multidisciplinary computational tools that accurately and efficiently model the physics of the source of rotorcraft noise, and predict the noise at far-field observer locations. It uses systematic coupling approaches among multiple disciplines including Computational Fluid Dynamics (CFD), Computational Structural Dynamics (CSD), and high fidelity acoustics. Within MUTE, advanced high-order CFD tools are used around the rotor blade to predict the transonic flow (shock wave) effects, which generate the high-speed impulsive noise. Predictions of the blade-vortex interaction noise in low speed flight are also improved by using the Particle Vortex Transport Method (PVTM), which preserves the wake flow details required for blade/wake and fuselage/wake interactions. The accuracy of the source noise prediction is further improved by utilizing a coupling approach between CFD and CSD, so that the effects of key structural dynamics, elastic blade deformations, and trim solutions are correctly represented in the analysis. The blade loading information and/or the flow field parameters around the rotor blade predicted by the CFD/CSD coupling approach are used to predict the acoustic signatures at far-field observer locations with a high-fidelity noise propagation code (WOPWOP3). The predicted results from the MUTE tool for rotor blade aerodynamic loading and far-field acoustic signatures are compared and validated with a variation of experimental data sets, such as UH60-A data, DNW test data and HART II test data.

  18. Development of an accurate fluid management system for a pediatric continuous renal replacement therapy device

    PubMed Central

    SANTHANAKRISHNAN, ARVIND; NESTLE, TRENT T.; MOORE, BRIAN L.; YOGANATHAN, AJIT P.; PADEN, MATTHEW L.

    2013-01-01

    Acute kidney injury is common in critically ill children and renal replacement therapies provide a life saving therapy to a subset of these children. However, there is no Food and Drug Administration approved device to provide pediatric continuous renal replacement therapy (CRRT). Consequently, clinicians adapt approved adult CRRT devices for use in children due to lack of safer alternatives. Complications occur using adult CRRT devices in children due to inaccurate fluid balance (FB) between the volumes of ultrafiltrate (UF) removed and replacement fluid (RF) delivered. We demonstrate the design and validation of a pediatric fluid management system for obtaining accurate instantaneous and cumulative FB. Fluid transport was achieved via multiple novel pulsatile diaphragm pumps. The conservation of volume principle leveraging the physical property of fluid incompressibility along with mechanical coupling via a crankshaft was used for FB. Accuracy testing was conducted in vitro for 8-hour long continuous operation of the coupled UF and RF pumps. The mean cumulative FB error was <1% across filtration flows from 300 mL/hour to 3000 mL/hour. This approach of FB control in a pediatric specific CRRT device would represent a significant accuracy improvement over currently used clinical implementations. PMID:23644618

  19. Is Three-Dimensional Soft Tissue Prediction by Software Accurate?

    PubMed

    Nam, Ki-Uk; Hong, Jongrak

    2015-11-01

    The authors assessed whether virtual surgery, performed with a soft tissue prediction program, could correctly simulate the actual surgical outcome, focusing on soft tissue movement. Preoperative and postoperative computed tomography (CT) data for 29 patients, who had undergone orthognathic surgery, were obtained and analyzed using the Simplant Pro software. The program made a predicted soft tissue image (A) based on presurgical CT data. After the operation, we obtained actual postoperative CT data and an actual soft tissue image (B) was generated. Finally, the 2 images (A and B) were superimposed and analyzed differences between the A and B. Results were grouped in 2 classes: absolute values and vector values. In the absolute values, the left mouth corner was the most significant error point (2.36 mm). The right mouth corner (2.28 mm), labrale inferius (2.08 mm), and the pogonion (2.03 mm) also had significant errors. In vector values, prediction of the right-left side had a left-sided tendency, the superior-inferior had a superior tendency, and the anterior-posterior showed an anterior tendency. As a result, with this program, the position of points tended to be located more left, anterior, and superior than the "real" situation. There is a need to improve the prediction accuracy for soft tissue images. Such software is particularly valuable in predicting craniofacial soft tissues landmarks, such as the pronasale. With this software, landmark positions were most inaccurate in terms of anterior-posterior predictions.

  20. Fast and accurate automatic structure prediction with HHpred.

    PubMed

    Hildebrand, Andrea; Remmert, Michael; Biegert, Andreas; Söding, Johannes

    2009-01-01

    Automated protein structure prediction is becoming a mainstream tool for biological research. This has been fueled by steady improvements of publicly available automated servers over the last decade, in particular their ability to build good homology models for an increasing number of targets by reliably detecting and aligning more and more remotely homologous templates. Here, we describe the three fully automated versions of the HHpred server that participated in the community-wide blind protein structure prediction competition CASP8. What makes HHpred unique is the combination of usability, short response times (typically under 15 min) and a model accuracy that is competitive with those of the best servers in CASP8.

  1. Accurate perception of negative emotions predicts functional capacity in schizophrenia.

    PubMed

    Abram, Samantha V; Karpouzian, Tatiana M; Reilly, James L; Derntl, Birgit; Habel, Ute; Smith, Matthew J

    2014-04-30

    Several studies suggest facial affect perception (FAP) deficits in schizophrenia are linked to poorer social functioning. However, whether reduced functioning is associated with inaccurate perception of specific emotional valence or a global FAP impairment remains unclear. The present study examined whether impairment in the perception of specific emotional valences (positive, negative) and neutrality were uniquely associated with social functioning, using a multimodal social functioning battery. A sample of 59 individuals with schizophrenia and 41 controls completed a computerized FAP task, and measures of functional capacity, social competence, and social attainment. Participants also underwent neuropsychological testing and symptom assessment. Regression analyses revealed that only accurately perceiving negative emotions explained significant variance (7.9%) in functional capacity after accounting for neurocognitive function and symptoms. Partial correlations indicated that accurately perceiving anger, in particular, was positively correlated with functional capacity. FAP for positive, negative, or neutral emotions were not related to social competence or social attainment. Our findings were consistent with prior literature suggesting negative emotions are related to functional capacity in schizophrenia. Furthermore, the observed relationship between perceiving anger and performance of everyday living skills is novel and warrants further exploration.

  2. Asymptotic expansion based equation of state for hard-disk fluids offering accurate virial coefficients.

    PubMed

    Tian, Jianxiang; Gui, Yuanxing; Mulero, A

    2010-01-01

    Despite the fact that more than 30 analytical expressions for the equation of state of hard-disk fluids have been proposed in the literature, none of them is capable of reproducing the currently accepted numeric or estimated values for the first eighteen virial coefficients. Using the asymptotic expansion method, extended to the first ten virial coefficients for hard-disk fluids, fifty-seven new expressions for the equation of state have been studied. Of these, a new equation of state is selected which reproduces accurately all the first eighteen virial coefficients. Comparisons for the compressibility factor with computer simulations show that this new equation is as accurate as other similar expressions with the same number of parameters. Finally, the location of the poles of the 57 new equations shows that there are some particular configurations which could give both the accurate virial coefficients and the correct closest packing fraction in the future when higher than the tenth virial coefficients are numerically calculated.

  3. Towards Accurate Ab Initio Predictions of the Spectrum of Methane

    NASA Technical Reports Server (NTRS)

    Schwenke, David W.; Kwak, Dochan (Technical Monitor)

    2001-01-01

    We have carried out extensive ab initio calculations of the electronic structure of methane, and these results are used to compute vibrational energy levels. We include basis set extrapolations, core-valence correlation, relativistic effects, and Born- Oppenheimer breakdown terms in our calculations. Our ab initio predictions of the lowest lying levels are superb.

  4. Accurate Theoretical Prediction of the Properties of Energetic Materials

    DTIC Science & Technology

    2007-11-02

    calculations (e.g. Cheetah ). 8. Sensitivity. The structure prediction and lattice potential work will serve as a platform to examine impact/shock...nitromethane molecules. (In an extension of the present work, we will freeze the internal coordinates of the molecules and assess the extent to which the

  5. Learning regulatory programs that accurately predict differential expression with MEDUSA.

    PubMed

    Kundaje, Anshul; Lianoglou, Steve; Li, Xuejing; Quigley, David; Arias, Marta; Wiggins, Chris H; Zhang, Li; Leslie, Christina

    2007-12-01

    Inferring gene regulatory networks from high-throughput genomic data is one of the central problems in computational biology. In this paper, we describe a predictive modeling approach for studying regulatory networks, based on a machine learning algorithm called MEDUSA. MEDUSA integrates promoter sequence, mRNA expression, and transcription factor occupancy data to learn gene regulatory programs that predict the differential expression of target genes. Instead of using clustering or correlation of expression profiles to infer regulatory relationships, MEDUSA determines condition-specific regulators and discovers regulatory motifs that mediate the regulation of target genes. In this way, MEDUSA meaningfully models biological mechanisms of transcriptional regulation. MEDUSA solves the problem of predicting the differential (up/down) expression of target genes by using boosting, a technique from statistical learning, which helps to avoid overfitting as the algorithm searches through the high-dimensional space of potential regulators and sequence motifs. Experimental results demonstrate that MEDUSA achieves high prediction accuracy on held-out experiments (test data), that is, data not seen in training. We also present context-specific analysis of MEDUSA regulatory programs for DNA damage and hypoxia, demonstrating that MEDUSA identifies key regulators and motifs in these processes. A central challenge in the field is the difficulty of validating reverse-engineered networks in the absence of a gold standard. Our approach of learning regulatory programs provides at least a partial solution for the problem: MEDUSA's prediction accuracy on held-out data gives a concrete and statistically sound way to validate how well the algorithm performs. With MEDUSA, statistical validation becomes a prerequisite for hypothesis generation and network building rather than a secondary consideration.

  6. Standardized EEG interpretation accurately predicts prognosis after cardiac arrest

    PubMed Central

    Rossetti, Andrea O.; van Rootselaar, Anne-Fleur; Wesenberg Kjaer, Troels; Horn, Janneke; Ullén, Susann; Friberg, Hans; Nielsen, Niklas; Rosén, Ingmar; Åneman, Anders; Erlinge, David; Gasche, Yvan; Hassager, Christian; Hovdenes, Jan; Kjaergaard, Jesper; Kuiper, Michael; Pellis, Tommaso; Stammet, Pascal; Wanscher, Michael; Wetterslev, Jørn; Wise, Matt P.; Cronberg, Tobias

    2016-01-01

    Objective: To identify reliable predictors of outcome in comatose patients after cardiac arrest using a single routine EEG and standardized interpretation according to the terminology proposed by the American Clinical Neurophysiology Society. Methods: In this cohort study, 4 EEG specialists, blinded to outcome, evaluated prospectively recorded EEGs in the Target Temperature Management trial (TTM trial) that randomized patients to 33°C vs 36°C. Routine EEG was performed in patients still comatose after rewarming. EEGs were classified into highly malignant (suppression, suppression with periodic discharges, burst-suppression), malignant (periodic or rhythmic patterns, pathological or nonreactive background), and benign EEG (absence of malignant features). Poor outcome was defined as best Cerebral Performance Category score 3–5 until 180 days. Results: Eight TTM sites randomized 202 patients. EEGs were recorded in 103 patients at a median 77 hours after cardiac arrest; 37% had a highly malignant EEG and all had a poor outcome (specificity 100%, sensitivity 50%). Any malignant EEG feature had a low specificity to predict poor prognosis (48%) but if 2 malignant EEG features were present specificity increased to 96% (p < 0.001). Specificity and sensitivity were not significantly affected by targeted temperature or sedation. A benign EEG was found in 1% of the patients with a poor outcome. Conclusions: Highly malignant EEG after rewarming reliably predicted poor outcome in half of patients without false predictions. An isolated finding of a single malignant feature did not predict poor outcome whereas a benign EEG was highly predictive of a good outcome. PMID:26865516

  7. How Accurately Can We Predict Eclipses for Algol? (Poster abstract)

    NASA Astrophysics Data System (ADS)

    Turner, D.

    2016-06-01

    (Abstract only) beta Persei, or Algol, is a very well known eclipsing binary system consisting of a late B-type dwarf that is regularly eclipsed by a GK subgiant every 2.867 days. Eclipses, which last about 8 hours, are regular enough that predictions for times of minima are published in various places, Sky & Telescope magazine and The Observer's Handbook, for example. But eclipse minimum lasts for less than a half hour, whereas subtle mistakes in the current ephemeris for the star can result in predictions that are off by a few hours or more. The Algol system is fairly complex, with the Algol A and Algol B eclipsing system also orbited by Algol C with an orbital period of nearly 2 years. Added to that are complex long-term O-C variations with a periodicity of almost two centuries that, although suggested by Hoffmeister to be spurious, fit the type of light travel time variations expected for a fourth star also belonging to the system. The AB sub-system also undergoes mass transfer events that add complexities to its O-C behavior. Is it actually possible to predict precise times of eclipse minima for Algol months in advance given such complications, or is it better to encourage ongoing observations of the star so that O-C variations can be tracked in real time?

  8. Predictive rendering for accurate material perception: modeling and rendering fabrics

    NASA Astrophysics Data System (ADS)

    Bala, Kavita

    2012-03-01

    In computer graphics, rendering algorithms are used to simulate the appearance of objects and materials in a wide range of applications. Designers and manufacturers rely entirely on these rendered images to previsualize scenes and products before manufacturing them. They need to differentiate between different types of fabrics, paint finishes, plastics, and metals, often with subtle differences, for example, between silk and nylon, formaica and wood. Thus, these applications need predictive algorithms that can produce high-fidelity images that enable such subtle material discrimination.

  9. A high order accurate finite element algorithm for high Reynolds number flow prediction

    NASA Technical Reports Server (NTRS)

    Baker, A. J.

    1978-01-01

    A Galerkin-weighted residuals formulation is employed to establish an implicit finite element solution algorithm for generally nonlinear initial-boundary value problems. Solution accuracy, and convergence rate with discretization refinement, are quantized in several error norms, by a systematic study of numerical solutions to several nonlinear parabolic and a hyperbolic partial differential equation characteristic of the equations governing fluid flows. Solutions are generated using selective linear, quadratic and cubic basis functions. Richardson extrapolation is employed to generate a higher-order accurate solution to facilitate isolation of truncation error in all norms. Extension of the mathematical theory underlying accuracy and convergence concepts for linear elliptic equations is predicted for equations characteristic of laminar and turbulent fluid flows at nonmodest Reynolds number. The nondiagonal initial-value matrix structure introduced by the finite element theory is determined intrinsic to improved solution accuracy and convergence. A factored Jacobian iteration algorithm is derived and evaluated to yield a consequential reduction in both computer storage and execution CPU requirements while retaining solution accuracy.

  10. Objective criteria accurately predict amputation following lower extremity trauma.

    PubMed

    Johansen, K; Daines, M; Howey, T; Helfet, D; Hansen, S T

    1990-05-01

    MESS (Mangled Extremity Severity Score) is a simple rating scale for lower extremity trauma, based on skeletal/soft-tissue damage, limb ischemia, shock, and age. Retrospective analysis of severe lower extremity injuries in 25 trauma victims demonstrated a significant difference between MESS values for 17 limbs ultimately salvaged (mean, 4.88 +/- 0.27) and nine requiring amputation (mean, 9.11 +/- 0.51) (p less than 0.01). A prospective trial of MESS in lower extremity injuries managed at two trauma centers again demonstrated a significant difference between MESS values of 14 salvaged (mean, 4.00 +/- 0.28) and 12 doomed (mean, 8.83 +/- 0.53) limbs (p less than 0.01). In both the retrospective survey and the prospective trial, a MESS value greater than or equal to 7 predicted amputation with 100% accuracy. MESS may be useful in selecting trauma victims whose irretrievably injured lower extremities warrant primary amputation.

  11. Improved Ecosystem Predictions of the California Current System via Accurate Light Calculations

    DTIC Science & Technology

    2011-09-30

    System via Accurate Light Calculations Curtis D. Mobley Sequoia Scientific, Inc. 2700 Richards Road, Suite 107 Bellevue, WA 98005 phone: 425...incorporate extremely fast but accurate light calculations into coupled physical-biological-optical ocean ecosystem models as used for operational three...dimensional ecosystem predictions. Improvements in light calculations lead to improvements in predictions of chlorophyll concentrations and other

  12. Generating highly accurate prediction hypotheses through collaborative ensemble learning

    PubMed Central

    Arsov, Nino; Pavlovski, Martin; Basnarkov, Lasko; Kocarev, Ljupco

    2017-01-01

    Ensemble generation is a natural and convenient way of achieving better generalization performance of learning algorithms by gathering their predictive capabilities. Here, we nurture the idea of ensemble-based learning by combining bagging and boosting for the purpose of binary classification. Since the former improves stability through variance reduction, while the latter ameliorates overfitting, the outcome of a multi-model that combines both strives toward a comprehensive net-balancing of the bias-variance trade-off. To further improve this, we alter the bagged-boosting scheme by introducing collaboration between the multi-model’s constituent learners at various levels. This novel stability-guided classification scheme is delivered in two flavours: during or after the boosting process. Applied among a crowd of Gentle Boost ensembles, the ability of the two suggested algorithms to generalize is inspected by comparing them against Subbagging and Gentle Boost on various real-world datasets. In both cases, our models obtained a 40% generalization error decrease. But their true ability to capture details in data was revealed through their application for protein detection in texture analysis of gel electrophoresis images. They achieve improved performance of approximately 0.9773 AUROC when compared to the AUROC of 0.9574 obtained by an SVM based on recursive feature elimination. PMID:28304378

  13. Accurate predictions for the production of vaporized water

    SciTech Connect

    Morin, E.; Montel, F.

    1995-12-31

    The production of water vaporized in the gas phase is controlled by the local conditions around the wellbore. The pressure gradient applied to the formation creates a sharp increase of the molar water content in the hydrocarbon phase approaching the well; this leads to a drop in the pore water saturation around the wellbore. The extent of the dehydrated zone which is formed is the key controlling the bottom-hole content of vaporized water. The maximum water content in the hydrocarbon phase at a given pressure, temperature and salinity is corrected by capillarity or adsorption phenomena depending on the actual water saturation. Describing the mass transfer of the water between the hydrocarbon phases and the aqueous phase into the tubing gives a clear idea of vaporization effects on the formation of scales. Field example are presented for gas fields with temperatures ranging between 140{degrees}C and 180{degrees}C, where water vaporization effects are significant. Conditions for salt plugging in the tubing are predicted.

  14. Generating highly accurate prediction hypotheses through collaborative ensemble learning

    NASA Astrophysics Data System (ADS)

    Arsov, Nino; Pavlovski, Martin; Basnarkov, Lasko; Kocarev, Ljupco

    2017-03-01

    Ensemble generation is a natural and convenient way of achieving better generalization performance of learning algorithms by gathering their predictive capabilities. Here, we nurture the idea of ensemble-based learning by combining bagging and boosting for the purpose of binary classification. Since the former improves stability through variance reduction, while the latter ameliorates overfitting, the outcome of a multi-model that combines both strives toward a comprehensive net-balancing of the bias-variance trade-off. To further improve this, we alter the bagged-boosting scheme by introducing collaboration between the multi-model’s constituent learners at various levels. This novel stability-guided classification scheme is delivered in two flavours: during or after the boosting process. Applied among a crowd of Gentle Boost ensembles, the ability of the two suggested algorithms to generalize is inspected by comparing them against Subbagging and Gentle Boost on various real-world datasets. In both cases, our models obtained a 40% generalization error decrease. But their true ability to capture details in data was revealed through their application for protein detection in texture analysis of gel electrophoresis images. They achieve improved performance of approximately 0.9773 AUROC when compared to the AUROC of 0.9574 obtained by an SVM based on recursive feature elimination.

  15. Change in BMI Accurately Predicted by Social Exposure to Acquaintances

    PubMed Central

    Oloritun, Rahman O.; Ouarda, Taha B. M. J.; Moturu, Sai; Madan, Anmol; Pentland, Alex (Sandy); Khayal, Inas

    2013-01-01

    Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO) method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC) and R2. This study found a model that explains 68% (p<0.0001) of the variation in change in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as close friends. PMID

  16. Fast and accurate pressure-drop prediction in straightened atherosclerotic coronary arteries.

    PubMed

    Schrauwen, Jelle T C; Koeze, Dion J; Wentzel, Jolanda J; van de Vosse, Frans N; van der Steen, Anton F W; Gijsen, Frank J H

    2015-01-01

    Atherosclerotic disease progression in coronary arteries is influenced by wall shear stress. To compute patient-specific wall shear stress, computational fluid dynamics (CFD) is required. In this study we propose a method for computing the pressure-drop in regions proximal and distal to a plaque, which can serve as a boundary condition in CFD. As a first step towards exploring the proposed method we investigated ten straightened coronary arteries. First, the flow fields were calculated with CFD and velocity profiles were fitted on the results. Second, the Navier-Stokes equation was simplified and solved with the found velocity profiles to obtain a pressure-drop estimate (Δp (1)). Next, Δp (1) was compared to the pressure-drop from CFD (Δp CFD) as a validation step. Finally, the velocity profiles, and thus the pressure-drop were predicted based on geometry and flow, resulting in Δp geom. We found that Δp (1) adequately estimated Δp CFD with velocity profiles that have one free parameter β. This β was successfully related to geometry and flow, resulting in an excellent agreement between Δp CFD and Δp geom: 3.9 ± 4.9% difference at Re = 150. We showed that this method can quickly and accurately predict pressure-drop on the basis of geometry and flow in straightened coronary arteries that are mildly diseased.

  17. Modeling Tools Predict Flow in Fluid Dynamics

    NASA Technical Reports Server (NTRS)

    2010-01-01

    "Because rocket engines operate under extreme temperature and pressure, they present a unique challenge to designers who must test and simulate the technology. To this end, CRAFT Tech Inc., of Pipersville, Pennsylvania, won Small Business Innovation Research (SBIR) contracts from Marshall Space Flight Center to develop software to simulate cryogenic fluid flows and related phenomena. CRAFT Tech enhanced its CRUNCH CFD (computational fluid dynamics) software to simulate phenomena in various liquid propulsion components and systems. Today, both government and industry clients in the aerospace, utilities, and petrochemical industries use the software for analyzing existing systems as well as designing new ones."

  18. Novel methodology for accurate resolution of fluid signatures from multi-dimensional NMR well-logging measurements.

    PubMed

    Anand, Vivek

    2017-03-01

    A novel methodology for accurate fluid characterization from multi-dimensional nuclear magnetic resonance (NMR) well-logging measurements is introduced. This methodology overcomes a fundamental challenge of poor resolution of features in multi-dimensional NMR distributions due to low signal-to-noise ratio (SNR) of well-logging measurements. Based on an unsupervised machine-learning concept of blind source separation, the methodology resolves fluid responses from simultaneous analysis of large quantities of well-logging data. The multi-dimensional NMR distributions from a well log are arranged in a database matrix that is expressed as the product of two non-negative matrices. The first matrix contains the unique fluid signatures, and the second matrix contains the relative contributions of the signatures for each measurement sample. No a priori information or subjective assumptions about the underlying features in the data are required. Furthermore, the dimensionality of the data is reduced by several orders of magnitude, which greatly simplifies the visualization and interpretation of the fluid signatures. Compared to traditional methods of NMR fluid characterization which only use the information content of a single measurement, the new methodology uses the orders-of-magnitude higher information content of the entire well log. Simulations show that the methodology can resolve accurate fluid responses in challenging SNR conditions. The application of the methodology to well-logging data from a heavy oil reservoir shows that individual fluid signatures of heavy oil, water associated with clays and water in interstitial pores can be accurately obtained.

  19. Novel methodology for accurate resolution of fluid signatures from multi-dimensional NMR well-logging measurements

    NASA Astrophysics Data System (ADS)

    Anand, Vivek

    2017-03-01

    A novel methodology for accurate fluid characterization from multi-dimensional nuclear magnetic resonance (NMR) well-logging measurements is introduced. This methodology overcomes a fundamental challenge of poor resolution of features in multi-dimensional NMR distributions due to low signal-to-noise ratio (SNR) of well-logging measurements. Based on an unsupervised machine-learning concept of blind source separation, the methodology resolves fluid responses from simultaneous analysis of large quantities of well-logging data. The multi-dimensional NMR distributions from a well log are arranged in a database matrix that is expressed as the product of two non-negative matrices. The first matrix contains the unique fluid signatures, and the second matrix contains the relative contributions of the signatures for each measurement sample. No a priori information or subjective assumptions about the underlying features in the data are required. Furthermore, the dimensionality of the data is reduced by several orders of magnitude, which greatly simplifies the visualization and interpretation of the fluid signatures. Compared to traditional methods of NMR fluid characterization which only use the information content of a single measurement, the new methodology uses the orders-of-magnitude higher information content of the entire well log. Simulations show that the methodology can resolve accurate fluid responses in challenging SNR conditions. The application of the methodology to well-logging data from a heavy oil reservoir shows that individual fluid signatures of heavy oil, water associated with clays and water in interstitial pores can be accurately obtained.

  20. A Low-Cost, Accurate, and High-Precision Fluid Dispensing System for Microscale Application.

    PubMed

    Das, Champak; Wang, Guochun; Nguyen, Chien

    2017-04-01

    We present here the development of a low-cost, accurate, and precise fluid dispensing system. It can be used with peristaltic or any other pump to improve the flow characteristics. The dispensing system has a range of 1 to 100 µL with accuracy of ~99.5% and standard deviation at ~150 nL over the entire range. The system developed does not depend on the accuracy or precision of the driving pump; therefore, any positive displacement pump can be used to get similar accuracy and precision, which gives an opportunity to reduce the cost of the system. The dispensing system does not require periodic calibration and can also be miniaturized for microfluidic application. Although primarily designed for aqueous liquid, it can be extended for different nonconductive liquids as well with modifications. The unit is further used for near real-time measurement of lactate from microdialysate. The individual components can easily be made disposable or sterilized for use in biomedical applications.

  1. Prediction of fluid forces acting on a hand model in unsteady flow conditions.

    PubMed

    Kudo, Shigetada; Yanai, Toshimasa; Wilson, Barry; Takagi, Hideki; Vennell, Ross

    2008-01-01

    The aim of this study was to develop a method to predict fluid forces acting on the human hand in unsteady flow swimming conditions. A mechanical system consisting of a pulley and chain mechanism and load cell was constructed to rotate a hand model in fluid flows. To measure the angular displacement of the hand model a potentiometer was attached to the axis of the rotation. The hand model was then fixed at various angles about the longitudinal axis of the hand model and rotated at different flow velocities in a swimming flume for 258 different trials to approximate a swimmer's stroke in unsteady flow conditions. Pressures were taken from 12 transducers embedded in the hand model at a sampling frequency of 200Hz. The resultant fluid force acting on the hand model was then determined on the basis of the kinetic and kinematic data taken from the mechanical system at the frequency of 200Hz. A stepwise regression analysis was applied to acquire higher order polynomial equations that predict the fluid force acting on the accelerating hand model from the 12 pressure values. The root mean square (RMS) difference between the resultant fluid force measured and that predicted from the single best-fit polynomial equation across all trials was 5N. The method developed in the present study accurately predicted the fluid forces acting on the hand model.

  2. Accurate Prediction of One-Dimensional Protein Structure Features Using SPINE-X.

    PubMed

    Faraggi, Eshel; Kloczkowski, Andrzej

    2017-01-01

    Accurate prediction of protein secondary structure and other one-dimensional structure features is essential for accurate sequence alignment, three-dimensional structure modeling, and function prediction. SPINE-X is a software package to predict secondary structure as well as accessible surface area and dihedral angles ϕ and ψ. For secondary structure SPINE-X achieves an accuracy of between 81 and 84 % depending on the dataset and choice of tests. The Pearson correlation coefficient for accessible surface area prediction is 0.75 and the mean absolute error from the ϕ and ψ dihedral angles are 20(∘) and 33(∘), respectively. The source code and a Linux executables for SPINE-X are available from Research and Information Systems at http://mamiris.com .

  3. A novel equation of state for the prediction of thermodynamic properties of fluids.

    PubMed

    Polishuk, Ilya; Vera, Juan H

    2005-03-31

    This work proposes a new equation of state (EOS) based on molecular theory for the prediction of thermodynamic properties of real fluids. The new EOS uses a novel repulsive term, which gives the correct hard sphere close packed limit and yields accurate values for hard sphere and hard chain virial coefficients. The pressure obtained from this repulsive term is corrected by a combination of van der Waals and Dieterici potentials. No empirical temperature functionality of the parameters has been introduced at this stage. The novel EOS predicts the experimental volumetric data of different compounds and their mixtures better than the successful EOS of Peng and Robinson. The prediction of vapor pressures is only slightly less accurate than the results obtained with the Peng-Robinson equation that is designed for these purposes. The theoretically based parameters of the new EOS make its predictions more reliable than those obtained from purely empirical forms.

  4. Accurate prediction of adsorption energies on graphene, using a dispersion-corrected semiempirical method including solvation.

    PubMed

    Vincent, Mark A; Hillier, Ian H

    2014-08-25

    The accurate prediction of the adsorption energies of unsaturated molecules on graphene in the presence of water is essential for the design of molecules that can modify its properties and that can aid its processability. We here show that a semiempirical MO method corrected for dispersive interactions (PM6-DH2) can predict the adsorption energies of unsaturated hydrocarbons and the effect of substitution on these values to an accuracy comparable to DFT values and in good agreement with the experiment. The adsorption energies of TCNE, TCNQ, and a number of sulfonated pyrenes are also predicted, along with the effect of hydration using the COSMO model.

  5. Time-Accurate Computational Fluid Dynamics Simulation of a Pair of Moving Solid Rocket Boosters

    NASA Technical Reports Server (NTRS)

    Strutzenberg, Louise L.; Williams, Brandon R.

    2011-01-01

    Since the Columbia accident, the threat to the Shuttle launch vehicle from debris during the liftoff timeframe has been assessed by the Liftoff Debris Team at NASA/MSFC. In addition to engineering methods of analysis, CFD-generated flow fields during the liftoff timeframe have been used in conjunction with 3-DOF debris transport methods to predict the motion of liftoff debris. Early models made use of a quasi-steady flow field approximation with the vehicle positioned at a fixed location relative to the ground; however, a moving overset mesh capability has recently been developed for the Loci/CHEM CFD software which enables higher-fidelity simulation of the Shuttle transient plume startup and liftoff environment. The present work details the simulation of the launch pad and mobile launch platform (MLP) with truncated solid rocket boosters (SRBs) moving in a prescribed liftoff trajectory derived from Shuttle flight measurements. Using Loci/CHEM, time-accurate RANS and hybrid RANS/LES simulations were performed for the timeframe T0+0 to T0+3.5 seconds, which consists of SRB startup to a vehicle altitude of approximately 90 feet above the MLP. Analysis of the transient flowfield focuses on the evolution of the SRB plumes in the MLP plume holes and the flame trench, impingement on the flame deflector, and especially impingment on the MLP deck resulting in upward flow which is a transport mechanism for debris. The results show excellent qualitative agreement with the visual record from past Shuttle flights, and comparisons to pressure measurements in the flame trench and on the MLP provide confidence in these simulation capabilities.

  6. Accurately predicting copper interconnect topographies in foundry design for manufacturability flows

    NASA Astrophysics Data System (ADS)

    Lu, Daniel; Fan, Zhong; Tak, Ki Duk; Chang, Li-Fu; Zou, Elain; Jiang, Jenny; Yang, Josh; Zhuang, Linda; Chen, Kuang Han; Hurat, Philippe; Ding, Hua

    2011-04-01

    This paper presents a model-based Chemical Mechanical Polishing (CMP) Design for Manufacturability (DFM) () methodology that includes an accurate prediction of post-CMP copper interconnect topographies at the advanced process technology nodes. Using procedures of extensive model calibration and validation, the CMP process model accurately predicts post-CMP dimensions, such as erosion, dishing, and copper thickness with excellent correlation to silicon measurements. This methodology provides an efficient DFM flow to detect and fix physical manufacturing hotspots related to copper pooling and Depth of Focus (DOF) failures at both block- and full chip level designs. Moreover, the predicted thickness output is used in the CMP-aware RC extraction and Timing analysis flows for better understanding of performance yield and timing impact. In addition, the CMP model can be applied to the verification of model-based dummy fill flows.

  7. Cas9-chromatin binding information enables more accurate CRISPR off-target prediction

    PubMed Central

    Singh, Ritambhara; Kuscu, Cem; Quinlan, Aaron; Qi, Yanjun; Adli, Mazhar

    2015-01-01

    The CRISPR system has become a powerful biological tool with a wide range of applications. However, improving targeting specificity and accurately predicting potential off-targets remains a significant goal. Here, we introduce a web-based CRISPR/Cas9 Off-target Prediction and Identification Tool (CROP-IT) that performs improved off-target binding and cleavage site predictions. Unlike existing prediction programs that solely use DNA sequence information; CROP-IT integrates whole genome level biological information from existing Cas9 binding and cleavage data sets. Utilizing whole-genome chromatin state information from 125 human cell types further enhances its computational prediction power. Comparative analyses on experimentally validated datasets show that CROP-IT outperforms existing computational algorithms in predicting both Cas9 binding as well as cleavage sites. With a user-friendly web-interface, CROP-IT outputs scored and ranked list of potential off-targets that enables improved guide RNA design and more accurate prediction of Cas9 binding or cleavage sites. PMID:26032770

  8. Modeling methodology for the accurate and prompt prediction of symptomatic events in chronic diseases.

    PubMed

    Pagán, Josué; Risco-Martín, José L; Moya, José M; Ayala, José L

    2016-08-01

    Prediction of symptomatic crises in chronic diseases allows to take decisions before the symptoms occur, such as the intake of drugs to avoid the symptoms or the activation of medical alarms. The prediction horizon is in this case an important parameter in order to fulfill the pharmacokinetics of medications, or the time response of medical services. This paper presents a study about the prediction limits of a chronic disease with symptomatic crises: the migraine. For that purpose, this work develops a methodology to build predictive migraine models and to improve these predictions beyond the limits of the initial models. The maximum prediction horizon is analyzed, and its dependency on the selected features is studied. A strategy for model selection is proposed to tackle the trade off between conservative but robust predictive models, with respect to less accurate predictions with higher horizons. The obtained results show a prediction horizon close to 40min, which is in the time range of the drug pharmacokinetics. Experiments have been performed in a realistic scenario where input data have been acquired in an ambulatory clinical study by the deployment of a non-intrusive Wireless Body Sensor Network. Our results provide an effective methodology for the selection of the future horizon in the development of prediction algorithms for diseases experiencing symptomatic crises.

  9. Theoretical prediction of multiple fluid-fluid transitions in monocomponent fluids

    NASA Astrophysics Data System (ADS)

    Cervantes, L. A.; Benavides, A. L.; del Río, F.

    2007-02-01

    The authors use the analytical equation of state obtained by the discrete perturbation theory [A. L. Benavides and A. Gil-Villegas, Mol. Phys. 97, 1225 (1999)] to study the phase diagram of fluids with discrete spherical potentials formed by a repulsive square-shoulder plus an attractive square-well interaction (SS+SW). This interaction is characterized by the usual energy and size parameters plus three dimensionless parameters: two of them measuring the widths of the SS and the SW and the third the relative height of the SS. The matter of interest is that, for certain values of the interaction parameters, the SS +SW systems exhibit more than one first-order fluid-fluid transition. The evidence that several real substances (such as water, phosphorus, carbon, and silica, among others) exhibit an extra liquid-liquid transition has drawn interest into the study of interactions responsible for this behavior. The simple SS +SW fluid is one of the systems that, in spite of being spherically symmetric, shows multiple fluid-fluid transitions. In this work the authors investigate systematically the effect on the phase diagram of varying the interaction parameters. The use of an analytical free-energy equation gives a clear thermodynamic picture of the emergence of different types of critical points, throwing new light on the phase behavior of these fluids and thus clarifying previous results obtained by other techniques. The interplay of attractive and repulsive forces with several scale lengths produces very rich phase diagrams, including cases with three critical points. The region of the interaction-parameter space where multiple critical points appear is mapped for various families of interactions.

  10. An effective method for accurate prediction of the first hyperpolarizability of alkalides.

    PubMed

    Wang, Jia-Nan; Xu, Hong-Liang; Sun, Shi-Ling; Gao, Ting; Li, Hong-Zhi; Li, Hui; Su, Zhong-Min

    2012-01-15

    The proper theoretical calculation method for nonlinear optical (NLO) properties is a key factor to design the excellent NLO materials. Yet it is a difficult task to obatin the accurate NLO property of large scale molecule. In present work, an effective intelligent computing method, as called extreme learning machine-neural network (ELM-NN), is proposed to predict accurately the first hyperpolarizability (β(0)) of alkalides from low-accuracy first hyperpolarizability. Compared with neural network (NN) and genetic algorithm neural network (GANN), the root-mean-square deviations of the predicted values obtained by ELM-NN, GANN, and NN with their MP2 counterpart are 0.02, 0.08, and 0.17 a.u., respectively. It suggests that the predicted values obtained by ELM-NN are more accurate than those calculated by NN and GANN methods. Another excellent point of ELM-NN is the ability to obtain the high accuracy level calculated values with less computing cost. Experimental results show that the computing time of MP2 is 2.4-4 times of the computing time of ELM-NN. Thus, the proposed method is a potentially powerful tool in computational chemistry, and it may predict β(0) of the large scale molecules, which is difficult to obtain by high-accuracy theoretical method due to dramatic increasing computational cost.

  11. Hash: a Program to Accurately Predict Protein Hα Shifts from Neighboring Backbone Shifts3

    PubMed Central

    Zeng, Jianyang; Zhou, Pei; Donald, Bruce Randall

    2012-01-01

    Chemical shifts provide not only peak identities for analyzing NMR data, but also an important source of conformational information for studying protein structures. Current structural studies requiring Hα chemical shifts suffer from the following limitations. (1) For large proteins, the Hα chemical shifts can be difficult to assign using conventional NMR triple-resonance experiments, mainly due to the fast transverse relaxation rate of Cα that restricts the signal sensitivity. (2) Previous chemical shift prediction approaches either require homologous models with high sequence similarity or rely heavily on accurate backbone and side-chain structural coordinates. When neither sequence homologues nor structural coordinates are available, we must resort to other information to predict Hα chemical shifts. Predicting accurate Hα chemical shifts using other obtainable information, such as the chemical shifts of nearby backbone atoms (i.e., adjacent atoms in the sequence), can remedy the above dilemmas, and hence advance NMR-based structural studies of proteins. By specifically exploiting the dependencies on chemical shifts of nearby backbone atoms, we propose a novel machine learning algorithm, called Hash, to predict Hα chemical shifts. Hash combines a new fragment-based chemical shift search approach with a non-parametric regression model, called the generalized additive model, to effectively solve the prediction problem. We demonstrate that the chemical shifts of nearby backbone atoms provide a reliable source of information for predicting accurate Hα chemical shifts. Our testing results on different possible combinations of input data indicate that Hash has a wide rage of potential NMR applications in structural and biological studies of proteins. PMID:23242797

  12. Accurate Prediction of Ligand Affinities for a Proton-Dependent Oligopeptide Transporter

    PubMed Central

    Samsudin, Firdaus; Parker, Joanne L.; Sansom, Mark S.P.; Newstead, Simon; Fowler, Philip W.

    2016-01-01

    Summary Membrane transporters are critical modulators of drug pharmacokinetics, efficacy, and safety. One example is the proton-dependent oligopeptide transporter PepT1, also known as SLC15A1, which is responsible for the uptake of the β-lactam antibiotics and various peptide-based prodrugs. In this study, we modeled the binding of various peptides to a bacterial homolog, PepTSt, and evaluated a range of computational methods for predicting the free energy of binding. Our results show that a hybrid approach (endpoint methods to classify peptides into good and poor binders and a theoretically exact method for refinement) is able to accurately predict affinities, which we validated using proteoliposome transport assays. Applying the method to a homology model of PepT1 suggests that the approach requires a high-quality structure to be accurate. Our study provides a blueprint for extending these computational methodologies to other pharmaceutically important transporter families. PMID:27028887

  13. Can phenological models predict tree phenology accurately under climate change conditions?

    NASA Astrophysics Data System (ADS)

    Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

    2014-05-01

    The onset of the growing season of trees has been globally earlier by 2.3 days/decade during the last 50 years because of global warming and this trend is predicted to continue according to climate forecast. The effect of temperature on plant phenology is however not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud dormancy, and on the other hand higher temperatures are necessary to promote bud cells growth afterwards. Increasing phenological changes in temperate woody species have strong impacts on forest trees distribution and productivity, as well as crops cultivation areas. Accurate predictions of trees phenology are therefore a prerequisite to understand and foresee the impacts of climate change on forests and agrosystems. Different process-based models have been developed in the last two decades to predict the date of budburst or flowering of woody species. They are two main families: (1) one-phase models which consider only the ecodormancy phase and make the assumption that endodormancy is always broken before adequate climatic conditions for cell growth occur; and (2) two-phase models which consider both the endodormancy and ecodormancy phases and predict a date of dormancy break which varies from year to year. So far, one-phase models have been able to predict accurately tree bud break and flowering under historical climate. However, because they do not consider what happens prior to ecodormancy, and especially the possible negative effect of winter temperature warming on dormancy break, it seems unlikely that they can provide accurate predictions in future climate conditions. It is indeed well known that a lack of low temperature results in abnormal pattern of bud break and development in temperate fruit trees. An accurate modelling of the dormancy break date has thus become a major issue in phenology modelling. Two-phases phenological models predict that global warming should delay

  14. Bicluster Sampled Coherence Metric (BSCM) provides an accurate environmental context for phenotype predictions

    PubMed Central

    2015-01-01

    Background Biclustering is a popular method for identifying under which experimental conditions biological signatures are co-expressed. However, the general biclustering problem is NP-hard, offering room to focus algorithms on specific biological tasks. We hypothesize that conditional co-regulation of genes is a key factor in determining cell phenotype and that accurately segregating conditions in biclusters will improve such predictions. Thus, we developed a bicluster sampled coherence metric (BSCM) for determining which conditions and signals should be included in a bicluster. Results Our BSCM calculates condition and cluster size specific p-values, and we incorporated these into the popular integrated biclustering algorithm cMonkey. We demonstrate that incorporation of our new algorithm significantly improves bicluster co-regulation scores (p-value = 0.009) and GO annotation scores (p-value = 0.004). Additionally, we used a bicluster based signal to predict whether a given experimental condition will result in yeast peroxisome induction. Using the new algorithm, the classifier accuracy improves from 41.9% to 76.1% correct. Conclusions We demonstrate that the proposed BSCM helps determine which signals ought to be co-clustered, resulting in more accurately assigned bicluster membership. Furthermore, we show that BSCM can be extended to more accurately detect under which experimental conditions the genes are co-clustered. Features derived from this more accurate analysis of conditional regulation results in a dramatic improvement in the ability to predict a cellular phenotype in yeast. The latest cMonkey is available for download at https://github.com/baliga-lab/cmonkey2. The experimental data and source code featured in this paper is available http://AitchisonLab.com/BSCM. BSCM has been incorporated in the official cMonkey release. PMID:25881257

  15. Highly Accurate Structure-Based Prediction of HIV-1 Coreceptor Usage Suggests Intermolecular Interactions Driving Tropism.

    PubMed

    Kieslich, Chris A; Tamamis, Phanourios; Guzman, Yannis A; Onel, Melis; Floudas, Christodoulos A

    2016-01-01

    HIV-1 entry into host cells is mediated by interactions between the V3-loop of viral glycoprotein gp120 and chemokine receptor CCR5 or CXCR4, collectively known as HIV-1 coreceptors. Accurate genotypic prediction of coreceptor usage is of significant clinical interest and determination of the factors driving tropism has been the focus of extensive study. We have developed a method based on nonlinear support vector machines to elucidate the interacting residue pairs driving coreceptor usage and provide highly accurate coreceptor usage predictions. Our models utilize centroid-centroid interaction energies from computationally derived structures of the V3-loop:coreceptor complexes as primary features, while additional features based on established rules regarding V3-loop sequences are also investigated. We tested our method on 2455 V3-loop sequences of various lengths and subtypes, and produce a median area under the receiver operator curve of 0.977 based on 500 runs of 10-fold cross validation. Our study is the first to elucidate a small set of specific interacting residue pairs between the V3-loop and coreceptors capable of predicting coreceptor usage with high accuracy across major HIV-1 subtypes. The developed method has been implemented as a web tool named CRUSH, CoReceptor USage prediction for HIV-1, which is available at http://ares.tamu.edu/CRUSH/.

  16. Accurate similarity index based on activity and connectivity of node for link prediction

    NASA Astrophysics Data System (ADS)

    Li, Longjie; Qian, Lvjian; Wang, Xiaoping; Luo, Shishun; Chen, Xiaoyun

    2015-05-01

    Recent years have witnessed the increasing of available network data; however, much of those data is incomplete. Link prediction, which can find the missing links of a network, plays an important role in the research and analysis of complex networks. Based on the assumption that two unconnected nodes which are highly similar are very likely to have an interaction, most of the existing algorithms solve the link prediction problem by computing nodes' similarities. The fundamental requirement of those algorithms is accurate and effective similarity indices. In this paper, we propose a new similarity index, namely similarity based on activity and connectivity (SAC), which performs link prediction more accurately. To compute the similarity between two nodes, this index employs the average activity of these two nodes in their common neighborhood and the connectivities between them and their common neighbors. The higher the average activity is and the stronger the connectivities are, the more similar the two nodes are. The proposed index not only commendably distinguishes the contributions of paths but also incorporates the influence of endpoints. Therefore, it can achieve a better predicting result. To verify the performance of SAC, we conduct experiments on 10 real-world networks. Experimental results demonstrate that SAC outperforms the compared baselines.

  17. Melatonin levels in follicular fluid as markers for IVF outcomes and predicting ovarian reserve.

    PubMed

    Tong, Jing; Sheng, Shile; Sun, Yun; Li, Huihui; Li, Wei-Ping; Zhang, Cong; Chen, Zi-Jiang

    2017-04-01

    Good-quality oocytes are critical for the success of in vitro fertilization (IVF), but, to date, there is no marker of ovarian reserve available that can accurately predict oocyte quality. Melatonin exerts its antioxidant actions as a strong radical scavenger that might affect oocyte quality directly as it is the most potent antioxidant in follicular fluid. To investigate the precise role of endogenous melatonin in IVF outcomes, we recruited 61 women undergoing treatment cycles of IVF or intracytoplasmic sperm injection (ICSI) procedures and classified them into three groups according to their response to ovarian stimulation. Follicular fluid was collected to assess melatonin levels using a direct RIA method. We found good correlations between melatonin levels in follicular fluid with age, anti-Müllerian hormone (AMH) and baseline follicle-stimulating hormone (bFSH), all of which have been used to predict ovarian reserve. Furthermore, as melatonin levels correlated to IVF outcomes, higher numbers of oocytes were collected from patients with higher melatonin levels and consequently the number of oocytes fertilized, zygotes cleaved, top quality embryos on D3, blastocysts obtained and embryos suitable for transplantation was higher. The blastocyst rate increased in concert with the melatonin levels across the gradient between the poor response group and the high response group. These results demonstrated that the melatonin levels in follicular fluid is associated with both the quantity and quality of oocytes and can predict IVF outcomes as well making them highly relevant biochemical markers of ovarian reserve.

  18. Accurate prediction of the linear viscoelastic properties of highly entangled mono and bidisperse polymer melts.

    PubMed

    Stephanou, Pavlos S; Mavrantzas, Vlasis G

    2014-06-07

    We present a hierarchical computational methodology which permits the accurate prediction of the linear viscoelastic properties of entangled polymer melts directly from the chemical structure, chemical composition, and molecular architecture of the constituent chains. The method entails three steps: execution of long molecular dynamics simulations with moderately entangled polymer melts, self-consistent mapping of the accumulated trajectories onto a tube model and parameterization or fine-tuning of the model on the basis of detailed simulation data, and use of the modified tube model to predict the linear viscoelastic properties of significantly higher molecular weight (MW) melts of the same polymer. Predictions are reported for the zero-shear-rate viscosity η0 and the spectra of storage G'(ω) and loss G″(ω) moduli for several mono and bidisperse cis- and trans-1,4 polybutadiene melts as well as for their MW dependence, and are found to be in remarkable agreement with experimentally measured rheological data.

  19. Accurate prediction of unsteady and time-averaged pressure loads using a hybrid Reynolds-Averaged/large-eddy simulation technique

    NASA Astrophysics Data System (ADS)

    Bozinoski, Radoslav

    Significant research has been performed over the last several years on understanding the unsteady aerodynamics of various fluid flows. Much of this work has focused on quantifying the unsteady, three-dimensional flow field effects which have proven vital to the accurate prediction of many fluid and aerodynamic problems. Up until recently, engineers have predominantly relied on steady-state simulations to analyze the inherently three-dimensional ow structures that are prevalent in many of today's "real-world" problems. Increases in computational capacity and the development of efficient numerical methods can change this and allow for the solution of the unsteady Reynolds-Averaged Navier-Stokes (RANS) equations for practical three-dimensional aerodynamic applications. An integral part of this capability has been the performance and accuracy of the turbulence models coupled with advanced parallel computing techniques. This report begins with a brief literature survey of the role fully three-dimensional, unsteady, Navier-Stokes solvers have on the current state of numerical analysis. Next, the process of creating a baseline three-dimensional Multi-Block FLOw procedure called MBFLO3 is presented. Solutions for an inviscid circular arc bump, laminar at plate, laminar cylinder, and turbulent at plate are then presented. Results show good agreement with available experimental, numerical, and theoretical data. Scalability data for the parallel version of MBFLO3 is presented and shows efficiencies of 90% and higher for processes of no less than 100,000 computational grid points. Next, the description and implementation techniques used for several turbulence models are presented. Following the successful implementation of the URANS and DES procedures, the validation data for separated, non-reattaching flows over a NACA 0012 airfoil, wall-mounted hump, and a wing-body junction geometry are presented. Results for the NACA 0012 showed significant improvement in flow predictions

  20. Prediction of Accurate Thermochemistry of Medium and Large Sized Radicals Using Connectivity-Based Hierarchy (CBH).

    PubMed

    Sengupta, Arkajyoti; Raghavachari, Krishnan

    2014-10-14

    Accurate modeling of the chemical reactions in many diverse areas such as combustion, photochemistry, or atmospheric chemistry strongly depends on the availability of thermochemical information of the radicals involved. However, accurate thermochemical investigations of radical systems using state of the art composite methods have mostly been restricted to the study of hydrocarbon radicals of modest size. In an alternative approach, systematic error-canceling thermochemical hierarchy of reaction schemes can be applied to yield accurate results for such systems. In this work, we have extended our connectivity-based hierarchy (CBH) method to the investigation of radical systems. We have calibrated our method using a test set of 30 medium sized radicals to evaluate their heats of formation. The CBH-rad30 test set contains radicals containing diverse functional groups as well as cyclic systems. We demonstrate that the sophisticated error-canceling isoatomic scheme (CBH-2) with modest levels of theory is adequate to provide heats of formation accurate to ∼1.5 kcal/mol. Finally, we predict heats of formation of 19 other large and medium sized radicals for which the accuracy of available heats of formation are less well-known.

  1. Simple and accurate theory for strong shock waves in a dense hard-sphere fluid.

    PubMed

    Montanero, J M; López de Haro, M; Santos, A; Garzó, V

    1999-12-01

    Following an earlier work by Holian et al. [Phys. Rev. E 47, R24 (1993)] for a dilute gas, we present a theory for strong shock waves in a hard-sphere fluid described by the Enskog equation. The idea is to use the Navier-Stokes hydrodynamic equations but taking the temperature in the direction of shock propagation rather than the actual temperature in the computation of the transport coefficients. In general, for finite densities, this theory agrees much better with Monte Carlo simulations than the Navier-Stokes and (linear) Burnett theories, in contrast to the well-known superiority of the Burnett theory for dilute gases.

  2. Planar Near-Field Phase Retrieval Using GPUs for Accurate THz Far-Field Prediction

    NASA Astrophysics Data System (ADS)

    Junkin, Gary

    2013-04-01

    With a view to using Phase Retrieval to accurately predict Terahertz antenna far-field from near-field intensity measurements, this paper reports on three fundamental advances that achieve very low algorithmic error penalties. The first is a new Gaussian beam analysis that provides accurate initial complex aperture estimates including defocus and astigmatic phase errors, based only on first and second moment calculations. The second is a powerful noise tolerant near-field Phase Retrieval algorithm that combines Anderson's Plane-to-Plane (PTP) with Fienup's Hybrid-Input-Output (HIO) and Successive Over-Relaxation (SOR) to achieve increased accuracy at reduced scan separations. The third advance employs teraflop Graphical Processing Units (GPUs) to achieve practically real time near-field phase retrieval and to obtain the optimum aperture constraint without any a priori information.

  3. Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space.

    PubMed

    Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; Pronobis, Wiktor; von Lilienfeld, O Anatole; Müller, Klaus-Robert; Tkatchenko, Alexandre

    2015-06-18

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. In addition, the same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies.

  4. Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space

    DOE PAGES

    Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; ...

    2015-06-04

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstratemore » prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. The same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies.« less

  5. Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space

    SciTech Connect

    Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; Pronobis, Wiktor; von Lilienfeld, O. Anatole; Müller, Klaus -Robert; Tkatchenko, Alexandre

    2015-06-04

    Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. The same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies.

  6. A Novel Method for Accurate Operon Predictions in All SequencedProkaryotes

    SciTech Connect

    Price, Morgan N.; Huang, Katherine H.; Alm, Eric J.; Arkin, Adam P.

    2004-12-01

    We combine comparative genomic measures and the distance separating adjacent genes to predict operons in 124 completely sequenced prokaryotic genomes. Our method automatically tailors itself to each genome using sequence information alone, and thus can be applied to any prokaryote. For Escherichia coli K12 and Bacillus subtilis, our method is 85 and 83% accurate, respectively, which is similar to the accuracy of methods that use the same features but are trained on experimentally characterized transcripts. In Halobacterium NRC-1 and in Helicobacterpylori, our method correctly infers that genes in operons are separated by shorter distances than they are in E.coli, and its predictions using distance alone are more accurate than distance-only predictions trained on a database of E.coli transcripts. We use microarray data from sixphylogenetically diverse prokaryotes to show that combining intergenic distance with comparative genomic measures further improves accuracy and that our method is broadly effective. Finally, we survey operon structure across 124 genomes, and find several surprises: H.pylori has many operons, contrary to previous reports; Bacillus anthracis has an unusual number of pseudogenes within conserved operons; and Synechocystis PCC6803 has many operons even though it has unusually wide spacings between conserved adjacent genes.

  7. Accurate prediction of severe allergic reactions by a small set of environmental parameters (NDVI, temperature).

    PubMed

    Notas, George; Bariotakis, Michail; Kalogrias, Vaios; Andrianaki, Maria; Azariadis, Kalliopi; Kampouri, Errika; Theodoropoulou, Katerina; Lavrentaki, Katerina; Kastrinakis, Stelios; Kampa, Marilena; Agouridakis, Panagiotis; Pirintsos, Stergios; Castanas, Elias

    2015-01-01

    Severe allergic reactions of unknown etiology,necessitating a hospital visit, have an important impact in the life of affected individuals and impose a major economic burden to societies. The prediction of clinically severe allergic reactions would be of great importance, but current attempts have been limited by the lack of a well-founded applicable methodology and the wide spatiotemporal distribution of allergic reactions. The valid prediction of severe allergies (and especially those needing hospital treatment) in a region, could alert health authorities and implicated individuals to take appropriate preemptive measures. In the present report we have collecterd visits for serious allergic reactions of unknown etiology from two major hospitals in the island of Crete, for two distinct time periods (validation and test sets). We have used the Normalized Difference Vegetation Index (NDVI), a satellite-based, freely available measurement, which is an indicator of live green vegetation at a given geographic area, and a set of meteorological data to develop a model capable of describing and predicting severe allergic reaction frequency. Our analysis has retained NDVI and temperature as accurate identifiers and predictors of increased hospital severe allergic reactions visits. Our approach may contribute towards the development of satellite-based modules, for the prediction of severe allergic reactions in specific, well-defined geographical areas. It could also probably be used for the prediction of other environment related diseases and conditions.

  8. Microstructure-Dependent Gas Adsorption: Accurate Predictions of Methane Uptake in Nanoporous Carbons

    SciTech Connect

    Ihm, Yungok; Cooper, Valentino R; Gallego, Nidia C; Contescu, Cristian I; Morris, James R

    2014-01-01

    We demonstrate a successful, efficient framework for predicting gas adsorption properties in real materials based on first-principles calculations, with a specific comparison of experiment and theory for methane adsorption in activated carbons. These carbon materials have different pore size distributions, leading to a variety of uptake characteristics. Utilizing these distributions, we accurately predict experimental uptakes and heats of adsorption without empirical potentials or lengthy simulations. We demonstrate that materials with smaller pores have higher heats of adsorption, leading to a higher gas density in these pores. This pore-size dependence must be accounted for, in order to predict and understand the adsorption behavior. The theoretical approach combines: (1) ab initio calculations with a van der Waals density functional to determine adsorbent-adsorbate interactions, and (2) a thermodynamic method that predicts equilibrium adsorption densities by directly incorporating the calculated potential energy surface in a slit pore model. The predicted uptake at P=20 bar and T=298 K is in excellent agreement for all five activated carbon materials used. This approach uses only the pore-size distribution as an input, with no fitting parameters or empirical adsorbent-adsorbate interactions, and thus can be easily applied to other adsorbent-adsorbate combinations.

  9. Accurate Prediction of Severe Allergic Reactions by a Small Set of Environmental Parameters (NDVI, Temperature)

    PubMed Central

    Andrianaki, Maria; Azariadis, Kalliopi; Kampouri, Errika; Theodoropoulou, Katerina; Lavrentaki, Katerina; Kastrinakis, Stelios; Kampa, Marilena; Agouridakis, Panagiotis; Pirintsos, Stergios; Castanas, Elias

    2015-01-01

    Severe allergic reactions of unknown etiology,necessitating a hospital visit, have an important impact in the life of affected individuals and impose a major economic burden to societies. The prediction of clinically severe allergic reactions would be of great importance, but current attempts have been limited by the lack of a well-founded applicable methodology and the wide spatiotemporal distribution of allergic reactions. The valid prediction of severe allergies (and especially those needing hospital treatment) in a region, could alert health authorities and implicated individuals to take appropriate preemptive measures. In the present report we have collecterd visits for serious allergic reactions of unknown etiology from two major hospitals in the island of Crete, for two distinct time periods (validation and test sets). We have used the Normalized Difference Vegetation Index (NDVI), a satellite-based, freely available measurement, which is an indicator of live green vegetation at a given geographic area, and a set of meteorological data to develop a model capable of describing and predicting severe allergic reaction frequency. Our analysis has retained NDVI and temperature as accurate identifiers and predictors of increased hospital severe allergic reactions visits. Our approach may contribute towards the development of satellite-based modules, for the prediction of severe allergic reactions in specific, well-defined geographical areas. It could also probably be used for the prediction of other environment related diseases and conditions. PMID:25794106

  10. Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network

    NASA Astrophysics Data System (ADS)

    Ben Ali, Jaouher; Chebel-Morello, Brigitte; Saidi, Lotfi; Malinowski, Simon; Fnaiech, Farhat

    2015-05-01

    Accurate remaining useful life (RUL) prediction of critical assets is an important challenge in condition based maintenance to improve reliability and decrease machine's breakdown and maintenance's cost. Bearing is one of the most important components in industries which need to be monitored and the user should predict its RUL. The challenge of this study is to propose an original feature able to evaluate the health state of bearings and to estimate their RUL by Prognostics and Health Management (PHM) techniques. In this paper, the proposed method is based on the data-driven prognostic approach. The combination of Simplified Fuzzy Adaptive Resonance Theory Map (SFAM) neural network and Weibull distribution (WD) is explored. WD is used just in the training phase to fit measurement and to avoid areas of fluctuation in the time domain. SFAM training process is based on fitted measurements at present and previous inspection time points as input. However, the SFAM testing process is based on real measurements at present and previous inspections. Thanks to the fuzzy learning process, SFAM has an important ability and a good performance to learn nonlinear time series. As output, seven classes are defined; healthy bearing and six states for bearing degradation. In order to find the optimal RUL prediction, a smoothing phase is proposed in this paper. Experimental results show that the proposed method can reliably predict the RUL of rolling element bearings (REBs) based on vibration signals. The proposed prediction approach can be applied to prognostic other various mechanical assets.

  11. SIFTER search: a web server for accurate phylogeny-based protein function prediction

    PubMed Central

    Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

    2015-01-01

    We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access to precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. The SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded. PMID:25979264

  12. SIFTER search: a web server for accurate phylogeny-based protein function prediction

    SciTech Connect

    Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

    2015-05-15

    We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access to precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.

  13. SIFTER search: a web server for accurate phylogeny-based protein function prediction

    DOE PAGES

    Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

    2015-05-15

    We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access tomore » precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.« less

  14. Accurate verification of the conserved-vector-current and standard-model predictions

    SciTech Connect

    Sirlin, A.; Zucchini, R.

    1986-10-20

    An approximate analytic calculation of O(Z..cap alpha../sup 2/) corrections to Fermi decays is presented. When the analysis of Koslowsky et al. is modified to take into account the new results, it is found that each of the eight accurately studied scrFt values differs from the average by approx. <1sigma, thus significantly improving the comparison of experiments with conserved-vector-current predictions. The new scrFt values are lower than before, which also brings experiments into very good agreement with the three-generation standard model, at the level of its quantum corrections.

  15. Special purpose hybrid transfinite elements and unified computational methodology for accurately predicting thermoelastic stress waves

    NASA Technical Reports Server (NTRS)

    Tamma, Kumar K.; Railkar, Sudhir B.

    1988-01-01

    This paper represents an attempt to apply extensions of a hybrid transfinite element computational approach for accurately predicting thermoelastic stress waves. The applicability of the present formulations for capturing the thermal stress waves induced by boundary heating for the well known Danilovskaya problems is demonstrated. A unique feature of the proposed formulations for applicability to the Danilovskaya problem of thermal stress waves in elastic solids lies in the hybrid nature of the unified formulations and the development of special purpose transfinite elements in conjunction with the classical Galerkin techniques and transformation concepts. Numerical test cases validate the applicability and superior capability to capture the thermal stress waves induced due to boundary heating.

  16. The MIDAS touch for Accurately Predicting the Stress-Strain Behavior of Tantalum

    SciTech Connect

    Jorgensen, S.

    2016-03-02

    Testing the behavior of metals in extreme environments is not always feasible, so material scientists use models to try and predict the behavior. To achieve accurate results it is necessary to use the appropriate model and material-specific parameters. This research evaluated the performance of six material models available in the MIDAS database [1] to determine at which temperatures and strain-rates they perform best, and to determine to which experimental data their parameters were optimized. Additionally, parameters were optimized for the Johnson-Cook model using experimental data from Lassila et al [2].

  17. Can Transthoracic Echocardiography Be Used to Predict Fluid Responsiveness in the Critically Ill Patient? A Systematic Review

    PubMed Central

    Mandeville, Justin C.; Colebourn, Claire L.

    2012-01-01

    Introduction. We systematically evaluated the use of transthoracic echocardiography in the assessment of dynamic markers of preload to predict fluid responsiveness in the critically ill adult patient. Methods. Studies in the critically ill using transthoracic echocardiography (TTE) to predict a response in stroke volume or cardiac output to a fluid load were selected. Selection was limited to English language and adult patients. Studies on patients with an open thorax or abdomen were excluded. Results. The predictive power of diagnostic accuracy of inferior vena cava diameter and transaortic Doppler signal changes with the respiratory cycle or passive leg raising in mechanically ventilated patients was strong throughout the articles reviewed. Limitations of the technique relate to patient tolerance of the procedure, adequacy of acoustic windows, and operator skill. Conclusions. Transthoracic echocardiographic techniques accurately predict fluid responsiveness in critically ill patients. Discriminative power is not affected by the technique selected. PMID:22400109

  18. Accurate prediction of human drug toxicity: a major challenge in drug development.

    PubMed

    Li, Albert P

    2004-11-01

    Over the past decades, a number of drugs have been withdrawn or have required special labeling due to adverse effects observed post-marketing. Species differences in drug toxicity in preclinical safety tests and the lack of sensitive biomarkers and nonrepresentative patient population in clinical trials are probable reasons for the failures in predicting human drug toxicity. It is proposed that toxicology should evolve from an empirical practice to an investigative discipline. Accurate prediction of human drug toxicity requires resources and time to be spent in clearly defining key toxic pathways and corresponding risk factors, which hopefully, will be compensated by the benefits of a lower percentage of clinical failure due to toxicity and a decreased frequency of market withdrawal due to unacceptable adverse drug effects.

  19. Accurate prediction of the response of freshwater fish to a mixture of estrogenic chemicals.

    PubMed

    Brian, Jayne V; Harris, Catherine A; Scholze, Martin; Backhaus, Thomas; Booy, Petra; Lamoree, Marja; Pojana, Giulio; Jonkers, Niels; Runnalls, Tamsin; Bonfà, Angela; Marcomini, Antonio; Sumpter, John P

    2005-06-01

    Existing environmental risk assessment procedures are limited in their ability to evaluate the combined effects of chemical mixtures. We investigated the implications of this by analyzing the combined effects of a multicomponent mixture of five estrogenic chemicals using vitellogenin induction in male fathead minnows as an end point. The mixture consisted of estradiol, ethynylestradiol, nonylphenol, octylphenol, and bisphenol A. We determined concentration-response curves for each of the chemicals individually. The chemicals were then combined at equipotent concentrations and the mixture tested using fixed-ratio design. The effects of the mixture were compared with those predicted by the model of concentration addition using biomathematical methods, which revealed that there was no deviation between the observed and predicted effects of the mixture. These findings demonstrate that estrogenic chemicals have the capacity to act together in an additive manner and that their combined effects can be accurately predicted by concentration addition. We also explored the potential for mixture effects at low concentrations by exposing the fish to each chemical at one-fifth of its median effective concentration (EC50). Individually, the chemicals did not induce a significant response, although their combined effects were consistent with the predictions of concentration addition. This demonstrates the potential for estrogenic chemicals to act additively at environmentally relevant concentrations. These findings highlight the potential for existing environmental risk assessment procedures to underestimate the hazard posed by mixtures of chemicals that act via a similar mode of action, thereby leading to erroneous conclusions of absence of risk.

  20. Accurate Prediction of the Response of Freshwater Fish to a Mixture of Estrogenic Chemicals

    PubMed Central

    Brian, Jayne V.; Harris, Catherine A.; Scholze, Martin; Backhaus, Thomas; Booy, Petra; Lamoree, Marja; Pojana, Giulio; Jonkers, Niels; Runnalls, Tamsin; Bonfà, Angela; Marcomini, Antonio; Sumpter, John P.

    2005-01-01

    Existing environmental risk assessment procedures are limited in their ability to evaluate the combined effects of chemical mixtures. We investigated the implications of this by analyzing the combined effects of a multicomponent mixture of five estrogenic chemicals using vitellogenin induction in male fathead minnows as an end point. The mixture consisted of estradiol, ethynylestradiol, nonylphenol, octylphenol, and bisphenol A. We determined concentration–response curves for each of the chemicals individually. The chemicals were then combined at equipotent concentrations and the mixture tested using fixed-ratio design. The effects of the mixture were compared with those predicted by the model of concentration addition using biomathematical methods, which revealed that there was no deviation between the observed and predicted effects of the mixture. These findings demonstrate that estrogenic chemicals have the capacity to act together in an additive manner and that their combined effects can be accurately predicted by concentration addition. We also explored the potential for mixture effects at low concentrations by exposing the fish to each chemical at one-fifth of its median effective concentration (EC50). Individually, the chemicals did not induce a significant response, although their combined effects were consistent with the predictions of concentration addition. This demonstrates the potential for estrogenic chemicals to act additively at environmentally relevant concentrations. These findings highlight the potential for existing environmental risk assessment procedures to underestimate the hazard posed by mixtures of chemicals that act via a similar mode of action, thereby leading to erroneous conclusions of absence of risk. PMID:15929895

  1. IDSite: An accurate approach to predict P450-mediated drug metabolism

    PubMed Central

    Li, Jianing; Schneebeli, Severin T.; Bylund, Joseph; Farid, Ramy; Friesner, Richard A.

    2011-01-01

    Accurate prediction of drug metabolism is crucial for drug design. Since a large majority of drugs metabolism involves P450 enzymes, we herein describe a computational approach, IDSite, to predict P450-mediated drug metabolism. To model induced-fit effects, IDSite samples the conformational space with flexible docking in Glide followed by two refinement stages using the Protein Local Optimization Program (PLOP). Sites of metabolism (SOMs) are predicted according to a physical-based score that evaluates the potential of atoms to react with the catalytic iron center. As a preliminary test, we present in this paper the prediction of hydroxylation and O-dealkylation sites mediated by CYP2D6 using two different models: a physical-based simulation model, and a modification of this model in which a small number of parameters are fit to a training set. Without fitting any parameters to experimental data, the Physical IDSite scoring recovers 83% of the experimental observations for 56 compounds with a very low false positive rate. With only 4 fitted parameters, the Fitted IDSite was trained with the subset of 36 compounds and successfully applied to the other 20 compounds, recovering 94% of the experimental observations with high sensitivity and specificity for both sets. PMID:22247702

  2. Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction.

    PubMed

    Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H

    2017-01-09

    The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

  3. Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction

    PubMed Central

    Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K.; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G.; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H.

    2017-01-01

    The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively. PMID:27899623

  4. ILT based defect simulation of inspection images accurately predicts mask defect printability on wafer

    NASA Astrophysics Data System (ADS)

    Deep, Prakash; Paninjath, Sankaranarayanan; Pereira, Mark; Buck, Peter

    2016-05-01

    At advanced technology nodes mask complexity has been increased because of large-scale use of resolution enhancement technologies (RET) which includes Optical Proximity Correction (OPC), Inverse Lithography Technology (ILT) and Source Mask Optimization (SMO). The number of defects detected during inspection of such mask increased drastically and differentiation of critical and non-critical defects are more challenging, complex and time consuming. Because of significant defectivity of EUVL masks and non-availability of actinic inspection, it is important and also challenging to predict the criticality of defects for printability on wafer. This is one of the significant barriers for the adoption of EUVL for semiconductor manufacturing. Techniques to decide criticality of defects from images captured using non actinic inspection images is desired till actinic inspection is not available. High resolution inspection of photomask images detects many defects which are used for process and mask qualification. Repairing all defects is not practical and probably not required, however it's imperative to know which defects are severe enough to impact wafer before repair. Additionally, wafer printability check is always desired after repairing a defect. AIMSTM review is the industry standard for this, however doing AIMSTM review for all defects is expensive and very time consuming. Fast, accurate and an economical mechanism is desired which can predict defect printability on wafer accurately and quickly from images captured using high resolution inspection machine. Predicting defect printability from such images is challenging due to the fact that the high resolution images do not correlate with actual mask contours. The challenge is increased due to use of different optical condition during inspection other than actual scanner condition, and defects found in such images do not have correlation with actual impact on wafer. Our automated defect simulation tool predicts

  5. Fast Prediction of HCCI Combustion with an Artificial Neural Network Linked to a Fluid Mechanics Code

    SciTech Connect

    Aceves, S M; Flowers, D L; Chen, J; Babaimopoulos, A

    2006-08-29

    We have developed an artificial neural network (ANN) based combustion model and have integrated it into a fluid mechanics code (KIVA3V) to produce a new analysis tool (titled KIVA3V-ANN) that can yield accurate HCCI predictions at very low computational cost. The neural network predicts ignition delay as a function of operating parameters (temperature, pressure, equivalence ratio and residual gas fraction). KIVA3V-ANN keeps track of the time history of the ignition delay during the engine cycle to evaluate the ignition integral and predict ignition for each computational cell. After a cell ignites, chemistry becomes active, and a two-step chemical kinetic mechanism predicts composition and heat generation in the ignited cells. KIVA3V-ANN has been validated by comparison with isooctane HCCI experiments in two different engines. The neural network provides reasonable predictions for HCCI combustion and emissions that, although typically not as good as obtained with the more physically representative multi-zone model, are obtained at a much reduced computational cost. KIVA3V-ANN can perform reasonably accurate HCCI calculations while requiring only 10% more computational effort than a motored KIVA3V run. It is therefore considered a valuable tool for evaluation of engine maps or other performance analysis tasks requiring multiple individual runs.

  6. 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

  7. Prediction of a structural transition in the hard disk fluid.

    PubMed

    Piasecki, Jarosław; Szymczak, Piotr; Kozak, John J

    2010-10-28

    Starting from the second equilibrium equation in the BBGKY hierarchy under the Kirkwood superposition closure, we implement a new method for studying the asymptotic decay of correlations in the hard disk fluid in the high density regime. From our analysis and complementary numerical studies, we find that exponentially damped oscillations can occur only up to a packing fraction η(∗)∼0.718, a value that is in substantial agreement with the packing fraction, η∼0.723, believed to characterize the transition from the ordered solid phase to a dense fluid phase, as inferred from Mak's Monte Carlo simulations [Phys. Rev. E 73, 065104 (2006)]. Next, we show that the same method of analysis predicts that the exponential damping of oscillations in the hard sphere fluid becomes impossible when λ=4nπσ(3)[1+H(1)]≥34.81, where H(1) is the contact value of the correlation function, n is the number density, and σ is the sphere diameter in exact agreement with the condition, λ≥34.8, which is first reported in a numerical study of the Kirkwood equation by Kirkwood et al. [J. Chem. Phys. 18, 1040 (1950)]. Finally, we show that our method confirms the absence of any structural transition in hard rods for the entire range of densities below close packing.

  8. A hierarchical approach to accurate predictions of macroscopic thermodynamic behavior from quantum mechanics and molecular simulations

    NASA Astrophysics Data System (ADS)

    Garrison, Stephen L.

    2005-07-01

    The combination of molecular simulations and potentials obtained from quantum chemistry is shown to be able to provide reasonably accurate thermodynamic property predictions. Gibbs ensemble Monte Carlo simulations are used to understand the effects of small perturbations to various regions of the model Lennard-Jones 12-6 potential. However, when the phase behavior and second virial coefficient are scaled by the critical properties calculated for each potential, the results obey a corresponding states relation suggesting a non-uniqueness problem for interaction potentials fit to experimental phase behavior. Several variations of a procedure collectively referred to as quantum mechanical Hybrid Methods for Interaction Energies (HM-IE) are developed and used to accurately estimate interaction energies from CCSD(T) calculations with a large basis set in a computationally efficient manner for the neon-neon, acetylene-acetylene, and nitrogen-benzene systems. Using these results and methods, an ab initio, pairwise-additive, site-site potential for acetylene is determined and then improved using results from molecular simulations using this initial potential. The initial simulation results also indicate that a limited range of energies important for accurate phase behavior predictions. Second virial coefficients calculated from the improved potential indicate that one set of experimental data in the literature is likely erroneous. This prescription is then applied to methanethiol. Difficulties in modeling the effects of the lone pair electrons suggest that charges on the lone pair sites negatively impact the ability of the intermolecular potential to describe certain orientations, but that the lone pair sites may be necessary to reasonably duplicate the interaction energies for several orientations. Two possible methods for incorporating the effects of three-body interactions into simulations within the pairwise-additivity formulation are also developed. A low density

  9. Intermolecular potentials and the accurate prediction of the thermodynamic properties of water

    NASA Astrophysics Data System (ADS)

    Shvab, I.; Sadus, Richard J.

    2013-11-01

    The ability of intermolecular potentials to correctly predict the thermodynamic properties of liquid water at a density of 0.998 g/cm3 for a wide range of temperatures (298-650 K) and pressures (0.1-700 MPa) is investigated. Molecular dynamics simulations are reported for the pressure, thermal pressure coefficient, thermal expansion coefficient, isothermal and adiabatic compressibilities, isobaric and isochoric heat capacities, and Joule-Thomson coefficient of liquid water using the non-polarizable SPC/E and TIP4P/2005 potentials. The results are compared with both experiment data and results obtained from the ab initio-based Matsuoka-Clementi-Yoshimine non-additive (MCYna) [J. Li, Z. Zhou, and R. J. Sadus, J. Chem. Phys. 127, 154509 (2007)] potential, which includes polarization contributions. The data clearly indicate that both the SPC/E and TIP4P/2005 potentials are only in qualitative agreement with experiment, whereas the polarizable MCYna potential predicts some properties within experimental uncertainty. This highlights the importance of polarizability for the accurate prediction of the thermodynamic properties of water, particularly at temperatures beyond 298 K.

  10. Intermolecular potentials and the accurate prediction of the thermodynamic properties of water.

    PubMed

    Shvab, I; Sadus, Richard J

    2013-11-21

    The ability of intermolecular potentials to correctly predict the thermodynamic properties of liquid water at a density of 0.998 g∕cm(3) for a wide range of temperatures (298-650 K) and pressures (0.1-700 MPa) is investigated. Molecular dynamics simulations are reported for the pressure, thermal pressure coefficient, thermal expansion coefficient, isothermal and adiabatic compressibilities, isobaric and isochoric heat capacities, and Joule-Thomson coefficient of liquid water using the non-polarizable SPC∕E and TIP4P∕2005 potentials. The results are compared with both experiment data and results obtained from the ab initio-based Matsuoka-Clementi-Yoshimine non-additive (MCYna) [J. Li, Z. Zhou, and R. J. Sadus, J. Chem. Phys. 127, 154509 (2007)] potential, which includes polarization contributions. The data clearly indicate that both the SPC∕E and TIP4P∕2005 potentials are only in qualitative agreement with experiment, whereas the polarizable MCYna potential predicts some properties within experimental uncertainty. This highlights the importance of polarizability for the accurate prediction of the thermodynamic properties of water, particularly at temperatures beyond 298 K.

  11. Intermolecular potentials and the accurate prediction of the thermodynamic properties of water

    SciTech Connect

    Shvab, I.; Sadus, Richard J.

    2013-11-21

    The ability of intermolecular potentials to correctly predict the thermodynamic properties of liquid water at a density of 0.998 g/cm{sup 3} for a wide range of temperatures (298–650 K) and pressures (0.1–700 MPa) is investigated. Molecular dynamics simulations are reported for the pressure, thermal pressure coefficient, thermal expansion coefficient, isothermal and adiabatic compressibilities, isobaric and isochoric heat capacities, and Joule-Thomson coefficient of liquid water using the non-polarizable SPC/E and TIP4P/2005 potentials. The results are compared with both experiment data and results obtained from the ab initio-based Matsuoka-Clementi-Yoshimine non-additive (MCYna) [J. Li, Z. Zhou, and R. J. Sadus, J. Chem. Phys. 127, 154509 (2007)] potential, which includes polarization contributions. The data clearly indicate that both the SPC/E and TIP4P/2005 potentials are only in qualitative agreement with experiment, whereas the polarizable MCYna potential predicts some properties within experimental uncertainty. This highlights the importance of polarizability for the accurate prediction of the thermodynamic properties of water, particularly at temperatures beyond 298 K.

  12. Distance scaling method for accurate prediction of slowly varying magnetic fields in satellite missions

    NASA Astrophysics Data System (ADS)

    Zacharias, Panagiotis P.; Chatzineofytou, Elpida G.; Spantideas, Sotirios T.; Capsalis, Christos N.

    2016-07-01

    In the present work, the determination of the magnetic behavior of localized magnetic sources from near-field measurements is examined. The distance power law of the magnetic field fall-off is used in various cases to accurately predict the magnetic signature of an equipment under test (EUT) consisting of multiple alternating current (AC) magnetic sources. Therefore, parameters concerning the location of the observation points (magnetometers) are studied towards this scope. The results clearly show that these parameters are independent of the EUT's size and layout. Additionally, the techniques developed in the present study enable the placing of the magnetometers close to the EUT, thus achieving high signal-to-noise ratio (SNR). Finally, the proposed method is verified by real measurements, using a mobile phone as an EUT.

  13. A fast and accurate method to predict 2D and 3D aerodynamic boundary layer flows

    NASA Astrophysics Data System (ADS)

    Bijleveld, H. A.; Veldman, A. E. P.

    2014-12-01

    A quasi-simultaneous interaction method is applied to predict 2D and 3D aerodynamic flows. This method is suitable for offshore wind turbine design software as it is a very accurate and computationally reasonably cheap method. This study shows the results for a NACA 0012 airfoil. The two applied solvers converge to the experimental values when the grid is refined. We also show that in separation the eigenvalues remain positive thus avoiding the Goldstein singularity at separation. In 3D we show a flow over a dent in which separation occurs. A rotating flat plat is used to show the applicability of the method for rotating flows. The shown capabilities of the method indicate that the quasi-simultaneous interaction method is suitable for design methods for offshore wind turbine blades.

  14. Exchange-Hole Dipole Dispersion Model for Accurate Energy Ranking in Molecular Crystal Structure Prediction.

    PubMed

    Whittleton, Sarah R; Otero-de-la-Roza, A; Johnson, Erin R

    2017-02-14

    Accurate energy ranking is a key facet to the problem of first-principles crystal-structure prediction (CSP) of molecular crystals. This work presents a systematic assessment of B86bPBE-XDM, a semilocal density functional combined with the exchange-hole dipole moment (XDM) dispersion model, for energy ranking using 14 compounds from the first five CSP blind tests. Specifically, the set of crystals studied comprises 11 rigid, planar compounds and 3 co-crystals. The experimental structure was correctly identified as the lowest in lattice energy for 12 of the 14 total crystals. One of the exceptions is 4-hydroxythiophene-2-carbonitrile, for which the experimental structure was correctly identified once a quasi-harmonic estimate of the vibrational free-energy contribution was included, evidencing the occasional importance of thermal corrections for accurate energy ranking. The other exception is an organic salt, where charge-transfer error (also called delocalization error) is expected to cause the base density functional to be unreliable. Provided the choice of base density functional is appropriate and an estimate of temperature effects is used, XDM-corrected density-functional theory is highly reliable for the energetic ranking of competing crystal structures.

  15. Measuring solar reflectance Part I: Defining a metric that accurately predicts solar heat gain

    SciTech Connect

    Levinson, Ronnen; Akbari, Hashem; Berdahl, Paul

    2010-05-14

    Solar reflectance can vary with the spectral and angular distributions of incident sunlight, which in turn depend on surface orientation, solar position and atmospheric conditions. A widely used solar reflectance metric based on the ASTM Standard E891 beam-normal solar spectral irradiance underestimates the solar heat gain of a spectrally selective 'cool colored' surface because this irradiance contains a greater fraction of near-infrared light than typically found in ordinary (unconcentrated) global sunlight. At mainland U.S. latitudes, this metric RE891BN can underestimate the annual peak solar heat gain of a typical roof or pavement (slope {le} 5:12 [23{sup o}]) by as much as 89 W m{sup -2}, and underestimate its peak surface temperature by up to 5 K. Using R{sub E891BN} to characterize roofs in a building energy simulation can exaggerate the economic value N of annual cool-roof net energy savings by as much as 23%. We define clear-sky air mass one global horizontal ('AM1GH') solar reflectance R{sub g,0}, a simple and easily measured property that more accurately predicts solar heat gain. R{sub g,0} predicts the annual peak solar heat gain of a roof or pavement to within 2 W m{sup -2}, and overestimates N by no more than 3%. R{sub g,0} is well suited to rating the solar reflectances of roofs, pavements and walls. We show in Part II that R{sub g,0} can be easily and accurately measured with a pyranometer, a solar spectrophotometer or version 6 of the Solar Spectrum Reflectometer.

  16. Point-of-care cardiac troponin test accurately predicts heat stroke severity in rats.

    PubMed

    Audet, Gerald N; Quinn, Carrie M; Leon, Lisa R

    2015-11-15

    Heat stroke (HS) remains a significant public health concern. Despite the substantial threat posed by HS, there is still no field or clinical test of HS severity. We suggested previously that circulating cardiac troponin (cTnI) could serve as a robust biomarker of HS severity after heating. In the present study, we hypothesized that (cTnI) point-of-care test (ctPOC) could be used to predict severity and organ damage at the onset of HS. Conscious male Fischer 344 rats (n = 16) continuously monitored for heart rate (HR), blood pressure (BP), and core temperature (Tc) (radiotelemetry) were heated to maximum Tc (Tc,Max) of 41.9 ± 0.1°C and recovered undisturbed for 24 h at an ambient temperature of 20°C. Blood samples were taken at Tc,Max and 24 h after heat via submandibular bleed and analyzed on ctPOC test. POC cTnI band intensity was ranked using a simple four-point scale via two blinded observers and compared with cTnI levels measured by a clinical blood analyzer. Blood was also analyzed for biomarkers of systemic organ damage. HS severity, as previously defined using HR, BP, and recovery Tc profile during heat exposure, correlated strongly with cTnI (R(2) = 0.69) at Tc,Max. POC cTnI band intensity ranking accurately predicted cTnI levels (R(2) = 0.64) and HS severity (R(2) = 0.83). Five markers of systemic organ damage also correlated with ctPOC score (albumin, alanine aminotransferase, blood urea nitrogen, cholesterol, and total bilirubin; R(2) > 0.4). This suggests that cTnI POC tests can accurately determine HS severity and could serve as simple, portable, cost-effective HS field tests.

  17. Highly Accurate Prediction of Protein-Protein Interactions via Incorporating Evolutionary Information and Physicochemical Characteristics

    PubMed Central

    Li, Zheng-Wei; You, Zhu-Hong; Chen, Xing; Gui, Jie; Nie, Ru

    2016-01-01

    Protein-protein interactions (PPIs) occur at almost all levels of cell functions and play crucial roles in various cellular processes. Thus, identification of PPIs is critical for deciphering the molecular mechanisms and further providing insight into biological processes. Although a variety of high-throughput experimental techniques have been developed to identify PPIs, existing PPI pairs by experimental approaches only cover a small fraction of the whole PPI networks, and further, those approaches hold inherent disadvantages, such as being time-consuming, expensive, and having high false positive rate. Therefore, it is urgent and imperative to develop automatic in silico approaches to predict PPIs efficiently and accurately. In this article, we propose a novel mixture of physicochemical and evolutionary-based feature extraction method for predicting PPIs using our newly developed discriminative vector machine (DVM) classifier. The improvements of the proposed method mainly consist in introducing an effective feature extraction method that can capture discriminative features from the evolutionary-based information and physicochemical characteristics, and then a powerful and robust DVM classifier is employed. To the best of our knowledge, it is the first time that DVM model is applied to the field of bioinformatics. When applying the proposed method to the Yeast and Helicobacter pylori (H. pylori) datasets, we obtain excellent prediction accuracies of 94.35% and 90.61%, respectively. The computational results indicate that our method is effective and robust for predicting PPIs, and can be taken as a useful supplementary tool to the traditional experimental methods for future proteomics research. PMID:27571061

  18. Human cervicovaginal fluid biomarkers to predict term and preterm labor

    PubMed Central

    Heng, Yujing J.; Liong, Stella; Permezel, Michael; Rice, Gregory E.; Di Quinzio, Megan K. W.; Georgiou, Harry M.

    2015-01-01

    Preterm birth (PTB; birth before 37 completed weeks of gestation) remains the major cause of neonatal morbidity and mortality. The current generation of biomarkers predictive of PTB have limited utility. In pregnancy, the human cervicovaginal fluid (CVF) proteome is a reflection of the local biochemical milieu and is influenced by the physical changes occurring in the vagina, cervix and adjacent overlying fetal membranes. Term and preterm labor (PTL) share common pathways of cervical ripening, myometrial activation and fetal membranes rupture leading to birth. We therefore hypothesize that CVF biomarkers predictive of labor may be similar in both the term and preterm labor setting. In this review, we summarize some of the existing published literature as well as our team's breadth of work utilizing the CVF for the discovery and validation of putative CVF biomarkers predictive of human labor. Our team established an efficient method for collecting serial CVF samples for optimal 2-dimensional gel electrophoresis resolution and analysis. We first embarked on CVF biomarker discovery for the prediction of spontaneous onset of term labor using 2D-electrophoresis and solution array multiple analyte profiling. 2D-electrophoretic analyses were subsequently performed on CVF samples associated with PTB. Several proteins have been successfully validated and demonstrate that these biomarkers are associated with term and PTL and may be predictive of both term and PTL. In addition, the measurement of these putative biomarkers was found to be robust to the influences of vaginal microflora and/or semen. The future development of a multiple biomarker bed-side test would help improve the prediction of PTB and the clinical management of patients. PMID:26029118

  19. A Critical Review for Developing Accurate and Dynamic Predictive Models Using Machine Learning Methods in Medicine and Health Care.

    PubMed

    Alanazi, Hamdan O; Abdullah, Abdul Hanan; Qureshi, Kashif Naseer

    2017-04-01

    Recently, Artificial Intelligence (AI) has been used widely in medicine and health care sector. In machine learning, the classification or prediction is a major field of AI. Today, the study of existing predictive models based on machine learning methods is extremely active. Doctors need accurate predictions for the outcomes of their patients' diseases. In addition, for accurate predictions, timing is another significant factor that influences treatment decisions. In this paper, existing predictive models in medicine and health care have critically reviewed. Furthermore, the most famous machine learning methods have explained, and the confusion between a statistical approach and machine learning has clarified. A review of related literature reveals that the predictions of existing predictive models differ even when the same dataset is used. Therefore, existing predictive models are essential, and current methods must be improved.

  20. A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina.

    PubMed

    Maturana, Matias I; Apollo, Nicholas V; Hadjinicolaou, Alex E; Garrett, David J; Cloherty, Shaun L; Kameneva, Tatiana; Grayden, David B; Ibbotson, Michael R; Meffin, Hamish

    2016-04-01

    Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron's electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy.

  1. ChIP-seq Accurately Predicts Tissue-Specific Activity of Enhancers

    SciTech Connect

    Visel, Axel; Blow, Matthew J.; Li, Zirong; Zhang, Tao; Akiyama, Jennifer A.; Holt, Amy; Plajzer-Frick, Ingrid; Shoukry, Malak; Wright, Crystal; Chen, Feng; Afzal, Veena; Ren, Bing; Rubin, Edward M.; Pennacchio, Len A.

    2009-02-01

    A major yet unresolved quest in decoding the human genome is the identification of the regulatory sequences that control the spatial and temporal expression of genes. Distant-acting transcriptional enhancers are particularly challenging to uncover since they are scattered amongst the vast non-coding portion of the genome. Evolutionary sequence constraint can facilitate the discovery of enhancers, but fails to predict when and where they are active in vivo. Here, we performed chromatin immunoprecipitation with the enhancer-associated protein p300, followed by massively-parallel sequencing, to map several thousand in vivo binding sites of p300 in mouse embryonic forebrain, midbrain, and limb tissue. We tested 86 of these sequences in a transgenic mouse assay, which in nearly all cases revealed reproducible enhancer activity in those tissues predicted by p300 binding. Our results indicate that in vivo mapping of p300 binding is a highly accurate means for identifying enhancers and their associated activities and suggest that such datasets will be useful to study the role of tissue-specific enhancers in human biology and disease on a genome-wide scale.

  2. A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina

    PubMed Central

    Maturana, Matias I.; Apollo, Nicholas V.; Hadjinicolaou, Alex E.; Garrett, David J.; Cloherty, Shaun L.; Kameneva, Tatiana; Grayden, David B.; Ibbotson, Michael R.; Meffin, Hamish

    2016-01-01

    Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron’s electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy. PMID:27035143

  3. Accurate load prediction by BEM with airfoil data from 3D RANS simulations

    NASA Astrophysics Data System (ADS)

    Schneider, Marc S.; Nitzsche, Jens; Hennings, Holger

    2016-09-01

    In this paper, two methods for the extraction of airfoil coefficients from 3D CFD simulations of a wind turbine rotor are investigated, and these coefficients are used to improve the load prediction of a BEM code. The coefficients are extracted from a number of steady RANS simulations, using either averaging of velocities in annular sections, or an inverse BEM approach for determination of the induction factors in the rotor plane. It is shown that these 3D rotor polars are able to capture the rotational augmentation at the inner part of the blade as well as the load reduction by 3D effects close to the blade tip. They are used as input to a simple BEM code and the results of this BEM with 3D rotor polars are compared to the predictions of BEM with 2D airfoil coefficients plus common empirical corrections for stall delay and tip loss. While BEM with 2D airfoil coefficients produces a very different radial distribution of loads than the RANS simulation, the BEM with 3D rotor polars manages to reproduce the loads from RANS very accurately for a variety of load cases, as long as the blade pitch angle is not too different from the cases from which the polars were extracted.

  4. Accurate First-Principles Spectra Predictions for Planetological and Astrophysical Applications at Various T-Conditions

    NASA Astrophysics Data System (ADS)

    Rey, M.; Nikitin, A. V.; Tyuterev, V.

    2014-06-01

    Knowledge of near infrared intensities of rovibrational transitions of polyatomic molecules is essential for the modeling of various planetary atmospheres, brown dwarfs and for other astrophysical applications 1,2,3. For example, to analyze exoplanets, atmospheric models have been developed, thus making the need to provide accurate spectroscopic data. Consequently, the spectral characterization of such planetary objects relies on the necessity of having adequate and reliable molecular data in extreme conditions (temperature, optical path length, pressure). On the other hand, in the modeling of astrophysical opacities, millions of lines are generally involved and the line-by-line extraction is clearly not feasible in laboratory measurements. It is thus suggested that this large amount of data could be interpreted only by reliable theoretical predictions. There exists essentially two theoretical approaches for the computation and prediction of spectra. The first one is based on empirically-fitted effective spectroscopic models. Another way for computing energies, line positions and intensities is based on global variational calculations using ab initio surfaces. They do not yet reach the spectroscopic accuracy stricto sensu but implicitly account for all intramolecular interactions including resonance couplings in a wide spectral range. The final aim of this work is to provide reliable predictions which could be quantitatively accurate with respect to the precision of available observations and as complete as possible. All this thus requires extensive first-principles quantum mechanical calculations essentially based on three necessary ingredients which are (i) accurate intramolecular potential energy surface and dipole moment surface components well-defined in a large range of vibrational displacements and (ii) efficient computational methods combined with suitable choices of coordinates to account for molecular symmetry properties and to achieve a good numerical

  5. Accurate and Robust Genomic Prediction of Celiac Disease Using Statistical Learning

    PubMed Central

    Abraham, Gad; Tye-Din, Jason A.; Bhalala, Oneil G.; Kowalczyk, Adam; Zobel, Justin; Inouye, Michael

    2014-01-01

    Practical application of genomic-based risk stratification to clinical diagnosis is appealing yet performance varies widely depending on the disease and genomic risk score (GRS) method. Celiac disease (CD), a common immune-mediated illness, is strongly genetically determined and requires specific HLA haplotypes. HLA testing can exclude diagnosis but has low specificity, providing little information suitable for clinical risk stratification. Using six European cohorts, we provide a proof-of-concept that statistical learning approaches which simultaneously model all SNPs can generate robust and highly accurate predictive models of CD based on genome-wide SNP profiles. The high predictive capacity replicated both in cross-validation within each cohort (AUC of 0.87–0.89) and in independent replication across cohorts (AUC of 0.86–0.9), despite differences in ethnicity. The models explained 30–35% of disease variance and up to ∼43% of heritability. The GRS's utility was assessed in different clinically relevant settings. Comparable to HLA typing, the GRS can be used to identify individuals without CD with ≥99.6% negative predictive value however, unlike HLA typing, fine-scale stratification of individuals into categories of higher-risk for CD can identify those that would benefit from more invasive and costly definitive testing. The GRS is flexible and its performance can be adapted to the clinical situation by adjusting the threshold cut-off. Despite explaining a minority of disease heritability, our findings indicate a genomic risk score provides clinically relevant information to improve upon current diagnostic pathways for CD and support further studies evaluating the clinical utility of this approach in CD and other complex diseases. PMID:24550740

  6. Energy expenditure during level human walking: seeking a simple and accurate predictive solution.

    PubMed

    Ludlow, Lindsay W; Weyand, Peter G

    2016-03-01

    Accurate prediction of the metabolic energy that walking requires can inform numerous health, bodily status, and fitness outcomes. We adopted a two-step approach to identifying a concise, generalized equation for predicting level human walking metabolism. Using literature-aggregated values we compared 1) the predictive accuracy of three literature equations: American College of Sports Medicine (ACSM), Pandolf et al., and Height-Weight-Speed (HWS); and 2) the goodness-of-fit possible from one- vs. two-component descriptions of walking metabolism. Literature metabolic rate values (n = 127; speed range = 0.4 to 1.9 m/s) were aggregated from 25 subject populations (n = 5-42) whose means spanned a 1.8-fold range of heights and a 4.2-fold range of weights. Population-specific resting metabolic rates (V̇o2 rest) were determined using standardized equations. Our first finding was that the ACSM and Pandolf et al. equations underpredicted nearly all 127 literature-aggregated values. Consequently, their standard errors of estimate (SEE) were nearly four times greater than those of the HWS equation (4.51 and 4.39 vs. 1.13 ml O2·kg(-1)·min(-1), respectively). For our second comparison, empirical best-fit relationships for walking metabolism were derived from the data set in one- and two-component forms for three V̇o2-speed model types: linear (∝V(1.0)), exponential (∝V(2.0)), and exponential/height (∝V(2.0)/Ht). We found that the proportion of variance (R(2)) accounted for, when averaged across the three model types, was substantially lower for one- vs. two-component versions (0.63 ± 0.1 vs. 0.90 ± 0.03) and the predictive errors were nearly twice as great (SEE = 2.22 vs. 1.21 ml O2·kg(-1)·min(-1)). Our final analysis identified the following concise, generalized equation for predicting level human walking metabolism: V̇o2 total = V̇o2 rest + 3.85 + 5.97·V(2)/Ht (where V is measured in m/s, Ht in meters, and V̇o2 in ml O2·kg(-1)·min(-1)).

  7. Can radiation therapy treatment planning system accurately predict surface doses in postmastectomy radiation therapy patients?

    SciTech Connect

    Wong, Sharon; Back, Michael; Tan, Poh Wee; Lee, Khai Mun; Baggarley, Shaun; Lu, Jaide Jay

    2012-07-01

    Skin doses have been an important factor in the dose prescription for breast radiotherapy. Recent advances in radiotherapy treatment techniques, such as intensity-modulated radiation therapy (IMRT) and new treatment schemes such as hypofractionated breast therapy have made the precise determination of the surface dose necessary. Detailed information of the dose at various depths of the skin is also critical in designing new treatment strategies. The purpose of this work was to assess the accuracy of surface dose calculation by a clinically used treatment planning system and those measured by thermoluminescence dosimeters (TLDs) in a customized chest wall phantom. This study involved the construction of a chest wall phantom for skin dose assessment. Seven TLDs were distributed throughout each right chest wall phantom to give adequate representation of measured radiation doses. Point doses from the CMS Xio Registered-Sign treatment planning system (TPS) were calculated for each relevant TLD positions and results correlated. There were no significant difference between measured absorbed dose by TLD and calculated doses by the TPS (p > 0.05 (1-tailed). Dose accuracy of up to 2.21% was found. The deviations from the calculated absorbed doses were overall larger (3.4%) when wedges and bolus were used. 3D radiotherapy TPS is a useful and accurate tool to assess the accuracy of surface dose. Our studies have shown that radiation treatment accuracy expressed as a comparison between calculated doses (by TPS) and measured doses (by TLD dosimetry) can be accurately predicted for tangential treatment of the chest wall after mastectomy.

  8. Structure-based constitutive model can accurately predict planar biaxial properties of aortic wall tissue.

    PubMed

    Polzer, S; Gasser, T C; Novak, K; Man, V; Tichy, M; Skacel, P; Bursa, J

    2015-03-01

    Structure-based constitutive models might help in exploring mechanisms by which arterial wall histology is linked to wall mechanics. This study aims to validate a recently proposed structure-based constitutive model. Specifically, the model's ability to predict mechanical biaxial response of porcine aortic tissue with predefined collagen structure was tested. Histological slices from porcine thoracic aorta wall (n=9) were automatically processed to quantify the collagen fiber organization, and mechanical testing identified the non-linear properties of the wall samples (n=18) over a wide range of biaxial stretches. Histological and mechanical experimental data were used to identify the model parameters of a recently proposed multi-scale constitutive description for arterial layers. The model predictive capability was tested with respect to interpolation and extrapolation. Collagen in the media was predominantly aligned in circumferential direction (planar von Mises distribution with concentration parameter bM=1.03 ± 0.23), and its coherence decreased gradually from the luminal to the abluminal tissue layers (inner media, b=1.54 ± 0.40; outer media, b=0.72 ± 0.20). In contrast, the collagen in the adventitia was aligned almost isotropically (bA=0.27 ± 0.11), and no features, such as families of coherent fibers, were identified. The applied constitutive model captured the aorta biaxial properties accurately (coefficient of determination R(2)=0.95 ± 0.03) over the entire range of biaxial deformations and with physically meaningful model parameters. Good predictive properties, well outside the parameter identification space, were observed (R(2)=0.92 ± 0.04). Multi-scale constitutive models equipped with realistic micro-histological data can predict macroscopic non-linear aorta wall properties. Collagen largely defines already low strain properties of media, which explains the origin of wall anisotropy seen at this strain level. The structure and mechanical

  9. Predicting accurate fluorescent spectra for high molecular weight polycyclic aromatic hydrocarbons using density functional theory

    NASA Astrophysics Data System (ADS)

    Powell, Jacob; Heider, Emily C.; Campiglia, Andres; Harper, James K.

    2016-10-01

    The ability of density functional theory (DFT) methods to predict accurate fluorescence spectra for polycyclic aromatic hydrocarbons (PAHs) is explored. Two methods, PBE0 and CAM-B3LYP, are evaluated both in the gas phase and in solution. Spectra for several of the most toxic PAHs are predicted and compared to experiment, including three isomers of C24H14 and a PAH containing heteroatoms. Unusually high-resolution experimental spectra are obtained for comparison by analyzing each PAH at 4.2 K in an n-alkane matrix. All theoretical spectra visually conform to the profiles of the experimental data but are systematically offset by a small amount. Specifically, when solvent is included the PBE0 functional overestimates peaks by 16.1 ± 6.6 nm while CAM-B3LYP underestimates the same transitions by 14.5 ± 7.6 nm. These calculated spectra can be empirically corrected to decrease the uncertainties to 6.5 ± 5.1 and 5.7 ± 5.1 nm for the PBE0 and CAM-B3LYP methods, respectively. A comparison of computed spectra in the gas phase indicates that the inclusion of n-octane shifts peaks by +11 nm on average and this change is roughly equivalent for PBE0 and CAM-B3LYP. An automated approach for comparing spectra is also described that minimizes residuals between a given theoretical spectrum and all available experimental spectra. This approach identifies the correct spectrum in all cases and excludes approximately 80% of the incorrect spectra, demonstrating that an automated search of theoretical libraries of spectra may eventually become feasible.

  10. New consensus definition for acute kidney injury accurately predicts 30-day mortality in cirrhosis with infection

    PubMed Central

    Wong, Florence; O’Leary, Jacqueline G; Reddy, K Rajender; Patton, Heather; Kamath, Patrick S; Fallon, Michael B; Garcia-Tsao, Guadalupe; Subramanian, Ram M.; Malik, Raza; Maliakkal, Benedict; Thacker, Leroy R; Bajaj, Jasmohan S

    2015-01-01

    Background & Aims A consensus conference proposed that cirrhosis-associated acute kidney injury (AKI) be defined as an increase in serum creatinine by >50% from the stable baseline value in <6 months or by ≥0.3mg/dL in <48 hrs. We prospectively evaluated the ability of these criteria to predict mortality within 30 days among hospitalized patients with cirrhosis and infection. Methods 337 patients with cirrhosis admitted with or developed an infection in hospital (56% men; 56±10 y old; model for end-stage liver disease score, 20±8) were followed. We compared data on 30-day mortality, hospital length-of-stay, and organ failure between patients with and without AKI. Results 166 (49%) developed AKI during hospitalization, based on the consensus criteria. Patients who developed AKI had higher admission Child-Pugh (11.0±2.1 vs 9.6±2.1; P<.0001), and MELD scores (23±8 vs17±7; P<.0001), and lower mean arterial pressure (81±16mmHg vs 85±15mmHg; P<.01) than those who did not. Also higher amongst patients with AKI were mortality in ≤30 days (34% vs 7%), intensive care unit transfer (46% vs 20%), ventilation requirement (27% vs 6%), and shock (31% vs 8%); AKI patients also had longer hospital stays (17.8±19.8 days vs 13.3±31.8 days) (all P<.001). 56% of AKI episodes were transient, 28% persistent, and 16% resulted in dialysis. Mortality was 80% among those without renal recovery, higher compared to partial (40%) or complete recovery (15%), or AKI-free patients (7%; P<.0001). Conclusions 30-day mortality is 10-fold higher among infected hospitalized cirrhotic patients with irreversible AKI than those without AKI. The consensus definition of AKI accurately predicts 30-day mortality, length of hospital stay, and organ failure. PMID:23999172

  11. Predicting Fluid Flow in Stressed Fractures: A Quantitative Evaluation of Methods

    NASA Astrophysics Data System (ADS)

    Weihmann, S. A.; Healy, D.

    2015-12-01

    Reliable estimation of fracture stability in the subsurface is crucial to the success of exploration and production in the petroleum industry, and also for wider applications to earthquake mechanics, hydrogeology and waste disposal. Previous work suggests that fracture stability is related to fluid flow in crystalline basement rocks through shear or tensile instabilities of fractures. Our preliminary scoping analysis compares the fracture stability of 60 partly open (apertures 1.5-3 cm) and electrically conductive (low acoustic amplitudes relative to matrix) fractures from a 16 m section of a producing zone in a basement well in Bayoot field, Yemen, to a non-producing zone in the same well (also 16 m). We determine the Critically Stressed Fractures (CSF; Barton et al., 1995) and dilatation tendency (Td; Ferrill et al., 1999). We find that: 1. CSF (Fig. 1) is a poor predictor of high fluid flow in the inflow zone; 88% of the fractures are predicted to be NOT critically stressed and yet they all occur within a zone of high fluid flow rate 2. Td (Fig. 2) is also a poor predictor of high fluid flow in the inflow zone; 67% of the fractures have a LOW Td(< 0.6) 3. For the non-producing zone CSF is a very reliable predictor (100% are not critically stressed) whereas the values of Tdare consistent with their location in non-producing interval (81% are < 0.6) (Fig. 3 & 4). In summary, neither method correlates well with the observed abundance of hydraulically conductive fractures within the producing zone. Within the non-producing zone CSF and Td make reasonably accurate predictions. Fractures may be filled or partially filled with drilling mud or a lower density and electrically conductive fill such as clay in the producing zone and therefore appear (partly) open. In situ stress, fluid pressure, rock properties (friction, strength) and fracture orientation data used as inputs for the CSF and Td calculations are all subject to uncertainty. Our results suggest that scope

  12. Fast and Accurate Prediction of Numerical Relativity Waveforms from Binary Black Hole Coalescences Using Surrogate Models.

    PubMed

    Blackman, Jonathan; Field, Scott E; Galley, Chad R; Szilágyi, Béla; Scheel, Mark A; Tiglio, Manuel; Hemberger, Daniel A

    2015-09-18

    Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. Using reduced order modeling techniques, we construct an accurate surrogate model, which is evaluated in a millisecond to a second, for numerical relativity (NR) waveforms from nonspinning binary black hole coalescences with mass ratios in [1, 10] and durations corresponding to about 15 orbits before merger. We assess the model's uncertainty and show that our modeling strategy predicts NR waveforms not used for the surrogate's training with errors nearly as small as the numerical error of the NR code. Our model includes all spherical-harmonic _{-2}Y_{ℓm} waveform modes resolved by the NR code up to ℓ=8. We compare our surrogate model to effective one body waveforms from 50M_{⊙} to 300M_{⊙} for advanced LIGO detectors and find that the surrogate is always more faithful (by at least an order of magnitude in most cases).

  13. Cluster abundance in chameleon f(R) gravity I: toward an accurate halo mass function prediction

    NASA Astrophysics Data System (ADS)

    Cataneo, Matteo; Rapetti, David; Lombriser, Lucas; Li, Baojiu

    2016-12-01

    We refine the mass and environment dependent spherical collapse model of chameleon f(R) gravity by calibrating a phenomenological correction inspired by the parameterized post-Friedmann framework against high-resolution N-body simulations. We employ our method to predict the corresponding modified halo mass function, and provide fitting formulas to calculate the enhancement of the f(R) halo abundance with respect to that of General Relativity (GR) within a precision of lesssim 5% from the results obtained in the simulations. Similar accuracy can be achieved for the full f(R) mass function on the condition that the modeling of the reference GR abundance of halos is accurate at the percent level. We use our fits to forecast constraints on the additional scalar degree of freedom of the theory, finding that upper bounds competitive with current Solar System tests are within reach of cluster number count analyses from ongoing and upcoming surveys at much larger scales. Importantly, the flexibility of our method allows also for this to be applied to other scalar-tensor theories characterized by a mass and environment dependent spherical collapse.

  14. Accurate prediction of band gaps and optical properties of HfO2

    NASA Astrophysics Data System (ADS)

    Ondračka, Pavel; Holec, David; Nečas, David; Zajíčková, Lenka

    2016-10-01

    We report on optical properties of various polymorphs of hafnia predicted within the framework of density functional theory. The full potential linearised augmented plane wave method was employed together with the Tran-Blaha modified Becke-Johnson potential (TB-mBJ) for exchange and local density approximation for correlation. Unit cells of monoclinic, cubic and tetragonal crystalline, and a simulated annealing-based model of amorphous hafnia were fully relaxed with respect to internal positions and lattice parameters. Electronic structures and band gaps for monoclinic, cubic, tetragonal and amorphous hafnia were calculated using three different TB-mBJ parametrisations and the results were critically compared with the available experimental and theoretical reports. Conceptual differences between a straightforward comparison of experimental measurements to a calculated band gap on the one hand and to a whole electronic structure (density of electronic states) on the other hand, were pointed out, suggesting the latter should be used whenever possible. Finally, dielectric functions were calculated at two levels, using the random phase approximation without local field effects and with a more accurate Bethe-Salpether equation (BSE) to account for excitonic effects. We conclude that a satisfactory agreement with experimental data for HfO2 was obtained only in the latter case.

  15. Accurate prediction of V1 location from cortical folds in a surface coordinate system

    PubMed Central

    Hinds, Oliver P.; Rajendran, Niranjini; Polimeni, Jonathan R.; Augustinack, Jean C.; Wiggins, Graham; Wald, Lawrence L.; Rosas, H. Diana; Potthast, Andreas; Schwartz, Eric L.; Fischl, Bruce

    2008-01-01

    Previous studies demonstrated substantial variability of the location of primary visual cortex (V1) in stereotaxic coordinates when linear volume-based registration is used to match volumetric image intensities (Amunts et al., 2000). However, other qualitative reports of V1 location (Smith, 1904; Stensaas et al., 1974; Rademacher et al., 1993) suggested a consistent relationship between V1 and the surrounding cortical folds. Here, the relationship between folds and the location of V1 is quantified using surface-based analysis to generate a probabilistic atlas of human V1. High-resolution (about 200 μm) magnetic resonance imaging (MRI) at 7 T of ex vivo human cerebral hemispheres allowed identification of the full area via the stria of Gennari: a myeloarchitectonic feature specific to V1. Separate, whole-brain scans were acquired using MRI at 1.5 T to allow segmentation and mesh reconstruction of the cortical gray matter. For each individual, V1 was manually identified in the high-resolution volume and projected onto the cortical surface. Surface-based intersubject registration (Fischl et al., 1999b) was performed to align the primary cortical folds of individual hemispheres to those of a reference template representing the average folding pattern. An atlas of V1 location was constructed by computing the probability of V1 inclusion for each cortical location in the template space. This probabilistic atlas of V1 exhibits low prediction error compared to previous V1 probabilistic atlases built in volumetric coordinates. The increased predictability observed under surface-based registration suggests that the location of V1 is more accurately predicted by the cortical folds than by the shape of the brain embedded in the volume of the skull. In addition, the high quality of this atlas provides direct evidence that surface-based intersubject registration methods are superior to volume-based methods at superimposing functional areas of cortex, and therefore are better

  16. Raoult’s law revisited: accurately predicting equilibrium relative humidity points for humidity control experiments

    PubMed Central

    Bowler, Michael G.

    2017-01-01

    The humidity surrounding a sample is an important variable in scientific experiments. Biological samples in particular require not just a humid atmosphere but often a relative humidity (RH) that is in equilibrium with a stabilizing solution required to maintain the sample in the same state during measurements. The controlled dehydration of macromolecular crystals can lead to significant increases in crystal order, leading to higher diffraction quality. Devices that can accurately control the humidity surrounding crystals while monitoring diffraction have led to this technique being increasingly adopted, as the experiments become easier and more reproducible. Matching the RH to the mother liquor is the first step in allowing the stable mounting of a crystal. In previous work [Wheeler, Russi, Bowler & Bowler (2012). Acta Cryst. F68, 111–114], the equilibrium RHs were measured for a range of concentrations of the most commonly used precipitants in macromolecular crystallography and it was shown how these related to Raoult’s law for the equilibrium vapour pressure of water above a solution. However, a discrepancy between the measured values and those predicted by theory could not be explained. Here, a more precise humidity control device has been used to determine equilibrium RH points. The new results are in agreement with Raoult’s law. A simple argument in statistical mechanics is also presented, demonstrating that the equilibrium vapour pressure of a solvent is proportional to its mole fraction in an ideal solution: Raoult’s law. The same argument can be extended to the case where the solvent and solute molecules are of different sizes, as is the case with polymers. The results provide a framework for the correct maintenance of the RH surrounding a sample. PMID:28381983

  17. Raoult's law revisited: accurately predicting equilibrium relative humidity points for humidity control experiments.

    PubMed

    Bowler, Michael G; Bowler, David R; Bowler, Matthew W

    2017-04-01

    The humidity surrounding a sample is an important variable in scientific experiments. Biological samples in particular require not just a humid atmosphere but often a relative humidity (RH) that is in equilibrium with a stabilizing solution required to maintain the sample in the same state during measurements. The controlled dehydration of macromolecular crystals can lead to significant increases in crystal order, leading to higher diffraction quality. Devices that can accurately control the humidity surrounding crystals while monitoring diffraction have led to this technique being increasingly adopted, as the experiments become easier and more reproducible. Matching the RH to the mother liquor is the first step in allowing the stable mounting of a crystal. In previous work [Wheeler, Russi, Bowler & Bowler (2012). Acta Cryst. F68, 111-114], the equilibrium RHs were measured for a range of concentrations of the most commonly used precipitants in macromolecular crystallography and it was shown how these related to Raoult's law for the equilibrium vapour pressure of water above a solution. However, a discrepancy between the measured values and those predicted by theory could not be explained. Here, a more precise humidity control device has been used to determine equilibrium RH points. The new results are in agreement with Raoult's law. A simple argument in statistical mechanics is also presented, demonstrating that the equilibrium vapour pressure of a solvent is proportional to its mole fraction in an ideal solution: Raoult's law. The same argument can be extended to the case where the solvent and solute molecules are of different sizes, as is the case with polymers. The results provide a framework for the correct maintenance of the RH surrounding a sample.

  18. Fluid reasoning predicts future mathematical performance among children and adolescents.

    PubMed

    Green, Chloe T; Bunge, Silvia A; Briones Chiongbian, Victoria; Barrow, Maia; Ferrer, Emilio

    2017-05-01

    The aim of this longitudinal study was to determine whether fluid reasoning (FR) plays a significant role in the acquisition of mathematics skills above and beyond the effects of other cognitive and numerical abilities. Using a longitudinal cohort sequential design, we examined how FR measured at three assessment occasions, spaced approximately 1.5years apart, predicted math outcomes for a group of 69 participants between ages 6 and 21years across all three assessment occasions. We used structural equation modeling (SEM) to examine the direct and indirect relations between children's previous cognitive abilities and their future math achievement. A model including age, FR, vocabulary, and spatial skills accounted for 90% of the variance in future math achievement. In this model, FR was the only significant predictor of future math achievement; age, vocabulary, and spatial skills were not significant predictors. Thus, FR was the only predictor of future math achievement across a wide age range that spanned primary school and secondary school. These findings build on Cattell's conceptualization of FR as a scaffold for learning, showing that this domain-general ability supports the acquisition of rudimentary math skills as well as the ability to solve more complex mathematical problems.

  19. Hippocampal volume predicts fluid intelligence in musically trained people.

    PubMed

    Oechslin, Mathias S; Descloux, Céline; Croquelois, Alexandre; Chanal, Julien; Van De Ville, Dimitri; Lazeyras, François; James, Clara E

    2013-07-01

    Recently, age-related hippocampal (HP) volume loss could be associated with a decrease in general fluid intelligence (gF). In the present study we investigated whether and how extensive musical training modulates human HP volume and gF performance. Previously, some studies demonstrated positive effects of musical training on higher cognitive functions such as learning and memory, associated with neural adaptations beyond the auditory domain. In order to detect possible associations between musical training and gF, we bilaterally segmented the HP formation and assessed the individual gF performance of people with different levels of musical expertise. Multiple regression analyses revealed that HP volume predicts gF in musicians but not in nonmusicians; in particular, bilaterally enhanced HP volume is associated with increased gF exclusively in musically trained people (amateurs and experts). This result suggests that musical training facilitates the recruitment of cognitive resources, which are essential for gF and linked to HP functioning. Musical training, even at a moderate level of intensity, can thus be considered as a potential strategy to decelerate age-related effects of cognitive decline.

  20. Predicting phase behavior of mixtures of reservoir fluids with carbon dioxide

    SciTech Connect

    Grigg, R.B.; Lingane, P.J.

    1983-01-01

    The use of an equation of state to predict phase behavior during carbon dioxide flooding is well established. The characterization of the C/sub 7/ fraction and the selection of interaction parameters are the most important variables. Single-contact phase behavior is presented for mixtures of Ford Geraldine (Delaware), Maljamar (Grayburg), West Sussex (Shannon), and Reservoir D reservoir fluids, and of a synthetic oil with carbon dioxide. The phase behavior of these mixtures can be reproduced using 3 to 5 pseudo components and common interaction parameters. The critical properties of the pseudo components are calculated from detailed oil characterizations. Because the parameters are not further adjusted, this approach reduces the empiricism in fitting phase data and may result in a more accurate representation of the system as the composition of the oil changes during the approach to miscibility. 21 references.

  1. Prediction of quantitative intrathoracic fluid volume to diagnose pulmonary oedema using LabVIEW.

    PubMed

    Urooj, Shabana; Khan, M; Ansari, A Q; Lay-Ekuakille, Aimé; Salhan, Ashok K

    2012-01-01

    Pulmonary oedema is a life-threatening disease that requires special attention in the area of research and clinical diagnosis. Computer-based techniques are rarely used to quantify the intrathoracic fluid volume (IFV) for diagnostic purposes. This paper discusses a software program developed to detect and diagnose pulmonary oedema using LabVIEW. The software runs on anthropometric dimensions and physiological parameters, mainly transthoracic electrical impedance (TEI). This technique is accurate and faster than existing manual techniques. The LabVIEW software was used to compute the parameters required to quantify IFV. An equation relating per cent control and IFV was obtained. The results of predicted TEI and measured TEI were compared with previously reported data to validate the developed program. It was found that the predicted values of TEI obtained from the computer-based technique were much closer to the measured values of TEI. Six new subjects were enrolled to measure and predict transthoracic impedance and hence to quantify IFV. A similar difference was also observed in the measured and predicted values of TEI for the new subjects.

  2. Combining Structural Modeling with Ensemble Machine Learning to Accurately Predict Protein Fold Stability and Binding Affinity Effects upon Mutation

    PubMed Central

    Garcia Lopez, Sebastian; Kim, Philip M.

    2014-01-01

    Advances in sequencing have led to a rapid accumulation of mutations, some of which are associated with diseases. However, to draw mechanistic conclusions, a biochemical understanding of these mutations is necessary. For coding mutations, accurate prediction of significant changes in either the stability of proteins or their affinity to their binding partners is required. Traditional methods have used semi-empirical force fields, while newer methods employ machine learning of sequence and structural features. Here, we show how combining both of these approaches leads to a marked boost in accuracy. We introduce ELASPIC, a novel ensemble machine learning approach that is able to predict stability effects upon mutation in both, domain cores and domain-domain interfaces. We combine semi-empirical energy terms, sequence conservation, and a wide variety of molecular details with a Stochastic Gradient Boosting of Decision Trees (SGB-DT) algorithm. The accuracy of our predictions surpasses existing methods by a considerable margin, achieving correlation coefficients of 0.77 for stability, and 0.75 for affinity predictions. Notably, we integrated homology modeling to enable proteome-wide prediction and show that accurate prediction on modeled structures is possible. Lastly, ELASPIC showed significant differences between various types of disease-associated mutations, as well as between disease and common neutral mutations. Unlike pure sequence-based prediction methods that try to predict phenotypic effects of mutations, our predictions unravel the molecular details governing the protein instability, and help us better understand the molecular causes of diseases. PMID:25243403

  3. Industrial Compositional Streamline Simulation for Efficient and Accurate Prediction of Gas Injection and WAG Processes

    SciTech Connect

    Margot Gerritsen

    2008-10-31

    Gas-injection processes are widely and increasingly used for enhanced oil recovery (EOR). In the United States, for example, EOR production by gas injection accounts for approximately 45% of total EOR production and has tripled since 1986. The understanding of the multiphase, multicomponent flow taking place in any displacement process is essential for successful design of gas-injection projects. Due to complex reservoir geometry, reservoir fluid properties and phase behavior, the design of accurate and efficient numerical simulations for the multiphase, multicomponent flow governing these processes is nontrivial. In this work, we developed, implemented and tested a streamline based solver for gas injection processes that is computationally very attractive: as compared to traditional Eulerian solvers in use by industry it computes solutions with a computational speed orders of magnitude higher and a comparable accuracy provided that cross-flow effects do not dominate. We contributed to the development of compositional streamline solvers in three significant ways: improvement of the overall framework allowing improved streamline coverage and partial streamline tracing, amongst others; parallelization of the streamline code, which significantly improves wall clock time; and development of new compositional solvers that can be implemented along streamlines as well as in existing Eulerian codes used by industry. We designed several novel ideas in the streamline framework. First, we developed an adaptive streamline coverage algorithm. Adding streamlines locally can reduce computational costs by concentrating computational efforts where needed, and reduce mapping errors. Adapting streamline coverage effectively controls mass balance errors that mostly result from the mapping from streamlines to pressure grid. We also introduced the concept of partial streamlines: streamlines that do not necessarily start and/or end at wells. This allows more efficient coverage and avoids

  4. Towards more accurate wind and solar power prediction by improving NWP model physics

    NASA Astrophysics Data System (ADS)

    Steiner, Andrea; Köhler, Carmen; von Schumann, Jonas; Ritter, Bodo

    2014-05-01

    The growing importance and successive expansion of renewable energies raise new challenges for decision makers, economists, transmission system operators, scientists and many more. In this interdisciplinary field, the role of Numerical Weather Prediction (NWP) is to reduce the errors and provide an a priori estimate of remaining uncertainties associated with the large share of weather-dependent power sources. For this purpose it is essential to optimize NWP model forecasts with respect to those prognostic variables which are relevant for wind and solar power plants. An improved weather forecast serves as the basis for a sophisticated power forecasts. Consequently, a well-timed energy trading on the stock market, and electrical grid stability can be maintained. The German Weather Service (DWD) currently is involved with two projects concerning research in the field of renewable energy, namely ORKA*) and EWeLiNE**). Whereas the latter is in collaboration with the Fraunhofer Institute (IWES), the project ORKA is led by energy & meteo systems (emsys). Both cooperate with German transmission system operators. The goal of the projects is to improve wind and photovoltaic (PV) power forecasts by combining optimized NWP and enhanced power forecast models. In this context, the German Weather Service aims to improve its model system, including the ensemble forecasting system, by working on data assimilation, model physics and statistical post processing. This presentation is focused on the identification of critical weather situations and the associated errors in the German regional NWP model COSMO-DE. First steps leading to improved physical parameterization schemes within the NWP-model are presented. Wind mast measurements reaching up to 200 m height above ground are used for the estimation of the (NWP) wind forecast error at heights relevant for wind energy plants. One particular problem is the daily cycle in wind speed. The transition from stable stratification during

  5. A review of drug solubility in human intestinal fluids: implications for the prediction of oral absorption.

    PubMed

    Augustijns, Patrick; Wuyts, Benjamin; Hens, Bart; Annaert, Pieter; Butler, James; Brouwers, Joachim

    2014-06-16

    The purpose of this paper is to collate all recently published solubility data of orally administered drugs in human intestinal fluids (HIF) that were aspirated from the upper small intestine (duodenum and jejunum). The data set comprises in total 102 solubility values in fasted state HIF and 37 solubility values in fed state HIF, covering 59 different drugs. Despite differences in the protocol for HIF sampling and subsequent handling, this summary of HIF solubilities provides a critical reference data set to judge the value of simulated media for intestinal solubility estimation. In this regard, the review includes correlations between the reported solubilizing capacity of HIF and fasted or fed state simulated intestinal fluid (FaSSIF/FeSSIF). Correlating with HIF solubilities enables the optimal use of solubility measurements in simulated biorelevant media to obtain accurate estimates of intestinal solubility during drug development. Considering the fraction of poorly soluble new molecular entities in contemporary drug discovery, adequate prediction of intestinal solubility is critical for efficient lead optimization, early candidate profiling, and further development.

  6. A machine learning approach to the accurate prediction of multi-leaf collimator positional errors

    NASA Astrophysics Data System (ADS)

    Carlson, Joel N. K.; Park, Jong Min; Park, So-Yeon; In Park, Jong; Choi, Yunseok; Ye, Sung-Joon

    2016-03-01

    Discrepancies between planned and delivered movements of multi-leaf collimators (MLCs) are an important source of errors in dose distributions during radiotherapy. In this work we used machine learning techniques to train models to predict these discrepancies, assessed the accuracy of the model predictions, and examined the impact these errors have on quality assurance (QA) procedures and dosimetry. Predictive leaf motion parameters for the models were calculated from the plan files, such as leaf position and velocity, whether the leaf was moving towards or away from the isocenter of the MLC, and many others. Differences in positions between synchronized DICOM-RT planning files and DynaLog files reported during QA delivery were used as a target response for training of the models. The final model is capable of predicting MLC positions during delivery to a high degree of accuracy. For moving MLC leaves, predicted positions were shown to be significantly closer to delivered positions than were planned positions. By incorporating predicted positions into dose calculations in the TPS, increases were shown in gamma passing rates against measured dose distributions recorded during QA delivery. For instance, head and neck plans with 1%/2 mm gamma criteria had an average increase in passing rate of 4.17% (SD  =  1.54%). This indicates that the inclusion of predictions during dose calculation leads to a more realistic representation of plan delivery. To assess impact on the patient, dose volumetric histograms (DVH) using delivered positions were calculated for comparison with planned and predicted DVHs. In all cases, predicted dose volumetric parameters were in closer agreement to the delivered parameters than were the planned parameters, particularly for organs at risk on the periphery of the treatment area. By incorporating the predicted positions into the TPS, the treatment planner is given a more realistic view of the dose distribution as it will truly be

  7. An accurate and efficient method to predict the electronic excitation energies of BODIPY fluorescent dyes.

    PubMed

    Wang, Jia-Nan; Jin, Jun-Ling; Geng, Yun; Sun, Shi-Ling; Xu, Hong-Liang; Lu, Ying-Hua; Su, Zhong-Min

    2013-03-15

    Recently, the extreme learning machine neural network (ELMNN) as a valid computing method has been proposed to predict the nonlinear optical property successfully (Wang et al., J. Comput. Chem. 2012, 33, 231). In this work, first, we follow this line of work to predict the electronic excitation energies using the ELMNN method. Significantly, the root mean square deviation of the predicted electronic excitation energies of 90 4,4-difluoro-4-bora-3a,4a-diaza-s-indacene (BODIPY) derivatives between the predicted and experimental values has been reduced to 0.13 eV. Second, four groups of molecule descriptors are considered when building the computing models. The results show that the quantum chemical descriptions have the closest intrinsic relation with the electronic excitation energy values. Finally, a user-friendly web server (EEEBPre: Prediction of electronic excitation energies for BODIPY dyes), which is freely accessible to public at the web site: http://202.198.129.218, has been built for prediction. This web server can return the predicted electronic excitation energy values of BODIPY dyes that are high consistent with the experimental values. We hope that this web server would be helpful to theoretical and experimental chemists in related research.

  8. Sensor data fusion for accurate cloud presence prediction using Dempster-Shafer evidence theory.

    PubMed

    Li, Jiaming; Luo, Suhuai; Jin, Jesse S

    2010-01-01

    Sensor data fusion technology can be used to best extract useful information from multiple sensor observations. It has been widely applied in various applications such as target tracking, surveillance, robot navigation, signal and image processing. This paper introduces a novel data fusion approach in a multiple radiation sensor environment using Dempster-Shafer evidence theory. The methodology is used to predict cloud presence based on the inputs of radiation sensors. Different radiation data have been used for the cloud prediction. The potential application areas of the algorithm include renewable power for virtual power station where the prediction of cloud presence is the most challenging issue for its photovoltaic output. The algorithm is validated by comparing the predicted cloud presence with the corresponding sunshine occurrence data that were recorded as the benchmark. Our experiments have indicated that comparing to the approaches using individual sensors, the proposed data fusion approach can increase correct rate of cloud prediction by ten percent, and decrease unknown rate of cloud prediction by twenty three percent.

  9. 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.

  10. NESmapper: accurate prediction of leucine-rich nuclear export signals using activity-based profiles.

    PubMed

    Kosugi, Shunichi; Yanagawa, Hiroshi; Terauchi, Ryohei; Tabata, Satoshi

    2014-09-01

    The nuclear export of proteins is regulated largely through the exportin/CRM1 pathway, which involves the specific recognition of leucine-rich nuclear export signals (NESs) in the cargo proteins, and modulates nuclear-cytoplasmic protein shuttling by antagonizing the nuclear import activity mediated by importins and the nuclear import signal (NLS). Although the prediction of NESs can help to define proteins that undergo regulated nuclear export, current methods of predicting NESs, including computational tools and consensus-sequence-based searches, have limited accuracy, especially in terms of their specificity. We found that each residue within an NES largely contributes independently and additively to the entire nuclear export activity. We created activity-based profiles of all classes of NESs with a comprehensive mutational analysis in mammalian cells. The profiles highlight a number of specific activity-affecting residues not only at the conserved hydrophobic positions but also in the linker and flanking regions. We then developed a computational tool, NESmapper, to predict NESs by using profiles that had been further optimized by training and combining the amino acid properties of the NES-flanking regions. This tool successfully reduced the considerable number of false positives, and the overall prediction accuracy was higher than that of other methods, including NESsential and Wregex. This profile-based prediction strategy is a reliable way to identify functional protein motifs. NESmapper is available at http://sourceforge.net/projects/nesmapper.

  11. Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli

    PubMed Central

    Kim, Minseung; Rai, Navneet; Zorraquino, Violeta; Tagkopoulos, Ilias

    2016-01-01

    A significant obstacle in training predictive cell models is the lack of integrated data sources. We develop semi-supervised normalization pipelines and perform experimental characterization (growth, transcriptional, proteome) to create Ecomics, a consistent, quality-controlled multi-omics compendium for Escherichia coli with cohesive meta-data information. We then use this resource to train a multi-scale model that integrates four omics layers to predict genome-wide concentrations and growth dynamics. The genetic and environmental ontology reconstructed from the omics data is substantially different and complementary to the genetic and chemical ontologies. The integration of different layers confers an incremental increase in the prediction performance, as does the information about the known gene regulatory and protein-protein interactions. The predictive performance of the model ranges from 0.54 to 0.87 for the various omics layers, which far exceeds various baselines. This work provides an integrative framework of omics-driven predictive modelling that is broadly applicable to guide biological discovery. PMID:27713404

  12. Empirical approaches to more accurately predict benthic-pelagic coupling in biogeochemical ocean models

    NASA Astrophysics Data System (ADS)

    Dale, Andy; Stolpovsky, Konstantin; Wallmann, Klaus

    2016-04-01

    The recycling and burial of biogenic material in the sea floor plays a key role in the regulation of ocean chemistry. Proper consideration of these processes in ocean biogeochemical models is becoming increasingly recognized as an important step in model validation and prediction. However, the rate of organic matter remineralization in sediments and the benthic flux of redox-sensitive elements are difficult to predict a priori. In this communication, examples of empirical benthic flux models that can be coupled to earth system models to predict sediment-water exchange in the open ocean are presented. Large uncertainties hindering further progress in this field include knowledge of the reactivity of organic carbon reaching the sediment, the importance of episodic variability in bottom water chemistry and particle rain rates (for both the deep-sea and margins) and the role of benthic fauna. How do we meet the challenge?

  13. An endometrial gene expression signature accurately predicts recurrent implantation failure after IVF

    PubMed Central

    Koot, Yvonne E. M.; van Hooff, Sander R.; Boomsma, Carolien M.; van Leenen, Dik; Groot Koerkamp, Marian J. A.; Goddijn, Mariëtte; Eijkemans, Marinus J. C.; Fauser, Bart C. J. M.; Holstege, Frank C. P.; Macklon, Nick S.

    2016-01-01

    The primary limiting factor for effective IVF treatment is successful embryo implantation. Recurrent implantation failure (RIF) is a condition whereby couples fail to achieve pregnancy despite consecutive embryo transfers. Here we describe the collection of gene expression profiles from mid-luteal phase endometrial biopsies (n = 115) from women experiencing RIF and healthy controls. Using a signature discovery set (n = 81) we identify a signature containing 303 genes predictive of RIF. Independent validation in 34 samples shows that the gene signature predicts RIF with 100% positive predictive value (PPV). The strength of the RIF associated expression signature also stratifies RIF patients into distinct groups with different subsequent implantation success rates. Exploration of the expression changes suggests that RIF is primarily associated with reduced cellular proliferation. The gene signature will be of value in counselling and guiding further treatment of women who fail to conceive upon IVF and suggests new avenues for developing intervention. PMID:26797113

  14. Accurate ab initio prediction of NMR chemical shifts of nucleic acids and nucleic acids/protein complexes

    PubMed Central

    Victora, Andrea; Möller, Heiko M.; Exner, Thomas E.

    2014-01-01

    NMR chemical shift predictions based on empirical methods are nowadays indispensable tools during resonance assignment and 3D structure calculation of proteins. However, owing to the very limited statistical data basis, such methods are still in their infancy in the field of nucleic acids, especially when non-canonical structures and nucleic acid complexes are considered. Here, we present an ab initio approach for predicting proton chemical shifts of arbitrary nucleic acid structures based on state-of-the-art fragment-based quantum chemical calculations. We tested our prediction method on a diverse set of nucleic acid structures including double-stranded DNA, hairpins, DNA/protein complexes and chemically-modified DNA. Overall, our quantum chemical calculations yield highly/very accurate predictions with mean absolute deviations of 0.3–0.6 ppm and correlation coefficients (r2) usually above 0.9. This will allow for identifying misassignments and validating 3D structures. Furthermore, our calculations reveal that chemical shifts of protons involved in hydrogen bonding are predicted significantly less accurately. This is in part caused by insufficient inclusion of solvation effects. However, it also points toward shortcomings of current force fields used for structure determination of nucleic acids. Our quantum chemical calculations could therefore provide input for force field optimization. PMID:25404135

  15. β-human chorionic gonadotropin assay in vaginal washing fluid for the accurate diagnosis of premature rupture of membranes during late pregnancy

    PubMed Central

    Temel, Orhan; Çöğendez, Ebru; Selçuk, Selçuk; Asoğlu, Mehmet Reşit; Kaya, Erdal

    2013-01-01

    Objective To determine whether the measurement of beta-human chorionic gonadotropin (β-hCG) levels in vaginal fluid is useful for the diagnosis of premature rupture of membranes (PROM). Material and Methods A total of 92 pregnant women between 24 and 40 weeks gestation participated in this study. The patients with fluid leaking from the vagina were designated Group 1, the patients with no fluid leaking from the vagina were Group 2, and those with a suspicion of fluid leaking from the vagina were classified as Group 3. Irrigating the posterior vaginal fornix with 5 mL sterile saline was used to measure β-hCG levels of the patients. Receiver operator curve (ROC) analysis was used to determine the cut-off value for a positive diagnosis. Results The β-hCG levels of vaginal fluid were measured as 20.5±25.0 mIU/mL, 254.6±346.8 mIU/mL, and 74.3±100.8 mIU/mL in Group 1, Group 2, and Group 3, respectively. Vaginal β-hCG level was higher statistically significantly in Group 2 than Group 1 and 3 (p<0.001). 100 mIU/mL was accepted as a cut-off value by using the receiver operating characteristic curve. According to 100 mIU/mL, sensitivity, specificity, positive predictive and negative predictive values were calculated as 71.2, 100, 100, and 65.1%, respectively. Conclusion The study showed that the measurement of β-hCG level in vaginal washing fluid is an efficient and easy diagnostic test for predicting the amount of fluid leaking from the vagina. However, due to the low negative predictive value of the test, it would not be convenient in daily practice. PMID:24592106

  16. Dynamics of Flexible MLI-type Debris for Accurate Orbit Prediction

    DTIC Science & Technology

    2014-09-01

    SUBJECT TERMS EOARD, orbital debris , HAMR objects, multi-layered insulation, orbital dynamics, orbit predictions, orbital propagation 16. SECURITY...illustration are orbital debris [Souce: NASA...piece of space junk (a paint fleck) during the STS-7 mission (Photo: NASA Orbital Debris Program Office

  17. Hippocampus neuronal metabolic gene expression outperforms whole tissue data in accurately predicting Alzheimer's disease progression.

    PubMed

    Stempler, Shiri; Waldman, Yedael Y; Wolf, Lior; Ruppin, Eytan

    2012-09-01

    Numerous metabolic alterations are associated with the impairment of brain cells in Alzheimer's disease (AD). Here we use gene expression microarrays of both whole hippocampus tissue and hippocampal neurons of AD patients to investigate the ability of metabolic gene expression to predict AD progression and its cognitive decline. We find that the prediction accuracy of different AD stages is markedly higher when using neuronal expression data (0.9) than when using whole tissue expression (0.76). Furthermore, the metabolic genes' expression is shown to be as effective in predicting AD severity as the entire gene list. Remarkably, a regression model from hippocampal metabolic gene expression leads to a marked correlation of 0.57 with the Mini-Mental State Examination cognitive score. Notably, the expression of top predictive neuronal genes in AD is significantly higher than that of other metabolic genes in the brains of healthy subjects. All together, the analyses point to a subset of metabolic genes that is strongly associated with normal brain functioning and whose disruption plays a major role in AD.

  18. Predicting repeat self-harm in children--how accurate can we expect to be?

    PubMed

    Chitsabesan, Prathiba; Harrington, Richard; Harrington, Valerie; Tomenson, Barbara

    2003-01-01

    The main objective of the study was to find which variables predict repetition of deliberate self-harm in children. The study is based on a group of children who took part in a randomized control trial investigating the effects of a home-based family intervention for children who had deliberately poisoned themselves. These children had a range of baseline and outcome measures collected on two occasions (two and six months follow-up). Outcome data were collected from 149 (92 %) of the initial 162 children over the six months. Twenty-three children made a further deliberate self-harm attempt within the follow-up period. A number of variables at baseline were found to be significantly associated with repeat self-harm. Parental mental health and a history of previous attempts were the strongest predictors. A model of prediction of further deliberate self-harm combining these significant individual variables produced a high positive predictive value (86 %) but had low sensitivity (28 %). Predicting repeat self-harm in children is difficult, even with a comprehensive series of assessments over multiple time points, and we need to adapt services with this in mind. We propose a model of service provision which takes these findings into account.

  19. Predictions of bubbly flows in vertical pipes using two-fluid models in CFDS-FLOW3D code

    SciTech Connect

    Banas, A.O.; Carver, M.B.; Unrau, D.

    1995-09-01

    This paper reports the results of a preliminary study exploring the performance of two sets of two-fluid closure relationships applied to the simulation of turbulent air-water bubbly upflows through vertical pipes. Predictions obtained with the default CFDS-FLOW3D model for dispersed flows were compared with the predictions of a new model (based on the work of Lee), and with the experimental data of Liu. The new model, implemented in the CFDS-FLOW3D code, included additional source terms in the {open_quotes}standard{close_quotes} {kappa}-{epsilon} transport equations for the liquid phase, as well as modified model coefficients and wall functions. All simulations were carried out in a 2-D axisymmetric format, collapsing the general multifluid framework of CFDS-FLOW3D to the two-fluid (air-water) case. The newly implemented model consistently improved predictions of radial-velocity profiles of both phases, but failed to accurately reproduce the experimental phase-distribution data. This shortcoming was traced to the neglect of anisotropic effects in the modelling of liquid-phase turbulence. In this sense, the present investigation should be considered as the first step toward the ultimate goal of developing a theoretically sound and universal CFD-type two-fluid model for bubbly flows in channels.

  20. Accurate prediction of the optical rotation and NMR properties for highly flexible chiral natural products.

    PubMed

    Hashmi, Muhammad Ali; Andreassend, Sarah K; Keyzers, Robert A; Lein, Matthias

    2016-09-21

    Despite advances in electronic structure theory the theoretical prediction of spectroscopic properties remains a computational challenge. This is especially true for natural products that exhibit very large conformational freedom and hence need to be sampled over many different accessible conformations. We report a strategy, which is able to predict NMR chemical shifts and more elusive properties like the optical rotation with great precision, through step-wise incremental increases of the conformational degrees of freedom. The application of this method is demonstrated for 3-epi-xestoaminol C, a chiral natural compound with a long, linear alkyl chain of 14 carbon atoms. Experimental NMR and [α]D values are reported to validate the results of the density functional theory calculations.

  1. FastRNABindR: Fast and Accurate Prediction of Protein-RNA Interface Residues.

    PubMed

    El-Manzalawy, Yasser; Abbas, Mostafa; Malluhi, Qutaibah; Honavar, Vasant

    2016-01-01

    A wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses are mediated by RNA-protein interactions. However, experimental determination of the structures of protein-RNA complexes is expensive and technically challenging. Hence, a number of computational tools have been developed for predicting protein-RNA interfaces. Some of the state-of-the-art protein-RNA interface predictors rely on position-specific scoring matrix (PSSM)-based encoding of the protein sequences. The computational efforts needed for generating PSSMs severely limits the practical utility of protein-RNA interface prediction servers. In this work, we experiment with two approaches, random sampling and sequence similarity reduction, for extracting a representative reference database of protein sequences from more than 50 million protein sequences in UniRef100. Our results suggest that random sampled databases produce better PSSM profiles (in terms of the number of hits used to generate the profile and the distance of the generated profile to the corresponding profile generated using the entire UniRef100 data as well as the accuracy of the machine learning classifier trained using these profiles). Based on our results, we developed FastRNABindR, an improved version of RNABindR for predicting protein-RNA interface residues using PSSM profiles generated using 1% of the UniRef100 sequences sampled uniformly at random. To the best of our knowledge, FastRNABindR is the only protein-RNA interface residue prediction online server that requires generation of PSSM profiles for query sequences and accepts hundreds of protein sequences per submission. Our approach for determining the optimal BLAST database for a protein-RNA interface residue classification task has the potential of substantially speeding up, and hence increasing the practical utility of, other amino acid sequence based predictors of protein-protein and protein

  2. Robust and Accurate Modeling Approaches for Migraine Per-Patient Prediction from Ambulatory Data.

    PubMed

    Pagán, Josué; De Orbe, M Irene; Gago, Ana; Sobrado, Mónica; Risco-Martín, José L; Mora, J Vivancos; Moya, José M; Ayala, José L

    2015-06-30

    Migraine is one of the most wide-spread neurological disorders, and its medical treatment represents a high percentage of the costs of health systems. In some patients, characteristic symptoms that precede the headache appear. However, they are nonspecific, and their prediction horizon is unknown and pretty variable; hence, these symptoms are almost useless for prediction, and they are not useful to advance the intake of drugs to be effective and neutralize the pain. To solve this problem, this paper sets up a realistic monitoring scenario where hemodynamic variables from real patients are monitored in ambulatory conditions with a wireless body sensor network (WBSN). The acquired data are used to evaluate the predictive capabilities and robustness against noise and failures in sensors of several modeling approaches. The obtained results encourage the development of per-patient models based on state-space models (N4SID) that are capable of providing average forecast windows of 47 min and a low rate of false positives.

  3. Accurate structure prediction of peptide–MHC complexes for identifying highly immunogenic antigens

    SciTech Connect

    Park, Min-Sun; Park, Sung Yong; Miller, Keith R.; Collins, Edward J.; Lee, Ha Youn

    2013-11-01

    Designing an optimal HIV-1 vaccine faces the challenge of identifying antigens that induce a broad immune capacity. One factor to control the breadth of T cell responses is the surface morphology of a peptide–MHC complex. Here, we present an in silico protocol for predicting peptide–MHC structure. A robust signature of a conformational transition was identified during all-atom molecular dynamics, which results in a model with high accuracy. A large test set was used in constructing our protocol and we went another step further using a blind test with a wild-type peptide and two highly immunogenic mutants, which predicted substantial conformational changes in both mutants. The center residues at position five of the analogs were configured to be accessible to solvent, forming a prominent surface, while the residue of the wild-type peptide was to point laterally toward the side of the binding cleft. We then experimentally determined the structures of the blind test set, using high resolution of X-ray crystallography, which verified predicted conformational changes. Our observation strongly supports a positive association of the surface morphology of a peptide–MHC complex to its immunogenicity. Our study offers the prospect of enhancing immunogenicity of vaccines by identifying MHC binding immunogens.

  4. Fast and accurate numerical method for predicting gas chromatography retention time.

    PubMed

    Claumann, Carlos Alberto; Wüst Zibetti, André; Bolzan, Ariovaldo; Machado, Ricardo A F; Pinto, Leonel Teixeira

    2015-08-07

    Predictive modeling for gas chromatography compound retention depends on the retention factor (ki) and on the flow of the mobile phase. Thus, different approaches for determining an analyte ki in column chromatography have been developed. The main one is based on the thermodynamic properties of the component and on the characteristics of the stationary phase. These models can be used to estimate the parameters and to optimize the programming of temperatures, in gas chromatography, for the separation of compounds. Different authors have proposed the use of numerical methods for solving these models, but these methods demand greater computational time. Hence, a new method for solving the predictive modeling of analyte retention time is presented. This algorithm is an alternative to traditional methods because it transforms its attainments into root determination problems within defined intervals. The proposed approach allows for tr calculation, with accuracy determined by the user of the methods, and significant reductions in computational time; it can also be used to evaluate the performance of other prediction methods.

  5. Revisiting the blind tests in crystal structure prediction: accurate energy ranking of molecular crystals.

    PubMed

    Asmadi, Aldi; Neumann, Marcus A; Kendrick, John; Girard, Pascale; Perrin, Marc-Antoine; Leusen, Frank J J

    2009-12-24

    In the 2007 blind test of crystal structure prediction hosted by the Cambridge Crystallographic Data Centre (CCDC), a hybrid DFT/MM method correctly ranked each of the four experimental structures as having the lowest lattice energy of all the crystal structures predicted for each molecule. The work presented here further validates this hybrid method by optimizing the crystal structures (experimental and submitted) of the first three CCDC blind tests held in 1999, 2001, and 2004. Except for the crystal structures of compound IX, all structures were reminimized and ranked according to their lattice energies. The hybrid method computes the lattice energy of a crystal structure as the sum of the DFT total energy and a van der Waals (dispersion) energy correction. Considering all four blind tests, the crystal structure with the lowest lattice energy corresponds to the experimentally observed structure for 12 out of 14 molecules. Moreover, good geometrical agreement is observed between the structures determined by the hybrid method and those measured experimentally. In comparison with the correct submissions made by the blind test participants, all hybrid optimized crystal structures (apart from compound II) have the smallest calculated root mean squared deviations from the experimentally observed structures. It is predicted that a new polymorph of compound V exists under pressure.

  6. Robust and Accurate Modeling Approaches for Migraine Per-Patient Prediction from Ambulatory Data

    PubMed Central

    Pagán, Josué; Irene De Orbe, M.; Gago, Ana; Sobrado, Mónica; Risco-Martín, José L.; Vivancos Mora, J.; Moya, José M.; Ayala, José L.

    2015-01-01

    Migraine is one of the most wide-spread neurological disorders, and its medical treatment represents a high percentage of the costs of health systems. In some patients, characteristic symptoms that precede the headache appear. However, they are nonspecific, and their prediction horizon is unknown and pretty variable; hence, these symptoms are almost useless for prediction, and they are not useful to advance the intake of drugs to be effective and neutralize the pain. To solve this problem, this paper sets up a realistic monitoring scenario where hemodynamic variables from real patients are monitored in ambulatory conditions with a wireless body sensor network (WBSN). The acquired data are used to evaluate the predictive capabilities and robustness against noise and failures in sensors of several modeling approaches. The obtained results encourage the development of per-patient models based on state-space models (N4SID) that are capable of providing average forecast windows of 47 min and a low rate of false positives. PMID:26134103

  7. Accurate prediction of drug-induced liver injury using stem cell-derived populations.

    PubMed

    Szkolnicka, Dagmara; Farnworth, Sarah L; Lucendo-Villarin, Baltasar; Storck, Christopher; Zhou, Wenli; Iredale, John P; Flint, Oliver; Hay, David C

    2014-02-01

    Despite major progress in the knowledge and management of human liver injury, there are millions of people suffering from chronic liver disease. Currently, the only cure for end-stage liver disease is orthotopic liver transplantation; however, this approach is severely limited by organ donation. Alternative approaches to restoring liver function have therefore been pursued, including the use of somatic and stem cell populations. Although such approaches are essential in developing scalable treatments, there is also an imperative to develop predictive human systems that more effectively study and/or prevent the onset of liver disease and decompensated organ function. We used a renewable human stem cell resource, from defined genetic backgrounds, and drove them through developmental intermediates to yield highly active, drug-inducible, and predictive human hepatocyte populations. Most importantly, stem cell-derived hepatocytes displayed equivalence to primary adult hepatocytes, following incubation with known hepatotoxins. In summary, we have developed a serum-free, scalable, and shippable cell-based model that faithfully predicts the potential for human liver injury. Such a resource has direct application in human modeling and, in the future, could play an important role in developing renewable cell-based therapies.

  8. Accurate prediction of cellular co-translational folding indicates proteins can switch from post- to co-translational folding

    NASA Astrophysics Data System (ADS)

    Nissley, Daniel A.; Sharma, Ajeet K.; Ahmed, Nabeel; Friedrich, Ulrike A.; Kramer, Günter; Bukau, Bernd; O'Brien, Edward P.

    2016-02-01

    The rates at which domains fold and codons are translated are important factors in determining whether a nascent protein will co-translationally fold and function or misfold and malfunction. Here we develop a chemical kinetic model that calculates a protein domain's co-translational folding curve during synthesis using only the domain's bulk folding and unfolding rates and codon translation rates. We show that this model accurately predicts the course of co-translational folding measured in vivo for four different protein molecules. We then make predictions for a number of different proteins in yeast and find that synonymous codon substitutions, which change translation-elongation rates, can switch some protein domains from folding post-translationally to folding co-translationally--a result consistent with previous experimental studies. Our approach explains essential features of co-translational folding curves and predicts how varying the translation rate at different codon positions along a transcript's coding sequence affects this self-assembly process.

  9. Predicting critical temperatures of ionic and non-ionic fluids from thermophysical data obtained near the melting point.

    PubMed

    Weiss, Volker C

    2015-10-14

    In the correlation and prediction of thermophysical data of fluids based on a corresponding-states approach, the critical temperature Tc plays a central role. For some fluids, in particular ionic ones, however, the critical region is difficult or even impossible to access experimentally. For molten salts, Tc is on the order of 3000 K, which makes accurate measurements a challenging task. Room temperature ionic liquids (RTILs) decompose thermally between 400 K and 600 K due to their organic constituents; this range of temperatures is hundreds of degrees below recent estimates of their Tc. In both cases, reliable methods to deduce Tc based on extrapolations of experimental data recorded at much lower temperatures near the triple or melting points are needed and useful because the critical point influences the fluid's behavior in the entire liquid region. Here, we propose to employ the scaling approach leading to universal fluid behavior [Román et al., J. Chem. Phys. 123, 124512 (2005)] to derive a very simple expression that allows one to estimate Tc from the density of the liquid, the surface tension, or the enthalpy of vaporization measured in a very narrow range of low temperatures. We demonstrate the validity of the approach for simple and polar neutral fluids, for which Tc is known, and then use the methodology to obtain estimates of Tc for ionic fluids. When comparing these estimates to those reported in the literature, good agreement is found for RTILs, whereas the ones for the molten salts NaCl and KCl are lower than previous estimates by 10%. The coexistence curve for ionic fluids is found to be more adequately described by an effective exponent of βeff = 0.5 than by βeff = 0.33.

  10. Can tritiated water-dilution space accurately predict total body water in chukar partridges

    SciTech Connect

    Crum, B.G.; Williams, J.B.; Nagy, K.A.

    1985-11-01

    Total body water (TBW) volumes determined from the dilution space of injected tritiated water have consistently overestimated actual water volumes (determined by desiccation to constant mass) in reptiles and mammals, but results for birds are controversial. We investigated potential errors in both the dilution method and the desiccation method in an attempt to resolve this controversy. Tritiated water dilution yielded an accurate measurement of water mass in vitro. However, in vivo, this method yielded a 4.6% overestimate of the amount of water (3.1% of live body mass) in chukar partridges, apparently largely because of loss of tritium from body water to sites of dissociable hydrogens on body solids. An additional source of overestimation (approximately 2% of body mass) was loss of tritium to the solids in blood samples during distillation of blood to obtain pure water for tritium analysis. Measuring tritium activity in plasma samples avoided this problem but required measurement of, and correction for, the dry matter content in plasma. Desiccation to constant mass by lyophilization or oven-drying also overestimated the amount of water actually in the bodies of chukar partridges by 1.4% of body mass, because these values included water adsorbed onto the outside of feathers. When desiccating defeathered carcasses, oven-drying at 70 degrees C yielded TBW values identical to those obtained from lyophilization, but TBW was overestimated (0.5% of body mass) by drying at 100 degrees C due to loss of organic substances as well as water.

  11. Does preoperative cross-sectional imaging accurately predict main duct involvement in intraductal papillary mucinous neoplasm?

    PubMed

    Barron, M R; Roch, A M; Waters, J A; Parikh, J A; DeWitt, J M; Al-Haddad, M A; Ceppa, E P; House, M G; Zyromski, N J; Nakeeb, A; Pitt, H A; Schmidt, C Max

    2014-03-01

    Main pancreatic duct (MPD) involvement is a well-demonstrated risk factor for malignancy in intraductal papillary mucinous neoplasm (IPMN). Preoperative radiographic determination of IPMN type is heavily relied upon in oncologic risk stratification. We hypothesized that radiographic assessment of MPD involvement in IPMN is an accurate predictor of pathological MPD involvement. Data regarding all patients undergoing resection for IPMN at a single academic institution between 1992 and 2012 were gathered prospectively. Retrospective analysis of imaging and pathologic data was undertaken. Preoperative classification of IPMN type was based on cross-sectional imaging (MRI/magnetic resonance cholangiopancreatography (MRCP) and/or CT). Three hundred sixty-two patients underwent resection for IPMN. Of these, 334 had complete data for analysis. Of 164 suspected branch duct (BD) IPMN, 34 (20.7%) demonstrated MPD involvement on final pathology. Of 170 patients with suspicion of MPD involvement, 50 (29.4%) demonstrated no MPD involvement. Of 34 patients with suspected BD-IPMN who were found to have MPD involvement on pathology, 10 (29.4%) had invasive carcinoma. Alternatively, 2/50 (4%) of the patients with suspected MPD involvement who ultimately had isolated BD-IPMN demonstrated invasive carcinoma. Preoperative radiographic IPMN type did not correlate with final pathology in 25% of the patients. In addition, risk of invasive carcinoma correlates with pathologic presence of MPD involvement.

  12. DisoMCS: Accurately Predicting Protein Intrinsically Disordered Regions Using a Multi-Class Conservative Score Approach

    PubMed Central

    Wang, Zhiheng; Yang, Qianqian; Li, Tonghua; Cong, Peisheng

    2015-01-01

    The precise prediction of protein intrinsically disordered regions, which play a crucial role in biological procedures, is a necessary prerequisite to further the understanding of the principles and mechanisms of protein function. Here, we propose a novel predictor, DisoMCS, which is a more accurate predictor of protein intrinsically disordered regions. The DisoMCS bases on an original multi-class conservative score (MCS) obtained by sequence-order/disorder alignment. Initially, near-disorder regions are defined on fragments located at both the terminus of an ordered region connecting a disordered region. Then the multi-class conservative score is generated by sequence alignment against a known structure database and represented as order, near-disorder and disorder conservative scores. The MCS of each amino acid has three elements: order, near-disorder and disorder profiles. Finally, the MCS is exploited as features to identify disordered regions in sequences. DisoMCS utilizes a non-redundant data set as the training set, MCS and predicted secondary structure as features, and a conditional random field as the classification algorithm. In predicted near-disorder regions a residue is determined as an order or a disorder according to the optimized decision threshold. DisoMCS was evaluated by cross-validation, large-scale prediction, independent tests and CASP (Critical Assessment of Techniques for Protein Structure Prediction) tests. All results confirmed that DisoMCS was very competitive in terms of accuracy of prediction when compared with well-established publicly available disordered region predictors. It also indicated our approach was more accurate when a query has higher homologous with the knowledge database. Availability The DisoMCS is available at http://cal.tongji.edu.cn/disorder/. PMID:26090958

  13. Size-extensivity-corrected multireference configuration interaction schemes to accurately predict bond dissociation energies of oxygenated hydrocarbons

    SciTech Connect

    Oyeyemi, Victor B.; Krisiloff, David B.; Keith, John A.; Libisch, Florian; Pavone, Michele; Carter, Emily A.

    2014-01-28

    Oxygenated hydrocarbons play important roles in combustion science as renewable fuels and additives, but many details about their combustion chemistry remain poorly understood. Although many methods exist for computing accurate electronic energies of molecules at equilibrium geometries, a consistent description of entire combustion reaction potential energy surfaces (PESs) requires multireference correlated wavefunction theories. Here we use bond dissociation energies (BDEs) as a foundational metric to benchmark methods based on multireference configuration interaction (MRCI) for several classes of oxygenated compounds (alcohols, aldehydes, carboxylic acids, and methyl esters). We compare results from multireference singles and doubles configuration interaction to those utilizing a posteriori and a priori size-extensivity corrections, benchmarked against experiment and coupled cluster theory. We demonstrate that size-extensivity corrections are necessary for chemically accurate BDE predictions even in relatively small molecules and furnish examples of unphysical BDE predictions resulting from using too-small orbital active spaces. We also outline the specific challenges in using MRCI methods for carbonyl-containing compounds. The resulting complete basis set extrapolated, size-extensivity-corrected MRCI scheme produces BDEs generally accurate to within 1 kcal/mol, laying the foundation for this scheme's use on larger molecules and for more complex regions of combustion PESs.

  14. Size-extensivity-corrected multireference configuration interaction schemes to accurately predict bond dissociation energies of oxygenated hydrocarbons

    NASA Astrophysics Data System (ADS)

    Oyeyemi, Victor B.; Krisiloff, David B.; Keith, John A.; Libisch, Florian; Pavone, Michele; Carter, Emily A.

    2014-01-01

    Oxygenated hydrocarbons play important roles in combustion science as renewable fuels and additives, but many details about their combustion chemistry remain poorly understood. Although many methods exist for computing accurate electronic energies of molecules at equilibrium geometries, a consistent description of entire combustion reaction potential energy surfaces (PESs) requires multireference correlated wavefunction theories. Here we use bond dissociation energies (BDEs) as a foundational metric to benchmark methods based on multireference configuration interaction (MRCI) for several classes of oxygenated compounds (alcohols, aldehydes, carboxylic acids, and methyl esters). We compare results from multireference singles and doubles configuration interaction to those utilizing a posteriori and a priori size-extensivity corrections, benchmarked against experiment and coupled cluster theory. We demonstrate that size-extensivity corrections are necessary for chemically accurate BDE predictions even in relatively small molecules and furnish examples of unphysical BDE predictions resulting from using too-small orbital active spaces. We also outline the specific challenges in using MRCI methods for carbonyl-containing compounds. The resulting complete basis set extrapolated, size-extensivity-corrected MRCI scheme produces BDEs generally accurate to within 1 kcal/mol, laying the foundation for this scheme's use on larger molecules and for more complex regions of combustion PESs.

  15. Computational methods toward accurate RNA structure prediction using coarse-grained and all-atom models.

    PubMed

    Krokhotin, Andrey; Dokholyan, Nikolay V

    2015-01-01

    Computational methods can provide significant insights into RNA structure and dynamics, bridging the gap in our understanding of the relationship between structure and biological function. Simulations enrich and enhance our understanding of data derived on the bench, as well as provide feasible alternatives to costly or technically challenging experiments. Coarse-grained computational models of RNA are especially important in this regard, as they allow analysis of events occurring in timescales relevant to RNA biological function, which are inaccessible through experimental methods alone. We have developed a three-bead coarse-grained model of RNA for discrete molecular dynamics simulations. This model is efficient in de novo prediction of short RNA tertiary structure, starting from RNA primary sequences of less than 50 nucleotides. To complement this model, we have incorporated additional base-pairing constraints and have developed a bias potential reliant on data obtained from hydroxyl probing experiments that guide RNA folding to its correct state. By introducing experimentally derived constraints to our computer simulations, we are able to make reliable predictions of RNA tertiary structures up to a few hundred nucleotides. Our refined model exemplifies a valuable benefit achieved through integration of computation and experimental methods.

  16. Neural network and SVM classifiers accurately predict lipid binding proteins, irrespective of sequence homology.

    PubMed

    Bakhtiarizadeh, Mohammad Reza; Moradi-Shahrbabak, Mohammad; Ebrahimi, Mansour; Ebrahimie, Esmaeil

    2014-09-07

    Due to the central roles of lipid binding proteins (LBPs) in many biological processes, sequence based identification of LBPs is of great interest. The major challenge is that LBPs are diverse in sequence, structure, and function which results in low accuracy of sequence homology based methods. Therefore, there is a need for developing alternative functional prediction methods irrespective of sequence similarity. To identify LBPs from non-LBPs, the performances of support vector machine (SVM) and neural network were compared in this study. Comprehensive protein features and various techniques were employed to create datasets. Five-fold cross-validation (CV) and independent evaluation (IE) tests were used to assess the validity of the two methods. The results indicated that SVM outperforms neural network. SVM achieved 89.28% (CV) and 89.55% (IE) overall accuracy in identification of LBPs from non-LBPs and 92.06% (CV) and 92.90% (IE) (in average) for classification of different LBPs classes. Increasing the number and the range of extracted protein features as well as optimization of the SVM parameters significantly increased the efficiency of LBPs class prediction in comparison to the only previous report in this field. Altogether, the results showed that the SVM algorithm can be run on broad, computationally calculated protein features and offers a promising tool in detection of LBPs classes. The proposed approach has the potential to integrate and improve the common sequence alignment based methods.

  17. Accurate Prediction of the Dynamical Changes within the Second PDZ Domain of PTP1e

    PubMed Central

    Cilia, Elisa; Vuister, Geerten W.; Lenaerts, Tom

    2012-01-01

    Experimental NMR relaxation studies have shown that peptide binding induces dynamical changes at the side-chain level throughout the second PDZ domain of PTP1e, identifying as such the collection of residues involved in long-range communication. Even though different computational approaches have identified subsets of residues that were qualitatively comparable, no quantitative analysis of the accuracy of these predictions was thus far determined. Here, we show that our information theoretical method produces quantitatively better results with respect to the experimental data than some of these earlier methods. Moreover, it provides a global network perspective on the effect experienced by the different residues involved in the process. We also show that these predictions are consistent within both the human and mouse variants of this domain. Together, these results improve the understanding of intra-protein communication and allostery in PDZ domains, underlining at the same time the necessity of producing similar data sets for further validation of thses kinds of methods. PMID:23209399

  18. Fluid Flow Prediction with Development System Interwell Connectivity Influence

    NASA Astrophysics Data System (ADS)

    Bolshakov, M.; Deeva, T.; Pustovskikh, A.

    2016-03-01

    In this paper interwell connectivity has been studied. First of all, literature review of existing methods was made which is divided into three groups: Statistically-Based Methods, Material (fluid) Propagation-Based Methods and Potential (pressure) Change Propagation-Based Method. The disadvantages of the first and second groups are as follows: methods do not involve fluid flow through porous media, ignore any changes of well conditions (BHP, skin factor, etc.). The last group considers changes of well conditions and fluid flow through porous media. In this work Capacitance method (CM) has been chosen for research. This method is based on material balance and uses weight coefficients lambdas to assess well influence. In the next step synthetic model was created for examining CM. This model consists of an injection well and a production well. CM gave good results, it means that flow rates which were calculated by analytical method (CM) show matching with flow rate in model. Further new synthetic model was created which includes six production and one injection wells. This model represents seven-spot pattern. To obtain lambdas weight coefficients, the delta function was entered using by minimization algorithm. Also synthetic model which has three injectors and thirteen producer wells was created. This model simulates seven-spot pattern production system. Finally Capacitance method (CM) has been adjusted on real data of oil Field Ω. In this case CM does not give enough satisfying results in terms of field data liquid rate. In conclusion, recommendations to simplify CM calculations were given. Field Ω is assumed to have one injection and one production wells. In this case, satisfying results for production rates and cumulative production were obtained.

  19. Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

    SciTech Connect

    Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.; Fournier, Marcia V.

    2008-10-20

    One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic

  20. Combining multiple regression and principal component analysis for accurate predictions for column ozone in Peninsular Malaysia

    NASA Astrophysics Data System (ADS)

    Rajab, Jasim M.; MatJafri, M. Z.; Lim, H. S.

    2013-06-01

    This study encompasses columnar ozone modelling in the peninsular Malaysia. Data of eight atmospheric parameters [air surface temperature (AST), carbon monoxide (CO), methane (CH4), water vapour (H2Ovapour), skin surface temperature (SSKT), atmosphere temperature (AT), relative humidity (RH), and mean surface pressure (MSP)] data set, retrieved from NASA's Atmospheric Infrared Sounder (AIRS), for the entire period (2003-2008) was employed to develop models to predict the value of columnar ozone (O3) in study area. The combined method, which is based on using both multiple regressions combined with principal component analysis (PCA) modelling, was used to predict columnar ozone. This combined approach was utilized to improve the prediction accuracy of columnar ozone. Separate analysis was carried out for north east monsoon (NEM) and south west monsoon (SWM) seasons. The O3 was negatively correlated with CH4, H2Ovapour, RH, and MSP, whereas it was positively correlated with CO, AST, SSKT, and AT during both the NEM and SWM season periods. Multiple regression analysis was used to fit the columnar ozone data using the atmospheric parameter's variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to acquire subsets of the predictor variables to be comprised in the linear regression model of the atmospheric parameter's variables. It was found that the increase in columnar O3 value is associated with an increase in the values of AST, SSKT, AT, and CO and with a drop in the levels of CH4, H2Ovapour, RH, and MSP. The result of fitting the best models for the columnar O3 value using eight of the independent variables gave about the same values of the R (≈0.93) and R2 (≈0.86) for both the NEM and SWM seasons. The common variables that appeared in both regression equations were SSKT, CH4 and RH, and the principal precursor of the columnar O3 value in both the NEM and SWM seasons was SSKT.

  1. How Accurate Is the Prediction of Maximal Oxygen Uptake with Treadmill Testing?

    PubMed Central

    Wicks, John R.; Oldridge, Neil B.

    2016-01-01

    Background Cardiorespiratory fitness measured by treadmill testing has prognostic significance in determining mortality with cardiovascular and other chronic disease states. The accuracy of a recently developed method for estimating maximal oxygen uptake (VO2peak), the heart rate index (HRI), is dependent only on heart rate (HR) and was tested against oxygen uptake (VO2), either measured or predicted from conventional treadmill parameters (speed, incline, protocol time). Methods The HRI equation, METs = 6 x HRI– 5, where HRI = maximal HR/resting HR, provides a surrogate measure of VO2peak. Forty large scale treadmill studies were identified through a systematic search using MEDLINE, Google Scholar and Web of Science in which VO2peak was either measured (TM-VO2meas; n = 20) or predicted (TM-VO2pred; n = 20) based on treadmill parameters. All studies were required to have reported group mean data of both resting and maximal HRs for determination of HR index-derived oxygen uptake (HRI-VO2). Results The 20 studies with measured VO2 (TM-VO2meas), involved 11,477 participants (median 337) with a total of 105,044 participants (median 3,736) in the 20 studies with predicted VO2 (TM-VO2pred). A difference of only 0.4% was seen between mean (±SD) VO2peak for TM- VO2meas and HRI-VO2 (6.51±2.25 METs and 6.54±2.28, respectively; p = 0.84). In contrast, there was a highly significant 21.1% difference between mean (±SD) TM-VO2pred and HRI-VO2 (8.12±1.85 METs and 6.71±1.92, respectively; p<0.001). Conclusion Although mean TM-VO2meas and HRI-VO2 were almost identical, mean TM-VO2pred was more than 20% greater than mean HRI-VO2. PMID:27875547

  2. A Foundation for the Accurate Prediction of the Soft Error Vulnerability of Scientific Applications

    SciTech Connect

    Bronevetsky, G; de Supinski, B; Schulz, M

    2009-02-13

    Understanding the soft error vulnerability of supercomputer applications is critical as these systems are using ever larger numbers of devices that have decreasing feature sizes and, thus, increasing frequency of soft errors. As many large scale parallel scientific applications use BLAS and LAPACK linear algebra routines, the soft error vulnerability of these methods constitutes a large fraction of the applications overall vulnerability. This paper analyzes the vulnerability of these routines to soft errors by characterizing how their outputs are affected by injected errors and by evaluating several techniques for predicting how errors propagate from the input to the output of each routine. The resulting error profiles can be used to understand the fault vulnerability of full applications that use these routines.

  3. Fast and Accurate Accessible Surface Area Prediction Without a Sequence Profile.

    PubMed

    Faraggi, Eshel; Kouza, Maksim; Zhou, Yaoqi; Kloczkowski, Andrzej

    2017-01-01

    A fast accessible surface area (ASA) predictor is presented. In this new approach no residue mutation profiles generated by multiple sequence alignments are used as inputs. Instead, we use only single sequence information and global features such as single-residue and two-residue compositions of the chain. The resulting predictor is both highly more efficient than sequence alignment based predictors and of comparable accuracy to them. Introduction of the global inputs significantly helps achieve this comparable accuracy. The predictor, termed ASAquick, is found to perform similarly well for so-called easy and hard cases indicating generalizability and possible usability for de-novo protein structure prediction. The source code and a Linux executables for ASAquick are available from Research and Information Systems at http://mamiris.com and from the Battelle Center for Mathematical Medicine at http://mathmed.org .

  4. Sequence features accurately predict genome-wide MeCP2 binding in vivo

    PubMed Central

    Rube, H. Tomas; Lee, Wooje; Hejna, Miroslav; Chen, Huaiyang; Yasui, Dag H.; Hess, John F.; LaSalle, Janine M.; Song, Jun S.; Gong, Qizhi

    2016-01-01

    Methyl-CpG binding protein 2 (MeCP2) is critical for proper brain development and expressed at near-histone levels in neurons, but the mechanism of its genomic localization remains poorly understood. Using high-resolution MeCP2-binding data, we show that DNA sequence features alone can predict binding with 88% accuracy. Integrating MeCP2 binding and DNA methylation in a probabilistic graphical model, we demonstrate that previously reported genome-wide association with methylation is in part due to MeCP2's affinity to GC-rich chromatin, a result replicated using published data. Furthermore, MeCP2 co-localizes with nucleosomes. Finally, MeCP2 binding downstream of promoters correlates with increased expression in Mecp2-deficient neurons. PMID:27008915

  5. Simplified versus geometrically accurate models of forefoot anatomy to predict plantar pressures: A finite element study.

    PubMed

    Telfer, Scott; Erdemir, Ahmet; Woodburn, James; Cavanagh, Peter R

    2016-01-25

    Integration of patient-specific biomechanical measurements into the design of therapeutic footwear has been shown to improve clinical outcomes in patients with diabetic foot disease. The addition of numerical simulations intended to optimise intervention design may help to build on these advances, however at present the time and labour required to generate and run personalised models of foot anatomy restrict their routine clinical utility. In this study we developed second-generation personalised simple finite element (FE) models of the forefoot with varying geometric fidelities. Plantar pressure predictions from barefoot, shod, and shod with insole simulations using simplified models were compared to those obtained from CT-based FE models incorporating more detailed representations of bone and tissue geometry. A simplified model including representations of metatarsals based on simple geometric shapes, embedded within a contoured soft tissue block with outer geometry acquired from a 3D surface scan was found to provide pressure predictions closest to the more complex model, with mean differences of 13.3kPa (SD 13.4), 12.52kPa (SD 11.9) and 9.6kPa (SD 9.3) for barefoot, shod, and insole conditions respectively. The simplified model design could be produced in <1h compared to >3h in the case of the more detailed model, and solved on average 24% faster. FE models of the forefoot based on simplified geometric representations of the metatarsal bones and soft tissue surface geometry from 3D surface scans may potentially provide a simulation approach with improved clinical utility, however further validity testing around a range of therapeutic footwear types is required.

  6. Development of a method to accurately calculate the Dpb and quickly predict the strength of a chemical bond

    NASA Astrophysics Data System (ADS)

    Du, Xia; Zhao, Dong-Xia; Yang, Zhong-Zhi

    2013-02-01

    A new approach to characterize and measure bond strength has been developed. First, we propose a method to accurately calculate the potential acting on an electron in a molecule (PAEM) at the saddle point along a chemical bond in situ, denoted by Dpb. Then, a direct method to quickly evaluate bond strength is established. We choose some familiar molecules as models for benchmarking this method. As a practical application, the Dpb of base pairs in DNA along C-H and N-H bonds are obtained for the first time. All results show that C7-H of A-T and C8-H of G-C are the relatively weak bonds that are the injured positions in DNA damage. The significance of this work is twofold: (i) A method is developed to calculate Dpb of various sizable molecules in situ quickly and accurately; (ii) This work demonstrates the feasibility to quickly predict the bond strength in macromolecules.

  7. Fast and accurate prediction for aerodynamic forces and moments acting on satellites flying in Low-Earth Orbit

    NASA Astrophysics Data System (ADS)

    Jin, Xuhon; Huang, Fei; Hu, Pengju; Cheng, Xiaoli

    2016-11-01

    A fundamental prerequisite for satellites operating in a Low Earth Orbit (LEO) is the availability of fast and accurate prediction of non-gravitational aerodynamic forces, which is characterised by the free molecular flow regime. However, conventional computational methods like the analytical integral method and direct simulation Monte Carlo (DSMC) technique are found failing to deal with flow shadowing and multiple reflections or computationally expensive. This work develops a general computer program for the accurate calculation of aerodynamic forces in the free molecular flow regime using the test particle Monte Carlo (TPMC) method, and non-gravitational aerodynamic forces actiong on the Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite is calculated for different freestream conditions and gas-surface interaction models by the computer program.

  8. Reliable activation to novel stimuli predicts higher fluid intelligence.

    PubMed

    Euler, Matthew J; Weisend, Michael P; Jung, Rex E; Thoma, Robert J; Yeo, Ronald A

    2015-07-01

    The ability to reliably respond to stimuli could be an important biological determinant of differences in fluid intelligence (Gf). However, most electrophysiological studies of Gf employ event-related potential (ERP) measures that average brain activity over trials, and hence have limited power to quantify neural variability. Time-frequency analyses can capture cross-trial variation in the phase of neural activity, and thus can help address the importance of neural reliability to differences in Gf. This study recruited a community sample of healthy adults and measured inter-trial phase clustering (ITPC), total spectral power, and ERP amplitudes elicited by Repeated and Novel non-target stimuli during two visual oddball tasks. Condition effects, relations among the EEG measures, and relations with Gf were assessed. Early visual responses to Repeated stimuli elicited higher ITPC, yet only ITPC elicited by Novel stimuli was associated with Gf. Analyses of spectral power further highlighted the contribution of phase consistency to the findings. The link between Gf and reliable responding to changing inputs suggests an important role for flexible resource allocation in fluid intellectual skills.

  9. Simplified risk score models accurately predict the risk of major in-hospital complications following percutaneous coronary intervention.

    PubMed

    Resnic, F S; Ohno-Machado, L; Selwyn, A; Simon, D I; Popma, J J

    2001-07-01

    The objectives of this analysis were to develop and validate simplified risk score models for predicting the risk of major in-hospital complications after percutaneous coronary intervention (PCI) in the era of widespread stenting and use of glycoprotein IIb/IIIa antagonists. We then sought to compare the performance of these simplified models with those of full logistic regression and neural network models. From January 1, 1997 to December 31, 1999, data were collected on 4,264 consecutive interventional procedures at a single center. Risk score models were derived from multiple logistic regression models using the first 2,804 cases and then validated on the final 1,460 cases. The area under the receiver operating characteristic (ROC) curve for the risk score model that predicted death was 0.86 compared with 0.85 for the multiple logistic model and 0.83 for the neural network model (validation set). For the combined end points of death, myocardial infarction, or bypass surgery, the corresponding areas under the ROC curves were 0.74, 0.78, and 0.81, respectively. Previously identified risk factors were confirmed in this analysis. The use of stents was associated with a decreased risk of in-hospital complications. Thus, risk score models can accurately predict the risk of major in-hospital complications after PCI. Their discriminatory power is comparable to those of logistic models and neural network models. Accurate bedside risk stratification may be achieved with these simple models.

  10. Predicting phase behavior of mixtures of reservoir fluids with carbon dioxide

    SciTech Connect

    Grigg, R.B.; Lingane, P.J.

    1983-10-01

    The use of an equation of state to predict phase behavior during carbon dioxide flooding is well established. There is consensus that the characterization of the C fraction, the grouping of this fraction into ''pseudo components'', and the selection of interaction parameters are the most important variables. However, the literature is vague as to how to best select the pseudo components, especially when aiming for a few-component representation as for a field scale compositional simulation. Single-contact phase behavior is presented for mixtures of Ford Geraldine (Delaware), Maljamar (Grayburg), West Sussex (Shannon), and Reservoir D reservoir fluids, and of a synthetic oil C/C/C, with carbon dioxide. One can reproduce the phase behavior of these mixtures using 3-5 pseudo components and common interaction parameters. The critical properties of the pseudo components are calculated from detailed oil characterizations. Because the parameters are not further adjusted, this approach reduces the empiricism in fitting phase data and may result in a more accurate representation of the system as the composition of the oil changes during the approach to miscibility.

  11. Integrative subcellular proteomic analysis allows accurate prediction of human disease-causing genes

    PubMed Central

    Zhao, Li; Chen, Yiyun; Bajaj, Amol Onkar; Eblimit, Aiden; Xu, Mingchu; Soens, Zachry T.; Wang, Feng; Ge, Zhongqi; Jung, Sung Yun; He, Feng; Li, Yumei; Wensel, Theodore G.; Qin, Jun; Chen, Rui

    2016-01-01

    Proteomic profiling on subcellular fractions provides invaluable information regarding both protein abundance and subcellular localization. When integrated with other data sets, it can greatly enhance our ability to predict gene function genome-wide. In this study, we performed a comprehensive proteomic analysis on the light-sensing compartment of photoreceptors called the outer segment (OS). By comparing with the protein profile obtained from the retina tissue depleted of OS, an enrichment score for each protein is calculated to quantify protein subcellular localization, and 84% accuracy is achieved compared with experimental data. By integrating the protein OS enrichment score, the protein abundance, and the retina transcriptome, the probability of a gene playing an essential function in photoreceptor cells is derived with high specificity and sensitivity. As a result, a list of genes that will likely result in human retinal disease when mutated was identified and validated by previous literature and/or animal model studies. Therefore, this new methodology demonstrates the synergy of combining subcellular fractionation proteomics with other omics data sets and is generally applicable to other tissues and diseases. PMID:26912414

  12. Accurate prediction of the refractive index of polymers using first principles and data modeling

    NASA Astrophysics Data System (ADS)

    Afzal, Mohammad Atif Faiz; Cheng, Chong; Hachmann, Johannes

    Organic polymers with a high refractive index (RI) have recently attracted considerable interest due to their potential application in optical and optoelectronic devices. The ability to tailor the molecular structure of polymers is the key to increasing the accessible RI values. Our work concerns the creation of predictive in silico models for the optical properties of organic polymers, the screening of large-scale candidate libraries, and the mining of the resulting data to extract the underlying design principles that govern their performance. This work was set up to guide our experimentalist partners and allow them to target the most promising candidates. Our model is based on the Lorentz-Lorenz equation and thus includes the polarizability and number density values for each candidate. For the former, we performed a detailed benchmark study of different density functionals, basis sets, and the extrapolation scheme towards the polymer limit. For the number density we devised an exceedingly efficient machine learning approach to correlate the polymer structure and the packing fraction in the bulk material. We validated the proposed RI model against the experimentally known RI values of 112 polymers. We could show that the proposed combination of physical and data modeling is both successful and highly economical to characterize a wide range of organic polymers, which is a prerequisite for virtual high-throughput screening.

  13. The human skin/chick chorioallantoic membrane model accurately predicts the potency of cosmetic allergens.

    PubMed

    Slodownik, Dan; Grinberg, Igor; Spira, Ram M; Skornik, Yehuda; Goldstein, Ronald S

    2009-04-01

    The current standard method for predicting contact allergenicity is the murine local lymph node assay (LLNA). Public objection to the use of animals in testing of cosmetics makes the development of a system that does not use sentient animals highly desirable. The chorioallantoic membrane (CAM) of the chick egg has been extensively used for the growth of normal and transformed mammalian tissues. The CAM is not innervated, and embryos are sacrificed before the development of pain perception. The aim of this study was to determine whether the sensitization phase of contact dermatitis to known cosmetic allergens can be quantified using CAM-engrafted human skin and how these results compare with published EC3 data obtained with the LLNA. We studied six common molecules used in allergen testing and quantified migration of epidermal Langerhans cells (LC) as a measure of their allergic potency. All agents with known allergic potential induced statistically significant migration of LC. The data obtained correlated well with published data for these allergens generated using the LLNA test. The human-skin CAM model therefore has great potential as an inexpensive, non-radioactive, in vivo alternative to the LLNA, which does not require the use of sentient animals. In addition, this system has the advantage of testing the allergic response of human, rather than animal skin.

  14. Searching for Computational Strategies to Accurately Predict pKas of Large Phenolic Derivatives.

    PubMed

    Rebollar-Zepeda, Aida Mariana; Campos-Hernández, Tania; Ramírez-Silva, María Teresa; Rojas-Hernández, Alberto; Galano, Annia

    2011-08-09

    Twenty-two reaction schemes have been tested, within the cluster-continuum model including up to seven explicit water molecules. They have been used in conjunction with nine different methods, within the density functional theory and with second-order Møller-Plesset. The quality of the pKa predictions was found to be strongly dependent on the chosen scheme, while only moderately influenced by the method of calculation. We recommend the E1 reaction scheme [HA + OH(-) (3H2O) ↔ A(-) (H2O) + 3H2O], since it yields mean unsigned errors (MUE) lower than 1 unit of pKa for most of the tested functionals. The best pKa values obtained from this reaction scheme are those involving calculations with PBE0 (MUE = 0.77), TPSS (MUE = 0.82), BHandHLYP (MUE = 0.82), and B3LYP (MUE = 0.86) functionals. This scheme has the additional advantage, compared to the proton exchange method, which also gives very small values of MUE, of being experiment independent. It should be kept in mind, however, that these recommendations are valid within the cluster-continuum model, using the polarizable continuum model in conjunction with the united atom Hartree-Fock cavity and the strategy based on thermodynamic cycles. Changes in any of these aspects of the used methodology may lead to different outcomes.

  15. Towards Relaxing the Spherical Solar Radiation Pressure Model for Accurate Orbit Predictions

    NASA Astrophysics Data System (ADS)

    Lachut, M.; Bennett, J.

    2016-09-01

    The well-known cannonball model has been used ubiquitously to capture the effects of atmospheric drag and solar radiation pressure on satellites and/or space debris for decades. While it lends itself naturally to spherical objects, its validity in the case of non-spherical objects has been debated heavily for years throughout the space situational awareness community. One of the leading motivations to improve orbit predictions by relaxing the spherical assumption, is the ongoing demand for more robust and reliable conjunction assessments. In this study, we explore the orbit propagation of a flat plate in a near-GEO orbit under the influence of solar radiation pressure, using a Lambertian BRDF model. Consequently, this approach will account for the spin rate and orientation of the object, which is typically determined in practice using a light curve analysis. Here, simulations will be performed which systematically reduces the spin rate to demonstrate the point at which the spherical model no longer describes the orbital elements of the spinning plate. Further understanding of this threshold would provide insight into when a higher fidelity model should be used, thus resulting in improved orbit propagations. Therefore, the work presented here is of particular interest to organizations and researchers that maintain their own catalog, and/or perform conjunction analyses.

  16. Towards Accurate Prediction of Turbulent, Three-Dimensional, Recirculating Flows with the NCC

    NASA Technical Reports Server (NTRS)

    Iannetti, A.; Tacina, R.; Jeng, S.-M.; Cai, J.

    2001-01-01

    The National Combustion Code (NCC) was used to calculate the steady state, nonreacting flow field of a prototype Lean Direct Injection (LDI) swirler. This configuration used nine groups of eight holes drilled at a thirty-five degree angle to induce swirl. These nine groups created swirl in the same direction, or a corotating pattern. The static pressure drop across the holes was fixed at approximately four percent. Computations were performed on one quarter of the geometry, because the geometry is considered rotationally periodic every ninety degrees. The final computational grid used was approximately 2.26 million tetrahedral cells, and a cubic nonlinear k - epsilon model was used to model turbulence. The NCC results were then compared to time averaged Laser Doppler Velocimetry (LDV) data. The LDV measurements were performed on the full geometry, but four ninths of the geometry was measured. One-, two-, and three-dimensional representations of both flow fields are presented. The NCC computations compare both qualitatively and quantitatively well to the LDV data, but differences exist downstream. The comparison is encouraging, and shows that NCC can be used for future injector design studies. To improve the flow prediction accuracy of turbulent, three-dimensional, recirculating flow fields with the NCC, recommendations are given.

  17. A coupled phase-field and volume-of-fluid method for accurate representation of limiting water wave deformation

    NASA Astrophysics Data System (ADS)

    Liu, Yu; Yu, Xiping

    2016-09-01

    A coupled phase-field and volume-of-fluid method is developed to study the sensitive behavior of water waves during breaking. The THINC model is employed to solve the volume-of-fluid function over the entire domain covered by a relatively coarse grid while the phase-field model based on Allen-Cahn equation is applied over the fine grid. A special algorithm that takes into account the sharpness of the diffuse-interface is introduced to correlate the order parameter obtained on the fine grid and the volume-of-fluid function obtained on the coarse grid. The coupled model is then applied to the study of water waves generated by moving pressures on the free surface. The deformation process of the wave crest during the initial stage of breaking is discussed in details. It is shown that there is a significant variation of the free nappe developed at the front side of the wave crest as the wave steepness differs. It is of a plunging type at large wave steepness while of a spilling type at small wave steepness. The numerical results also indicate that breaking occurs later and the duration of breaking is shorter for waves of smaller steepness and vice versa. Neglecting the capillary effect leads to wave breaking with a sharper nappe and a more dynamic plunging process. The surface tension also has an effect to prevent the formation of a free nappe at the front side of the wave crest in some cases.

  18. The development and verification of a highly accurate collision prediction model for automated noncoplanar plan delivery

    SciTech Connect

    Yu, Victoria Y.; Tran, Angelia; Nguyen, Dan; Cao, Minsong; Ruan, Dan; Low, Daniel A.; Sheng, Ke

    2015-11-15

    attributed to phantom setup errors due to the slightly deformable and flexible phantom extremities. The estimated site-specific safety buffer distance with 0.001% probability of collision for (gantry-to-couch, gantry-to-phantom) was (1.23 cm, 3.35 cm), (1.01 cm, 3.99 cm), and (2.19 cm, 5.73 cm) for treatment to the head, lung, and prostate, respectively. Automated delivery to all three treatment sites was completed in 15 min and collision free using a digital Linac. Conclusions: An individualized collision prediction model for the purpose of noncoplanar beam delivery was developed and verified. With the model, the study has demonstrated the feasibility of predicting deliverable beams for an individual patient and then guiding fully automated noncoplanar treatment delivery. This work motivates development of clinical workflows and quality assurance procedures to allow more extensive use and automation of noncoplanar beam geometries.

  19. The development and verification of a highly accurate collision prediction model for automated noncoplanar plan delivery

    PubMed Central

    Yu, Victoria Y.; Tran, Angelia; Nguyen, Dan; Cao, Minsong; Ruan, Dan; Low, Daniel A.; Sheng, Ke

    2015-01-01

    attributed to phantom setup errors due to the slightly deformable and flexible phantom extremities. The estimated site-specific safety buffer distance with 0.001% probability of collision for (gantry-to-couch, gantry-to-phantom) was (1.23 cm, 3.35 cm), (1.01 cm, 3.99 cm), and (2.19 cm, 5.73 cm) for treatment to the head, lung, and prostate, respectively. Automated delivery to all three treatment sites was completed in 15 min and collision free using a digital Linac. Conclusions: An individualized collision prediction model for the purpose of noncoplanar beam delivery was developed and verified. With the model, the study has demonstrated the feasibility of predicting deliverable beams for an individual patient and then guiding fully automated noncoplanar treatment delivery. This work motivates development of clinical workflows and quality assurance procedures to allow more extensive use and automation of noncoplanar beam geometries. PMID:26520735

  20. How Accurate Are the Anthropometry Equations in in Iranian Military Men in Predicting Body Composition?

    PubMed Central

    Shakibaee, Abolfazl; Faghihzadeh, Soghrat; Alishiri, Gholam Hossein; Ebrahimpour, Zeynab; Faradjzadeh, Shahram; Sobhani, Vahid; Asgari, Alireza

    2015-01-01

    Background: The body composition varies according to different life styles (i.e. intake calories and caloric expenditure). Therefore, it is wise to record military personnel’s body composition periodically and encourage those who abide to the regulations. Different methods have been introduced for body composition assessment: invasive and non-invasive. Amongst them, the Jackson and Pollock equation is most popular. Objectives: The recommended anthropometric prediction equations for assessing men’s body composition were compared with dual-energy X-ray absorptiometry (DEXA) gold standard to develop a modified equation to assess body composition and obesity quantitatively among Iranian military men. Patients and Methods: A total of 101 military men aged 23 - 52 years old with a mean age of 35.5 years were recruited and evaluated in the present study (average height, 173.9 cm and weight, 81.5 kg). The body-fat percentages of subjects were assessed both with anthropometric assessment and DEXA scan. The data obtained from these two methods were then compared using multiple regression analysis. Results: The mean and standard deviation of body fat percentage of the DEXA assessment was 21.2 ± 4.3 and body fat percentage obtained from three Jackson and Pollock 3-, 4- and 7-site equations were 21.1 ± 5.8, 22.2 ± 6.0 and 20.9 ± 5.7, respectively. There was a strong correlation between these three equations and DEXA (R² = 0.98). Conclusions: The mean percentage of body fat obtained from the three equations of Jackson and Pollock was very close to that of body fat obtained from DEXA; however, we suggest using a modified Jackson-Pollock 3-site equation for volunteer military men because the 3-site equation analysis method is simpler and faster than other methods. PMID:26715964

  1. The predictive performance of infusion strategy nomogram based on a fluid kinetic model

    PubMed Central

    Choi, Byung Moon; Karm, Myung Hwan; Jung, Kyeo Woon; Yeo, Young Goo

    2015-01-01

    Background In a previous study, fluid kinetic models were applied to describe the volume expansion of the fluid space by administration of crystalloid and colloid solutions. However, validation of the models were not performed, it is necessary to evaluate the predictive performance of these models in another population. Methods Ninety five consenting patients undergoing elective spinal surgery under general anesthesia were enrolled in this study. These patients were randomly assigned to three fluid groups i.e. Hartmann's solution (H group, n = 28), Voluven® (V group, n = 34), and Hextend® (X group, n = 33). After completion of their preparation for surgery, the patients received a loading and maintenance volume of each fluid predetermined by nomograms based on fluid pharmacokinetic models during the 60-minute use of an infusion pump. Arterial samples were obtained at preset intervals of 0, 10, 20, and 30 min after fluid administration. The predictive performances of the fluid kinetic modes were evaluated using the fractional change of arterial hemoglobin. The relationship between blood-volume dilution and target dilution of body fluid space was also evaluated using regression analysis. Results A total of 194 hemoglobin measurements were used. The bias and inaccuracy of these models were -2.69 and 35.62 for the H group, -1.53 and 43.21 for the V group, and 9.05 and 41.82 for the X group, respectively. The blood-volume dilution and target dilution of body-fluid space showed a significant linear relationship in each group (P < 0.05). Conclusions Based on the inaccuracy of predictive performance, the fluid-kinetic model for Hartmann's solution showed better performance than the other models. PMID:25844130

  2. Deformation, Failure, and Fatigue Life of SiC/Ti-15-3 Laminates Accurately Predicted by MAC/GMC

    NASA Technical Reports Server (NTRS)

    Bednarcyk, Brett A.; Arnold, Steven M.

    2002-01-01

    NASA Glenn Research Center's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) (ref.1) has been extended to enable fully coupled macro-micro deformation, failure, and fatigue life predictions for advanced metal matrix, ceramic matrix, and polymer matrix composites. Because of the multiaxial nature of the code's underlying micromechanics model, GMC--which allows the incorporation of complex local inelastic constitutive models--MAC/GMC finds its most important application in metal matrix composites, like the SiC/Ti-15-3 composite examined here. Furthermore, since GMC predicts the microscale fields within each constituent of the composite material, submodels for local effects such as fiber breakage, interfacial debonding, and matrix fatigue damage can and have been built into MAC/GMC. The present application of MAC/GMC highlights the combination of these features, which has enabled the accurate modeling of the deformation, failure, and life of titanium matrix composites.

  3. Does a more precise chemical description of protein-ligand complexes lead to more accurate prediction of binding affinity?

    PubMed

    Ballester, Pedro J; Schreyer, Adrian; Blundell, Tom L

    2014-03-24

    Predicting the binding affinities of large sets of diverse molecules against a range of macromolecular targets is an extremely challenging task. The scoring functions that attempt such computational prediction are essential for exploiting and analyzing the outputs of docking, which is in turn an important tool in problems such as structure-based drug design. Classical scoring functions assume a predetermined theory-inspired functional form for the relationship between the variables that describe an experimentally determined or modeled structure of a protein-ligand complex and its binding affinity. The inherent problem of this approach is in the difficulty of explicitly modeling the various contributions of intermolecular interactions to binding affinity. New scoring functions based on machine-learning regression models, which are able to exploit effectively much larger amounts of experimental data and circumvent the need for a predetermined functional form, have already been shown to outperform a broad range of state-of-the-art scoring functions in a widely used benchmark. Here, we investigate the impact of the chemical description of the complex on the predictive power of the resulting scoring function using a systematic battery of numerical experiments. The latter resulted in the most accurate scoring function to date on the benchmark. Strikingly, we also found that a more precise chemical description of the protein-ligand complex does not generally lead to a more accurate prediction of binding affinity. We discuss four factors that may contribute to this result: modeling assumptions, codependence of representation and regression, data restricted to the bound state, and conformational heterogeneity in data.

  4. Easy-to-use, general, and accurate multi-Kinect calibration and its application to gait monitoring for fall prediction.

    PubMed

    Staranowicz, Aaron N; Ray, Christopher; Mariottini, Gian-Luca

    2015-01-01

    Falls are the most-common causes of unintentional injury and death in older adults. Many clinics, hospitals, and health-care providers are urgently seeking accurate, low-cost, and easy-to-use technology to predict falls before they happen, e.g., by monitoring the human walking pattern (or "gait"). Despite the wide popularity of Microsoft's Kinect and the plethora of solutions for gait monitoring, no strategy has been proposed to date to allow non-expert users to calibrate the cameras, which is essential to accurately fuse the body motion observed by each camera in a single frame of reference. In this paper, we present a novel multi-Kinect calibration algorithm that has advanced features when compared to existing methods: 1) is easy to use, 2) it can be used in any generic Kinect arrangement, and 3) it provides accurate calibration. Extensive real-world experiments have been conducted to validate our algorithm and to compare its performance against other multi-Kinect calibration approaches, especially to show the improved estimate of gait parameters. Finally, a MATLAB Toolbox has been made publicly available for the entire research community.

  5. Dynamic and Volumetric Variables Reliably Predict Fluid Responsiveness in a Porcine Model with Pleural Effusion

    PubMed Central

    Broch, Ole; Gruenewald, Matthias; Renner, Jochen; Meybohm, Patrick; Schöttler, Jan; Heß, Katharina; Steinfath, Markus; Bein, Berthold

    2013-01-01

    Background The ability of stroke volume variation (SVV), pulse pressure variation (PPV) and global end-diastolic volume (GEDV) for prediction of fluid responsiveness in presence of pleural effusion is unknown. The aim of the present study was to challenge the ability of SVV, PPV and GEDV to predict fluid responsiveness in a porcine model with pleural effusions. Methods Pigs were studied at baseline and after fluid loading with 8 ml kg−1 6% hydroxyethyl starch. After withdrawal of 8 ml kg−1 blood and induction of pleural effusion up to 50 ml kg−1 on either side, measurements at baseline and after fluid loading were repeated. Cardiac output, stroke volume, central venous pressure (CVP) and pulmonary occlusion pressure (PAOP) were obtained by pulmonary thermodilution, whereas GEDV was determined by transpulmonary thermodilution. SVV and PPV were monitored continuously by pulse contour analysis. Results Pleural effusion was associated with significant changes in lung compliance, peak airway pressure and stroke volume in both responders and non-responders. At baseline, SVV, PPV and GEDV reliably predicted fluid responsiveness (area under the curve 0.85 (p<0.001), 0.88 (p<0.001), 0.77 (p = 0.007). After induction of pleural effusion the ability of SVV, PPV and GEDV to predict fluid responsiveness was well preserved and also PAOP was predictive. Threshold values for SVV and PPV increased in presence of pleural effusion. Conclusions In this porcine model, bilateral pleural effusion did not affect the ability of SVV, PPV and GEDV to predict fluid responsiveness. PMID:23418546

  6. Pore Structure Model for Predicting Elastic Wavespeeds in Fluid-Saturated Sandstones

    NASA Astrophysics Data System (ADS)

    Zimmerman, R. W.; David, E. C.

    2011-12-01

    underpredict the rock stiffness and that, for ultrasonic measurements performed at high frequencies (~MHz), it is more accurate to use the results from effective medium theories, which implicitly assume that the fluid is trapped in the pores. Hence, we use the aspect ratio distribution inverted from dry data, but this time introducing fluid in the pores. For a good number of experimental data on sandstones, our predictions for the saturated velocities match well the experimental data. This validates the use of a spheroidal model for pores. The results are only very weakly dependent on the choice of the effective medium theory. We conclude that our method, which remain relatively simple, is a useful tool to extract the pore aspect ratio distribution, as well as predicting the saturated velocities for sandstones.

  7. A cross-race effect in metamemory: Predictions of face recognition are more accurate for members of our own race

    PubMed Central

    Hourihan, Kathleen L.; Benjamin, Aaron S.; Liu, Xiping

    2012-01-01

    The Cross-Race Effect (CRE) in face recognition is the well-replicated finding that people are better at recognizing faces from their own race, relative to other races. The CRE reveals systematic limitations on eyewitness identification accuracy and suggests that some caution is warranted in evaluating cross-race identification. The CRE is a problem because jurors value eyewitness identification highly in verdict decisions. In the present paper, we explore how accurate people are in predicting their ability to recognize own-race and other-race faces. Caucasian and Asian participants viewed photographs of Caucasian and Asian faces, and made immediate judgments of learning during study. An old/new recognition test replicated the CRE: both groups displayed superior discriminability of own-race faces, relative to other-race faces. Importantly, relative metamnemonic accuracy was also greater for own-race faces, indicating that the accuracy of predictions about face recognition is influenced by race. This result indicates another source of concern when eliciting or evaluating eyewitness identification: people are less accurate in judging whether they will or will not recognize a face when that face is of a different race than they are. This new result suggests that a witness’s claim of being likely to recognize a suspect from a lineup should be interpreted with caution when the suspect is of a different race than the witness. PMID:23162788

  8. A Weibull statistics-based lignocellulose saccharification model and a built-in parameter accurately predict lignocellulose hydrolysis performance.

    PubMed

    Wang, Mingyu; Han, Lijuan; Liu, Shasha; Zhao, Xuebing; Yang, Jinghua; Loh, Soh Kheang; Sun, Xiaomin; Zhang, Chenxi; Fang, Xu

    2015-09-01

    Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed.

  9. Shrinking the Psoriasis Assessment Gap: Early Gene-Expression Profiling Accurately Predicts Response to Long-Term Treatment.

    PubMed

    Correa da Rosa, Joel; Kim, Jaehwan; Tian, Suyan; Tomalin, Lewis E; Krueger, James G; Suárez-Fariñas, Mayte

    2017-02-01

    There is an "assessment gap" between the moment a patient's response to treatment is biologically determined and when a response can actually be determined clinically. Patients' biochemical profiles are a major determinant of clinical outcome for a given treatment. It is therefore feasible that molecular-level patient information could be used to decrease the assessment gap. Thanks to clinically accessible biopsy samples, high-quality molecular data for psoriasis patients are widely available. Psoriasis is therefore an excellent disease for testing the prospect of predicting treatment outcome from molecular data. Our study shows that gene-expression profiles of psoriasis skin lesions, taken in the first 4 weeks of treatment, can be used to accurately predict (>80% area under the receiver operating characteristic curve) the clinical endpoint at 12 weeks. This could decrease the psoriasis assessment gap by 2 months. We present two distinct prediction modes: a universal predictor, aimed at forecasting the efficacy of untested drugs, and specific predictors aimed at forecasting clinical response to treatment with four specific drugs: etanercept, ustekinumab, adalimumab, and methotrexate. We also develop two forms of prediction: one from detailed, platform-specific data and one from platform-independent, pathway-based data. We show that key biomarkers are associated with responses to drugs and doses and thus provide insight into the biology of pathogenesis reversion.

  10. Verification Benchmarks to Assess the Implementation of Computational Fluid Dynamics Based Hemolysis Prediction Models.

    PubMed

    Hariharan, Prasanna; D'Souza, Gavin; Horner, Marc; Malinauskas, Richard A; Myers, Matthew R

    2015-09-01

    As part of an ongoing effort to develop verification and validation (V&V) standards for using computational fluid dynamics (CFD) in the evaluation of medical devices, we have developed idealized flow-based verification benchmarks to assess the implementation of commonly cited power-law based hemolysis models in CFD. Verification process ensures that all governing equations are solved correctly and the model is free of user and numerical errors. To perform verification for power-law based hemolysis modeling, analytical solutions for the Eulerian power-law blood damage model (which estimates hemolysis index (HI) as a function of shear stress and exposure time) were obtained for Couette and inclined Couette flow models, and for Newtonian and non-Newtonian pipe flow models. Subsequently, CFD simulations of fluid flow and HI were performed using Eulerian and three different Lagrangian-based hemolysis models and compared with the analytical solutions. For all the geometries, the blood damage results from the Eulerian-based CFD simulations matched the Eulerian analytical solutions within ∼1%, which indicates successful implementation of the Eulerian hemolysis model. Agreement between the Lagrangian and Eulerian models depended upon the choice of the hemolysis power-law constants. For the commonly used values of power-law constants (α  = 1.9-2.42 and β  = 0.65-0.80), in the absence of flow acceleration, most of the Lagrangian models matched the Eulerian results within 5%. In the presence of flow acceleration (inclined Couette flow), moderate differences (∼10%) were observed between the Lagrangian and Eulerian models. This difference increased to greater than 100% as the beta exponent decreased. These simplified flow problems can be used as standard benchmarks for verifying the implementation of blood damage predictive models in commercial and open-source CFD codes. The current study only used power-law model as an illustrative example to emphasize the need

  11. Prediction of critical heat flux in water-cooled plasma facing components using computational fluid dynamics.

    SciTech Connect

    Bullock, James H.; Youchison, Dennis Lee; Ulrickson, Michael Andrew

    2010-11-01

    Several commercial computational fluid dynamics (CFD) codes now have the capability to analyze Eulerian two-phase flow using the Rohsenow nucleate boiling model. Analysis of boiling due to one-sided heating in plasma facing components (pfcs) is now receiving attention during the design of water-cooled first wall panels for ITER that may encounter heat fluxes as high as 5 MW/m2. Empirical thermalhydraulic design correlations developed for long fission reactor channels are not reliable when applied to pfcs because fully developed flow conditions seldom exist. Star-CCM+ is one of the commercial CFD codes that can model two-phase flows. Like others, it implements the RPI model for nucleate boiling, but it also seamlessly transitions to a volume-of-fluid model for film boiling. By benchmarking the results of our 3d models against recent experiments on critical heat flux for both smooth rectangular channels and hypervapotrons, we determined the six unique input parameters that accurately characterize the boiling physics for ITER flow conditions under a wide range of absorbed heat flux. We can now exploit this capability to predict the onset of critical heat flux in these components. In addition, the results clearly illustrate the production and transport of vapor and its effect on heat transfer in pfcs from nucleate boiling through transition to film boiling. This article describes the boiling physics implemented in CCM+ and compares the computational results to the benchmark experiments carried out independently in the United States and Russia. Temperature distributions agreed to within 10 C for a wide range of heat fluxes from 3 MW/m2 to 10 MW/m2 and flow velocities from 1 m/s to 10 m/s in these devices. Although the analysis is incapable of capturing the stochastic nature of critical heat flux (i.e., time and location may depend on a local materials defect or turbulence phenomenon), it is highly reliable in determining the heat flux where boiling instabilities begin

  12. Stroke volume changes induced by a recruitment maneuver predict fluid responsiveness in patients with protective ventilation in the operating theater

    PubMed Central

    De Broca, Bruno; Garnier, Jeremie; Fischer, Marc-Olivier; Archange, Thomas; Marc, Julien; Abou-Arab, Osama; Dupont, Hervé; Lorne, Emmanuel; Guinot, Pierre-grégoire

    2016-01-01

    Abstract During abdominal surgery, the use of protective ventilation with a low tidal volume, positive expiratory pressure (PEEP) and recruitment maneuvers (RMs) may limit the applicability of dynamic preload indices. The objective of the present study was to establish whether or not the variation in stroke volume (SV) during an RM could predict fluid responsiveness. We prospectively included patients receiving protective ventilation (tidal volume: 6 mL kg−1, PEEP: 5–7 cmH2O; RMs). Hemodynamic variables, such as heart rate, arterial pressure, SV, cardiac output (CO), respiratory variation in SV (ΔrespSV) and pulse pressure (ΔrespPP), and the variation in SV (ΔrecSV) as well as pulse pressure (ΔrecPP) during an RM were measured at baseline, at the end of the RM, and after fluid expansion. Responders were defined as patients with an SV increase of at least 15% after infusion of 500 mL of crystalloid solution. Thirty-seven (62%) of the 60 included patients were responders. Responders and nonresponders differed significantly in terms of the median ΔrecSV (26% [19–37] vs 10% [4–12], respectively; P < 0.0001). A ΔrecSV value more than 16% predicted fluid responsiveness with an area under the receiver-operating characteristic curve (AU) of 0.95 (95% confidence interval [CI]: 0.91–0.99; P < 0.0001) and a narrow gray zone between 15% and 17%. The area under the curve values for ΔrecPP and ΔrespSV were, respectively, 0.81 (95%CI: 0.7–0.91; P = 0.0001) and 0.80 (95%CI: 0.70–0.94; P < 0.0001). ΔrespPP did not predict fluid responsiveness. During abdominal surgery with protective ventilation, a ΔrecSV value more than 16% accurately predicted fluid responsiveness and had a narrow gray zone (between 15% and 17%). ΔrecPP and ΔrespSV (but not ΔrespPP) were also predictive. PMID:27428237

  13. Predicting adsorption isotherms using a two-dimensional statistical associating fluid theory

    NASA Astrophysics Data System (ADS)

    Martinez, Alejandro; Castro, Martin; McCabe, Clare; Gil-Villegas, Alejandro

    2007-02-01

    A molecular thermodynamics approach is developed in order to describe the adsorption of fluids on solid surfaces. The new theory is based on the statistical associating fluid theory for potentials of variable range [A. Gil-Villegas et al., J. Chem. Phys. 106, 4168 (1997)] and uses a quasi-two-dimensional approximation to describe the properties of adsorbed fluids. The theory is tested against Gibbs ensemble Monte Carlo simulations and excellent agreement with the theoretical predictions is achieved. Additionally the authors use the new approach to describe the adsorption isotherms for nitrogen and methane on dry activated carbon.

  14. Predicting adsorption isotherms using a two-dimensional statistical associating fluid theory.

    PubMed

    Martinez, Alejandro; Castro, Martin; McCabe, Clare; Gil-Villegas, Alejandro

    2007-02-21

    A molecular thermodynamics approach is developed in order to describe the adsorption of fluids on solid surfaces. The new theory is based on the statistical associating fluid theory for potentials of variable range [A. Gil-Villegas et al., J. Chem. Phys. 106, 4168 (1997)] and uses a quasi-two-dimensional approximation to describe the properties of adsorbed fluids. The theory is tested against Gibbs ensemble Monte Carlo simulations and excellent agreement with the theoretical predictions is achieved. Additionally the authors use the new approach to describe the adsorption isotherms for nitrogen and methane on dry activated carbon.

  15. Prediction of blood glucose using interstitial fluid extracted by ultrasound and vacuum

    NASA Astrophysics Data System (ADS)

    Li, Dachao; Yu, Haixia; Huang, Xian; Huang, Fuxiang; Hu, Xiaotang; Xu, Kexin

    2007-02-01

    Prediction of blood glucose using interstitial fluid extracted by ultrasound and vacuum is proposed by the paper. Low-frequency ultrasound with 55 KHz is applied for about 30 seconds to enhance the skin permeability to interstitial fluid by disrupting the stratum corneum lipid bilayers and then interstitial fluid is extracted out of skin successfully by 10in.Hg vacuum for 15 minutes. The glucose concentration in the interstitial fluid is measured by an instrument with immobilized enzyme sensor. And then a method of data analysis is set up to prediction the glucose concentration in the blood by the measurement of the glucose concentration in the interstitial fluid. At last, Clarke Error Grid analysis is performed to assess if the prediction accuracy could satisfy the requirements of clinical application. The whole method and experimental system above is set up in the article and the feasibility of this way for blood glucose detecting is primarily validated for clinical application with the requirements of bloodless, painless, continuous glucose monitoring. Additional a prototype of miniature diabetes monitoring device with the technique of surface plasma resonance to measure the glucose concentration in the interstitial fluid is also being developed.

  16. Computational fluid dynamic prediction of the residence time of a vortex separator applied to disinfection.

    PubMed

    Egarr, D; Faram, M G; O'Doherty, T; Phipps, D; Syred, N

    2005-01-01

    A Hydrodynamic Vortex Separator (HDVS) has been modelled using Computational Fluid Dynamics (CFD) in order to predict the residence time of the fluid at the overflow and underflow outlets. A technique which was developed for use in Heating, Ventilation and Air Conditioning (HVAC) was used to determine the residence time and the results have been compared with those determined experimentally. It is shown that in using CFD, it is possible to predict the mean residence time of the fluid and to study the response to a pulse injection of tracer. It is also shown that it is possible to apply these techniques to predict the mean survival rate of bacteria in a combined separation and disinfection process.

  17. Accurate prediction of polarised high order electrostatic interactions for hydrogen bonded complexes using the machine learning method kriging

    NASA Astrophysics Data System (ADS)

    Hughes, Timothy J.; Kandathil, Shaun M.; Popelier, Paul L. A.

    2015-02-01

    As intermolecular interactions such as the hydrogen bond are electrostatic in origin, rigorous treatment of this term within force field methodologies should be mandatory. We present a method able of accurately reproducing such interactions for seven van der Waals complexes. It uses atomic multipole moments up to hexadecupole moment mapped to the positions of the nuclear coordinates by the machine learning method kriging. Models were built at three levels of theory: HF/6-31G**, B3LYP/aug-cc-pVDZ and M06-2X/aug-cc-pVDZ. The quality of the kriging models was measured by their ability to predict the electrostatic interaction energy between atoms in external test examples for which the true energies are known. At all levels of theory, >90% of test cases for small van der Waals complexes were predicted within 1 kJ mol-1, decreasing to 60-70% of test cases for larger base pair complexes. Models built on moments obtained at B3LYP and M06-2X level generally outperformed those at HF level. For all systems the individual interactions were predicted with a mean unsigned error of less than 1 kJ mol-1.

  18. Accurate prediction of polarised high order electrostatic interactions for hydrogen bonded complexes using the machine learning method kriging.

    PubMed

    Hughes, Timothy J; Kandathil, Shaun M; Popelier, Paul L A

    2015-02-05

    As intermolecular interactions such as the hydrogen bond are electrostatic in origin, rigorous treatment of this term within force field methodologies should be mandatory. We present a method able of accurately reproducing such interactions for seven van der Waals complexes. It uses atomic multipole moments up to hexadecupole moment mapped to the positions of the nuclear coordinates by the machine learning method kriging. Models were built at three levels of theory: HF/6-31G(**), B3LYP/aug-cc-pVDZ and M06-2X/aug-cc-pVDZ. The quality of the kriging models was measured by their ability to predict the electrostatic interaction energy between atoms in external test examples for which the true energies are known. At all levels of theory, >90% of test cases for small van der Waals complexes were predicted within 1 kJ mol(-1), decreasing to 60-70% of test cases for larger base pair complexes. Models built on moments obtained at B3LYP and M06-2X level generally outperformed those at HF level. For all systems the individual interactions were predicted with a mean unsigned error of less than 1 kJ mol(-1).

  19. Accurate prediction of cellular co-translational folding indicates proteins can switch from post- to co-translational folding

    PubMed Central

    Nissley, Daniel A.; Sharma, Ajeet K.; Ahmed, Nabeel; Friedrich, Ulrike A.; Kramer, Günter; Bukau, Bernd; O'Brien, Edward P.

    2016-01-01

    The rates at which domains fold and codons are translated are important factors in determining whether a nascent protein will co-translationally fold and function or misfold and malfunction. Here we develop a chemical kinetic model that calculates a protein domain's co-translational folding curve during synthesis using only the domain's bulk folding and unfolding rates and codon translation rates. We show that this model accurately predicts the course of co-translational folding measured in vivo for four different protein molecules. We then make predictions for a number of different proteins in yeast and find that synonymous codon substitutions, which change translation-elongation rates, can switch some protein domains from folding post-translationally to folding co-translationally—a result consistent with previous experimental studies. Our approach explains essential features of co-translational folding curves and predicts how varying the translation rate at different codon positions along a transcript's coding sequence affects this self-assembly process. PMID:26887592

  20. TIMP2•IGFBP7 biomarker panel accurately predicts acute kidney injury in high-risk surgical patients

    PubMed Central

    Gunnerson, Kyle J.; Shaw, Andrew D.; Chawla, Lakhmir S.; Bihorac, Azra; Al-Khafaji, Ali; Kashani, Kianoush; Lissauer, Matthew; Shi, Jing; Walker, Michael G.; Kellum, John A.

    2016-01-01

    BACKGROUND Acute kidney injury (AKI) is an important complication in surgical patients. Existing biomarkers and clinical prediction models underestimate the risk for developing AKI. We recently reported data from two trials of 728 and 408 critically ill adult patients in whom urinary TIMP2•IGFBP7 (NephroCheck, Astute Medical) was used to identify patients at risk of developing AKI. Here we report a preplanned analysis of surgical patients from both trials to assess whether urinary tissue inhibitor of metalloproteinase 2 (TIMP-2) and insulin-like growth factor–binding protein 7 (IGFBP7) accurately identify surgical patients at risk of developing AKI. STUDY DESIGN We enrolled adult surgical patients at risk for AKI who were admitted to one of 39 intensive care units across Europe and North America. The primary end point was moderate-severe AKI (equivalent to KDIGO [Kidney Disease Improving Global Outcomes] stages 2–3) within 12 hours of enrollment. Biomarker performance was assessed using the area under the receiver operating characteristic curve, integrated discrimination improvement, and category-free net reclassification improvement. RESULTS A total of 375 patients were included in the final analysis of whom 35 (9%) developed moderate-severe AKI within 12 hours. The area under the receiver operating characteristic curve for [TIMP-2]•[IGFBP7] alone was 0.84 (95% confidence interval, 0.76–0.90; p < 0.0001). Biomarker performance was robust in sensitivity analysis across predefined subgroups (urgency and type of surgery). CONCLUSION For postoperative surgical intensive care unit patients, a single urinary TIMP2•IGFBP7 test accurately identified patients at risk for developing AKI within the ensuing 12 hours and its inclusion in clinical risk prediction models significantly enhances their performance. LEVEL OF EVIDENCE Prognostic study, level I. PMID:26816218

  1. A novel fibrosis index comprising a non-cholesterol sterol accurately predicts HCV-related liver cirrhosis.

    PubMed

    Ydreborg, Magdalena; Lisovskaja, Vera; Lagging, Martin; Brehm Christensen, Peer; Langeland, Nina; Buhl, Mads Rauning; Pedersen, Court; Mørch, Kristine; Wejstål, Rune; Norkrans, Gunnar; Lindh, Magnus; Färkkilä, Martti; Westin, Johan

    2014-01-01

    Diagnosis of liver cirrhosis is essential in the management of chronic hepatitis C virus (HCV) infection. Liver biopsy is invasive and thus entails a risk of complications as well as a potential risk of sampling error. Therefore, non-invasive diagnostic tools are preferential. The aim of the present study was to create a model for accurate prediction of liver cirrhosis based on patient characteristics and biomarkers of liver fibrosis, including a panel of non-cholesterol sterols reflecting cholesterol synthesis and absorption and secretion. We evaluated variables with potential predictive significance for liver fibrosis in 278 patients originally included in a multicenter phase III treatment trial for chronic HCV infection. A stepwise multivariate logistic model selection was performed with liver cirrhosis, defined as Ishak fibrosis stage 5-6, as the outcome variable. A new index, referred to as Nordic Liver Index (NoLI) in the paper, was based on the model: Log-odds (predicting cirrhosis) = -12.17+ (age × 0.11) + (BMI (kg/m(2)) × 0.23) + (D7-lathosterol (μg/100 mg cholesterol)×(-0.013)) + (Platelet count (x10(9)/L) × (-0.018)) + (Prothrombin-INR × 3.69). The area under the ROC curve (AUROC) for prediction of cirrhosis was 0.91 (95% CI 0.86-0.96). The index was validated in a separate cohort of 83 patients and the AUROC for this cohort was similar (0.90; 95% CI: 0.82-0.98). In conclusion, the new index may complement other methods in diagnosing cirrhosis in patients with chronic HCV infection.

  2. Life span decrements in fluid intelligence and processing speed predict mortality risk.

    PubMed

    Aichele, Stephen; Rabbitt, Patrick; Ghisletta, Paolo

    2015-09-01

    We examined life span changes in 5 domains of cognitive performance as predictive of mortality risk. Data came from the Manchester Longitudinal Study of Cognition, a 20-plus-year investigation of 6,203 individuals ages 42-97 years. Cognitive domains were general crystallized intelligence, general fluid intelligence, verbal memory, visuospatial memory, and processing speed. Life span decrements were evident across these domains, controlling for baseline performance at age 70 and adjusting for retest effects. Survival analyses stratified by sex and conducted independently by cognitive domain showed that lower baseline performance levels in all domains-and larger life span decrements in general fluid intelligence and processing speed-were predictive of increased mortality risk for both women and men. Critically, analyses of the combined predictive power of cognitive performance variables showed that baseline levels of processing speed (in women) and general fluid intelligence (in men), and decrements in processing speed (in women and in men) and general fluid intelligence (in women), accounted for most of the explained variation in mortality risk. In light of recent evidence from brain-imaging studies, we speculate that cognitive abilities closely linked to cerebral white matter integrity (such as processing speed and general fluid intelligence) may represent particularly sensitive markers of mortality risk. In addition, we presume that greater complexity in cognition-survival associations observed in women (in analyses incorporating all cognitive predictors) may be a consequence of longer and more variable cognitive declines in women relative to men.

  3. Low Drain Fluid Amylase Predicts Absence of Pancreatic Fistula Following Pancreatectomy

    PubMed Central

    Lee, Christina W.; Pitt, Henry A.; Riall, Taylor S.; Ronnekleiv-Kelly, Sean S.; Israel, Jacqueline S.; Leverson, Glen E.; Parmar, Abhishek D.; Kilbane, E. Molly; Hall, Bruce L.

    2016-01-01

    Introduction Improvements in the ability to predict pancreatic fistula could enhance patient outcomes. Previous studies demonstrate that drain fluid amylase on postoperative day 1 (DFA1) is predictive of pancreatic fistula. We sought to assess the accuracy of DFA1 and to identify a reliable DFA1 threshold under which pancreatic fistula is ruled out. Methods Patients undergoing pancreatic resection from November 1, 2011 to December 31, 2012 were selected from the American College of Surgeons-National Surgical Quality Improvement Program Pancreatectomy Demonstration Project data-base. Pancreatic fistula was defined as drainage of amylase-rich fluid with drain continuation >7 days, percutaneous drainage, or reoperation for a pancreatic fluid collection. Univariate and multi-variable regression models were utilized to identify factors predictive of pancreatic fistula. Results DFA1 was recorded in 536 of 2,805 patients who underwent pancreatic resection, including pancreaticoduodenectomy (n=380), distal pancreatectomy (n=140), and enucleation (n=16). Pancreatic fistula occurred in 92/536 (17.2 %) patients. DFA1, increased body mass index, small pancreatic duct size, and soft texture were associated with fistula (p<0.05). A DFA1 cutoff value of <90 U/L demonstrated the highest negative predictive value of 98.2 %. Receiver operating characteristic (ROC) curve confirmed the predictive relationship of DFA1 and pancreatic fistula. Conclusion Low DFA1 predicts the absence of a pancreatic fistula. In patients with DFA1<90 U/L, early drain removal is advisable. PMID:25112411

  4. Estimating the state of a geophysical system with sparse observations: time delay methods to achieve accurate initial states for prediction

    NASA Astrophysics Data System (ADS)

    An, Zhe; Rey, Daniel; Ye, Jingxin; Abarbanel, Henry D. I.

    2017-01-01

    The problem of forecasting the behavior of a complex dynamical system through analysis of observational time-series data becomes difficult when the system expresses chaotic behavior and the measurements are sparse, in both space and/or time. Despite the fact that this situation is quite typical across many fields, including numerical weather prediction, the issue of whether the available observations are "sufficient" for generating successful forecasts is still not well understood. An analysis by Whartenby et al. (2013) found that in the context of the nonlinear shallow water equations on a β plane, standard nudging techniques require observing approximately 70 % of the full set of state variables. Here we examine the same system using a method introduced by Rey et al. (2014a), which generalizes standard nudging methods to utilize time delayed measurements. We show that in certain circumstances, it provides a sizable reduction in the number of observations required to construct accurate estimates and high-quality predictions. In particular, we find that this estimate of 70 % can be reduced to about 33 % using time delays, and even further if Lagrangian drifter locations are also used as measurements.

  5. Accurate X-Ray Spectral Predictions: An Advanced Self-Consistent-Field Approach Inspired by Many-Body Perturbation Theory

    NASA Astrophysics Data System (ADS)

    Liang, Yufeng; Vinson, John; Pemmaraju, Sri; Drisdell, Walter S.; Shirley, Eric L.; Prendergast, David

    2017-03-01

    Constrained-occupancy delta-self-consistent-field (Δ SCF ) methods and many-body perturbation theories (MBPT) are two strategies for obtaining electronic excitations from first principles. Using the two distinct approaches, we study the O 1 s core excitations that have become increasingly important for characterizing transition-metal oxides and understanding strong electronic correlation. The Δ SCF approach, in its current single-particle form, systematically underestimates the pre-edge intensity for chosen oxides, despite its success in weakly correlated systems. By contrast, the Bethe-Salpeter equation within MBPT predicts much better line shapes. This motivates one to reexamine the many-electron dynamics of x-ray excitations. We find that the single-particle Δ SCF approach can be rectified by explicitly calculating many-electron transition amplitudes, producing x-ray spectra in excellent agreement with experiments. This study paves the way to accurately predict x-ray near-edge spectral fingerprints for physics and materials science beyond the Bethe-Salpether equation.

  6. An accurate density functional theory for the vapor-liquid interface of associating chain molecules based on the statistical associating fluid theory for potentials of variable range

    NASA Astrophysics Data System (ADS)

    Gloor, Guy J.; Jackson, George; Blas, Felipe J.; del Río, Elvira Martín; de Miguel, Enrique

    2004-12-01

    A Helmholtz free energy density functional is developed to describe the vapor-liquid interface of associating chain molecules. The functional is based on the statistical associating fluid theory with attractive potentials of variable range (SAFT-VR) for the homogenous fluid [A. Gil-Villegas, A. Galindo, P. J. Whitehead, S. J. Mills, G. Jackson, and A. N. Burgess, J. Chem. Phys. 106, 4168 (1997)]. A standard perturbative density functional theory (DFT) is constructed by partitioning the free energy density into a reference term (which incorporates all of the short-range interactions, and is treated locally) and an attractive perturbation (which incorporates the long-range dispersion interactions). In our previous work [F. J. Blas, E. Martı´n del Rı´o, E. de Miguel, and G. Jackson, Mol. Phys. 99, 1851 (2001); G. J. Gloor, F. J. Blas, E. Martı´n del Rı´o, E. de Miguel, and G. Jackson, Fluid Phase Equil. 194, 521 (2002)] we used a mean-field version of the theory (SAFT-HS) in which the pair correlations were neglected in the attractive term. This provides only a qualitative description of the vapor-liquid interface, due to the inadequate mean-field treatment of the vapor-liquid equilibria. Two different approaches are used to include the correlations in the attractive term: in the first, the free energy of the homogeneous fluid is partitioned such that the effect of correlations are incorporated in the local reference term; in the second, a density averaged correlation function is incorporated into the perturbative term in a similar way to that proposed by Toxvaerd [S. Toxvaerd, J. Chem. Phys. 64, 2863 (1976)]. The latter is found to provide the most accurate description of the vapor-liquid surface tension on comparison with new simulation data for a square-well fluid of variable range. The SAFT-VR DFT is used to examine the effect of molecular chain length and association on the surface tension. Different association schemes (dimerization, straight and

  7. Ventral striatal prediction error signaling is associated with dopamine synthesis capacity and fluid intelligence.

    PubMed

    Schlagenhauf, Florian; Rapp, Michael A; Huys, Quentin J M; Beck, Anne; Wüstenberg, Torsten; Deserno, Lorenz; Buchholz, Hans-Georg; Kalbitzer, Jan; Buchert, Ralph; Bauer, Michael; Kienast, Thorsten; Cumming, Paul; Plotkin, Michail; Kumakura, Yoshitaka; Grace, Anthony A; Dolan, Raymond J; Heinz, Andreas

    2013-06-01

    Fluid intelligence represents the capacity for flexible problem solving and rapid behavioral adaptation. Rewards drive flexible behavioral adaptation, in part via a teaching signal expressed as reward prediction errors in the ventral striatum, which has been associated with phasic dopamine release in animal studies. We examined a sample of 28 healthy male adults using multimodal imaging and biological parametric mapping with (1) functional magnetic resonance imaging during a reversal learning task and (2) in a subsample of 17 subjects also with positron emission tomography using 6-[(18) F]fluoro-L-DOPA to assess dopamine synthesis capacity. Fluid intelligence was measured using a battery of nine standard neuropsychological tests. Ventral striatal BOLD correlates of reward prediction errors were positively correlated with fluid intelligence and, in the right ventral striatum, also inversely correlated with dopamine synthesis capacity (FDOPA K inapp). When exploring aspects of fluid intelligence, we observed that prediction error signaling correlates with complex attention and reasoning. These findings indicate that individual differences in the capacity for flexible problem solving relate to ventral striatal activation during reward-related learning, which in turn proved to be inversely associated with ventral striatal dopamine synthesis capacity.

  8. Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance

    PubMed Central

    Hong, Ha; Solomon, Ethan A.; DiCarlo, James J.

    2015-01-01

    database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. PMID:26424887

  9. Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.

    PubMed

    Majaj, Najib J; Hong, Ha; Solomon, Ethan A; DiCarlo, James J

    2015-09-30

    database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior.

  10. Accurate ab initio predictions of ionization energies and heats of formation for the 2-propyl, phenyl, and benzyl radicals

    NASA Astrophysics Data System (ADS)

    Lau, K.-C.; Ng, C. Y.

    2006-01-01

    The ionization energies (IEs) for the 2-propyl (2-C3H7), phenyl (C6H5), and benzyl (C6H5CH2) radicals have been calculated by the wave-function-based ab initio CCSD(T)/CBS approach, which involves the approximation to the complete basis set (CBS) limit at the coupled cluster level with single and double excitations plus quasiperturbative triple excitation [CCSD(T)]. The zero-point vibrational energy correction, the core-valence electronic correction, and the scalar relativistic effect correction have been also made in these calculations. Although a precise IE value for the 2-C3H7 radical has not been directly determined before due to the poor Franck-Condon factor for the photoionization transition at the ionization threshold, the experimental value deduced indirectly using other known energetic data is found to be in good accord with the present CCSD(T)/CBS prediction. The comparison between the predicted value through the focal-point analysis and the highly precise experimental value for the IE(C6H5CH2) determined in the previous pulsed field ionization photoelectron (PFI-PE) study shows that the CCSD(T)/CBS method is capable of providing an accurate IE prediction for C6H5CH2, achieving an error limit of 35 meV. The benchmarking of the CCSD(T)/CBS IE(C6H5CH2) prediction suggests that the CCSD(T)/CBS IE(C6H5) prediction obtained here has a similar accuracy of 35 meV. Taking into account this error limit for the CCSD(T)/CBS prediction and the experimental uncertainty, the CCSD(T)/CBS IE(C6H5) value is also consistent with the IE(C6H5) reported in the previous HeI photoelectron measurement. Furthermore, the present study provides support for the conclusion that the CCSD(T)/CBS approach with high-level energy corrections can be used to provide reliable IE predictions for C3-C7 hydrocarbon radicals with an uncertainty of +/-35 meV. Employing the atomization scheme, we have also computed the 0 K (298 K) heats of formation in kJ/mol at the CCSD(T)/CBS level for 2-C3H7

  11. Brachial artery peak velocity variation to predict fluid responsiveness in mechanically ventilated patients

    PubMed Central

    2009-01-01

    Introduction Although several parameters have been proposed to predict the hemodynamic response to fluid expansion in critically ill patients, most of them are invasive or require the use of special monitoring devices. The aim of this study is to determine whether noninvasive evaluation of respiratory variation of brachial artery peak velocity flow measured using Doppler ultrasound could predict fluid responsiveness in mechanically ventilated patients. Methods We conducted a prospective clinical research in a 17-bed multidisciplinary ICU and included 38 mechanically ventilated patients for whom fluid administration was planned due to the presence of acute circulatory failure. Volume expansion (VE) was performed with 500 mL of a synthetic colloid. Patients were classified as responders if stroke volume index (SVi) increased ≥ 15% after VE. The respiratory variation in Vpeakbrach (ΔVpeakbrach) was calculated as the difference between maximum and minimum values of Vpeakbrach over a single respiratory cycle, divided by the mean of the two values and expressed as a percentage. Radial arterial pressure variation (ΔPPrad) and stroke volume variation measured using the FloTrac/Vigileo system (ΔSVVigileo), were also calculated. Results VE increased SVi by ≥ 15% in 19 patients (responders). At baseline, ΔVpeakbrach, ΔPPrad and ΔSVVigileo were significantly higher in responder than nonresponder patients [14 vs 8%; 18 vs. 5%; 13 vs 8%; P < 0.0001, respectively). A ΔVpeakbrach value >10% predicted fluid responsiveness with a sensitivity of 74% and a specificity of 95%. A ΔPPrad value >10% and a ΔSVVigileo >11% predicted volume responsiveness with a sensitivity of 95% and 79%, and a specificity of 95% and 89%, respectively. Conclusions Respiratory variations in brachial artery peak velocity could be a feasible tool for the noninvasive assessment of fluid responsiveness in patients with mechanical ventilatory support and acute circulatory failure. Trial Registration

  12. Molecular Dynamics in Mixed Solvents Reveals Protein-Ligand Interactions, Improves Docking, and Allows Accurate Binding Free Energy Predictions.

    PubMed

    Arcon, Juan Pablo; Defelipe, Lucas A; Modenutti, Carlos P; López, Elias D; Alvarez-Garcia, Daniel; Barril, Xavier; Turjanski, Adrián G; Martí, Marcelo A

    2017-03-31

    One of the most important biological processes at the molecular level is the formation of protein-ligand complexes. Therefore, determining their structure and underlying key interactions is of paramount relevance and has direct applications in drug development. Because of its low cost relative to its experimental sibling, molecular dynamics (MD) simulations in the presence of different solvent probes mimicking specific types of interactions have been increasingly used to analyze protein binding sites and reveal protein-ligand interaction hot spots. However, a systematic comparison of different probes and their real predictive power from a quantitative and thermodynamic point of view is still missing. In the present work, we have performed MD simulations of 18 different proteins in pure water as well as water mixtures of ethanol, acetamide, acetonitrile and methylammonium acetate, leading to a total of 5.4 μs simulation time. For each system, we determined the corresponding solvent sites, defined as space regions adjacent to the protein surface where the probability of finding a probe atom is higher than that in the bulk solvent. Finally, we compared the identified solvent sites with 121 different protein-ligand complexes and used them to perform molecular docking and ligand binding free energy estimates. Our results show that combining solely water and ethanol sites allows sampling over 70% of all possible protein-ligand interactions, especially those that coincide with ligand-based pharmacophoric points. Most important, we also show how the solvent sites can be used to significantly improve ligand docking in terms of both accuracy and precision, and that accurate predictions of ligand binding free energies, along with relative ranking of ligand affinity, can be performed.

  13. A Support Vector Machine model for the prediction of proteotypic peptides for accurate mass and time proteomics

    SciTech Connect

    Webb-Robertson, Bobbie-Jo M.; Cannon, William R.; Oehmen, Christopher S.; Shah, Anuj R.; Gurumoorthi, Vidhya; Lipton, Mary S.; Waters, Katrina M.

    2008-07-01

    Motivation: The standard approach to identifying peptides based on accurate mass and elution time (AMT) compares these profiles obtained from a high resolution mass spectrometer to a database of peptides previously identified from tandem mass spectrometry (MS/MS) studies. It would be advantageous, with respect to both accuracy and cost, to only search for those peptides that are detectable by MS (proteotypic). Results: We present a Support Vector Machine (SVM) model that uses a simple descriptor space based on 35 properties of amino acid content, charge, hydrophilicity, and polarity for the quantitative prediction of proteotypic peptides. Using three independently derived AMT databases (Shewanella oneidensis, Salmonella typhimurium, Yersinia pestis) for training and validation within and across species, the SVM resulted in an average accuracy measure of ~0.8 with a standard deviation of less than 0.025. Furthermore, we demonstrate that these results are achievable with a small set of 12 variables and can achieve high proteome coverage. Availability: http://omics.pnl.gov/software/STEPP.php

  14. Predicting dermal permeability of biocides in commercial cutting fluids using a LSER approach.

    PubMed

    Vijay, Vikrant; Yeatts, James L; Riviere, Jim E; Baynes, Ronald E

    2007-12-10

    The aim of this study is to predict dermal permeability of four phenolic biocides in four different formulations using a linear solvation energy relationship (LSER) approach, with a calibrated flow through diffusion cell system. Mathematical descriptors were determined in the laboratory, by mathematical computations, and by statistical methods. Infinite doses of 4 biocides and 25 probe chemicals in water, 17% methanol and 2 commercial metalworking fluids namely Astrocut-C and Tapfree 2 were applied to porcine skin flow through diffusion cells. The strength coefficients for the 25 probe compounds for each system were determined from multiple linear regression analysis and plugged into the Abraham's LSER equation to predict permeability values for biocides. Biocide permeability significantly decreased in methanol, Astrocut-C and Tapfree 2 when compared to water. The strength coefficients revealed that hydrophobicity played an important role in explaining the reduced permeability in vehicles compared to water. This finding is important for selection of biocides and cutting fluids formulation. The R(2) between experimental and predicted log Kp of probe solutes for water, methanol, Astrocut-C and Tapfree 2 were 0.70, 0.78, 0.89 and 0.84, respectively. In conclusion, the LSER approach adequately predicted the dermal permeability of four biocides in commercial cutting fluids and also shed light on the chemical interactions resulting in reduced permeability.

  15. Predicting the amount of intraperitoneal fluid accumulation by computed tomography and its clinical use in patients with perforated peptic ulcer.

    PubMed

    Ishiguro, Toru; Kumagai, Youichi; Baba, Hiroyuki; Tajima, Yusuke; Imaizumi, Hideko; Suzuki, Okihide; Kuwabara, Koki; Matsuzawa, Takeaki; Sobajima, Jun; Fukuchi, Minoru; Ishibashi, Keiichiro; Mochiki, Erito; Ishida, Hideyuki

    2014-01-01

    The correlation between the amount of peritoneal fluid and clinical parameters in patients with perforated peptic ulcer (PPU) has not been investigated. The authors' objective was to derive a reliable formula for determining the amount of peritoneal fluid in patients with PPU before surgery, and to evaluate the correlation between the estimated amount of peritoneal fluid and clinical parameters. We investigated 62 consecutive patients who underwent emergency surgery for PPU, and in whom prediction of the amount of accumulated intraperitoneal fluid was possible by computed tomography (CT) using the methods described by Oriuchi et al. We examined the relationship between the predicted amount of accumulated intraperitoneal fluid and that measured during surgery, and the relationship between the amount of fluid predicted preoperatively or measured during surgery and several clinical parameters. There was a significant positive correlation between the amount of fluid predicted by CT scan and that measured during surgery. When patients with gastric ulcer and duodenal ulcer were analyzed collectively, the predicted amount of intraperitoneal fluid and the amount measured during surgery were each associated with the period from onset until CT scan, perforation size, the Mannheim peritoneal index, and the severity of postoperative complications according to the Clavien-Dindo classification. Our present results suggest that the method of Oriuchi et al is useful for predicting the amount of accumulated intraperitoneal fluid in patients with PPU, and that this would be potentially helpful for treatment decision-making and estimating the severity of postoperative complications.

  16. Preserving drinking water quality in geotechnical operations: predicting the feedback between fluid injection, fluid flow, and contamination

    NASA Astrophysics Data System (ADS)

    Schilling, Frank R.

    2014-05-01

    Not only in densely populated areas the preservation of drinking water quality is of vital interest. On the other side, our modern economies request for a sustained energy supply and a secure storage of waste materials. As energy sources with a high security of supply, oil, natural gas, and geothermal energy cover ca. 60% of Europe's energy demand; together with coal more than 75% (IEA 2011). Besides geothermal energy, all of the resources have a high greenhouse gas footprint. All these production activities are related to fluid injection and/or fluid production. The same holds true for gas storage operations in porous reservoirs, to store natural gases, oil, or greenhouse gases. Different concerns are discussed in the public and geoscientific community to influence the drinking water quality: - wastewater discharges from field exploration, drilling, production, well treatment and completion - wastewater sequestration - gas storage - tight gas and tight oil production (including hydraulic fracturing) - Shale gas production (including hydraulic fracturing) - mine drainage This overview contribution focusses on strategies to systematically reduce the risk of water pollution in geotechnical operations of deep reservoirs. The principals will be exemplarily revealed for different geotechnical operations. - How to control hydraulic fracturing operations to reduce the risk of enhanced seismic activity and avoiding the connection of originally separated aquifers. The presented approach to quantitatively predict the impact of stimulation activities is based on petrophysical models taking the feedback of geomechanical processes and fluid flow in porous media, fissures and faults into account. The specific flow patterns in various rock types lead to distinguished differences in operational risk. - How can a proper planning of geotechnical operations reduce the involved risks. A systematic risk reduction strategy will be discussed. On selected samples the role of exploration

  17. High IFIT1 expression predicts improved clinical outcome, and IFIT1 along with MGMT more accurately predicts prognosis in newly diagnosed glioblastoma.

    PubMed

    Zhang, Jin-Feng; Chen, Yao; Lin, Guo-Shi; Zhang, Jian-Dong; Tang, Wen-Long; Huang, Jian-Huang; Chen, Jin-Shou; Wang, Xing-Fu; Lin, Zhi-Xiong

    2016-06-01

    Interferon-induced protein with tetratricopeptide repeat 1 (IFIT1) plays a key role in growth suppression and apoptosis promotion in cancer cells. Interferon was reported to induce the expression of IFIT1 and inhibit the expression of O-6-methylguanine-DNA methyltransferase (MGMT).This study aimed to investigate the expression of IFIT1, the correlation between IFIT1 and MGMT, and their impact on the clinical outcome in newly diagnosed glioblastoma. The expression of IFIT1 and MGMT and their correlation were investigated in the tumor tissues from 70 patients with newly diagnosed glioblastoma. The effects on progression-free survival and overall survival were evaluated. Of 70 cases, 57 (81.4%) tissue samples showed high expression of IFIT1 by immunostaining. The χ(2) test indicated that the expression of IFIT1 and MGMT was negatively correlated (r = -0.288, P = .016). Univariate and multivariate analyses confirmed high IFIT1 expression as a favorable prognostic indicator for progression-free survival (P = .005 and .017) and overall survival (P = .001 and .001), respectively. Patients with 2 favorable factors (high IFIT1 and low MGMT) had an improved prognosis as compared with others. The results demonstrated significantly increased expression of IFIT1 in newly diagnosed glioblastoma tissue. The negative correlation between IFIT1 and MGMT expression may be triggered by interferon. High IFIT1 can be a predictive biomarker of favorable clinical outcome, and IFIT1 along with MGMT more accurately predicts prognosis in newly diagnosed glioblastoma.

  18. 4D ERT-based calibration and prediction of biostimulant induced changes in fluid conductivity

    NASA Astrophysics Data System (ADS)

    Johnson, T. C.; Versteeg, R. J.; Day-Lewis, F. D.; Major, W. R.; Wright, K. E.

    2008-12-01

    In-situ bioremediation is an emerging and cost-effective method of removing organic contaminants from groundwater. The performance of bioremedial systems depends on the adequate delivery and distribution of biostimulants to contaminated zones. Monitoring the distribution of biostimulants using monitoring wells is expensive, time consuming, and provides inadequate information between sampling wells. We discuss a Hydrogeophysical Performance Monitoring System (HPMS) deployed to monitor bioremediation efforts at a TCE-contaminated Superfund site in Brandywine MD. The HPMS enables autonomous electrical geophysical data acquisition, processing, quality-assurance/quality-control, and inversion. Our objective is to demonstrate the feasibility and cost effectiveness of the HPMS to provide near real-time information on the spatiotemporal behavior of injected biostimulants. As a first step, we use time-lapse electrical resistivity tomography (ERT) to estimate changes in bulk conductivity caused by the injectate. We demonstrate how ERT-based bulk conductivity estimates can be calibrated with a small number of fluid conductivity measurements to produce ERT-based estimates of fluid conductivity. The calibration procedure addresses the spatially variable resolution of the ERT tomograms. To test the validity of these estimates, we used the ERT results to predict the fluid conductivity at tens of points prior to field sampling of fluid conductivity at the same points. The comparison of ERT-predicted vs. observed fluid conductivity displays a high degree of correlation (correlation coefficient over 0.8), and demonstrates the ability of the HPMS to estimate the four-dimensional (4D) distribution of fluid conductivity caused by the biostimulant injection.

  19. Fluid force predictions and experimental measurements for a magnetically levitated pediatric ventricular assist device.

    PubMed

    Throckmorton, Amy L; Untaroiu, Alexandrina; Lim, D Scott; Wood, Houston G; Allaire, Paul E

    2007-05-01

    The latest generation of artificial blood pumps incorporates the use of magnetic bearings to levitate the rotating component of the pump, the impeller. A magnetic suspension prevents the rotating impeller from contacting the internal surfaces of the pump and reduces regions of stagnant and high shear flow that surround fluid or mechanical bearings. Applying this third-generation technology, the Virginia Artificial Heart Institute has developed a ventricular assist device (VAD) to support infants and children. In consideration of the suspension design, the axial and radial fluid forces exerted on the rotor of the pediatric VAD were estimated using computational fluid dynamics (CFD) such that fluid perturbations would be counterbalanced. In addition, a prototype was built for experimental measurements of the axial fluid forces and estimations of the radial fluid forces during operation using a blood analog mixture. The axial fluid forces for a centered impeller position were found to range from 0.5 +/- 0.01 to 1 +/- 0.02 N in magnitude for 0.5 +/- 0.095 to 3.5 +/- 0.164 Lpm over rotational speeds of 6110 +/- 0.39 to 8030 +/- 0.57% rpm. The CFD predictions for the axial forces deviated from the experimental data by approximately 8.5% with a maximum difference of 18% at higher flow rates. Similarly for the off-centered impeller conditions, the maximum radial fluid force along the y-axis was found to be -0.57 +/- 0.17 N. The maximum cross-coupling force in the x direction was found to be larger with a maximum value of 0.74 +/- 0.22 N. This resulted in a 25-35% overestimate of the radial fluid force as compared to the CFD predictions; this overestimation will lead to a far more robust magnetic suspension design. The axial and radial forces estimated from the computational results are well within a range over which a compact magnetic suspension can compensate for flow perturbations. This study also serves as an effective and novel design methodology for blood pump

  20. A time accurate prediction of the viscous flow in a turbine stage including a rotor in motion

    NASA Astrophysics Data System (ADS)

    Shavalikul, Akamol

    accurate flow characteristics in the NGV domain and the rotor domain with less computational time and computer memory requirements. In contrast, the time accurate flow simulation can predict all unsteady flow characteristics occurring in the turbine stage, but with high computational resource requirements. (Abstract shortened by UMI.)

  1. Predicting multidimensional annular flows with a locally based two-fluid model

    SciTech Connect

    Antal, S.P. Edwards, D.P.; Strayer, T.D.

    1998-06-01

    Annular flows are a well utilized flow regime in many industrial applications, such as, heat exchangers, chemical reactors and industrial process equipment. These flows are characterized by a droplet laden vapor core with a thin, wavy liquid film wetting the walls. The prediction of annular flows has been largely confined to one-dimensional modeling which typically correlates the film thickness, droplet loading, and phase velocities by considering the average flow conditions and global mass and momentum balances to infer the flow topology. In this paper, a methodology to predict annular flows using a locally based two-fluid model of multiphase flow is presented. The purpose of this paper is to demonstrate a modeling approach for annular flows using a multifield, multidimensional two-fluid model and discuss the need for further work in this area.

  2. Geochemical tracers of dolomitizing fluids: A tool for predicting diagenetically controlled porosity on a reservoir scale

    SciTech Connect

    Major, R.P.; Lucia, F.J.; Ruppel, S.C. )

    1992-04-01

    Mole-per-mole replacement of calcite by dolomite yields an approximately 12% increase in porosity because dolomite is denser than calcite. However, data from the Pliocene-Pleistocene Seroe Domi Formation of Bonaire, Netherlands Antilles, demonstrate the dolomitization of these rocks resulted in porosity reduction. Rocks proximal to the source of dolomitizing fluids exhibit a greater amount of porosity occlusion than more distal rocks, indicating that dolomitization is a porosity-destroying process and that the degree of destruction can be calibrated to the flow path of dolomitizing fludis. Porosity observed in Bonaire dolomite varies over a distance of hundreds of meters along fluid-flow paths. In three examples of dolomites in which the pathways of dolomitizing fluids can be interpreted from the spatial geometry of dolomite compositions, the distances over which these changes occur are pertinent to interpreting diagenetically controlled reservoir heterogeneity in oil and gas fields. These include the Bonaire Dolomite, the Lower Ordovician Ranger Peak Formation of west Texas, and the Permian Clear Fork Formation of west Texas. Tracing dolomitizing fluid pathways may predict diagenetically controlled porosity trends in ancient rocks. Because porosity trends are associated with significant changes in petrophysical characteristics and fluid storage capacity at a between-well scale, this interpretation scheme may aid mapping of flow units in hydrocarbon reservoirs.

  3. [The value of brachial artery peak velocity variation during the Valsalva maneuver to predict fluid responsiveness].

    PubMed

    Sheng, L F; Yan, M; Zhang, F J; Ren, Q S; Yu, S H; Wu, M

    2017-02-14

    Objective: To evaluate whether brachial artery peak velocity variation(ΔVp) during a Valsalva maneuver(VM) could predict fluid responsiveness in spontaneously breathing patients. Methods: Ninety-six patients required radial artery catheter for elective surgery of Ningbo Yinzhou People's Hospital from December 2014 to June 2016 were enrolled. The brachial artery Doppler signal was recorded to measure the ΔVp while the VM was performed.Then doing the volume expansion (VE) , the cardiac output variation (ΔCO) before and after VE were measured.Pearson correlational analyses were conducted between ΔVp and ΔCO. Also the sensitivity and specificity of ΔVp were determined in predicting fluid responsiveness by the receiver operating characteristic (ROC) curve. Results: Patients were classified as group responders (n=24) and group non-responders (n=72). Responder was defined as cardiac output increased≥15% after VE.The ΔVp correlated well with ΔCO (r=0.792, P<0.01). The area under ROC curve was 0.903, with the ΔVp cut-off of 33%, the sensitivity of 87% and the specificity of 82%(P<0.01). Conclusion: Brachial artery peak velocity variation during a valsalva maneuver is a feasible method for predicting fluid responsiveness in spontaneously breathing patients.

  4. Predicting Flow Reversals in a Computational Fluid Dynamics Simulated Thermosyphon Using Data Assimilation

    PubMed Central

    Reagan, Andrew J.; Dubief, Yves; Dodds, Peter Sheridan; Danforth, Christopher M.

    2016-01-01

    A thermal convection loop is a annular chamber filled with water, heated on the bottom half and cooled on the top half. With sufficiently large forcing of heat, the direction of fluid flow in the loop oscillates chaotically, dynamics analogous to the Earth’s weather. As is the case for state-of-the-art weather models, we only observe the statistics over a small region of state space, making prediction difficult. To overcome this challenge, data assimilation (DA) methods, and specifically ensemble methods, use the computational model itself to estimate the uncertainty of the model to optimally combine these observations into an initial condition for predicting the future state. Here, we build and verify four distinct DA methods, and then, we perform a twin model experiment with the computational fluid dynamics simulation of the loop using the Ensemble Transform Kalman Filter (ETKF) to assimilate observations and predict flow reversals. We show that using adaptively shaped localized covariance outperforms static localized covariance with the ETKF, and allows for the use of less observations in predicting flow reversals. We also show that a Dynamic Mode Decomposition (DMD) of the temperature and velocity fields recovers the low dimensional system underlying reversals, finding specific modes which together are predictive of reversal direction. PMID:26849061

  5. Predicting Flow Reversals in a Computational Fluid Dynamics Simulated Thermosyphon Using Data Assimilation.

    PubMed

    Reagan, Andrew J; Dubief, Yves; Dodds, Peter Sheridan; Danforth, Christopher M

    2016-01-01

    A thermal convection loop is a annular chamber filled with water, heated on the bottom half and cooled on the top half. With sufficiently large forcing of heat, the direction of fluid flow in the loop oscillates chaotically, dynamics analogous to the Earth's weather. As is the case for state-of-the-art weather models, we only observe the statistics over a small region of state space, making prediction difficult. To overcome this challenge, data assimilation (DA) methods, and specifically ensemble methods, use the computational model itself to estimate the uncertainty of the model to optimally combine these observations into an initial condition for predicting the future state. Here, we build and verify four distinct DA methods, and then, we perform a twin model experiment with the computational fluid dynamics simulation of the loop using the Ensemble Transform Kalman Filter (ETKF) to assimilate observations and predict flow reversals. We show that using adaptively shaped localized covariance outperforms static localized covariance with the ETKF, and allows for the use of less observations in predicting flow reversals. We also show that a Dynamic Mode Decomposition (DMD) of the temperature and velocity fields recovers the low dimensional system underlying reversals, finding specific modes which together are predictive of reversal direction.

  6. Predicting Next Year's Resources--Short-Term Enrollment Forecasting for Accurate Budget Planning. AIR Forum Paper 1978.

    ERIC Educational Resources Information Center

    Salley, Charles D.

    Accurate enrollment forecasts are a prerequisite for reliable budget projections. This is because tuition payments make up a significant portion of a university's revenue, and anticipated revenue is the immediate constraint on current operating expenditures. Accurate forecasts are even more critical to revenue projections when a university's…

  7. Creation of an idealized nasopharynx geometry for accurate computational fluid dynamics simulations of nasal airflow in patient-specific models lacking the nasopharynx anatomy.

    PubMed

    A T Borojeni, Azadeh; Frank-Ito, Dennis O; Kimbell, Julia S; Rhee, John S; Garcia, Guilherme J M

    2016-08-15

    Virtual surgery planning based on computational fluid dynamics (CFD) simulations has the potential to improve surgical outcomes for nasal airway obstruction patients, but the benefits of virtual surgery planning must outweigh the risks of radiation exposure. Cone beam computed tomography (CT) scans represent an attractive imaging modality for virtual surgery planning due to lower costs and lower radiation exposures compared with conventional CT scans. However, to minimize the radiation exposure, the cone beam CT sinusitis protocol sometimes images only the nasal cavity, excluding the nasopharynx. The goal of this study was to develop an idealized nasopharynx geometry for accurate representation of outlet boundary conditions when the nasopharynx geometry is unavailable. Anatomically accurate models of the nasopharynx created from 30 CT scans were intersected with planes rotated at different angles to obtain an average geometry. Cross sections of the idealized nasopharynx were approximated as ellipses with cross-sectional areas and aspect ratios equal to the average in the actual patient-specific models. CFD simulations were performed to investigate whether nasal airflow patterns were affected when the CT-based nasopharynx was replaced by the idealized nasopharynx in 10 nasal airway obstruction patients. Despite the simple form of the idealized geometry, all biophysical variables (nasal resistance, airflow rate, and heat fluxes) were very similar in the idealized vs patient-specific models. The results confirmed the expectation that the nasopharynx geometry has a minimal effect in the nasal airflow patterns during inspiration. The idealized nasopharynx geometry will be useful in future CFD studies of nasal airflow based on medical images that exclude the nasopharynx.

  8. Pulse pressure variation to predict fluid responsiveness in spontaneously breathing patients: tidal vs. forced inspiratory breathing.

    PubMed

    Hong, D M; Lee, J M; Seo, J H; Min, J J; Jeon, Y; Bahk, J H

    2014-07-01

    We evaluated whether pulse pressure variation can predict fluid responsiveness in spontaneously breathing patients. Fifty-nine elective thoracic surgical patients were studied before induction of general anaesthesia. After volume expansion with hydroxyethyl starch 6 ml.kg(-1) , patients were defined as responders by a ≥ 15% increase in the cardiac index. Haemodynamic variables were measured before and after volume expansion and pulse pressure variations were calculated during tidal breathing and during forced inspiratory breathing. Median (IQR [range]) pulse pressure variation during forced inspiratory breathing was significantly higher in responders (n = 29) than in non-responders (n = 30) before volume expansion (18.2 (IQR 14.7-18.2 [9.3-31.3])% vs. 10.1 (IQR 8.3-12.6 [4.8-21.1])%, respectively, p < 0.001). The receiver-operating characteristic curve revealed that pulse pressure variation during forced inspiratory breathing could predict fluid responsiveness (area under the curve 0.910, p < 0.0001). Pulse pressure variation measured during forced inspiratory breathing can be used to guide fluid management in spontaneously breathing patients.

  9. Multiscale framework for predicting the coupling between deformation and fluid diffusion in porous rocks

    SciTech Connect

    Andrade, José E; Rudnicki, John W

    2012-12-14

    In this project, a predictive multiscale framework will be developed to simulate the strong coupling between solid deformations and fluid diffusion in porous rocks. We intend to improve macroscale modeling by incorporating fundamental physical modeling at the microscale in a computationally efficient way. This is an essential step toward further developments in multiphysics modeling, linking hydraulic, thermal, chemical, and geomechanical processes. This research will focus on areas where severe deformations are observed, such as deformation bands, where classical phenomenology breaks down. Multiscale geometric complexities and key geomechanical and hydraulic attributes of deformation bands (e.g., grain sliding and crushing, and pore collapse, causing interstitial fluid expulsion under saturated conditions), can significantly affect the constitutive response of the skeleton and the intrinsic permeability. Discrete mechanics (DEM) and the lattice Boltzmann method (LBM) will be used to probe the microstructure---under the current state---to extract the evolution of macroscopic constitutive parameters and the permeability tensor. These evolving macroscopic constitutive parameters are then directly used in continuum scale predictions using the finite element method (FEM) accounting for the coupled solid deformation and fluid diffusion. A particularly valuable aspect of this research is the thorough quantitative verification and validation program at different scales. The multiscale homogenization framework will be validated using X-ray computed tomography and 3D digital image correlation in situ at the Advanced Photon Source in Argonne National Laboratories. Also, the hierarchical computations at the specimen level will be validated using the aforementioned techniques in samples of sandstone undergoing deformation bands.

  10. Predicting total body water and extracellular fluid volumes from bioelectrical measurements of the human body.

    PubMed

    Johnson, H L; Virk, S P; Mayclin, P; Barbieri, T

    1992-10-01

    Two biological impedance analyzers, a 50 kHz (RJL) and 20-100 kHz (BMA) instrument, and a total body electrical conductivity (TOBEC) instrument were used to estimate total body water (TBW), extracellular (ECF) and intracellular (ICF) fluid volumes by repeated measurements of 16 normal men (19-38 years old) to assess which, if any, would provide the best estimates. At 3-week intervals, TBW was determined by deuterium dilution, ECF by bromide dilution, ICF by difference (TBW-ECF) and lean body mass by density. Prediction equations were obtained by regression; predicted values for the body fluid volumes were calculated and the results were statistically evaluated. Both the TOBEC and the BMA provided rapid and reliable estimates for body fluid volumes with standard errors of the estimates of about 0.5-1.1 L for ECF, 1.0-1.8 L for TBW, and 1.0-1.3 L for ICF. Part of the error was attributable to standard tracer-dilution methods.

  11. Population Synthesis in the Blue. IV. Accurate Model Predictions for Lick Indices and UBV Colors in Single Stellar Populations

    NASA Astrophysics Data System (ADS)

    Schiavon, Ricardo P.

    2007-07-01

    We present a new set of model predictions for 16 Lick absorption line indices from Hδ through Fe5335 and UBV colors for single stellar populations with ages ranging between 1 and 15 Gyr, [Fe/H] ranging from -1.3 to +0.3, and variable abundance ratios. The models are based on accurate stellar parameters for the Jones library stars and a new set of fitting functions describing the behavior of line indices as a function of effective temperature, surface gravity, and iron abundance. The abundances of several key elements in the library stars have been obtained from the literature in order to characterize the abundance pattern of the stellar library, thus allowing us to produce model predictions for any set of abundance ratios desired. We develop a method to estimate mean ages and abundances of iron, carbon, nitrogen, magnesium, and calcium that explores the sensitivity of the various indices modeled to those parameters. The models are compared to high-S/N data for Galactic clusters spanning the range of ages, metallicities, and abundance patterns of interest. Essentially all line indices are matched when the known cluster parameters are adopted as input. Comparing the models to high-quality data for galaxies in the nearby universe, we reproduce previous results regarding the enhancement of light elements and the spread in the mean luminosity-weighted ages of early-type galaxies. When the results from the analysis of blue and red indices are contrasted, we find good consistency in the [Fe/H] that is inferred from different Fe indices. Applying our method to estimate mean ages and abundances from stacked SDSS spectra of early-type galaxies brighter than L*, we find mean luminosity-weighed ages of the order of ~8 Gyr and iron abundances slightly below solar. Abundance ratios, [X/Fe], tend to be higher than solar and are positively correlated with galaxy luminosity. Of all elements, nitrogen is the more strongly correlated with galaxy luminosity, which seems to indicate

  12. Prediction of subsidence: Relationship between lowering of formation pressure and subsidence due to fluid withdrawal

    SciTech Connect

    Serebryakov, V.A.; Chilingar, G.V.

    2000-06-01

    Abnormally low formation pressures develop in petroleum reservoirs during intensive oil and gas production or in aquifers as a result of water extraction. A simple method is presented for calculating (predicting) the amount of compaction (and resulting subsidence) from the pressure drop in formation due to production, i.e., the increase in the effective pressure p{sub e} (p{sub e} = p{sub t} {minus} p{sub p}, where p{sub t} is the total overburden pressure and p{sub p} is the fluid or pore pressure). This work is based on extensive data collected in Russia. For example, large petroliferous areas in Western Siberia became marshlands as a result of fluid withdrawal. One should remember that sophisticated methods, such as FSMT (direct measurement of rock compaction by wireline tools in situ) and GPS (measurement of surface subsidence by satellite microwave Doppler techniques), are not yet available in many areas of the world.

  13. Do Skilled Elementary Teachers Hold Scientific Conceptions and Can They Accurately Predict the Type and Source of Students' Preconceptions of Electric Circuits?

    ERIC Educational Resources Information Center

    Lin, Jing-Wen

    2016-01-01

    Holding scientific conceptions and having the ability to accurately predict students' preconceptions are a prerequisite for science teachers to design appropriate constructivist-oriented learning experiences. This study explored the types and sources of students' preconceptions of electric circuits. First, 438 grade 3 (9 years old) students were…

  14. Single Trial EEG Patterns for the Prediction of Individual Differences in Fluid Intelligence

    PubMed Central

    Qazi, Emad-ul-Haq; Hussain, Muhammad; Aboalsamh, Hatim; Malik, Aamir Saeed; Amin, Hafeez Ullah; Bamatraf, Saeed

    2017-01-01

    Assessing a person's intelligence level is required in many situations, such as career counseling and clinical applications. EEG evoked potentials in oddball task and fluid intelligence score are correlated because both reflect the cognitive processing and attention. A system for prediction of an individual's fluid intelligence level using single trial Electroencephalography (EEG) signals has been proposed. For this purpose, we employed 2D and 3D contents and 34 subjects each for 2D and 3D, which were divided into low-ability (LA) and high-ability (HA) groups using Raven's Advanced Progressive Matrices (RAPM) test. Using visual oddball cognitive task, neural activity of each group was measured and analyzed over three midline electrodes (Fz, Cz, and Pz). To predict whether an individual belongs to LA or HA group, features were extracted using wavelet decomposition of EEG signals recorded in visual oddball task and support vector machine (SVM) was used as a classifier. Two different types of Haar wavelet transform based features have been extracted from the band (0.3 to 30 Hz) of EEG signals. Statistical wavelet features and wavelet coefficient features from the frequency bands 0.0–1.875 Hz (delta low) and 1.875–3.75 Hz (delta high), resulted in the 100 and 98% prediction accuracies, respectively, both for 2D and 3D contents. The analysis of these frequency bands showed clear difference between LA and HA groups. Further, discriminative values of the features have been validated using statistical significance tests and inter-class and intra-class variation analysis. Also, statistical test showed that there was no effect of 2D and 3D content on the assessment of fluid intelligence level. Comparisons with state-of-the-art techniques showed the superiority of the proposed system. PMID:28163676

  15. Draft tube pressure pulsation predictions in Francis turbines with transient Computational Fluid Dynamics methodology

    NASA Astrophysics Data System (ADS)

    Melot, M.; Nennemann, B.; Désy, N.

    2014-03-01

    An automatic Computational Fluid Dynamics (CFD) procedure that aims at predicting Draft Tube Pressure Pulsations (DTPP) at part load is presented. After a brief review of the physics involved, a description of the transient numerical setup is given. Next, the paper describes a post processing technique, namely the separation of pressure signals into synchronous, asynchronous and random pulsations. Combining the CFD calculation with the post-processing technique allows the quantification of the potential excitation of the mechanical system during the design phase. Consequently it provides the hydraulic designer with a tool to specifically target DTPP and thus helps in the development of more robust designs for part load operation of turbines.

  16. Serum and synovial fluid lipidomic profiles predict obesity-associated osteoarthritis, synovitis, and wound repair

    PubMed Central

    Wu, Chia-Lung; Kimmerling, Kelly A.; Little, Dianne; Guilak, Farshid

    2017-01-01

    High-fat diet-induced obesity is a major risk factor for osteoarthritis (OA) and diminished wound healing. The objective of this study was to determine the associations among serum and synovial fluid lipid levels with OA, synovitis, adipokine levels, and wound healing in a pre-clinical obese mouse model of OA. Male C57BL/6 J mice were fed either a low-fat (10% kcal) or one of three high-fat (HF, 60% kcal) diets rich in saturated fatty acids (SFAs), ω-6 or ω-3 polyunsaturated FAs (PUFAs). OA was induced by destabilization of the medial meniscus. Mice also received an ear punch for evaluating wound healing. Serum and synovial fluid were collected for lipidomic and adipokine analyses. We demonstrated that the serum levels of ω-3 PUFAs were negatively correlated with OA and wound size, but positively correlated with adiponectin levels. In contrast, most ω-6 PUFAs exhibited positive correlations with OA, impaired healing, and inflammatory adipokines. Interestingly, levels of pentadecylic acid (C15:0, an odd-chain SFA) and palmitoleic acid were inversely correlated with joint degradation. This study extends our understanding of the links of FAs with OA, synovitis and wound healing, and reports newly identified serum and synovial fluid FAs as predictive biomarkers of OA in obesity. PMID:28317846

  17. A comparison among five equations of state in predicting the inversion curve of some fluids

    NASA Astrophysics Data System (ADS)

    Haghighi, Behzad; Laee, Mohammad Reza; Seyed Matin, Naser

    2003-07-01

    Five equations of state, modified Peng-Robinson by Danesh et al. (MPR1), modified SRK equation of state by Mathias and Copeman (MSRK), Vdw11, Harmens-Knapp (HK) and modified Peng-Robinson equation of state by Ruzy (MPR2) were compared in predicting of the inversion curve of some fluids. This enable us to judge the accuracy of the results obtained from different equations of state. MSRK and HK equations of state give good prediction of the low-temperatures branch of the inversion curve and are closely matched with the experimental inversion curve. As a corollary to the present study, we have perceived that the agreement of the MPR2 and Vdw11 equations of state with the inversion curve are inadequate. We also calculated maximum inversion temperature and maximum inversion pressure for every component used in this work.

  18. Cerebrospinal Fluid α-Synuclein Predicts Cognitive Decline in Parkinson Disease Progression in the DATATOP Cohort

    PubMed Central

    Stewart, Tessandra; Liu, Changqin; Ginghina, Carmen; Cain, Kevin C.; Auinger, Peggy; Cholerton, Brenna; Shi, Min; Zhang, Jing

    2015-01-01

    Most patients with Parkinson disease (PD) develop both cognitive and motor impairment, and biomarkers for progression are urgently needed. Although α-synuclein is altered in cerebrospinal fluid of patients with PD, it is not known whether it predicts motor or cognitive deterioration. We examined clinical data and α-synuclein in >300 unmedicated patients with PD who participated in the deprenyl and tocopherol antioxidative therapy of parkinsonism (DATATOP) study, with up to 8 years of follow-up. Longitudinal measures of motor and cognitive function were studied before (phase 1) and during (phase 2) levodopa therapy; cerebrospinal fluid was collected at the beginning of each phase. Correlations and linear mixed models were used to assess α-synuclein association with disease severity and prediction of progression in the subsequent follow-up period. Despite decreasing α-synuclein (phase 1 to phase 2 change of −0.05 ± 0.21 log-transformed values, P < 0.001), no correlations were observed between α-synuclein and motor symptoms. Longitudinally, lower α-synuclein predicted better preservation of cognitive function by several measures [Selective Reminding Test total recall α-synuclein × time interaction effect coefficient, −0.12 (P = 0.037); delayed recall, −0.05 (P = 0.002); New Dot Test, −0.03 (P = 0.002)]. Thus, α-synuclein, although not clinically useful for motor progression, might predict cognitive decline, and future longitudinal studies should include this outcome for further validation. PMID:24625392

  19. Untargeted Metabolomic Analysis of Amniotic Fluid in the Prediction of Preterm Delivery and Bronchopulmonary Dysplasia

    PubMed Central

    Baraldi, Eugenio; Giordano, Giuseppe; Stocchero, Matteo; Moschino, Laura; Zaramella, Patrizia; Tran, Maria Rosa; Carraro, Silvia; Romero, Roberto; Gervasi, Maria Teresa

    2016-01-01

    Objective Bronchopulmonary dysplasia (BPD) is a serious complication associated with preterm birth. A growing body of evidence suggests a role for prenatal factors in its pathogenesis. Metabolomics allows simultaneous characterization of low molecular weight compounds and may provide a picture of such a complex condition. The aim of this study was to evaluate whether an unbiased metabolomic analysis of amniotic fluid (AF) can be used to investigate the risk of spontaneous preterm delivery (PTD) and BPD development in the offspring. Study design We conducted an exploratory study on 32 infants born from mothers who had undergone an amniocentesis between 21 and 28 gestational weeks because of spontaneous preterm labor with intact membranes. The AF samples underwent untargeted metabolomic analysis using mass spectrometry combined with ultra-performance liquid chromatography. The data obtained were analyzed using multivariate and univariate statistical data analysis tools. Results Orthogonally Constrained Projection to Latent Structures-Discriminant Analysis (oCPLS2-DA) excluded effects on data modelling of crucial clinical variables. oCPLS2-DA was able to find unique differences in select metabolites between term (n = 11) and preterm (n = 13) deliveries (negative ionization data set: R2 = 0.47, mean AUC ROC in prediction = 0.65; positive ionization data set: R2 = 0.47, mean AUC ROC in prediction = 0.70), and between PTD followed by the development of BPD (n = 10), and PTD without BPD (n = 11) (negative data set: R2 = 0.48, mean AUC ROC in prediction = 0.73; positive data set: R2 = 0.55, mean AUC ROC in prediction = 0.71). Conclusions This study suggests that amniotic fluid metabolic profiling may be promising for identifying spontaneous preterm birth and fetuses at risk for developing BPD. These findings support the hypothesis that some prenatal metabolic dysregulations may play a key role in the pathogenesis of PTD and the development of BPD. PMID:27755564

  20. Volume-Of-Fluid Simulation for Predicting Two-Phase Cooling in a Microchannel

    NASA Astrophysics Data System (ADS)

    Gorle, Catherine; Parida, Pritish; Houshmand, Farzad; Asheghi, Mehdi; Goodson, Kenneth

    2014-11-01

    Two-phase flow in microfluidic geometries has applications of increasing interest for next generation electronic and optoelectronic systems, telecommunications devices, and vehicle electronics. While there has been progress on comprehensive simulation of two-phase flows in compact geometries, validation of the results in different flow regimes should be considered to determine the predictive capabilities. In the present study we use the volume-of-fluid method to model the flow through a single micro channel with cross section 100 × 100 μm and length 10 mm. The channel inlet mass flux and the heat flux at the lower wall result in a subcooled boiling regime in the first 2.5 mm of the channel and a saturated flow regime further downstream. A conservation equation for the vapor volume fraction, and a single set of momentum and energy equations with volume-averaged fluid properties are solved. A reduced-physics phase change model represents the evaporation of the liquid and the corresponding heat loss, and the surface tension is accounted for by a source term in the momentum equation. The phase change model used requires the definition of a time relaxation parameter, which can significantly affect the solution since it determines the rate of evaporation. The results are compared to experimental data available from literature, focusing on the capability of the reduced-physics phase change model to predict the correct flow pattern, temperature profile and pressure drop.

  1. A comparison of molecular dynamics and diffuse interface model predictions of Lennard-Jones fluid evaporation

    SciTech Connect

    Barbante, Paolo; Frezzotti, Aldo; Gibelli, Livio

    2014-12-09

    The unsteady evaporation of a thin planar liquid film is studied by molecular dynamics simulations of Lennard-Jones fluid. The obtained results are compared with the predictions of a diffuse interface model in which capillary Korteweg contributions are added to hydrodynamic equations, in order to obtain a unified description of the liquid bulk, liquid-vapor interface and vapor region. Particular care has been taken in constructing a diffuse interface model matching the thermodynamic and transport properties of the Lennard-Jones fluid. The comparison of diffuse interface model and molecular dynamics results shows that, although good agreement is obtained in equilibrium conditions, remarkable deviations of diffuse interface model predictions from the reference molecular dynamics results are observed in the simulation of liquid film evaporation. It is also observed that molecular dynamics results are in good agreement with preliminary results obtained from a composite model which describes the liquid film by a standard hydrodynamic model and the vapor by the Boltzmann equation. The two mathematical model models are connected by kinetic boundary conditions assuming unit evaporation coefficient.

  2. PSSP-RFE: accurate prediction of protein structural class by recursive feature extraction from PSI-BLAST profile, physical-chemical property and functional annotations.

    PubMed

    Li, Liqi; Cui, Xiang; Yu, Sanjiu; Zhang, Yuan; Luo, Zhong; Yang, Hua; Zhou, Yue; Zheng, Xiaoqi

    2014-01-01

    Protein structure prediction is critical to functional annotation of the massively accumulated biological sequences, which prompts an imperative need for the development of high-throughput technologies. As a first and key step in protein structure prediction, protein structural class prediction becomes an increasingly challenging task. Amongst most homological-based approaches, the accuracies of protein structural class prediction are sufficiently high for high similarity datasets, but still far from being satisfactory for low similarity datasets, i.e., below 40% in pairwise sequence similarity. Therefore, we present a novel method for accurate and reliable protein structural class prediction for both high and low similarity datasets. This method is based on Support Vector Machine (SVM) in conjunction with integrated features from position-specific score matrix (PSSM), PROFEAT and Gene Ontology (GO). A feature selection approach, SVM-RFE, is also used to rank the integrated feature vectors through recursively removing the feature with the lowest ranking score. The definitive top features selected by SVM-RFE are input into the SVM engines to predict the structural class of a query protein. To validate our method, jackknife tests were applied to seven widely used benchmark datasets, reaching overall accuracies between 84.61% and 99.79%, which are significantly higher than those achieved by state-of-the-art tools. These results suggest that our method could serve as an accurate and cost-effective alternative to existing methods in protein structural classification, especially for low similarity datasets.

  3. Accurate and computationally efficient prediction of thermochemical properties of biomolecules using the generalized connectivity-based hierarchy.

    PubMed

    Sengupta, Arkajyoti; Ramabhadran, Raghunath O; Raghavachari, Krishnan

    2014-08-14

    In this study we have used the connectivity-based hierarchy (CBH) method to derive accurate heats of formation of a range of biomolecules, 18 amino acids and 10 barbituric acid/uracil derivatives. The hierarchy is based on the connectivity of the different atoms in a large molecule. It results in error-cancellation reaction schemes that are automated, general, and can be readily used for a broad range of organic molecules and biomolecules. Herein, we first locate stable conformational and tautomeric forms of these biomolecules using an accurate level of theory (viz. CCSD(T)/6-311++G(3df,2p)). Subsequently, the heats of formation of the amino acids are evaluated using the CBH-1 and CBH-2 schemes and routinely employed density functionals or wave function-based methods. The calculated heats of formation obtained herein using modest levels of theory and are in very good agreement with those obtained using more expensive W1-F12 and W2-F12 methods on amino acids and G3 results on barbituric acid derivatives. Overall, the present study (a) highlights the small effect of including multiple conformers in determining the heats of formation of biomolecules and (b) in concurrence with previous CBH studies, proves that use of the more effective error-cancelling isoatomic scheme (CBH-2) results in more accurate heats of formation with modestly sized basis sets along with common density functionals or wave function-based methods.

  4. Measurements and computational fluid dynamics predictions of the acoustic impedance of orifices

    NASA Astrophysics Data System (ADS)

    Su, J.; Rupp, J.; Garmory, A.; Carrotte, J. F.

    2015-09-01

    The response of orifices to incident acoustic waves, which is important for many engineering applications, is investigated with an approach combining both experimental measurements and numerical simulations. This paper presents experimental data on acoustic impedance of orifices, which is subsequently used for validation of a numerical technique developed for the purpose of predicting the acoustic response of a range of geometries with moderate computational cost. Measurements are conducted for orifices with length to diameter ratios, L/D, of 0.5, 5 and 10. The experimental data is obtained for a range of frequencies using a configuration in which a mean (or bias) flow passes from a duct through the test orifices before issuing into a plenum. Acoustic waves are provided by a sound generator on the upstream side of the orifices. Computational fluid dynamics (CFD) calculations of the same configuration have also been performed. These have been undertaken using an unsteady Reynolds averaged Navier-Stokes (URANS) approach with a pressure based compressible formulation with appropriate characteristic based boundary conditions to simulate the correct acoustic behaviour at the boundaries. The CFD predictions are in very good agreement with the experimental data, predicting the correct trend with both frequency and orifice L/D in a way not seen with analytical models. The CFD was also able to successfully predict a negative resistance, and hence a reflection coefficient greater than unity for the L / D = 0.5 case.

  5. Communication: Fine discretization of pair interactions and an approximate analytical strategy for predicting equilibrium behavior of complex fluids

    NASA Astrophysics Data System (ADS)

    Hollingshead, Kyle B.; Jain, Avni; Truskett, Thomas M.

    2013-10-01

    We study whether fine discretization (i.e., terracing) of continuous pair interactions, when used in combination with first-order mean-spherical approximation theory, can lead to a simple and general analytical strategy for predicting the equilibrium structure and thermodynamics of complex fluids. Specifically, we implement a version of this approach to predict how screened electrostatic repulsions, solute-mediated depletion attractions, or ramp-shaped repulsions modify the radial distribution function and the potential energy of reference hard-sphere fluids, and we compare the predictions to exact results from molecular simulations.

  6. Comparative proteomics of cerebrospinal fluid reveals a predictive model for differential diagnosis of pneumococcal, meningococcal, and enteroviral meningitis, and novel putative therapeutic targets

    PubMed Central

    2015-01-01

    Background Meningitis is the inflammation of the meninges in response to infection or chemical agents. While aseptic meningitis, most frequently caused by enteroviruses, is usually benign with a self-limiting course, bacterial meningitis remains associated with high morbidity and mortality rates, despite advances in antimicrobial therapy and intensive care. Fast and accurate differential diagnosis is crucial for assertive choice of the appropriate therapeutic approach for each form of meningitis. Methods We used 2D-PAGE and mass spectrometry to identify the cerebrospinal fluid proteome specifically related to the host response to pneumococcal, meningococcal, and enteroviral meningitis. The disease-specific proteome signatures were inspected by pathway analysis. Results Unique cerebrospinal fluid proteome signatures were found to the three aetiological forms of meningitis investigated, and a qualitative predictive model with four protein markers was developed for the differential diagnosis of these diseases. Nevertheless, pathway analysis of the disease-specific proteomes unveiled that Kallikrein-kinin system may play a crucial role in the pathophysiological mechanisms leading to brain damage in bacterial meningitis. Proteins taking part in this cellular process are proposed as putative targets to novel adjunctive therapies. Conclusions Comparative proteomics of cerebrospinal fluid disclosed candidate biomarkers, which were combined in a qualitative and sequential predictive model with potential to improve the differential diagnosis of pneumococcal, meningococcal and enteroviral meningitis. Moreover, we present the first evidence of the possible implication of Kallikrein-kinin system in the pathophysiology of bacterial meningitis. PMID:26040285

  7. Can the conventional sextant prostate biopsy accurately predict unilateral prostate cancer in low-risk, localized, prostate cancer?

    PubMed

    Mayes, Janice M; Mouraviev, Vladimir; Sun, Leon; Tsivian, Matvey; Madden, John F; Polascik, Thomas J

    2011-01-01

    We evaluate the reliability of routine sextant prostate biopsy to detect unilateral lesions. A total of 365 men with complete records including all clinical and pathologic variables who underwent a preoperative sextant biopsy and subsequent radical prostatectomy (RP) for clinically localized prostate cancer at our medical center between January 1996 and December 2006 were identified. When the sextant biopsy detects unilateral disease, according to RP results, the NPV is high (91%) with a low false negative rate (9%). However, the sextant biopsy has a PPV of 28% with a high false positive rate (72%). Therefore, a routine sextant prostate biopsy cannot provide reliable, accurate information about the unilaterality of tumor lesion(s).

  8. Is Demography Destiny? Application of Machine Learning Techniques to Accurately Predict Population Health Outcomes from a Minimal Demographic Dataset

    PubMed Central

    Luo, Wei; Nguyen, Thin; Nichols, Melanie; Tran, Truyen; Rana, Santu; Gupta, Sunil; Phung, Dinh; Venkatesh, Svetha; Allender, Steve

    2015-01-01

    For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease. PMID:25938675

  9. Is demography destiny? Application of machine learning techniques to accurately predict population health outcomes from a minimal demographic dataset.

    PubMed

    Luo, Wei; Nguyen, Thin; Nichols, Melanie; Tran, Truyen; Rana, Santu; Gupta, Sunil; Phung, Dinh; Venkatesh, Svetha; Allender, Steve

    2015-01-01

    For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.

  10. A Maximal Graded Exercise Test to Accurately Predict VO2max in 18-65-Year-Old Adults

    ERIC Educational Resources Information Center

    George, James D.; Bradshaw, Danielle I.; Hyde, Annette; Vehrs, Pat R.; Hager, Ronald L.; Yanowitz, Frank G.

    2007-01-01

    The purpose of this study was to develop an age-generalized regression model to predict maximal oxygen uptake (VO sub 2 max) based on a maximal treadmill graded exercise test (GXT; George, 1996). Participants (N = 100), ages 18-65 years, reached a maximal level of exertion (mean plus or minus standard deviation [SD]; maximal heart rate [HR sub…

  11. Accurate Prediction of Protein Functional Class From Sequence in the Mycobacterium Tuberculosis and Escherichia Coli Genomes Using Data Mining

    PubMed Central

    Karwath, Andreas; Clare, Amanda; Dehaspe, Luc

    2000-01-01

    The analysis of genomics data needs to become as automated as its generation. Here we present a novel data-mining approach to predicting protein functional class from sequence. This method is based on a combination of inductive logic programming clustering and rule learning. We demonstrate the effectiveness of this approach on the M. tuberculosis and E. coli genomes, and identify biologically interpretable rules which predict protein functional class from information only available from the sequence. These rules predict 65% of the ORFs with no assigned function in M. tuberculosis and 24% of those in E. coli, with an estimated accuracy of 60–80% (depending on the level of functional assignment). The rules are founded on a combination of detection of remote homology, convergent evolution and horizontal gene transfer. We identify rules that predict protein functional class even in the absence of detectable sequence or structural homology. These rules give insight into the evolutionary history of M. tuberculosis and E. coli. PMID:11119305

  12. Herbivore-induced plant volatiles accurately predict history of coexistence, diet breadth, and feeding mode of herbivores.

    PubMed

    Danner, Holger; Desurmont, Gaylord A; Cristescu, Simona M; van Dam, Nicole M

    2017-01-30

    Herbivore-induced plant volatiles (HIPVs) serve as specific cues to higher trophic levels. Novel, exotic herbivores entering native foodwebs may disrupt the infochemical network as a result of changes in HIPV profiles. Here, we analysed HIPV blends of native Brassica rapa plants infested with one of 10 herbivore species with different coexistence histories, diet breadths and feeding modes. Partial least squares (PLS) models were fitted to assess whether HIPV blends emitted by Dutch B. rapa differ between native and exotic herbivores, between specialists and generalists, and between piercing-sucking and chewing herbivores. These models were used to predict the status of two additional herbivores. We found that HIPV blends predicted the evolutionary history, diet breadth and feeding mode of the herbivore with an accuracy of 80% or higher. Based on the HIPVs, the PLS models reliably predicted that Trichoplusia ni and Spodoptera exigua are perceived as exotic, leaf-chewing generalists by Dutch B. rapa plants. These results indicate that there are consistent and predictable differences in HIPV blends depending on global herbivore characteristics, including coexistence history. Consequently, native organisms may be able to rapidly adapt to potentially disruptive effects of exotic herbivores on the infochemical network.

  13. Genomic Models of Short-Term Exposure Accurately Predict Long-Term Chemical Carcinogenicity and Identify Putative Mechanisms of Action

    PubMed Central

    Gusenleitner, Daniel; Auerbach, Scott S.; Melia, Tisha; Gómez, Harold F.; Sherr, David H.; Monti, Stefano

    2014-01-01

    Background Despite an overall decrease in incidence of and mortality from cancer, about 40% of Americans will be diagnosed with the disease in their lifetime, and around 20% will die of it. Current approaches to test carcinogenic chemicals adopt the 2-year rodent bioassay, which is costly and time-consuming. As a result, fewer than 2% of the chemicals on the market have actually been tested. However, evidence accumulated to date suggests that gene expression profiles from model organisms exposed to chemical compounds reflect underlying mechanisms of action, and that these toxicogenomic models could be used in the prediction of chemical carcinogenicity. Results In this study, we used a rat-based microarray dataset from the NTP DrugMatrix Database to test the ability of toxicogenomics to model carcinogenicity. We analyzed 1,221 gene-expression profiles obtained from rats treated with 127 well-characterized compounds, including genotoxic and non-genotoxic carcinogens. We built a classifier that predicts a chemical's carcinogenic potential with an AUC of 0.78, and validated it on an independent dataset from the Japanese Toxicogenomics Project consisting of 2,065 profiles from 72 compounds. Finally, we identified differentially expressed genes associated with chemical carcinogenesis, and developed novel data-driven approaches for the molecular characterization of the response to chemical stressors. Conclusion Here, we validate a toxicogenomic approach to predict carcinogenicity and provide strong evidence that, with a larger set of compounds, we should be able to improve the sensitivity and specificity of the predictions. We found that the prediction of carcinogenicity is tissue-dependent and that the results also confirm and expand upon previous studies implicating DNA damage, the peroxisome proliferator-activated receptor, the aryl hydrocarbon receptor, and regenerative pathology in the response to carcinogen exposure. PMID:25058030

  14. Predictive models for pressure-driven fluid infusions into brain parenchyma

    NASA Astrophysics Data System (ADS)

    Raghavan, Raghu; Brady, Martin

    2011-10-01

    Direct infusions into brain parenchyma of biological therapeutics for serious brain diseases have been, and are being, considered. However, individual brains, as well as distinct cytoarchitectural regions within brains, vary in their response to fluid flow and pressure. Further, the tissue responds dynamically to these stimuli, requiring a nonlinear treatment of equations that would describe fluid flow and drug transport in brain. We here report in detail on an individual-specific model and a comparison of its prediction with simulations for living porcine brains. Two critical features we introduced into our model—absent from previous ones, but requirements for any useful simulation—are the infusion-induced interstitial expansion and the backflow. These are significant determinants of the flow. Another feature of our treatment is the use of cross-property relations to obtain individual-specific parameters that are coefficients in the equations. The quantitative results are at least encouraging, showing a high fraction of overlap between the computed and measured volumes of distribution of a tracer molecule and are potentially clinically useful. Several improvements are called for; principally a treatment of the interstitial expansion more fundamentally based on poroelasticity and a better delineation of the diffusion tensor of a particle confined to the interstitial spaces.

  15. Can blood or follicular fluid levels of presepsin predict reproductive outcomes in ART; a preliminary study.

    PubMed

    Ovayolu, Ali; Özdamar, Özkan; Gün, İsmet; Arslanbuga, Cansev Yılmaz; Sofuoğlu, Kenan; Tunalı, Gülden; Topuz, Samet

    2015-01-01

    Many stages of COH protocols are considered to potentiate a state of systemic inflammation. The limit beyond which inflammation has negative impacts on the formation of conception and the reproductive outcomes are compromised still remains unclear. Presepsin is a novel biomarker for diagnosing systemic inflammation and sepsis. We aimed to investigate whether plasma and follicular fluid presepsin values on oocyte pick-up (OPU) day, embryo transfer (ET) day and pregnancy test (PT) days could predict reproductive outcomes during IVF treatment in women with UEI. Patients were assigned to two groups according to pregnancy test results; pregnant (Group 1) and non-pregnant (Group 2). From all patients included in the study, 2 cc of venous blood was sampled on the three days and follicular fluid (FF) was collected during oocyte retrieval. Plasma presepsin, CRP and WBC values and FF presepsin values were measured and compared between the 2 groups. There was no significant difference between FF and plasma presepsin levels on the OPU day (298±797.4 ve 352.9±657.1; P=0.701, respectively). Plasma WBC, CRP and presepsin levels on the OPU, ET and PT days and FF presepsin levels on OPU day were not different between the 2 groups. Plasma presepsin course on the separate 3 days were different between the groups.

  16. Metabolite Profile of Cervicovaginal Fluids from Early Pregnancy Is Not Predictive of Spontaneous Preterm Birth

    PubMed Central

    Thomas, Melinda M.; Sulek, Karolina; McKenzie, Elizabeth J.; Jones, Beatrix; Han, Ting-Li; Villas-Boas, Silas G.; Kenny, Louise C.; McCowan, Lesley M. E.; Baker, Philip N.

    2015-01-01

    In our study, we used a mass spectrometry-based metabolomic approach to search for biomarkers that may act as early indicators of spontaneous preterm birth (sPTB). Samples were selected as a nested case-control study from the Screening for Pregnancy Endpoints (SCOPE) biobank in Auckland, New Zealand. Cervicovaginal swabs were collected at 20 weeks from women who were originally assessed as being at low risk of sPTB. Samples were analysed using gas chromatography-mass spectrometry (GC-MS). Despite the low amount of biomass (16–23 mg), 112 compounds were detected. Statistical analysis showed no significant correlations with sPTB. Comparison of reported infection and plasma inflammatory markers from early pregnancy showed two inflammatory markers were correlated with reported infection, but no correlation with any compounds in the metabolite profile was observed. We hypothesise that the lack of biomarkers of sPTB in the cervicovaginal fluid metabolome is simply because it lacks such markers in early pregnancy. We propose alternative biofluids be investigated for markers of sPTB. Our results lead us to call for greater scrutiny of previously published metabolomic data relating to biomarkers of sPTB in cervicovaginal fluids, as the use of small, high risk, or late pregnancy cohorts may identify metabolite biomarkers that are irrelevant for predicting risk in normal populations. PMID:26610472

  17. Predictive models for pressure-driven fluid infusions into brain parenchyma

    PubMed Central

    Raghavan, Raghu; Brady, Martin

    2011-01-01

    Direct infusions into brain parenchyma of biological therapeutics for serious brain diseases have been, and are being, considered. However, individual brains, as well as distinct cytoarchitectural regions within brains, vary in their response to fluid flow and pressure. Further, the tissue responds dynamically to these stimuli, requiring a nonlinear treatment of equations that would describe fluid flow and drug transport in brain. We here report in detail on an individual–specific model and a comparison of its prediction with simulations for living porcine brains. Two critical features we introduced into our model — absent from previous ones, but requirements for any useful simulation — are the infusion-induced interstitial expansion and the backflow. These are significant determinants of the flow. Another feature of our treatment is the use of cross–property relations to obtain individual–specific parameters that are coefficients in the equations. The quantitative results are at least encouraging, showing a high fraction of overlap between the computed and measured volumes of distribution of a tracer molecule, and are potentially clinically useful. Several improvements are called for; principally a treatment of the interstitial expansion more fundamentally based on poroelasticity, and a better delineation of the diffusion tensor of a particle confined to the interstitial spaces. PMID:21891847

  18. Accurate and efficient prediction of fine-resolution hydrologic and carbon dynamic simulations from coarse-resolution models

    NASA Astrophysics Data System (ADS)

    Pau, George Shu Heng; Shen, Chaopeng; Riley, William J.; Liu, Yaning

    2016-02-01

    The topography, and the biotic and abiotic parameters are typically upscaled to make watershed-scale hydrologic-biogeochemical models computationally tractable. However, upscaling procedure can produce biases when nonlinear interactions between different processes are not fully captured at coarse resolutions. Here we applied the Proper Orthogonal Decomposition Mapping Method (PODMM) to downscale the field solutions from a coarse (7 km) resolution grid to a fine (220 m) resolution grid. PODMM trains a reduced-order model (ROM) with coarse-resolution and fine-resolution solutions, here obtained using PAWS+CLM, a quasi-3-D watershed processes model that has been validated for many temperate watersheds. Subsequent fine-resolution solutions were approximated based only on coarse-resolution solutions and the ROM. The approximation errors were efficiently quantified using an error estimator. By jointly estimating correlated variables and temporally varying the ROM parameters, we further reduced the approximation errors by up to 20%. We also improved the method's robustness by constructing multiple ROMs using different set of variables, and selecting the best approximation based on the error estimator. The ROMs produced accurate downscaling of soil moisture, latent heat flux, and net primary production with O(1000) reduction in computational cost. The subgrid distributions were also nearly indistinguishable from the ones obtained using the fine-resolution model. Compared to coarse-resolution solutions, biases in upscaled ROM solutions were reduced by up to 80%. This method has the potential to help address the long-standing spatial scaling problem in hydrology and enable long-time integration, parameter estimation, and stochastic uncertainty analysis while accurately representing the heterogeneities.

  19. How accurately can subject-specific finite element models predict strains and strength of human femora? Investigation using full-field measurements.

    PubMed

    Grassi, Lorenzo; Väänänen, Sami P; Ristinmaa, Matti; Jurvelin, Jukka S; Isaksson, Hanna

    2016-03-21

    Subject-specific finite element models have been proposed as a tool to improve fracture risk assessment in individuals. A thorough laboratory validation against experimental data is required before introducing such models in clinical practice. Results from digital image correlation can provide full-field strain distribution over the specimen surface during in vitro test, instead of at a few pre-defined locations as with strain gauges. The aim of this study was to validate finite element models of human femora against experimental data from three cadaver femora, both in terms of femoral strength and of the full-field strain distribution collected with digital image correlation. The results showed a high accuracy between predicted and measured principal strains (R(2)=0.93, RMSE=10%, 1600 validated data points per specimen). Femoral strength was predicted using a rate dependent material model with specific strain limit values for yield and failure. This provided an accurate prediction (<2% error) for two out of three specimens. In the third specimen, an accidental change in the boundary conditions occurred during the experiment, which compromised the femoral strength validation. The achieved strain accuracy was comparable to that obtained in state-of-the-art studies which validated their prediction accuracy against 10-16 strain gauge measurements. Fracture force was accurately predicted, with the predicted failure location being very close to the experimental fracture rim. Despite the low sample size and the single loading condition tested, the present combined numerical-experimental method showed that finite element models can predict femoral strength by providing a thorough description of the local bone mechanical response.

  20. SnowyOwl: accurate prediction of fungal genes by using RNA-Seq and homology information to select among ab initio models

    PubMed Central

    2014-01-01

    Background Locating the protein-coding genes in novel genomes is essential to understanding and exploiting the genomic information but it is still difficult to accurately predict all the genes. The recent availability of detailed information about transcript structure from high-throughput sequencing of messenger RNA (RNA-Seq) delineates many expressed genes and promises increased accuracy in gene prediction. Computational gene predictors have been intensively developed for and tested in well-studied animal genomes. Hundreds of fungal genomes are now or will soon be sequenced. The differences of fungal genomes from animal genomes and the phylogenetic sparsity of well-studied fungi call for gene-prediction tools tailored to them. Results SnowyOwl is a new gene prediction pipeline that uses RNA-Seq data to train and provide hints for the generation of Hidden Markov Model (HMM)-based gene predictions and to evaluate the resulting models. The pipeline has been developed and streamlined by comparing its predictions to manually curated gene models in three fungal genomes and validated against the high-quality gene annotation of Neurospora crassa; SnowyOwl predicted N. crassa genes with 83% sensitivity and 65% specificity. SnowyOwl gains sensitivity by repeatedly running the HMM gene predictor Augustus with varied input parameters and selectivity by choosing the models with best homology to known proteins and best agreement with the RNA-Seq data. Conclusions SnowyOwl efficiently uses RNA-Seq data to produce accurate gene models in both well-studied and novel fungal genomes. The source code for the SnowyOwl pipeline (in Python) and a web interface (in PHP) is freely available from http://sourceforge.net/projects/snowyowl/. PMID:24980894

  1. Accurate prediction of the electronic properties of low-dimensional graphene derivatives using a screened hybrid density functional.

    PubMed

    Barone, Veronica; Hod, Oded; Peralta, Juan E; Scuseria, Gustavo E

    2011-04-19

    Over the last several years, low-dimensional graphene derivatives, such as carbon nanotubes and graphene nanoribbons, have played a central role in the pursuit of a plausible carbon-based nanotechnology. Their electronic properties can be either metallic or semiconducting depending purely on morphology, but predicting their electronic behavior has proven challenging. The combination of experimental efforts with modeling of these nanometer-scale structures has been instrumental in gaining insight into their physical and chemical properties and the processes involved at these scales. Particularly, approximations based on density functional theory have emerged as a successful computational tool for predicting the electronic structure of these materials. In this Account, we review our efforts in modeling graphitic nanostructures from first principles with hybrid density functionals, namely the Heyd-Scuseria-Ernzerhof (HSE) screened exchange hybrid and the hybrid meta-generalized functional of Tao, Perdew, Staroverov, and Scuseria (TPSSh). These functionals provide a powerful tool for quantitatively studying structure-property relations and the effects of external perturbations such as chemical substitutions, electric and magnetic fields, and mechanical deformations on the electronic and magnetic properties of these low-dimensional carbon materials. We show how HSE and TPSSh successfully predict the electronic properties of these materials, providing a good description of their band structure and density of states, their work function, and their magnetic ordering in the cases in which magnetism arises. Moreover, these approximations are capable of successfully predicting optical transitions (first and higher order) in both metallic and semiconducting single-walled carbon nanotubes of various chiralities and diameters with impressive accuracy. This versatility includes the correct prediction of the trigonal warping splitting in metallic nanotubes. The results predicted

  2. An Electroacoustic Hearing Protector Simulator That Accurately Predicts Pressure Levels in the Ear Based on Standard Performance Metrics

    DTIC Science & Technology

    2013-08-01

    24 Figure 20. ABQ experiment showing five volunteers located 1.0 m from source in upper-left panel wearing...study (Royster et al.,1996) in which users self-fit hearing protectors (ANSI S12.6- 2008 method B: user fit) with no experimenter instruction gives an...values provided by the experimenters and simulator fits for the intact and modified muffs. Figure 22 (upper panel) shows the simulator prediction

  3. Knowledge-guided docking: accurate prospective prediction of bound configurations of novel ligands using Surflex-Dock

    NASA Astrophysics Data System (ADS)

    Cleves, Ann E.; Jain, Ajay N.

    2015-06-01

    Prediction of the bound configuration of small-molecule ligands that differ substantially from the cognate ligand of a protein co-crystal structure is much more challenging than re-docking the cognate ligand. Success rates for cross-docking in the range of 20-30 % are common. We present an approach that uses structural information known prior to a particular cutoff-date to make predictions on ligands whose bounds structures were determined later. The knowledge-guided docking protocol was tested on a set of ten protein targets using a total of 949 ligands. The benchmark data set, called PINC ("PINC Is Not Cognate"), is publicly available. Protein pocket similarity was used to choose representative structures for ensemble-docking. The docking protocol made use of known ligand poses prior to the cutoff-date, both to help guide the configurational search and to adjust the rank of predicted poses. Overall, the top-scoring pose family was correct over 60 % of the time, with the top-two pose families approaching a 75 % success rate. Correct poses among all those predicted were identified nearly 90 % of the time. The largest improvements came from the use of molecular similarity to improve ligand pose rankings and the strategy for identifying representative protein structures. With the exception of a single outlier target, the knowledge-guided docking protocol produced results matching the quality of cognate-ligand re-docking, but it did so on a very challenging temporally-segregated cross-docking benchmark.

  4. Knowledge-guided docking: accurate prospective prediction of bound configurations of novel ligands using Surflex-Dock.

    PubMed

    Cleves, Ann E; Jain, Ajay N

    2015-06-01

    Prediction of the bound configuration of small-molecule ligands that differ substantially from the cognate ligand of a protein co-crystal structure is much more challenging than re-docking the cognate ligand. Success rates for cross-docking in the range of 20-30 % are common. We present an approach that uses structural information known prior to a particular cutoff-date to make predictions on ligands whose bounds structures were determined later. The knowledge-guided docking protocol was tested on a set of ten protein targets using a total of 949 ligands. The benchmark data set, called PINC ("PINC Is Not Cognate"), is publicly available. Protein pocket similarity was used to choose representative structures for ensemble-docking. The docking protocol made use of known ligand poses prior to the cutoff-date, both to help guide the configurational search and to adjust the rank of predicted poses. Overall, the top-scoring pose family was correct over 60 % of the time, with the top-two pose families approaching a 75 % success rate. Correct poses among all those predicted were identified nearly 90 % of the time. The largest improvements came from the use of molecular similarity to improve ligand pose rankings and the strategy for identifying representative protein structures. With the exception of a single outlier target, the knowledge-guided docking protocol produced results matching the quality of cognate-ligand re-docking, but it did so on a very challenging temporally-segregated cross-docking benchmark.

  5. An Optimized Method for Accurate Fetal Sex Prediction and Sex Chromosome Aneuploidy Detection in Non-Invasive Prenatal Testing

    PubMed Central

    Li, Haibo; Ding, Jie; Wen, Ping; Zhang, Qin; Xiang, Jingjing; Li, Qiong; Xuan, Liming; Kong, Lingyin; Mao, Yan; Zhu, Yijun; Shen, Jingjing; Liang, Bo; Li, Hong

    2016-01-01

    Massively parallel sequencing (MPS) combined with bioinformatic analysis has been widely applied to detect fetal chromosomal aneuploidies such as trisomy 21, 18, 13 and sex chromosome aneuploidies (SCAs) by sequencing cell-free fetal DNA (cffDNA) from maternal plasma, so-called non-invasive prenatal testing (NIPT). However, many technical challenges, such as dependency on correct fetal sex prediction, large variations of chromosome Y measurement and high sensitivity to random reads mapping, may result in higher false negative rate (FNR) and false positive rate (FPR) in fetal sex prediction as well as in SCAs detection. Here, we developed an optimized method to improve the accuracy of the current method by filtering out randomly mapped reads in six specific regions of the Y chromosome. The method reduces the FNR and FPR of fetal sex prediction from nearly 1% to 0.01% and 0.06%, respectively and works robustly under conditions of low fetal DNA concentration (1%) in testing and simulation of 92 samples. The optimized method was further confirmed by large scale testing (1590 samples), suggesting that it is reliable and robust enough for clinical testing. PMID:27441628

  6. Fast and accurate multivariate Gaussian modeling of protein families: predicting residue contacts and protein-interaction partners.

    PubMed

    Baldassi, Carlo; Zamparo, Marco; Feinauer, Christoph; Procaccini, Andrea; Zecchina, Riccardo; Weigt, Martin; Pagnani, Andrea

    2014-01-01

    In the course of evolution, proteins show a remarkable conservation of their three-dimensional structure and their biological function, leading to strong evolutionary constraints on the sequence variability between homologous proteins. Our method aims at extracting such constraints from rapidly accumulating sequence data, and thereby at inferring protein structure and function from sequence information alone. Recently, global statistical inference methods (e.g. direct-coupling analysis, sparse inverse covariance estimation) have achieved a breakthrough towards this aim, and their predictions have been successfully implemented into tertiary and quaternary protein structure prediction methods. However, due to the discrete nature of the underlying variable (amino-acids), exact inference requires exponential time in the protein length, and efficient approximations are needed for practical applicability. Here we propose a very efficient multivariate Gaussian modeling approach as a variant of direct-coupling analysis: the discrete amino-acid variables are replaced by continuous Gaussian random variables. The resulting statistical inference problem is efficiently and exactly solvable. We show that the quality of inference is comparable or superior to the one achieved by mean-field approximations to inference with discrete variables, as done by direct-coupling analysis. This is true for (i) the prediction of residue-residue contacts in proteins, and (ii) the identification of protein-protein interaction partner in bacterial signal transduction. An implementation of our multivariate Gaussian approach is available at the website http://areeweb.polito.it/ricerca/cmp/code.

  7. A highly accurate protein structural class prediction approach using auto cross covariance transformation and recursive feature elimination.

    PubMed

    Li, Xiaowei; Liu, Taigang; Tao, Peiying; Wang, Chunhua; Chen, Lanming

    2015-12-01

    Structural class characterizes the overall folding type of a protein or its domain. Many methods have been proposed to improve the prediction accuracy of protein structural class in recent years, but it is still a challenge for the low-similarity sequences. In this study, we introduce a feature extraction technique based on auto cross covariance (ACC) transformation of position-specific score matrix (PSSM) to represent a protein sequence. Then support vector machine-recursive feature elimination (SVM-RFE) is adopted to select top K features according to their importance and these features are input to a support vector machine (SVM) to conduct the prediction. Performance evaluation of the proposed method is performed using the jackknife test on three low-similarity datasets, i.e., D640, 1189 and 25PDB. By means of this method, the overall accuracies of 97.2%, 96.2%, and 93.3% are achieved on these three datasets, which are higher than those of most existing methods. This suggests that the proposed method could serve as a very cost-effective tool for predicting protein structural class especially for low-similarity datasets.

  8. How many clinic BP readings are needed to predict cardiovascular events as accurately as ambulatory BP monitoring?

    PubMed

    Eguchi, K; Hoshide, S; Shimada, K; Kario, K

    2014-12-01

    We tested the hypothesis that multiple clinic blood pressure (BP) readings over an extended baseline period would be as predictive as ambulatory BP (ABP) for cardiovascular disease (CVD). Clinic and ABP monitoring were performed in 457 hypertensive patients at baseline. Clinic BP was measured monthly and the means of the first 3, 5 and 10 clinic BP readings were taken as the multiple clinic BP readings. The subjects were followed up, and stroke, HARD CVD, and ALL CVD events were determined as outcomes. In multivariate Cox regression analyses, ambulatory systolic BP (SBP) best predicted three outcomes independently of baseline and multiple clinic SBP readings. The mean of 10 clinic SBP readings predicted stroke (hazards ratio (HR)=1.39, 95% confidence interval (CI)=1.02-1.90, P=0.04) and ALL CVD (HR=1.41, 95% CI=1.13-1.74, P=0.002) independently of baseline clinic SBP. Clinic SBPs by three and five readings were not associated with any CVD events, except that clinic SBP by three readings was associated with ALL CVD (P=0.015). Besides ABP values, the mean of the first 10 clinic SBP values was a significant predictor of stroke and ALL CVD events. It is important to take more than several clinic BP readings early after the baseline period for the risk stratification of future CVD events.

  9. Dual X-ray absorptiometry accurately predicts carcass composition from live sheep and chemical composition of live and dead sheep.

    PubMed

    Pearce, K L; Ferguson, M; Gardner, G; Smith, N; Greef, J; Pethick, D W

    2009-01-01

    Fifty merino wethers (liveweight range from 44 to 81kg, average of 58.6kg) were lot fed for 42d and scanned through a dual X-ray absorptiometry (DXA) as both a live animal and whole carcass (carcass weight range from 15 to 32kg, average of 22.9kg) producing measures of total tissue, lean, fat and bone content. The carcasses were subsequently boned out into saleable cuts and the weights and yield of boned out muscle, fat and bone recorded. The relationship between chemical lean (protein+water) was highly correlated with DXA carcass lean (r(2)=0.90, RSD=0.674kg) and moderately with DXA live lean (r(2)=0.72, RSD=1.05kg). The relationship between the chemical fat was moderately correlated with DXA carcass fat (r(2)=0.86, RSD=0.42kg) and DXA live fat (r(2)=0.70, RSD=0.71kg). DXA carcass and live animal bone was not well correlated with chemical ash (both r(2)=0.38, RSD=0.3). DXA carcass lean was moderately well predicted from DXA live lean with the inclusion of bodyweight in the regression (r(2)=0.82, RSD=0.87kg). DXA carcass fat was well predicted from DXA live fat (r(2)=0.86, RSD=0.54kg). DXA carcass lean and DXA carcass fat with the inclusion of carcass weight in the regression significantly predicted boned out muscle (r(2)=0.97, RSD=0.32kg) and fat weight, respectively (r(2)=0.92, RSD=0.34kg). The use of DXA live lean and DXA live fat with the inclusion of bodyweight to predict boned out muscle (r(2)=0.83, RSD=0.75kg) and fat (r(2)=0.86, RSD=0.46kg) weight, respectively, was moderate. The use of DXA carcass and live lean and fat to predict boned out muscle and fat yield was not correlated as weight. The future for the DXA will exist in the determination of body composition in live animals and carcasses in research experiments but there is potential for the DXA to be used as an online carcass grading system.

  10. Empathic accuracy for happiness in the daily lives of older couples: Fluid cognitive performance predicts pattern accuracy among men.

    PubMed

    Hülür, Gizem; Hoppmann, Christiane A; Rauers, Antje; Schade, Hannah; Ram, Nilam; Gerstorf, Denis

    2016-08-01

    Correctly identifying other's emotional states is a central cognitive component of empathy. We examined the role of fluid cognitive performance for empathic accuracy for happiness in the daily lives of 86 older couples (mean relationship length = 45 years; mean age = 75 years) on up to 42 occasions over 7 consecutive days. Men performing better on the Digit Symbol test were more accurate in identifying ups and downs of their partner's happiness. A similar association was not found for women. We discuss the potential role of fluid cognitive performance and other individual, partner, and situation characteristics for empathic accuracy. (PsycINFO Database Record

  11. Network Biomarkers Constructed from Gene Expression and Protein-Protein Interaction Data for Accurate Prediction of Leukemia

    PubMed Central

    Yuan, Xuye; Chen, Jiajia; Lin, Yuxin; Li, Yin; Xu, Lihua; Chen, Luonan; Hua, Haiying; Shen, Bairong

    2017-01-01

    Leukemia is a leading cause of cancer deaths in the developed countries. Great efforts have been undertaken in search of diagnostic biomarkers of leukemia. However, leukemia is highly complex and heterogeneous, involving interaction among multiple molecular components. Individual molecules are not necessarily sensitive diagnostic indicators. Network biomarkers are considered to outperform individual molecules in disease characterization. We applied an integrative approach that identifies active network modules as putative biomarkers for leukemia diagnosis. We first reconstructed the leukemia-specific PPI network using protein-protein interactions from the Protein Interaction Network Analysis (PINA) and protein annotations from GeneGo. The network was further integrated with gene expression profiles to identify active modules with leukemia relevance. Finally, the candidate network-based biomarker was evaluated for the diagnosing performance. A network of 97 genes and 400 interactions was identified for accurate diagnosis of leukemia. Functional enrichment analysis revealed that the network biomarkers were enriched in pathways in cancer. The network biomarkers could discriminate leukemia samples from the normal controls more effectively than the known biomarkers. The network biomarkers provide a useful tool to diagnose leukemia and also aids in further understanding the molecular basis of leukemia. PMID:28243332

  12. IrisPlex: a sensitive DNA tool for accurate prediction of blue and brown eye colour in the absence of ancestry information.

    PubMed

    Walsh, Susan; Liu, Fan; Ballantyne, Kaye N; van Oven, Mannis; Lao, Oscar; Kayser, Manfred

    2011-06-01

    A new era of 'DNA intelligence' is arriving in forensic biology, due to the impending ability to predict externally visible characteristics (EVCs) from biological material such as those found at crime scenes. EVC prediction from forensic samples, or from body parts, is expected to help concentrate police investigations towards finding unknown individuals, at times when conventional DNA profiling fails to provide informative leads. Here we present a robust and sensitive tool, termed IrisPlex, for the accurate prediction of blue and brown eye colour from DNA in future forensic applications. We used the six currently most eye colour-informative single nucleotide polymorphisms (SNPs) that previously revealed prevalence-adjusted prediction accuracies of over 90% for blue and brown eye colour in 6168 Dutch Europeans. The single multiplex assay, based on SNaPshot chemistry and capillary electrophoresis, both widely used in forensic laboratories, displays high levels of genotyping sensitivity with complete profiles generated from as little as 31pg of DNA, approximately six human diploid cell equivalents. We also present a prediction model to correctly classify an individual's eye colour, via probability estimation solely based on DNA data, and illustrate the accuracy of the developed prediction test on 40 individuals from various geographic origins. Moreover, we obtained insights into the worldwide allele distribution of these six SNPs using the HGDP-CEPH samples of 51 populations. Eye colour prediction analyses from HGDP-CEPH samples provide evidence that the test and model presented here perform reliably without prior ancestry information, although future worldwide genotype and phenotype data shall confirm this notion. As our IrisPlex eye colour prediction test is capable of immediate implementation in forensic casework, it represents one of the first steps forward in the creation of a fully individualised EVC prediction system for future use in forensic DNA intelligence.

  13. Predicting Individual Action Switching in Covert and Continuous Interactive Tasks Using the Fluid Events Model

    PubMed Central

    Radvansky, Gabriel A.; D’Mello, Sidney K.; Abbott, Robert G.; Bixler, Robert E.

    2016-01-01

    The Fluid Events Model is aimed at predicting changes in the actions people take on a moment-by-moment basis. In contrast with other research on action selection, this work does not investigate why some course of action was selected, but rather the likelihood of discontinuing the current course of action and selecting another in the near future. This is done using both task-based and experience-based factors. Prior work evaluated this model in the context of trial-by-trial, independent, interactive events, such as choosing how to copy a figure of a line drawing. In this paper, we extend this model to more covert event experiences, such as reading narratives, as well as to continuous interactive events, such as playing a video game. To this end, the model was applied to existing data sets of reading time and event segmentation for written and picture stories. It was also applied to existing data sets of performance in a strategy board game, an aerial combat game, and a first person shooter game in which a participant’s current state was dependent on prior events. The results revealed that the model predicted behavior changes well, taking into account both the theoretically defined structure of the described events, as well as a person’s prior experience. Thus, theories of event cognition can benefit from efforts that take into account not only how events in the world are structured, but also how people experience those events. PMID:26858673

  14. Predicting Individual Action Switching in Covert and Continuous Interactive Tasks Using the Fluid Events Model.

    PubMed

    Radvansky, Gabriel A; D'Mello, Sidney K; Abbott, Robert G; Bixler, Robert E

    2016-01-01

    The Fluid Events Model is aimed at predicting changes in the actions people take on a moment-by-moment basis. In contrast with other research on action selection, this work does not investigate why some course of action was selected, but rather the likelihood of discontinuing the current course of action and selecting another in the near future. This is done using both task-based and experience-based factors. Prior work evaluated this model in the context of trial-by-trial, independent, interactive events, such as choosing how to copy a figure of a line drawing. In this paper, we extend this model to more covert event experiences, such as reading narratives, as well as to continuous interactive events, such as playing a video game. To this end, the model was applied to existing data sets of reading time and event segmentation for written and picture stories. It was also applied to existing data sets of performance in a strategy board game, an aerial combat game, and a first person shooter game in which a participant's current state was dependent on prior events. The results revealed that the model predicted behavior changes well, taking into account both the theoretically defined structure of the described events, as well as a person's prior experience. Thus, theories of event cognition can benefit from efforts that take into account not only how events in the world are structured, but also how people experience those events.

  15. Predicting individual action switching in covert and continuous interactive tasks using the fluid events model

    SciTech Connect

    Radvansky, Gabriel A.; D’Mello, Sidney K.; Abbott, Robert G.; Bixler, Robert E.

    2016-01-27

    The Fluid Events Model is aimed at predicting changes in the actions people take on a moment-by-moment basis. In contrast with other research on action selection, this work does not investigate why some course of action was selected, but rather the likelihood of discontinuing the current course of action and selecting another in the near future. This is done using both task-based and experience-based factors. Prior work evaluated this model in the context of trial-by-trial, independent, interactive events, such as choosing how to copy a figure of a line drawing. In this paper, we extend this model to more covert event experiences, such as reading narratives, as well as to continuous interactive events, such as playing a video game. To this end, the model was applied to existing data sets of reading time and event segmentation for written and picture stories. It was also applied to existing data sets of performance in a strategy board game, an aerial combat game, and a first person shooter game in which a participant’s current state was dependent on prior events. The results revealed that the model predicted behavior changes well, taking into account both the theoretically defined structure of the described events, as well as a person’s prior experience. Hence, theories of event cognition can benefit from efforts that take into account not only how events in the world are structured, but also how people experience those events.

  16. Predicting individual action switching in covert and continuous interactive tasks using the fluid events model

    DOE PAGES

    Radvansky, Gabriel A.; D’Mello, Sidney K.; Abbott, Robert G.; ...

    2016-01-27

    The Fluid Events Model is aimed at predicting changes in the actions people take on a moment-by-moment basis. In contrast with other research on action selection, this work does not investigate why some course of action was selected, but rather the likelihood of discontinuing the current course of action and selecting another in the near future. This is done using both task-based and experience-based factors. Prior work evaluated this model in the context of trial-by-trial, independent, interactive events, such as choosing how to copy a figure of a line drawing. In this paper, we extend this model to more covertmore » event experiences, such as reading narratives, as well as to continuous interactive events, such as playing a video game. To this end, the model was applied to existing data sets of reading time and event segmentation for written and picture stories. It was also applied to existing data sets of performance in a strategy board game, an aerial combat game, and a first person shooter game in which a participant’s current state was dependent on prior events. The results revealed that the model predicted behavior changes well, taking into account both the theoretically defined structure of the described events, as well as a person’s prior experience. Hence, theories of event cognition can benefit from efforts that take into account not only how events in the world are structured, but also how people experience those events.« less

  17. Performance of a municipal solid waste (MSW) incinerator predicted with a computational fluid dynamics (CFD) code

    SciTech Connect

    Anglesio, P.; Negreanu, G.P.

    1998-07-01

    The purpose of this paper is to investigate by the means of numerical simulation the performance of the MSW incinerator with of Vercelli (Italy). FLUENT, a finite-volumes commercial code for Fluid Dynamics has been used to predict the 3-D reacting flows (gaseous phase) within the incinerator geometry, in order to estimate if the three conditions settled by the Italian law (P.D. 915 / 82) are respected: (a) Flue gas temperature at the input of the secondary combustion chamber must exceed 950 C. (b) Oxygen concentration in the same section must exceed 6 %. (c) Residence time for the flue gas in the secondary combustion chamber must exceed 2 seconds. The model of the incinerator has been created using the software pre-processing facilities (wall, input, outlet and live cells), together with the set-up of boundary conditions. There are also imposed the combustion constants (stoichiometry, heat of combustion, air excess). The solving procedure transforms at the level of each live cell the partial derivative equations in algebraic equations, computing the velocities field, the temperatures, gases concentration, etc. These predicted values were compared with the design properties, and the conclusion was that the conditions (a), (b), (c), are respected in normal operation. The powerful graphic interface helps the user to visualize the magnitude of the computed parameters. These results may be successfully used for the design and operation improvements for MSW incinerators. This fact will substantially increase the efficiency, reduce pollutant emissions and optimize the plant overall performance.

  18. Genomic inference accurately predicts the timing and severity of a recent bottleneck in a non-model insect population

    PubMed Central

    McCoy, Rajiv C.; Garud, Nandita R.; Kelley, Joanna L.; Boggs, Carol L.; Petrov, Dmitri A.

    2015-01-01

    The analysis of molecular data from natural populations has allowed researchers to answer diverse ecological questions that were previously intractable. In particular, ecologists are often interested in the demographic history of populations, information that is rarely available from historical records. Methods have been developed to infer demographic parameters from genomic data, but it is not well understood how inferred parameters compare to true population history or depend on aspects of experimental design. Here we present and evaluate a method of SNP discovery using RNA-sequencing and demographic inference using the program δaδi, which uses a diffusion approximation to the allele frequency spectrum to fit demographic models. We test these methods in a population of the checkerspot butterfly Euphydryas gillettii. This population was intentionally introduced to Gothic, Colorado in 1977 and has since experienced extreme fluctuations including bottlenecks of fewer than 25 adults, as documented by nearly annual field surveys. Using RNA-sequencing of eight individuals from Colorado and eight individuals from a native population in Wyoming, we generate the first genomic resources for this system. While demographic inference is commonly used to examine ancient demography, our study demonstrates that our inexpensive, all-in-one approach to marker discovery and genotyping provides sufficient data to accurately infer the timing of a recent bottleneck. This demographic scenario is relevant for many species of conservation concern, few of which have sequenced genomes. Our results are remarkably insensitive to sample size or number of genomic markers, which has important implications for applying this method to other non-model systems. PMID:24237665

  19. Experimental verification and theoretical prediction of cartilage interstitial fluid pressurization at an impermeable contact interface in confined compression.

    PubMed

    Soltz, M A; Ateshian, G A

    1998-10-01

    Interstitial fluid pressurization has long been hypothesized to play a fundamental role in the load support mechanism and frictional response of articular cartilage. However, to date, few experimental studies have been performed to verify this hypothesis from direct measurements. The first objective of this study was to investigate experimentally the hypothesis that cartilage interstitial fluid pressurization does support the great majority of the applied load, in the testing configurations of confined compression creep and stress relaxation. The second objective was to investigate the hypothesis that the experimentally observed interstitial fluid pressurization could also be predicted using the linear biphasic theory of Mow et al. (J. Biomech. Engng ASME, 102, 73-84, 1980). Fourteen bovine cartilage samples were tested in a confined compression chamber fitted with a microchip piezoresistive transducer to measure interstitial fluid pressure, while simultaneously measuring (during stress relaxation) or prescribing (during creep) the total stress. It was found that interstitial fluid pressure supported more than 90% of the total stress for durations as long as 725 +/- 248 s during stress relaxation (mean +/- S.D., n = 7), and 404 +/- 229 s during creep (n = 7). When comparing experimental measurements of the time-varying interstitial fluid pressure against predictions from the linear biphasic theory, nonlinear coefficients of determination r2 = 0.871 +/- 0.086 (stress relaxation) and r2 = 0.941 +/- 0.061 (creep) were found. The results of this study provide some of the most direct evidence to date that interstitial fluid pressurization plays a fundamental role in cartilage mechanics; they also indicate that the mechanism of fluid load support in cartilage can be properly predicted from theory.

  20. An accurate method to predict the stress concentration in composite laminates with a circular hole under tensile loading

    NASA Astrophysics Data System (ADS)

    Russo, A.; Zuccarello, B.

    2007-07-01

    The paper presents a theoretical-numerical hybrid method for determining the stresses distribution in composite laminates containing a circular hole and subjected to uniaxial tensile loading. The method is based upon an appropriate corrective function allowing a simple and rapid evaluation of stress distributions in a generic plate of finite width with a hole based on the theoretical stresses distribution in an infinite plate with the same hole geometry and material. In order to verify the accuracy of the method proposed, various numerical and experimental tests have been performed by considering different laminate lay-ups; in particular, the experimental results have shown that a combined use of the method proposed and the well-know point-stress criterion leads to reliable strength predictions for GFRP or CFRP laminates with a circular hole.

  1. Accurate prediction of secreted substrates and identification of a conserved putative secretion signal for type III secretion systems

    SciTech Connect

    Samudrala, Ram; Heffron, Fred; McDermott, Jason E.

    2009-04-24

    The type III secretion system is an essential component for virulence in many Gram-negative bacteria. Though components of the secretion system apparatus are conserved, its substrates, effector proteins, are not. We have used a machine learning approach to identify new secreted effectors. The method integrates evolutionary measures, such as the pattern of homologs in a range of other organisms, and sequence-based features, such as G+C content, amino acid composition and the N-terminal 30 residues of the protein sequence. The method was trained on known effectors from Salmonella typhimurium and validated on a corresponding set of effectors from Pseudomonas syringae, after eliminating effectors with detectable sequence similarity. The method was able to identify all of the known effectors in P. syringae with a specificity of 84% and sensitivity of 82%. The reciprocal validation, training on P. syringae and validating on S. typhimurium, gave similar results with a specificity of 86% when the sensitivity level was 87%. These results show that type III effectors in disparate organisms share common features. We found that maximal performance is attained by including an N-terminal sequence of only 30 residues, which agrees with previous studies indicating that this region contains the secretion signal. We then used the method to define the most important residues in this putative secretion signal. Finally, we present novel predictions of secreted effectors in S. typhimurium, some of which have been experimentally validated, and apply the method to predict secreted effectors in the genetically intractable human pathogen Chlamydia trachomatis. This approach is a novel and effective way to identify secreted effectors in a broad range of pathogenic bacteria for further experimental characterization and provides insight into the nature of the type III secretion signal.

  2. A single bioavailability model can accurately predict Ni toxicity to green microalgae in soft and hard surface waters.

    PubMed

    Deleebeeck, Nele M E; De Laender, Frederik; Chepurnov, Victor A; Vyverman, Wim; Janssen, Colin R; De Schamphelaere, Karel A C

    2009-04-01

    The major research questions addressed in this study were (i) whether green microalgae living in soft water (operationally defined water hardness<10mg CaCO(3)/L) are intrinsically more sensitive to Ni than green microalgae living in hard water (operationally defined water hardness >25mg CaCO(3)/L), and (ii) whether a single bioavailability model can be used to predict the effect of water hardness on the toxicity of Ni to green microalgae in both soft and hard water. Algal growth inhibition tests were conducted with clones of 10 different species collected in soft and hard water lakes in Sweden. Soft water algae were tested in a 'soft' and a 'moderately hard' test medium (nominal water hardness=6.25 and 16.3mg CaCO(3)/L, respectively), whereas hard water algae were tested in a 'moderately hard' and a 'hard' test medium (nominal water hardness=16.3 and 43.4 mg CaCO(3)/L, respectively). The results from the growth inhibition tests in the 'moderately hard' test medium revealed no significant sensitivity differences between the soft and the hard water algae used in this study. Increasing water hardness significantly reduced Ni toxicity to both soft and hard water algae. Because it has previously been demonstrated that Ca does not significantly protect the unicellular green alga Pseudokirchneriella subcapitata against Ni toxicity, it was assumed that the protective effect of water hardness can be ascribed to Mg alone. The logK(MgBL) (=5.5) was calculated to be identical for the soft and the hard water algae used in this study. A single bioavailability model can therefore be used to predict Ni toxicity to green microalgae in soft and hard surface waters as a function of water hardness.

  3. Cerebrospinal fluid and plasma oxytocin concentrations are positively correlated and negatively predict anxiety in children.

    PubMed

    Carson, D S; Berquist, S W; Trujillo, T H; Garner, J P; Hannah, S L; Hyde, S A; Sumiyoshi, R D; Jackson, L P; Moss, J K; Strehlow, M C; Cheshier, S H; Partap, S; Hardan, A Y; Parker, K J

    2015-09-01

    The neuropeptide oxytocin (OXT) exerts anxiolytic and prosocial effects in the central nervous system of rodents. A number of recent studies have attempted to translate these findings by investigating the relationships between peripheral (e.g., blood, urinary and salivary) OXT concentrations and behavioral functioning in humans. Although peripheral samples are easy to obtain in humans, whether peripheral OXT measures are functionally related to central OXT activity remains unclear. To investigate a possible relationship, we quantified OXT concentrations in concomitantly collected cerebrospinal fluid (CSF) and blood samples from child and adult patients undergoing clinically indicated lumbar punctures or other CSF-related procedures. Anxiety scores were obtained in a subset of child participants whose parents completed psychometric assessments. Findings from this study indicate that plasma OXT concentrations significantly and positively predict CSF OXT concentrations (r=0.56, P=0.0064, N=27). Moreover, both plasma (r=-0.92, P=0.0262, N=10) and CSF (r=-0.91, P=0.0335, N=10) OXT concentrations significantly and negatively predicted trait anxiety scores, consistent with the preclinical literature. Importantly, plasma OXT concentrations significantly and positively (r=0.96, P=0.0115, N=10) predicted CSF OXT concentrations in the subset of child participants who provided behavioral data. This study provides the first empirical support for the use of blood measures of OXT as a surrogate for central OXT activity, validated in the context of behavioral functioning. These preliminary findings also suggest that impaired OXT signaling may be a biomarker of anxiety in humans, and a potential target for therapeutic development in individuals with anxiety disorders.

  4. Synchronized Chaos in Geophysical Fluid Dynamics and in the Predictive Modeling of Natural Systems

    NASA Astrophysics Data System (ADS)

    Duane, Gregory S.

    2008-03-01

    The ubiquitous phenomenon of synchronization among regular oscillators in Nature has been shown, in the past two decades, to extend to chaotic systems. Despite sensitive dependence on initial conditions, two chaotic systems will commonly fall into synchronized motion along their strange attractors when only some of the many degrees of freedom of one system are coupled to corresponding variables in the other. In geophysical fluid models, synchronization can mediate scale interactions, so that coupling of degrees of freedom that describe medium-scale components of the flow can result in synchronization, or partial synchronization, at all scales. Chaos synchronization has been used to interpret non-local "teleconnection" patterns in the Earth's climate system and to predict new ones. In the realm of practical meteorology, the fact that two PDE systems, conceived as "truth" and "model", respectively, can be made to synchronize when coupled at only a discrete set of points, explains how observations at a discrete set of weather stations can be sufficient for weather prediction by a synchronously coupled model. Minimizing synchronization error leads to general recipes for assimilation of observed data into a running model that systematize the treatment of nonlinearities in the dynamical equations. Equations can generally be added to adapt parameters as well as states as the model is running, so that the model "learns". The synchronization view of predictive modelling extends to any translationally- any PDE with constant coefficients, the general form of physical theories. The reliance on synchronicity as an organizing principle in Nature, alternative to causality, has philosophical roots in the collaboration of Carl Jung and Wolfgang Pauli, on the one hand, and in traditions outside of European science, on the other.

  5. Generalized spin-ratio scaled MP2 method for accurate prediction of intermolecular interactions for neutral and ionic species

    NASA Astrophysics Data System (ADS)

    Tan, Samuel; Barrera Acevedo, Santiago; Izgorodina, Ekaterina I.

    2017-02-01

    The accurate calculation of intermolecular interactions is important to our understanding of properties in large molecular systems. The high computational cost of the current "gold standard" method, coupled cluster with singles and doubles and perturbative triples (CCSD(T), limits its application to small- to medium-sized systems. Second-order Møller-Plesset perturbation (MP2) theory is a cheaper alternative for larger systems, although at the expense of its decreased accuracy, especially when treating van der Waals complexes. In this study, a new modification of the spin-component scaled MP2 method was proposed for a wide range of intermolecular complexes including two well-known datasets, S22 and S66, and a large dataset of ionic liquids consisting of 174 single ion pairs, IL174. It was found that the spin ratio, ɛΔ s=E/INT O SEIN T S S , calculated as the ratio of the opposite-spin component to the same-spin component of the interaction correlation energy fell in the range of 0.1 and 1.6, in contrast to the range of 3-4 usually observed for the ratio of absolute correlation energy, ɛs=E/OSES S , in individual molecules. Scaled coefficients were found to become negative when the spin ratio fell in close proximity to 1.0, and therefore, the studied intermolecular complexes were divided into two groups: (1) complexes with ɛΔ s< 1 and (2) complexes with ɛΔ s≥ 1 . A separate set of coefficients was obtained for both groups. Exclusion of counterpoise correction during scaling was found to produce superior results due to decreased error. Among a series of Dunning's basis sets, cc-pVTZ and cc-pVQZ were found to be the best performing ones, with a mean absolute error of 1.4 kJ mol-1 and maximum errors below 6.2 kJ mol-1. The new modification, spin-ratio scaled second-order Møller-Plesset perturbation, treats both dispersion-driven and hydrogen-bonded complexes equally well, thus validating its robustness with respect to the interaction type ranging from ionic

  6. Accurate Predictions of Mean Geomagnetic Dipole Excursion and Reversal Frequencies, Mean Paleomagnetic Field Intensity, and the Radius of Earth's Core Using McLeod's Rule

    NASA Technical Reports Server (NTRS)

    Voorhies, Coerte V.; Conrad, Joy

    1996-01-01

    The geomagnetic spatial power spectrum R(sub n)(r) is the mean square magnetic induction represented by degree n spherical harmonic coefficients of the internal scalar potential averaged over the geocentric sphere of radius r. McLeod's Rule for the magnetic field generated by Earth's core geodynamo says that the expected core surface power spectrum (R(sub nc)(c)) is inversely proportional to (2n + 1) for 1 less than n less than or equal to N(sub E). McLeod's Rule is verified by locating Earth's core with main field models of Magsat data; the estimated core radius of 3485 kn is close to the seismologic value for c of 3480 km. McLeod's Rule and similar forms are then calibrated with the model values of R(sub n) for 3 less than or = n less than or = 12. Extrapolation to the degree 1 dipole predicts the expectation value of Earth's dipole moment to be about 5.89 x 10(exp 22) Am(exp 2)rms (74.5% of the 1980 value) and the expected geomagnetic intensity to be about 35.6 (mu)T rms at Earth's surface. Archeo- and paleomagnetic field intensity data show these and related predictions to be reasonably accurate. The probability distribution chi(exp 2) with 2n+1 degrees of freedom is assigned to (2n + 1)R(sub nc)/(R(sub nc). Extending this to the dipole implies that an exceptionally weak absolute dipole moment (less than or = 20% of the 1980 value) will exist during 2.5% of geologic time. The mean duration for such major geomagnetic dipole power excursions, one quarter of which feature durable axial dipole reversal, is estimated from the modern dipole power time-scale and the statistical model of excursions. The resulting mean excursion duration of 2767 years forces us to predict an average of 9.04 excursions per million years, 2.26 axial dipole reversals per million years, and a mean reversal duration of 5533 years. Paleomagnetic data show these predictions to be quite accurate. McLeod's Rule led to accurate predictions of Earth's core radius, mean paleomagnetic field

  7. Integrating metabolic performance, thermal tolerance, and plasticity enables for more accurate predictions on species vulnerability to acute and chronic effects of global warming.

    PubMed

    Magozzi, Sarah; Calosi, Piero

    2015-01-01

    Predicting species vulnerability to global warming requires a comprehensive, mechanistic understanding of sublethal and lethal thermal tolerances. To date, however, most studies investigating species physiological responses to increasing temperature have focused on the underlying physiological traits of either acute or chronic tolerance in isolation. Here we propose an integrative, synthetic approach including the investigation of multiple physiological traits (metabolic performance and thermal tolerance), and their plasticity, to provide more accurate and balanced predictions on species and assemblage vulnerability to both acute and chronic effects of global warming. We applied this approach to more accurately elucidate relative species vulnerability to warming within an assemblage of six caridean prawns occurring in the same geographic, hence macroclimatic, region, but living in different thermal habitats. Prawns were exposed to four incubation temperatures (10, 15, 20 and 25 °C) for 7 days, their metabolic rates and upper thermal limits were measured, and plasticity was calculated according to the concept of Reaction Norms, as well as Q10 for metabolism. Compared to species occupying narrower/more stable thermal niches, species inhabiting broader/more variable thermal environments (including the invasive Palaemon macrodactylus) are likely to be less vulnerable to extreme acute thermal events as a result of their higher upper thermal limits. Nevertheless, they may be at greater risk from chronic exposure to warming due to the greater metabolic costs they incur. Indeed, a trade-off between acute and chronic tolerance was apparent in the assemblage investigated. However, the invasive species P. macrodactylus represents an exception to this pattern, showing elevated thermal limits and plasticity of these limits, as well as a high metabolic control. In general, integrating multiple proxies for species physiological acute and chronic responses to increasing

  8. Predicting College Students' First Year Success: Should Soft Skills Be Taken into Consideration to More Accurately Predict the Academic Achievement of College Freshmen?

    ERIC Educational Resources Information Center

    Powell, Erica Dion

    2013-01-01

    This study presents a survey developed to measure the skills of entering college freshmen in the areas of responsibility, motivation, study habits, literacy, and stress management, and explores the predictive power of this survey as a measure of academic performance during the first semester of college. The survey was completed by 334 incoming…

  9. Microdosing of a Carbon-14 Labeled Protein in Healthy Volunteers Accurately Predicts Its Pharmacokinetics at Therapeutic Dosages.

    PubMed

    Vlaming, M L H; van Duijn, E; Dillingh, M R; Brands, R; Windhorst, A D; Hendrikse, N H; Bosgra, S; Burggraaf, J; de Koning, M C; Fidder, A; Mocking, J A J; Sandman, H; de Ligt, R A F; Fabriek, B O; Pasman, W J; Seinen, W; Alves, T; Carrondo, M; Peixoto, C; Peeters, P A M; Vaes, W H J

    2015-08-01

    Preclinical development of new biological entities (NBEs), such as human protein therapeutics, requires considerable expenditure of time and costs. Poor prediction of pharmacokinetics in humans further reduces net efficiency. In this study, we show for the first time that pharmacokinetic data of NBEs in humans can be successfully obtained early in the drug development process by the use of microdosing in a small group of healthy subjects combined with ultrasensitive accelerator mass spectrometry (AMS). After only minimal preclinical testing, we performed a first-in-human phase 0/phase 1 trial with a human recombinant therapeutic protein (RESCuing Alkaline Phosphatase, human recombinant placental alkaline phosphatase [hRESCAP]) to assess its safety and kinetics. Pharmacokinetic analysis showed dose linearity from microdose (53 μg) [(14) C]-hRESCAP to therapeutic doses (up to 5.3 mg) of the protein in healthy volunteers. This study demonstrates the value of a microdosing approach in a very small cohort for accelerating the clinical development of NBEs.

  10. Women's age and embryo developmental speed accurately predict clinical pregnancy after single vitrified-warmed blastocyst transfer.

    PubMed

    Kato, Keiichi; Ueno, Satoshi; Yabuuchi, Akiko; Uchiyama, Kazuo; Okuno, Takashi; Kobayashi, Tamotsu; Segawa, Tomoya; Teramoto, Shokichi

    2014-10-01

    The aim of this study was to establish a simple, objective blastocyst grading system using women's age and embryo developmental speed to predict clinical pregnancy after single vitrified-warmed blastocyst transfer. A 6-year retrospective cohort study was conducted in a private infertility centre. A total of 7341 single vitrified-armed blastocyst transfer cycles were included, divided into those carried out between 2006 and 2011 (6046 cycles) and 2012 (1295 cycles). Clinical pregnancy rate, ongoing pregnancy rate and delivery rates were stratified by women's age (<35, 35-37, 38-39, 40-41, 42-45 years) and time to blastocyst expansion (<120, 120-129, 130-139, 140-149, >149 h) as embryo developmental speed. In all the age groups, clinical pregnancy rate, ongoing pregnancy rate and delivery rates decreased as the embryo developmental speed decreased (P < 0.0001). A simple five-grade score based on women's age and embryo developmental speed was determined by actual clinical pregnancy rates observed in the 2006-2011 cohort. Subsequently, the novel grading score was validated in the 2012 cohort (1295 cycles), finding an excellent association. In conclusion, we established a novel blastocyst grading system using women's age and embryo developmental speed as objective parameters.

  11. Transcription factor regulation can be accurately predicted from the presence of target gene signatures in microarray gene expression data

    PubMed Central

    Essaghir, Ahmed; Toffalini, Federica; Knoops, Laurent; Kallin, Anders; van Helden, Jacques; Demoulin, Jean-Baptiste

    2010-01-01

    Deciphering transcription factor networks from microarray data remains difficult. This study presents a simple method to infer the regulation of transcription factors from microarray data based on well-characterized target genes. We generated a catalog containing transcription factors associated with 2720 target genes and 6401 experimentally validated regulations. When it was available, a distinction between transcriptional activation and inhibition was included for each regulation. Next, we built a tool (www.tfacts.org) that compares submitted gene lists with target genes in the catalog to detect regulated transcription factors. TFactS was validated with published lists of regulated genes in various models and compared to tools based on in silico promoter analysis. We next analyzed the NCI60 cancer microarray data set and showed the regulation of SOX10, MITF and JUN in melanomas. We then performed microarray experiments comparing gene expression response of human fibroblasts stimulated by different growth factors. TFactS predicted the specific activation of Signal transducer and activator of transcription factors by PDGF-BB, which was confirmed experimentally. Our results show that the expression levels of transcription factor target genes constitute a robust signature for transcription factor regulation, and can be efficiently used for microarray data mining. PMID:20215436

  12. The Prediction of Students' Academic Performance With Fluid Intelligence in Giving Special Consideration to the Contribution of Learning.

    PubMed

    Ren, Xuezhu; Schweizer, Karl; Wang, Tengfei; Xu, Fen

    2015-01-01

    The present study provides a new account of how fluid intelligence influences academic performance. In this account a complex learning component of fluid intelligence tests is proposed to play a major role in predicting academic performance. A sample of 2, 277 secondary school students completed two reasoning tests that were assumed to represent fluid intelligence and standardized math and verbal tests assessing academic performance. The fluid intelligence data were decomposed into a learning component that was associated with the position effect of intelligence items and a constant component that was independent of the position effect. Results showed that the learning component contributed significantly more to the prediction of math and verbal performance than the constant component. The link from the learning component to math performance was especially strong. These results indicated that fluid intelligence, which has so far been considered as homogeneous, could be decomposed in such a way that the resulting components showed different properties and contributed differently to the prediction of academic performance. Furthermore, the results were in line with the expectation that learning was a predictor of performance in school.

  13. Infectious titres of sheep scrapie and bovine spongiform encephalopathy agents cannot be accurately predicted from quantitative laboratory test results.

    PubMed

    González, Lorenzo; Thorne, Leigh; Jeffrey, Martin; Martin, Stuart; Spiropoulos, John; Beck, Katy E; Lockey, Richard W; Vickery, Christopher M; Holder, Thomas; Terry, Linda

    2012-11-01

    It is widely accepted that abnormal forms of the prion protein (PrP) are the best surrogate marker for the infectious agent of prion diseases and, in practice, the detection of such disease-associated (PrP(d)) and/or protease-resistant (PrP(res)) forms of PrP is the cornerstone of diagnosis and surveillance of the transmissible spongiform encephalopathies (TSEs). Nevertheless, some studies question the consistent association between infectivity and abnormal PrP detection. To address this discrepancy, 11 brain samples of sheep affected with natural scrapie or experimental bovine spongiform encephalopathy were selected on the basis of the magnitude and predominant types of PrP(d) accumulation, as shown by immunohistochemical (IHC) examination; contra-lateral hemi-brain samples were inoculated at three different dilutions into transgenic mice overexpressing ovine PrP and were also subjected to quantitative analysis by three biochemical tests (BCTs). Six samples gave 'low' infectious titres (10⁶·⁵ to 10⁶·⁷ LD₅₀ g⁻¹) and five gave 'high titres' (10⁸·¹ to ≥ 10⁸·⁷ LD₅₀ g⁻¹) and, with the exception of the Western blot analysis, those two groups tended to correspond with samples with lower PrP(d)/PrP(res) results by IHC/BCTs. However, no statistical association could be confirmed due to high individual sample variability. It is concluded that although detection of abnormal forms of PrP by laboratory methods remains useful to confirm TSE infection, infectivity titres cannot be predicted from quantitative test results, at least for the TSE sources and host PRNP genotypes used in this study. Furthermore, the near inverse correlation between infectious titres and Western blot results (high protease pre-treatment) argues for a dissociation between infectivity and PrP(res).

  14. Noncontrast computed tomography can predict the outcome of shockwave lithotripsy via accurate stone measurement and abdominal fat distribution determination.

    PubMed

    Geng, Jiun-Hung; Tu, Hung-Pin; Shih, Paul Ming-Chen; Shen, Jung-Tsung; Jang, Mei-Yu; Wu, Wen-Jen; Li, Ching-Chia; Chou, Yii-Her; Juan, Yung-Shun

    2015-01-01

    Urolithiasis is a common disease of the urinary system. Extracorporeal shockwave lithotripsy (SWL) has become one of the standard treatments for renal and ureteral stones; however, the success rates range widely and failure of stone disintegration may cause additional outlay, alternative procedures, and even complications. We used the data available from noncontrast abdominal computed tomography (NCCT) to evaluate the impact of stone parameters and abdominal fat distribution on calculus-free rates following SWL. We retrospectively reviewed 328 patients who had urinary stones and had undergone SWL from August 2012 to August 2013. All of them received pre-SWL NCCT; 1 month after SWL, radiography was arranged to evaluate the condition of the fragments. These patients were classified into stone-free group and residual stone group. Unenhanced computed tomography variables, including stone attenuation, abdominal fat area, and skin-to-stone distance (SSD) were analyzed. In all, 197 (60%) were classified as stone-free and 132 (40%) as having residual stone. The mean ages were 49.35 ± 13.22 years and 55.32 ± 13.52 years, respectively. On univariate analysis, age, stone size, stone surface area, stone attenuation, SSD, total fat area (TFA), abdominal circumference, serum creatinine, and the severity of hydronephrosis revealed statistical significance between these two groups. From multivariate logistic regression analysis, the independent parameters impacting SWL outcomes were stone size, stone attenuation, TFA, and serum creatinine. [Adjusted odds ratios and (95% confidence intervals): 9.49 (3.72-24.20), 2.25 (1.22-4.14), 2.20 (1.10-4.40), and 2.89 (1.35-6.21) respectively, all p < 0.05]. In the present study, stone size, stone attenuation, TFA and serum creatinine were four independent predictors for stone-free rates after SWL. These findings suggest that pretreatment NCCT may predict the outcomes after SWL. Consequently, we can use these predictors for selecting

  15. Prediction of space sickness in astronauts from preflight fluid, electrolyte, and cardiovascular variables and Weightless Environmental Training Facility (WETF) training

    NASA Technical Reports Server (NTRS)

    Simanonok, K.; Mosely, E.; Charles, J.

    1992-01-01

    Nine preflight variables related to fluid, electrolyte, and cardiovascular status from 64 first-time Shuttle crewmembers were differentially weighted by discrimination analysis to predict the incidence and severity of each crewmember's space sickness as rated by NASA flight surgeons. The nine variables are serum uric acid, red cell count, environmental temperature at the launch site, serum phosphate, urine osmolality, serum thyroxine, sitting systolic blood pressure, calculated blood volume, and serum chloride. Using two methods of cross-validation on the original samples (jackknife and a stratefied random subsample), these variables enable the prediction of space sickness incidence (NONE or SICK) with 80 percent sickness and space severity (NONE, MILD, MODERATE, of SEVERE) with 59 percent success by one method of cross-validation and 67 percent by another method. Addition of a tenth variable, hours spent in the Weightlessness Environment Training Facility (WETF) did not improve the prediction of space sickness incidences but did improve the prediction of space sickness severity to 66 percent success by the first method of cross-validation of original samples and to 71 percent by the second method. Results to date suggest the presence of predisposing physiologic factors to space sickness that implicate fluid shift etiology. The data also suggest that prior exposure to fluid shift during WETF training may produce some circulatory pre-adaption to fluid shifts in weightlessness that results in a reduction of space sickness severity.

  16. An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints.

    PubMed

    Wang, Shiyao; Deng, Zhidong; Yin, Gang

    2016-02-24

    A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS-inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car.

  17. An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints

    PubMed Central

    Wang, Shiyao; Deng, Zhidong; Yin, Gang

    2016-01-01

    A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS–inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car. PMID:26927108

  18. Profile-QSAR: a novel meta-QSAR method that combines activities across the kinase family to accurately predict affinity, selectivity, and cellular activity.

    PubMed

    Martin, Eric; Mukherjee, Prasenjit; Sullivan, David; Jansen, Johanna

    2011-08-22

    Profile-QSAR is a novel 2D predictive model building method for kinases. This "meta-QSAR" method models the activity of each compound against a new kinase target as a linear combination of its predicted activities against a large panel of 92 previously studied kinases comprised from 115 assays. Profile-QSAR starts with a sparse incomplete kinase by compound (KxC) activity matrix, used to generate Bayesian QSAR models for the 92 "basis-set" kinases. These Bayesian QSARs generate a complete "synthetic" KxC activity matrix of predictions. These synthetic activities are used as "chemical descriptors" to train partial-least squares (PLS) models, from modest amounts of medium-throughput screening data, for predicting activity against new kinases. The Profile-QSAR predictions for the 92 kinases (115 assays) gave a median external R²(ext) = 0.59 on 25% held-out test sets. The method has proven accurate enough to predict pairwise kinase selectivities with a median correlation of R²(ext) = 0.61 for 958 kinase pairs with at least 600 common compounds. It has been further expanded by adding a "C(k)XC" cellular activity matrix to the KxC matrix to predict cellular activity for 42 kinase driven cellular assays with median R²(ext) = 0.58 for 24 target modulation assays and R²(ext) = 0.41 for 18 cell proliferation assays. The 2D Profile-QSAR, along with the 3D Surrogate AutoShim, are the foundations of an internally developed iterative medium-throughput screening (IMTS) methodology for virtual screening (VS) of compound archives as an alternative to experimental high-throughput screening (HTS). The method has been applied to 20 actual prospective kinase projects. Biological results have so far been obtained in eight of them. Q² values ranged from 0.3 to 0.7. Hit-rates at 10 uM for experimentally tested compounds varied from 25% to 80%, except in K5, which was a special case aimed specifically at finding "type II" binders, where none of the compounds were predicted to be

  19. The predictive value of cerebrospinal fluid tap-test in normal pressure hydrocephalus.

    PubMed

    Damasceno, B P; Carelli, E F; Honorato, D C; Facure, J J

    1997-06-01

    Eighteen patients (mean age of 66.5 years) with normal pressure hydrocephalus (NPH) underwent a ventriculo-peritoneal shunt surgery. Prior to operation a cerebrospinal fluid tap-test (CSF-TT) was performed with measurements of gait pattern and psychometric functions (memory, visuo-motor speed and visuo-constructive skills) before and after the removal of 50 ml CSF by lumbar puncture (LP). Fifteen patients improved and 3 were unchanged after surgery. Short duration of disease, gait disturbance preceding mental deterioration, wide temporal horns and small sulci on CT-scan were associated with good outcome after shunting. There was a good correlation between the results of CSF-TT and shunt surgery (chi 2 = 4.11, phi = 0.48, p < 0.05), with gait test showing highest correlation (r = 0.99, p = 0.01). In conclusion, this version of CSF-TT proved to be an effective test to predict improvement after shunting in patients with NPH.

  20. Multireference correlation consistent composite approach [MR-ccCA]: toward accurate prediction of the energetics of excited and transition state chemistry.

    PubMed

    Oyedepo, Gbenga A; Wilson, Angela K

    2010-08-26

    The correlation consistent Composite Approach, ccCA [ Deyonker , N. J. ; Cundari , T. R. ; Wilson , A. K. J. Chem. Phys. 2006 , 124 , 114104 ] has been demonstrated to predict accurate thermochemical properties of chemical species that can be described by a single configurational reference state, and at reduced computational cost, as compared with ab initio methods such as CCSD(T) used in combination with large basis sets. We have developed three variants of a multireference equivalent of this successful theoretical model. The method, called the multireference correlation consistent composite approach (MR-ccCA), is designed to predict the thermochemical properties of reactive intermediates, excited state species, and transition states to within chemical accuracy (e.g., 1 kcal/mol for enthalpies of formation) of reliable experimental values. In this study, we have demonstrated the utility of MR-ccCA: (1) in the determination of the adiabatic singlet-triplet energy separations and enthalpies of formation for the ground states for a set of diradicals and unsaturated compounds, and (2) in the prediction of energetic barriers to internal rotation, in ethylene and its heavier congener, disilene. Additionally, we have utilized MR-ccCA to predict the enthalpies of formation of the low-lying excited states of all the species considered. MR-ccCA is shown to give quantitative results without reliance upon empirically derived parameters, making it suitable for application to study novel chemical systems with significant nondynamical correlation effects.

  1. Accurate prediction of death by serial determination of galactose elimination capacity in primary biliary cirrhosis: a comparison with the Mayo model.

    PubMed

    Reichen, J; Widmer, T; Cotting, J

    1991-09-01

    We retrospectively analyzed the predictive accuracy of serial determinations of galactose elimination capacity in 61 patients with primary biliary cirrhosis. Death was predicted from the time that the regression line describing the decline in galactose elimination capacity vs. time intersected a value of 4 mg.min-1.kg-1. Thirty-one patients exhibited decreasing galactose elimination capacity; in 11 patients it remained stable and in 19 patients only one value was available. Among those patients with decreasing galactose elimination capacity, 10 died and three underwent liver transplantation; prediction of death was accurate to 7 +/- 19 mo. This criterion incorrectly predicted death in two patients with portal-vein thrombosis; otherwise, it did better than or as well as the Mayo clinic score. The latter was also tested on our patients and was found to adequately describe risk in yet another independent population of patients with primary biliary cirrhosis. Cox regression analysis selected only bilirubin and galactose elimination capacity, however, as independent predictors of death. We submit that serial determination of galactose elimination capacity in patients with primary biliary cirrhosis may be a useful adjunct to optimize the timing of liver transplantation and to evaluate new pharmacological treatment modalities of this disease.

  2. Communication: Superstabilization of fluids in nanocontainers

    SciTech Connect

    Wilhelmsen, Øivind; Bedeaux, Dick; Kjelstrup, Signe; Reguera, David

    2014-08-21

    One of the main challenges of thermodynamics is to predict and measure accurately the properties of metastable fluids. Investigation of these fluids is hindered by their spontaneous transformation by nucleation into a more stable phase. We show how small closed containers can be used to completely prevent nucleation, achieving infinitely long-lived metastable states. Using a general thermodynamic framework, we derive simple formulas to predict accurately the conditions (container sizes) at which this superstabilization takes place and it becomes impossible to form a new stable phase. This phenomenon opens the door to control nucleation of deeply metastable fluids at experimentally feasible conditions, having important implications in a wide variety of fields.

  3. Prediction of cavitation performance and choking flow limit of inducers for cold water and for fluids with thermodynamic effect

    NASA Astrophysics Data System (ADS)

    Sauvage-Boutar, E.; Desclaux, J.

    1990-07-01

    Two methods of prediction of partial cavitation in inducers of rocket engine turbopumps have been developed. The first one is an analytical method previously developed to predict minimum NPSH (inlet total head minus vapor pressure) and the choking flow limit which was modified to include the computation of blade and boundary layer blockage. The second one is a method based on the work of Moore and Ruggeri (1969). This method takes into account thermodynamic effect for the prediction of the cavitation parameter Ki. For the choking flow limit, the first method can be extended to cryogenic fluids. Comparisons with available experimental data obtained with VULCAIN inducer pumping water and liquid hydrogen are presented.

  4. Cerebrospinal fluid total tau concentration predicts clinical phenotype in Huntington's disease.

    PubMed

    Rodrigues, Filipe Brogueira; Byrne, Lauren; McColgan, Peter; Robertson, Nicola; Tabrizi, Sarah J; Leavitt, Blair R; Zetterberg, Henrik; Wild, Edward J

    2016-10-01

    neuronal death, in cerebrospinal fluid and found it was increased in patients with Huntington's disease and predicted motor, cognitive, and functional disability in patients. It is therefore likely to be a biomarker of disease progression, and possibly of therapeutic response. Read the Editorial Highlight for this article on page 9.

  5. Accurate prediction of hard-sphere virial coefficients B6 to B12 from a compressibility-based equation of state

    NASA Astrophysics Data System (ADS)

    Hansen-Goos, Hendrik

    2016-04-01

    We derive an analytical equation of state for the hard-sphere fluid that is within 0.01% of computer simulations for the whole range of the stable fluid phase. In contrast, the commonly used Carnahan-Starling equation of state deviates by up to 0.3% from simulations. The derivation uses the functional form of the isothermal compressibility from the Percus-Yevick closure of the Ornstein-Zernike relation as a starting point. Two additional degrees of freedom are introduced, which are constrained by requiring the equation of state to (i) recover the exact fourth virial coefficient B4 and (ii) involve only integer coefficients on the level of the ideal gas, while providing best possible agreement with the numerical result for B5. Virial coefficients B6 to B10 obtained from the equation of state are within 0.5% of numerical computations, and coefficients B11 and B12 are within the error of numerical results. We conjecture that even higher virial coefficients are reliably predicted.

  6. Accurate prediction of hard-sphere virial coefficients B6 to B12 from a compressibility-based equation of state.

    PubMed

    Hansen-Goos, Hendrik

    2016-04-28

    We derive an analytical equation of state for the hard-sphere fluid that is within 0.01% of computer simulations for the whole range of the stable fluid phase. In contrast, the commonly used Carnahan-Starling equation of state deviates by up to 0.3% from simulations. The derivation uses the functional form of the isothermal compressibility from the Percus-Yevick closure of the Ornstein-Zernike relation as a starting point. Two additional degrees of freedom are introduced, which are constrained by requiring the equation of state to (i) recover the exact fourth virial coefficient B4 and (ii) involve only integer coefficients on the level of the ideal gas, while providing best possible agreement with the numerical result for B5. Virial coefficients B6 to B10 obtained from the equation of state are within 0.5% of numerical computations, and coefficients B11 and B12 are within the error of numerical results. We conjecture that even higher virial coefficients are reliably predicted.

  7. Consistent prediction of streaming potential in non-Newtonian fluids: the effect of solvent rheology and confinement on ionic conductivity.

    PubMed

    Bandopadhyay, Aditya; Chakraborty, Suman

    2015-03-21

    By considering an ion moving inside an imaginary sphere filled with a power-law fluid, we bring out the implications of the fluid rheology and the influence of the proximity of the other ions towards evaluating the conduction current in an ionic solution. We show that the variation of the conductivity as a function of the ionic concentration is both qualitatively and quantitatively similar to that predicted by the Kohlrausch law. We then utilize this consideration for estimating streaming potentials developed across narrow fluidic confinements as a consequence of the transport of ions in a convective medium constituting a power-law fluid. These estimates turn out to be in sharp contrast to the classical estimates of streaming potential for non-Newtonian fluids, in which the effect of rheology of the solvent is merely considered to affect the advection current, disregarding its contributions to the conduction current. Our results have potential implications of devising a new paradigm of consistent estimation of streaming potentials for non-Newtonian fluids, with combined considerations of the confinement effect and fluid rheology in the theoretical calculations.

  8. Unprecedently Large-Scale Kinase Inhibitor Set Enabling the Accurate Prediction of Compound–Kinase Activities: A Way toward Selective Promiscuity by Design?

    PubMed Central

    2016-01-01

    Drug discovery programs frequently target members of the human kinome and try to identify small molecule protein kinase inhibitors, primarily for cancer treatment, additional indications being increasingly investigated. One of the challenges is controlling the inhibitors degree of selectivity, assessed by in vitro profiling against panels of protein kinases. We manually extracted, compiled, and standardized such profiles published in the literature: we collected 356 908 data points corresponding to 482 protein kinases, 2106 inhibitors, and 661 patents. We then analyzed this data set in terms of kinome coverage, results reproducibility, popularity, and degree of selectivity of both kinases and inhibitors. We used the data set to create robust proteochemometric models capable of predicting kinase activity (the ligand–target space was modeled with an externally validated RMSE of 0.41 ± 0.02 log units and R02 0.74 ± 0.03), in order to account for missing or unreliable measurements. The influence on the prediction quality of parameters such as number of measurements, Murcko scaffold frequency or inhibitor type was assessed. Interpretation of the models enabled to highlight inhibitors and kinases properties correlated with higher affinities, and an analysis in the context of kinases crystal structures was performed. Overall, the models quality allows the accurate prediction of kinase-inhibitor activities and their structural interpretation, thus paving the way for the rational design of compounds with a targeted selectivity profile. PMID:27482722

  9. Identification of fidgety movements and prediction of CP by the use of computer-based video analysis is more accurate when based on two video recordings.

    PubMed

    Adde, Lars; Helbostad, Jorunn; Jensenius, Alexander R; Langaas, Mette; Støen, Ragnhild

    2013-08-01

    This study evaluates the role of postterm age at assessment and the use of one or two video recordings for the detection of fidgety movements (FMs) and prediction of cerebral palsy (CP) using computer vision software. Recordings between 9 and 17 weeks postterm age from 52 preterm and term infants (24 boys, 28 girls; 26 born preterm) were used. Recordings were analyzed using computer vision software. Movement variables, derived from differences between subsequent video frames, were used for quantitative analysis. Sensitivities, specificities, and area under curve were estimated for the first and second recording, or a mean of both. FMs were classified based on the Prechtl approach of general movement assessment. CP status was reported at 2 years. Nine children developed CP of whom all recordings had absent FMs. The mean variability of the centroid of motion (CSD) from two recordings was more accurate than using only one recording, and identified all children who were diagnosed with CP at 2 years. Age at assessment did not influence the detection of FMs or prediction of CP. The accuracy of computer vision techniques in identifying FMs and predicting CP based on two recordings should be confirmed in future studies.

  10. Pulmonary involvement in diffuse cutaneous systemic sclerosis: broncheoalveolar fluid granulocytosis predicts progression of fibrosing alveolitis

    PubMed Central

    Witt, C.; Borges, A.; John, M.; Fietze, I.; Baumann, G.; Krause, A.

    1999-01-01

    OBJECTIVE—The clinical course of fibrosing alveolitis (FA) in patients with systemic sclerosis (SSc) may vary considerably from stable condition for years to continuous fatal progression. This prospective study aimed at identifying the prognostic value of bronchoalveolar lavage fluid (BALF) analysis in FASSc.
METHODS—Seventy three consecutive patients with SSc and clinical signs of pulmonary involvement were enrolled. Every patient underwent clinical examination, lung function tests, computed tomography (CT), gallium scan, echocardiography, and bronchoalveolar lavage (BAL). Forty nine patients, 26 with pathological and 23 with normal BALF findings were prospectively followed up for two years and re-evaluated annually.
RESULTS—At baseline, 51 subjects (70%) showed radiological signs of lung fibrosis and/or alveolitis by CT and diffusion capacity for carbon monoxide (DLco) was decreased in 47 patients (64%). Thirty five patients (48%) had pathological BALF findings. BALF differential counts included BALF granulocytosis in 18, BALF lymphocytosis in 12, and a mixed increase of both granulocytes and lymphocytes in five patients. On follow up, a progression of FA with a significant decrease of DLco was only observed in patients with BALF granulocytosis. In contrast, patients with BALF lymphocytosis or normal BALF cell count had stable lung funtion parameters during the study period. In none of our patients echocardiography showed evidence of pulmonary hypertension.
CONCLUSION—BALF granulocytosis predicts progression of FA with deterioration of lung function, which is most sensitively monitored by DLco. Immunosuppressive treatment is recommended in patients with granulocytic FASSc.

 PMID:10491363

  11. The Use of Fluid Mechanics to Predict Regions of Microscopic Thrombus Formation in Pulsatile VADs.

    PubMed

    Topper, Stephen R; Navitsky, Michael A; Medvitz, Richard B; Paterson, Eric G; Siedlecki, Christopher A; Slattery, Margaret J; Deutsch, Steven; Rosenberg, Gerson; Manning, Keefe B

    2014-03-01

    We compare the velocity and shear obtained from particle image velocimetry (PIV) and computational fluid dynamics (CFD) in a pulsatile ventricular assist device (VAD) to further test our thrombus predictive methodology using microscopy data from an explanted VAD. To mimic physiological conditions in vitro, a mock circulatory loop is used with a blood analog that matched blood's viscoelastic behavior at 40% hematocrit. Under normal physiologic pressures and for a heart rate of 75 bpm, PIV data is acquired and wall shear maps are produced. The resolution of the PIV shear rate calculations are tested using the CFD and found to be in the same range. A bovine study, using a model of the 50 cc Penn State V-2 VAD, for 30 days at a constant beat rate of 75 beats per minute (bpm) provides the microscopic data whereby after the 30 days, the device is explanted and the sac surface analyzed using scanning electron microscopy (SEM) and, after immunofluorescent labeling for platelets and fibrin, confocal microscopy. Areas are examined based on PIV measurements and CFD, with special attention to low shear regions where platelet and fibrin deposition are most likely to occur. Data collected within the outlet port in a direction normal to the front wall of the VAD shows that some regions experience wall shear rates less than 500 s(-1), which increases the likelihood of platelet and fibrin deposition. Despite only one animal study, correlations between PIV, CFD, and in vivo data show promise. Deposition probability is quantified by the thrombus susceptibility potential, a calculation to correlate low shear and time of shear with deposition.

  12. Quasi-static magnetic measurements to predict specific absorption rates in magnetic fluid hyperthermia experiments

    NASA Astrophysics Data System (ADS)

    Coral, D. F.; Mendoza Zélis, P.; de Sousa, M. E.; Muraca, D.; Lassalle, V.; Nicolás, P.; Ferreira, M. L.; Fernández van Raap, M. B.

    2014-01-01

    In this work, the issue on whether dynamic magnetic properties of polydispersed magnetic colloids modeled using physical magnitudes derived from quasi-static magnetic measurement can be extrapolated to analyze specific absorption rate data acquired at high amplitudes and frequencies of excitation fields is addressed. To this end, we have analyzed two colloids of magnetite nanoparticles coated with oleic acid and chitosan in water displaying, under a radiofrequency field, high and low specific heat power release. Both colloids are alike in terms of liquid carrier, surfactant and magnetic phase composition but differ on the nanoparticle structuring. The colloid displaying low specific dissipation consists of spaced magnetic nanoparticles of mean size around 4.8 nm inside a large chitosan particle of 52.5 nm. The one displaying high specific dissipation consists of clusters of magnetic nanoparticles of mean size around 9.7 nm inside a chitosan particle of 48.6 nm. The experimental evaluation of Néel and Brown relaxation times (˜10-10 s and 10-4 s, respectively) indicate that the nanoparticles in both colloids magnetically relax by Néel mechanism. The isothermal magnetization curves analysis for this mechanism show that the magnetic nanoparticles behave in the interacting superparamagnetic regime. The specific absorption rates were determined calorimetrically at 260 kHz and up to 52 kA/m and were well modeled within linear response theory using the anisotropy density energy retrieved from quasi-static magnetic measurement, validating their use to predict heating ability of a given polydispersed particle suspension. Our findings provide new insight in the validity of quasi-static magnetic characterization to analyze the high frequency behavior of polydispersed colloids within the framework of the linear response and Wohlfarth theories and indicate that dipolar interactions play a key role being their strength larger for the colloid displaying higher dissipation, i

  13. Dose Addition Models Based on Biologically Relevant Reductions in Fetal Testosterone Accurately Predict Postnatal Reproductive Tract Alterations by a Phthalate Mixture in Rats

    PubMed Central

    Howdeshell, Kembra L.; Rider, Cynthia V.; Wilson, Vickie S.; Furr, Johnathan R.; Lambright, Christy R.; Gray, L. Earl

    2015-01-01

    Challenges in cumulative risk assessment of anti-androgenic phthalate mixtures include a lack of data on all the individual phthalates and difficulty determining the biological relevance of reduction in fetal testosterone (T) on postnatal development. The objectives of the current study were 2-fold: (1) to test whether a mixture model of dose addition based on the fetal T production data of individual phthalates would predict the effects of a 5 phthalate mixture on androgen-sensitive postnatal male reproductive tract development, and (2) to determine the biological relevance of the reductions in fetal T to induce abnormal postnatal reproductive tract development using data from the mixture study. We administered a dose range of the mixture (60, 40, 20, 10, and 5% of the top dose used in the previous fetal T production study consisting of 300 mg/kg per chemical of benzyl butyl (BBP), di(n)butyl (DBP), diethyl hexyl phthalate (DEHP), di-isobutyl phthalate (DiBP), and 100 mg dipentyl (DPP) phthalate/kg; the individual phthalates were present in equipotent doses based on their ability to reduce fetal T production) via gavage to Sprague Dawley rat dams on GD8-postnatal day 3. We compared observed mixture responses to predictions of dose addition based on the previously published potencies of the individual phthalates to reduce fetal T production relative to a reference chemical and published postnatal data for the reference chemical (called DAref). In addition, we predicted DA (called DAall) and response addition (RA) based on logistic regression analysis of all 5 individual phthalates when complete data were available. DA ref and DA all accurately predicted the observed mixture effect for 11 of 14 endpoints. Furthermore, reproductive tract malformations were seen in 17–100% of F1 males when fetal T production was reduced by about 25–72%, respectively. PMID:26350170

  14. Absolute Measurements of Macrophage Migration Inhibitory Factor and Interleukin-1-β mRNA Levels Accurately Predict Treatment Response in Depressed Patients

    PubMed Central

    Ferrari, Clarissa; Uher, Rudolf; Bocchio-Chiavetto, Luisella; Riva, Marco Andrea; Pariante, Carmine M.

    2016-01-01

    Background: Increased levels of inflammation have been associated with a poorer response to antidepressants in several clinical samples, but these findings have had been limited by low reproducibility of biomarker assays across laboratories, difficulty in predicting response probability on an individual basis, and unclear molecular mechanisms. Methods: Here we measured absolute mRNA values (a reliable quantitation of number of molecules) of Macrophage Migration Inhibitory Factor and interleukin-1β in a previously published sample from a randomized controlled trial comparing escitalopram vs nortriptyline (GENDEP) as well as in an independent, naturalistic replication sample. We then used linear discriminant analysis to calculate mRNA values cutoffs that best discriminated between responders and nonresponders after 12 weeks of antidepressants. As Macrophage Migration Inhibitory Factor and interleukin-1β might be involved in different pathways, we constructed a protein-protein interaction network by the Search Tool for the Retrieval of Interacting Genes/Proteins. Results: We identified cutoff values for the absolute mRNA measures that accurately predicted response probability on an individual basis, with positive predictive values and specificity for nonresponders of 100% in both samples (negative predictive value=82% to 85%, sensitivity=52% to 61%). Using network analysis, we identified different clusters of targets for these 2 cytokines, with Macrophage Migration Inhibitory Factor interacting predominantly with pathways involved in neurogenesis, neuroplasticity, and cell proliferation, and interleukin-1β interacting predominantly with pathways involved in the inflammasome complex, oxidative stress, and neurodegeneration. Conclusion: We believe that these data provide a clinically suitable approach to the personalization of antidepressant therapy: patients who have absolute mRNA values above the suggested cutoffs could be directed toward earlier access to more

  15. Discovery of a general method of solving the Schrödinger and dirac equations that opens a way to accurately predictive quantum chemistry.

    PubMed

    Nakatsuji, Hiroshi

    2012-09-18

    Just as Newtonian law governs classical physics, the Schrödinger equation (SE) and the relativistic Dirac equation (DE) rule the world of chemistry. So, if we can solve these equations accurately, we can use computation to predict chemistry precisely. However, for approximately 80 years after the discovery of these equations, chemists believed that they could not solve SE and DE for atoms and molecules that included many electrons. This Account reviews ideas developed over the past decade to further the goal of predictive quantum chemistry. Between 2000 and 2005, I discovered a general method of solving the SE and DE accurately. As a first inspiration, I formulated the structure of the exact wave function of the SE in a compact mathematical form. The explicit inclusion of the exact wave function's structure within the variational space allows for the calculation of the exact wave function as a solution of the variational method. Although this process sounds almost impossible, it is indeed possible, and I have published several formulations and applied them to solve the full configuration interaction (CI) with a very small number of variables. However, when I examined analytical solutions for atoms and molecules, the Hamiltonian integrals in their secular equations diverged. This singularity problem occurred in all atoms and molecules because it originates from the singularity of the Coulomb potential in their Hamiltonians. To overcome this problem, I first introduced the inverse SE and then the scaled SE. The latter simpler idea led to immediate and surprisingly accurate solution for the SEs of the hydrogen atom, helium atom, and hydrogen molecule. The free complement (FC) method, also called the free iterative CI (free ICI) method, was efficient for solving the SEs. In the FC method, the basis functions that span the exact wave function are produced by the Hamiltonian of the system and the zeroth-order wave function. These basis functions are called complement

  16. Joint Inversion of Marine Seismic and CSEM Data for Fluid Saturation Prediction

    NASA Astrophysics Data System (ADS)

    Hoversten, G. M.; Gasperikova, E.; Chen, J.; Newman, G.

    2005-12-01

    Recent developments in the application of controlled source marine electromagnetic (CSEM) data in petroleum exploration have brought this technology to the attention of many in exploration and production within the oil and gas industry. These developments are founded on more than two decades of research carried out in academia and at U.S. national laboratories. The commercial availability of CSEM data now makes it possible to consider integrating this new data with existing seismic data in ways that will add considerable value. In particular, the sensitivity of CSEM data to water saturation (Sw), when combined with the spatial and reservoir parameter sensitivity (porosity, Sw, gas saturation [Sg], and oil saturation [So]) of seismic data, can provide enhanced prediction of fluid saturations within existing or prospective reservoirs. There are many ways in which CSEM and seismic data can be combined to estimate reservoir parameters. The possibilities range from what we term cooperative inversion, in which both data sets are used without any formal linkage in the inversion of either, to fully coupled joint inversion, in which both data sets are inverted simultaneously to directly estimate reservoir parameters. Hoversten et al. (2003) present an example of the former, in which crosswell EM and seismic travel-time tomography are used to estimate reservoir parameters using time-lapse changes in shear velocity, electrical conductivity, and acoustic velocity to sequentially strip off the effects of pressure and water saturation before estimating oil and CO2 saturations. Direct reservoir parameter estimation by joint inversion was demonstrated by Hoversten et al. (2004) and Chen et al. (2004), where marine CSEM and AVA data were used in a formal joint inverse to estimate reservoir Sw, So, Sg, and porosity (φ). The formal joint inversion is currently being extended to replace the 1D CSEM solution with full 3D. While the development and testing of more computationally

  17. The Need for Accurate Risk Prediction Models for Road Mapping, Shared Decision Making and Care Planning for the Elderly with Advanced Chronic Kidney Disease.

    PubMed

    Stryckers, Marijke; Nagler, Evi V; Van Biesen, Wim

    2016-11-01

    As people age, chronic kidney disease becomes more common, but it rarely leads to end-stage kidney disease. When it does, the choice between dialysis and conservative care can be daunting, as much depends on life expectancy and personal expectations of medical care. Shared decision making implies adequately informing patients about their options, and facilitating deliberation of the available information, such that decisions are tailored to the individual's values and preferences. Accurate estimations of one's risk of progression to end-stage kidney disease and death with or without dialysis are essential for shared decision making to be effective. Formal risk prediction models can help, provided they are externally validated, well-calibrated and discriminative; include unambiguous and measureable variables; and come with readily applicable equations or scores. Reliable, externally validated risk prediction models for progression of chronic kidney disease to end-stage kidney disease or mortality in frail elderly with or without chronic kidney disease are scant. Within this paper, we discuss a number of promising models, highlighting both the strengths and limitations physicians should understand for using them judiciously, and emphasize the need for external validation over new development for further advancing the field.

  18. Method and Apparatus for Predicting Unsteady Pressure and Flow Rate Distribution in a Fluid Network

    NASA Technical Reports Server (NTRS)

    Majumdar, Alok K. (Inventor)

    2009-01-01

    A method and apparatus for analyzing steady state and transient flow in a complex fluid network, modeling phase changes, compressibility, mixture thermodynamics, external body forces such as gravity and centrifugal force and conjugate heat transfer. In some embodiments, a graphical user interface provides for the interactive development of a fluid network simulation having nodes and branches. In some embodiments, mass, energy, and specific conservation equations are solved at the nodes, and momentum conservation equations are solved in the branches. In some embodiments, contained herein are data objects for computing thermodynamic and thermophysical properties for fluids. In some embodiments, the systems of equations describing the fluid network are solved by a hybrid numerical method that is a combination of the Newton-Raphson and successive substitution methods.

  19. Mother's but not father's education predicts general fluid intelligence in emerging adulthood: Behavioral and neuroanatomical evidence.

    PubMed

    Kong, Feng; Chen, Zhencai; Xue, Song; Wang, Xu; Liu, Jia

    2015-11-01

    Lower parental education impairs cognitive abilities of their offspring such as general fluid intelligence dependent on the prefrontal cortex (PFC), but the independent contribution of mother's and father's education is unknown. We used an individual difference approach to test whether mother's and father's education independently affected general fluid intelligence in emerging adulthood at both the behavioral and neural level. Behaviorally, mother's but not father's education accounted for unique variance in general fluid intelligence in emerging adulthood (assessed by the Raven's advanced progressive matrices). Neurally, the whole-brain correlation analysis revealed that the regional gray matter volume (rGMV) in the medial PFC was related to both mother's education and general fluid intelligence but not father's education. Furthermore, after controlling for mother's education, the association between general fluid intelligence and the rGMV in medial PFC was no longer significant, indicating that mother's education plays an important role in influencing the structure of the medial PFC associated with general fluid intelligence. Taken together, our study provides the first behavioral and neural evidence that mother's education is a more important determinant of general cognitive ability in emerging adulthood than father's education.

  20. How Accurately Can Extended X-ray Absorption Spectra Be Predicted from First Principles? Implications for Modeling the Oxygen-Evolving Complex in Photosystem II.

    PubMed

    Beckwith, Martha A; Ames, William; Vila, Fernando D; Krewald, Vera; Pantazis, Dimitrios A; Mantel, Claire; Pécaut, Jacques; Gennari, Marcello; Duboc, Carole; Collomb, Marie-Noëlle; Yano, Junko; Rehr, John J; Neese, Frank; DeBeer, Serena

    2015-10-14

    First principle calculations of extended X-ray absorption fine structure (EXAFS) data have seen widespread use in bioinorganic chemistry, perhaps most notably for modeling the Mn4Ca site in the oxygen evolving complex (OEC) of photosystem II (PSII). The logic implied by the calculations rests on the assumption that it is possible to a priori predict an accurate EXAFS spectrum provided that the underlying geometric structure is correct. The present study investigates the extent to which this is possible using state of the art EXAFS theory. The FEFF program is used to evaluate the ability of a multiple scattering-based approach to directly calculate the EXAFS spectrum of crystallographically defined model complexes. The results of these parameter free predictions are compared with the more traditional approach of fitting FEFF calculated spectra to experimental data. A series of seven crystallographically characterized Mn monomers and dimers is used as a test set. The largest deviations between the FEFF calculated EXAFS spectra and the experimental EXAFS spectra arise from the amplitudes. The amplitude errors result from a combination of errors in calculated S0(2) and Debye-Waller values as well as uncertainties in background subtraction. Additional errors may be attributed to structural parameters, particularly in cases where reliable high-resolution crystal structures are not available. Based on these investigations, the strengths and weaknesses of using first-principle EXAFS calculations as a predictive tool are discussed. We demonstrate that a range of DFT optimized structures of the OEC may all be considered consistent with experimental EXAFS data and that caution must be exercised when using EXAFS data to obtain topological arrangements of complex clusters.

  1. The VACS Index Accurately Predicts Mortality and Treatment Response among Multi-Drug Resistant HIV Infected Patients Participating in the Options in Management with Antiretrovirals (OPTIMA) Study

    PubMed Central

    Brown, Sheldon T.; Tate, Janet P.; Kyriakides, Tassos C.; Kirkwood, Katherine A.; Holodniy, Mark; Goulet, Joseph L.; Angus, Brian J.; Cameron, D. William; Justice, Amy C.

    2014-01-01

    Objectives The VACS Index is highly predictive of all-cause mortality among HIV infected individuals within the first few years of combination antiretroviral therapy (cART). However, its accuracy among highly treatment experienced individuals and its responsiveness to treatment interventions have yet to be evaluated. We compared the accuracy and responsiveness of the VACS Index with a Restricted Index of age and traditional HIV biomarkers among patients enrolled in the OPTIMA study. Methods Using data from 324/339 (96%) patients in OPTIMA, we evaluated associations between indices and mortality using Kaplan-Meier estimates, proportional hazards models, Harrel’s C-statistic and net reclassification improvement (NRI). We also determined the association between study interventions and risk scores over time, and change in score and mortality. Results Both the Restricted Index (c = 0.70) and VACS Index (c = 0.74) predicted mortality from baseline, but discrimination was improved with the VACS Index (NRI = 23%). Change in score from baseline to 48 weeks was more strongly associated with survival for the VACS Index than the Restricted Index with respective hazard ratios of 0.26 (95% CI 0.14–0.49) and 0.39(95% CI 0.22–0.70) among the 25% most improved scores, and 2.08 (95% CI 1.27–3.38) and 1.51 (95%CI 0.90–2.53) for the 25% least improved scores. Conclusions The VACS Index predicts all-cause mortality more accurately among multi-drug resistant, treatment experienced individuals and is more responsive to changes in risk associated with treatment intervention than an index restricted to age and HIV biomarkers. The VACS Index holds promise as an intermediate outcome for intervention research. PMID:24667813

  2. Cerebrospinal Fluid IL-10 and IL-10/IL-6 as Accurate Diagnostic Biomarkers for Primary Central Nervous System Large B-cell Lymphoma

    PubMed Central

    Song, Yang; Zhang, Wei; Zhang, Li; Wu, Wei; Zhang, Yan; Han, Xiao; Yang, Chen; Zhang, Lu; Zhou, Daobin

    2016-01-01

    Early diagnosis of primary central nervous system lymphoma (PCNSL) represents a challenge, and cerebrospinal fluid (CSF) cytokines may be diagnostic biomarkers for PCNSL. We used an electrochemiluminescence immunoassay to measure interleukin (IL)-10, IL-6, IL-8 and tumor necrosis factor α (TNF-α) in the CSF of 22 B cell PCNSL patients and 80 patients with other CNS diseases. CSF IL-10 was significantly higher in PCNSL patients than in the control group (median 74.7 pg/ml vs < 5.0 pg/ml, P < 0.000). Using a CSF IL-10 cutoff value of 8.2 pg/ml, the diagnostic sensitivity and specificity were 95.5% and 96.1%, respectively (AUC, 0.957; 95% CI, 0.901–1.000). For a CSF IL-10/IL-6 cutoff value of 0.72, the sensitivity was 95.5%, and the specificity was 100.0% (AUC, 0.976; 95% CI, 0.929–1.000). An increased CSF IL-10 level at diagnosis and post-treatment was associated with poor Progression free survival (PFS) for patients with PCNSL (P = 0.0181 and P = 0.0002, respectively). A low diagnostic value for PCNSL was found with CSF IL-8 or TNF-α. In conclusion, increased CSF IL-10 was a reliable diagnostic biomarker for large B cell PCNSL, and an IL-10/IL-6 ratio facilitates differentiation from other conditions, especially a CNS infection. PMID:27924864

  3. Toward Relatively General and Accurate Quantum Chemical Predictions of Solid-State (17)O NMR Chemical Shifts in Various Biologically Relevant Oxygen-Containing Compounds.

    PubMed

    Rorick, Amber; Michael, Matthew A; Yang, Liu; Zhang, Yong

    2015-09-03

    Oxygen is an important element in most biologically significant molecules, and experimental solid-state (17)O NMR studies have provided numerous useful structural probes to study these systems. However, computational predictions of solid-state (17)O NMR chemical shift tensor properties are still challenging in many cases, and in particular, each of the prior computational works is basically limited to one type of oxygen-containing system. This work provides the first systematic study of the effects of geometry refinement, method, and basis sets for metal and nonmetal elements in both geometry optimization and NMR property calculations of some biologically relevant oxygen-containing compounds with a good variety of XO bonding groups (X = H, C, N, P, and metal). The experimental range studied is of 1455 ppm, a major part of the reported (17)O NMR chemical shifts in organic and organometallic compounds. A number of computational factors toward relatively general and accurate predictions of (17)O NMR chemical shifts were studied to provide helpful and detailed suggestions for future work. For the studied kinds of oxygen-containing compounds, the best computational approach results in a theory-versus-experiment correlation coefficient (R(2)) value of 0.9880 and a mean absolute deviation of 13 ppm (1.9% of the experimental range) for isotropic NMR shifts and an R(2) value of 0.9926 for all shift-tensor properties. These results shall facilitate future computational studies of (17)O NMR chemical shifts in many biologically relevant systems, and the high accuracy may also help the refinement and determination of active-site structures of some oxygen-containing substrate-bound proteins.

  4. Predictive Role of ADA in Bronchoalveolar Lavage Fluid in Making the Diagnosis of Pulmonary Tuberculosis.

    PubMed

    Binesh, Fariba; Halvani, Abolhassan

    2013-01-01

    Current diagnostic tests for tuberculosis (TB) are time-consuming. The aim of this study was to evaluate the diagnostic usefulness of ADA in bronchoalveolar lavage fluid in patients with pulmonary TB. A cross-sectional study was performed in Yazd, Iran, between 2009 and 2010. Patients suspected of pulmonary TB with negative sputum smear for AFB were included in the study. Mean ADA levels in BAL fluids were measured and compared between study groups. Sixty-three patients were enrolled in the study among which 15 cases had pulmonary TB, 33 had pulmonary diseases other than TB, and 15 subjects with normal bronchoscopy results were considered as controls. Mean ADA levels in BAL fluid were 4.13 ± 2.55, 2.42 ± 1.06, and 1.93 ± 0.88, respectively. This rate was significantly higher in the pulmonary TB group compared to the other two groups (P = 0.001). Using ROC curve with a cut-off value of 3.5 IU/L, the highest sensitivity (57%) and specificity (84%) were obtained in diagnosis of TB. The results showed that although ADA activity in BAL fluid of pulmonary TB patients was higher than those seen in other diseases, a negative test does not rule out pulmonary TB.

  5. Catalytic ferrous iron in amniotic fluid as a predictive marker of human maternal-fetal disorders.

    PubMed

    Hattori, Yuka; Mukaide, Takahiro; Jiang, Li; Kotani, Tomomi; Tsuda, Hiroyuki; Mano, Yukio; Sumigama, Seiji; Hirayama, Tasuku; Nagasawa, Hideko; Kikkawa, Fumitaka; Toyokuni, Shinya

    2015-01-01

    Amniotic fluid contains numerous biomolecules derived from fetus and mother, thus providing precious information on pregnancy. Here, we evaluated oxidative stress of human amniotic fluid and measured the concentration of catalytic Fe(II). Amniotic fluid samples were collected with consent from a total of 89 subjects in Nagoya University Hospital, under necessary medical interventions: normal pregnancy at term, normal pregnancy at the 2nd trimester, preterm delivery with maternal disorders but without fetal disorders, congenital diaphragmatic hernia, fetal growth restriction, pregnancy-induced hypertension, gestational diabetes mellitus, Down syndrome and trisomy 18. Catalytic Fe(II) and oxidative stress markers (8-hydroxy-2'-deoxyguanosine, 8-OHdG; dityrosine) were determined with RhoNox-1 and specific antibodies, respectively, using plate assays. Levels of 8-OHdG and dityrosine were higher in the 3rd trimester compared with the 2nd trimester in normal subjects, and the abnormal groups generally showed lower levels than the controls, thus suggesting that they represent fetal metabolic activities. In contrast, catalytic Fe(II) was higher in the 2nd trimester than the 3rd trimester in the normal subjects, and overall the abnormal groups showed higher levels than the controls, suggesting that high catalytic Fe(II) at late gestation reflects fetal pathologic alterations. Notably, products of H2O2 and catalytic Fe(II) remained almost constant in amniotic fluid.

  6. Integrating trans-abdominal ultrasonography with fecal steroid metabolite monitoring to accurately diagnose pregnancy and predict the timing of parturition in the red panda (Ailurus fulgens styani).

    PubMed

    Curry, Erin; Browning, Lissa J; Reinhart, Paul; Roth, Terri L

    2017-02-23

    Red pandas (Ailurus fulgens styani) exhibit a variable gestation length and may experience a pseudopregnancy indistinguishable from true pregnancy; therefore, it is not possible to deduce an individual's true pregnancy status and parturition date based on breeding dates or fecal progesterone excretion patterns alone. The goal of this study was to evaluate the use of transabdominal ultrasonography for pregnancy diagnosis in red pandas. Two to three females were monitored over 4 consecutive years, generating a total of seven profiles (four pregnancies, two pseudopregnancies, and one lost pregnancy). Fecal samples were collected and assayed for progesterone (P4) and estrogen conjugate (EC) to characterize patterns associated with breeding activity and parturition events. Animals were trained for voluntary transabdominal ultrasound and examinations were performed weekly. Breeding behaviors and fecal EC data suggest that the estrus cycle of this species is 11-12 days in length. Fecal steroid metabolite analyses also revealed that neither P4 nor EC concentrations were suitable indicators of pregnancy in this species; however, a secondary increase in P4 occurred 69-71 days prior to parturition in all pregnant females, presumably coinciding with embryo implantation. Using ultrasonography, embryos were detected as early as 62 days post-breeding/50 days pre-partum and serial measurements of uterine lumen diameter were documented throughout four pregnancies. Advances in reproductive diagnostics, such as the implementation of ultrasonography, may facilitate improved husbandry of pregnant females and allow for the accurate prediction of parturition.

  7. FDG-PET measurement is more accurate than neuropsychological assessments to predict global cognitive deterioration in patients with mild cognitive impairment.

    PubMed

    Chételat, Gaël; Eustache, Francis; Viader, Fausto; De La Sayette, Vincent; Pélerin, Alice; Mézenge, Florence; Hannequin, Didier; Dupuy, Benoît; Baron, Jean-Claude; Desgranges, Béatrice

    2005-02-01

    The accurate prediction, at a pre-dementia stage of Alzheimer's disease (AD), of the subsequent clinical evolution of patients would be a major breakthrough from both therapeutic and research standpoints. Amnestic mild cognitive impairment (MCI) is presently the most common reference to address the pre-dementia stage of AD. However, previous longitudinal studies on patients with MCI assessing neuropsychological and PET markers of future conversion to AD are sparse and yield discrepant findings, while a comprehensive comparison of the relative accuracy of these two categories of measure is still lacking. In the present study, we assessed the global cognitive decline as measured by the Mattis scale in 18 patients with amnestic MCI over an 18-month follow-up period, studying which subtest of this scale showed significant deterioration over time. Using baseline measurements from neuropsychological evaluation of memory and PET, we then assessed significant markers of global cognitive change, that is, percent annual change in the Mattis scale total score, and searched for the best predictor of this global cognitive decline. Altogether, our results revealed significant decline over the 18-month follow-up period in the total score and the verbal initiation and memory-recall subscores of the Mattis scale. The percent annual change in the total Mattis score significantly correlated with age and baseline performances in delayed episodic memory recall as well as semantic autobiographical and category word fluencies. Regarding functional imaging, significant correlations were also found with baseline PET values in the right temporo-parietal and medial frontal areas. Age and right temporo-parietal PET values were the most significant predictors of subsequent global cognitive decline, and the only ones to survive stepwise regression analyses. Our findings are consistent with previous works showing predominant delayed recall and semantic memory impairment at a pre-dementia stage

  8. Computational fluid dynamics prediction of blood damage in a centrifugal pump.

    PubMed

    Song, Xinwei; Throckmorton, Amy L; Wood, Houston G; Antaki, James F; Olsen, Don B

    2003-10-01

    This study explores a quantitative evaluation of blood damage that occurs in a continuous flow left ventricular assist device due to fluid stress. Computational fluid dynamics (CFD) analysis is used to track the shear stress history of 388 particle streaklines. The accumulation of shear and exposure time is integrated along the streaklines to evaluate the levels of blood trauma. This analysis, which includes viscous and turbulent stresses, provides a statistical estimate of possible damage to cells flowing through the pump. In vitro normalized index of hemolysis values for clinically available ventricular assist devices were compared to our damage indices. This allowed for an order of magnitude comparison between our estimations and experimentally measured hemolysis levels, which resulted in a reasonable correlation. This work ultimately demonstrates that CFD is a convenient and effective approach to analyze the Lagranian behavior of blood in a heart assist device.

  9. WETTABILITY AND PREDICTION OF OIL RECOVERY FROM RESERVOIRS DEVELOPED WITH MODERN DRILLING AND COMPLETION FLUIDS

    SciTech Connect

    Jill S. Buckley; Norman R. Morrow

    2004-11-01

    Contamination of crude oils by surface-active agents from drilling fluids or other oil-field chemicals is more difficult to detect and quantify than bulk contamination with, for example, base fluids from oil-based muds. Bulk contamination can be detected by gas chromatography or other common analytical techniques, but surface-active contaminants can be influential at much lower concentrations that are more difficult to detect analytically, especially in the context of a mixture as complex as a crude oil. In this report we present a baseline study of interfacial tensions of 39 well-characterized crude oil samples with aqueous phases that vary in pH and ionic composition. This extensive study will provide the basis for assessing the effects of surface-active contaminant on interfacial tension and other surface properties of crude oil/brine/rock ensembles.

  10. FRACTURING FLUID CHARACTERIZATION FACILITY

    SciTech Connect

    Subhash Shah

    2000-08-01

    Hydraulic fracturing technology has been successfully applied for well stimulation of low and high permeability reservoirs for numerous years. Treatment optimization and improved economics have always been the key to the success and it is more so when the reservoirs under consideration are marginal. Fluids are widely used for the stimulation of wells. The Fracturing Fluid Characterization Facility (FFCF) has been established to provide the accurate prediction of the behavior of complex fracturing fluids under downhole conditions. The primary focus of the facility is to provide valuable insight into the various mechanisms that govern the flow of fracturing fluids and slurries through hydraulically created fractures. During the time between September 30, 1992, and March 31, 2000, the research efforts were devoted to the areas of fluid rheology, proppant transport, proppant flowback, dynamic fluid loss, perforation pressure losses, and frictional pressure losses. In this regard, a unique above-the-ground fracture simulator was designed and constructed at the FFCF, labeled ''The High Pressure Simulator'' (HPS). The FFCF is now available to industry for characterizing and understanding the behavior of complex fluid systems. To better reflect and encompass the broad spectrum of the petroleum industry, the FFCF now operates under a new name of ''The Well Construction Technology Center'' (WCTC). This report documents the summary of the activities performed during 1992-2000 at the FFCF.

  11. Prediction of the wall factor of arbitrary particle settling through various fluid media in a cylindrical tube using artificial intelligence.

    PubMed

    Li, Mingzhong; Zhang, Guodong; Xue, Jianquan; Li, Yanchao; Tang, Shukai

    2014-01-01

    Considering the influence of particle shape and the rheological properties of fluid, two artificial intelligence methods (Artificial Neural Network and Support Vector Machine) were used to predict the wall factor which is widely introduced to deduce the net hydrodynamic drag force of confining boundaries on settling particles. 513 data points were culled from the experimental data of previous studies, which were divided into training set and test set. Particles with various shapes were divided into three kinds: sphere, cylinder, and rectangular prism; feature parameters of each kind of particle were extracted; prediction models of sphere and cylinder using artificial neural network were established. Due to the little number of rectangular prism sample, support vector machine was used to predict the wall factor, which is more suitable for addressing the problem of small samples. The characteristic dimension was presented to describe the shape and size of the diverse particles and a comprehensive prediction model of particles with arbitrary shapes was established to cover all types of conditions. Comparisons were conducted between the predicted values and the experimental results.

  12. IMPre: An Accurate and Efficient Software for Prediction of T- and B-Cell Receptor Germline Genes and Alleles from Rearranged Repertoire Data

    PubMed Central

    Zhang, Wei; Wang, I-Ming; Wang, Changxi; Lin, Liya; Chai, Xianghua; Wu, Jinghua; Bett, Andrew J.; Dhanasekaran, Govindarajan; Casimiro, Danilo R.; Liu, Xiao

    2016-01-01

    Large-scale study of the properties of T-cell receptor (TCR) and B-cell receptor (BCR) repertoires through next-generation sequencing is providing excellent insights into the understanding of adaptive immune responses. Variable(Diversity)Joining [V(D)J] germline genes and alleles must be characterized in detail to facilitate repertoire analyses. However, most species do not have well-characterized TCR/BCR germline genes because of their high homology. Also, more germline alleles are required for humans and other species, which limits the capacity for studying immune repertoires. Herein, we developed “Immune Germline Prediction” (IMPre), a tool for predicting germline V/J genes and alleles using deep-sequencing data derived from TCR/BCR repertoires. We developed a new algorithm, “Seed_Clust,” for clustering, produced a multiway tree for assembly and optimized the sequence according to the characteristics of rearrangement. We trained IMPre on human samples of T-cell receptor beta (TRB) and immunoglobulin heavy chain and then tested it on additional human samples. Accuracy of 97.7, 100, 92.9, and 100% was obtained for TRBV, TRBJ, IGHV, and IGHJ, respectively. Analyses of subsampling performance for these samples showed IMPre to be robust using different data quantities. Subsequently, IMPre was tested on samples from rhesus monkeys and human long sequences: the highly accurate results demonstrated IMPre to be stable with animal and multiple data types. With rapid accumulation of high-throughput sequence data for TCR and BCR repertoires, IMPre can be applied broadly for obtaining novel genes and a large number of novel alleles. IMPre is available at https://github.com/zhangwei2015/IMPre. PMID:27867380

  13. Cosmological constraints from the CFHTLenS shear measurements using a new, accurate, and flexible way of predicting non-linear mass clustering

    NASA Astrophysics Data System (ADS)

    Angulo, Raul E.; Hilbert, Stefan

    2015-03-01

    We explore the cosmological constraints from cosmic shear using a new way of modelling the non-linear matter correlation functions. The new formalism extends the method of Angulo & White, which manipulates outputs of N-body simulations to represent the 3D non-linear mass distribution in different cosmological scenarios. We show that predictions from our approach for shear two-point correlations at 1-300 arcmin separations are accurate at the ˜10 per cent level, even for extreme changes in cosmology. For moderate changes, with target cosmologies similar to that preferred by analyses of recent Planck data, the accuracy is close to ˜5 per cent. We combine this approach with a Monte Carlo Markov chain sampler to explore constraints on a Λ cold dark matter model from the shear correlation functions measured in the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS). We obtain constraints on the parameter combination σ8(Ωm/0.27)0.6 = 0.801 ± 0.028. Combined with results from cosmic microwave background data, we obtain marginalized constraints on σ8 = 0.81 ± 0.01 and Ωm = 0.29 ± 0.01. These results are statistically compatible with previous analyses, which supports the validity of our approach. We discuss the advantages of our method and the potential it offers, including a path to model in detail (i) the effects of baryons, (ii) high-order shear correlation functions, and (iii) galaxy-galaxy lensing, among others, in future high-precision cosmological analyses.

  14. Oscillatory fluid flow in deformable tubes: Implications for pore-scale hydromechanics from comparing experimental observations with theoretical predictions.

    PubMed

    Kurzeja, Patrick; Steeb, Holger; Strutz, Marc A; Renner, Jörg

    2016-12-01

    Oscillatory flow of four fluids (air, water, two aqueous sodium-tungstate solutions) was excited at frequencies up to 250 Hz in tubes of two materials (steel, silicone) covering a wide range in length, diameter, and thickness. The hydrodynamical response was characterized by phase shift and amplitude ratio between pressures in an upstream (pressure excitation) and a downstream reservoir connected by the tubes. The resulting standing flow waves reflect viscosity-controlled diffusive behavior and inertia-controlled wave behavior for oscillation frequencies relatively low and high compared to Biot's critical frequency, respectively. Rigid-tube theories correspond well with the experimental results for steel tubes filled with air or water. The wave modes observed for silicone tubes filled with the rather incompressible liquids or air, however, require accounting for the solid's shear and bulk modulus to correctly predict speed of pressure propagation and deformation mode. The shear mode may be responsible for significant macroscopic attenuation in porous materials with effective frame-shear moduli lower than the bulk modulus of the pore fluid. Despite notable effects of the ratio of densities and of acoustic and shear velocity of fluid and solid, Biot's frequency remains an approximate indicator of the transition from the viscosity to the inertia controlled regime.

  15. Investigations of Fluid-Structure-Coupling and Turbulence Model Effects on the DLR Results of the Fifth AIAA CFD Drag Prediction Workshop

    NASA Technical Reports Server (NTRS)

    Keye, Stefan; Togiti, Vamish; Eisfeld, Bernhard; Brodersen, Olaf P.; Rivers, Melissa B.

    2013-01-01

    The accurate calculation of aerodynamic forces and moments is of significant importance during the design phase of an aircraft. Reynolds-averaged Navier-Stokes (RANS) based Computational Fluid Dynamics (CFD) has been strongly developed over the last two decades regarding robustness, efficiency, and capabilities for aerodynamically complex configurations. Incremental aerodynamic coefficients of different designs can be calculated with an acceptable reliability at the cruise design point of transonic aircraft for non-separated flows. But regarding absolute values as well as increments at off-design significant challenges still exist to compute aerodynamic data and the underlying flow physics with the accuracy required. In addition to drag, pitching moments are difficult to predict because small deviations of the pressure distributions, e.g. due to neglecting wing bending and twisting caused by the aerodynamic loads can result in large discrepancies compared to experimental data. Flow separations that start to develop at off-design conditions, e.g. in corner-flows, at trailing edges, or shock induced, can have a strong impact on the predictions of aerodynamic coefficients too. Based on these challenges faced by the CFD community a working group of the AIAA Applied Aerodynamics Technical Committee initiated in 2001 the CFD Drag Prediction Workshop (DPW) series resulting in five international workshops. The results of the participants and the committee are summarized in more than 120 papers. The latest, fifth workshop took place in June 2012 in conjunction with the 30th AIAA Applied Aerodynamics Conference. The results in this paper will evaluate the influence of static aeroelastic wing deformations onto pressure distributions and overall aerodynamic coefficients based on the NASA finite element structural model and the common grids.

  16. Fluid mechanics of dynamic stall. II - Prediction of full scale characteristics

    NASA Technical Reports Server (NTRS)

    Ericsson, L. E.; Reding, J. P.

    1988-01-01

    Analytical extrapolations are made from experimental subscale dynamics to predict full scale characteristics of dynamic stall. The method proceeds by establishing analytic relationships between dynamic and static aerodynamic characteristics induced by viscous flow effects. The method is then validated by predicting dynamic test results on the basis of corresponding static test data obtained at the same subscale flow conditions, and the effect of Reynolds number on the static aerodynamic characteristics are determined from subscale to full scale flow conditions.

  17. Turbofan forced mixer-nozzle internal flowfield. Volume 2: Computational fluid dynamic predictions

    NASA Technical Reports Server (NTRS)

    Werle, M. J.; Vasta, V. N.

    1982-01-01

    A general program was conducted to develop and assess a computational method for predicting the flow properties in a turbofan forced mixed duct. The detail assessment of the resulting computer code is presented. It was found that the code provided excellent predictions of the kinematics of the mixing process throughout the entire length of the mixer nozzle. The thermal mixing process between the hot core and cold fan flows was found to be well represented in the low speed portion of the flowfield.

  18. Prediction of acoustic radiation from functionally graded shells of revolution in light and heavy fluids

    NASA Astrophysics Data System (ADS)

    Qu, Yegao; Meng, Guang

    2016-08-01

    This paper presents a semi-analytical method for the vibro-acoustic analysis of a functionally graded shell of revolution immersed in an infinite light or heavy fluid. The structural model of the shell is formulated on the basis of a modified variational method combined with a multi-segment technique, whereas a spectral Kirchhoff-Helmholtz integral formulation is employed to model the exterior fluid field. The material properties of the shell are estimated by using the Voigt's rule of mixture and the Mori-Tanaka's homogenization scheme. Displacement and sound pressure variables of each segment are expanded in the form of a mixed series using Fourier series and Chebyshev orthogonal polynomials. A set of collocation nodes distributed over the roots of Chebyshev polynomials are employed to establish the algebraic system of the acoustic integral equations, and the non-uniqueness solution is eliminated using a combined Helmholtz integral equation formulation. Loosely and strongly coupled schemes are implemented for the structure-acoustic interaction problem of a functionally graded shell immersed in a light and heavy fluid, respectively. The present method provides a flexible way to account for the individual contributions of circumferential wave modes to the vibration and acoustic responses of functionally graded shells of revolution in an analytical manner. Numerical tests are presented for sound radiation problems of spherical, cylindrical, conical and coupled shells. The individual contributions of the circumferential modes to the radiated sound pressure and sound power of functionally graded shells are observed. Effects of the material profile on the sound radiation of the shells are also investigated.

  19. PGE(2) in pancreatic cyst fluid helps differentiate IPMN from MCN and predict IPMN dysplasia.

    PubMed

    Schmidt, C Max; Yip-Schneider, Michele T; Ralstin, Matthew C; Wentz, Sabrina; DeWitt, John; Sherman, Stuart; Howard, Thomas J; McHenry, Lee; Dutkevitch, Sarah; Goggins, Michael; Nakeeb, Attila; Lillemoe, Keith D

    2008-02-01

    Current management of intraductal papillary mucinous neoplasm (IPMN) according to recently published International Consensus Guidelines depends upon distinguishing it from mucinous cystic neoplasms (MCNs). We have previously shown that prostaglandin E(2) (PGE(2)) is increased in pancreatic cancer tissue over normal controls. Thus, we hypothesized that PGE(2) level in pancreatic fluid differentiates IPMN and MCN and is a biomarker of IPMN dysplasia. Pancreatic fluid was collected in 65 patients at the time of endoscopy (EUS or ERCP) or operation (OR) and analyzed by PGE(2) enzyme-linked immunosorbent assay (ELISA). PGE(2) level was correlated with surgical pathologic diagnosis and dysplastic stage. Mean PGE(2) level (pg/microl) in IPMNs (2.2 +/- 0.6) was greater than in MCNs (0.2 +/- 0.1) (p < 0.05). Mean PGE(2) level of IPMN by dysplastic stage was 0.1 +/- 0.01 (low grade), 1.2 +/- 0.6 (medium grade), 4.4 +/- 0.9 (high grade), and 5.0 +/- 2.3 (invasive). Among invasive IPMN, PGE(2) level dropped in advanced cases with pancreatic ductal obstruction by tumor (0.3 +/- 0) vs non-obstructed (8.6 +/- 2.9). PGE(2) level may help in distinguishing IPMN from MCN in patients with known mucinous lesions. PGE(2) level may also be an indicator of malignant progression of IPMN before ductal obstruction by tumor. Prospective evaluation will be necessary to evaluate the clinical role of PGE(2) level in pancreatic fluid.

  20. Proteomic Analysis of Early Mid-Trimester Amniotic Fluid Does Not Predict Spontaneous Preterm Delivery

    PubMed Central

    Lenco, Juraj; Vajrychova, Marie; Link, Marek; Tambor, Vojtech; Liman, Victor; Bullarbo, Maria; Nilsson, Staffan; Tsiartas, Panagiotis; Cobo, Teresa; Kacerovsky, Marian; Jacobsson, Bo

    2016-01-01

    Objective The aim of this study was to identify early proteomic biomarkers of spontaneous preterm delivery (PTD) in mid-trimester amniotic fluid from asymptomatic women. Methods This is a case-cohort study. Amniotic fluid from mid-trimester genetic amniocentesis (14–19 weeks of gestation) was collected from 2008 to 2011. The analysis was conducted in 24 healthy women with subsequent spontaneous PTD (cases) and 40 randomly selected healthy women delivering at term (controls). An exploratory phase with proteomics analysis of pooled samples was followed by a verification phase with ELISA of individual case and control samples. Results The median (interquartile range (IQR: 25th; 75th percentiles) gestational age at delivery was 35+5 (33+6–36+6) weeks in women with spontaneous PTD and 40+0 (39+1–40+5) weeks in women who delivered at term. In the exploratory phase, the most pronounced differences were found in C-reactive protein (CRP) levels, that were approximately two-fold higher in the pooled case samples than in the pooled control samples. However, we could not verify these differences with ELISA. The median (25th; 75th IQR) CRP level was 95.2 ng/mL (64.3; 163.5) in women with spontaneous PTD and 86.0 ng/mL (51.2; 145.8) in women delivering at term (p = 0.37; t-test). Conclusions Proteomic analysis with mass spectrometry of mid-trimester amniotic fluid suggests CRP as a potential marker of spontaneous preterm delivery, but this prognostic potential was not verified with ELISA. PMID:27214132

  1. Identifying Thoracic Malignancies Through Pleural Fluid Biomarkers: A Predictive Multivariate Model.

    PubMed

    Porcel, José M; Esquerda, Aureli; Martínez-Alonso, Montserrat; Bielsa, Silvia; Salud, Antonieta

    2016-03-01

    The diagnosis of malignant pleural effusions may be challenging when cytological examination of aspirated pleural fluid is equivocal or noncontributory. The purpose of this study was to identify protein candidate biomarkers differentially expressed in the pleural fluid of patients with mesothelioma, lung adenocarcinoma, lymphoma, and tuberculosis (TB).A multiplex protein biochip comprising 120 biomarkers was used to determine the pleural fluid protein profile of 29 mesotheliomas, 29 lung adenocarcinomas, 12 lymphomas, and 35 tuberculosis. The relative abundance of these predetermined biomarkers among groups served to establish the differential diagnosis of: malignant versus benign (TB) effusions, lung adenocarcinoma versus mesothelioma, and lymphoma versus TB. The selected putative markers were validated using widely available commercial techniques in an independent sample of 102 patients.Significant differences were found in the protein expressions of metalloproteinase-9 (MMP-9), cathepsin-B, C-reactive protein, and chondroitin sulfate between malignant and TB effusions. When integrated into a scoring model, these proteins yielded 85% sensitivity, 100% specificity, and an area under the curve (AUC) of 0.98 for labeling malignancy in the verification sample. For lung adenocarcinoma-mesothelioma discrimination, combining CA19-9, CA15-3, and kallikrein-12 had maximal discriminatory capacity (65% sensitivity, 100% specificity, AUC 0.94); figures which also refer to the validation set. Last, cathepsin-B in isolation was only moderately useful (sensitivity 89%, specificity 62%, AUC 0.75) in separating lymphomatous and TB effusions. However, this last differentiation improved significantly when cathepsin-B was used with respect to the patient's age (sensitivity 72%, specificity 100%, AUC 0.94).In conclusion, panels of 4 (i.e., MMP-9, cathepsin-B, C-reactive protein, chondroitin sulfate), or 3 (i.e., CA19-9, CA15-3, kallikrein-12) different protein biomarkers on pleural

  2. WETTABILITY AND PREDICTION OF OIL RECOVERY FROM RESERVOIRS DEVELOPED WITH MODERN DRILLING AND COMPLETION FLUIDS

    SciTech Connect

    Jill S. Buckley; Norman R. Morrow

    2006-01-01

    The objectives of this project are: (1) to improve understanding of the wettability alteration of mixed-wet rocks that results from contact with the components of synthetic oil-based drilling and completion fluids formulated to meet the needs of arctic drilling; (2) to investigate cleaning methods to reverse the wettability alteration of mixed-wet cores caused by contact with these SBM components; and (3) to develop new approaches to restoration of wetting that will permit the use of cores drilled with SBM formulations for valid studies of reservoir properties.

  3. WETTABILITY AND PREDICTION OF OIL RECOVERY FROM RESERVOIRS DEVELOPED WITH MODERN DRILLING AND COMPLETION FLUIDS

    SciTech Connect

    Jill S. Buckley; Norman R. Morrow

    2003-10-01

    In this report we focus on surface studies of the wetting effects of SBM components; three areas of research are covered. First we present results of tests of interfacial properties of some commercial emulsifiers that are routinely used in both oil-based and synthetic oil-based drilling fluids. These products fall into two main groups, based on their CMC and IFT trends with changing pH. All can alter the wetting of mica, but measurements vary widely depending on the details of exposure and observation protocols. Non-equilibrium effects appear to be responsible for these variations, with equilibrated fluids generally giving lower contact angles than those observed with fluids that have not been pre-equilibrated. Addition of small amounts of emulsifier can increase the tendency of a crude oil to alter wetting of mica surfaces. The effects of similar amounts of these emulsifiers can be detected in interfacial tension measurements. Next, we report on the preliminary results of a study of polyethoxylated amines of varying structures on the wetting of mica surfaces. Contact angles have been measured for unequilibrated and pre-equilibrated fluids. Reduction in contact angles was generally observed when the surfaces were washed with toluene after exposure to surfactant solutions. Atomic forces microscopy is also being used to observe the interactions between these surfactants and mica surfaces. Finally, we show the results of a study of asphaltene stability in the presence of synthetic base oils. Most of the base oils in current use are paraffinic or olefinic--the aromatic content is minimized for environmental reasons--and they destabilize asphaltenes. Tests with two crude oils show onset conditions for base oils that are comparable to n-heptane and n-pentadecane in terms of the solubility conditions at the onset. Two ester-based products, Petrofree and Petrofree LV, did not cause asphaltene flocculation in these tests. A meeting of the research groups from New Mexico

  4. Fast Prediction of Wing Rock Onset Based on Computational Fluid Dynamics

    DTIC Science & Technology

    2005-09-14

    discretised using a central differencing scheme, and the convective terms are discretised using Osher’s ap- proximate Riemann solver with MUSCL interpolation...respect to the fluid unknowns wa. The residual for one cell in the grid is built up from fluxes. Following the usual approach for Riemann solvers, fi,j...fi,j(wl,wr) wherewl = wl(wi−2,j,wi−1,j,wi,j,wi+1,j) andwr = wr(wi−1,j,wi,j,wi+1,j,wi+2,j). Here fi,j is computed using Osher’s [26] approximate Riemann

  5. Application of a single-fluid model for the steam condensing flow prediction

    NASA Astrophysics Data System (ADS)

    Smołka, K.; Dykas, S.; Majkut, M.; Strozik, M.

    2016-10-01

    One of the results of many years of research conducted in the Institute of Power Engineering and Turbomachinery of the Silesian University of Technology are computational algorithms for modelling steam flows with a non-equilibrium condensation process. In parallel with theoretical and numerical research, works were also started on experimental testing of the steam condensing flow. This paper presents a comparison of calculations of a flow field modelled by means of a single-fluid model using both an in-house CFD code and the commercial Ansys CFX v16.2 software package. The calculation results are compared to inhouse experimental testing.

  6. Flow field prediction in full-scale Carrousel oxidation ditch by using computational fluid dynamics.

    PubMed

    Yang, Yin; Wu, Yingying; Yang, Xiao; Zhang, Kai; Yang, Jiakuan

    2010-01-01

    In order to optimize the flow field in a full-scale Carrousel oxidation ditch with many sets of disc aerators operating simultaneously, an experimentally validated numerical tool, based on computational fluid dynamics (CFD), was proposed. A full-scale, closed-loop bioreactor (Carrousel oxidation ditch) in Ping Dingshan Sewage Treatment Plant in Ping Dingshan City, a medium-sized city in Henan Province of China, was evaluated using CFD. Moving wall model was created to simulate many sets of disc aerators which created fluid motion in the ditch. The simulated results were acceptable compared with the experimental data and the following results were obtained: (1) a new method called moving wall model could simulate the flow field in Carrousel oxidation ditch with many sets of disc aerators operating simultaneously. The whole number of cells of grids decreased significantly, thus the calculation amount decreased, and (2) CFD modeling generally characterized the flow pattern in the full-scale tank. 3D simulation could be a good supplement for improving the hydrodynamic performance in oxidation ditch designs.

  7. Optimization of crystal nucleation close to a metastable fluid-fluid phase transition.

    PubMed

    Wedekind, Jan; Xu, Limei; Buldyrev, Sergey V; Stanley, H Eugene; Reguera, David; Franzese, Giancarlo

    2015-06-22

    The presence of a metastable fluid-fluid critical point is thought to dramatically influence the crystallization pathway, increasing the nucleation rate by many orders of magnitude over the predictions of classical nucleation theory. We use molecular dynamics simulations to study the kinetics of crystallization in the vicinity of this metastable critical point and throughout the metastable fluid-fluid phase diagram. To quantitatively understand how the fluid-fluid phase separation affects the crystal nucleation, we evaluate accurately the kinetics and reconstruct the thermodynamic free-energy landscape of crystal formation. Contrary to expectations, we find no special advantage of the proximity of the metastable critical point on the crystallization rates. However, we find that the ultrafast formation of a dense liquid phase causes the crystallization to accelerate both near the metastable critical point and almost everywhere below the fluid-fluid spinodal line. These results unveil three different scenarios for crystallization that could guide the optimization of the process in experiments.

  8. Computational fluid dynamics model for predicting flow of viscous fluids in a large fermentor with hydrofoil flow impellers and internal cooling coils

    PubMed

    Kelly; Humphrey

    1998-03-01

    Considerable debate has occurred over the use of hydrofoil impellers in large-scale fermentors to improve mixing and mass transfer in highly viscous non-Newtonian systems. Using a computational fluid dynamics software package (Fluent, version 4.30) extensive calculations were performed to study the effect of impeller speed (70-130 rpm), broth rheology (value of power law flow behavior index from 0.2 to 0.6), and distance between the cooling coil bank and the fermentor wall (6-18 in.) on flow near the perimeter of a large (75-m3) fermentor equipped with A315 impellers. A quadratic model utilizing the data was developed in an attempt to correlate the effect of A315 impeller speed, power law flow behavior index, and distance between the cooling coil bank and the fermentor wall on the average axial velocity in the coil bank-wall region. The results suggest that there is a potential for slow or stagnant flow in the coil bank-wall region which could result in poor oxygen and heat transfer for highly viscous fermentations. The results also indicate that there is the potential for slow or stagnant flow in the region between the top impeller and the gas headspace when flow through the coil bank-wall region is slow. Finally, a simple guideline was developed to allow fermentor design engineers to predict the degree of flow behind a bank of helical cooling coils in a large fermentor with hydrofoil flow impellers.

  9. The role of fluid-structure interaction for safety and life time prediction in hydraulic machinery

    NASA Astrophysics Data System (ADS)

    Hübner, B.; Weber, W.; Seidel, U.

    2016-11-01

    Reliable assessments of dynamic phenomena in hydraulic machinery require the consideration of fluid-structure interaction (FSI) if natural frequencies or damping properties of submerged structural parts clearly change due to the surrounding water or if the interaction may cause instabilities. Exemplarily, three different applications of strongly coupled FSI are presented which all have a high impact on operational safety or dynamic stresses and fatigue life. At first, flow induced damping effects at a Francis runner exhibit a strong dependency on operating condition and mode shape. Secondly, if a rotating disc is submerged, a splitting of natural frequencies is observed for mode shapes with different spinning direction. Finally, a hydroelastic instabilitiy is identified in a bypass valve at small opening.

  10. Neuropsychological Testing Predicts Cerebrospinal Fluid Aβ in Mild Cognitive Impairment (MCI)

    PubMed Central

    Kandel, Benjamin M.; Avants, Brian B.; Gee, James C.; Arnold, Steven E.; Wolk, David A.

    2015-01-01

    Background Psychometric tests predict conversion of Mild Cognitive Impairment (MCI) to probable Alzheimer's Disease (AD). Because the definition of clinical AD relies on those same psychometric tests, the ability of these tests to identify underlying AD pathology remains unclear. Objective To determine the degree to which psychometric testing predicts molecular evidence of AD amyloid pathology, as indicated by CSF Aβ1–42, in patients with MCI, as compared to neuroimaging biomarkers. Methods We identified 408 MCI subjects with CSF Aβ levels, psychometric test data, FDG-PET scans, and acceptable volumetric MR scans from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We used psychometric tests and imaging biomarkers in univariate and multivariate models to predict Aβ status. Results The 30-minute delayed recall score of the Rey Auditory Verbal Learning Test (AVLT) was the best predictor of Aβ status among the psychometric tests, achieving an AUC of 0.67±0.02 and odds ratio of 2.5±0.4. FDG-PET was the best imaging-based biomarker (AUC 0.67±0.03, OR 3.2±1.2), followed by hippocampal volume (AUC 0.64±0.02,,OR 2.4±0.3). A multivariate analysis based on the psychometric tests improved on the univariate predictors, achieving an AUC of 0.68±0.03 (OR 3.38±1.2). Adding imaging biomarkers to the multivariate analysis did not improve the AUC. Conclusion Psychometric tests perform as well as imaging biomarkers to predict presence of molecular markers of AD pathology in MCI patients and should be considered in the determination of the likelihood that MCI is due to AD. PMID:25881908

  11. High Cycle Fatigue Prediction for Mistuned Bladed Disks with Fully Coupled Fluid-Structural Interaction

    DTIC Science & Technology

    2006-06-01

    vibration and flutter boundary of 2D NACA 64A010 transonic airfoil, 3D plate wing structural response. The predicted results agree well with benchmark...CFD code coupled with a structural integrator based on the convolution integral to obtain the flutter boundary for a NACA 64A010 airfoil[10]. Alonso and...validation case of the scheme for moving grid system, the forced pitching NACA 64A010 airfoil is calculated. For this transonic airfoil, the Reynolds

  12. Dynamic evolution of D-dimer level in cerebrospinal fluid predicts poor outcome in patients with spontaneous intracerebral hemorrhage combined with intraventricular hemorrhage.

    PubMed

    Chen, Chih-Wei; Wu, En-Hsuan; Huang, Judy; Chang, Wen-Tsan; Ao, Kam-Hou; Cheng, Tain-Junn; Yang, Wuyang

    2016-07-01

    The risk of mortality in patients with intracerebral hemorrhage (ICH) significantly increases when complicated by intraventricular hemorrhage (IVH). We hypothesize that serial measurement of cerebrospinal fluid (CSF) D-dimer levels in patients with both ICH and IVH may serve as an early marker of IVH severity. We performed a prospective study of 43 consecutive ICH patients combined with IVH and external ventricular drainage placement admitted in our institution from 2005-2006. IVH severity (Graeb score) and fibrinolytic activity were evaluated continuously for 7days using CT scans and CSF D-dimer levels. The primary outcome was 30day mortality. Overall 30day mortality was 26% (n=11), with eight deaths (72.7%) after 3days (D3). Graeb score and CSF D-dimer on admission (D0) were not significantly different between survivors and non-survivors. The temporal profiles of both parameters were distinctly different, with a downward trend in survivors and an upward trend in non-survivors. A mortality rate of 54% was observed between D0-D3 when both scores increased during this interval. In contrast, the mortality was only 4% when both measures decreased during this interval. Early phase (D0-D3) CSF D-dimer or Graeb score change demonstrated high sensitivity of 88% and specificity of 81% when predicting 30day mortality. Early phase CSF D-dimer change in patients with both ICH and IVH is accurate in predicting mortality and may be utilized as a cost-effective surrogate indicator of IVH severity. Serial monitoring of CSF D-dimer dynamic changes is useful for early identification of patients with hematoma progression and poor outcome.

  13. Measuring Quality Factors From Multicomponent Reflection Seismic Data and its Significance for Lithology and Fluid Type Prediction

    NASA Astrophysics Data System (ADS)

    Ortiz-Osornio, M.; Calder¢n-Macias, C.; Ramos-Matinez, J.

    2003-12-01

    Relationships among shear and compressional wave velocities (VP and VS) and quality factors (QP and QS) for predicting lithology and fluid content, have been previously studied and proposed by some researchers. Thus, for example, VP/VS has been used as a lithology indicator for sandstone, shale and limestone. Likewise, QP/QS has been related to fluid content, mainly to discriminate oil, brine, and gas saturation. The velocities and quality factors for both P and S waves can be obtained from multicomponent reflection seismic data. Multicomponent data are most commonly recorded from compressional sources in the oil industry. Converted P to S waves or PS waves are generally measured in the radial component. In cases where there are heterogeneity and/or azimuthal anisotropy, the transverse component is also considered. Processing of the converted wave results in a PS image and an interpreted converted-wave velocity field (VPS). Likewise, it is possible to estimate a converted-wave quality factor (QPS) field. The converted-wave quality factor can also be used as a lithology and fluid content indicator since this parameter depends on VP/VS and QP/QS ratios. Crossplots involving QPS obtained from previously published laboratory measurements of P- and S-wave velocities and quality factors, reveal the significance of estimating QPS from multicomponent seismic data. An important advantage of using QPS as a lithology indicator is that it can be mapped directly from multicomponent surface seismic data. In this work we present a new methodology to obtain QPS. In the pure mode case, approaches for estimating Q are well known. However for converted-waves, some simplifying assumptions need to be made due to the propagation characteristics of the converted P- to S-wavepath.

  14. Use of systolic pressure variation to predict the cardiovascular response to mini-fluid challenge in anaesthetised dogs.

    PubMed

    Rabozzi, R; Franci, P

    2014-11-01

    Systolic pressure variation (SPV), the maximum variation in systolic pressure values following a single positive pressure breath delivered by controlled mechanical ventilation (CMV), is highly correlated with volaemia in dogs. The aim of this study was to determine an SPV value that would indicate when fluid administration would be beneficial in clinical practice. Twenty-six client-owned dogs were anaesthetised, following which CMV with a peak inspiratory pressure (PIP) of 8 cmH2O was applied. After SPV measurement and recording of heart rate (HR) and blood pressure (BP), 3 mL/kg fluid were administered, then HR and BP were recorded again. Dogs exhibiting a 10% decrease in HR and/or an increase in BP were defined as responders, and their SPV pre-bolus was analysed retrospectively. SPV values > 4 mmHg or >4.5% predicted haemodynamic improvement in dogs with normal cardiovascular function, with a sensitivity of 90% and a specificity of 87%. The area under the curve receiver operating characteristic value for SPV was 0.931 mmHg (95% confidence interval, CI, 0.76-0.99 mmHg) and 0.944% (95% CI 0.78-0.99%). It is proposed that SPV values > 4.5% in dogs with a normal cardiovascular function, anaesthetised with isoflurane in oxygen and air, and on CMV (PIP 8 cmH2O), can be used to predict a cardiovascular response (>10% increase in mean arterial BP and/or >10% decrease in heart rate).

  15. WETTABILITY AND PREDICTION OF OIL RECOVERY FROM RESERVOIRS DEVELOPED WITH MODERN DRILLING AND COMPLETION FLUIDS

    SciTech Connect

    Jill S. Buckley; Norman R. Morrow

    2005-04-01

    Exposure to crude oil in the presence of an initial brine saturation can render rocks mixed-wet. Subsequent exposure to components of synthetic oil-based drilling fluids can alter the wetting toward less water-wet or more oil-wet conditions. Mixing of the non-aromatic base oils used in synthetic oil-based muds (SBM) with an asphaltic crude oil can destabilize asphaltenes and make cores less water-wet. Wetting changes can also occur due to contact with the surfactants used in SBM formulations to emulsify water and make the rock cuttings oil-wet. Reservoir cores drilled with SBMs, therefore, show wetting properties much different from the reservoir wetting conditions, invalidating laboratory core analysis using SBM contaminated cores. Core cleaning is required in order to remove all the drilling mud contaminants. In theory, core wettability can then be restored to reservoir wetting conditions by exposure to brine and crude oil. The efficiency of core cleaning of SBM contaminated cores has been explored in this study. A new core cleaning procedure was developed aimed to remove the adsorbed asphaltenes and emulsifiers from the contaminated Berea sandstone cores. Sodium hydroxide was introduced into the cleaning process in order to create a strongly alkaline condition. The high pH environment in the pore spaces changed the electrical charges of both basic and acidic functional groups, reducing the attractive interactions between adsorbing materials and the rock surface. In cores, flow-through and extraction methods were investigated. The effectiveness of the cleaning procedure was assessed by spontaneous imbibition tests and Amott wettability measurements. Test results indicating that introduction of sodium hydroxide played a key role in removing adsorbed materials were confirmed by contact angle measurements on similarly treated mica surfaces. Cleaning of the contaminated cores reversed their wettability from oil-wet to strongly water-wet as demonstrated by spontaneous

  16. Non-Darcian flow of shear-thinning fluids through packed beads: Experiments and predictions using Forchheimer's law and Ergun's equation

    NASA Astrophysics Data System (ADS)

    Rodríguez de Castro, Antonio; Radilla, Giovanni

    2017-02-01

    The flow of shear-thinning fluids through unconsolidated porous media is present in a number of important industrial applications such as soil depollution, Enhanced Oil Recovery or filtration of polymeric liquids. Therefore, predicting the pressure drop-flow rate relationship in model porous media has been the scope of major research efforts during the last decades. Although the flow of Newtonian fluids through packs of spherical particles is well understood in most cases, much less is known regarding the flow of shear-thinning fluids as high molecular weight polymer aqueous solutions. In particular, the experimental data for the non-Darcian flow of shear-thinning fluids are scarce and so are the current approaches for their prediction. Given the relevance of non-Darcian shear-thinning flow, the scope of this work is to perform an experimental study to systematically evaluate the effects of fluid shear rheology on the flow rate-pressure drop relationships for the non-Darcian flow through different packs of glass spheres. To do so, xanthan gum aqueous solutions with different polymer concentrations are injected through four packs of glass spheres with uniform size under Darcian and inertial flow regimes. A total of 1560 experimental data are then compared with predictions coming from different methods based on the extension of widely used Ergun's equation and Forchheimer's law to the case of shear thinning fluids, determining the accuracy of these predictions. The use of a proper definition for Reynolds number and a realistic model to represent the rheology of the injected fluids results in the porous media are shown to be key aspects to successfully predict pressure drop-flow rate relationships for the inertial shear-thinning flow in packed beads.

  17. Development and validation of computational fluid dynamics models for prediction of heat transfer and thermal microenvironments of corals.

    PubMed

    Ong, Robert H; King, Andrew J C; Mullins, Benjamin J; Cooper, Timothy F; Caley, M Julian

    2012-01-01

    We present Computational Fluid Dynamics (CFD) models of the coupled dynamics of water flow, heat transfer and irradiance in and around corals to predict temperatures experienced by corals. These models were validated against controlled laboratory experiments, under constant and transient irradiance, for hemispherical and branching corals. Our CFD models agree very well with experimental studies. A linear relationship between irradiance and coral surface warming was evident in both the simulation and experimental result agreeing with heat transfer theory. However, CFD models for the steady state simulation produced a better fit to the linear relationship than the experimental data, likely due to experimental error in the empirical measurements. The consistency of our modelling results with experimental observations demonstrates the applicability of CFD simulations, such as the models developed here, to coral bleaching studies. A study of the influence of coral skeletal porosity and skeletal bulk density on surface warming was also undertaken, demonstrating boundary layer behaviour, and interstitial flow magnitude and temperature profiles in coral cross sections. Our models compliment recent studies showing systematic changes in these parameters in some coral colonies and have utility in the prediction of coral bleaching.

  18. Development and Validation of Computational Fluid Dynamics Models for Prediction of Heat Transfer and Thermal Microenvironments of Corals

    PubMed Central

    Ong, Robert H.; King, Andrew J. C.; Mullins, Benjamin J.; Cooper, Timothy F.; Caley, M. Julian

    2012-01-01

    We present Computational Fluid Dynamics (CFD) models of the coupled dynamics of water flow, heat transfer and irradiance in and around corals to predict temperatures experienced by corals. These models were validated against controlled laboratory experiments, under constant and transient irradiance, for hemispherical and branching corals. Our CFD models agree very well with experimental studies. A linear relationship between irradiance and coral surface warming was evident in both the simulation and experimental result agreeing with heat transfer theory. However, CFD models for the steady state simulation produced a better fit to the linear relationship than the experimental data, likely due to experimental error in the empirical measurements. The consistency of our modelling results with experimental observations demonstrates the applicability of CFD simulations, such as the models developed here, to coral bleaching studies. A study of the influence of coral skeletal porosity and skeletal bulk density on surface warming was also undertaken, demonstrating boundary layer behaviour, and interstitial flow magnitude and temperature profiles in coral cross sections. Our models compliment recent studies showing systematic changes in these parameters in some coral colonies and have utility in the prediction of coral bleaching. PMID:22701582

  19. Functional imaging using computational fluid dynamics to predict treatment success of mandibular advancement devices in sleep-disordered breathing.

    PubMed

    De Backer, J W; Vanderveken, O M; Vos, W G; Devolder, A; Verhulst, S L; Verbraecken, J A; Parizel, P M; Braem, M J; Van de Heyning, P H; De Backer, W A

    2007-01-01

    Mandibular advancement devices (MADs) have emerged as a popular alternative for the treatment of sleep-disordered breathing. These devices bring the mandibula forward in order to increase upper airway (UA) volume and prevent total UA collapse during sleep. However, the precise mechanism of action appears to be quite complex and is not yet completely understood; this might explain interindividual variation in treatment success. We examined whether an UA model, that combines imaging techniques and computational fluid dynamics (CFD), allows for a prediction of the treatment outcome with MADs. Ten patients that were treated with a custom-made mandibular advancement device (MAD), underwent split-night polysomnography. The morning after the sleep study, a low radiation dose CT scan was scheduled with and without the MAD. The CT examinations allowed for a comparison between the change in UA volume and the anatomical characteristics through the conversion to three-dimensional computer models. Furthermore, the change in UA resistance could be calculated through flow simulations with CFD. Boundary conditions for the model such as mass flow rate and pressure distributions were obtained during the split-night polysomnography. Therefore, the flow modeling was based on a patient specific geometry and patient specific boundary conditions. The results indicated that a decrease in UA resistance and an increase in UA volume correlate with both a clinical and an objective improvement. The results of this pilot study suggest that the outcome of MAD treatment can be predicted using the described UA model.

  20. WETTABILITY AND PREDICTION OF OIL RECOVERY FROM RESERVOIRS DEVELOPED WITH MODERN DRILLING AND COMPLETION FLUIDS

    SciTech Connect

    Jill S. Buckley; Norman R. Morrow

    2004-05-01

    We report on progress in three areas. In part one, the wetting effects of synthetic base oils are reported. Part two reports progress in understanding the effects of surfactants of known chemical structures, and part three integrates the results from surface and core tests that show the wetting effects of commercial surfactant products used in synthetic and traditional oil-based drilling fluids. An important difference between synthetic and traditional oil-based muds (SBM and OBM, respectively) is the elimination of aromatics from the base oil to meet environmental regulations. The base oils used include dearomatized mineral oils, linear alpha-olefins, internal olefins, and esters. We show in part one that all of these materials except the esters can, at sufficiently high concentrations, destabilize asphaltenes. The effects of asphaltenes on wetting are in part related to their stability. Although asphaltenes have some tendency to adsorb on solid surfaces from a good solvent, that tendency can be much increased near the onset of asphaltene instability. Tests in Berea sandstone cores demonstrate wetting alteration toward less water-wet conditions that occurs when a crude oil is displaced by paraffinic and olefinic SBM base oils, whereas exposure to the ester products has little effect on wetting properties of the cores. Microscopic observations with atomic forces microscopy (AFM) and macroscopic contact angle measurements have been used in part 2 to explore the effects on wetting of mica surfaces using oil-soluble polyethoxylated amine surfactants with varying hydrocarbon chain lengths and extent of ethoxylation. In the absence of water, only weak adsorption occurs. Much stronger, pH-dependent adsorption was observed when water was present. Varying hydrocarbon chain length had little or no effect on adsorption, whereas varying extent of ethoxylation had a much more significant impact, reducing contact angles at nearly all conditions tested. Preequilibration of

  1. Dielectric Interactions and the Prediction of Retention Times of Pesticides in Supercritical Fluid Chromatography with CO2

    NASA Astrophysics Data System (ADS)

    Alvarez, Guillermo A.; Baumanna, Wolfram

    2005-02-01

    A thermodynamic model for the partition of a solute (pesticide) between two immiscible phases, such as the stationary and mobile phases of supercritical fluid chromatography with CO2, is developed from first principles. A key ingredient of the model is the result of the calculation made by Liptay of the energy of interaction of a polar molecule with a dielectric continuum, which represents the solvent. The strength of the interaction between the solute and the solvent, which may be considered a measure of the solvent power, is characterized by a function g = (ɛ - 1)/(2ɛ +1), where ɛ is the dielectric constant of the medium, which is a function of the temperature T and the pressure P. Since the interactions between the nonpolar supercritical CO2 solvent and the slightly polar pesticide molecules are considered to be extremely weak, a regular solution model is appropriate from the thermodynamic point of view. At constant temperature, the model predicts a linear dependence of the logarithm of the capacity factor (lnk) of the chromatographic experiment on the function g = g(P), as the pressure is varied, with a slope which depends on the dipole moment of the solute, dispersion interactions and the size of the solute cavity in the solvent. At constant pressure, once the term containing the g (solvent interaction) factor is subtracted from lnk, a plot of the resulting term against the inverse of temperature yields the enthalpy change of transfer of the solute from the mobile (supercritical CO2) phase to the stationary (adsorbent) phase. The increase in temperature with the consequent large volume expansion of the supercritical fluid lowers its solvent strength and hence the capacity factor of the column (or solute retention time) increases. These pressure and temperature effects, predicted by the model, agree excellently with the experimental retention times of seven pesticides. Beyond a temperature of about 393 K, where the liquid solvent densities approach those of

  2. Supercritical fluid thermodynamics for coal processing

    SciTech Connect

    van Swol, F. . Dept. of Chemical Engineering); Eckert, C.A. . School of Chemical Engineering)

    1988-09-15

    The main objective of this research is to develop an equation of state that can be used to predict solubilities and tailor supercritical fluid solvents for the extraction and processing of coal. To meet this objective we have implemented a two-sided. approach. First, we expanded the database of model coal compound solubilities in higher temperature fluids, polar fluids, and fluid mixtures systems. Second, the unique solute/solute, solute/cosolvent and solute/solvent intermolecular interactions in supercritical fluid solutions were investigated using spectroscopic techniques. These results increased our understanding of the molecular phenomena that affect solubility in supercritical fluids and were significant in the development of an equation of state that accurately reflects the true molecular makeup of the solution. (VC)

  3. Utilizing left ventricular outflow tract velocity changes to predict fluid responsiveness in septic patients: a case report.

    PubMed

    Chiem, Alan T; Turner, Elizabeth

    2014-03-01

    Toxin-mediated vasodilation in the sepsis syndrome can lead to end-organ dysfunction and shock. Assessing for fluid responsiveness and preload optimization with intravenous fluids is a central tenet in the management of sepsis. Aggressive fluid administration can lead to pulmonary edema and heart failure, whereas premature inotropic or vasopressor support can worsen organ perfusion. Inferior vena cava ultrasonography is commonly used to assess for fluid responsiveness but has multiple limitations.

  4. Interspecies scaling of urinary excretory amounts of nine drugs belonging to different therapeutic areas with diverse chemical structures - accurate prediction of the human urinary excretory amounts.

    PubMed

    Bhamidipati, Ravi Kanth; Mullangi, Ramesh; Srinivas, Nuggehally R

    2017-02-01

    1. The human urinary excretory amounts of total drug (parent + metabolites) were predicted for nine drugs with diverse chemical structures using simple allometry. The drugs used for scaling were cephapirin, olanzapine, labetolol, carisbamate, voriconazole, tofacitinib, nevirapine, ropinirole, and cyclindole. 2. The traditional allometric scaling was attempted using Y = aW(b) relationship. The corresponding predicted urinary amounts were converted into % recovery by using appropriate human dose. Appropriate statistical tests comprising of fold-difference (predicted/observed values) and error calculations (MAE and RMSE) were performed. 3. The interspecies scaling of all nine drugs tested showed excellent correlation (r > 0.9672). The predictions for eight out of nine drugs (exception was cephaphirin) were contained within 0.80-1.25 fold-differences. The MAE and RMSE were within ± 18% and 14.64%, respectively. 4. The present work supported the potential application of prospective allometry scaling to predict the urinary excretory amounts of the total drug and gauge any issues for the renal handling of the total drug.

  5. Tumor Necrosis Factor-α in Temporomandibular Joint Synovial Fluid Predicts Treatment Effects on Pain by Intra-Articular Glucocorticoid Treatment

    PubMed Central

    Fredriksson, Lars; Alstergren, Per; Kopp, Sigvard

    2006-01-01

    The aim of this study was to investigate the influence of tumor necrosis factor-α (TNF-α) in temporomandibular joint (TMJ) synovial fluid and blood on the treatment effect on TMJ pain by intra-articular injection of glucocorticoid in patients with chronic inflammatory TMJ disorders. High pretreatment level of TNF-α in the synovial fluid was associated with a decrease of TNF-α and elimination of pain upon maximal mouth opening. Elimination of this TMJ pain was accordingly associated with decrease in synovial fluid level of TNF-α. There was also a significant decrease of C-reactive protein and TMJ resting pain after treatment. In conclusion, this study indicates that presence of TNF-α in the synovial fluid predicts a treatment effect of intra-articular injection of glucocorticoid on TMJ movement pain in patients with chronic TMJ inflammatory disorders. PMID:17392588

  6. A novel approach to gravitation from fluid theory: Titius-Bode structures, flat rotation rate of galaxies, and other predictions

    NASA Astrophysics Data System (ADS)

    Munera, Hector A.

    Following the discovery of quantum phenomena at laboratory scale (Couder & Fort 2006), de Broglie pilot wave theory (De Broglie 1962) has been revived under a hydrodynamic guise (Bush 2015). Theoretically, it boils down to solving the transport equations for the energy and linear momentum densities of a postulated fundamental fluid in terms of classical wave equations, which inherently are Lorentz-invariant and scale-invariant. Instead of the conventional harmonic solutions, for astronomical and gravitational problems the novel solutions for the homogeneous wave equation in spherical coordinates are more suitable (Munera et al. 1995, Munera & Guzman 1997, and Munera 2000). Two groups of solutions are particularly relevant: (a) The inherently-quantized helicoidal solutions that may be applicable to describe spiral galaxies, and (b) The non-harmonic solutions with time (t) and distance (r) entangled in the single variable q = Ct/r (C is the two-way local electromagnetic speed). When these functions are plotted against 1/q they manifestly depict quantum effects in the near field, and Newtonian-like gravity in the far-field. The near-field predicts quantized effects similar to ring structures and to Titius-Bode structures, both in our own solar system and in exoplanets, the correlation between predicted and observed structures being typically larger than 99 per cent. In the far-field, some non-harmonic functions have a rate of decrement with distance slower than inverse-square thus explaining the flat rotation rate of galaxies. Additional implications for Trojan orbits, and quantized effects in photon deflection were also noted.

  7. Prediction of the micro-fluid dynamic environment imposed to three-dimensional engineered cell systems in bioreactors.

    PubMed

    Boschetti, Federica; Raimondi, Manuela Teresa; Migliavacca, Francesco; Dubini, Gabriele

    2006-01-01

    Bioreactors allowing culture medium perfusion overcome diffusion limitations associated with static culturing and provide flow-mediated mechanical stimuli. The hydrodynamic stress imposed to cells will depend not only on the culture medium flow rate, but also on the scaffold three-dimensional (3D) micro-architecture. We developed a CFD model of the flow of culture medium through a 3D scaffold of homogeneous geometry, with the aim of predicting the shear stress acting on cells as a function of parameters that can be controlled during the scaffold fabrication process, such as the scaffold porosity and the pore size, and during the cell culture, such as the medium flow rate and the diameter of the perfused scaffold section. We built three groups of models corresponding to three pore sizes: 50, 100 and 150 microm. Each group was made of four models corresponding to 59%, 65%, 77%, and 89% porosity. A commercial finite-element code was used to set up and solve the problem and to analyze the results. The mode value of shear stress varied between 2 and 5 mPa, and was obtained for a circular scaffold of 15.5 mm diameter, perfused by a flow rate of 0.5 ml/min. The simulations showed that the pore size is a variable strongly influencing the predicted shear stress level, whereas the porosity is a variable strongly affecting the statistical distribution of the shear stresses, but not their magnitude. Our results provide a basis for the completion of more exhaustive quantitative studies to further assess the relationship between perfusion, at known micro-fluid dynamic conditions, and tissue growth in vitro.

  8. Nusselt correlation to predict heat transfer from an oscillated vertical annular fluid column through a porous domain

    NASA Astrophysics Data System (ADS)

    Sayar, Ersin; Sari, Ugurcan

    2016-08-01

    Experimental evaluation of the heat transfer in oscillating flow under the constant heat flux and constant amplitude fluid displacement conditions is presented for a vertical annular flow through a stainless steel wool porous media. The analysis is carried out for two different heat fluxes and for five different frequencies. The data is acquired from the measurements both in the initial transient period and in the pseudo-steady (cyclic) period by the system. The physical and mathematical behavior of the resulting Nusselt numbers are analyzed, according to data acquired from the experiments and in accordance with the results of the Buckingham Pi theorem. A cycle and space averaged Nusselt number correlation is suggested as a function of kinetic Reynolds number for oscillating flows. The suggested correlation is useful in predicting heat transfer from oscillating flows through highly porous and permeable solid media at low actuation frequencies and at low heat fluxes applied in the wall. The validity of the Nusselt numbers acquired by correlation is discussed using experimental Nusselt numbers for the selected kinetic Reynolds number interval. The present investigation has possible applications in moderate sized wicked heat pipes, solid matrix compact heat exchangers compromising of metallic foams, filtration equipment, and steam generators.

  9. Accurate prediction of higher-level electronic structure energies for large databases using neural networks, Hartree-Fock energies, and small subsets of the database.

    PubMed

    Malshe, M; Pukrittayakamee, A; Raff, L M; Hagan, M; Bukkapatnam, S; Komanduri, R

    2009-09-28

    A novel method is presented that significantly reduces the computational bottleneck of executing high-level, electronic structure calculations of the energies and their gradients for a large database that adequately samples the configuration space of importance for systems containing more than four atoms that are undergoing multiple, simultaneous reactions in several energetically open channels. The basis of the method is the high-degree of correlation that generally exists between the Hartree-Fock (HF) and higher-level electronic structure energies. It is shown that if the input vector to a neural network (NN) includes both the configuration coordinates and the HF energies of a small subset of the database, MP4(SDQ) energies with the same basis set can be predicted for the entire database using only the HF and MP4(SDQ) energies for the small subset and the HF energies for the remainder of the database. The predictive error is shown to be less than or equal to the NN fitting error if a NN is fitted to the entire database of higher-level electronic structure energies. The general method is applied to the computation of MP4(SDQ) energies of 68,308 configurations that comprise the database for the simultaneous, unimolecular decomposition of vinyl bromide into six different reaction channels. The predictive accuracy of the method is investigated by employing successively smaller subsets of the database to train the NN to predict the MP4(SDQ) energies of the remaining configurations of the database. The results indicate that for this system, the subset can be as small as 8% of the total number of configurations in the database without loss of accuracy beyond that expected if a NN is employed to fit the higher-level energies for the entire database. The utilization of this procedure is shown to save about 78% of the total computational time required for the execution of the MP4(SDQ) calculations. The sampling error involved with selection of the subset is shown to be

  10. Accurate prediction of higher-level electronic structure energies for large databases using neural networks, Hartree-Fock energies, and small subsets of the database

    NASA Astrophysics Data System (ADS)

    Malshe, M.; Pukrittayakamee, A.; Raff, L. M.; Hagan, M.; Bukkapatnam, S.; Komanduri, R.

    2009-09-01

    A novel method is presented that significantly reduces the computational bottleneck of executing high-level, electronic structure calculations of the energies and their gradients for a large database that adequately samples the configuration space of importance for systems containing more than four atoms that are undergoing multiple, simultaneous reactions in several energetically open channels. The basis of the method is the high-degree of correlation that generally exists between the Hartree-Fock (HF) and higher-level electronic structure energies. It is shown that if the input vector to a neural network (NN) includes both the configuration coordinates and the HF energies of a small subset of the database, MP4(SDQ) energies with the same basis set can be predicted for the entire database using only the HF and MP4(SDQ) energies for the small subset and the HF energies for the remainder of the database. The predictive error is shown to be less than or equal to the NN fitting error if a NN is fitted to the entire database of higher-level electronic structure energies. The general method is applied to the computation of MP4(SDQ) energies of 68 308 configurations that comprise the database for the simultaneous, unimolecular decomposition of vinyl bromide into six different reaction channels. The predictive accuracy of the method is investigated by employing successively smaller subsets of the database to train the NN to predict the MP4(SDQ) energies of the remaining configurations of the database. The results indicate that for this system, the subset can be as small as 8% of the total number of configurations in the database without loss of accuracy beyond that expected if a NN is employed to fit the higher-level energies for the entire database. The utilization of this procedure is shown to save about 78% of the total computational time required for the execution of the MP4(SDQ) calculations. The sampling error involved with selection of the subset is shown to be

  11. Closed-loop spontaneous baroreflex transfer function is inappropriate for system identification of neural arc but partly accurate for peripheral arc: predictability analysis.

    PubMed

    Kamiya, Atsunori; Kawada, Toru; Shimizu, Shuji; Sugimachi, Masaru

    2011-04-01

    Although the dynamic characteristics of the baroreflex system have been described by baroreflex transfer functions obtained from open-loop analysis, the predictability of time-series output dynamics from input signals, which should confirm the accuracy of system identification, remains to be elucidated. Moreover, despite theoretical concerns over closed-loop system identification, the accuracy and the predictability of the closed-loop spontaneous baroreflex transfer function have not been evaluated compared with the open-loop transfer function. Using urethane and α-chloralose anaesthetized, vagotomized and aortic-denervated rabbits (n = 10), we identified open-loop baroreflex transfer functions by recording renal sympathetic nerve activity (SNA) while varying the vascularly isolated intracarotid sinus pressure (CSP) according to a binary random (white-noise) sequence (operating pressure ± 20 mmHg), and using a simplified equation to calculate closed-loop-spontaneous baroreflex transfer function while matching CSP with systemic arterial pressure (AP). Our results showed that the open-loop baroreflex transfer functions for the neural and peripheral arcs predicted the time-series SNA and AP outputs from measured CSP and SNA inputs, with r2 of 0.8 ± 0.1 and 0.8 ± 0.1, respectively. In contrast, the closed-loop-spontaneous baroreflex transfer function for the neural arc was markedly different from the open-loop transfer function (enhanced gain increase and a phase lead), and did not predict the time-series SNA dynamics (r2; 0.1 ± 0.1). However, the closed-loop-spontaneous baroreflex transfer function of the peripheral arc partially matched the open-loop transfer function in gain and phase functions, and had limited but reasonable predictability of the time-series AP dynamics (r2, 0.7 ± 0.1). A numerical simulation suggested that a noise predominantly in the neural arc under resting conditions might be a possible mechanism responsible for our findings. Furthermore

  12. Use of dose-dependent absorption into target tissues to more accurately predict cancer risk at low oral doses of hexavalent chromium.

    PubMed

    Haney, J

    2015-02-01

    The mouse dose at the lowest water concentration used in the National Toxicology Program hexavalent chromium (CrVI) drinking water study (NTP, 2008) is about 74,500 times higher than the approximate human dose corresponding to the 35-city geometric mean reported in EWG (2010) and over 1000 times higher than that based on the highest reported tap water concentration. With experimental and environmental doses differing greatly, it is a regulatory challenge to extrapolate high-dose results to environmental doses orders of magnitude lower in a meaningful and toxicologically predictive manner. This seems particularly true for the low-dose extrapolation of results for oral CrVI-induced carcinogenesis since dose-dependent differences in the dose fraction absorbed by mouse target tissues are apparent (Kirman et al., 2012). These data can be used for a straightforward adjustment of the USEPA (2010) draft oral slope factor (SFo) to be more predictive of risk at environmentally-relevant doses. More specifically, the evaluation of observed and modeled differences in the fraction of dose absorbed by target tissues at the point-of-departure for the draft SFo calculation versus lower doses suggests that the draft SFo be divided by a dose-specific adjustment factor of at least an order of magnitude to be less over-predictive of risk at more environmentally-relevant doses.

  13. Normal Tissue Complication Probability Estimation by the Lyman-Kutcher-Burman Method Does Not Accurately Predict Spinal Cord Tolerance to Stereotactic Radiosurgery

    SciTech Connect

    Daly, Megan E.; Luxton, Gary; Choi, Clara Y.H.; Gibbs, Iris C.; Chang, Steven D.; Adler, John R.; Soltys, Scott G.

    2012-04-01

    Purpose: To determine whether normal tissue complication probability (NTCP) analyses of the human spinal cord by use of the Lyman-Kutcher-Burman (LKB) model, supplemented by linear-quadratic modeling to account for the effect of fractionation, predict the risk of myelopathy from stereotactic radiosurgery (SRS). Methods and Materials: From November 2001 to July 2008, 24 spinal hemangioblastomas in 17 patients were treated with SRS. Of the tumors, 17 received 1 fraction with a median dose of 20 Gy (range, 18-30 Gy) and 7 received 20 to 25 Gy in 2 or 3 sessions, with cord maximum doses of 22.7 Gy (range, 17.8-30.9 Gy) and 22.0 Gy (range, 20.2-26.6 Gy), respectively. By use of conventional values for {alpha}/{beta}, volume parameter n, 50% complication probability dose TD{sub 50}, and inverse slope parameter m, a computationally simplified implementation of the LKB model was used to calculate the biologically equivalent uniform dose and NTCP for each treatment. Exploratory calculations were performed with alternate values of {alpha}/{beta} and n. Results: In this study 1 case (4%) of myelopathy occurred. The LKB model using radiobiological parameters from Emami and the logistic model with parameters from Schultheiss overestimated complication rates, predicting 13 complications (54%) and 18 complications (75%), respectively. An increase in the volume parameter (n), to assume greater parallel organization, improved the predictive value of the models. Maximum-likelihood LKB fitting of {alpha}/{beta} and n yielded better predictions (0.7 complications), with n = 0.023 and {alpha}/{beta} = 17.8 Gy. Conclusions: The spinal cord tolerance to the dosimetry of SRS is higher than predicted by the LKB model using any set of accepted parameters. Only a high {alpha}/{beta} value in the LKB model and only a large volume effect in the logistic model with Schultheiss data could explain the low number of complications observed. This finding emphasizes that radiobiological models

  14. Lost in translation: preclinical studies on 3,4-methylenedioxymethamphetamine provide information on mechanisms of action, but do not allow accurate prediction of adverse events in humans

    PubMed Central

    Green, AR; King, MV; Shortall, SE; Fone, KCF

    2012-01-01

    3,4-Methylenedioxymethamphetamine (MDMA) induces both acute adverse effects and long-term neurotoxic loss of brain 5-HT neurones in laboratory animals. However, when choosing doses, most preclinical studies have paid little attention to the pharmacokinetics of the drug in humans or animals. The recreational use of MDMA and current clinical investigations of the drug for therapeutic purposes demand better translational pharmacology to allow accurate risk assessment of its ability to induce adverse events. Recent pharmacokinetic studies on MDMA in animals and humans are reviewed and indicate that the risks following MDMA ingestion should be re-evaluated. Acute behavioural and body temperature changes result from rapid MDMA-induced monoamine release, whereas long-term neurotoxicity is primarily caused by metabolites of the drug. Therefore acute physiological changes in humans are fairly accurately mimicked in animals by appropriate dosing, although allometric dosing calculations have little value. Long-term changes require MDMA to be metabolized in a similar manner in experimental animals and humans. However, the rate of metabolism of MDMA and its major metabolites is slower in humans than rats or monkeys, potentially allowing endogenous neuroprotective mechanisms to function in a species specific manner. Furthermore acute hyperthermia in humans probably limits the chance of recreational users ingesting sufficient MDMA to produce neurotoxicity, unlike in the rat. MDMA also inhibits the major enzyme responsible for its metabolism in humans thereby also assisting in preventing neurotoxicity. These observations question whether MDMA alone produces long-term 5-HT neurotoxicity in human brain, although when taken in combination with other recreational drugs it may induce neurotoxicity. LINKED ARTICLES This article is commented on by Parrott, pp. 1518–1520 of this issue. To view this commentary visit http://dx.doi.org/10.1111/j.1476-5381.2012.01941.x and to view the the

  15. Race-specific genetic risk score is more accurate than nonrace-specific genetic risk score for predicting prostate cancer and high-grade diseases.

    PubMed

    Na, Rong; Ye, Dingwei; Qi, Jun; Liu, Fang; Lin, Xiaoling; Helfand, Brian T; Brendler, Charles B; Conran, Carly; Gong, Jian; Wu, Yishuo; Gao, Xu; Chen, Yaqing; Zheng, S Lilly; Mo, Zengnan; Ding, Qiang; Sun, Yinghao; Xu, Jianfeng

    2016-01-01

    Genetic risk score (GRS) based on disease risk-associated single nucleotide polymorphisms (SNPs) is an informative tool that can be used to provide inherited information for specific diseases in addition to family history. However, it is still unknown whether only SNPs that are implicated in a specific racial group should be used when calculating GRSs. The objective of this study is to compare the performance of race-specific GRS and nonrace-specific GRS for predicting prostate cancer (PCa) among 1338 patients underwent prostate biopsy in Shanghai, China. A race-specific GRS was calculated with seven PCa risk-associated SNPs implicated in East Asians (GRS7), and a nonrace-specific GRS was calculated based on 76 PCa risk-associated SNPs implicated in at least one racial group (GRS76). The means of GRS7 and GRS76 were 1.19 and 1.85, respectively, in the study population. Higher GRS7 and GRS76 were independent predictors for PCa and high-grade PCa in univariate and multivariate analyses. GRS7 had a better area under the receiver-operating curve (AUC) than GRS76 for discriminating PCa (0.602 vs 0.573) and high-grade PCa (0.603 vs 0.575) but did not reach statistical significance. GRS7 had a better (up to 13% at different cutoffs) positive predictive value (PPV) than GRS76. In conclusion, a race-specific GRS is more robust and has a better performance when predicting PCa in East Asian men than a GRS calculated using SNPs that are not shown to be associated with East Asians.

  16. The CUPIC algorithm: an accurate model for the prediction of sustained viral response under telaprevir or boceprevir triple therapy in cirrhotic patients.

    PubMed

    Boursier, J; Ducancelle, A; Vergniol, J; Veillon, P; Moal, V; Dufour, C; Bronowicki, J-P; Larrey, D; Hézode, C; Zoulim, F; Fontaine, H; Canva, V; Poynard, T; Allam, S; De Lédinghen, V

    2015-12-01

    Triple therapy using boceprevir or telaprevir remains the reference treatment for genotype 1 chronic hepatitis C in countries where new interferon-free regimens have not yet become available. Antiviral treatment is highly required in cirrhotic patients, but they represent a difficult-to-treat population. We aimed to develop a simple algorithm for the prediction of sustained viral response (SVR) in cirrhotic patients treated with triple therapy. A total of 484 cirrhotic patients from the ANRS CO20 CUPIC cohort treated with triple therapy were randomly distributed into derivation and validation sets. A total of 52.1% of patients achieved SVR. In the derivation set, a D0 score for the prediction of SVR before treatment initiation included the following independent predictors collected at day 0: prior treatment response, gamma-GT, platelets, telaprevir treatment, viral load. To refine the prediction at the early phase of the treatment, a W4 score included as additional parameter the viral load collected at week 4. The D0 and W4 scores were combined in the CUPIC algorithm defining three subgroups: 'no treatment initiation or early stop at week 4', 'undetermined' and 'SVR highly probable'. In the validation set, the rates of SVR in these three subgroups were, respectively, 11.1%, 50.0% and 82.2% (P < 0.001). By replacing the variable 'prior treatment response' with 'IL28B genotype', another algorithm was derived for treatment-naïve patients with similar results. The CUPIC algorithm is an easy-to-use tool that helps physicians weigh their decision between immediately treating cirrhotic patients using boceprevir/telaprevir triple therapy or waiting for new drugs to become available in their country.

  17. Ab initio molecular dynamics of liquid water using embedded-fragment second-order many-body perturbation theory towards its accurate property prediction

    PubMed Central

    Willow, Soohaeng Yoo; Salim, Michael A.; Kim, Kwang S.; Hirata, So

    2015-01-01

    A direct, simultaneous calculation of properties of a liquid using an ab initio electron-correlated theory has long been unthinkable. Here we present structural, dynamical, and response properties of liquid water calculated by ab initio molecular dynamics using the embedded-fragment spin-component-scaled second-order many-body perturbation method with the aug-cc-pVDZ basis set. This level of theory is chosen as it accurately and inexpensively reproduces the water dimer potential energy surface from the coupled-cluster singles, doubles, and noniterative triples with the aug-cc-pVQZ basis set, which is nearly exact. The calculated radial distribution function, self-diffusion coefficient, coordinate number, and dipole moment, as well as the infrared and Raman spectra are in excellent agreement with experimental results. The shapes and widths of the OH stretching bands in the infrared and Raman spectra and their isotropic-anisotropic Raman noncoincidence, which reflect the diverse local hydrogen-bond environment, are also reproduced computationally. The simulation also reveals intriguing dynamic features of the environment, which are difficult to probe experimentally, such as a surprisingly large fluctuation in the coordination number and the detailed mechanism by which the hydrogen donating water molecules move across the first and second shells, thereby causing this fluctuation. PMID:26400690

  18. Accurate prediction of diradical chemistry from a single-reference density-matrix method: Model application to the bicyclobutane to gauche-1,3-butadiene isomerization

    SciTech Connect

    Bertels, Luke W.; Mazziotti, David A.

    2014-07-28

    Multireference correlation in diradical molecules can be captured by a single-reference 2-electron reduced-density-matrix (2-RDM) calculation with only single and double excitations in the 2-RDM parametrization. The 2-RDM parametrization is determined by N-representability conditions that are non-perturbative in their treatment of the electron correlation. Conventional single-reference wave function methods cannot describe the entanglement within diradical molecules without employing triple- and potentially even higher-order excitations of the mean-field determinant. In the isomerization of bicyclobutane to gauche-1,3-butadiene the parametric 2-RDM (p2-RDM) method predicts that the diradical disrotatory transition state is 58.9 kcal/mol above bicyclobutane. This barrier is in agreement with previous multireference calculations as well as recent Monte Carlo and higher-order coupled cluster calculations. The p2-RDM method predicts the Nth natural-orbital occupation number of the transition state to be 0.635, revealing its diradical character. The optimized geometry from the p2-RDM method differs in important details from the complete-active-space self-consistent-field geometry used in many previous studies including the Monte Carlo calculation.

  19. Accurate Prediction of Glucuronidation of Structurally Diverse Phenolics by Human UGT1A9 Using Combined Experimental and In Silico Approaches

    PubMed Central

    Wu, Baojian; Wang, Xiaoqiang; Zhang, Shuxing; Hu, Ming

    2012-01-01

    Purpose The catalytic selectivity of human UGT1A9, an important membrane-bound enzyme catalyzing glucuronidation of xenobiotics were determined experimentally using 145 phenolics, and analyzed by 3D-QSAR methods. Methods The catalytic efficiency of UGT1A9 was determined by kinetic profiling. Quantitative structure activity relationships were analyzed using the CoMFA and CoMSIA techniques. Molecular alignment of the substrate structures was made by superimposing the glucuronidation site and its adjacent aromatic ring to achieve maximal steric overlap. For a substrate with multiple active glucuronidation sites, each site was considered as a separate substrate. Results The 3D-QSAR analyses produced statistically reliable models with good predictive power (CoMFA: q2 = 0.548, r2= 0.949, r2pred = 0.775; CoMSIA: q2 = 0.579, r2= 0.876, r2pred = 0.700). The contour coefficient maps were applied to elucidate structural features among substrates that are responsible for the selectivity differences. Furthermore, the contour coefficient maps were overlaid in the catalytic pocket of a homology model of UGT1A9; this enabled us to identify the UGT1A9 catalytic pocket with a high degree of confidence. Conclusion The CoMFA/CoMSIA models can predict the substrate selectivity and in vitro clearance of UGT1A9. Our findings also provide a possible molecular basis for understanding UGT1A9 functions and its substrate selectivity. PMID:22302521

  20. Is scoring system of computed tomography based metric parameters can accurately predicts shock wave lithotripsy stone-free rates and aid in the development of treatment strategies?

    PubMed Central

    Badran, Yasser Ali; Abdelaziz, Alsayed Saad; Shehab, Mohamed Ahmed; Mohamed, Hazem Abdelsabour Dief; Emara, Absel-Aziz Ali; Elnabtity, Ali Mohamed Ali; Ghanem, Maged Mohammed; ELHelaly, Hesham Abdel Azim

    2016-01-01

    Objective: The objective was to determine the predicting success of shock wave lithotripsy (SWL) using a combination of computed tomography based metric parameters to improve the treatment plan. Patients and Methods: Consecutive 180 patients with symptomatic upper urinary tract calculi 20 mm or less were enrolled in our study underwent extracorporeal SWL were divided into two main groups, according to the stone size, Group A (92 patients with stone ≤10 mm) and Group B (88 patients with stone >10 mm). Both groups were evaluated, according to the skin to stone distance (SSD) and Hounsfield units (≤500, 500–1000 and >1000 HU). Results: Both groups were comparable in baseline data and stone characteristics. About 92.3% of Group A rendered stone-free, whereas 77.2% were stone-free in Group B (P = 0.001). Furthermore, in both group SWL success rates was a significantly higher for stones with lower attenuation <830 HU than with stones >830 HU (P < 0.034). SSD were statistically differences in SWL outcome (P < 0.02). Simultaneous consideration of three parameters stone size, stone attenuation value, and SSD; we found that stone-free rate (SFR) was 100% for stone attenuation value <830 HU for stone <10 mm or >10 mm but total number SWL sessions and shock waves required for the larger stone group were higher than in the smaller group (P < 0.01). Furthermore, SFR was 83.3% and 37.5% for stone <10 mm, mean HU >830, SSD 90 mm and SSD >120 mm, respectively. On the other hand, SFR was 52.6% and 28.57% for stone >10 mm, mean HU >830, SSD <90 mm and SSD >120 mm, respectively. Conclusion: Stone size, stone density (HU), and SSD is simple to calculate and can be reported by radiologists to applying combined score help to augment predictive power of SWL, reduce cost, and improving of treatment strategies. PMID:27141192

  1. SNP development from RNA-seq data in a nonmodel fish: how many individuals are needed for accurate allele frequency prediction?

    PubMed

    Schunter, C; Garza, J C; Macpherson, E; Pascual, M

    2014-01-01

    Single nucleotide polymorphisms (SNPs) are rapidly becoming the marker of choice in population genetics due to a variety of advantages relative to other markers, including higher genomic density, data quality, reproducibility and genotyping efficiency, as well as ease of portability between laboratories. Advances in sequencing technology and methodologies to reduce genomic representation have made the isolation of SNPs feasible for nonmodel organisms. RNA-seq is one such technique for the discovery of SNPs and development of markers for large-scale genotyping. Here, we report the development of 192 validated SNP markers for parentage analysis in Tripterygion delaisi (the black-faced blenny), a small rocky-shore fish from the Mediterranean Sea. RNA-seq data for 15 individual samples were used for SNP discovery by applying a series of selection criteria. Genotypes were then collected from 1599 individuals from the same population with the resulting loci. Differences in heterozygosity and allele frequencies were found between the two data sets. Heterozygosity was lower, on average, in the population sample, and the mean difference between the frequencies of particular alleles in the two data sets was 0.135 ± 0.100. We used bootstrap resampling of the sequence data to predict appropriate sample sizes for SNP discovery. As cDNA library production is time-consuming and expensive, we suggest that using seven individuals for RNA sequencing reduces the probability of discarding highly informative SNP loci, due to lack of observed polymorphism, whereas use of more than 12 samples does not considerably improve prediction of true allele frequencies.

  2. Computer simulation to predict energy use, greenhouse gas emissions and costs for production of fluid milk using alternative processing methods

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Computer simulation is a useful tool for benchmarking the electrical and fuel energy consumption and water use in a fluid milk plant. In this study, a computer simulation model of the fluid milk process based on high temperature short time (HTST) pasteurization was extended to include models for pr...

  3. From pore-scale flow measurements towards a Computational Fluid Dynamics prediction of momentum exchange across river bed interface

    NASA Astrophysics Data System (ADS)

    Sambrook Smith, G.; Hardy, R. J.; Best, J.; Blois, G.; Lead, J.

    2010-12-01

    Developing numerical models capable of simulating the hydrodynamics of open-channel flows over rough and within permeable beds is crucial for predicting the morphodynamic evolution of alluvial channels, as well as understanding the complex physical-chemical processes occurring within the subsurface (hyporheic zone) of river beds. However, most current numerical models assume that alluvial streams have an impermeable channel bed, which represents a considerable simplification since experimental observations have shown turbulence within gravel-beds can be significant. Thus, Darcian theory, suitable for low-conductivity porous media, should not be applied within cohesionless gravel-bed rivers. Although the Reynolds Averaged Navier Stokes (RANS) equations can be used to model flow through a porous media if the internal morphology is known, this has rarely been accomplished, and the complexity of the internal morphology of the bed has meant that the normal approach to this problem is to volume-average the NS equations and close them with the Hazen-Dupui-Darcy (HDD) model. However, if the internal morphology of the bed is known a Computational Fluid Dynamics (CFD) approach with a mass flux scaling algorithm (MFSA), which has been developed to include complex bed topography into a numerically stable discretization, can be applied. This allows both time averaged, and time dependent prediction of the flow. Even though these models represent the state-of-the-art, they have yet to be validated, and hence their reliability remains unknown. The lack of appropriate validation data is due to the fact that experimental techniques cannot currently meet the significant challenges required to fully characterize the complex instantaneous turbulent patterns produced within bed pore spaces. To meet this challenge, a novel high-resolution endoscopic particle image velocimetry (E-PIV) technique, capable of collecting data within the pore spaces of a submerged permeable bed, has been

  4. A novel approach to gravitation from fluid theory: Titius-Bode structures, flat rotation rate of galaxies and other predictions

    NASA Astrophysics Data System (ADS)

    Munera, Hector A.

    2015-08-01

    The formal analogy between electromagnetism (EM) and gravitation was noted by Maxwell and Faraday, and later on by Heaviside in the 1890s; the analogy was extensively used in the gravito-magnetism of the 20th century. The connection between EM and fluid theory is explicit in Maxwell’s work, and the equivalence of Maxwell equations (ME) to various wave equations is explained in electrodynamics textbooks (say, Jackson’s) additionally, a little-known paper presented by Henri Malet to the Paris Academy of Sciences (1926), demonstrated that the validity of ME concurrently requires the validity of the vector and the scalar homogeneous wave equations.In the 1990s the present author reported in Foundations of Physics Letters the existence of novel solutions for the homogeneous wave equation in spherical coordinates; it turns out that one class of our solutions (the nonharmonic functions of the first-kind, NHFFK) is equivalent to the unified force of nature proposed around 1760 by Boscovich from philosophical considerations, but without a formal mathematical basis. Our finding is significant because it lends a mathematical foundation to Boscovich’s force, which has extremely interesting properties, as quantization in energy and distance —noted by J. J. Thomson before Bohr’s quantum theory.Associated with spherical surfaces in gravitational equilibrium, the family of even NHFFKs described here predict Titius-Body structures at different scales, as the solar system and the moons of Mars, Jupiter, Uranus, Saturn, and Neptune. Each calculated radius is compared to an average distance of moons/planets: the correlation and the R2 coefficients are quite high. The same NHFFK also predict the existence of ring structures, as those observed in Saturn, and in asteroids belts in our solar system. Newtonian gravity appears as the limit at very large distances from the center of force. The family of odd NHFFK exhibits a non-zero limit as distance tends to infinity, feature that

  5. TU-EF-204-01: Accurate Prediction of CT Tube Current Modulation: Estimating Tube Current Modulation Schemes for Voxelized Patient Models Used in Monte Carlo Simulations

    SciTech Connect

    McMillan, K; Bostani, M; McNitt-Gray, M; McCollough, C

    2015-06-15

    Purpose: Most patient models used in Monte Carlo-based estimates of CT dose, including computational phantoms, do not have tube current modulation (TCM) data associated with them. While not a problem for fixed tube current simulations, this is a limitation when modeling the effects of TCM. Therefore, the purpose of this work was to develop and validate methods to estimate TCM schemes for any voxelized patient model. Methods: For 10 patients who received clinically-indicated chest (n=5) and abdomen/pelvis (n=5) scans on a Siemens CT scanner, both CT localizer radiograph (“topogram”) and image data were collected. Methods were devised to estimate the complete x-y-z TCM scheme using patient attenuation data: (a) available in the Siemens CT localizer radiograph/topogram itself (“actual-topo”) and (b) from a simulated topogram (“sim-topo”) derived from a projection of the image data. For comparison, the actual TCM scheme was extracted from the projection data of each patient. For validation, Monte Carlo simulations were performed using each TCM scheme to estimate dose to the lungs (chest scans) and liver (abdomen/pelvis scans). Organ doses from simulations using the actual TCM were compared to those using each of the estimated TCM methods (“actual-topo” and “sim-topo”). Results: For chest scans, the average differences between doses estimated using actual TCM schemes and estimated TCM schemes (“actual-topo” and “sim-topo”) were 3.70% and 4.98%, respectively. For abdomen/pelvis scans, the average differences were 5.55% and 6.97%, respectively. Conclusion: Strong agreement between doses estimated using actual and estimated TCM schemes validates the methods for simulating Siemens topograms and converting attenuation data into TCM schemes. This indicates that the methods developed in this work can be used to accurately estimate TCM schemes for any patient model or computational phantom, whether a CT localizer radiograph is available or not

  6. Full-Dimensional Potential Energy and Dipole Moment Surfaces of GeH4 Molecule and Accurate First-Principle Rotationally Resolved Intensity Predictions in the Infrared.

    PubMed

    Nikitin, A V; Rey, M; Rodina, A; Krishna, B M; Tyuterev, Vl G

    2016-11-17

    Nine-dimensional potential energy surface (PES) and dipole moment surface (DMS) of the germane molecule are constructed using extended ab initio CCSD(T) calculations at 19 882 points. PES analytical representation is determined as an expansion in nonlinear symmetry adapted products of orthogonal and internal coordinates involving 340 parameters up to eighth order. Minor empirical refinement of the equilibrium geometry and of four quadratic parameters of the PES computed at the CCSD(T)/aug-cc-pVQZ-DK level of the theory yielded the accuracy below 1 cm(-1) for all experimentally known vibrational band centers of five stable isotopologues of (70)GeH4, (72)GeH4, (73)GeH4, (74)GeH4, and (76)GeH4 up to 8300 cm(-1). The optimized equilibrium bond re = 1.517 594 Å is very close to best ab initio values. Rotational energies up to J = 15 are calculated using potential expansion in normal coordinate tensors with maximum errors of 0.004 and 0.0006 cm(-1) for (74)GeH4 and (76)GeH4. The DMS analytical representation is determined through an expansion in symmetry-adapted products of internal nonlinear coordinates involving 967 parameters up to the sixth order. Vibration-rotation line intensities of five stable germane isotopologues were calculated from purely ab initio DMS using nuclear motion variational calculations with a full account of the tetrahedral symmetry of the molecules. For the first time a good overall agreement of main absorption features with experimental rotationally resolved Pacific Northwest National Laboratory spectra was achieved in the entire range of 700-5300 cm(-1). It was found that very accurate description of state-dependent isotopic shifts is mandatory to correctly describe complex patterns of observed spectra at natural isotopic abundance resulting from the superposition of five stable isotopologues. The data obtained in this work will be made available through the TheoReTS information system.

  7. Density-functional theory for polar fluids at functionalized surfaces. I. Fluid-wall association

    NASA Astrophysics Data System (ADS)

    Tripathi, Sandeep; Chapman, Walter G.

    2003-12-01

    We present a novel perturbation density-functional theory (DFT) to describe adsorption of associating fluids on surfaces activated with polar sites to which fluid molecules can bond or associate, such as water adsorbing on activated carbon, silica, clay minerals, etc. Association is modeled within the framework of first order thermodynamic perturbation theory (TPT1). In this first of two papers, we explore in detail the changes brought about in a system due to fluid-wall (FW) association. Hence fluid-fluid association is not considered here. However, the theory can be coupled with existing DF theories of associating fluids to study the interplay between the wall-fluid and fluid-fluid association as is shown in a future paper by S. Tripathi. The proposed theory, in excellent agreement with simulations, shows that FW association significantly changes the fluid structure and adsorption behavior. The theory accurately predicts the distribution of bonded and nonbonded species away from the surface, adsorption characteristics and surface coverage over a range of conditions commonly found in several real systems. The most striking feature of the theory is that in addition to properties away from the wall, it also estimates the distribution of the fluid along the surface, or the three-dimensional (3D) structure, despite being one-dimensional (1D) in form.

  8. A machine-learning approach reveals that alignment properties alone can accurately predict inference of lateral gene transfer from discordant phylogenies.

    PubMed

    Roettger, Mayo; Martin, William; Dagan, Tal

    2009-09-01

    Among the methods currently used in phylogenomic practice to detect the presence of lateral gene transfer (LGT), one of the most frequently employed is the comparison of gene tree topologies for different genes. In cases where the phylogenies for different genes are incompatible, or discordant, for well-supported branches there are three simple interpretations for the result: 1) gene duplications (paralogy) followed by many independent gene losses have occurred, 2) LGT has occurred, or 3) the phylogeny is well supported but for reasons unknown is nonetheless incorrect. Here, we focus on the third possibility by examining the properties of 22,437 published multiple sequence alignments, the Bayesian maximum likelihood trees for which either do or do not suggest the occurrence of LGT by the criterion of discordant branches. The alignments that produce discordant phylogenies differ significantly in several salient alignment properties from those that do not. Using a support vector machine, we were able to predict the inference of discordant tree topologies with up to 80% accuracy from alignment properties alone.

  9. Accurate predictions of spectroscopic and molecular properties of 27 Λ-S and 73 Ω states of AsS radical.

    PubMed

    Shi, Deheng; Song, Ziyue; Niu, Xianghong; Sun, Jinfeng; Zhu, Zunlue

    2016-01-15

    The PECs are calculated for the 27 Λ-S states and their corresponding 73 Ω states of AsS radical. Of these Λ-S states, only the 2(2)Δ and 5(4)Π states are replulsive. The 1(2)Σ(+), 2(2)Σ(+), 4(2)Π, 3(4)Δ, 3(4)Σ(+), and 4(4)Π states possess double wells. The 3(2)Σ(+) state possesses three wells. The A(2)Π, 3(2)Π, 1(2)Φ, 2(4)Π, 3(4)Π, 2(4)Δ, 3(4)Δ, 1(6)Σ(+), and 1(6)Π states are inverted with the SO coupling effect included. The 1(4)Σ(+), 2(4)Σ(+), 2(4)Σ(-), 2(4)Δ, 1(4)Φ, 1(6)Σ(+), and 1(6)Π states, the second wells of 1(2)Σ(+), 3(4)Σ(+), 4(2)Π, 4(4)Π, and 3(4)Δ states, and the third well of 3(2)Σ(+) state are very weakly-bound states. The PECs are extrapolated to the CBS limit. The effect of SO coupling on the PECs is discussed. The spectroscopic parameters are evaluated, and compared with available measurements and other theoretical ones. The vibrational properties of several weakly-bound states are determined. The spectroscopic properties reported here can be expected to be reliably predicted ones.

  10. Accurate predictions of spectroscopic and molecular properties of 27 Λ-S and 73 Ω states of AsS radical

    NASA Astrophysics Data System (ADS)

    Shi, Deheng; Song, Ziyue; Niu, Xianghong; Sun, Jinfeng; Zhu, Zunlue

    2016-01-01

    The PECs are calculated for the 27 Λ-S states and their corresponding 73 Ω states of AsS radical. Of these Λ-S states, only the 22Δ and 54Π states are replulsive. The 12Σ+, 22Σ+, 42Π, 34Δ, 34Σ+, and 44Π states possess double wells. The 32Σ+ state possesses three wells. The A2Π, 32Π, 12Φ, 24Π, 34Π, 24Δ, 34Δ, 16Σ+, and 16Π states are inverted with the SO coupling effect included. The 14Σ+, 24Σ+, 24Σ-, 24Δ, 14Φ, 16Σ+, and 16Π states, the second wells of 12Σ+, 34Σ+, 42Π, 44Π, and 34Δ states, and the third well of 32Σ+ state are very weakly-bound states. The PECs are extrapolated to the CBS limit. The effect of SO coupling on the PECs is discussed. The spectroscopic parameters are evaluated, and compared with available measurements and other theoretical ones. The vibrational properties of several weakly-bound states are determined. The spectroscopic properties reported here can be expected to be reliably predicted ones.

  11. Inter-operator Reliability of Magnetic Resonance Image-Based Computational Fluid Dynamics Prediction of Cerebrospinal Fluid Motion in the Cervical Spine.

    PubMed

    Martin, Bryn A; Yiallourou, Theresia I; Pahlavian, Soroush Heidari; Thyagaraj, Suraj; Bunck, Alexander C; Loth, Francis; Sheffer, Daniel B; Kröger, Jan Robert; Stergiopulos, Nikolaos

    2016-05-01

    For the first time, inter-operator dependence of MRI based computational fluid dynamics (CFD) modeling of cerebrospinal fluid (CSF) in the cervical spinal subarachnoid space (SSS) is evaluated. In vivo MRI flow measurements and anatomy MRI images were obtained at the cervico-medullary junction of a healthy subject and a Chiari I malformation patient. 3D anatomies of the SSS were reconstructed by manual segmentation by four independent operators for both cases. CFD results were compared at nine axial locations along the SSS in terms of hydrodynamic and geometric parameters. Intraclass correlation (ICC) assessed the inter-operator agreement for each parameter over the axial locations and coefficient of variance (CV) compared the percentage of variance for each parameter between the operators. Greater operator dependence was found for the patient (0.19 < ICC < 0.99) near the craniovertebral junction compared to the healthy subject (ICC > 0.78). For the healthy subject, hydraulic diameter and Womersley number had the least variance (CV = ~2%). For the patient, peak diastolic velocity and Reynolds number had the smallest variance (CV = ~3%). These results show a high degree of inter-operator reliability for MRI-based CFD simulations of CSF flow in the cervical spine for healthy subjects and a lower degree of reliability for patients with Type I Chiari malformation.

  12. Development of a Rat Plasma and Brain Extracellular Fluid Pharmacokinetic Model for Bupropion and Hydroxybupropion Based on Microdialysis Sampling, and Application to Predict Human Brain Concentrations.

    PubMed

    Cremers, Thomas I F H; Flik, Gunnar; Folgering, Joost H A; Rollema, Hans; Stratford, Robert E

    2016-05-01

    Administration of bupropion [(±)-2-(tert-butylamino)-1-(3-chlorophenyl)propan-1-one] and its preformed active metabolite, hydroxybupropion [(±)-1-(3-chlorophenyl)-2-[(1-hydroxy-2-methyl-2-propanyl)amino]-1-propanone], to rats with measurement of unbound concentrations by quantitative microdialysis sampling of plasma and brain extracellular fluid was used to develop a compartmental pharmacokinetics model to describe the blood-brain barrier transport of both substances. The population model revealed rapid equilibration of both entities across the blood-brain barrier, with resultant steady-state brain extracellular fluid/plasma unbound concentration ratio estimates of 1.9 and 1.7 for bupropion and hydroxybupropion, respectively, which is thus indicative of a net uptake asymmetry. An overshoot of the brain extracellular fluid/plasma unbound concentration ratio at early time points was observed with bupropion; this was modeled as a time-dependent uptake clearance of the drug across the blood-brain barrier. Translation of the model was used to predict bupropion and hydroxybupropion exposure in human brain extracellular fluid after twice-daily administration of 150 mg bupropion. Predicted concentrations indicate that preferential inhibition of the dopamine and norepinephrine transporters by the metabolite, with little to no contribution by bupropion, would be expected at this therapeutic dose. Therefore, these results extend nuclear imaging studies on dopamine transporter occupancy and suggest that inhibition of both transporters contributes significantly to bupropion's therapeutic efficacy.

  13. The M. D. Anderson Symptom Inventory-Head and Neck Module, a Patient-Reported Outcome Instrument, Accurately Predicts the Severity of Radiation-Induced Mucositis

    SciTech Connect

    Rosenthal, David I. Mendoza, Tito R.; Chambers, Mark; Burkett, V. Shannon; Garden, Adam S.; Hessell, Amy C.; Lewin, Jan S.; Ang, K. Kian; Kies, Merrill S.

    2008-12-01

    Purpose: To compare the M. D. Anderson Symptom Inventory-Head and Neck (MDASI-HN) module, a symptom burden instrument, with the Functional Assessment of Cancer Therapy-Head and Neck (FACT-HN) module, a quality-of-life instrument, for the assessment of mucositis in patients with head-and-neck cancer treated with radiotherapy and to identify the most distressing symptoms from the patient's perspective. Methods and Materials: Consecutive patients with head-and-neck cancer (n = 134) completed the MDASI-HN and FACT-HN before radiotherapy (time 1) and after 6 weeks of radiotherapy or chemoradiotherapy (time 2). The mean global and subscale scores for each instrument were compared with the objective mucositis scores determined from the National Cancer Institute Common Terminology Criteria for Adverse Events, version 3.0. Results: The global and subscale scores for each instrument showed highly significant changes from time 1 to time 2 and a significant correlation with the objective mucositis scores at time 2. Only the MDASI scores, however, were significant predictors of objective Common Terminology Criteria for Adverse Events mucositis scores on multivariate regression analysis (standardized regression coefficient, 0.355 for the global score and 0.310 for the head-and-neck cancer-specific score). Most of the moderate and severe symptoms associated with mucositis as identified on the MDASI-HN are not present on the FACT-HN. Conclusion: Both the MDASI-HN and FACT-HN modules can predict the mucositis scores. However, the MDASI-HN, a symptom burden instrument, was more closely associated with the severity of radiation-induced mucositis than the FACT-HN on multivariate regression analysis. This greater association was most likely related to the inclusion of a greater number of face-valid mucositis-related items in the MDASI-HN compared with the FACT-HN.

  14. Prognosis of locally advanced rectal cancer can be predicted more accurately using pre- and post-chemoradiotherapy neutrophil-lymphocyte ratios in patients who received preoperative chemoradiotherapy

    PubMed Central

    Sung, SooYoon; Park, Eun Young; Kay, Chul Seung

    2017-01-01

    Purpose The neutrophil-lymphocyte ratio (NLR) has been suggested as an inflammation-related factor, but also as an indicator of systemic anti-tumor immunity. We aimed to evaluate the prognostic value of the NLR and to propose a proper cut-off value in patients with locally advanced rectal cancer who received preoperative chemoradiation (CRT) followed by curative total mesorectal excision (TME). Methods A total of 110 rectal cancer patients with clinical T3-4 or node-positive disease were retrospectively analyzed. The NLR value before preoperative CRT (pre-CRT NLR) and the NLR value between preoperative CRT and surgery (post-CRT NLR) were obtained. Using a maximally selected log-rank test, cut-off values were determined as 1.75 for the pre-CRT NLR and 5.14 for the post-CRT NLR. Results Patients were grouped as follows: group A, pre-CRT NLR ≤ 1.75 and post-CRT NLR ≤ 5.14 (n = 29); group B, pre-CRT NLR > 1.75 and post-CRT NLR ≤ 5.14, or pre-CRT NLR ≤ 1.75 and post-CRT NLR > 5.14 (n = 61); group C, pre-CRT NLR > 1.75 and post-CRT NLR > 5.14 (n = 20). The median follow-up time was 31.1 months. The 3-year disease-free survival (DFS) and overall survival (OS) rates showed significant differences between the NLR groups (3-year DFS rate: 92.7% vs. 73.0% vs. 47.3%, for group A, B, and C, respectively, p = 0.018; 3-year OS rate: 96.0% vs. 85.5% vs. 59.8%, p = 0.034). Multivariate analysis revealed that the NLR was an independent prognostic factor for DFS (p = 0.028). Conclusion Both the pre-CRT NLR and the post-CRT NLR have a predictive value for the prognosis of patients with locally advanced rectal cancer treated with preoperative CRT followed by curative TME and adjuvant chemotherapy. A persistently elevated post-CRT NLR may be an indicator of an increased risk of distant metastasis. PMID:28291841

  15. Accurate quantum chemical calculations

    NASA Technical Reports Server (NTRS)

    Bauschlicher, Charles W., Jr.; Langhoff, Stephen R.; Taylor, Peter R.

    1989-01-01

    An important goal of quantum chemical calculations is to provide an understanding of chemical bonding and molecular electronic structure. A second goal, the prediction of energy differences to chemical accuracy, has been much harder to attain. First, the computational resources required to achieve such accuracy are very large, and second, it is not straightforward to demonstrate that an apparently accurate result, in terms of agreement with experiment, does not result from a cancellation of errors. Recent advances in electronic structure methodology, coupled with the power of vector supercomputers, have made it possible to solve a number of electronic structure problems exactly using the full configuration interaction (FCI) method within a subspace of the complete Hilbert space. These exact results can be used to benchmark approximate techniques that are applicable to a wider range of chemical and physical problems. The methodology of many-electron quantum chemistry is reviewed. Methods are considered in detail for performing FCI calculations. The application of FCI methods to several three-electron problems in molecular physics are discussed. A number of benchmark applications of FCI wave functions are described. Atomic basis sets and the development of improved methods for handling very large basis sets are discussed: these are then applied to a number of chemical and spectroscopic problems; to transition metals; and to problems involving potential energy surfaces. Although the experiences described give considerable grounds for optimism about the general ability to perform accurate calculations, there are several problems that have proved less tractable, at least with current computer resources, and these and possible solutions are discussed.

  16. Fluid imbalance

    MedlinePlus

    ... up in the body. This is called fluid overload (volume overload). This can lead to edema (excess fluid in ... Water imbalance; Fluid imbalance - dehydration; Fluid buildup; Fluid overload; Volume overload; Loss of fluids; Edema - fluid imbalance; ...

  17. The method of characteristics and computational fluid dynamics applied to the prediction of underexpanded jet flows in annular geometry

    NASA Astrophysics Data System (ADS)

    Kim, Sangwon

    2005-11-01

    High pressure (3.4 MPa) injection from a shroud valve can improve natural gas engine efficiency by enhancing fuel-air mixing. Since the fuel jet issuing from the shroud valve has a nearly annular jet flow configuration, it is necessary to analyze the annular jet flow to understand the fuel jet behavior in the mixing process and to improve the shroud design for better mixing. The method of characteristics (MOC) was used as the primary modeling algorithm in this work and Computational Fluid Dynamics (CFD) was used primarily to validate the MOC results. A consistent process for dealing with the coalescence of compression characteristic lines into a shock wave during the MOC computation was developed. By the application of shock polar in the pressure-flow angle plane to the incident shock wave for an axisymmetric underexpanded jet and the comparison with the triple point location found in experimental results, it was found that, in the static pressure ratios of 2--50, a triple point of the jet was located at the point where the flow angle after the incident shock became -5° relative to the axis and this point was situated between the von Neumann and detachment criteria on the incident shock. MOC computations of the jet flow with annular geometry were performed for pressure ratios of 10 and 20 with rannulus = 10--50 units, Deltar = 2 units. In this pressure ratio range, the MOC results did not predict a Mach disc in the core flow of the annular jet, but did indicate the formation of a Mach disc where the jet meets the axis of symmetry. The MOC results display the annular jet configurations clearly. Three types of nozzles for application to gas injectors (convergent-divergent nozzle, conical nozzle, and aerospike nozzle) were designed using the MOC and evaluated in on- and off-design conditions using CFD. The average axial momentum per unit mass was improved by 17 to 24% and the average kinetic energy per unit fuel mass was improved by 30 to 80% compared with a standard

  18. Implementing the Effects of Changing Landscape by the Recent Bark Beetle Infestation on Snow Accumulation and Ablation to More Accurately Predict Stream Flow in the Upper Little Laramie River, Wyoming watershed.

    NASA Astrophysics Data System (ADS)

    Heward, J.; Ohara, N.

    2014-12-01

    In many alpine regions, especially in the western United States, the snow pack is the cause of the peak discharge and most of the annual flow. A distributed snow melt model with a point-scale snow melt theory is used to estimate the timing and intensity of both snow accumulation and ablation. The type and distribution of vegetation across a watershed influences timing and intensity of snow melt processes. Efforts are being made to understand how a changing landscape will ultimately affect stream flow in a mountainous environment. This study includes an analysis of the effects of the recent bark beetle infestation, using leaf area index (LAI) data acquired from MODIS data sets. These changes were incorporated into the snow model to more accurately predict snow melt timing and intensity. It was observed through the primary model implementation that snowmelt was intensified by the LAI reduction. The radiation change and turbulent flux effects were separately quantified by the vegetation parameterization in the snow model. This distributed snow model will be used to more accurately predict stream flow in the Upper Little Laramie River, Wyoming watershed.

  19. Pollutant dispersion in a large indoor space: Part 2 -Computational Fluid Dynamics (CFD) predictions and comparison with ascale model experiment for isothermal flow

    SciTech Connect

    Finlayson, Elizabeth U.; Gadgil, Ashok J.; Thatcher, Tracy L.; Sextro, Richard G.

    2002-10-01

    This paper reports on an investigation of the adequacy of Computational fluid dynamics (CFD), using a standard Reynolds Averaged Navier Stokes (RANS) model, for predicting dispersion of neutrally buoyant gas in a large indoor space. We used CFD to predict pollutant (dye) concentration profiles in a water filled scale model of an atrium with a continuous pollutant source. Predictions from the RANS formulation are comparable to an ensemble average of independent identical experiments. Model results were compared to pollutant concentration data in a horizontal plane from experiments in a scale model atrium. Predictions were made for steady-state (fully developed) and transient (developing) pollutant concentrations. Agreement between CFD predictions and ensemble averaged experimental measurements is quantified using the ratios of CFD-predicted and experimentally measured dye concentration at a large number of points in the measurement plane. Agreement is considered good if these ratios fall between 0.5 and 2.0 at all points in the plane. The standard k-epsilon two equation turbulence model obtains this level of agreement and predicts pollutant arrival time to the measurement plane within a few seconds. These results suggest that this modeling approach is adequate for predicting isothermal pollutant transport in a large room with simple geometry.

  20. Thermophysical Properties of Fluids and Fluid Mixtures

    SciTech Connect

    Sengers, Jan V.; Anisimov, Mikhail A.

    2004-05-03

    The major goal of the project was to study the effect of critical fluctuations on the thermophysical properties and phase behavior of fluids and fluid mixtures. Long-range fluctuations appear because of the presence of critical phase transitions. A global theory of critical fluctuations was developed and applied to represent thermodynamic properties and transport properties of molecular fluids and fluid mixtures. In the second phase of the project, the theory was extended to deal with critical fluctuations in complex fluids such as polymer solutions and electrolyte solutions. The theoretical predictions have been confirmed by computer simulations and by light-scattering experiments. Fluctuations in fluids in nonequilibrium states have also been investigated.

  1. Small for gestational age and poor fluid intelligence in childhood predict externalizing behaviors among young adults born at extremely low birth weight.

    PubMed

    Lahat, Ayelet; Van Lieshout, Ryan J; Saigal, Saroj; Boyle, Michael H; Schmidt, Louis A

    2015-02-01

    Although infants born at extremely low birth weight (ELBW; birth weight < 1000 g) are at increased risk for developing later psychopathology, the mechanisms contributing to this association are largely unknown. In the present study, we examined a putative cognitive link to psychopathology in a cohort of ELBW survivors. These individuals were followed up prospectively at age 8 and again at ages 22-26. At 8 years, participants completed measures of fluid and general intelligence. As young adults, a subset of ELBW survivors free of major neurosensory impairments provided self-reports of personality characteristics related to psychopathology. Data from 66 participants indicated that, as predicted, the association between ELBW and externalizing behaviors was moderated by fluid intelligence. Specifically, ELBW individuals with poor fluid intelligence who were born small for gestational age (birth weight < 10th percentile for gestational age) showed the highest level of externalizing behaviors. These findings provide support for a cumulative risk model and suggest that fluid intelligence might be a cognitive mechanism contributing to the development of psychopathology among nonimpaired individuals who were born at ELBW and small for gestational age.

  2. Diagnosis Accuracy of Mean Arterial Pressure Variation during a Lung Recruitment Maneuver to Predict Fluid Responsiveness in Thoracic Surgery with One-Lung Ventilation

    PubMed Central

    Kang, Woon-Seok; Oh, Chung-Sik; Park, Chulmin; Shin, Bo Mi; Yoon, Tae-Gyoon; Rhee, Ka-Young; Woo, Nam-Sik

    2016-01-01

    Background. Lung recruitment maneuver (LRM) during thoracic surgery can reduce systemic venous return and resulting drop in systemic blood pressure depends on the patient's fluid status. We hypothesized that changes in systemic blood pressure during the transition in LRM from one-lung ventilation (OLV) to two-lung ventilation (TLV) may provide an index to predict fluid responsiveness. Methods. Hemodynamic parameters were measured before LRM (T0); after LRM at the time of the lowest mean arterial blood pressure (MAP) (T1) and at 3 minutes (T2); before fluid administration (T3); and 5 minutes after ending it (T4). If the stroke volume index increased by >25% following 10 mL/kg colloid administration for 30 minutes, then the patients were assigned to responder group. Results. Changes in MAP, central venous pressure (CVP), and stroke volume variation (SVV) between T0 and T1 were significantly larger in responders. Areas under the curve for change in MAP, CVP, and SVV were 0.852, 0.759, and 0.820, respectively; the optimal threshold values for distinguishment of responders were 9.5 mmHg, 0.5 mmHg, and 3.5%, respectively. Conclusions. The change in the MAP associated with LRM at the OLV to TLV conversion appears to be a useful indicator of fluid responsiveness after thoracic surgery. Trial Registration. This trial is registered at Clinical Research Information Service with KCT0000774. PMID:27819002

  3. Can Selforganizing Maps Accurately Predict Photometric Redshifts?

    NASA Technical Reports Server (NTRS)

    Way, Michael J.; Klose, Christian

    2012-01-01

    We present an unsupervised machine-learning approach that can be employed for estimating photometric redshifts. The proposed method is based on a vector quantization called the self-organizing-map (SOM) approach. A variety of photometrically derived input values were utilized from the Sloan Digital Sky Survey's main galaxy sample, luminous red galaxy, and quasar samples, along with the PHAT0 data set from the Photo-z Accuracy Testing project. Regression results obtained with this new approach were evaluated in terms of root-mean-square error (RMSE) to estimate the accuracy of the photometric redshift estimates. The results demonstrate competitive RMSE and outlier percentages when compared with several other popular approaches, such as artificial neural networks and Gaussian process regression. SOM RMSE results (using delta(z) = z(sub phot) - z(sub spec)) are 0.023 for the main galaxy sample, 0.027 for the luminous red galaxy sample, 0.418 for quasars, and 0.022 for PHAT0 synthetic data. The results demonstrate that there are nonunique solutions for estimating SOM RMSEs. Further research is needed in order to find more robust estimation techniques using SOMs, but the results herein are a positive indication of their capabilities when compared with other well-known methods

  4. Accurate sperm morphology assessment predicts sperm function.

    PubMed

    Abu Hassan Abu, D; Franken, D R; Hoffman, B; Henkel, R

    2012-05-01

    Sperm morphology has been associated with in vitro as well as in vivo fertilisation. The study aimed to evaluate the possible relation between the percentage of spermatozoa with normal morphology and the following sperm functional assays: (i) zona-induced acrosome reaction (ZIAR); (ii) DNA integrity; (iii) chromatin condensation; (iv) sperm apoptosis; and (v) fertilisation rates. Regression analysis was employed to calculate the association between morphology and different functional tests. Normal sperm morphology correlated significantly with the percentages of live acrosome-reacted spermatozoa in the ZIAR (r = 0.518; P < 0.0001; n = 92), DNA integrity (r = -0.515; P = 0.0018; n = 34), CMA(3) -positive spermatozoa (r = -0.745; P < 0.0001; n = 92), sperm apoptosis (r = -0.395; P = 0.0206; n = 34) and necrosis (r = -0.545; P = 0.0009; n = 34). Negative correlations existed between for the acrosome reaction, and DNA integrity, while negative associations were recorded with the percentages of CMA(3) -positive spermatozoa, apoptotic and necrotic spermatozoa. Sperm morphology is related to sperm dysfunction such as poor chromatin condensation, acrosome reaction and DNA integrity. Negative and significant correlations existed between normal sperm morphology and chromatin condensation, the percentage of spermatozoa with abnormal DNA and spermatozoa with apoptotic activity. The authors do not regard sperm morphology as the only test for the diagnosis of male fertility, but sperm morphology can serve as a valuable indicator of underlying dysfunction.

  5. Comparison of Hydrodynamic Load Predictions Between Engineering Models and Computational Fluid Dynamics for the OC4-DeepCwind Semi-Submersible: Preprint

    SciTech Connect

    Benitz, M. A.; Schmidt, D. P.; Lackner, M. A.; Stewart, G. M.; Jonkman, J.; Robertson, A.

    2014-09-01

    Hydrodynamic loads on the platforms of floating offshore wind turbines are often predicted with computer-aided engineering tools that employ Morison's equation and/or potential-flow theory. This work compares results from one such tool, FAST, NREL's wind turbine computer-aided engineering tool, and the computational fluid dynamics package, OpenFOAM, for the OC4-DeepCwind semi-submersible analyzed in the International Energy Agency Wind Task 30 project. Load predictions from HydroDyn, the offshore hydrodynamics module of FAST, are compared with high-fidelity results from OpenFOAM. HydroDyn uses a combination of Morison's equations and potential flow to predict the hydrodynamic forces on the structure. The implications of the assumptions in HydroDyn are evaluated based on this code-to-code comparison.

  6. Statistical analysis of accurate prediction of local atmospheric optical attenuation with a new model according to weather together with beam wandering compensation system: a season-wise experimental investigation

    NASA Astrophysics Data System (ADS)

    Arockia Bazil Raj, A.; Padmavathi, S.

    2016-07-01

    Atmospheric parameters strongly affect the performance of Free Space Optical Communication (FSOC) system when the optical wave is propagating through the inhomogeneous turbulent medium. Developing a model to get an accurate prediction of optical attenuation according to meteorological parameters becomes significant to understand the behaviour of FSOC channel during different seasons. A dedicated free space optical link experimental set-up is developed for the range of 0.5 km at an altitude of 15.25 m. The diurnal profile of received power and corresponding meteorological parameters are continuously measured using the developed optoelectronic assembly and weather station, respectively, and stored in a data logging computer. Measured meteorological parameters (as input factors) and optical attenuation (as response factor) of size [177147 × 4] are used for linear regression analysis and to design the mathematical model that is more suitable to predict the atmospheric optical attenuation at our test field. A model that exhibits the R2 value of 98.76% and average percentage deviation of 1.59% is considered for practical implementation. The prediction accuracy of the proposed model is investigated along with the comparative results obtained from some of the existing models in terms of Root Mean Square Error (RMSE) during different local seasons in one-year period. The average RMSE value of 0.043-dB/km is obtained in the longer range dynamic of meteorological parameters variations.

  7. Near-infrared reflectance spectroscopy (NIRS) enables the fast and accurate prediction of essential amino acid contents. 2. Results for wheat, barley, corn, triticale, wheat bran/middlings, rice bran, and sorghum.

    PubMed

    Fontaine, Johannes; Schirmer, Barbara; Hörr, Jutta

    2002-07-03

    Further NIRS calibrations were developed for the accurate and fast prediction of the total contents of methionine, cystine, lysine, threonine, tryptophan, and other essential amino acids, protein, and moisture in the most important cereals and brans or middlings for animal feed production. More than 1100 samples of global origin collected over five years were analyzed for amino acids following the Official Methods of the United States and European Union. Detailed data and graphics are given to characterize the obtained calibration equations. NIRS was validated with 98 independent samples for wheat and 78 samples for corn and compared to amino acid predictions using linear crude protein regression equations. With a few exceptions, validation showed that 70-98% of the amino acid variance in the samples could be explained using NIRS. Especially for lysine and methionine, the most limiting amino acids for farm animals, NIRS can predict contents in cereals much better than crude protein regressions. Through low cost and high speed of analysis NIRS enables the amino acid analysis of many samples in order to improve the accuracy of feed formulation and obtain better quality and lower production costs.

  8. The Role of Fluid, Crystallized, and Creative Abilities in the Prediction of Scores on Essay and Objective Tests.

    ERIC Educational Resources Information Center

    Legg, Sue M.; Ware, William B.

    Student and test characteristics were examined by multiple regression analysis and discriminant function analysis to explain why 171 political science undergraduates scored differently on essay versus objective final examinations. Student characteristics included: (1) patterns of creative, crystallized, and fluid abilities as measured by the…

  9. Predictions of hydrothermal alteration within near-ridge oceanic crust from coordinated geochemical and fluid flow models

    USGS Publications Warehouse

    Wetzel, L.R.; Raffensperger, J.P.; Shock, E.L.

    2001-01-01

    Coordinated geochemical and hydrological calculations guide our understanding of the composition, fluid flow patterns, and thermal structure of near-ridge oceanic crust. The case study presented here illustrates geochemical and thermal changes taking place as oceanic crust ages from 0.2 to 1.0 Myr. Using a finite element code, we model fluid flow and heat transport through the upper few hundred meters of an abyssal hill created at an intermediate spreading rate. We use a reaction path model with a customized database to calculate equilibrium fluid compositions and mineral assemblages of basalt and seawater at 500 bars and temperatures ranging from 150 to 400??C. In one scenario, reaction path calculations suggest that volume increases on the order of 10% may occur within portions of the basaltic basement. If this change in volume occurred, it would be sufficient to fill all primary porosity in some locations, effectively sealing off portions of the oceanic crust. Thermal profiles resulting from fluid flow simulations indicate that volume changes along this possible reaction path occur primarily within the first 0.4 Myr of crustal aging. ?? 2001 Elsevier Science B.V. All rights reserved.

  10. Fluid Shifts

    NASA Technical Reports Server (NTRS)

    Stenger, M.; Hargens, A.; Dulchavsky, S.; Ebert, D.; Lee, S.; Lauriie, S.; Garcia, K.; Sargsyan, A.; Martin, D.; Ribeiro, L.; Lui, J.; Macias, B.; Arbeille, P.; Danielson, R.; Chang, D.; Johnston, S.; Ploutz-Snyder, R.; Smith, S.

    2016-01-01

    NASA is focusing on long-duration missions on the International Space Station (ISS) and future exploration-class missions beyond low-Earth orbit. Visual acuity changes observed after short-duration missions were largely transient, but more than 50% of ISS astronauts experienced more profound, chronic changes with objective structural and functional findings such as papilledema and choroidal folds. Globe flattening, optic nerve sheath dilation, and optic nerve tortuosity also are apparent. This pattern is referred to as the visual impairment and intracranial pressure (VIIP) syndrome. VIIP signs and symptoms, as well as postflight lumbar puncture data, suggest that elevated intracranial pressure (ICP) may be associated with the spaceflight-induced cephalad fluid shifts, but this hypothesis has not been tested. The purpose of this study is to characterize fluid distribution and compartmentalization associated with long-duration spaceflight, and to correlate these findings with vision changes and other elements of the VIIP syndrome. We also seek to determine whether the magnitude of fluid shifts during spaceflight, as well as the VIIP-related effects of those shifts, is predicted by the crewmember's preflight conditions and responses to acute hemodynamic manipulations (such as head-down tilt). Lastly, we will evaluate the patterns of fluid distribution in ISS astronauts during acute reversal of fluid shifts through application of lower body negative pressure (LBNP) interventions to characterize and explain general and individual responses. METHODS: We will examine a variety of physiologic variables in 10 long-duration ISS crewmembers using the test conditions and timeline presented in the Figure below. Measures include: (1) fluid compartmentalization (total body water by D2O, extracellular fluid by NaBr, intracellular fluid by calculation, plasma volume by CO rebreathe, interstitial fluid by calculation); (2) forehead/eyelids, tibia, calcaneus tissue thickness (by

  11. An immersed boundary method for two-phase fluids and gels and the swimming of Caenorhabditis elegans through viscoelastic fluids

    PubMed Central

    Lee, Pilhwa; Wolgemuth, Charles W.

    2016-01-01

    The swimming of microorganisms typically involves the undulation or rotation of thin, filamentary objects in a fluid or other medium. Swimming in Newtonian fluids has been examined extensively, and only recently have investigations into microorganism swimming through non-Newtonian fluids and gels been explored. The equations that govern these more complex media are often nonlinear and require computational algorithms to study moderate to large amplitude motions of the swimmer. Here, we develop an immersed boundary method for handling fluid-structure interactions in a general two-phase medium, where one phase is a Newtonian fluid and the other phase is viscoelastic (e.g., a polymer melt or network). We use this algorithm to investigate the swimming of an undulating, filamentary swimmer in 2D (i.e., a sheet). A novel aspect of our method is that it allows one to specify how forces produced by the swimmer are distributed between the two phases of the fluid. The algorithm is validated by comparing theoretical predictions for small amplitude swimming in gels and viscoelastic fluids. We show how the swimming velocity depends on material parameters of the fluid and the interaction between the fluid and swimmer. In addition, we simulate the swimming of Caenorhabditis elegans in viscoelastic fluids and find good agreement between the swimming speeds and fluid flows in our simulations and previous experimental measurements. These results suggest that our methodology provides an accurate means for exploring the physics of swimming through non-Newtonian fluids and gels. PMID:26858520

  12. Phase behavior of coal fluids: Data for correlation development

    SciTech Connect

    Robinson, R.L. Jr.

    1990-02-06

    The effective design and operation of processes for conversion of coal to fluid fuels requires accurate knowledge of the phase behavior of the fluid mixtures encountered in the conversion process. Multiple phases are present in essentially all stages of feed preparation, conversion reactions and product separation; thus, knowledge of the behavior of these multiple phases is important in each step. The overall objective of the author's work is to develop accurate predictive methods for representation of vapor-liquid equilibria in systems encountered in coal conversion processes. 59 refs., 6 figs., 7 tabs.

  13. Prediction of {sup 2}D Rydberg energy levels of {sup 6}Li and {sup 7}Li based on very accurate quantum mechanical calculations performed with explicitly correlated Gaussian functions

    SciTech Connect

    Bubin, Sergiy; Sharkey, Keeper L.; Adamowicz, Ludwik

    2013-04-28

    Very accurate variational nonrelativistic finite-nuclear-mass calculations employing all-electron explicitly correlated Gaussian basis functions are carried out for six Rydberg {sup 2}D states (1s{sup 2}nd, n= 6, Horizontal-Ellipsis , 11) of the {sup 7}Li and {sup 6}Li isotopes. The exponential parameters of the Gaussian functions are optimized using the variational method with the aid of the analytical energy gradient determined with respect to these parameters. The experimental results for the lower states (n= 3, Horizontal-Ellipsis , 6) and the calculated results for the higher states (n= 7, Horizontal-Ellipsis , 11) fitted with quantum-defect-like formulas are used to predict the energies of {sup 2}D 1s{sup 2}nd states for {sup 7}Li and {sup 6}Li with n up to 30.

  14. More-Accurate Model of Flows in Rocket Injectors

    NASA Technical Reports Server (NTRS)

    Hosangadi, Ashvin; Chenoweth, James; Brinckman, Kevin; Dash, Sanford

    2011-01-01

    An improved computational model for simulating flows in liquid-propellant injectors in rocket engines has been developed. Models like this one are needed for predicting fluxes of heat in, and performances of, the engines. An important part of predicting performance is predicting fluctuations of temperature, fluctuations of concentrations of chemical species, and effects of turbulence on diffusion of heat and chemical species. Customarily, diffusion effects are represented by parameters known in the art as the Prandtl and Schmidt numbers. Prior formulations include ad hoc assumptions of constant values of these parameters, but these assumptions and, hence, the formulations, are inaccurate for complex flows. In the improved model, these parameters are neither constant nor specified in advance: instead, they are variables obtained as part of the solution. Consequently, this model represents the effects of turbulence on diffusion of heat and chemical species more accurately than prior formulations do, and may enable more-accurate prediction of mixing and flows of heat in rocket-engine combustion chambers. The model has been implemented within CRUNCH CFD, a proprietary computational fluid dynamics (CFD) computer program, and has been tested within that program. The model could also be implemented within other CFD programs.

  15. Fluid Shifts

    NASA Technical Reports Server (NTRS)

    Stenger, M. B.; Hargens, A.; Dulchavsky, S.; Ebert, D.; Lee, S.; Laurie, S.; Garcia, K.; Sargsyan, A.; Martin, D.; Lui, J.; Macias, B.; Arbeille, P.; Danielson, R.; Chang, D.; Gunga, H.; Johnston, S.; Westby, C.; Ribeiro, L.; Ploutz-Snyder, R.; Smith, S.

    2015-01-01

    INTRODUCTION: Mechanisms responsible for the ocular structural and functional changes that characterize the visual impairment and intracranial pressure (ICP) syndrome (VIIP) are unclear, but hypothesized to be secondary to the cephalad fluid shift experienced in spaceflight. This study will relate the fluid distribution and compartmentalization associated with long-duration spaceflight with VIIP symptoms. We also seek to determine whether the magnitude of fluid shifts during spaceflight, as well as the VIIP-related effects of those shifts, can be predicted preflight with acute hemodynamic manipulations, and also if lower body negative pressure (LBNP) can reverse the VIIP effects. METHODS: Physiologic variables will be examined pre-, in- and post-flight in 10 International Space Station crewmembers including: fluid compartmentalization (D2O and NaBr dilution); interstitial tissue thickness (ultrasound); vascular dimensions and dynamics (ultrasound and MRI (including cerebrospinal fluid pulsatility)); ocular measures (optical coherence tomography, intraocular pressure, ultrasound); and ICP measures (tympanic membrane displacement, otoacoustic emissions). Pre- and post-flight measures will be assessed while upright, supine and during 15 deg head-down tilt (HDT). In-flight measures will occur early and late during 6 or 12 month missions. LBNP will be evaluated as a countermeasure during HDT and during spaceflight. RESULTS: The first two crewmembers are in the preflight testing phase. Preliminary results characterize the acute fluid shifts experienced from upright, to supine and HDT postures (increased stroke volume, jugular dimensions and measures of ICP) which are reversed with 25 millimeters Hg LBNP. DISCUSSION: Initial results indicate that acute cephalad fluid shifts may be related to VIIP symptoms, but also may be reversible by LBNP. The effect of a chronic fluid shift has yet to be evaluated. Learning Objectives: Current spaceflight VIIP research is described

  16. Benchmarking a computational fluid dynamics model of separated flow in a thin rectangular channel for use in predictive design analysis

    SciTech Connect

    Stovall, T.K.; Crabtree, A.; Felde, D.

    1995-04-01

    The Advanced Neutron Source (ANS) reactor is being designed to provide a research tool with capabilities beyond those of any existing reactors. One portion of its state-of-the-art design requires high speed fluid flow through narrow channels between the fuel plates in the core. Experience with previous reactors has shown that fuel plate damage can occur when debris becomes lodged at the entrance to these channels. Such debris can disrupt the fluid flow to the plate surfaces and prevent adequate cooling of the fuel. Preliminary ANS designs addressed this issue by providing an unheated entrance length for each fuel plate. In theory, any flow disruption would recover within this unheated length, thus providing adequate heat removal from the downstream heated portions of the fuel plates.

  17. validation and Enhancement of Computational Fluid Dynamics and Heat Transfer Predictive Capabilities for Generation IV Reactor Systems

    SciTech Connect

    Robert E. Spall; Barton Smith; Thomas Hauser

    2008-12-08

    Nationwide, the demand for electricity due to population and industrial growth is on the rise. However, climate change and air quality issues raise serious questions about the wisdom of addressing these shortages through the construction of additional fossil fueled power plants. In 1997, the President's Committee of Advisors on Science and Technology Energy Research and Development Panel determined that restoring a viable nuclear energy option was essential and that the DOE should implement a R&D effort to address principal obstacles to achieving this option. This work has addressed the need for improved thermal/fluid analysis capabilities, through the use of computational fluid dynamics, which are necessary to support the design of generation IV gas-cooled and supercritical water reactors.

  18. Intrathoracic impedance vs daily weight monitoring for predicting worsening heart failure events: results of the Fluid Accumulation Status Trial (FAST).

    PubMed

    Abraham, William T; Compton, Steven; Haas, Garrie; Foreman, Blair; Canby, Robert C; Fishel, Robert; McRae, Scott; Toledo, Gloria B; Sarkar, Shantanu; Hettrick, Douglas A

    2011-01-01

    The relative sensitivity and unexplained detection rate of changes in intrathoracic impedance has not been compared with standard heart failure (HF) monitoring using daily weight changes. The Fluid Accumulation Status Trial (FAST) prospectively followed 156 HF patients with implanted cardioverter-defibrillator or cardiac resynchronization therapy defibrillator devices modified to record daily changes in intrathoracic impedance in a blinded fashion for 537±312 days. Daily impedance changes were used to calculate a fluid index that could be compared with a prespecified threshold. True positives were defined as adjudicated episodes of worsening HF occurring within 30 days of a fluid index above threshold or an acute weight gain. Unexplained detections were defined as threshold crossings or acute weight gains not associated with worsening HF. Impedance measurements were performed on >99% of follow-up days, compared with only 76% of days for weight measurements. Sixty-five HF events occurred during follow-up (0.32/patient-year). Forty HF events were detected by impedance but not weight, whereas 5 were detected by weight but not impedance. Sensitivity was greater (76% vs 23%; P<.0001) and unexplained detection rate was lower (1.9 vs 4.3/patient-year; P<.0001) for intrathoracic impedance monitoring at the threshold of 60Ω days compared with acute weight increases of 3 lbs in 1 day or 5 lbs in 3 days and also over a wide range of fluid index and weight thresholds. The sensitivity and unexplained detection rate of intrathoracic impedance monitoring was superior to that seen for acute weight changes. Intrathoracic impedance monitoring represents a useful adjunctive clinical tool for managing HF in patients with implanted devices.

  19. Prediction and monitoring of fluid responsiveness after coronary bypass surgery using the Initial Systolic Time Interval: Preliminary results

    NASA Astrophysics Data System (ADS)

    Smorenberg, A.; Lust, E. J.; Verdaasdonk, R. M.; Groeneveld, A. B. J.; Meijer, J. H.

    2010-04-01

    The objective of the study is to develop a non-invasive method to optimize the assessment of cardiac preload and therapeutic fluid administration after coronary artery bypass surgery. Previous studies have reported that the pre-ejection period (PEP), obtained from the electro-cardiogram (ECG) and from the invasively measured arterial pressure Pa, can be used for this assessment as it is dependent on the cardiac preload. The Initial Systolic Time Interval (ISTI), obtained non-invasively by simultaneous measurement of the Electro-CardioGram (ECG) and Impedance CardioGram (ICG), is expected to depend on the cardiac preload as well. 16 patients, admitted to the Intensive Care Unit after coronary artery bypass surgery and presumably hypovolaemic, were measured during administration of 2×250 ml of an isosmotic colloidal fluid solution. The parameters PEP and ISTI were determined before and after the administrations and compared with the change in cardiac output (CO), obtained by a thermodilution technique. Preliminary results show significant relationships between ISTI and CO and between changes in both of these variables before and after fluid administration.

  20. A thermal NO(x) prediction model - Scalar computation module for CFD codes with fluid and kinetic effects

    NASA Technical Reports Server (NTRS)

    Mcbeath, Giorgio; Ghorashi, Bahman; Chun, Kue

    1993-01-01

    A thermal NO(x) prediction model is developed to interface with a CFD, k-epsilon based code. A converged solution from the CFD code is the input to the postprocessing model for prediction of thermal NO(x). The model uses a decoupled analysis to estimate the equilibrium level of (NO(x))e which is the constant rate limit. This value is used to estimate the flame (NO(x)) and in turn predict the rate of formation at each node using a two-step Zeldovich mechanism. The rate is fixed on the NO(x) production rate plot by estimating the time to reach equilibrium by a differential analysis based on the reaction: O + N2 = NO + N. The rate is integrated in the nonequilibrium time space based on the residence time at each node in the computational domain. The sum of all nodal predictions yields the total NO(x) level.

  1. Real-Time PCR Detection of Paenibacillus spp. in Raw Milk To Predict Shelf Life Performance of Pasteurized Fluid Milk Products

    PubMed Central

    Ranieri, Matthew L.; Ivy, Reid A.; Mitchell, W. Robert; Call, Emma; Masiello, Stephanie N.; Wiedmann, Martin

    2012-01-01

    Psychrotolerant sporeformers, specifically Paenibacillus spp., are important spoilage bacteria for pasteurized, refrigerated foods such as fluid milk. While Paenibacillus spp. have been isolated from farm environments, raw milk, processing plant environments, and pasteurized fluid milk, no information on the number of Paenibacillus spp. that need to be present in raw milk to cause pasteurized milk spoilage was available. A real-time PCR assay targeting the 16S rRNA gene was designed to detect Paenibacillus spp. in fluid milk and to discriminate between Paenibacillus and other closely related spore-forming bacteria. Specificity was confirmed using 16 Paenibacillus and 17 Bacillus isolates. All 16 Paenibacillus isolates were detected with a mean cycle threshold (CT) of 19.14 ± 0.54. While 14/17 Bacillus isolates showed no signal (CT > 40), 3 Bacillus isolates showed very weak positive signals (CT = 38.66 ± 0.65). The assay provided a detection limit of approximately 3.25 × 101 CFU/ml using total genomic DNA extracted from raw milk samples inoculated with Paenibacillus. Application of the TaqMan PCR to colony lysates obtained from heat-treated and enriched raw milk provided fast and accurate detection of Paenibacillus. Heat-treated milk samples where Paenibacillus (≥1 CFU/ml) was detected by this colony TaqMan PCR showed high bacterial counts (>4.30 log CFU/ml) after refrigerated storage (6°C) for 21 days. We thus developed a tool for rapid detection of Paenibacillus that has the potential to identify raw milk with microbial spoilage potential as a pasteurized product. PMID:22685148

  2. Rotor noise due to atmospheric turbulence ingestion. I - Fluid mechanics

    NASA Technical Reports Server (NTRS)

    Simonich, J. C.; Amiet, R. K.; Schlinker, R. H.; Greitzer, E. M.

    1986-01-01

    In the present analytical procedure for the prediction of helicopter rotor noise generation due to the ingestion of atmospheric turbulence, different models for turbulence fluid mechanics and the ingestion process are combined. The mean flow and turbulence statistics associated with the atmospheric boundary layer are modeled with attention to the effects of atmospheric stability length, windspeed, and altitude. The turbulence field can be modeled as isotropic, locally stationary, and homogeneous. For large mean flow contraction ratios, accurate predictions of turbulence vorticity components at the rotor face requires the incorporation of the differential drift of fluid particles on adjacent streamlines.

  3. Optimization of crystal nucleation close to a metastable fluid-fluid phase transition

    PubMed Central

    Wedekind, Jan; Xu, Limei; Buldyrev, Sergey V.; Stanley, H. Eugene; Reguera, David; Franzese, Giancarlo

    2015-01-01

    The presence of a metastable fluid-fluid critical point is thought to dramatically influence the crystallization pathway, increasing the nucleation rate by many orders of magnitude over the predictions of classical nucleation theory. We use molecular dynamics simulations to study the kinetics of crystallization in the vicinity of this metastable critical point and throughout the metastable fluid-fluid phase diagram. To quantitatively understand how the fluid-fluid phase separation affects the crystal nucleation, we evaluate accurately the kinetics and reconstruct the thermodynamic free-energy landscape of crystal formation. Contrary to expectations, we find no special advantage of the proximity of the metastable critical point on the crystallization rates. However, we find that the ultrafast formation of a dense liquid phase causes the crystallization to accelerate both near the metastable critical point and almost everywhere below the fluid-fluid spinodal line. These results unveil three different scenarios for crystallization that could guide the optimization of the process in experiments PMID:26095898

  4. Current Progress of a Finite Element Computational Fluid Dynamics Prediction of Flutter for the AeroStructures Test Wing

    NASA Technical Reports Server (NTRS)

    Arena, Andrew S., Jr.

    2002-01-01

    This progress report focuses on the use of the STructural Analysis RoutineS suite program, SOLIDS, input for the AeroStructures Test Wing. The AeroStructures Test Wing project as a whole is described. The use of the SOLIDS code to find the mode shapes of a structure is discussed. The frequencies, and the structural dynamics to which they relate are examined. The results of the CFD predictions are compared to experimental data from a Ground Vibration Test.

  5. In-situ fluid-pressure measurements for earthquake prediction: An example from a deep well at Hi Vista, California

    USGS Publications Warehouse

    Healy, J.H.; Urban, T.C.

    1985-01-01

    Short-term earthquake prediction requires sensitive instruments for measuring the small anomalous changes in stress and strain that precede earthquakes. Instruments installed at or near the surface have proven too noisy for measuring anomalies of the size expected to occur, and it is now recognized that even to have the possibility of a reliable earthquake-prediction system will require instruments installed in drill holes at depths sufficient to reduce the background noise to a level below that of the expected premonitory signals. We are conducting experiments to determine the maximum signal-to-noise improvement that can be obtained in drill holes. In a 592 m well in the Mojave Desert near Hi Vista, California, we measured water-level changes with amplitudes greater than 10 cm, induced by earth tides. By removing the effects of barometric pressure and the stress related to earth tides, we have achieved a sensitivity to volumetric strain rates of 10-9 to 10-10 per day. Further improvement may be possible, and it appears that a successful earthquake-prediction capability may be achieved with an array of instruments installed in drill holes at depths of about 1 km, assuming that the premonitory strain signals are, in fact, present. ?? 1985 Birkha??user Verlag.

  6. Carbohydrate antigens in nipple aspirate fluid predict the presence of atypia and cancer in women requiring diagnostic breast biopsy

    PubMed Central

    2010-01-01

    Background The goal of this prospective study was to determine (a) concentrations of the carbohydrate biomarkers Thomsen Friedenreich (TF) antigen and its precursor, Tn antigen, in nipple discharge (ND) collected from women requiring biopsy because of a suspicious breast lesion; and (b) if concentration levels predicted pathologic diagnosis. Methods Adult women requiring biopsy to exclude breast cancer were enrolled and ND obtained. The samples from 124 women were analyzed using an anti-TF and anti-Tn monoclonal antibodies in direct immunoassay. Results The highest median concentration in ND for TF and Tn was in women with ductal carcinoma in situ (DCIS). TF was higher in women with 1) cancer (DCIS or invasive) vs. either no cancer (atypia or benign pathology, p = .048), or benign pathology (p = .018); and 2) abnormal (atypia or cancer) versus benign pathology (p = .016); and was more predictive of atypia or cancer in post- compared to premenopausal women. Tn was not predictive of disease. High TF concentration and age were independent predictors of disease, correctly classifying either cancer or abnormal vs. benign pathology 83% of the time in postmenopausal women. Conclusions TF concentrations in ND were higher in women with precancer and cancer compared to women with benign disease, and TF was an independent predictor of breast atypia and cancer. TF may prove useful in early breast cancer detection. PMID:20920311

  7. Postoperative fluid management

    PubMed Central

    Kayilioglu, Selami Ilgaz; Dinc, Tolga; Sozen, Isa; Bostanoglu, Akin; Cete, Mukerrem; Coskun, Faruk

    2015-01-01

    Postoperative care units are run by an anesthesiologist or a surgeon, or a team formed of both. Management of postoperative fluid therapy should be done considering both patients’ status and intraoperative events. Types of the fluids, amount of the fluid given and timing of the administration are the main topics that determine the fluid management strategy. The main goal of fluid resuscitation is to provide adequate tissue perfusion without harming the patient. The endothelial glycocalyx dysfunction and fluid shift to extracellular compartment should be considered wisely. Fluid management must be done based on patient’s body fluid status. Patients who are responsive to fluids can benefit from fluid resuscitation, whereas patients who are not fluid responsive are more likely to suffer complications of over-hydration. Therefore, common use of central venous pressure measurement, which is proved to be inefficient to predict fluid responsiveness, should be avoided. Goal directed strategy is the most rational approach to assess the patient and maintain optimum fluid balance. However, accessible and applicable monitoring tools for determining patient’s actual fluid need should be further studied and universalized. The debate around colloids and crystalloids should also be considered with goal directed therapies. Advantages and disadvantages of each solution must be evaluated with the patient’s specific condition. PMID:26261771

  8. Quantum mechanically based estimation of perturbed-chain polar statistical associating fluid theory parameters for analyzing their physical significance and predicting properties.

    PubMed

    Nhu, Nguyen Van; Singh, Mahendra; Leonhard, Kai

    2008-05-08

    We have computed molecular descriptors for sizes, shapes, charge distributions, and dispersion interactions for 67 compounds using quantum chemical ab initio and density functional theory methods. For the same compounds, we have fitted the three perturbed-chain polar statistical associating fluid theory (PCP-SAFT) equation of state (EOS) parameters to experimental data and have performed a statistical analysis for relations between the descriptors and the EOS parameters. On this basis, an analysis of the physical significance of the parameters, the limits of the present descriptors, and the PCP-SAFT EOS has been performed. The result is a method that can be used to estimate the vapor pressure curve including the normal boiling point, the liquid volume, the enthalpy of vaporization, the critical data, mixture properties, and so on. When only two of the three parameters are predicted and one is adjusted to experimental normal boiling point data, excellent predictions of all investigated pure compound and mixture properties are obtained. We are convinced that the methodology presented in this work will lead to new EOS applications as well as improved EOS models whose predictive performance is likely to surpass that of most present quantum chemically based, quantitative structure-property relationship, and group contribution methods for a broad range of chemical substances.

  9. Antigen sandwich ELISA predicts RT-PCR detection of dengue virus genome in infected culture fluids of Aedes albopictus C6/36 cells.

    PubMed

    Buerano, Corazon C; Natividad, Filipinas F; Contreras, Rodolfo C; Ibrahim, Ima Nurisa; Mangada, Marlou Noel M; Hasebe, Futoshi; Inoue, Shingo; Matias, Ronald R; Igarashi, Akira

    2008-09-01

    Antigen detection by sandwich ELISA was evaluated to predict RT-PCR detection of dengue viral genome in infected culture fluid of Aedes albopictus clone C6/36 cells. Serum specimens collected from dengue patients within 5 days from onset of fever in 2 hospitals in Metro Manila, Philippines, were inoculated into C6/36 cells, and incubated at 28 degrees C. A total of 282 infected culture fluid specimens were harvested and examined by sandwich ELISA and RT-PCR to detect dengue viral antigen and genome, respectively. In the sandwich ELISA, the P/N ratio was calculated by dividing optical density (OD) of a given test specimen by the OD of the standard negative specimen. Samples with a P/N ratio > or = 4.001 were positive for viral genome detection by RT-PCR. The sensitivity and specificity of antigen sandwich ELISA with RT-PCR as the standard, were 90.4% and 100%, respectively. Although antigen sandwich ELISA is less sensitive than RT-PCR, its usefulness lies in its capability to screen a large number of samples at a minimum cost, especially during an outbreak. Samples that meet a set cutoff value can undergo confirmation by RT-PCR for further epidemiological studies.

  10. Effect of turbulence modelling to predict combustion and nanoparticle production in the flame assisted spray dryer based on computational fluid dynamics

    NASA Astrophysics Data System (ADS)

    Septiani, Eka Lutfi; Widiyastuti, W.; Winardi, Sugeng; Machmudah, Siti; Nurtono, Tantular; Kusdianto

    2016-02-01

    Flame assisted spray dryer are widely uses for large-scale production of nanoparticles because of it ability. Numerical approach is needed to predict combustion and particles production in scale up and optimization process due to difficulty in experimental observation and relatively high cost. Computational Fluid Dynamics (CFD) can provide the momentum, energy and mass transfer, so that CFD more efficient than experiment due to time and cost. Here, two turbulence models, k-ɛ and Large Eddy Simulation were compared and applied in flame assisted spray dryer system. The energy sources for particle drying was obtained from combustion between LPG as fuel and air as oxidizer and carrier gas that modelled by non-premixed combustion in simulation. Silica particles was used to particle modelling from sol silica solution precursor. From the several comparison result, i.e. flame contour, temperature distribution and particle size distribution, Large Eddy Simulation turbulence model can provide the closest data to the experimental result.

  11. On the use of computational fluid dynamics in the prediction and control of exposure to airborne contaminants-an illustration using spray painting.

    PubMed

    Flynn, M R; Sills, E D

    2000-05-01

    Computational fluid dynamics (CFD) is employed to simulate breathing-zone concentration for a simple representation of spray painting a flat plate in a cross-flow ventilated booth. The results demonstrate the capability of CFD to track correctly changes in breathing-zone concentration associated with work practices shown previously to be significant in determining exposure. Empirical data, and models verified through field studies, are used to examine the predictive capability of these simulations and to identify important issues in the conduct of such comparisons. A commercially available CFD package is used to solve a three-dimensional turbulent flow problem for the velocity field, and to subsequently generate particle trajectories for polydisperse aerosols. An in-house algorithm is developed to convert the trajectory data to breathing-zone concentrations, transfer efficiencies and aerosol size distributions. The mesh size, time step, duration of the simulation, and number of particles per size interval are all important variables in achieving convergent results.

  12. Fluid Shifts

    NASA Technical Reports Server (NTRS)

    Stenger, Michael; Hargens, A.; Dulchavsky, S.; Ebert, D.; Lee, S.; Sargsyan, A.; Martin, D.; Lui, J.; Macias, B.; Arbeille, P.; Platts, S.

    2014-01-01

    NASA is focusing on long-duration missions on the International Space Station (ISS) and future exploration-class missions beyond low Earth orbit. Visual acuity changes observed after short-duration missions were largely transient, but more than 30% of ISS astronauts experience more profound, chronic changes with objective structural and functional findings such as papilledema and choroidal folds. Globe flattening, optic nerve sheath dilation, and optic nerve tortuosity also are apparent. This pattern is referred to as the visual impairment and intracranial pressure (VIIP) syndrome. VIIP signs and symptoms, as well as postflight lumbar puncture data, suggest that elevated intracranial pressure (ICP) may be associated with the space flight-induced cephalad fluid shifts, but this hypothesis has not been tested. The purpose of this study is to characterize fluid distribution and compartmentalization associated with long-duration space flight, and to correlate these findings with vision changes and other elements of the VIIP syndrome. We also seek to determine whether the magnitude of fluid shifts during space flight, as well as the VIIP-related effects of those shifts, is predicted by the crewmember's pre-flight condition and responses to acute hemodynamic manipulations (such as head-down tilt). Lastly, we will evaluate the patterns of fluid distribution in ISS astronauts during acute reversal of fluid shifts through application of lower body negative pressure (LBNP) interventions to characterize and explain general and individual responses. We will examine a variety of physiologic variables in 10 long-duration ISS crewmembers using the test conditions and timeline presented in the Figure below. Measures include: (1) fluid compartmentalization (total body water by D2O, extracellular fluid by NaBr, intracellular fluid by calculation, plasma volume by CO rebreathe, interstitial fluid by calculation); (2) forehead/eyelids, tibia, calcaneus tissue thickness (by ultrasound

  13. A computational fluid-structure interaction model to predict the biomechanical properties of the artificial functionally graded aorta.

    PubMed

    Khosravi, Arezoo; Bani, Milad Salimi; Bahreinizade, Hossein; Karimi, Alireza

    2016-12-01

    In the present study, three layers of the ascending aorta in respect to the time and space at various blood pressures have been simulated. Two well-known commercial finite element (FE) software have used to be able to provide a range of reliable numerical results while independent on the software type. The radial displacement compared with the time as well as the peripheral stress and von Mises stress of the aorta have calculated. The aorta model was validated using the differential quadrature method (DQM) solution and, then, in order to design functionally graded materials (FGMs) with different heterogeneous indexes for the artificial vessel, two different materials have been employed. Fluid-structure interaction (FSI) simulation has been carried out on the FGM and a natural vessel of the human body. The heterogeneous index defines the variation of the length in a function. The blood pressure was considered to be a function of both the time and location. Finally, the response characteristics of functionally graded biomaterials (FGBMs) models wi