Are we near the predictability limit of tropical Indo-Pacific sea surface temperatures?

NASA Astrophysics Data System (ADS)

Newman, Matthew; Sardeshmukh, Prashant D.

2017-08-01

The predictability of seasonal anomalies worldwide rests largely on the predictability of tropical sea surface temperature (SST) anomalies. Tropical forecast skill is also a key metric of climate models. We find, however, that despite extensive model development, the tropical SST forecast skill of the operational North American Multi-Model Ensemble (NMME) of eight coupled atmosphere-ocean models remains close both regionally and temporally to that of a vastly simpler linear inverse model (LIM) derived from observed covariances of SST, sea surface height, and wind fields. The LIM clearly captures the essence of the predictable SST dynamics. The NMME and LIM skills also closely track and are only slightly lower than the potential skill estimated using the LIM's forecast signal-to-noise ratios. This suggests that the scope for further skill improvement is small in most regions, except in the western equatorial Pacific where the NMME skill is currently much lower than the LIM skill.

Stem thrust prediction model for W-K-M double wedge parallel expanding gate valves

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

Eldiwany, B.; Alvarez, P.D.; Wolfe, K.

1996-12-01

An analytical model for determining the required valve stem thrust during opening and closing strokes of W-K-M parallel expanding gate valves was developed as part of the EPRI Motor-Operated Valve Performance Prediction Methodology (EPRI MOV PPM) Program. The model was validated against measured stem thrust data obtained from in-situ testing of three W-K-M valves. Model predictions show favorable, bounding agreement with the measured data for valves with Stellite 6 hardfacing on the disks and seat rings for water flow in the preferred flow direction (gate downstream). The maximum required thrust to open and to close the valve (excluding wedging andmore » unwedging forces) occurs at a slightly open position and not at the fully closed position. In the nonpreferred flow direction, the model shows that premature wedging can occur during {Delta}P closure strokes even when the coefficients of friction at different sliding surfaces are within the typical range. This paper summarizes the model description and comparison against test data.« less

Attachment predicts cortisol response and closeness in dyadic social interaction.

PubMed

Ketay, Sarah; Beck, Lindsey A

2017-06-01

The present study examined how the interplay of partners' attachment styles influences cortisol response, actual closeness, and desired closeness during friendship initiation. Participants provided salivary cortisol samples at four timepoints throughout either a high or low closeness task that facilitated high or low levels of self-disclosure with a potential friend (i.e., another same-sex participant). Levels of actual closeness and desired closeness following the task were measured via inclusion of other in the self. Results from multi-level modeling indicated that the interaction of both participants' attachment avoidance predicted cortisol response patterns, with participants showing the highest cortisol response when there was a mismatch between their own and their partners' attachment avoidance. Further, the interaction between both participants' attachment anxiety predicted actual closeness and desired closeness, with participants both feeling and wanting the most closeness with partners when both they and their partners were low in attachment anxiety. Copyright © 2017 Elsevier Ltd. All rights reserved.

On the frequency of close binary systems among very low-mass stars and brown dwarfs

NASA Astrophysics Data System (ADS)

Maxted, P. F. L.; Jeffries, R. D.

2005-09-01

We have used Monte Carlo simulation techniques and published radial velocity surveys to constrain the frequency of very low-mass star (VLMS) and brown dwarf (BD) binary systems and their separation (a) distribution. Gaussian models for the separation distribution with a peak at a= 4au and 0.6 <=σlog(a/au)<= 1.0, correctly predict the number of observed binaries, yielding a close (a < 2.6au) binary frequency of 17-30 per cent and an overall VLMS/BD binary frequency of 32-45 per cent. We find that the available N-body models of VLMS/BD formation from dynamically decaying protostellar multiple systems are excluded at >99 per cent confidence because they predict too few close binary VLMS/BDs. The large number of close binaries and high overall binary frequency are also very inconsistent with recent smoothed particle hydrodynamical modelling and argue against a dynamical origin for VLMS/BDs.

A new possible picture of the hadron structure

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

Pokrovsky, Yury E.

A new chiral-scale invariant version of the bag model (CSB) is developed and applied to calculations of masses and radii for single bag states. The mass formula of the CSB model contains no free parameters and connects masses and radii of the bags with fundamental QCD scales, namely with {lambda}{sub QCD}, , , and quark masses. For high angular momentum states the CSB model well describes hadron Regge trajectories and predicts thin flux tubes with R{sub tube}{approx_equal}0.25 fm close to the small tube radii introduced a posteriori in modern models. For low angular momentum states this model predicts smallmore » radii of the bags R{sub bag}{approx_equal}0.25 fm close to the radii associated with constituent quarks. Masses of the lowest angular momentum bags are obtained close to the data for well known hadron resonances ({pi}(1300), {omega}(1420), N(1440),{delta}(1600), etc.). These resonances are predicted to be almost single bag states. But ground states of SU(3) hadrons (N(940), {pi}(140), etc.) are treated as strongly bounded multi bag states--BagBag-mesons, and BagBagBag-baryons like in the old Fermi, Yang, and Sakata models. As well, this model predicts the low mass excitations of SU(3) hadrons newly observed for nucleons at the following masses 1004, 1044, and 1094 MeV.« less

Sakurai Prize: Extended Higgs Sectors--phenomenology and future prospects

NASA Astrophysics Data System (ADS)

Gunion, John

2017-01-01

The discovery of a spin-0 state at 125 GeV with properties close to those predicted for the single Higgs boson of the Standard Model does not preclude the existence of additional Higgs bosons. In this talk, models with extended Higgs sectors are reviewed, including two-Higgs-doublet models with and without an extra singlet Higgs field and supersymmetric models. Special emphasis is given to the limit in which the couplings and properties of one of the Higgs bosons of the extended Higgs sector are very close to those predicted for the single Standard Model Higgs boson while the other Higgs bosons are relatively light, perhaps even having masses close to or below the SM-like 125 GeV state. Constraints on this type of scenario given existing data are summarized and prospects for observing these non-SM-like Higgs bosons are discussed. Supported by the Department of Energy.

Modulation of the error-related negativity by response conflict.

PubMed

Danielmeier, Claudia; Wessel, Jan R; Steinhauser, Marco; Ullsperger, Markus

2009-11-01

An arrow version of the Eriksen flanker task was employed to investigate the influence of conflict on the error-related negativity (ERN). The degree of conflict was modulated by varying the distance between flankers and the target arrow (CLOSE and FAR conditions). Error rates and reaction time data from a behavioral experiment were used to adapt a connectionist model of this task. This model was based on the conflict monitoring theory and simulated behavioral and event-related potential data. The computational model predicted an increased ERN amplitude in FAR incompatible (the low-conflict condition) compared to CLOSE incompatible errors (the high-conflict condition). A subsequent ERP experiment confirmed the model predictions. The computational model explains this finding with larger post-response conflict in far trials. In addition, data and model predictions of the N2 and the LRP support the conflict interpretation of the ERN.

Mathematical model for predicting human vertebral fracture

NASA Technical Reports Server (NTRS)

Benedict, J. V.

1973-01-01

Mathematical model has been constructed to predict dynamic response of tapered, curved beam columns in as much as human spine closely resembles this form. Model takes into consideration effects of impact force, mass distribution, and material properties. Solutions were verified by dynamic tests on curved, tapered, elastic polyethylene beam.

Detailed ADM-based Modeling of Shock Retreat and X-ray Emission of τ Sco

NASA Astrophysics Data System (ADS)

Fletcher, C. L.; Petit, V.; Cohen, D. H.; Townsend, R. H.; Wade, G. A.

2018-01-01

Leveraging the improvement of spectropolarimeters over the past few decades, surveys have found that about 10% of OB-type stars host strong (˜ kG) and mostly dipolar surface magnetic fields. One B-type star, τ Sco, has a more complex surface magnetic field than the general population of OB stars. Interestingly, its X-ray luminosity is an order of magnitude higher than predicted from analytical models of magnetized winds. Previous studies of τ Sco's magnetosphere have predicted that the region of closed field loops should be located close to the stellar surface. However, the lack of X-ray variability and the location of the shock-heated plasma measured from forbidden-to-intercombination X-ray line ratios suggest that the hot plasma, and hence the closed magnetic loops, extend considerably farther from the stellar surface, implying a significantly lower mass loss rate than initially assumed. We present an adaptation of the Analytic Dynamical Magnetosphere model, describing the magnetic confinement of the stellar wind, for an arbitrary field loop configuration. This model is used to predict the shock-heated plasma temperatures for individual field loops, which are then compared to high resolution grating spectra from the Chandra X-ray Observatory. This comparison shows that larger closed magnetic loops are needed.

Parenting and antisocial behavior: a model of the relationship between adolescent self-disclosure, parental closeness, parental control, and adolescent antisocial behavior.

PubMed

Vieno, Alessio; Nation, Maury; Pastore, Massimiliano; Santinello, Massimo

2009-11-01

This study used data collected from a sample of 840 Italian adolescents (418 boys; M age = 12.58) and their parents (657 mothers; M age = 43.78) to explore the relations between parenting, adolescent self-disclosure, and antisocial behavior. In the hypothesized model, parenting practices (e.g., parental monitoring and control) have direct effects on parental knowledge and antisocial behavior. Parenting style (e.g., parent-child closeness), on the other hand, is directly related to adolescent self-disclosure, which in turn is positively related to parental knowledge and negatively related to adolescents' antisocial behavior. A structural equation model, which incorporated data from parents and adolescents, largely supported the hypothesized model. Gender-specific models also found some gender differences among adolescents and parents, as the hypothesized model adequately fit the subsample of mothers but not fathers. Mothers' closeness to girls predicted their knowledge of their daughters' behavior; mothers' control predicted boys' antisocial behavior.

Amasia and Supercontinent Formation by Orthoversion

NASA Astrophysics Data System (ADS)

Mitchell, R. N.; Evans, D. A.; Kilian, T. M.

2015-12-01

Traditional models of the supercontinent cycle predict that the next supercontinent—'Amasia'—will form either where Pangaea rifted (the 'introversion' model) or on the opposite side of the world (the 'extroversion' models). In contrast, a new model termed "orthoversion", predicts a new supercontinent will form 90° away from the previous one, somewhere along the subduction girdle encircling its predecessor. As continents are expected to aggregate over mantle convective downwellings, orthoversion predicts that a continent central to the assembling supercontinent would plot 90° away from the center of the dispersing continent. Supercontinent centers can be quantified by identifying the long-lived axis of oscillatory true polar wander associated with each supercontinent cycle; measuring the angle between two successive true polar wander axes allows one to test between the various models (0˚, 90˚, or 180˚) of supercontinent formation. The past three supercontinents (Pangea, Rodinia, and Nuna) appear to follow the 90° "orthoversion" model closely. Orthoversion predicts that Amasia will take form ~100 million years from now over the North Pole by closing the Caribbean and Artic oceans which are located in Pangea's subduction girdle.

First principles nickel-cadmium and nickel hydrogen spacecraft battery models

NASA Technical Reports Server (NTRS)

Timmerman, P.; Ratnakumar, B. V.; Distefano, S.

1996-01-01

The principles of Nickel-Cadmium and Nickel-Hydrogen spacecraft battery models are discussed. The Ni-Cd battery model includes two phase positive electrode and its predictions are very close to actual data. But the Ni-H2 battery model predictions (without the two phase positive electrode) are unacceptable even though the model is operational. Both models run on UNIX and Macintosh computers.

Verification of a 2 kWe Closed-Brayton-Cycle Power Conversion System Mechanical Dynamics Model

NASA Technical Reports Server (NTRS)

Ludwiczak, Damian R.; Le, Dzu K.; McNelis, Anne M.; Yu, Albert C.; Samorezov, Sergey; Hervol, Dave S.

2005-01-01

Vibration test data from an operating 2 kWe closed-Brayton-cycle (CBC) power conversion system (PCS) located at the NASA Glenn Research Center was used for a comparison with a dynamic disturbance model of the same unit. This effort was performed to show that a dynamic disturbance model of a CBC PCS can be developed that can accurately predict the torque and vibration disturbance fields of such class of rotating machinery. The ability to accurately predict these disturbance fields is required before such hardware can be confidently integrated onto a spacecraft mission. Accurate predictions of CBC disturbance fields will be used for spacecraft control/structure interaction analyses and for understanding the vibration disturbances affecting the scientific instrumentation onboard. This paper discusses how test cell data measurements for the 2 kWe CBC PCS were obtained, the development of a dynamic disturbance model used to predict the transient torque and steady state vibration fields of the same unit, and a comparison of the two sets of data.

Nonlinear predictive control for adaptive adjustments of deep brain stimulation parameters in basal ganglia-thalamic network.

PubMed

Su, Fei; Wang, Jiang; Niu, Shuangxia; Li, Huiyan; Deng, Bin; Liu, Chen; Wei, Xile

2018-02-01

The efficacy of deep brain stimulation (DBS) for Parkinson's disease (PD) depends in part on the post-operative programming of stimulation parameters. Closed-loop stimulation is one method to realize the frequent adjustment of stimulation parameters. This paper introduced the nonlinear predictive control method into the online adjustment of DBS amplitude and frequency. This approach was tested in a computational model of basal ganglia-thalamic network. The autoregressive Volterra model was used to identify the process model based on physiological data. Simulation results illustrated the efficiency of closed-loop stimulation methods (amplitude adjustment and frequency adjustment) in improving the relay reliability of thalamic neurons compared with the PD state. Besides, compared with the 130Hz constant DBS the closed-loop stimulation methods can significantly reduce the energy consumption. Through the analysis of inter-spike-intervals (ISIs) distribution of basal ganglia neurons, the evoked network activity by the closed-loop frequency adjustment stimulation was closer to the normal state. Copyright © 2017 Elsevier Ltd. All rights reserved.

VTOL in ground effect flows for closely spaced jets. [to predict pressure and upwash forces on aircraft structures

NASA Technical Reports Server (NTRS)

Migdal, D.; Hill, W. G., Jr.; Jenkins, R. C.

1979-01-01

Results of a series of in ground effect twin jet tests are presented along with flow models for closely spaced jets to help predict pressure and upwash forces on simulated aircraft surfaces. The isolated twin jet tests revealed unstable fountains over a range of spacings and jet heights, regions of below ambient pressure on the ground, and negative pressure differential in the upwash flow field. A separate computer code was developed for vertically oriented, incompressible jets. This model more accurately reflects fountain behavior without fully formed wall jets, and adequately predicts ground isobars, upwash dynamic pressure decay, and fountain lift force variation with height above ground.

Predicting neutron damage using TEM with in situ ion irradiation and computer modeling

NASA Astrophysics Data System (ADS)

Kirk, Marquis A.; Li, Meimei; Xu, Donghua; Wirth, Brian D.

2018-01-01

We have constructed a computer model of irradiation defect production closely coordinated with TEM and in situ ion irradiation of Molybdenum at 80 °C over a range of dose, dose rate and foil thickness. We have reexamined our previous ion irradiation data to assign appropriate error and uncertainty based on more recent work. The spatially dependent cascade cluster dynamics model is updated with recent Molecular Dynamics results for cascades in Mo. After a careful assignment of both ion and neutron irradiation dose values in dpa, TEM data are compared for both ion and neutron irradiated Mo from the same source material. Using the computer model of defect formation and evolution based on the in situ ion irradiation of thin foils, the defect microstructure, consisting of densities and sizes of dislocation loops, is predicted for neutron irradiation of bulk material at 80 °C and compared with experiment. Reasonable agreement between model prediction and experimental data demonstrates a promising direction in understanding and predicting neutron damage using a closely coordinated program of in situ ion irradiation experiment and computer simulation.

A simplified heat transfer model for predicting temperature change inside food package kept in cold room.

PubMed

Raval, A H; Solanki, S C; Yadav, Rajvir

2013-04-01

A simple analytical heat flow model for a closed rectangular food package containing fruits or vegetables is proposed for predicting time temperature distribution during transient cooling in a controlled environment cold room. It is based on the assumption of only conductive heat transfer inside a closed food package with effective thermal properties, and convective and radiative heat transfer at the outside of the package. The effective thermal conductivity of the food package is determined by evaluating its effective thermal resistance to heat conduction in the packages. Food packages both as an infinite slab and a finite slab have been investigated. The finite slab solution has been obtained as the product of three infinite slab solutions describe in ASHRAE guide and data book. Time temperature variation has been determined and is presented graphically. The cooling rate and the half cooling time were also obtained. These predicted values, are compared with the experimentally measured values for both the finite and infinite closed packages containing oranges. An excellent agreement between them validated the simple proposed model.

Planning a Stigmatized Nonvisible Illness Disclosure: Applying the Disclosure Decision-Making Model

PubMed Central

Choi, Soe Yoon; Venetis, Maria K.; Greene, Kathryn; Magsamen-Conrad, Kate; Checton, Maria G.; Banerjee, Smita C.

2016-01-01

This study applied the disclosure decision-making model (DD-MM) to explore how individuals plan to disclose nonvisible illness (Study 1), compared to planning to disclose personal information (Study 2). Study 1 showed that perceived stigma from the illness negatively predicted disclosure efficacy; closeness predicted anticipated response (i.e., provision of support) although it did not influence disclosure efficacy; disclosure efficacy led to reduced planning, with planning leading to scheduling. Study 2 demonstrated that when information was considered to be intimate, it negatively influenced disclosure efficacy. Unlike the model with stigma (Study 1), closeness positively predicted both anticipated response and disclosure efficacy. The rest of the hypothesized relationships showed a similar pattern to Study 1: disclosure efficacy reduced planning, which then positively influenced scheduling. Implications of understanding stages of planning for stigmatized information are discussed. PMID:27662447

Planning a Stigmatized Nonvisible Illness Disclosure: Applying the Disclosure Decision-Making Model.

PubMed

Choi, Soe Yoon; Venetis, Maria K; Greene, Kathryn; Magsamen-Conrad, Kate; Checton, Maria G; Banerjee, Smita C

2016-11-16

This study applied the disclosure decision-making model (DD-MM) to explore how individuals plan to disclose nonvisible illness (Study 1), compared to planning to disclose personal information (Study 2). Study 1 showed that perceived stigma from the illness negatively predicted disclosure efficacy; closeness predicted anticipated response (i.e., provision of support) although it did not influence disclosure efficacy; disclosure efficacy led to reduced planning, with planning leading to scheduling. Study 2 demonstrated that when information was considered to be intimate, it negatively influenced disclosure efficacy. Unlike the model with stigma (Study 1), closeness positively predicted both anticipated response and disclosure efficacy. The rest of the hypothesized relationships showed a similar pattern to Study 1: disclosure efficacy reduced planning, which then positively influenced scheduling. Implications of understanding stages of planning for stigmatized information are discussed.

A method for grounding grid corrosion rate prediction

NASA Astrophysics Data System (ADS)

Han, Juan; Du, Jingyi

2017-06-01

Involved in a variety of factors, prediction of grounding grid corrosion complex, and uncertainty in the acquisition process, we propose a combination of EAHP (extended AHP) and fuzzy nearness degree of effective grounding grid corrosion rate prediction model. EAHP is used to establish judgment matrix and calculate the weight of each factors corrosion of grounding grid; different sample classification properties have different corrosion rate of contribution, and combining the principle of close to predict corrosion rate.The application result shows, the model can better capture data variation, thus to improve the validity of the model to get higher prediction precision.

Characterization of the 2012-044C Briz-M Upper Stage Breakup

NASA Technical Reports Server (NTRS)

Hamilton, Joseph A.; Matney, Mark

2013-01-01

The NASA breakup model prediction was close to the observed population for catalog objects. The NASA breakup model predicted a larger population than was observed for objects under 10 cm. The stare technique produces low observation counts, but is readily comparable to model predictions. Customized stare parameters (Az, El, Range) were effective to increase the opportunities for HAX to observe the debris cloud. Other techniques to increase observation count will be considered for future breakup events.

Physiological time model for predicting adult emergence of western corn rootworm (Coleoptera: Chrysomelidae) in the Texas High Plains.

PubMed

Stevenson, Douglass E; Michels, Gerald J; Bible, John B; Jackman, John A; Harris, Marvin K

2008-10-01

Field observations at three locations in the Texas High Plains were used to develop and validate a degree-day phenology model to predict the onset and proportional emergence of adult Diabrotica virgifera virgifera LeConte (Coleoptera: Chrysomelidae) adults. Climatic data from the Texas High Plains Potential Evapotranspiration network were used with records of cumulative proportional adult emergence to determine the functional lower developmental temperature, optimum starting date, and the sum of degree-days for phenological events from onset to 99% adult emergence. The model base temperature, 10 degrees C (50 degrees F), corresponds closely to known physiological lower limits for development. The model uses a modified Gompertz equation, y = 96.5 x exp (-(exp(6.0 - 0.00404 x (x - 4.0), where x is cumulative heat (degree-days), to predict y, cumulative proportional emergence expressed as a percentage. The model starts degree-day accumulation on the date of corn, Zea mays L., emergence, and predictions correspond closely to corn phenological stages from tasseling to black layer development. Validation shows the model predicts cumulative proportional adult emergence within a satisfactory interval of 4.5 d. The model is flexible enough to accommodate early planting, late emergence, and the effects of drought and heat stress. The model provides corn producers ample lead time to anticipate and implement adult control practices.

Predicting the effects of unmodeled dynamics on an aircraft flight control system design using eigenspace assignment

NASA Technical Reports Server (NTRS)

Johnson, Eric N.; Davidson, John B.; Murphy, Patrick C.

1994-01-01

When using eigenspace assignment to design an aircraft flight control system, one must first develop a model of the plant. Certain questions arise when creating this model as to which dynamics of the plant need to be included in the model and which dynamics can be left out or approximated. The answers to these questions are important because a poor choice can lead to closed-loop dynamics that are unpredicted by the design model. To alleviate this problem, a method has been developed for predicting the effect of not including certain dynamics in the design model on the final closed-loop eigenspace. This development provides insight as to which characteristics of unmodeled dynamics will ultimately affect the closed-loop rigid-body dynamics. What results from this insight is a guide for eigenstructure control law designers to aid them in determining which dynamics need or do not need to be included and a new way to include these dynamics in the flight control system design model to achieve a required accuracy in the closed-loop rigid-body dynamics. The method is illustrated for a lateral-directional flight control system design using eigenspace assignment for the NASA High Alpha Research Vehicle (HARV).

A study on the influence of corona on currents and electromagnetic fields predicted by a nonlinear lightning return-stroke model

NASA Astrophysics Data System (ADS)

De Conti, Alberto; Silveira, Fernando H.; Visacro, Silvério

2014-05-01

This paper investigates the influence of corona on currents and electromagnetic fields predicted by a return-stroke model that represents the lightning channel as a nonuniform transmission line with time-varying (nonlinear) resistance. The corona model used in this paper allows the calculation of corona currents as a function of the radial electric field in the vicinity of the channel. A parametric study is presented to investigate the influence of corona parameters, such as the breakdown electric field and the critical electric field for the stable propagation of streamers, on predicted currents and electromagnetic fields. The results show that, regardless of the assumed corona parameters, the incorporation of corona into the nonuniform and nonlinear transmission line model under investigation modifies the model predictions so that they consistently reproduce most of the typical features of experimentally observed lightning electromagnetic fields and return-stroke speed profiles. In particular, it is shown that the proposed model leads to close vertical electric fields presenting waveforms, amplitudes, and decay with distance in good agreement with dart leader electric field changes measured in triggered lightning experiments. A comparison with popular engineering return-stroke models further confirms the model's ability to predict consistent electric field waveforms in the close vicinity of the channel. Some differences observed in the field amplitudes calculated with the different models can be related to the fact that current distortion, while present in the proposed model, is ultimately neglected in the considered engineering return-stroke models.

Two-Dimensional Ordering of Solute Nanoclusters at a Close-Packed Stacking Fault: Modeling and Experimental Analysis

PubMed Central

Kimizuka, Hajime; Kurokawa, Shu; Yamaguchi, Akihiro; Sakai, Akira; Ogata, Shigenobu

2014-01-01

Predicting the equilibrium ordered structures at internal interfaces, especially in the case of nanometer-scale chemical heterogeneities, is an ongoing challenge in materials science. In this study, we established an ab-initio coarse-grained modeling technique for describing the phase-like behavior of a close-packed stacking-fault-type interface containing solute nanoclusters, which undergo a two-dimensional disorder-order transition, depending on the temperature and composition. Notably, this approach can predict the two-dimensional medium-range ordering in the nanocluster arrays realized in Mg-based alloys, in a manner consistent with scanning tunneling microscopy-based measurements. We predicted that the repulsively interacting solute-cluster system undergoes a continuous evolution into a highly ordered densely packed morphology while maintaining a high degree of six-fold orientational order, which is attributable mainly to an entropic effect. The uncovered interaction-dependent ordering properties may be useful for the design of nanostructured materials utilizing the self-organization of two-dimensional nanocluster arrays in the close-packed interfaces. PMID:25471232

An approach to the mathematical modelling of a controlled ecological life support system

NASA Technical Reports Server (NTRS)

Averner, M. M.

1981-01-01

An approach to the design of a computer based model of a closed ecological life-support system suitable for use in extraterrestrial habitats is presented. The model is based on elemental mass balance and contains representations of the metabolic activities of biological components. The model can be used as a tool in evaluating preliminary designs for closed regenerative life support systems and as a method for predicting the behavior of such systems.

Microarray-based cancer prediction using soft computing approach.

PubMed

Wang, Xiaosheng; Gotoh, Osamu

2009-05-26

One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes. We screen highly discriminative genes and gene pairs to create simple prediction models involved in single genes or gene pairs on the basis of soft computing approach and rough set theory. Accurate cancerous prediction is obtained when we apply the simple prediction models for four cancerous gene expression datasets: CNS tumor, colon tumor, lung cancer and DLBCL. Some genes closely correlated with the pathogenesis of specific or general cancers are identified. In contrast with other models, our models are simple, effective and robust. Meanwhile, our models are interpretable for they are based on decision rules. Our results demonstrate that very simple models may perform well on cancerous molecular prediction and important gene markers of cancer can be detected if the gene selection approach is chosen reasonably.

Closing the contrast gap between testbed and model prediction with WFIRST-CGI shaped pupil coronagraph

NASA Astrophysics Data System (ADS)

Zhou, Hanying; Nemati, Bijan; Krist, John; Cady, Eric; Prada, Camilo M.; Kern, Brian; Poberezhskiy, Ilya

2016-07-01

JPL has recently passed an important milestone in its technology development for a proposed NASA WFIRST mission coronagraph: demonstration of better than 1x10-8 contrast over broad bandwidth (10%) on both shaped pupil coronagraph (SPC) and hybrid Lyot coronagraph (HLC) testbeds with the WFIRST obscuration pattern. Challenges remain, however, in the technology readiness for the proposed mission. One is the discrepancies between the achieved contrasts on the testbeds and their corresponding model predictions. A series of testbed diagnoses and modeling activities were planned and carried out on the SPC testbed in order to close the gap. A very useful tool we developed was a derived "measured" testbed wavefront control Jacobian matrix that could be compared with the model-predicted "control" version that was used to generate the high contrast dark hole region in the image plane. The difference between these two is an estimate of the error in the control Jacobian. When the control matrix, which includes both amplitude and phase, was modified to reproduce the error, the simulated performance closely matched the SPC testbed behavior in both contrast floor and contrast convergence speed. This is a step closer toward model validation for high contrast coronagraphs. Further Jacobian analysis and modeling provided clues to the possible sources for the mismatch: DM misregistration and testbed optical wavefront error (WFE) and the deformable mirror (DM) setting for correcting this WFE. These analyses suggested that a high contrast coronagraph has a tight tolerance in the accuracy of its control Jacobian. Modifications to both testbed control model as well as prediction model are being implemented, and future works are discussed.

Will Big Data Close the Missing Heritability Gap?

PubMed

Kim, Hwasoon; Grueneberg, Alexander; Vazquez, Ana I; Hsu, Stephen; de Los Campos, Gustavo

2017-11-01

Despite the important discoveries reported by genome-wide association (GWA) studies, for most traits and diseases the prediction R-squared (R-sq.) achieved with genetic scores remains considerably lower than the trait heritability. Modern biobanks will soon deliver unprecedentedly large biomedical data sets: Will the advent of big data close the gap between the trait heritability and the proportion of variance that can be explained by a genomic predictor? We addressed this question using Bayesian methods and a data analysis approach that produces a surface response relating prediction R-sq. with sample size and model complexity ( e.g. , number of SNPs). We applied the methodology to data from the interim release of the UK Biobank. Focusing on human height as a model trait and using 80,000 records for model training, we achieved a prediction R-sq. in testing ( n = 22,221) of 0.24 (95% C.I.: 0.23-0.25). Our estimates show that prediction R-sq. increases with sample size, reaching an estimated plateau at values that ranged from 0.1 to 0.37 for models using 500 and 50,000 (GWA-selected) SNPs, respectively. Soon much larger data sets will become available. Using the estimated surface response, we forecast that larger sample sizes will lead to further improvements in prediction R-sq. We conclude that big data will lead to a substantial reduction of the gap between trait heritability and the proportion of interindividual differences that can be explained with a genomic predictor. However, even with the power of big data, for complex traits we anticipate that the gap between prediction R-sq. and trait heritability will not be fully closed. Copyright © 2017 by the Genetics Society of America.

Will Big Data Close the Missing Heritability Gap?

PubMed Central

Kim, Hwasoon; Grueneberg, Alexander; Vazquez, Ana I.; Hsu, Stephen; de los Campos, Gustavo

2017-01-01

Despite the important discoveries reported by genome-wide association (GWA) studies, for most traits and diseases the prediction R-squared (R-sq.) achieved with genetic scores remains considerably lower than the trait heritability. Modern biobanks will soon deliver unprecedentedly large biomedical data sets: Will the advent of big data close the gap between the trait heritability and the proportion of variance that can be explained by a genomic predictor? We addressed this question using Bayesian methods and a data analysis approach that produces a surface response relating prediction R-sq. with sample size and model complexity (e.g., number of SNPs). We applied the methodology to data from the interim release of the UK Biobank. Focusing on human height as a model trait and using 80,000 records for model training, we achieved a prediction R-sq. in testing (n = 22,221) of 0.24 (95% C.I.: 0.23–0.25). Our estimates show that prediction R-sq. increases with sample size, reaching an estimated plateau at values that ranged from 0.1 to 0.37 for models using 500 and 50,000 (GWA-selected) SNPs, respectively. Soon much larger data sets will become available. Using the estimated surface response, we forecast that larger sample sizes will lead to further improvements in prediction R-sq. We conclude that big data will lead to a substantial reduction of the gap between trait heritability and the proportion of interindividual differences that can be explained with a genomic predictor. However, even with the power of big data, for complex traits we anticipate that the gap between prediction R-sq. and trait heritability will not be fully closed. PMID:28893854

Research on reverse logistics location under uncertainty environment based on grey prediction

NASA Astrophysics Data System (ADS)

Zhenqiang, Bao; Congwei, Zhu; Yuqin, Zhao; Quanke, Pan

This article constructs reverse logistic network based on uncertain environment, integrates the reverse logistics network and distribution network, and forms a closed network. An optimization model based on cost is established to help intermediate center, manufacturing center and remanufacturing center make location decision. A gray model GM (1, 1) is used to predict the product holdings of the collection points, and then prediction results are carried into the cost optimization model and a solution is got. Finally, an example is given to verify the effectiveness and feasibility of the model.

On the simple random-walk models of ion-channel gate dynamics reflecting long-term memory.

PubMed

Wawrzkiewicz, Agata; Pawelek, Krzysztof; Borys, Przemyslaw; Dworakowska, Beata; Grzywna, Zbigniew J

2012-06-01

Several approaches to ion-channel gating modelling have been proposed. Although many models describe the dwell-time distributions correctly, they are incapable of predicting and explaining the long-term correlations between the lengths of adjacent openings and closings of a channel. In this paper we propose two simple random-walk models of the gating dynamics of voltage and Ca(2+)-activated potassium channels which qualitatively reproduce the dwell-time distributions, and describe the experimentally observed long-term memory quite well. Biological interpretation of both models is presented. In particular, the origin of the correlations is associated with fluctuations of channel mass density. The long-term memory effect, as measured by Hurst R/S analysis of experimental single-channel patch-clamp recordings, is close to the behaviour predicted by our models. The flexibility of the models enables their use as templates for other types of ion channel.

Differential effects of two types of formative assessment in predicting performance of first-year medical students.

PubMed

Krasne, Sally; Wimmers, Paul F; Relan, Anju; Drake, Thomas A

2006-05-01

Formative assessments are systematically designed instructional interventions to assess and provide feedback on students' strengths and weaknesses in the course of teaching and learning. Despite their known benefits to student attitudes and learning, medical school curricula have been slow to integrate such assessments into the curriculum. This study investigates how performance on two different modes of formative assessment relate to each other and to performance on summative assessments in an integrated, medical-school environment. Two types of formative assessment were administered to 146 first-year medical students each week over 8 weeks: a timed, closed-book component to assess factual recall and image recognition, and an un-timed, open-book component to assess higher order reasoning including the ability to identify and access appropriate resources and to integrate and apply knowledge. Analogous summative assessments were administered in the ninth week. Models relating formative and summative assessment performance were tested using Structural Equation Modeling. Two latent variables underlying achievement on formative and summative assessments could be identified; a "formative-assessment factor" and a "summative-assessment factor," with the former predicting the latter. A latent variable underlying achievement on open-book formative assessments was highly predictive of achievement on both open- and closed-book summative assessments, whereas a latent variable underlying closed-book assessments only predicted performance on the closed-book summative assessment. Formative assessments can be used as effective predictive tools of summative performance in medical school. Open-book, un-timed assessments of higher order processes appeared to be better predictors of overall summative performance than closed-book, timed assessments of factual recall and image recognition.

Regression models of monthly water-level change in and near the Closed Basin Division of the San Luis Valley, south-central Colorado

USGS Publications Warehouse

Watts, Kenneth R.

1995-01-01

The Bureau of Reclamation is developing a water-resource project, the Closed Basin Division, in the San Luis Valley of south-central Colorado that is designed to salvage unconfined ground water that currently is discharged as evapotranspiration. The water table in and near the 130,000-acre Closed Basin Division area will be lowered by an annual withdrawal of as much as 100,000 acre-feet of ground water from the unconfined aquifer. The legislation authorizing the project limits resulting drawdown of the water table in preexisting irrigation and domestic wells outside the Closed Basin Division to a maximum of 2 feet. Water levels in the closed basin in the northern part of the San Luis Valley historically have fluctuated more than 2 feet in response to water-use practices and variation of climatically controlled recharge and discharge. Declines of water levels in nearby wells that are caused by withdrawals in the Closed Basin Division can be quantified if water-level fluctuations that result from other water-use practices and climatic variations can be estimated. This study was done to evaluate water-level change at selected observation wells in and near the Closed Basin Division. Regression models of monthly water-level change were developed to predict monthly water-level change in 46 selected observation wells. Predictions of monthly water-level change are based on one or more of the following: elapsed time, cosine and sine functions with an annual period, streamflow depletion of the Rio Grande, electrical use for agricultural purposes, runoff into the closed basin, precipitation, and mean air temperature. Regression models for five of the wells include only an intercept term and either an elapsed-time term or terms determined by the cosine and sine functions. Regression models for the other 41 wells include 1 to 4 of the 5 other variables, which can vary from month to month and from year to year. Serial correlation of the residuals was detected in 24 of the regression models. These models also include an autoregressive term to account for serial correlation in the residuals. The adjusted coefficient of determination (Ra2) for the 46 regression models range from 0.08 to 0.89, and the standard errors of estimate range from 0.034 to 2.483 feet. The regression models of monthly water- level change can be used to evaluate whether post-1985 monthly water-level change values at the selected observation wells are within the 95-percent confidence limits of predicted monthly water-level change.

Expanding a dynamic flux balance model of yeast fermentation to genome-scale

PubMed Central

2011-01-01

Background Yeast is considered to be a workhorse of the biotechnology industry for the production of many value-added chemicals, alcoholic beverages and biofuels. Optimization of the fermentation is a challenging task that greatly benefits from dynamic models able to accurately describe and predict the fermentation profile and resulting products under different genetic and environmental conditions. In this article, we developed and validated a genome-scale dynamic flux balance model, using experimentally determined kinetic constraints. Results Appropriate equations for maintenance, biomass composition, anaerobic metabolism and nutrient uptake are key to improve model performance, especially for predicting glycerol and ethanol synthesis. Prediction profiles of synthesis and consumption of the main metabolites involved in alcoholic fermentation closely agreed with experimental data obtained from numerous lab and industrial fermentations under different environmental conditions. Finally, fermentation simulations of genetically engineered yeasts closely reproduced previously reported experimental results regarding final concentrations of the main fermentation products such as ethanol and glycerol. Conclusion A useful tool to describe, understand and predict metabolite production in batch yeast cultures was developed. The resulting model, if used wisely, could help to search for new metabolic engineering strategies to manage ethanol content in batch fermentations. PMID:21595919

Geometric modeling of Plateau borders using the orthographic projection method for closed cell rigid polyurethane foam thermal conductivity prediction

NASA Astrophysics Data System (ADS)

Xu, Jie; Wu, Tao; Peng, Chuang; Adegbite, Stephen

2017-09-01

The geometric Plateau border model for closed cell polyurethane foam was developed based on volume integrations of approximated 3D four-cusp hypocycloid structure. The tetrahedral structure of convex struts was orthogonally projected into 2D three-cusp deltoid with three central cylinders. The idealized single unit strut was modeled by superposition. The volume of each component was calculated by geometric analyses. The strut solid fraction f s and foam porosity coefficient δ were calculated based on representative elementary volume of Kelvin and Weaire-Phelan structures. The specific surface area Sv derived respectively from packing structures and deltoid approximation model were put into contrast against strut dimensional ratio ɛ. The characteristic foam parameters obtained from this semi-empirical model were further employed to predict foam thermal conductivity.

Open Up or Close Down: How Do Parental Reactions Affect Youth Information Management?

ERIC Educational Resources Information Center

Tilton-Weaver, Lauree; Kerr, Margaret; Pakalniskeine, Vilmante; Tokic, Ana; Salihovic, Selma; Stattin, Hakan

2010-01-01

The purpose of this study was to test a process model of youths' information management. Using three waves of longitudinal data collected from 982 youths, we modeled parents' positive and negative reactions to disclosure predicting youths' feelings about their parents, in turn predicting youths' disclosure and secrecy about their daily activities.…

Modeling and evaluation of urban pollution events of atmospheric heavy metals from a large Cu-smelter.

PubMed

Chen, Bing; Stein, Ariel F; Castell, Nuria; Gonzalez-Castanedo, Yolanda; Sanchez de la Campa, A M; de la Rosa, J D

2016-01-01

Metal smelting and processing are highly polluting activities that have a strong influence on the levels of heavy metals in air, soil, and crops. We employ an atmospheric transport and dispersion model to predict the pollution levels originated from the second largest Cu-smelter in Europe. The model predicts that the concentrations of copper (Cu), zinc (Zn), and arsenic (As) in an urban area close to the Cu-smelter can reach 170, 70, and 30 ng m−3, respectively. The model captures all the observed urban pollution events, but the magnitude of the elemental concentrations is predicted to be lower than that of the observed values; ~300, ~500, and ~100 ng m−3 for Cu, Zn, and As, respectively. The comparison between model and observations showed an average correlation coefficient of 0.62 ± 0.13. The simulation shows that the transport of heavy metals reaches a peak in the afternoon over the urban area. The under-prediction in the peak is explained by the simulated stronger winds compared with monitoring data. The stronger simulated winds enhance the transport and dispersion of heavy metals to the regional area, diminishing the impact of pollution events in the urban area. This model, driven by high resolution meteorology (2 km in horizontal), predicts the hourly-interval evolutions of atmospheric heavy metal pollutions in the close by urban area of industrial hotspot.

Improved Modeling of Open Waveguide Aperture Radiators for use in Conformal Antenna Arrays

NASA Astrophysics Data System (ADS)

Nelson, Gregory James

Open waveguide apertures have been used as radiating elements in conformal arrays. Individual radiating element model patterns are used in constructing overall array models. The existing models for these aperture radiating elements may not accurately predict the array pattern for TEM waves which are not on boresight for each radiating element. In particular, surrounding structures can affect the far field patterns of these apertures, which ultimately affects the overall array pattern. New models of open waveguide apertures are developed here with the goal of accounting for the surrounding structure effects on the aperture far field patterns such that the new models make accurate pattern predictions. These aperture patterns (both E plane and H plane) are measured in an anechoic chamber and the manner in which they deviate from existing model patterns are studied. Using these measurements as a basis, existing models for both E and H planes are updated with new factors and terms which allow the prediction of far field open waveguide aperture patterns with improved accuracy. These new and improved individual radiator models are then used to predict overall conformal array patterns. Arrays of open waveguide apertures are constructed and measured in a similar fashion to the individual aperture measurements. These measured array patterns are compared with the newly modeled array patterns to verify the improved accuracy of the new models as compared with the performance of existing models in making array far field pattern predictions. The array pattern lobe characteristics are then studied for predicting fully circularly conformal arrays of varying radii. The lobe metrics that are tracked are angular location and magnitude as the radii of the conformal arrays are varied. A constructed, measured array that is close to conforming to a circular surface is compared with a fully circularly conformal modeled array pattern prediction, with the predicted lobe angular locations and magnitudes tracked, plotted and tabulated. The close match between the patterns of the measured array and the modeled circularly conformal array verifies the validity of the modeled circularly conformal array pattern predictions.

Some Unsolved Problems, Questions, and Applications of the Brightsen Nucleon Cluster Model

NASA Astrophysics Data System (ADS)

Smarandache, Florentin

2010-10-01

Brightsen Model is opposite to the Standard Model, and it was build on John Weeler's Resonating Group Structure Model and on Linus Pauling's Close-Packed Spheron Model. Among Brightsen Model's predictions and applications we cite the fact that it derives the average number of prompt neutrons per fission event, it provides a theoretical way for understanding the low temperature / low energy reactions and for approaching the artificially induced fission, it predicts that forces within nucleon clusters are stronger than forces between such clusters within isotopes; it predicts the unmatter entities inside nuclei that result from stable and neutral union of matter and antimatter, and so on. But these predictions have to be tested in the future at the new CERN laboratory.

FHWA roadway construction noise model, version 1.0 : user's guide

DOT National Transportation Integrated Search

2006-01-01

The Roadway Construction Noise Model (RCNM) is the Federal Highway Administrations (FHWA) national model for the prediction of construction noise. Due to the fact that construction is often conducted in close proximity to residences and businesses...

Predicting performance of power converters operating with switching frequencies in the vicinity of 100 kHZ

NASA Technical Reports Server (NTRS)

Bahler, D. D.; Owen, H. A., Jr.; Wilson, T. G.

1978-01-01

A model describing the turning-on period of a power switching transistor in an energy storage voltage step-up converter is presented. Comparisons between an experimental layout and the circuit model during the turning-on interval demonstrate the ability of the model to closely predict the effects of circuit topology on the performance of the converter. A phenomenon of particular importance that is observed in the experimental circuits and is predicted by the model is the deleterious feedback effect of the parasitic emitter lead inductance on the base current waveform during the turning-on interval.

Random close packing in protein cores

NASA Astrophysics Data System (ADS)

Ohern, Corey

Shortly after the determination of the first protein x-ray crystal structures, researchers analyzed their cores and reported packing fractions ϕ ~ 0 . 75 , a value that is similar to close packing equal-sized spheres. A limitation of these analyses was the use of `extended atom' models, rather than the more physically accurate `explicit hydrogen' model. The validity of using the explicit hydrogen model is proved by its ability to predict the side chain dihedral angle distributions observed in proteins. We employ the explicit hydrogen model to calculate the packing fraction of the cores of over 200 high resolution protein structures. We find that these protein cores have ϕ ~ 0 . 55 , which is comparable to random close-packing of non-spherical particles. This result provides a deeper understanding of the physical basis of protein structure that will enable predictions of the effects of amino acid mutations and design of new functional proteins. We gratefully acknowledge the support of the Raymond and Beverly Sackler Institute for Biological, Physical, and Engineering Sciences, National Library of Medicine training grant T15LM00705628 (J.C.G.), and National Science Foundation DMR-1307712 (L.R.).

Recovery of speed of information processing in closed-head-injury patients.

PubMed

Zwaagstra, R; Schmidt, I; Vanier, M

1996-06-01

After severe traumatic brain injury, patients almost invariably demonstrate a slowing of reaction time, reflecting a slowing of central information processing. Methodological problems associated with the traditional method for the analysis of longitudinal data (MANOVA) severely complicate studies on cognitive recovery. It is argued that multilevel models are often better suited for the analysis of improvement over time in clinical settings. Multilevel models take into account individual differences in both overall performance level and recovery. These models enable individual predictions for the recovery of speed of information processing. Recovery is modelled in a group of closed-head-injury patients (N = 24). Recovery was predicted by age and severity of injury, as indicated by coma duration. Over a period up to 44 months post trauma, reaction times were found to decrease faster for patients with longer coma duration.

Bayesian model checking: A comparison of tests

NASA Astrophysics Data System (ADS)

Lucy, L. B.

2018-06-01

Two procedures for checking Bayesian models are compared using a simple test problem based on the local Hubble expansion. Over four orders of magnitude, p-values derived from a global goodness-of-fit criterion for posterior probability density functions agree closely with posterior predictive p-values. The former can therefore serve as an effective proxy for the difficult-to-calculate posterior predictive p-values.

Linear prediction and single-channel recording.

PubMed

Carter, A A; Oswald, R E

1995-08-01

The measurement of individual single-channel events arising from the gating of ion channels provides a detailed data set from which the kinetic mechanism of a channel can be deduced. In many cases, the pattern of dwells in the open and closed states is very complex, and the kinetic mechanism and parameters are not easily determined. Assuming a Markov model for channel kinetics, the probability density function for open and closed time dwells should consist of a sum of decaying exponentials. One method of approaching the kinetic analysis of such a system is to determine the number of exponentials and the corresponding parameters which comprise the open and closed dwell time distributions. These can then be compared to the relaxations predicted from the kinetic model to determine, where possible, the kinetic constants. We report here the use of a linear technique, linear prediction/singular value decomposition, to determine the number of exponentials and the exponential parameters. Using simulated distributions and comparing with standard maximum-likelihood analysis, the singular value decomposition techniques provide advantages in some situations and are a useful adjunct to other single-channel analysis techniques.

Air pollution dispersion models for human exposure predictions in London.

PubMed

Beevers, Sean D; Kitwiroon, Nutthida; Williams, Martin L; Kelly, Frank J; Ross Anderson, H; Carslaw, David C

2013-01-01

The London household survey has shown that people travel and are exposed to air pollutants differently. This argues for human exposure to be based upon space-time-activity data and spatio-temporal air quality predictions. For the latter, we have demonstrated the role that dispersion models can play by using two complimentary models, KCLurban, which gives source apportionment information, and Community Multi-scale Air Quality Model (CMAQ)-urban, which predicts hourly air quality. The KCLurban model is in close agreement with observations of NO(X), NO(2) and particulate matter (PM)(10/2.5), having a small normalised mean bias (-6% to 4%) and a large Index of Agreement (0.71-0.88). The temporal trends of NO(X) from the CMAQ-urban model are also in reasonable agreement with observations. Spatially, NO(2) predictions show that within 10's of metres of major roads, concentrations can range from approximately 10-20 p.p.b. up to 70 p.p.b. and that for PM(10/2.5) central London roadside concentrations are approximately double the suburban background concentrations. Exposure to different PM sources is important and we predict that brake wear-related PM(10) concentrations are approximately eight times greater near major roads than at suburban background locations. Temporally, we have shown that average NO(X) concentrations close to roads can range by a factor of approximately six between the early morning minimum and morning rush hour maximum periods. These results present strong arguments for the hybrid exposure model under development at King's and, in future, for in-building models and a model for the London Underground.

A two-component rain model for the prediction of attenuation and diversity improvement

NASA Technical Reports Server (NTRS)

Crane, R. K.

1982-01-01

A new model was developed to predict attenuation statistics for a single Earth-satellite or terrestrial propagation path. The model was extended to provide predictions of the joint occurrences of specified or higher attenuation values on two closely spaced Earth-satellite paths. The joint statistics provide the information required to obtain diversity gain or diversity advantage estimates. The new model is meteorologically based. It was tested against available Earth-satellite beacon observations and terrestrial path measurements. The model employs the rain climate region descriptions of the Global rain model. The rms deviation between the predicted and observed attenuation values for the terrestrial path data was 35 percent, a result consistent with the expectations of the Global model when the rain rate distribution for the path is not used in the calculation. Within the United States the rms deviation between measurement and prediction was 36 percent but worldwide it was 79 percent.

Modeling and optimization of trihalomethanes formation potential of surface water (a drinking water source) using Box-Behnken design.

PubMed

Singh, Kunwar P; Rai, Premanjali; Pandey, Priyanka; Sinha, Sarita

2012-01-01

The present research aims to investigate the individual and interactive effects of chlorine dose/dissolved organic carbon ratio, pH, temperature, bromide concentration, and reaction time on trihalomethanes (THMs) formation in surface water (a drinking water source) during disinfection by chlorination in a prototype laboratory-scale simulation and to develop a model for the prediction and optimization of THMs levels in chlorinated water for their effective control. A five-factor Box-Behnken experimental design combined with response surface and optimization modeling was used for predicting the THMs levels in chlorinated water. The adequacy of the selected model and statistical significance of the regression coefficients, independent variables, and their interactions were tested by the analysis of variance and t test statistics. The THMs levels predicted by the model were very close to the experimental values (R(2) = 0.95). Optimization modeling predicted maximum (192 μg/l) TMHs formation (highest risk) level in water during chlorination was very close to the experimental value (186.8 ± 1.72 μg/l) determined in laboratory experiments. The pH of water followed by reaction time and temperature were the most significant factors that affect the THMs formation during chlorination. The developed model can be used to determine the optimum characteristics of raw water and chlorination conditions for maintaining the THMs levels within the safe limit.

Finite element based model predictive control for active vibration suppression of a one-link flexible manipulator.

PubMed

Dubay, Rickey; Hassan, Marwan; Li, Chunying; Charest, Meaghan

2014-09-01

This paper presents a unique approach for active vibration control of a one-link flexible manipulator. The method combines a finite element model of the manipulator and an advanced model predictive controller to suppress vibration at its tip. This hybrid methodology improves significantly over the standard application of a predictive controller for vibration control. The finite element model used in place of standard modelling in the control algorithm provides a more accurate prediction of dynamic behavior, resulting in enhanced control. Closed loop control experiments were performed using the flexible manipulator, instrumented with strain gauges and piezoelectric actuators. In all instances, experimental and simulation results demonstrate that the finite element based predictive controller provides improved active vibration suppression in comparison with using a standard predictive control strategy. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Predicting human olfactory perception from chemical features of odor molecules.

PubMed

Keller, Andreas; Gerkin, Richard C; Guan, Yuanfang; Dhurandhar, Amit; Turu, Gabor; Szalai, Bence; Mainland, Joel D; Ihara, Yusuke; Yu, Chung Wen; Wolfinger, Russ; Vens, Celine; Schietgat, Leander; De Grave, Kurt; Norel, Raquel; Stolovitzky, Gustavo; Cecchi, Guillermo A; Vosshall, Leslie B; Meyer, Pablo

2017-02-24

It is still not possible to predict whether a given molecule will have a perceived odor or what olfactory percept it will produce. We therefore organized the crowd-sourced DREAM Olfaction Prediction Challenge. Using a large olfactory psychophysical data set, teams developed machine-learning algorithms to predict sensory attributes of molecules based on their chemoinformatic features. The resulting models accurately predicted odor intensity and pleasantness and also successfully predicted 8 among 19 rated semantic descriptors ("garlic," "fish," "sweet," "fruit," "burnt," "spices," "flower," and "sour"). Regularized linear models performed nearly as well as random forest-based ones, with a predictive accuracy that closely approaches a key theoretical limit. These models help to predict the perceptual qualities of virtually any molecule with high accuracy and also reverse-engineer the smell of a molecule. Copyright © 2017, American Association for the Advancement of Science.

Non-parallel coevolution of sender and receiver in the acoustic communication system of treefrogs.

PubMed

Schul, Johannes; Bush, Sarah L

2002-09-07

Advertisement calls of closely related species often differ in quantitative features such as the repetition rate of signal units. These differences are important in species recognition. Current models of signal-receiver coevolution predict two possible patterns in the evolution of the mechanism used by receivers to recognize the call: (i) classical sexual selection models (Fisher process, good genes/indirect benefits, direct benefits models) predict that close relatives use qualitatively similar signal recognition mechanisms tuned to different values of a call parameter; and (ii) receiver bias models (hidden preference, pre-existing bias models) predict that if different signal recognition mechanisms are used by sibling species, evidence of an ancestral mechanism will persist in the derived species, and evidence of a pre-existing bias will be detectable in the ancestral species. We describe qualitatively different call recognition mechanisms in sibling species of treefrogs. Whereas Hyla chrysoscelis uses pulse rate to recognize male calls, Hyla versicolor uses absolute measurements of pulse duration and interval duration. We found no evidence of either hidden preferences or pre-existing biases. The results are compared with similar data from katydids (Tettigonia sp.). In both taxa, the data are not adequately explained by current models of signal-receiver coevolution.

Dynamic Simulation of Human Gait Model With Predictive Capability.

PubMed

Sun, Jinming; Wu, Shaoli; Voglewede, Philip A

2018-03-01

In this paper, it is proposed that the central nervous system (CNS) controls human gait using a predictive control approach in conjunction with classical feedback control instead of exclusive classical feedback control theory that controls based on past error. To validate this proposition, a dynamic model of human gait is developed using a novel predictive approach to investigate the principles of the CNS. The model developed includes two parts: a plant model that represents the dynamics of human gait and a controller that represents the CNS. The plant model is a seven-segment, six-joint model that has nine degrees-of-freedom (DOF). The plant model is validated using data collected from able-bodied human subjects. The proposed controller utilizes model predictive control (MPC). MPC uses an internal model to predict the output in advance, compare the predicted output to the reference, and optimize the control input so that the predicted error is minimal. To decrease the complexity of the model, two joints are controlled using a proportional-derivative (PD) controller. The developed predictive human gait model is validated by simulating able-bodied human gait. The simulation results show that the developed model is able to simulate the kinematic output close to experimental data.

Predictive model for the growth kinetics of Staphylococcus aureus in raw pork developed using Integrated Pathogen Modeling Program (IPMP) 2013.

PubMed

Lee, Yong Ju; Jung, Byeong Su; Kim, Kee-Tae; Paik, Hyun-Dong

2015-09-01

A predictive model was performed to describe the growth of Staphylococcus aureus in raw pork by using Integrated Pathogen Modeling Program 2013 and a polynomial model as a secondary predictive model. S. aureus requires approximately 180 h to reach 5-6 log CFU/g at 10 °C. At 15 °C and 25 °C, approximately 48 and 20 h, respectively, are required to cause food poisoning. Predicted data using the Gompertz model was the most accurate in this study. For lag time (LT) model, bias factor (Bf) and accuracy factor (Af) values were both 1.014, showing that the predictions were within a reliable range. For specific growth rate (SGR) model, Bf and Af were 1.188 and 1.190, respectively. Additionally, both Bf and Af values of the LT and SGR models were close to 1, indicating that IPMP Gompertz model is more adequate for predicting the growth of S. aureus on raw pork than other models. Copyright © 2015 Elsevier Ltd. All rights reserved.

Statistical models and time series forecasting of sulfur dioxide: a case study Tehran.

PubMed

Hassanzadeh, S; Hosseinibalam, F; Alizadeh, R

2009-08-01

This study performed a time-series analysis, frequency distribution and prediction of SO(2) levels for five stations (Pardisan, Vila, Azadi, Gholhak and Bahman) in Tehran for the period of 2000-2005. Most sites show a quite similar characteristic with highest pollution in autumn-winter time and least pollution in spring-summer. The frequency distributions show higher peaks at two residential sites. The potential for SO(2) problems is high because of high emissions and the close geographical proximity of the major industrial and urban centers. The ACF and PACF are nonzero for several lags, indicating a mixed (ARMA) model, then at Bahman station an ARMA model was used for forecasting SO(2). The partial autocorrelations become close to 0 after about 5 lags while the autocorrelations remain strong through all the lags shown. The results proved that ARMA (2,2) model can provides reliable, satisfactory predictions for time series.

A classical model for closed-loop diagrams of binary liquid mixtures

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

Schnitzler, J.v.; Prausnitz, J.M.

1994-03-01

A classical lattice model for closed-loop temperature-composition phase diagrams has been developed. It considers the effect of specific interactions, such as hydrogen bonding, between dissimilar components. This van Laar-type model includes a Flory-Huggins term for the excess entropy of mixing. It is applied to several liquid-liquid equilibria of nonelectrolytes, where the molecules of the two components differ in size. The model is able to represent the observed data semi-quantitatively, but in most cases it is not flexible enough to predict all parts of the closed loop quantitatively. The ability of the model to represent different binary systems is discussed. Finally,more » attention is given to a correction term, concerning the effect of concentration fluctuations near the upper critical solution temperature.« less

A continuous mixing model for pdf simulations and its applications to combusting shear flows

NASA Technical Reports Server (NTRS)

Hsu, A. T.; Chen, J.-Y.

1991-01-01

The problem of time discontinuity (or jump condition) in the coalescence/dispersion (C/D) mixing model is addressed in this work. A C/D mixing model continuous in time is introduced. With the continuous mixing model, the process of chemical reaction can be fully coupled with mixing. In the case of homogeneous turbulence decay, the new model predicts a pdf very close to a Gaussian distribution, with finite higher moments also close to that of a Gaussian distribution. Results from the continuous mixing model are compared with both experimental data and numerical results from conventional C/D models.

Improving Fermi Orbit Determination and Prediction in an Uncertain Atmospheric Drag Environment

NASA Technical Reports Server (NTRS)

Vavrina, Matthew A.; Newman, Clark P.; Slojkowski, Steven E.; Carpenter, J. Russell

2014-01-01

Orbit determination and prediction of the Fermi Gamma-ray Space Telescope trajectory is strongly impacted by the unpredictability and variability of atmospheric density and the spacecraft's ballistic coefficient. Operationally, Global Positioning System point solutions are processed with an extended Kalman filter for orbit determination, and predictions are generated for conjunction assessment with secondary objects. When these predictions are compared to Joint Space Operations Center radar-based solutions, the close approach distance between the two predictions can greatly differ ahead of the conjunction. This work explores strategies for improving prediction accuracy and helps to explain the prediction disparities. Namely, a tuning analysis is performed to determine atmospheric drag modeling and filter parameters that can improve orbit determination as well as prediction accuracy. A 45% improvement in three-day prediction accuracy is realized by tuning the ballistic coefficient and atmospheric density stochastic models, measurement frequency, and other modeling and filter parameters.

A model for predicting aortic dynamic response to -G sub z impact acceleration.

NASA Technical Reports Server (NTRS)

Advani, S. H.; Tarnay, T. J.; Byars, E. F.; Love, J. S.

1972-01-01

A steady state dynamic response model for the radial motion of the aorta is developed from in vivo pressure-displacement and nerve stimulation experiments on canines. The model represented by a modified Van der Pol wave motion oscillator closely predicts steady state and perturbed response results. The applicability of the steady state canine aortic model to tailward acting impact forces is studied by means of the perturbed phase plane of the oscillator. The backflow through the aortic arch resulting from a specified acceleration-time profile is computed and an analysis for predicting the forced motion aortic response is presented.

Effect of Interfacial Turbulence and Accommodation Coefficient on CFD Predictions of Pressurization and Pressure Control in Cryogenic Storage Tank

NASA Technical Reports Server (NTRS)

Kassemi, Mohammad; Kartuzova, Olga; Hylton, Sonya

2015-01-01

Laminar models agree closely with the pressure evolution and vapor phase temperature stratification but under-predict liquid temperatures. Turbulent SST k-w and k-e models under-predict the pressurization rate and extent of stratification in the vapor but represent liquid temperature distributions fairly well. These conclusions seem to equally apply to large cryogenic tank simulations as well as small scale simulant fluid pressurization cases. Appropriate turbulent models that represent both interfacial and bulk vapor phase turbulence with greater fidelity are needed. Application of LES models to the tank pressurization problem can serve as a starting point.

Multiscale Modeling of Structurally-Graded Materials Using Discrete Dislocation Plasticity Models and Continuum Crystal Plasticity Models

NASA Technical Reports Server (NTRS)

Saether, Erik; Hochhalter, Jacob D.; Glaessgen, Edward H.

2012-01-01

A multiscale modeling methodology that combines the predictive capability of discrete dislocation plasticity and the computational efficiency of continuum crystal plasticity is developed. Single crystal configurations of different grain sizes modeled with periodic boundary conditions are analyzed using discrete dislocation plasticity (DD) to obtain grain size-dependent stress-strain predictions. These relationships are mapped into crystal plasticity parameters to develop a multiscale DD/CP model for continuum level simulations. A polycrystal model of a structurally-graded microstructure is developed, analyzed and used as a benchmark for comparison between the multiscale DD/CP model and the DD predictions. The multiscale DD/CP model follows the DD predictions closely up to an initial peak stress and then follows a strain hardening path that is parallel but somewhat offset from the DD predictions. The difference is believed to be from a combination of the strain rate in the DD simulation and the inability of the DD/CP model to represent non-monotonic material response.

Measurement-based reliability prediction methodology. M.S. Thesis

NASA Technical Reports Server (NTRS)

Linn, Linda Shen

1991-01-01

In the past, analytical and measurement based models were developed to characterize computer system behavior. An open issue is how these models can be used, if at all, for system design improvement. The issue is addressed here. A combined statistical/analytical approach to use measurements from one environment to model the system failure behavior in a new environment is proposed. A comparison of the predicted results with the actual data from the new environment shows a close correspondence.

Model of cohesive properties and structural phase transitions in non-metallic solids

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

Majewski, J.A.; Vogl, P.

1986-01-01

We have developed a simple, yet microscopic and universal model for cohesive properties of solids. This model explains the physical mechanisms determining the chemical and predicts semiquantitatively static and dynamic cohesive properties. It predicts a substantial softening of the long-wavelength transverse optical phonons across the pressure induced phase transition from the zincblenda to rocksalt structure in II-VI compounds. The origin of this softening is shown to be closely related to ferroelectricity.

Depth- and range-dependent variation in the performance of aquatic telemetry systems: understanding and predicting the susceptibility of acoustic tag-receiver pairs to close proximity detection interference.

PubMed

Scherrer, Stephen R; Rideout, Brendan P; Giorli, Giacomo; Nosal, Eva-Marie; Weng, Kevin C

2018-01-01

Passive acoustic telemetry using coded transmitter tags and stationary receivers is a popular method for tracking movements of aquatic animals. Understanding the performance of these systems is important in array design and in analysis. Close proximity detection interference (CPDI) is a condition where receivers fail to reliably detect tag transmissions. CPDI generally occurs when the tag and receiver are near one another in acoustically reverberant settings. Here we confirm transmission multipaths reflected off the environment arriving at a receiver with sufficient delay relative to the direct signal cause CPDI. We propose a ray-propagation based model to estimate the arrival of energy via multipaths to predict CPDI occurrence, and we show how deeper deployments are particularly susceptible. A series of experiments were designed to develop and validate our model. Deep (300 m) and shallow (25 m) ranging experiments were conducted using Vemco V13 acoustic tags and VR2-W receivers. Probabilistic modeling of hourly detections was used to estimate the average distance a tag could be detected. A mechanistic model for predicting the arrival time of multipaths was developed using parameters from these experiments to calculate the direct and multipath path lengths. This model was retroactively applied to the previous ranging experiments to validate CPDI observations. Two additional experiments were designed to validate predictions of CPDI with respect to combinations of deployment depth and distance. Playback of recorded tags in a tank environment was used to confirm multipaths arriving after the receiver's blanking interval cause CPDI effects. Analysis of empirical data estimated the average maximum detection radius (AMDR), the farthest distance at which 95% of tag transmissions went undetected by receivers, was between 840 and 846 m for the deep ranging experiment across all factor permutations. From these results, CPDI was estimated within a 276.5 m radius of the receiver. These empirical estimations were consistent with mechanistic model predictions. CPDI affected detection at distances closer than 259-326 m from receivers. AMDR determined from the shallow ranging experiment was between 278 and 290 m with CPDI neither predicted nor observed. Results of validation experiments were consistent with mechanistic model predictions. Finally, we were able to predict detection/nondetection with 95.7% accuracy using the mechanistic model's criterion when simulating transmissions with and without multipaths. Close proximity detection interference results from combinations of depth and distance that produce reflected signals arriving after a receiver's blanking interval has ended. Deployment scenarios resulting in CPDI can be predicted with the proposed mechanistic model. For deeper deployments, sea-surface reflections can produce CPDI conditions, resulting in transmission rejection, regardless of the reflective properties of the seafloor.

A Study of the Dependence of Microsegregation on Critical Solidification Parameters in Rapidly-Quenched Structures.

DTIC Science & Technology

1980-12-01

a formulation given in many sources (Refs. 1-3). The laser is assumed to penetrate completely through the material (making a " keyhole ") and the heat...absorbed laser power as determined from calor- imetric measurements. The analytical predictions were brought to close agree- ment with the experimental...kW power setting would be about 45 kW/cm 2. This value is close to the 50 kW/cm2 line predicted by the model. As in Fig. 13, the laser dwell time is

Stagnation Point Nonequilibrium Radiative Heating and the Influence of Energy Exchange Models

NASA Technical Reports Server (NTRS)

Hartung, Lin C.; Mitcheltree, Robert A.; Gnoffo, Peter A.

1991-01-01

A nonequilibrium radiative heating prediction method has been used to evaluate several energy exchange models used in nonequilibrium computational fluid dynamics methods. The radiative heating measurements from the FIRE II flight experiment supply an experimental benchmark against which different formulations for these exchange models can be judged. The models which predict the lowest radiative heating are found to give the best agreement with the flight data. Examination of the spectral distribution of radiation indicates that despite close agreement of the total radiation, many of the models examined predict excessive molecular radiation. It is suggested that a study of the nonequilibrium chemical kinetics may lead to a correction for this problem.

Scaling of chew cycle duration in primates.

PubMed

Ross, Callum F; Reed, David A; Washington, Rhyan L; Eckhardt, Alison; Anapol, Fred; Shahnoor, Nazima

2009-01-01

The biomechanical determinants of the scaling of chew cycle duration are important components of models of primate feeding systems at all levels, from the neuromechanical to the ecological. Chew cycle durations were estimated in 35 species of primates and analyzed in conjunction with data on morphological variables of the feeding system estimating moment of inertia of the mandible and force production capacity of the chewing muscles. Data on scaling of primate chew cycle duration were compared with the predictions of simple pendulum and forced mass-spring system models of the feeding system. The gravity-driven pendulum model best predicts the observed cycle duration scaling but is rejected as biomechanically unrealistic. The forced mass-spring model predicts larger increases in chew cycle duration with size than observed, but provides reasonable predictions of cycle duration scaling. We hypothesize that intrinsic properties of the muscles predict spring-like behavior of the jaw elevator muscles during opening and fast close phases of the jaw cycle and that modulation of stiffness by the central nervous system leads to spring-like properties during the slow close/power stroke phase. Strepsirrhines show no predictable relationship between chew cycle duration and jaw length. Anthropoids have longer chew cycle durations than nonprimate mammals with similar mandible lengths, possibly due to their enlarged symphyses, which increase the moment of inertia of the mandible. Deviations from general scaling trends suggest that both scaling of the jaw muscles and the inertial properties of the mandible are important in determining the scaling of chew cycle duration in primates.

The association between early generative concern and caregiving with friends from early to middle adolescence.

PubMed

Lawford, Heather L; Doyle, Anna-Beth; Markiewicz, Dorothy

2013-12-01

Generativity, defined as concern for future generations, is theorized to become a priority in midlife, preceded by a stage in which intimacy is the central issue. Recent research, however, has found evidence of generativity even in adolescence. This longitudinal study explored the associations between caregiving in friendships, closely related to intimacy, and early generative concern in a young adolescent sample. Given the importance of close friendships in adolescence, it was hypothesized that responsive caregiving in early adolescent friendships would predict later generative concern. Approximately 140 adolescents (56 % female, aged 14 at Time 1) completed questionnaires regarding generative concern and responsive caregiving with friends yearly across 2 years. Structural equation modeling revealed that caregiving predicted generative concern 1 year later but generative concern did not predict later caregiving. These results suggest that caregiving in close friendships plays an important role in the development of adolescents' motivation to contribute to future generations.

A mathematical model for the interactive behavior of sulfate-reducing bacteria and methanogens during anaerobic digestion.

PubMed

Ahammad, S Ziauddin; Gomes, James; Sreekrishnan, T R

2011-09-01

Anaerobic degradation of waste involves different classes of microorganisms, and there are different types of interactions among them for substrates, terminal electron acceptors, and so on. A mathematical model is developed based on the mass balance of different substrates, products, and microbes present in the system to study the interaction between methanogens and sulfate-reducing bacteria (SRB). The performance of major microbial consortia present in the system, such as propionate-utilizing acetogens, butyrate-utilizing acetogens, acetoclastic methanogens, hydrogen-utilizing methanogens, and SRB were considered and analyzed in the model. Different substrates consumed and products formed during the process also were considered in the model. The experimental observations and model predictions showed very good prediction capabilities of the model. Model prediction was validated statistically. It was observed that the model-predicted values matched the experimental data very closely, with an average error of 3.9%.

State-space prediction model for chaotic time series

NASA Astrophysics Data System (ADS)

Alparslan, A. K.; Sayar, M.; Atilgan, A. R.

1998-08-01

A simple method for predicting the continuation of scalar chaotic time series ahead in time is proposed. The false nearest neighbors technique in connection with the time-delayed embedding is employed so as to reconstruct the state space. A local forecasting model based upon the time evolution of the topological neighboring in the reconstructed phase space is suggested. A moving root-mean-square error is utilized in order to monitor the error along the prediction horizon. The model is tested for the convection amplitude of the Lorenz model. The results indicate that for approximately 100 cycles of the training data, the prediction follows the actual continuation very closely about six cycles. The proposed model, like other state-space forecasting models, captures the long-term behavior of the system due to the use of spatial neighbors in the state space.

Dancing to CHANGA: a self-consistent prediction for close SMBH pair formation time-scales following galaxy mergers

NASA Astrophysics Data System (ADS)

Tremmel, M.; Governato, F.; Volonteri, M.; Quinn, T. R.; Pontzen, A.

2018-04-01

We present the first self-consistent prediction for the distribution of formation time-scales for close supermassive black hole (SMBH) pairs following galaxy mergers. Using ROMULUS25, the first large-scale cosmological simulation to accurately track the orbital evolution of SMBHs within their host galaxies down to sub-kpc scales, we predict an average formation rate density of close SMBH pairs of 0.013 cMpc-3 Gyr-1. We find that it is relatively rare for galaxy mergers to result in the formation of close SMBH pairs with sub-kpc separation and those that do form are often the result of Gyr of orbital evolution following the galaxy merger. The likelihood and time-scale to form a close SMBH pair depends strongly on the mass ratio of the merging galaxies, as well as the presence of dense stellar cores. Low stellar mass ratio mergers with galaxies that lack a dense stellar core are more likely to become tidally disrupted and deposit their SMBH at large radii without any stellar core to aid in their orbital decay, resulting in a population of long-lived `wandering' SMBHs. Conversely, SMBHs in galaxies that remain embedded within a stellar core form close pairs in much shorter time-scales on average. This time-scale is a crucial, though often ignored or very simplified, ingredient to models predicting SMBH mergers rates and the connection between SMBH and star formation activity.

Coupling sensing to crop models for closed-loop plant production in advanced life support systems

NASA Astrophysics Data System (ADS)

Cavazzoni, James; Ling, Peter P.

1999-01-01

We present a conceptual framework for coupling sensing to crop models for closed-loop analysis of plant production for NASA's program in advanced life support. Crop status may be monitored through non-destructive observations, while models may be independently applied to crop production planning and decision support. To achieve coupling, environmental variables and observations are linked to mode inputs and outputs, and monitoring results compared with model predictions of plant growth and development. The information thus provided may be useful in diagnosing problems with the plant growth system, or as a feedback to the model for evaluation of plant scheduling and potential yield. In this paper, we demonstrate this coupling using machine vision sensing of canopy height and top projected canopy area, and the CROPGRO crop growth model. Model simulations and scenarios are used for illustration. We also compare model predictions of the machine vision variables with data from soybean experiments conducted at New Jersey Agriculture Experiment Station Horticulture Greenhouse Facility, Rutgers University. Model simulations produce reasonable agreement with the available data, supporting our illustration.

A simple solution for model comparison in bold imaging: the special case of reward prediction error and reward outcomes.

PubMed

Erdeniz, Burak; Rohe, Tim; Done, John; Seidler, Rachael D

2013-01-01

Conventional neuroimaging techniques provide information about condition-related changes of the BOLD (blood-oxygen-level dependent) signal, indicating only where and when the underlying cognitive processes occur. Recently, with the help of a new approach called "model-based" functional neuroimaging (fMRI), researchers are able to visualize changes in the internal variables of a time varying learning process, such as the reward prediction error or the predicted reward value of a conditional stimulus. However, despite being extremely beneficial to the imaging community in understanding the neural correlates of decision variables, a model-based approach to brain imaging data is also methodologically challenging due to the multicollinearity problem in statistical analysis. There are multiple sources of multicollinearity in functional neuroimaging including investigations of closely related variables and/or experimental designs that do not account for this. The source of multicollinearity discussed in this paper occurs due to correlation between different subjective variables that are calculated very close in time. Here, we review methodological approaches to analyzing such data by discussing the special case of separating the reward prediction error signal from reward outcomes.

Simple Elasticity Modeling and Failure Prediction for Composite Flexbeams

NASA Technical Reports Server (NTRS)

Makeev, Andrew; Armanios, Erian; OBrien, T. Kevin (Technical Monitor)

2001-01-01

A simple 2D boundary element analysis, suitable for developing cost effective models for tapered composite laminates, is presented. Constant stress and displacement elements are used. Closed-form fundamental solutions are derived. Numerical results are provided for several configurations to illustrate the accuracy of the model.

Statistical optimization of the phytoremediation of arsenic by Ludwigia octovalvis- in a pilot reed bed using response surface methodology (RSM) versus an artificial neural network (ANN).

PubMed

Titah, Harmin Sulistiyaning; Halmi, Mohd Izuan Effendi Bin; Abdullah, Siti Rozaimah Sheikh; Hasan, Hassimi Abu; Idris, Mushrifah; Anuar, Nurina

2018-06-07

In this study, the removal of arsenic (As) by plant, Ludwigia octovalvis, in a pilot reed bed was optimized. A Box-Behnken design was employed including a comparative analysis of both Response Surface Methodology (RSM) and an Artificial Neural Network (ANN) for the prediction of maximum arsenic removal. The predicted optimum condition using the desirability function of both models was 39 mg kg -1 for the arsenic concentration in soil, an elapsed time of 42 days (the sampling day) and an aeration rate of 0.22 L/min, with the predicted values of arsenic removal by RSM and ANN being 72.6% and 71.4%, respectively. The validation of the predicted optimum point showed an actual arsenic removal of 70.6%. This was achieved with the deviation between the validation value and the predicted values being within 3.49% (RSM) and 1.87% (ANN). The performance evaluation of the RSM and ANN models showed that ANN performs better than RSM with a higher R 2 (0.97) close to 1.0 and very small Average Absolute Deviation (AAD) (0.02) and Root Mean Square Error (RMSE) (0.004) values close to zero. Both models were appropriate for the optimization of arsenic removal with ANN demonstrating significantly higher predictive and fitting ability than RSM.

Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Gaussian Processes Mixture

PubMed Central

Li, Lingling; Wang, Pengchong; Chao, Kuei-Hsiang; Zhou, Yatong; Xie, Yang

2016-01-01

The remaining useful life (RUL) prediction of Lithium-ion batteries is closely related to the capacity degeneration trajectories. Due to the self-charging and the capacity regeneration, the trajectories have the property of multimodality. Traditional prediction models such as the support vector machines (SVM) or the Gaussian Process regression (GPR) cannot accurately characterize this multimodality. This paper proposes a novel RUL prediction method based on the Gaussian Process Mixture (GPM). It can process multimodality by fitting different segments of trajectories with different GPR models separately, such that the tiny differences among these segments can be revealed. The method is demonstrated to be effective for prediction by the excellent predictive result of the experiments on the two commercial and chargeable Type 1850 Lithium-ion batteries, provided by NASA. The performance comparison among the models illustrates that the GPM is more accurate than the SVM and the GPR. In addition, GPM can yield the predictive confidence interval, which makes the prediction more reliable than that of traditional models. PMID:27632176

Thermal Pollution Mathematical Model. Volume 5: User's Manual for Three-Dimensional Rigid-Lid Model. [environment impact of thermal discharges from power plants

NASA Technical Reports Server (NTRS)

Lee, S. S.; Sengupta, S.; Nwadike, E. V.; Sinha, S. K.

1980-01-01

A user's manual for a three dimensional, rigid lid model used for hydrothermal predictions of closed basins subjected to a heated discharge together with various other inflows and outflows is presented. The model has the capability to predict (1) wind driven circulation; (2) the circulation caused by inflows and outflows to the domain; and (3) the thermal effects in the domain, and to combine the above processes. The calibration procedure consists of comparing ground truth corrected airborne radiometer data with surface isotherms predicted by the model. The model was verified for accuracy at various sites and results are found to be fairly accurate in all verification runs.

Modelling complex phenomena in optical fibres

NASA Astrophysics Data System (ADS)

Allington-Smith, Jeremy; Murray, Graham; Lemke, Ulrike

2012-09-01

We present a new model for predicting the performance of fibre systems in the multimode limit. This is based on ray-­-tracing but includes a semi-­-empirical description of Focal Ratio Degradation (FRD). We show how FRD is simulated by the model. With this ability, it can be used to investigate a wide variety of phenomena including scrambling and the loss of light close to the limiting numerical aperture. It can also be used to predict the performance of non-­-round and asymmetric fibres.

EnKF with closed-eye period - bridging intermittent model structural errors in soil hydrology

NASA Astrophysics Data System (ADS)

Bauser, Hannes H.; Jaumann, Stefan; Berg, Daniel; Roth, Kurt

2017-04-01

The representation of soil water movement exposes uncertainties in all model components, namely dynamics, forcing, subscale physics and the state itself. Especially model structural errors in the description of the dynamics are difficult to represent and can lead to an inconsistent estimation of the other components. We address the challenge of a consistent aggregation of information for a manageable specific hydraulic situation: a 1D soil profile with TDR-measured water contents during a time period of less than 2 months. We assess the uncertainties for this situation and detect initial condition, soil hydraulic parameters, small-scale heterogeneity, upper boundary condition, and (during rain events) the local equilibrium assumption by the Richards equation as the most important ones. We employ an iterative Ensemble Kalman Filter (EnKF) with an augmented state. Based on a single rain event, we are able to reduce all uncertainties directly, except for the intermittent violation of the local equilibrium assumption. We detect these times by analyzing the temporal evolution of estimated parameters. By introducing a closed-eye period - during which we do not estimate parameters, but only guide the state based on measurements - we can bridge these times. The introduced closed-eye period ensured constant parameters, suggesting that they resemble the believed true material properties. The closed-eye period improves predictions during periods when the local equilibrium assumption is met, but consequently worsens predictions when the assumption is violated. Such a prediction requires a description of the dynamics during local non-equilibrium phases, which remains an open challenge.

Closed Loop System Identification with Genetic Algorithms

NASA Technical Reports Server (NTRS)

Whorton, Mark S.

2004-01-01

High performance control design for a flexible space structure is challenging since high fidelity plant models are di.cult to obtain a priori. Uncertainty in the control design models typically require a very robust, low performance control design which must be tuned on-orbit to achieve the required performance. Closed loop system identi.cation is often required to obtain a multivariable open loop plant model based on closed-loop response data. In order to provide an accurate initial plant model to guarantee convergence for standard local optimization methods, this paper presents a global parameter optimization method using genetic algorithms. A minimal representation of the state space dynamics is employed to mitigate the non-uniqueness and over-parameterization of general state space realizations. This control-relevant system identi.cation procedure stresses the joint nature of the system identi.cation and control design problem by seeking to obtain a model that minimizes the di.erence between the predicted and actual closed-loop performance.

Predictability and Coupled Dynamics of MJO During DYNAMO

DTIC Science & Technology

2013-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Predictability and Coupled Dynamics of MJO During DYNAMO ... DYNAMO time period. APPROACH We are working as a team to study MJO dynamics and predictability using several models as team members of the ONR DRI...associated with the DYNAMO experiment. This is a fundamentally collaborative proposal that involves close collaboration with Dr. Hyodae Seo of the

Comparison of simulator fidelity model predictions with in-simulator evaluation data

NASA Technical Reports Server (NTRS)

Parrish, R. V.; Mckissick, B. T.; Ashworth, B. R.

1983-01-01

A full factorial in simulator experiment of a single axis, multiloop, compensatory pitch tracking task is described. The experiment was conducted to provide data to validate extensions to an analytic, closed loop model of a real time digital simulation facility. The results of the experiment encompassing various simulation fidelity factors, such as visual delay, digital integration algorithms, computer iteration rates, control loading bandwidths and proprioceptive cues, and g-seat kinesthetic cues, are compared with predictions obtained from the analytic model incorporating an optimal control model of the human pilot. The in-simulator results demonstrate more sensitivity to the g-seat and to the control loader conditions than were predicted by the model. However, the model predictions are generally upheld, although the predicted magnitudes of the states and of the error terms are sometimes off considerably. Of particular concern is the large sensitivity difference for one control loader condition, as well as the model/in-simulator mismatch in the magnitude of the plant states when the other states match.

A hybrid probabilistic/spectral model of scalar mixing

NASA Astrophysics Data System (ADS)

Vaithianathan, T.; Collins, Lance

2002-11-01

In the probability density function (PDF) description of a turbulent reacting flow, the local temperature and species concentration are replaced by a high-dimensional joint probability that describes the distribution of states in the fluid. The PDF has the great advantage of rendering the chemical reaction source terms closed, independent of their complexity. However, molecular mixing, which involves two-point information, must be modeled. Indeed, the qualitative shape of the PDF is sensitive to this modeling, hence the reliability of the model to predict even the closed chemical source terms rests heavily on the mixing model. We will present a new closure to the mixing based on a spectral representation of the scalar field. The model is implemented as an ensemble of stochastic particles, each carrying scalar concentrations at different wavenumbers. Scalar exchanges within a given particle represent ``transfer'' while scalar exchanges between particles represent ``mixing.'' The equations governing the scalar concentrations at each wavenumber are derived from the eddy damped quasi-normal Markovian (or EDQNM) theory. The model correctly predicts the evolution of an initial double delta function PDF into a Gaussian as seen in the numerical study by Eswaran & Pope (1988). Furthermore, the model predicts the scalar gradient distribution (which is available in this representation) approaches log normal at long times. Comparisons of the model with data derived from direct numerical simulations will be shown.

Social support, posttraumatic cognitions, and PTSD: The influence of family, friends, and a close other in an interpersonal and non-interpersonal trauma group.

PubMed

Woodward, Matthew J; Eddinger, Jasmine; Henschel, Aisling V; Dodson, Thomas S; Tran, Han N; Beck, J Gayle

2015-10-01

Research has suggested that social support can shape posttraumatic cognitions and PTSD. However, research has yet to compare the influence of separate domains of support on posttraumatic cognitions. Multiple-group path analysis was used to examine a model in a sample of 170 victims of intimate partner violence and 208 motor vehicle accident victims in which support from friends, family, and a close other were each predicted to influence posttraumatic cognitions, which were in turn predicted to influence PTSD. Analyses revealed that support from family and friends were each negatively correlated with posttraumatic cognitions, which in turn were positively associated with PTSD. Social support from a close other was not associated with posttraumatic cognitions. No significant differences in the model were found between trauma groups. Findings identify which relationships are likely to influence posttraumatic cognitions and are discussed with regard to interpersonal processes in the development and maintenance of PTSD. Copyright © 2015 Elsevier Ltd. All rights reserved.

Emotional closeness to parents and grandparents: A moderated mediation model predicting adolescent adjustment.

PubMed

Attar-Schwartz, Shalhevet

2015-09-01

Warm and emotionally close relationships with parents and grandparents have been found in previous studies to be linked with better adolescent adjustment. The present study, informed by Family Systems Theory and Intergenerational Solidarity Theory, uses a moderated mediation model analyzing the contribution of the dynamics of these intergenerational relationships to adolescent adjustment. Specifically, it examines the mediating role of emotional closeness to the closest grandparent in the relationship between emotional closeness to a parent (the offspring of the closest grandparent) and adolescent adjustment difficulties. The model also examines the moderating role of emotional closeness to parents in the relationship between emotional closeness to grandparents and adjustment difficulties. The study was based on a sample of 1,405 Jewish Israeli secondary school students (ages 12-18) who completed a structured questionnaire. It was found that emotional closeness to the closest grandparent was more strongly associated with reduced adjustment difficulties among adolescents with higher levels of emotional closeness to their parents. In addition, adolescent adjustment and emotional closeness to parents was partially mediated by emotional closeness to grandparents. Examining the family conditions under which adolescents' relationships with grandparents is stronger and more beneficial for them can help elucidate variations in grandparent-grandchild ties and expand our understanding of the mechanisms that shape child outcomes. (c) 2015 APA, all rights reserved).

SONOS Nonvolatile Memory Cell Programming Characteristics

NASA Technical Reports Server (NTRS)

MacLeod, Todd C.; Phillips, Thomas A.; Ho, Fat D.

2010-01-01

Silicon-oxide-nitride-oxide-silicon (SONOS) nonvolatile memory is gaining favor over conventional EEPROM FLASH memory technology. This paper characterizes the SONOS write operation using a nonquasi-static MOSFET model. This includes floating gate charge and voltage characteristics as well as tunneling current, voltage threshold and drain current characterization. The characterization of the SONOS memory cell predicted by the model closely agrees with experimental data obtained from actual SONOS memory cells. The tunnel current, drain current, threshold voltage and read drain current all closely agreed with empirical data.

The remarkable ability of turbulence model equations to describe transition

NASA Technical Reports Server (NTRS)

Wilcox, David C.

1992-01-01

This paper demonstrates how well the k-omega turbulence model describes the nonlinear growth of flow instabilities from laminar flow into the turbulent flow regime. Viscous modifications are proposed for the k-omega model that yield close agreement with measurements and with Direct Numerical Simulation results for channel and pipe flow. These modifications permit prediction of subtle sublayer details such as maximum dissipation at the surface, k approximately y(exp 2) as y approaches 0, and the sharp peak value of k near the surface. With two transition specific closure coefficients, the model equations accurately predict transition for an incompressible flat-plate boundary layer. The analysis also shows why the k-epsilon model is so difficult to use for predicting transition.

Large-scale wind-tunnel investigation of a close-coupled canard-delta-wing fighter model through high angles of attack

NASA Technical Reports Server (NTRS)

Stoll, F.; Koenig, D. G.

1983-01-01

Data obtained through very high angles of attack from a large-scale, subsonic wind-tunnel test of a close-coupled canard-delta-wing fighter model are analyzed. The canard delays wing leading-edge vortex breakdown, even for angles of attack at which the canard is completely stalled. A vortex-lattice method was applied which gave good predictions of lift and pitching moment up to an angle of attack of about 20 deg, where vortex-breakdown effects on performance become significant. Pitch-control inputs generally retain full effectiveness up to the angle of attack of maximum lift, beyond which, effectiveness drops off rapidly. A high-angle-of-attack prediction method gives good estimates of lift and drag for the completely stalled aircraft. Roll asymmetry observed at zero sideslip is apparently caused by an asymmetry in the model support structure.

Real-time economic nonlinear model predictive control for wind turbine control

NASA Astrophysics Data System (ADS)

Gros, Sebastien; Schild, Axel

2017-12-01

Nonlinear model predictive control (NMPC) is a strong candidate to handle the control challenges emerging in the modern wind energy industry. Recent research suggested that wind turbine (WT) control based on economic NMPC (ENMPC) can improve the closed-loop performance and simplify the task of controller design when compared to a classical NMPC approach. This paper establishes a formal relationship between the ENMPC controller and the classic NMPC approach, and compares empirically their closed-loop nominal behaviour and performance. The robustness of the performance is assessed for an inaccurate modelling of the tower fore-aft main frequency. Additionally, though a perfect wind preview is assumed here, the effect of having a limited horizon of preview of the wind speed via the LIght Detection And Ranging (LIDAR) sensor is investigated. Finally, this paper provides new algorithmic solutions for deploying ENMPC for WT control, and report improved computational times.

A Physiologically-Based Description of the Inhalation Pharmacokinetics of Styrene in Rats and Humans

DTIC Science & Technology

1983-01-01

model for rat were scaled to give a description of human kinetics and the predictions agreed closely with available data from the literature (Fig. 4...for predicting human kinetics from a data base in other mammalian species. The ability to anticipate kinetic behavior in humans could very much improve

[Application of an artificial neural network in the design of sustained-release dosage forms].

PubMed

Wei, X H; Wu, J J; Liang, W Q

2001-09-01

To use the artificial neural network (ANN) in Matlab 5.1 tool-boxes to predict the formulations of sustained-release tablets. The solubilities of nine drugs and various ratios of HPMC: Dextrin for 63 tablet formulations were used as the ANN model input, and in vitro accumulation released at 6 sampling times were used as output. The ANN model was constructed by selecting the optimal number of iterations (25) and model structure in which there are one hidden layer and five hidden layer nodes. The optimized ANN model was used for prediction of formulation based on desired target in vitro dissolution-time profiles. ANN predicted profiles based on ANN predicted formulations were closely similar to the target profiles. The ANN could be used for predicting the dissolution profiles of sustained release dosage form and for the design of optimal formulation.

Investigating calcite growth rates using a quartz crystal microbalance with dissipation (QCM-D)

NASA Astrophysics Data System (ADS)

Cao, Bo; Stack, Andrew G.; Steefel, Carl I.; DePaolo, Donald J.; Lammers, Laura N.; Hu, Yandi

2018-02-01

Calcite precipitation plays a significant role in processes such as geological carbon sequestration and toxic metal sequestration and, yet, the rates and mechanisms of calcite growth under close to equilibrium conditions are far from well understood. In this study, a quartz crystal microbalance with dissipation (QCM-D) was used for the first time to measure macroscopic calcite growth rates. Calcite seed crystals were first nucleated and grown on sensors, then growth rates of calcite seed crystals were measured in real-time under close to equilibrium conditions (saturation index, SI = log ({Ca2+}/{CO32-}/Ksp) = 0.01-0.7, where {i} represent ion activities and Ksp = 10-8.48 is the calcite thermodynamic solubility constant). At the end of the experiments, total masses of calcite crystals on sensors measured by QCM-D and inductively coupled plasma mass spectrometry (ICP-MS) were consistent, validating the QCM-D measurements. Calcite growth rates measured by QCM-D were compared with reported macroscopic growth rates measured with auto-titration, ICP-MS, and microbalance. Calcite growth rates measured by QCM-D were also compared with microscopic growth rates measured by atomic force microscopy (AFM) and with rates predicted by two process-based crystal growth models. The discrepancies in growth rates among AFM measurements and model predictions appear to mainly arise from differences in step densities, and the step velocities were consistent among the AFM measurements as well as with both model predictions. Using the predicted steady-state step velocity and the measured step densities, both models predict well the growth rates measured using QCM-D and AFM. This study provides valuable insights into the effects of reactive site densities on calcite growth rate, which may help design future growth models to predict transient-state step densities.

Model Predictions and Observed Performance of JWST's Cryogenic Position Metrology System

NASA Technical Reports Server (NTRS)

Lunt, Sharon R.; Rhodes, David; DiAntonio, Andrew; Boland, John; Wells, Conrad; Gigliotti, Trevis; Johanning, Gary

2016-01-01

The James Webb Space Telescope cryogenic testing requires measurement systems that both obtain a very high degree of accuracy and can function in that environment. Close-range photogrammetry was identified as meeting those criteria. Testing the capability of a close-range photogrammetric system prior to its existence is a challenging problem. Computer simulation was chosen over building a scaled mock-up to allow for increased flexibility in testing various configurations. Extensive validation work was done to ensure that the actual as-built system meet accuracy and repeatability requirements. The simulated image data predicted the uncertainty in measurement to be within specification and this prediction was borne out experimentally. Uncertainty at all levels was verified experimentally to be less than 0.1 millimeters.

Control of epileptic seizures in WAG/Rij rats by means of brain-computer interface

NASA Astrophysics Data System (ADS)

Makarov, Vladimir V.; Maksimenko, Vladimir A.; van Luijtelaar, Gilles; Lüttjohann, Annika; Hramov, Alexander E.

2018-02-01

The main issue of epileptology is the elimination of epileptic events. This can be achieved by a system that predicts the emergence of seizures in conjunction with a system that interferes with the process that leads to the onset of seizure. The prediction of seizures remains, for the present, unresolved in the absence epilepsy, due to the sudden onset of seizures. We developed an algorithm for predicting seizures in real time, evaluated it and implemented it into an online closed-loop brain stimulation system designed to prevent typical for the absence of epilepsy of spike waves (SWD) in the genetic rat model. The algorithm correctly predicts more than 85% of the seizures and the rest were successfully detected. Unlike the old beliefs that SWDs are unpredictable, current results show that they can be predicted and that the development of systems for predicting and preventing closed-loop capture is a feasible step on the way to intervention to achieve control and freedom from epileptic seizures.

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

Smith, Kandler A; Usseglio Viretta, Francois L; Graf, Peter A

This presentation describes research work led by NREL with team members from Argonne National Laboratory and Texas A&M University in microstructure analysis, modeling and validation under DOE's Computer-Aided Engineering of Batteries (CAEBAT) program. The goal of the project is to close the gaps between CAEBAT models and materials research by creating predictive models that can be used for electrode design.

Non-Nuclear Validation Test Results of a Closed Brayton Cycle Test-Loop

NASA Astrophysics Data System (ADS)

Wright, Steven A.

2007-01-01

Both NASA and DOE have programs that are investigating advanced power conversion cycles for planetary surface power on the moon or Mars, or for next generation nuclear power plants on earth. Although open Brayton cycles are in use for many applications (combined cycle power plants, aircraft engines), only a few closed Brayton cycles have been tested. Experience with closed Brayton cycles coupled to nuclear reactors is even more limited and current projections of Brayton cycle performance are based on analytic models. This report describes and compares experimental results with model predictions from a series of non-nuclear tests using a small scale closed loop Brayton cycle available at Sandia National Laboratories. A substantial amount of testing has been performed, and the information is being used to help validate models. In this report we summarize the results from three kinds of tests. These tests include: 1) test results that are useful for validating the characteristic flow curves of the turbomachinery for various gases ranging from ideal gases (Ar or Ar/He) to non-ideal gases such as CO2, 2) test results that represent shut down transients and decay heat removal capability of Brayton loops after reactor shut down, and 3) tests that map a range of operating power versus shaft speed curve and turbine inlet temperature that are useful for predicting stable operating conditions during both normal and off-normal operating behavior. These tests reveal significant interactions between the reactor and balance of plant. Specifically these results predict limited speed up behavior of the turbomachinery caused by loss of load, the conditions for stable operation, and for direct cooled reactors, the tests reveal that the coast down behavior during loss of power events can extend for hours provided the ultimate heat sink remains available.

Endorsement of sexist ideology in Taiwan and the United States: social dominance orientation, right-wing authoritarianism, and deferential family norms.

PubMed

Lee, I-Ching

2013-01-01

Despite close relationships between men and women in daily lives, gender inequality is ubiquitous and often supported by sexist ideology. The understanding of potential bases of sexist ideology is thus important. According to Duckitt's dual-process model (2001), different worldviews may explain different types of sexist ideology. Individuals who hold a "competitive world" worldview tend to endorse group-based dominance. This lends itself to the endorsement of hostile sexism, because hostile sexism is an obvious form of male dominance. Conversely, individuals who hold a "dangerous world" worldview tend to adhere to social cohesion, collective security, and social traditions. This lends itself to the endorsement of benevolent sexism, because benevolent sexism values women who conform to gender norms. As predicted by Duckitt's model, research has shown that social dominance orientation, a general orientation towards the endorsement of group-based dominance, is closely associated with hostile sexism. Furthermore, right-wing authoritarianism, which measures adherence to social traditions, is closely associated with benevolent sexism. Due to the interdependent nature of gender relationships, the current research proposed that a relationship-based belief in hierarchy, deferential family norms, and norms depicting proper manners among family members should predict the endorsement of hostile and benevolent sexism, after controlling for social dominance orientation and right-wing authoritarianism. As predicted, according to student samples collected in Taiwan and the US, the endorsement of deferential family norms predicted the endorsement of hostile sexism and of benevolent sexism, respectively. In addition, among men and women, social dominance orientation predicted hostile sexism more strongly (as opposed to benevolent sexism), whereas right-wing authoritarianism predicted benevolent sexism more strongly (as opposed to hostile sexism). Implications regarding relationship norms, social dominance orientation, right-wing authoritarianism, and sexist ideology are discussed.

Structure Prediction of the Second Extracellular Loop in G-Protein-Coupled Receptors

PubMed Central

Kmiecik, Sebastian; Jamroz, Michal; Kolinski, Michal

2014-01-01

G-protein-coupled receptors (GPCRs) play key roles in living organisms. Therefore, it is important to determine their functional structures. The second extracellular loop (ECL2) is a functionally important region of GPCRs, which poses significant challenge for computational structure prediction methods. In this work, we evaluated CABS, a well-established protein modeling tool for predicting ECL2 structure in 13 GPCRs. The ECL2s (with between 13 and 34 residues) are predicted in an environment of other extracellular loops being fully flexible and the transmembrane domain fixed in its x-ray conformation. The modeling procedure used theoretical predictions of ECL2 secondary structure and experimental constraints on disulfide bridges. Our approach yielded ensembles of low-energy conformers and the most populated conformers that contained models close to the available x-ray structures. The level of similarity between the predicted models and x-ray structures is comparable to that of other state-of-the-art computational methods. Our results extend other studies by including newly crystallized GPCRs. PMID:24896119

Integrated modeling and analysis of a space-truss article

NASA Technical Reports Server (NTRS)

Stockwell, Alan E.; Perez, Sharon E.; Pappa, Richard S.

1990-01-01

MSC/NASTRAN is being used in the Controls-Structures Interaction (CSI) program at NASA Langley Research Center as a key analytical tool for structural analysis as well as the basis for control law development, closed-loop performance evaluation, and system safety checks. Guest investigators from academia and industry are performing dynamics and control experiments on a flight-like deployable space truss called Mini-Mast to determine the effectiveness of various active-vibration control laws. MSC/NASTRAN was used to calculate natural frequencies and mode shapes below 100 Hz to describe the dynamics of the 20-meter-long lightweight Mini-Mast structure. Gravitational effects contribute significantly to structural stiffness and are accounted for through a two-phase solution in which the differential stiffness matrix is calculated and then used in the eigensolution. Reduced modal models are extracted for control law design and evaluation of closed-loop system performance. Predicted actuator forces from controls simulations are then applied to the extended model to predict member loads and stresses. These pre-test analyses reduce risks associated with the structural integrity of the test article, which is a major concern in closed-loop control experiments due to potential instabilities.

Analytical prediction of the interior noise for cylindrical models of aircraft fuselages for prescribed exterior noise fields. Phase 1: Development and validation of preliminary analytical models

NASA Technical Reports Server (NTRS)

Pope, L. D.; Rennison, D. C.; Wilby, E. G.

1980-01-01

The basic theoretical work required to understand sound transmission into an enclosed space (that is, one closed by the transmitting structure) is developed for random pressure fields and for harmonic (tonal) excitation. The analysis is used to predict the noise reducton of unpressurized unstiffened cylinder, and also the interior response of the cylinder given a tonal (plane wave) excitation. Predictions and measurements are compared and the transmission is analyzed. In addition, results for tonal (harmonic) mechanical excitation are considered.

GaN microrod sidewall epitaxial lateral overgrowth on a close-packed microrod template

NASA Astrophysics Data System (ADS)

Duan, Xiaoling; Zhang, Jincheng; Xiao, Ming; Zhang, Jinfeng; Hao, Yue

2018-05-01

We demonstrate a GaN growth method using microrod sidewall epitaxial lateral overgrowth (MSELO) on a close-packed microrod template by a nonlithographic technique. The density and distribution of threading dislocations were determined by the density and distribution of microrods and the nucleation model. MSELO exhibited two different nucleation models determined by the direction and degree of substrate misorientation and the sidewall curvature: one-sidewall and three-sidewall nucleation, predicting the dislocation density values. As a result, the threading dislocation density was markedly decreased from 2 × 109 to 5 × 107 cm‑2 with a small coalescence thickness of ∼2 µm for the close-packed 3000 nm microrod sample.

A New Framework for Cumulus Parametrization - A CPT in action

NASA Astrophysics Data System (ADS)

Jakob, C.; Peters, K.; Protat, A.; Kumar, V.

2016-12-01

The representation of convection in climate model remains a major Achilles Heel in our pursuit of better predictions of global and regional climate. The basic principle underpinning the parametrisation of tropical convection in global weather and climate models is that there exist discernible interactions between the resolved model scale and the parametrised cumulus scale. Furthermore, there must be at least some predictive power in the larger scales for the statistical behaviour on small scales for us to be able to formally close the parametrised equations. The presentation will discuss a new framework for cumulus parametrisation based on the idea of separating the prediction of cloud area from that of velocity. This idea is put into practice by combining an existing multi-scale stochastic cloud model with observations to arrive at the prediction of the area fraction for deep precipitating convection. Using mid-tropospheric humidity and vertical motion as predictors, the model is shown to reproduce the observed behaviour of both mean and variability of deep convective area fraction well. The framework allows for the inclusion of convective organisation and can - in principle - be made resolution-aware or resolution-independent. When combined with simple assumptions about cloud-base vertical motion the model can be used as a closure assumption in any existing cumulus parametrisation. Results of applying this idea in the the ECHAM model indicate significant improvements in the simulation of tropical variability, including but not limited to the MJO. This presentation will highlight how the close collaboration of the observational, theoretical and model development community in the spirit of the climate process teams can lead to significant progress in long-standing issues in climate modelling while preserving the freedom of individual groups in pursuing their specific implementation of an agreed framework.

An analytical study of aircraft lateral-directional handling qualities using pilot models

NASA Technical Reports Server (NTRS)

Adams, J. J.; Moore, F. L.

1976-01-01

A procedure for predicting lateral-directional pilot ratings on the basis of the characteristics of the pilot model and the closed-loop system characteristics is demonstrated. A correlation is shown to exist between experimentally obtained pilot ratings and the computed pilot ratings.

PHYSIOLOGICALLY BASED PHARMACOKINEITC (PBPK) MODELING OF METABOLIC INHIBITION FOR INTERACTION BETWEEN TRICHLOROETHYLENE AND CHLOROFORM

EPA Science Inventory

Trichloroethylene (TCE) and chloroform (CHCl3) are two of the most common environmental contaminants found in water. PBPK models have been increasingly used to predict target dose in internal tissues from available environmental exposure concentrations. A closed inhalation (or g...

Fundamental Algorithms of the Goddard Battery Model

NASA Technical Reports Server (NTRS)

Jagielski, J. M.

1985-01-01

The Goddard Space Flight Center (GSFC) is currently producing a computer model to predict Nickel Cadmium (NiCd) performance in a Low Earth Orbit (LEO) cycling regime. The model proper is currently still in development, but the inherent, fundamental algorithms (or methodologies) of the model are defined. At present, the model is closely dependent on empirical data and the data base currently used is of questionable accuracy. Even so, very good correlations have been determined between model predictions and actual cycling data. A more accurate and encompassing data base has been generated to serve dual functions: show the limitations of the current data base, and be inbred in the model properly for more accurate predictions. The fundamental algorithms of the model, and the present data base and its limitations, are described and a brief preliminary analysis of the new data base and its verification of the model's methodology are presented.

Preliminary results of Physiological plant growth modelling for human life support in space

NASA Astrophysics Data System (ADS)

Sasidharan L, Swathy; Dussap, Claude-Gilles; Hezard, Pauline

2012-07-01

Human life support is fundamental and crucial in any kind of space explorations. MELiSSA project of European Space Agency aims at developing a closed, artificial ecological life support system involving human, plants and micro organisms. Consuming carbon dioxide and water from the life support system, plants grow in one of the chambers and convert it into food and oxygen along with potable water. The environmental conditions, nutrient availability and its consumption of plants should be studied and necessarily modeled to predict the amount of food, oxygen and water with respect to the environmental changes and limitations. The reliability of a completely closed system mainly depends on the control laws and strategies used. An efficient control can occur, only if the system to control is itself well known, described and ideally if the responses of the system to environmental changes are predictable. In this aspect, the general structure of plant growth model has been designed together with physiological modelling.The physiological model consists of metabolic models of leaves, stem and roots, of which concern specific metabolisms of the associated plant parts. On the basis of the carbon source transport (eg. sucrose) through stem, the metabolic models (leaf and root) can be interconnected to each other and finally coupled to obtain the entire plant model. For the first step, leaf metabolic model network was built using stoichiometric, mass and energy balanced metabolic equations under steady state approach considering all necessary plant pathways for growth and maintenance of leaves. As the experimental data for lettuce plants grown in closed and controlled environmental chambers were available, the leaf metabolic model has been established for lettuce leaves. The constructed metabolic network is analyzed using known stoichiometric metabolic technique called metabolic flux analysis (MFA). Though, the leaf metabolic model alone is not sufficient to achieve the physiological plant model, in the case of lettuce (since the leaf metabolic model predominates), the developed model was verified with the carbon consumption of plant, as input. The model predicts the biomass production (as output) with respect to the quantum of light absorbed by the plant. The obtained result was found satisfying for the first initiation in the physiological plant modelling.

Analysis of spatial correlation in predictive models of forest variables that use LiDAR auxiliary information

Treesearch

F. Mauro; Vicente J. Monleon; H. Temesgen; L.A. Ruiz

2017-01-01

Accounting for spatial correlation of LiDAR model errors can improve the precision of model-based estimators. To estimate spatial correlation, sample designs that provide close observations are needed, but their implementation might be prohibitively expensive. To quantify the gains obtained by accounting for the spatial correlation of model errors, we examined (

Comparative Reannotation of 21 Aspergillus Genomes

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

Salamov, Asaf; Riley, Robert; Kuo, Alan

2013-03-08

We used comparative gene modeling to reannotate 21 Aspergillus genomes. Initial automatic annotation of individual genomes may contain some errors of different nature, e.g. missing genes, incorrect exon-intron structures, 'chimeras', which fuse 2 or more real genes or alternatively splitting some real genes into 2 or more models. The main premise behind the comparative modeling approach is that for closely related genomes most orthologous families have the same conserved gene structure. The algorithm maps all gene models predicted in each individual Aspergillus genome to the other genomes and, for each locus, selects from potentially many competing models, the one whichmore » most closely resembles the orthologous genes from other genomes. This procedure is iterated until no further change in gene models is observed. For Aspergillus genomes we predicted in total 4503 new gene models ( ~;;2percent per genome), supported by comparative analysis, additionally correcting ~;;18percent of old gene models. This resulted in a total of 4065 more genes with annotated PFAM domains (~;;3percent increase per genome). Analysis of a few genomes with EST/transcriptomics data shows that the new annotation sets also have a higher number of EST-supported splice sites at exon-intron boundaries.« less

Modeling to Predict Escherichia coli at Presque Isle Beach 2, City of Erie, Erie County, Pennsylvania

USGS Publications Warehouse

Zimmerman, Tammy M.

2008-01-01

The Lake Erie beaches in Pennsylvania are a valuable recreational resource for Erie County. Concentrations of Escherichia coli (E. coli) at monitored beaches in Presque Isle State Park in Erie, Pa., occasionally exceed the single-sample bathing-water standard of 235 colonies per 100 milliliters resulting in potentially unsafe swimming conditions and prompting beach managers to post public advisories or to close beaches to recreation. To supplement the current method for assessing recreational water quality (E. coli concentrations from the previous day), a predictive regression model for E. coli concentrations at Presque Isle Beach 2 was developed from data collected during the 2004 and 2005 recreational seasons. Model output included predicted E. coli concentrations and exceedance probabilities--the probability that E. coli concentrations would exceed the standard. For this study, E. coli concentrations and other water-quality and environmental data were collected during the 2006 recreational season at Presque Isle Beach 2. The data from 2006, an independent year, were used to test (validate) the 2004-2005 predictive regression model and compare the model performance to the current method. Using 2006 data, the 2004-2005 model yielded more correct responses and better predicted exceedances of the standard than the use of E. coli concentrations from the previous day. The differences were not pronounced, however, and more data are needed. For example, the model correctly predicted exceedances of the standard 11 percent of the time (1 out of 9 exceedances that occurred in 2006) whereas using the E. coli concentrations from the previous day did not result in any correctly predicted exceedances. After validation, new models were developed by adding the 2006 data to the 2004-2005 dataset and by analyzing the data in 2- and 3-year combinations. Results showed that excluding the 2004 data (using 2005 and 2006 data only) yielded the best model. Explanatory variables in the 2005-2006 model were log10 turbidity, bird count, and wave height. The 2005-2006 model correctly predicted when the standard would not be exceeded (specificity) with a response of 95.2 percent (178 out of 187 nonexceedances) and correctly predicted when the standard would be exceeded (sensitivity) with a response of 64.3 percent (9 out of 14 exceedances). In all cases, the results from predictive modeling produced higher percentages of correct predictions than using E. coli concentrations from the previous day. Additional data collected each year can be used to test and possibly improve the model. The results of this study will aid beach managers in more rapidly determining when waters are not safe for recreational use and, subsequently, when to close a beach or post an advisory.

Analysis of Highly-Resolved Simulations of 2-D Humps Toward Improvement of Second-Moment Closures

NASA Technical Reports Server (NTRS)

Jeyapaul, Elbert; Rumsey Christopher

2013-01-01

Fully resolved simulation data of flow separation over 2-D humps has been used to analyze the modeling terms in second-moment closures of the Reynolds-averaged Navier- Stokes equations. Existing models for the pressure-strain and dissipation terms have been analyzed using a priori calculations. All pressure-strain models are incorrect in the high-strain region near separation, although a better match is observed downstream, well into the separated-flow region. Near-wall inhomogeneity causes pressure-strain models to predict incorrect signs for the normal components close to the wall. In a posteriori computations, full Reynolds stress and explicit algebraic Reynolds stress models predict the separation point with varying degrees of success. However, as with one- and two-equation models, the separation bubble size is invariably over-predicted.

Predicting heavy metals' adsorption edges and adsorption isotherms on MnO2 with the parameters determined from Langmuir kinetics.

PubMed

Hu, Qinghai; Xiao, Zhongjin; Xiong, Xinmei; Zhou, Gongming; Guan, Xiaohong

2015-01-01

Although surface complexation models have been widely used to describe the adsorption of heavy metals, few studies have verified the feasibility of modeling the adsorption kinetics, edge, and isotherm data with one pH-independent parameter. A close inspection of the derivation process of Langmuir isotherm revealed that the equilibrium constant derived from the Langmuir kinetic model, KS-kinetic, is theoretically equivalent to the adsorption constant in Langmuir isotherm, KS-Langmuir. The modified Langmuir kinetic model (MLK model) and modified Langmuir isotherm model (MLI model) incorporating pH factor were developed. The MLK model was employed to simulate the adsorption kinetics of Cu(II), Co(II), Cd(II), Zn(II) and Ni(II) on MnO2 at pH3.2 or 3.3 to get the values of KS-kinetic. The adsorption edges of heavy metals could be modeled with the modified metal partitioning model (MMP model), and the values of KS-Langmuir were obtained. The values of KS-kinetic and KS-Langmuir are very close to each other, validating that the constants obtained by these two methods are basically the same. The MMP model with KS-kinetic constants could predict the adsorption edges of heavy metals on MnO2 very well at different adsorbent/adsorbate concentrations. Moreover, the adsorption isotherms of heavy metals on MnO2 at various pH levels could be predicted reasonably well by the MLI model with the KS-kinetic constants. Copyright © 2014. Published by Elsevier B.V.

78 FR 41940 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-12

...: Models to predict treatment outcomes for Intellectual and Developmental Disabilities. Date: July 30... Domestic Assistance Program Nos. 93.306, Comparative Medicine; 93.333, Clinical Research, 93.306, 93.333...

Optimizing the learning rate for adaptive estimation of neural encoding models

PubMed Central

2018-01-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel analytical approach to predictably achieve a desired level of error and convergence time in adaptive learning, with application to closed-loop neurotechnologies and other signal processing domains. PMID:29813069

Optimizing the learning rate for adaptive estimation of neural encoding models.

PubMed

Hsieh, Han-Lin; Shanechi, Maryam M

2018-05-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel analytical approach to predictably achieve a desired level of error and convergence time in adaptive learning, with application to closed-loop neurotechnologies and other signal processing domains.

Distributed model predictive control for constrained nonlinear systems with decoupled local dynamics.

PubMed

Zhao, Meng; Ding, Baocang

2015-03-01

This paper considers the distributed model predictive control (MPC) of nonlinear large-scale systems with dynamically decoupled subsystems. According to the coupled state in the overall cost function of centralized MPC, the neighbors are confirmed and fixed for each subsystem, and the overall objective function is disassembled into each local optimization. In order to guarantee the closed-loop stability of distributed MPC algorithm, the overall compatibility constraint for centralized MPC algorithm is decomposed into each local controller. The communication between each subsystem and its neighbors is relatively low, only the current states before optimization and the optimized input variables after optimization are being transferred. For each local controller, the quasi-infinite horizon MPC algorithm is adopted, and the global closed-loop system is proven to be exponentially stable. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Radiation Hardened Electronics for Space Environments (RHESE)

NASA Technical Reports Server (NTRS)

Keys, Andrew S.; Adams, James H.; Frazier, Donald O.; Patrick, Marshall C.; Watson, Michael D.; Johnson, Michael A.; Cressler, John D.; Kolawa, Elizabeth A.

2007-01-01

Radiation Environmental Modeling is crucial to proper predictive modeling and electronic response to the radiation environment. When compared to on-orbit data, CREME96 has been shown to be inaccurate in predicting the radiation environment. The NEDD bases much of its radiation environment data on CREME96 output. Close coordination and partnership with DoD radiation-hardened efforts will result in leveraged - not duplicated or independently developed - technology capabilities of: a) Radiation-hardened, reconfigurable FPGA-based electronics; and b) High Performance Processors (NOT duplication or independent development).

Optimal foraging on the roof of the world: Himalayan langurs and the classical prey model

PubMed Central

Sayers, Ken; Norconk, Marilyn A.; Conklin-Brittain, Nancy L.

2009-01-01

Optimal foraging theory has only been sporadically applied to nonhuman primates. The classical prey model, modified for patch choice, predicts a sliding “profitability threshold” for dropping patch types from the diet, preference for profitable foods, dietary niche breadth reduction as encounter rates increase, and that exploitation of a patch type is unrelated to its own abundance. We present results from a one-year study testing these predictions with Himalayan langurs (Semnopithecus entellus) at Langtang National Park, Nepal. Behavioral data included continuous recording of feeding bouts and between-patch travel times. Encounter rates were estimated for 55 food types, which were analyzed for crude protein, lipid, free simple sugar, and fibers. Patch types were entered into the prey model algorithm for eight seasonal time periods and differing age-sex classes and nutritional currencies. Although the model consistently underestimated diet breadth, the majority of non-predicted patch types represented rare foods. Profitability was positively related to annual/seasonal dietary contribution by organic matter estimates, while time estimates provided weaker relationships. Patch types utilized did not decrease with increasing encounter rates involving profitable foods, although low-ranking foods available year-round were taken predominantly when high-ranking foods were scarce. High-ranking foods were taken in close relation to encounter rates, while low-ranking foods were not. The utilization of an energetic currency generally resulted in closest conformation to model predictions, and it performed best when assumptions were most closely approximated. These results suggest that even simple models from foraging theory can provide a useful framework for the study of primate feeding behavior. PMID:19844998

Feedback and Sentence Learning.

ERIC Educational Resources Information Center

Guthrie, John T.

The theoretical functions of external feedback in SR and closed loop models of verbal learning are presented. Contradictory predictions from the models are tested with a three by three factorial experiment including three types of feedback and three amounts of rehearsal. There were 90 adult students run individually and they were required to learn…

Prediction models for transfer of arsenic from soil to corn grain (Zea mays L.).

PubMed

Yang, Hua; Li, Zhaojun; Long, Jian; Liang, Yongchao; Xue, Jianming; Davis, Murray; He, Wenxiang

2016-04-01

In this study, the transfer of arsenic (As) from soil to corn grain was investigated in 18 soils collected from throughout China. The soils were treated with three concentrations of As and the transfer characteristics were investigated in the corn grain cultivar Zhengdan 958 in a greenhouse experiment. Through stepwise multiple-linear regression analysis, prediction models were developed combining the As bioconcentration factor (BCF) of Zhengdan 958 and soil pH, organic matter (OM) content, and cation exchange capacity (CEC). The possibility of applying the Zhengdan 958 model to other cultivars was tested through a cross-cultivar extrapolation approach. The results showed that the As concentration in corn grain was positively correlated with soil pH. When the prediction model was applied to non-model cultivars, the ratio ranges between the predicted and measured BCF values were within a twofold interval between predicted and measured values. The ratios were close to a 1:1 relationship between predicted and measured values. It was also found that the prediction model (Log [BCF]=0.064 pH-2.297) could effectively reduce the measured BCF variability for all non-model corn cultivars. The novel model is firstly developed for As concentration in crop grain from soil, which will be very useful for understanding the As risk in soil environment.

Predicting Low Accrual in the National Cancer Institute’s Cooperative Group Clinical Trials

PubMed Central

Bennette, Caroline S.; Ramsey, Scott D.; McDermott, Cara L.; Carlson, Josh J.; Basu, Anirban; Veenstra, David L.

2016-01-01

Background: The extent to which trial-level factors differentially influence accrual to trials has not been comprehensively studied. Our objective was to evaluate the empirical relationship and predictive properties of putative risk factors for low accrual in the National Cancer Institute’s (NCI’s) Cooperative Group Program, now the National Clinical Trials Network (NCTN). Methods: Data from 787 phase II/III adult NCTN-sponsored trials launched between 2000 and 2011 were used to develop a logistic regression model to predict low accrual, defined as trials that closed with or were accruing at less than 50% of target; 46 trials opened between 2012 and 2013 were used for prospective validation. Candidate predictors were identified from a literature review and expert interviews; final predictors were selected using stepwise regression. Model performance was evaluated by calibration and discrimination via the area under the curve (AUC). All statistical tests were two-sided. Results: Eighteen percent (n = 145) of NCTN-sponsored trials closed with low accrual or were accruing at less than 50% of target three years or more after initiation. A multivariable model of twelve trial-level risk factors had good calibration and discrimination for predicting trials with low accrual (AUC in trials launched 2000–2011 = 0.739, 95% confidence interval [CI] = 0.696 to 0.783]; 2012–2013: AUC = 0.732, 95% CI = 0.547 to 0.917). Results were robust to different definitions of low accrual and predictor selection strategies. Conclusions: We identified multiple characteristics of NCTN-sponsored trials associated with low accrual, several of which have not been previously empirically described, and developed a prediction model that can provide a useful estimate of accrual risk based on these factors. Future work should assess the role of such prediction tools in trial design and prioritization decisions. PMID:26714555

Tropical cyclone prediction skills - MJO and ENSO dependence in S2S data sets

NASA Astrophysics Data System (ADS)

Lee, C. Y.; Camargo, S.; Vitart, F.; Sobel, A. H.; Tippett, M.

2017-12-01

The El Niño-Southern Oscillation (ENSO) and the Madden-Julian Oscillation (MJO) are two important climate controls on tropical cyclone (TC) activity. The seasonal prediction skill of dynamical models is determined in large part by their accurate representations of the ENSO-TC relationship. Regarding intraseasonal TC variability, observations suggest MJO to be the primary control. Given the ongoing effort to develop dynamical seasonal-to-subseasonal (S2S) TC predictions, it is important to examine whether the global models, running on S2S timescales, are able to reproduce these known ENSO-TC and MJO-TC relationships, and how this ability affects forecasting skill. Results from the S2S project (from F. Vitart) suggest that global models have skill in predicting MJO phase with up to two weeks of lead time (four weeks for ECMWF). Meanwhile, our results show that, qualitatively speaking, the MJO-TC relationship in storm genesis is reasonably captured, with some models (e.g., ECMWF, BoM, NCEP, MetFr) performing better than the others. However, we also find that model skill in predicting basin-wide genesis and accumulated cyclone energy (ACE) are mainly due to the models' ability to capture the climatological seasonality. Removing the seasonality significantly reduces the models' skill; even the best model (ECMWF) in the most reliable basin (western north Pacific and Atlantic) has very little skill (close to 0.1 in Brier skill score for genesis and close to 0 in rank probability skill score for ACE). This brings up the question: do any factors contribute to intraseasonal TC prediction skill other than seasonality? Is the low skill, after removing the seasonality, due to poor MJO and ENSO simulations, or to poor representation of other ENSO-TC or MJO-TC relationships, such as ENSO's impact on the storm tracks? We will quantitatively discuss the dependence of the TC prediction skill on ENSO and MJO, focusing on Western North Pacific and Atlantic, where we have sufficient sample sizes, and the S2S TC predictions are relatively more skillful. Various skill scores will be applied to genesis and ACE, with subsets of data binned based on ENSO and MJO status. We will also look at MJO and ENSO's impact on TC tracks through cluster analysis, and analyze model skill in each cluster.

The role of creep in the time-dependent resistance of Ohmic gold contacts in radio frequency microelectromechanical system devices

NASA Astrophysics Data System (ADS)

Rezvanian, O.; Brown, C.; Zikry, M. A.; Kingon, A. I.; Krim, J.; Irving, D. L.; Brenner, D. W.

2008-07-01

It is shown that measured and calculated time-dependent electrical resistances of closed gold Ohmic switches in radio frequency microelectromechanical system (rf-MEMS) devices are well described by a power law that can be derived from a single asperity creep model. The analysis reveals that the exponent and prefactor in the power law arise, respectively, from the coefficient relating creep rate to applied stress and the initial surface roughness. The analysis also shows that resistance plateaus are not, in fact, limiting resistances but rather result from the small coefficient in the power law. The model predicts that it will take a longer time for the contact resistance to attain a power law relation with each successive closing of the switch due to asperity blunting. Analysis of the first few seconds of the measured resistance for three successive openings and closings of one of the MEMS devices supports this prediction. This work thus provides guidance toward the rational design of Ohmic contacts with enhanced reliabilities by better defining variables that can be controlled through material selection, interface processing, and switch operation.

Testing an algebraic model of self-reflexion.

PubMed

Grice, James W; McDaniel, Brenda L; Thompsen, Dana

2005-06-01

Self-reflexion is the conscious process of taking the position of an observer in relation to one's own thoughts, feelings, and experiences. Building on the work of Lefebvre, Lefebvre, and Adams-Webber, we used a formal algebraic model of self-reflexion to derive several predictions regarding the frequencies with which individuals would rate themselves and others positively on bipolar scales anchored by adjective terms. The current results from 108 participants (41 men, 67 women; M age= 20.2 yr.) confirmed two predictions derived from the model. Three other predictions, however, were not supported even though the observed frequencies were close to the predicted values. Although not as promising as results reported by Lefebvre, et al., these mixed findings were interpreted as encouraging support for the validity of Lefebvre's algebraic model of self-reflexion. Differences between the current methods and those from previous investigations were also examined, and methodological implications for further studies were discussed.

A simple model for indentation creep

NASA Astrophysics Data System (ADS)

Ginder, Ryan S.; Nix, William D.; Pharr, George M.

2018-03-01

A simple model for indentation creep is developed that allows one to directly convert creep parameters measured in indentation tests to those observed in uniaxial tests through simple closed-form relationships. The model is based on the expansion of a spherical cavity in a power law creeping material modified to account for indentation loading in a manner similar to that developed by Johnson for elastic-plastic indentation (Johnson, 1970). Although only approximate in nature, the simple mathematical form of the new model makes it useful for general estimation purposes or in the development of other deformation models in which a simple closed-form expression for the indentation creep rate is desirable. Comparison to a more rigorous analysis which uses finite element simulation for numerical evaluation shows that the new model predicts uniaxial creep rates within a factor of 2.5, and usually much better than this, for materials creeping with stress exponents in the range 1 ≤ n ≤ 7. The predictive capabilities of the model are evaluated by comparing it to the more rigorous analysis and several sets of experimental data in which both the indentation and uniaxial creep behavior have been measured independently.

ℓ(p)-Norm multikernel learning approach for stock market price forecasting.

PubMed

Shao, Xigao; Wu, Kun; Liao, Bifeng

2012-01-01

Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ(1)-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ(p)-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ(1)-norm multiple support vector regression model.

Multiaxial Temperature- and Time-Dependent Failure Model

NASA Technical Reports Server (NTRS)

Richardson, David; McLennan, Michael; Anderson, Gregory; Macon, David; Batista-Rodriquez, Alicia

2003-01-01

A temperature- and time-dependent mathematical model predicts the conditions for failure of a material subjected to multiaxial stress. The model was initially applied to a filled epoxy below its glass-transition temperature, and is expected to be applicable to other materials, at least below their glass-transition temperatures. The model is justified simply by the fact that it closely approximates the experimentally observed failure behavior of this material: The multiaxiality of the model has been confirmed (see figure) and the model has been shown to be applicable at temperatures from -20 to 115 F (-29 to 46 C) and to predict tensile failures of constant-load and constant-load-rate specimens with failure times ranging from minutes to months..

A high-resolution model of the planetary boundary layer - Sensitivity tests and comparisons with SESAME-79 data

NASA Technical Reports Server (NTRS)

Zhang, D.; Anthes, R. A.

1982-01-01

A one-dimensional, planetary boundary layer (PBL) model is presented and verified using April 10, 1979 SESAME data. The model contains two modules to account for two different regimes of turbulent mixing. Separate parameterizations are made for stable and unstable conditions, with a predictive slab model for surface temperature. Atmospheric variables in the surface layer are calculated with a prognostic model, with moisture included in the coupled surface/PBL modeling. Sensitivity tests are performed for factors such as moisture availability, albedo, surface roughness, and thermal capacity, and a 24 hr simulation is summarized for day and night conditions. The comparison with the SESAME data comprises three hour intervals, using a time-dependent geostrophic wind. Close correlations were found with daytime conditions, but not in nighttime thermal structure, while the turbulence was faithfully predicted. Both geostrophic flow and surface characteristics were shown to have significant effects on the model predictions

Evaluating Nextgen Closely Spaced Parallel Operations Concepts with Validated Human Performance Models: Flight Deck Guidelines

NASA Technical Reports Server (NTRS)

Hooey, Becky Lee; Gore, Brian Francis; Mahlstedt, Eric; Foyle, David C.

2013-01-01

The objectives of the current research were to develop valid human performance models (HPMs) of approach and land operations; use these models to evaluate the impact of NextGen Closely Spaced Parallel Operations (CSPO) on pilot performance; and draw conclusions regarding flight deck display design and pilot-ATC roles and responsibilities for NextGen CSPO concepts. This document presents guidelines and implications for flight deck display designs and candidate roles and responsibilities. A companion document (Gore, Hooey, Mahlstedt, & Foyle, 2013) provides complete scenario descriptions and results including predictions of pilot workload, visual attention and time to detect off-nominal events.

Control of Systems With Slow Actuators Using Time Scale Separation

NASA Technical Reports Server (NTRS)

Stepanyan, Vehram; Nguyen, Nhan

2009-01-01

This paper addresses the problem of controlling a nonlinear plant with a slow actuator using singular perturbation method. For the known plant-actuator cascaded system the proposed scheme achieves tracking of a given reference model with considerably less control demand than would otherwise result when using conventional design techniques. This is the consequence of excluding the small parameter from the actuator dynamics via time scale separation. The resulting tracking error is within the order of this small parameter. For the unknown system the adaptive counterpart is developed based on the prediction model, which is driven towards the reference model by the control design. It is proven that the prediction model tracks the reference model with an error proportional to the small parameter, while the prediction error converges to zero. The resulting closed-loop system with all prediction models and adaptive laws remains stable. The benefits of the approach are demonstrated in simulation studies and compared to conventional control approaches.

Daddy's Little Girl Goes to College: An Investigation of Females' Perceived Closeness with Fathers and Later Risky Behaviors

ERIC Educational Resources Information Center

Rostad, Whitney L.; Silverman, Paul; McDonald, Molly K.

2014-01-01

Objective: The present study investigated the extent to which father-daughter relationships predicted risk-taking in a sample of female college students. Specifically, this study examined whether female adolescents' models of father psychological presence predicted substance use and sexual risk-taking, over and above impulsivity, depression,…

Prediction of winter vitamin D status and requirements in the UK population based on 25(OH) vitamin D half-life and dietary intake data.

PubMed

Schoenmakers, Inez; Gousias, Petros; Jones, Kerry S; Prentice, Ann

2016-11-01

On a population basis, there is a gradual decline in vitamin D status (plasma 25(OH)D) throughout winter. We developed a mathematical model to predict the population winter plasma 25(OH)D concentration longitudinally, using age-specific values for 25(OH)D expenditure (25(OH)D 3 t 1/2 ), cross-sectional plasma 25(OH)D concentration and vitamin D intake (VDI) data from older (70+ years; n=492) and younger adults (18-69 years; n=448) participating in the UK National Diet and Nutrition Survey. From this model, the population VDI required to maintain the mean plasma 25(OH)D at a set concentration can be derived. As expected, both predicted and measured population 25(OH)D (mean (95%CI)) progressively declined from September to March (from 51 (40-61) to 38 (36-41)nmol/L (predicted) vs 38 (27-48)nmol/L (measured) in older people and from 59 (54-65) to 34 (31-37)nmol/L (predicted) vs 37 (31-44)nmol/L (measured) in younger people). The predicted and measured mean values closely matched. The predicted VDIs required to maintain mean winter plasma 25(OH)D at 50nmol/L at the population level were 10 (0-20) to 11 (9-14) and 11 (6-16) to 13(11-16)μg/d for older and younger adults, respectively dependent on the month. In conclusion, a prediction model accounting for 25(OH)D 3 t 1/2 , VDI and scaling factor for the 25(OH)D response to VDI, closely predicts measured population winter values. Refinements of this model may include specific scaling factors accounting for the 25(OH)D response at different VDIs and as influenced by body composition and specific values for 25(OH)D 3 t 1/2 dependent on host factors such as kidney function. This model may help to reduce the need for longitudinal measurements. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Self-Esteem Maintenance in Family Dynamics.

ERIC Educational Resources Information Center

Tesser, Abraham

1980-01-01

In this study, a self-esteem maintenance model is introduced and is used to test predictions about sibling identification, sibling friction, and the closeness of father-son relationships as they relate to sibling performance. (Author/SS)

Comparison of closed loop model with flight test results

NASA Technical Reports Server (NTRS)

George, F. L.

1981-01-01

An analytic technique capable of predicting the landing characteristics of proposed aircraft configurations in the early stages of design was developed. In this analysis, a linear pilot-aircraft closed loop model was evaluated using experimental data generated with the NT-33 variable stability in-flight simulator. The pilot dynamics are modeled as inner and outer servo loop closures around aircraft pitch attitude, and altitude rate-of-change respectively. The landing flare maneuver is of particular interest as recent experience with military and other highly augmented vehicles shows this task to be relatively demanding, and potentially a critical design point. A unique feature of the pilot model is the incorporation of an internal model of the pilot's desired flight path for the flare maneuver.

Accounting for dominance to improve genomic evaluations of dairy cows for fertility and milk production traits.

PubMed

Aliloo, Hassan; Pryce, Jennie E; González-Recio, Oscar; Cocks, Benjamin G; Hayes, Ben J

2016-02-01

Dominance effects may contribute to genetic variation of complex traits in dairy cattle, especially for traits closely related to fitness such as fertility. However, traditional genetic evaluations generally ignore dominance effects and consider additive genetic effects only. Availability of dense single nucleotide polymorphisms (SNPs) panels provides the opportunity to investigate the role of dominance in quantitative variation of complex traits at both the SNP and animal levels. Including dominance effects in the genomic evaluation of animals could also help to increase the accuracy of prediction of future phenotypes. In this study, we estimated additive and dominance variance components for fertility and milk production traits of genotyped Holstein and Jersey cows in Australia. The predictive abilities of a model that accounts for additive effects only (additive), and a model that accounts for both additive and dominance effects (additive + dominance) were compared in a fivefold cross-validation. Estimates of the proportion of dominance variation relative to phenotypic variation that is captured by SNPs, for production traits, were up to 3.8 and 7.1 % in Holstein and Jersey cows, respectively, whereas, for fertility, they were equal to 1.2 % in Holstein and very close to zero in Jersey cows. We found that including dominance in the model was not consistently advantageous. Based on maximum likelihood ratio tests, the additive + dominance model fitted the data better than the additive model, for milk, fat and protein yields in both breeds. However, regarding the prediction of phenotypes assessed with fivefold cross-validation, including dominance effects in the model improved accuracy only for fat yield in Holstein cows. Regression coefficients of phenotypes on genetic values and mean squared errors of predictions showed that the predictive ability of the additive + dominance model was superior to that of the additive model for some of the traits. In both breeds, dominance effects were significant (P < 0.01) for all milk production traits but not for fertility. Accuracy of prediction of phenotypes was slightly increased by including dominance effects in the genomic evaluation model. Thus, it can help to better identify highly performing individuals and be useful for culling decisions.

System of closing relations of a two-fluid model for the HYDRA-IBRAE/LM/V1 code for calculation of sodium boiling in channels of power equipment

NASA Astrophysics Data System (ADS)

Usov, E. V.; Butov, A. A.; Dugarov, G. A.; Kudasov, I. G.; Lezhnin, S. I.; Mosunova, N. A.; Pribaturin, N. A.

2017-07-01

The system of equations from a two-fluid model is widely used in modeling thermohydraulic processes during accidents in nuclear reactors. The model includes conservation equations governing the balance of mass, momentum, and energy in each phase of the coolant. The features of heat and mass transfer, as well as of mechanical interaction between phases or with the channel wall, are described by a system of closing relations. Properly verified foreign and Russian codes with a comprehensive system of closing relations are available to predict processes in water coolant. As to the sodium coolant, only a few open publications on this subject are known. A complete system of closing relations used in the HYDRA-IBRAE/LM/V1 thermohydraulic code for calculation of sodium boiling in channels of power equipment is presented. The selection of these relations is corroborated on the basis of results of analysis of available publications with an account taken of the processes occurring in liquid sodium. A comparison with approaches outlined in foreign publications is presented. Particular attention has been given to the calculation of the sodium two-phase flow boiling. The flow regime map and a procedure for the calculation of interfacial friction and heat transfer in a sodium flow with account taken of high conductivity of sodium are described in sufficient detail. Correlations are presented for calculation of heat transfer for a single-phase sodium flow, sodium flow boiling, and sodium flow boiling crisis. A method is proposed for prediction of flow boiling crisis initiation.

Glass shell manufacturing in space

NASA Technical Reports Server (NTRS)

Downs, R. L.; Ebner, M. A.; Nolen, R. L., Jr.

1981-01-01

Highly-uniform, hollow glass spheres (shells), which are used for inertial confinement fusion targets, were formed from metal-organic gel powder feedstock in a vertical furnace. As a result of the rapid pyrolysis caused by the furnace, the gel is transformed to a shell in five distinct stages: (a) surface closure of the porous gel; (b) generation of a closed-cell foam structure in the gel; (c) spheridization of the gel and further expansion of the foam; (d) coalescence of the closed-cell foam to a single-void shell; and (e) fining of the glass shell. The heat transfer from the furnace to the falling gel particle was modeled to determine the effective heating rate of the gel. The model predicts the temperature history for a particle as a function of mass, dimensions, specific heat, and absorptance as well as furnace temperature profile and thermal conductivity of the furnace gas. A model was developed that predicts the gravity-induced degradation of shell concentricity in falling molten shells as a function of shell characteristics and time.

A Simplified Micromechanical Modeling Approach to Predict the Tensile Flow Curve Behavior of Dual-Phase Steels

NASA Astrophysics Data System (ADS)

Nanda, Tarun; Kumar, B. Ravi; Singh, Vishal

2017-11-01

Micromechanical modeling is used to predict material's tensile flow curve behavior based on microstructural characteristics. This research develops a simplified micromechanical modeling approach for predicting flow curve behavior of dual-phase steels. The existing literature reports on two broad approaches for determining tensile flow curve of these steels. The modeling approach developed in this work attempts to overcome specific limitations of the existing two approaches. This approach combines dislocation-based strain-hardening method with rule of mixtures. In the first step of modeling, `dislocation-based strain-hardening method' was employed to predict tensile behavior of individual phases of ferrite and martensite. In the second step, the individual flow curves were combined using `rule of mixtures,' to obtain the composite dual-phase flow behavior. To check accuracy of proposed model, four distinct dual-phase microstructures comprising of different ferrite grain size, martensite fraction, and carbon content in martensite were processed by annealing experiments. The true stress-strain curves for various microstructures were predicted with the newly developed micromechanical model. The results of micromechanical model matched closely with those of actual tensile tests. Thus, this micromechanical modeling approach can be used to predict and optimize the tensile flow behavior of dual-phase steels.

Per Aspera ad Astra: Through Complex Population Modeling to Predictive Theory.

PubMed

Topping, Christopher J; Alrøe, Hugo Fjelsted; Farrell, Katharine N; Grimm, Volker

2015-11-01

Population models in ecology are often not good at predictions, even if they are complex and seem to be realistic enough. The reason for this might be that Occam's razor, which is key for minimal models exploring ideas and concepts, has been too uncritically adopted for more realistic models of systems. This can tie models too closely to certain situations, thereby preventing them from predicting the response to new conditions. We therefore advocate a new kind of parsimony to improve the application of Occam's razor. This new parsimony balances two contrasting strategies for avoiding errors in modeling: avoiding inclusion of nonessential factors (false inclusions) and avoiding exclusion of sometimes-important factors (false exclusions). It involves a synthesis of traditional modeling and analysis, used to describe the essentials of mechanistic relationships, with elements that are included in a model because they have been reported to be or can arguably be assumed to be important under certain conditions. The resulting models should be able to reflect how the internal organization of populations change and thereby generate representations of the novel behavior necessary for complex predictions, including regime shifts.

In-situ intestinal rat perfusions for human Fabs prediction and BCS permeability class determination: Investigation of the single-pass vs. the Doluisio experimental approaches.

PubMed

Lozoya-Agullo, Isabel; Zur, Moran; Wolk, Omri; Beig, Avital; González-Álvarez, Isabel; González-Álvarez, Marta; Merino-Sanjuán, Matilde; Bermejo, Marival; Dahan, Arik

2015-03-01

Intestinal drug permeability has been recognized as a critical determinant of the fraction dose absorbed, with direct influence on bioavailability, bioequivalence and biowaiver. The purpose of this research was to compare intestinal permeability values obtained by two different intestinal rat perfusion methods: the single-pass intestinal perfusion (SPIP) model and the Doluisio (closed-loop) rat perfusion method. A list of 15 model drugs with different permeability characteristics (low, moderate, and high, as well as passively and actively absorbed) was constructed. We assessed the rat intestinal permeability of these 15 model drugs in both SPIP and the Doluisio methods, and evaluated the correlation between them. We then evaluated the ability of each of these methods to predict the fraction dose absorbed (Fabs) in humans, and to assign the correct BCS permeability class membership. Excellent correlation was obtained between the two experimental methods (r(2)=0.93). An excellent correlation was also shown between literature Fabs values and the predictions made by both rat perfusion techniques. Similar BCS permeability class membership was designated by literature data and by both SPIP and Doluisio methods for all compounds. In conclusion, the SPIP model and the Doluisio (closed-loop) rat perfusion method are both equally useful for obtaining intestinal permeability values that can be used for Fabs prediction and BCS classification. Copyright © 2015 Elsevier B.V. All rights reserved.

Long-range prediction of Indian summer monsoon rainfall using data mining and statistical approaches

NASA Astrophysics Data System (ADS)

H, Vathsala; Koolagudi, Shashidhar G.

2017-10-01

This paper presents a hybrid model to better predict Indian summer monsoon rainfall. The algorithm considers suitable techniques for processing dense datasets. The proposed three-step algorithm comprises closed itemset generation-based association rule mining for feature selection, cluster membership for dimensionality reduction, and simple logistic function for prediction. The application of predicting rainfall into flood, excess, normal, deficit, and drought based on 36 predictors consisting of land and ocean variables is presented. Results show good accuracy in the considered study period of 37years (1969-2005).

Statistical physics of interacting neural networks

NASA Astrophysics Data System (ADS)

Kinzel, Wolfgang; Metzler, Richard; Kanter, Ido

2001-12-01

Recent results on the statistical physics of time series generation and prediction are presented. A neural network is trained on quasi-periodic and chaotic sequences and overlaps to the sequence generator as well as the prediction errors are calculated numerically. For each network there exists a sequence for which it completely fails to make predictions. Two interacting networks show a transition to perfect synchronization. A pool of interacting networks shows good coordination in the minority game-a model of competition in a closed market. Finally, as a demonstration, a perceptron predicts bit sequences produced by human beings.

Modelling biological invasions: species traits, species interactions, and habitat heterogeneity.

PubMed

Cannas, Sergio A; Marco, Diana E; Páez, Sergio A

2003-05-01

In this paper we explore the integration of different factors to understand, predict and control ecological invasions, through a general cellular automaton model especially developed. The model includes life history traits of several species in a modular structure interacting multiple cellular automata. We performed simulations using field values corresponding to the exotic Gleditsia triacanthos and native co-dominant trees in a montane area. Presence of G. triacanthos juvenile bank was a determinant condition for invasion success. Main parameters influencing invasion velocity were mean seed dispersal distance and minimum reproductive age. Seed production had a small influence on the invasion velocity. Velocities predicted by the model agreed well with estimations from field data. Values of population density predicted matched field values closely. The modular structure of the model, the explicit interaction between the invader and the native species, and the simplicity of parameters and transition rules are novel features of the model.

Depositional sequence analysis and sedimentologic modeling for improved prediction of Pennsylvanian reservoirs

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

Watney, W.L.

1994-12-01

Reservoirs in the Lansing-Kansas City limestone result from complex interactions among paleotopography (deposition, concurrent structural deformation), sea level, and diagenesis. Analysis of reservoirs and surface and near-surface analogs has led to developing a {open_quotes}strandline grainstone model{close_quotes} in which relative sea-level stabilized during regressions, resulting in accumulation of multiple grainstone buildups along depositional strike. Resulting stratigraphy in these carbonate units are generally predictable correlating to inferred topographic elevation along the shelf. This model is a valuable predictive tool for (1) locating favorable reservoirs for exploration, and (2) anticipating internal properties of the reservoir for field development. Reservoirs in the Lansing-Kansas Citymore » limestones are developed in both oolitic and bioclastic grainstones, however, re-analysis of oomoldic reservoirs provides the greatest opportunity for developing bypassed oil. A new technique, the {open_quotes}Super{close_quotes} Pickett crossplot (formation resistivity vs. porosity) and its use in an integrated petrophysical characterization, has been developed to evaluate extractable oil remaining in these reservoirs. The manual method in combination with 3-D visualization and modeling can help to target production limiting heterogeneities in these complex reservoirs and moreover compute critical parameters for the field such as bulk volume water. Application of this technique indicates that from 6-9 million barrels of Lansing-Kansas City oil remain behind pipe in the Victory-Northeast Lemon Fields. Petroleum geologists are challenged to quantify inferred processes to aid in developing rationale geologically consistent models of sedimentation so that acceptable levels of prediction can be obtained.« less

The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set version 1

NASA Astrophysics Data System (ADS)

Day, Jonathan J.; Tietsche, Steffen; Collins, Mat; Goessling, Helge F.; Guemas, Virginie; Guillory, Anabelle; Hurlin, William J.; Ishii, Masayoshi; Keeley, Sarah P. E.; Matei, Daniela; Msadek, Rym; Sigmond, Michael; Tatebe, Hiroaki; Hawkins, Ed

2016-06-01

Recent decades have seen significant developments in climate prediction capabilities at seasonal-to-interannual timescales. However, until recently the potential of such systems to predict Arctic climate had rarely been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Interannual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to interannual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre), an assessment of Arctic sea ice extent and volume predictability estimates in these models, and an investigation into to what extent predictability is dependent on the initial state. The inclusion of additional models expands the range of sea ice volume and extent predictability estimates, demonstrating that there is model diversity in the potential to make seasonal-to-interannual timescale predictions. We also investigate whether sea ice forecasts started from extreme high and low sea ice initial states exhibit higher levels of potential predictability than forecasts started from close to the models' mean state, and find that the result depends on the metric. Although designed to address Arctic predictability, we describe the archived data here so that others can use this data set to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño-Southern Oscillation.

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. Copyright © 2016 Elsevier Inc. All rights reserved.

Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting: Preprint

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

Zhang, Jie; Hodge, Bri-Mathias; Lu, Siyuan

2015-08-05

Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reductionmore » in the amount of reserves that must be held to accommodate the uncertainty of solar power output. forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output.« less

A closed-form analytical model for predicting 3D boundary layer displacement thickness for the validation of viscous flow solvers

NASA Astrophysics Data System (ADS)

Kumar, V. R. Sanal; Sankar, Vigneshwaran; Chandrasekaran, Nichith; Saravanan, Vignesh; Natarajan, Vishnu; Padmanabhan, Sathyan; Sukumaran, Ajith; Mani, Sivabalan; Rameshkumar, Tharikaa; Nagaraju Doddi, Hema Sai; Vysaprasad, Krithika; Sharan, Sharad; Murugesh, Pavithra; Shankar, S. Ganesh; Nejaamtheen, Mohammed Niyasdeen; Baskaran, Roshan Vignesh; Rahman Mohamed Rafic, Sulthan Ariff; Harisrinivasan, Ukeshkumar; Srinivasan, Vivek

2018-02-01

A closed-form analytical model is developed for estimating the 3D boundary-layer-displacement thickness of an internal flow system at the Sanal flow choking condition for adiabatic flows obeying the physics of compressible viscous fluids. At this unique condition the boundary-layer blockage induced fluid-throat choking and the adiabatic wall-friction persuaded flow choking occur at a single sonic-fluid-throat location. The beauty and novelty of this model is that without missing the flow physics we could predict the exact boundary-layer blockage of both 2D and 3D cases at the sonic-fluid-throat from the known values of the inlet Mach number, the adiabatic index of the gas and the inlet port diameter of the internal flow system. We found that the 3D blockage factor is 47.33 % lower than the 2D blockage factor with air as the working fluid. We concluded that the exact prediction of the boundary-layer-displacement thickness at the sonic-fluid-throat provides a means to correctly pinpoint the causes of errors of the viscous flow solvers. The methodology presented herein with state-of-the-art will play pivotal roles in future physical and biological sciences for a credible verification, calibration and validation of various viscous flow solvers for high-fidelity 2D/3D numerical simulations of real-world flows. Furthermore, our closed-form analytical model will be useful for the solid and hybrid rocket designers for the grain-port-geometry optimization of new generation single-stage-to-orbit dual-thrust-motors with the highest promising propellant loading density within the given envelope without manifestation of the Sanal flow choking leading to possible shock waves causing catastrophic failures.

Application of Support Vector Machine to Forex Monitoring

NASA Astrophysics Data System (ADS)

Kamruzzaman, Joarder; Sarker, Ruhul A.

Previous studies have demonstrated superior performance of artificial neural network (ANN) based forex forecasting models over traditional regression models. This paper applies support vector machines to build a forecasting model from the historical data using six simple technical indicators and presents a comparison with an ANN based model trained by scaled conjugate gradient (SCG) learning algorithm. The models are evaluated and compared on the basis of five commonly used performance metrics that measure closeness of prediction as well as correctness in directional change. Forecasting results of six different currencies against Australian dollar reveal superior performance of SVM model using simple linear kernel over ANN-SCG model in terms of all the evaluation metrics. The effect of SVM parameter selection on prediction performance is also investigated and analyzed.

Numerical modeling of continuous flow microwave heating: a critical comparison of COMSOL and ANSYS.

PubMed

Salvi, D; Boldor, Dorin; Ortego, J; Aita, G M; Sabliov, C M

2010-01-01

Numerical models were developed to simulate temperature profiles in Newtonian fluids during continuous flow microwave heating by one way coupling electromagnetism, fluid flow, and heat transport in ANSYS 8.0 and COMSOL Multiphysics v3.4. Comparison of the results from the COMSOL model with the results from a pre-developed and validated ANSYS model ensured accuracy of the COMSOL model. Prediction of power Loss by both models was in close agreement (5-13% variation) and the predicted temperature profiles were similar. COMSOL provided a flexible model setup whereas ANSYS required coupling incompatible elements to transfer load between electromagnetic, fluid flow, and heat transport modules. Overall, both software packages provided the ability to solve multiphysics phenomena accurately.

Structure prediction of the second extracellular loop in G-protein-coupled receptors.

PubMed

Kmiecik, Sebastian; Jamroz, Michal; Kolinski, Michal

2014-06-03

G-protein-coupled receptors (GPCRs) play key roles in living organisms. Therefore, it is important to determine their functional structures. The second extracellular loop (ECL2) is a functionally important region of GPCRs, which poses significant challenge for computational structure prediction methods. In this work, we evaluated CABS, a well-established protein modeling tool for predicting ECL2 structure in 13 GPCRs. The ECL2s (with between 13 and 34 residues) are predicted in an environment of other extracellular loops being fully flexible and the transmembrane domain fixed in its x-ray conformation. The modeling procedure used theoretical predictions of ECL2 secondary structure and experimental constraints on disulfide bridges. Our approach yielded ensembles of low-energy conformers and the most populated conformers that contained models close to the available x-ray structures. The level of similarity between the predicted models and x-ray structures is comparable to that of other state-of-the-art computational methods. Our results extend other studies by including newly crystallized GPCRs. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Scoring annual earthquake predictions in China

NASA Astrophysics Data System (ADS)

Zhuang, Jiancang; Jiang, Changsheng

2012-02-01

The Annual Consultation Meeting on Earthquake Tendency in China is held by the China Earthquake Administration (CEA) in order to provide one-year earthquake predictions over most China. In these predictions, regions of concern are denoted together with the corresponding magnitude range of the largest earthquake expected during the next year. Evaluating the performance of these earthquake predictions is rather difficult, especially for regions that are of no concern, because they are made on arbitrary regions with flexible magnitude ranges. In the present study, the gambling score is used to evaluate the performance of these earthquake predictions. Based on a reference model, this scoring method rewards successful predictions and penalizes failures according to the risk (probability of being failure) that the predictors have taken. Using the Poisson model, which is spatially inhomogeneous and temporally stationary, with the Gutenberg-Richter law for earthquake magnitudes as the reference model, we evaluate the CEA predictions based on 1) a partial score for evaluating whether issuing the alarmed regions is based on information that differs from the reference model (knowledge of average seismicity level) and 2) a complete score that evaluates whether the overall performance of the prediction is better than the reference model. The predictions made by the Annual Consultation Meetings on Earthquake Tendency from 1990 to 2003 are found to include significant precursory information, but the overall performance is close to that of the reference model.

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

Leggett, Rich

The transition metal yttrium (Y, atomic number 39) is chemically similar to elements in the lanthanide family (atomic numbers 57-71, lanthanum through lutetium) and is always present with the lanthanides in rare earth ores. Yttrium and the lanthanide holmium are particularly close chemical and physical analogues and are referred to as geochemical twins because they typically show little fractionation in geological material. Extensive measurements on rocks, soils, and meteorites indicate that the Y/Ho mass concentration ratio rarely falls far from the “chondritic” or “solar system” ratio of ~26. Our paper presents a new biokinetic model for yttrium in adult humansmore » and examines whether yttrium and holmium may be biological as well as geochemical twins. Collected data on yttrium and holmium in plants and human tissues do not allow precise derivations of Y/Ho concentration ratios but with occasional exceptions yield ratios that are reasonably consistent with chondritic values. Predictions of the time-dependent behavior of yttrium in adult humans based on the yttrium model presented here closely approximate predictions of the behavior of holmium based on a previously developed model for holmium. We know that yttrium and holmium are close biological analogues, but the available comparative data are too limited and imprecise to reveal whether there are any significant differences in their biological behavior.« less

Towards seasonal Arctic shipping route predictions

NASA Astrophysics Data System (ADS)

Melia, N.; Haines, K.; Hawkins, E.; Day, J. J.

2017-08-01

The continuing decline in Arctic sea-ice will likely lead to increased human activity and opportunities for shipping in the region, suggesting that seasonal predictions of route openings will become ever more important. Here we present results from a set of ‘perfect model’ experiments to assess the predictability characteristics of the opening of Arctic sea routes. We find skilful predictions of the upcoming summer shipping season can be made from as early as January, although typically forecasts show lower skill before a May ‘predictability barrier’. We demonstrate that in forecasts started from January, predictions of route opening date are twice as uncertain as predicting the closing date and that the Arctic shipping season is becoming longer due to climate change, with later closing dates mostly responsible. We find that predictive skill is state dependent with predictions for high or low ice years exhibiting greater skill than medium ice years. Forecasting the fastest open water route through the Arctic is accurate to within 200 km when predicted from July, a six-fold increase in accuracy compared to forecasts initialised from the previous November, which are typically no better than climatology. Finally we find that initialisation of accurate summer sea-ice thickness information is crucial to obtain skilful forecasts, further motivating investment into sea-ice thickness observations, climate models, and assimilation systems.

An investigation of the information propagation and entropy transport aspects of Stirling machine numerical simulation

NASA Technical Reports Server (NTRS)

Goldberg, Louis F.

1992-01-01

Aspects of the information propagation modeling behavior of integral machine computer simulation programs are investigated in terms of a transmission line. In particular, the effects of pressure-linking and temporal integration algorithms on the amplitude ratio and phase angle predictions are compared against experimental and closed-form analytic data. It is concluded that the discretized, first order conservation balances may not be adequate for modeling information propagation effects at characteristic numbers less than about 24. An entropy transport equation suitable for generalized use in Stirling machine simulation is developed. The equation is evaluated by including it in a simulation of an incompressible oscillating flow apparatus designed to demonstrate the effect of flow oscillations on the enhancement of thermal diffusion. Numerical false diffusion is found to be a major factor inhibiting validation of the simulation predictions with experimental and closed-form analytic data. A generalized false diffusion correction algorithm is developed which allows the numerical results to match their analytic counterparts. Under these conditions, the simulation yields entropy predictions which satisfy Clausius' inequality.

Water quality management using statistical analysis and time-series prediction model

NASA Astrophysics Data System (ADS)

Parmar, Kulwinder Singh; Bhardwaj, Rashmi

2014-12-01

This paper deals with water quality management using statistical analysis and time-series prediction model. The monthly variation of water quality standards has been used to compare statistical mean, median, mode, standard deviation, kurtosis, skewness, coefficient of variation at Yamuna River. Model validated using R-squared, root mean square error, mean absolute percentage error, maximum absolute percentage error, mean absolute error, maximum absolute error, normalized Bayesian information criterion, Ljung-Box analysis, predicted value and confidence limits. Using auto regressive integrated moving average model, future water quality parameters values have been estimated. It is observed that predictive model is useful at 95 % confidence limits and curve is platykurtic for potential of hydrogen (pH), free ammonia, total Kjeldahl nitrogen, dissolved oxygen, water temperature (WT); leptokurtic for chemical oxygen demand, biochemical oxygen demand. Also, it is observed that predicted series is close to the original series which provides a perfect fit. All parameters except pH and WT cross the prescribed limits of the World Health Organization /United States Environmental Protection Agency, and thus water is not fit for drinking, agriculture and industrial use.

A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback

PubMed Central

2018-01-01

During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone. PMID:29342146

A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback.

PubMed

Buckley, Christopher L; Toyoizumi, Taro

2018-01-01

During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone.

Numerical modelling of closed-cell aluminium foam under dynamic loading

NASA Astrophysics Data System (ADS)

Hazell, Paul; Kader, M. A.; Islam, M. A.; Escobedo, J. P.; Saadatfar, M.

2015-06-01

Closed-cell aluminium foams are extensively used in aerospace and automobile industries. The understanding of their behaviour under impact loading conditions is extremely important since impact problems are directly related to design of these engineering structures. This research investigates the response of a closed-cell aluminium foam (CYMAT) subjected to dynamic loading using the finite element software ABAQUS/explicit. The aim of this research is to numerically investigate the material and structural properties of closed-cell aluminium foam under impact loading conditions with interest in shock propagation and its effects on cell wall deformation. A μ-CT based 3D foam geometry is developed to simulate the local cell collapse behaviours. A number of numerical techniques are applied for modelling the crush behaviour of aluminium foam to obtain the more accurate results. The simulation results are compared with experimental data. Comparison of the results shows a good correlation between the experimental results and numerical predictions.

Markov Chain Models for Stochastic Behavior in Resonance Overlap Regions

NASA Astrophysics Data System (ADS)

McCarthy, Morgan; Quillen, Alice

2018-01-01

We aim to predict lifetimes of particles in chaotic zoneswhere resonances overlap. A continuous-time Markov chain model isconstructed using mean motion resonance libration timescales toestimate transition times between resonances. The model is applied todiffusion in the co-rotation region of a planet. For particles begunat low eccentricity, the model is effective for early diffusion, butnot at later time when particles experience close encounters to the planet.

Modeling and closed-loop control of hypnosis by means of bispectral index (BIS) with isoflurane.

PubMed

Gentilini, A; Rossoni-Gerosa, M; Frei, C W; Wymann, R; Morari, M; Zbinden, A M; Schnider, T W

2001-08-01

A model-based closed-loop control system is presented to regulate hypnosis with the volatile anesthetic isoflurane. Hypnosis is assessed by means of the bispectral index (BIS), a processed parameter derived from the electroencephalogram. Isoflurane is administered through a closed-circuit respiratory system. The model for control was identified on a population of 20 healthy volunteers. It consists of three parts: a model for the respiratory system, a pharmacokinetic model and a pharmacodynamic model to predict BIS at the effect compartment. A cascaded internal model controller is employed. The master controller compares the actual BIS and the reference value set by the anesthesiologist and provides expired isoflurane concentration references to the slave controller. The slave controller maneuvers the fresh gas anesthetic concentration entering the respiratory system. The controller is designed to adapt to different respiratory conditions. Anti-windup measures protect against performance degradation in the event of saturation of the input signal. Fault detection schemes in the controller cope with BIS and expired concentration measurement artifacts. The results of clinical studies on humans are presented.

Explaining negative kin discrimination in a cooperative mammal society

PubMed Central

Cant, Michael A.; Sanderson, Jennifer L.; Gilchrist, Jason S.; Bell, Matthew B. V.; Hodge, Sarah J.; Johnstone, Rufus A.

2017-01-01

Kin selection theory predicts that, where kin discrimination is possible, animals should typically act more favorably toward closer genetic relatives and direct aggression toward less closely related individuals. Contrary to this prediction, we present data from an 18-y study of wild banded mongooses, Mungos mungo, showing that females that are more closely related to dominant individuals are specifically targeted for forcible eviction from the group, often suffering severe injury, and sometimes death, as a result. This pattern cannot be explained by inbreeding avoidance or as a response to more intense local competition among kin. Instead, we use game theory to show that such negative kin discrimination can be explained by selection for unrelated targets to invest more effort in resisting eviction. Consistent with our model, negative kin discrimination is restricted to eviction attempts of older females capable of resistance; dominants exhibit no kin discrimination when attempting to evict younger females, nor do they discriminate between more closely or less closely related young when carrying out infanticidal attacks on vulnerable infants who cannot defend themselves. We suggest that in contexts where recipients of selfish acts are capable of resistance, the usual prediction of positive kin discrimination can be reversed. Kin selection theory, as an explanation for social behavior, can benefit from much greater exploration of sequential social interactions. PMID:28439031

A comparison of multivariate and univariate time series approaches to modelling and forecasting emergency department demand in Western Australia.

PubMed

Aboagye-Sarfo, Patrick; Mai, Qun; Sanfilippo, Frank M; Preen, David B; Stewart, Louise M; Fatovich, Daniel M

2015-10-01

To develop multivariate vector-ARMA (VARMA) forecast models for predicting emergency department (ED) demand in Western Australia (WA) and compare them to the benchmark univariate autoregressive moving average (ARMA) and Winters' models. Seven-year monthly WA state-wide public hospital ED presentation data from 2006/07 to 2012/13 were modelled. Graphical and VARMA modelling methods were used for descriptive analysis and model fitting. The VARMA models were compared to the benchmark univariate ARMA and Winters' models to determine their accuracy to predict ED demand. The best models were evaluated by using error correction methods for accuracy. Descriptive analysis of all the dependent variables showed an increasing pattern of ED use with seasonal trends over time. The VARMA models provided a more precise and accurate forecast with smaller confidence intervals and better measures of accuracy in predicting ED demand in WA than the ARMA and Winters' method. VARMA models are a reliable forecasting method to predict ED demand for strategic planning and resource allocation. While the ARMA models are a closely competing alternative, they under-estimated future ED demand. Copyright © 2015 Elsevier Inc. All rights reserved.

ℓ p-Norm Multikernel Learning Approach for Stock Market Price Forecasting

PubMed Central

Shao, Xigao; Wu, Kun; Liao, Bifeng

2012-01-01

Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ 1-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ p-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ 1-norm multiple support vector regression model. PMID:23365561

Modeling polyvinyl chloride Plasma Modification by Neural Networks

NASA Astrophysics Data System (ADS)

Wang, Changquan

2018-03-01

Neural networks model were constructed to analyze the connection between dielectric barrier discharge parameters and surface properties of material. The experiment data were generated from polyvinyl chloride plasma modification by using uniform design. Discharge voltage, discharge gas gap and treatment time were as neural network input layer parameters. The measured values of contact angle were as the output layer parameters. A nonlinear mathematical model of the surface modification for polyvinyl chloride was developed based upon the neural networks. The optimum model parameters were obtained by the simulation evaluation and error analysis. The results of the optimal model show that the predicted value is very close to the actual test value. The prediction model obtained here are useful for discharge plasma surface modification analysis.

Initial and hourly headloss modelling on a tertiary nitrifying wastewater biofiltration plant.

PubMed

Bernier, Jean; Rocher, Vincent; Lessard, Paul

2016-01-01

The headloss prediction capability of a wastewater biofiltration model is evaluated on data from a full-scale tertiary nitrifying biofilter unit located in the Paris conurbation (Achères, France; 6,000,000 population equivalent). The model has been previously calibrated on nutrient conversion and TSS filtration observations. In this paper the mass of extracted biofilm during biofilter backwash and the headloss value at the start of an operation cycle are first calibrated on sludge production estimations and relative pressure measurements over the year 2009. The calibrated model is then used on two one-month periods in 2012 for which hourly headloss measurements were acquired. The observed trends are correctly predicted for 2009 but the model exhibits some heavy daily variation that is not found in measurements. Hourly predictions stay close to observations, although the model error rises slightly when the headloss does not vary much. The global model shows that both nutrient conversion and headloss build-up can be reasonably well predicted at the same time on a full-scale plant.

Data-driven modeling and predictive control for boiler-turbine unit using fuzzy clustering and subspace methods.

PubMed

Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y

2014-05-01

This paper develops a novel data-driven fuzzy modeling strategy and predictive controller for boiler-turbine unit using fuzzy clustering and subspace identification (SID) methods. To deal with the nonlinear behavior of boiler-turbine unit, fuzzy clustering is used to provide an appropriate division of the operation region and develop the structure of the fuzzy model. Then by combining the input data with the corresponding fuzzy membership functions, the SID method is extended to extract the local state-space model parameters. Owing to the advantages of the both methods, the resulting fuzzy model can represent the boiler-turbine unit very closely, and a fuzzy model predictive controller is designed based on this model. As an alternative approach, a direct data-driven fuzzy predictive control is also developed following the same clustering and subspace methods, where intermediate subspace matrices developed during the identification procedure are utilized directly as the predictor. Simulation results show the advantages and effectiveness of the proposed approach. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

An Open Singularity-Free Cosmological Model with Inflation

NASA Astrophysics Data System (ADS)

Karaca, Koray; Bayin, Selçuk

In the light of recent observations which point to an open universe (Ω0 < 1), we construct an open singularity-free cosmological model by reconsidering a model originally constructed for a closed universe. Our model starts from a nonsingular state called prematter, governed by an inflationary equation of state P = (γp - 1)ρ where γp (~= 10-3) is a small positive parameter representing the initial vacuum dominance of the universe. Unlike the closed models universe cannot be initially static hence, starts with an initial expansion rate represented by the initial value of the Hubble constant H(0). Therefore, our model is a two-parameter universe model (γp,H(0)). Comparing the predictions of this model for the present properties of the universe with the recent observational results, we argue that the model constructed in this work could be used as a realistic universe model.

Elongated Tetrakaidecahedron Micromechanics Model for Space Shuttle External Tank Foams

NASA Technical Reports Server (NTRS)

Sullivan, Roy M.; Ghosn, Louis J.; Lerch, Bradley A.; Baker, Eric H.

2009-01-01

The results of microstructural characterization studies and physical and mechanical testing of BX-265 and NCFI24-124 foams are reported. A micromechanics model developed previously by the authors is reviewed, and the resulting equations for the elastic constants, the relative density, and the strength of the foam in the principal material directions are presented. The micromechanics model is also used to derive equations to predict the effect of vacuum on the tensile strength and the strains induced by exposure to vacuum. Using a combination of microstructural dimensions and physical and mechanical measurements as input, the equations for the elastic constants and the relative density are applied and the remaining microstructural dimensions are predicted. The predicted microstructural dimensions are in close agreement with the average measured values for both BX-265 and NCFI24-124. With the microstructural dimensions, the model predicts the ratio of the strengths in the principal material directions for both foams. The model is also used to predict the Poisson s ratios, the vacuum-induced strains, and the effect of vacuum on the tensile strengths. However, the comparison of these predicted values with the measured values is not as favorable.

Experimental Evaluation of Balance Prediction Models for Sit-to-Stand Movement in the Sagittal Plane

PubMed Central

Pena Cabra, Oscar David; Watanabe, Takashi

2013-01-01

Evaluation of balance control ability would become important in the rehabilitation training. In this paper, in order to make clear usefulness and limitation of a traditional simple inverted pendulum model in balance prediction in sit-to-stand movements, the traditional simple model was compared to an inertia (rotational radius) variable inverted pendulum model including multiple-joint influence in the balance predictions. The predictions were tested upon experimentation with six healthy subjects. The evaluation showed that the multiple-joint influence model is more accurate in predicting balance under demanding sit-to-stand conditions. On the other hand, the evaluation also showed that the traditionally used simple inverted pendulum model is still reliable in predicting balance during sit-to-stand movement under non-demanding (normal) condition. Especially, the simple model was shown to be effective for sit-to-stand movements with low center of mass velocity at the seat-off. Moreover, almost all trajectories under the normal condition seemed to follow the same control strategy, in which the subjects used extra energy than the minimum one necessary for standing up. This suggests that the safety considerations come first than the energy efficiency considerations during a sit to stand, since the most energy efficient trajectory is close to the backward fall boundary. PMID:24187580

Prediction of frozen food properties during freezing using product composition.

PubMed

Boonsupthip, W; Heldman, D R

2007-06-01

Frozen water fraction (FWF), as a function of temperature, is an important parameter for use in the design of food freezing processes. An FWF-prediction model, based on concentrations and molecular weights of specific product components, has been developed. Published food composition data were used to determine the identity and composition of key components. The model proposed in this investigation had been verified using published experimental FWF data and initial freezing temperature data, and by comparison to outputs from previously published models. It was found that specific food components with significant influence on freezing temperature depression of food products included low molecular weight water-soluble compounds with molality of 50 micromol per 100 g food or higher. Based on an analysis of 200 high-moisture food products, nearly 45% of the experimental initial freezing temperature data were within an absolute difference (AD) of +/- 0.15 degrees C and standard error (SE) of +/- 0.65 degrees C when compared to values predicted by the proposed model. The predicted relationship between temperature and FWF for all analyzed food products provided close agreements with experimental data (+/- 0.06 SE). The proposed model provided similar prediction capability for high- and intermediate-moisture food products. In addition, the proposed model provided statistically better prediction of initial freezing temperature and FWF than previous published models.

Constrained off-line synthesis approach of model predictive control for networked control systems with network-induced delays.

PubMed

Tang, Xiaoming; Qu, Hongchun; Wang, Ping; Zhao, Meng

2015-03-01

This paper investigates the off-line synthesis approach of model predictive control (MPC) for a class of networked control systems (NCSs) with network-induced delays. A new augmented model which can be readily applied to time-varying control law, is proposed to describe the NCS where bounded deterministic network-induced delays may occur in both sensor to controller (S-A) and controller to actuator (C-A) links. Based on this augmented model, a sufficient condition of the closed-loop stability is derived by applying the Lyapunov method. The off-line synthesis approach of model predictive control is addressed using the stability results of the system, which explicitly considers the satisfaction of input and state constraints. Numerical example is given to illustrate the effectiveness of the proposed method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Microstructure-based hyperelastic models for closed-cell solids

PubMed Central

Wyatt, Hayley

2017-01-01

For cellular bodies involving large elastic deformations, mesoscopic continuum models that take into account the interplay between the geometry and the microstructural responses of the constituents are developed, analysed and compared with finite-element simulations of cellular structures with different architecture. For these models, constitutive restrictions for the physical plausibility of the material responses are established, and global descriptors such as nonlinear elastic and shear moduli and Poisson’s ratio are obtained from the material characteristics of the constituents. Numerical results show that these models capture well the mechanical responses of finite-element simulations for three-dimensional periodic structures of neo-Hookean material with closed cells under large tension. In particular, the mesoscopic models predict the macroscopic stiffening of the structure when the stiffness of the cell-core increases. PMID:28484340

Microstructure-based hyperelastic models for closed-cell solids.

PubMed

Mihai, L Angela; Wyatt, Hayley; Goriely, Alain

2017-04-01

For cellular bodies involving large elastic deformations, mesoscopic continuum models that take into account the interplay between the geometry and the microstructural responses of the constituents are developed, analysed and compared with finite-element simulations of cellular structures with different architecture. For these models, constitutive restrictions for the physical plausibility of the material responses are established, and global descriptors such as nonlinear elastic and shear moduli and Poisson's ratio are obtained from the material characteristics of the constituents. Numerical results show that these models capture well the mechanical responses of finite-element simulations for three-dimensional periodic structures of neo-Hookean material with closed cells under large tension. In particular, the mesoscopic models predict the macroscopic stiffening of the structure when the stiffness of the cell-core increases.

Microstructure-based hyperelastic models for closed-cell solids

NASA Astrophysics Data System (ADS)

Mihai, L. Angela; Wyatt, Hayley; Goriely, Alain

2017-04-01

For cellular bodies involving large elastic deformations, mesoscopic continuum models that take into account the interplay between the geometry and the microstructural responses of the constituents are developed, analysed and compared with finite-element simulations of cellular structures with different architecture. For these models, constitutive restrictions for the physical plausibility of the material responses are established, and global descriptors such as nonlinear elastic and shear moduli and Poisson's ratio are obtained from the material characteristics of the constituents. Numerical results show that these models capture well the mechanical responses of finite-element simulations for three-dimensional periodic structures of neo-Hookean material with closed cells under large tension. In particular, the mesoscopic models predict the macroscopic stiffening of the structure when the stiffness of the cell-core increases.

Random close packing in protein cores

NASA Astrophysics Data System (ADS)

Gaines, Jennifer C.; Smith, W. Wendell; Regan, Lynne; O'Hern, Corey S.

2016-03-01

Shortly after the determination of the first protein x-ray crystal structures, researchers analyzed their cores and reported packing fractions ϕ ≈0.75 , a value that is similar to close packing of equal-sized spheres. A limitation of these analyses was the use of extended atom models, rather than the more physically accurate explicit hydrogen model. The validity of the explicit hydrogen model was proved in our previous studies by its ability to predict the side chain dihedral angle distributions observed in proteins. In contrast, the extended atom model is not able to recapitulate the side chain dihedral angle distributions, and gives rise to large atomic clashes at side chain dihedral angle combinations that are highly probable in protein crystal structures. Here, we employ the explicit hydrogen model to calculate the packing fraction of the cores of over 200 high-resolution protein structures. We find that these protein cores have ϕ ≈0.56 , which is similar to results obtained from simulations of random packings of individual amino acids. This result provides a deeper understanding of the physical basis of protein structure that will enable predictions of the effects of amino acid mutations to protein cores and interfaces of known structure.

Random close packing in protein cores.

PubMed

Gaines, Jennifer C; Smith, W Wendell; Regan, Lynne; O'Hern, Corey S

2016-03-01

Shortly after the determination of the first protein x-ray crystal structures, researchers analyzed their cores and reported packing fractions ϕ ≈ 0.75, a value that is similar to close packing of equal-sized spheres. A limitation of these analyses was the use of extended atom models, rather than the more physically accurate explicit hydrogen model. The validity of the explicit hydrogen model was proved in our previous studies by its ability to predict the side chain dihedral angle distributions observed in proteins. In contrast, the extended atom model is not able to recapitulate the side chain dihedral angle distributions, and gives rise to large atomic clashes at side chain dihedral angle combinations that are highly probable in protein crystal structures. Here, we employ the explicit hydrogen model to calculate the packing fraction of the cores of over 200 high-resolution protein structures. We find that these protein cores have ϕ ≈ 0.56, which is similar to results obtained from simulations of random packings of individual amino acids. This result provides a deeper understanding of the physical basis of protein structure that will enable predictions of the effects of amino acid mutations to protein cores and interfaces of known structure.

Genetic and phylogenetic consequences of island biogeography.

PubMed

Johnson, K P; Adler, F R; Cherry, J L

2000-04-01

Island biogeography theory predicts that the number of species on an island should increase with island size and decrease with island distance to the mainland. These predictions are generally well supported in comparative and experimental studies. These ecological, equilibrium predictions arise as a result of colonization and extinction processes. Because colonization and extinction are also important processes in evolution, we develop methods to test evolutionary predictions of island biogeography. We derive a population genetic model of island biogeography that incorporates island colonization, migration of individuals from the mainland, and extinction of island populations. The model provides a means of estimating the rates of migration and extinction from population genetic data. This model predicts that within an island population the distribution of genetic divergences with respect to the mainland source population should be bimodal, with much of the divergence dating to the colonization event. Across islands, this model predicts that populations on large islands should be on average more genetically divergent from mainland source populations than those on small islands. Likewise, populations on distant islands should be more divergent than those on close islands. Published observations of a larger proportion of endemic species on large and distant islands support these predictions.

Improvement, Verification, and Refinement of Spatially-Explicit Exposure Models in Risk Assessment - FishRand Spatially-Explicit Bioaccumulation Model Demonstration

DTIC Science & Technology

2015-08-01

21  Figure 4. Data-based proportion of DDD , DDE and DDT in total DDx in fish and sediment by... DDD dichlorodiphenyldichloroethane DDE dichlorodiphenyldichloroethylene DDT dichlorodiphenyltrichloroethane DoD Department of Defense ERM... DDD ) at the other site. The spatially-explicit model consistently predicts tissue concentrations that closely match both the average and the

Assessment of Predictive Capabilities of L1 Orbiters using Realtime Solar Wind Data

NASA Astrophysics Data System (ADS)

Holmes, J.; Kasper, J. C.; Welling, D. T.

2017-12-01

Realtime measurements of solar wind conditions at L1 point allow us to predict geomagnetic activity at Earth up to an hour in advance. These predictions are quantified in the form of geomagnetic indices such as Kp and Ap, allowing for a concise, standardized prediction and measurement system. For years, the Space Weather Prediction Center used ACE realtime solar wind data to develop its one and four-hour Kp forecasts, but has in the past year switched to using DSCOVR data as its source. In this study, the performance of both orbiters in predicting Kp over the course of one month was assessed in an attempt to determine whether or not switching to DSCOVR data has resulted in improved forecasts. The period of study was chosen to encompass a time when the satellites were close to each other, and when moderate to high activity was observed. Kp predictions were made using the Geospace Model, part of the Space Weather Modeling Framework, to simulate conditions based on observed solar wind parameters. The performance of each satellite was assessed by comparing the model output to observed data.

Data-Based Predictive Control with Multirate Prediction Step

NASA Technical Reports Server (NTRS)

Barlow, Jonathan S.

2010-01-01

Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

Persistent grief in the aftermath of mass violence: the predictive roles of posttraumatic stress symptoms, self-efficacy, and disrupted worldview.

PubMed

Smith, Andrew J; Abeyta, Andrew A; Hughes, Michael; Jones, Russell T

2015-03-01

This study tested a conceptual model merging anxiety buffer disruption and social-cognitive theories to predict persistent grief severity among students who lost a close friend, significant other, and/or professor/teacher in tragic university campus shootings. A regression-based path model tested posttraumatic stress (PTS) symptom severity 3 to 4 months postshooting (Time 1) as a predictor of grief severity 1 year postshootings (Time 2), both directly and indirectly through cognitive processes (self-efficacy and disrupted worldview). Results revealed a model that predicted 61% of the variance in Time 2 grief severity. Hypotheses were supported, demonstrating that Time 1 PTS severity indirectly, positively predicted Time 2 grief severity through undermining self-efficacy and more severely disrupting worldview. Findings and theoretical interpretation yield important insights for future research and clinical application. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Experimental Evaluation of Tuned Chamber Core Panels for Payload Fairing Noise Control

NASA Technical Reports Server (NTRS)

Schiller, Noah H.; Allen, Albert R.; Herlan, Jonathan W.; Rosenthal, Bruce N.

2015-01-01

Analytical models have been developed to predict the sound absorption and sound transmission loss of tuned chamber core panels. The panels are constructed of two facesheets sandwiching a corrugated core. When ports are introduced through one facesheet, the long chambers within the core can be used as an array of low-frequency acoustic resonators. To evaluate the accuracy of the analytical models, absorption and sound transmission loss tests were performed on flat panels. Measurements show that the acoustic resonators embedded in the panels improve both the absorption and transmission loss of the sandwich structure at frequencies near the natural frequency of the resonators. Analytical predictions for absorption closely match measured data. However, transmission loss predictions miss important features observed in the measurements. This suggests that higher-fidelity analytical or numerical models will be needed to supplement transmission loss predictions in the future.

Random Wiring, Ganglion Cell Mosaics, and the Functional Architecture of the Visual Cortex

PubMed Central

Coppola, David; White, Leonard E.; Wolf, Fred

2015-01-01

The architecture of iso-orientation domains in the primary visual cortex (V1) of placental carnivores and primates apparently follows species invariant quantitative laws. Dynamical optimization models assuming that neurons coordinate their stimulus preferences throughout cortical circuits linking millions of cells specifically predict these invariants. This might indicate that V1’s intrinsic connectome and its functional architecture adhere to a single optimization principle with high precision and robustness. To validate this hypothesis, it is critical to closely examine the quantitative predictions of alternative candidate theories. Random feedforward wiring within the retino-cortical pathway represents a conceptually appealing alternative to dynamical circuit optimization because random dimension-expanding projections are believed to generically exhibit computationally favorable properties for stimulus representations. Here, we ask whether the quantitative invariants of V1 architecture can be explained as a generic emergent property of random wiring. We generalize and examine the stochastic wiring model proposed by Ringach and coworkers, in which iso-orientation domains in the visual cortex arise through random feedforward connections between semi-regular mosaics of retinal ganglion cells (RGCs) and visual cortical neurons. We derive closed-form expressions for cortical receptive fields and domain layouts predicted by the model for perfectly hexagonal RGC mosaics. Including spatial disorder in the RGC positions considerably changes the domain layout properties as a function of disorder parameters such as position scatter and its correlations across the retina. However, independent of parameter choice, we find that the model predictions substantially deviate from the layout laws of iso-orientation domains observed experimentally. Considering random wiring with the currently most realistic model of RGC mosaic layouts, a pairwise interacting point process, the predicted layouts remain distinct from experimental observations and resemble Gaussian random fields. We conclude that V1 layout invariants are specific quantitative signatures of visual cortical optimization, which cannot be explained by generic random feedforward-wiring models. PMID:26575467

Ecosystem behavior at Bermuda Station [open quotes]S[close quotes] and ocean weather station [open quotes]India[close quotes]: A general circulation model and observational analysis

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

Fasham, M.J.R.; Sarmiento, J.L.; Slater, R.D.

1993-06-01

One important theme of modern biological oceanography has been the attempt to develop models of how the marine ecosystem responds to variations in the physical forcing functions such as solar radiation and the wind field. The authors have addressed the problem by embedding simple ecosystem models into a seasonally forced three-dimensional general circulation model of the North Atlantic ocean. In this paper first, some of the underlying biological assumptions of the ecosystem model are presented, followed by an analysis of how well the model predicts the seasonal cycle of the biological variables at Bermuda Station s' and Ocean Weather Stationmore » India. The model gives a good overall fit to the observations but does not faithfully model the whole seasonal ecosystem model. 57 refs., 25 figs., 5 tabs.« less

An empirical model for prediction of household solid waste generation rate - A case study of Dhanbad, India.

PubMed

Kumar, Atul; Samadder, S R

2017-10-01

Accurate prediction of the quantity of household solid waste generation is very much essential for effective management of municipal solid waste (MSW). In actual practice, modelling methods are often found useful for precise prediction of MSW generation rate. In this study, two models have been proposed that established the relationships between the household solid waste generation rate and the socioeconomic parameters, such as household size, total family income, education, occupation and fuel used in the kitchen. Multiple linear regression technique was applied to develop the two models, one for the prediction of biodegradable MSW generation rate and the other for non-biodegradable MSW generation rate for individual households of the city Dhanbad, India. The results of the two models showed that the coefficient of determinations (R 2 ) were 0.782 for biodegradable waste generation rate and 0.676 for non-biodegradable waste generation rate using the selected independent variables. The accuracy tests of the developed models showed convincing results, as the predicted values were very close to the observed values. Validation of the developed models with a new set of data indicated a good fit for actual prediction purpose with predicted R 2 values of 0.76 and 0.64 for biodegradable and non-biodegradable MSW generation rate respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

A conceptual prediction model for seasonal drought processes using atmospheric and oceanic standardized anomalies: application to regional drought processes in China

NASA Astrophysics Data System (ADS)

Liu, Zhenchen; Lu, Guihua; He, Hai; Wu, Zhiyong; He, Jian

2018-01-01

Reliable drought prediction is fundamental for water resource managers to develop and implement drought mitigation measures. Considering that drought development is closely related to the spatial-temporal evolution of large-scale circulation patterns, we developed a conceptual prediction model of seasonal drought processes based on atmospheric and oceanic standardized anomalies (SAs). Empirical orthogonal function (EOF) analysis is first applied to drought-related SAs at 200 and 500 hPa geopotential height (HGT) and sea surface temperature (SST). Subsequently, SA-based predictors are built based on the spatial pattern of the first EOF modes. This drought prediction model is essentially the synchronous statistical relationship between 90-day-accumulated atmospheric-oceanic SA-based predictors and SPI3 (3-month standardized precipitation index), calibrated using a simple stepwise regression method. Predictor computation is based on forecast atmospheric-oceanic products retrieved from the NCEP Climate Forecast System Version 2 (CFSv2), indicating the lead time of the model depends on that of CFSv2. The model can make seamless drought predictions for operational use after a year-to-year calibration. Model application to four recent severe regional drought processes in China indicates its good performance in predicting seasonal drought development, despite its weakness in predicting drought severity. Overall, the model can be a worthy reference for seasonal water resource management in China.

Testing the Role of p21-Activated Kinases in Schwannoma Formation Using a Novel Genetically Engineered Murine Model that Closely Phenocopies Human NF2 Disease

DTIC Science & Technology

2015-06-01

preclinical models of NF1? Can whole kinome analysis predict pathways for drug resistance in treated mice? Procuring Contracting/Grants Officer: Emily...cells. b) Evaluate transduction of hydroxyethyl starch (HES)-processed hematopoietic cells. c) Monitor gene transfer in primary FANCC-/- progenitors

Infiltration-driven metamorphism, New England, USA: Regional CO2 fluxes and implications for Devonian climate and extinctions

NASA Astrophysics Data System (ADS)

Stewart, E. M.; Ague, Jay J.

2018-05-01

We undertake thermodynamic pseudosection modeling of metacarbonate rocks in the Wepawaug Schist, Connecticut, USA, and examine the implications for CO2 outgassing from collisional orogenic belts. Two broad types of pseudosections are calculated: (1) a fully closed-system model with no fluid infiltration and (2) a fluid-buffered model including an H2O-CO2 fluid of a fixed composition. This fluid-buffered model is used to approximate a system open to infiltration by a water-bearing fluid. In all cases the fully closed-system model fails to reproduce the observed major mineral zones, mineral compositions, reaction temperatures, and fluid compositions. The fluid-infiltrated models, on the other hand, successfully reproduce these observations when the XCO2 of the fluid is in the range ∼0.05 to ∼0.15. Fluid-infiltrated models predict significant progressive CO2 loss, peaking at ∼50% decarbonation at amphibolite facies. The closed-system models dramatically underestimate the degree of decarbonation, predicting only ∼15% CO2 loss at peak conditions, and, remarkably, <1% CO2 loss below ∼600 °C. We propagate the results of fluid-infiltrated pseudosections to determine an areal CO2 flux for the Wepawaug Schist. This yields ∼1012 mol CO2 km-2 Myr-1, consistent with multiple independent estimates of the metamorphic CO2 flux, and comparable in magnitude to fluxes from mid-ocean ridges and volcanic arcs. Extrapolating to the area of the Acadian orogenic belt, we suggest that metamorphic CO2 degassing is a plausible driver of global warming, sea level rise, and, perhaps, extinction in the mid- to late-Devonian.

Statistically Based Approach to Broadband Liner Design and Assessment

NASA Technical Reports Server (NTRS)

Jones, Michael G. (Inventor); Nark, Douglas M. (Inventor)

2016-01-01

A broadband liner design optimization includes utilizing in-duct attenuation predictions with a statistical fan source model to obtain optimum impedance spectra over a number of flow conditions for one or more liner locations in a bypass duct. The predicted optimum impedance information is then used with acoustic liner modeling tools to design liners having impedance spectra that most closely match the predicted optimum values. Design selection is based on an acceptance criterion that provides the ability to apply increasing weighting to specific frequencies and/or operating conditions. One or more broadband design approaches are utilized to produce a broadband liner that targets a full range of frequencies and operating conditions.

Temperature evolution during compaction of pharmaceutical powders.

PubMed

Zavaliangos, Antonios; Galen, Steve; Cunningham, John; Winstead, Denita

2008-08-01

A numerical approach to the prediction of temperature evolution in tablet compaction is presented here. It is based on a coupled thermomechanical finite element analysis and a calibrated Drucker-Prager Cap model. This approach is capable of predicting transient temperatures during compaction, which cannot be assessed by experimental techniques due to inherent test limitations. Model predictions are validated with infrared (IR) temperature measurements of the top tablet surface after ejection and match well with experiments. The dependence of temperature fields on speed and degree of compaction are naturally captured. The estimated transient temperatures are maximum at the end of compaction at the center of the tablet and close to the die wall next to the powder/die interface.

High capacity demonstration of honeycomb panel heat pipes

NASA Technical Reports Server (NTRS)

Tanzer, H. J.

1989-01-01

The feasibility of performance enhancing the sandwich panel heat pipe was investigated for moderate temperature range heat rejection radiators on future-high-power spacecraft. The hardware development program consisted of performance prediction modeling, fabrication, ground test, and data correlation. Using available sandwich panel materials, a series of subscale test panels were augumented with high-capacity sideflow and temperature control variable conductance features, and test evaluated for correlation with performance prediction codes. Using the correlated prediction model, a 50-kW full size radiator was defined using methanol working fluid and closely spaced sideflows. A new concept called the hybrid radiator individually optimizes heat pipe components. A 2.44-m long hybrid test vehicle demonstrated proof-of-principle performance.

Application of dimensionless sediment rating curves to predict suspended-sediment concentrations, bedload, and annual sediment loads for rivers in Minnesota

USGS Publications Warehouse

Ellison, Christopher A.; Groten, Joel T.; Lorenz, David L.; Koller, Karl S.

2016-10-27

Consistent and reliable sediment data are needed by Federal, State, and local government agencies responsible for monitoring water quality, planning river restoration, quantifying sediment budgets, and evaluating the effectiveness of sediment reduction strategies. Heightened concerns about excessive sediment in rivers and the challenge to reduce costs and eliminate data gaps has guided Federal and State interests in pursuing alternative methods for measuring suspended and bedload sediment. Simple and dependable data collection and estimation techniques are needed to generate hydraulic and water-quality information for areas where data are unavailable or difficult to collect.The U.S. Geological Survey, in cooperation with the Minnesota Pollution Control Agency and the Minnesota Department of Natural Resources, completed a study to evaluate the use of dimensionless sediment rating curves (DSRCs) to accurately predict suspended-sediment concentrations (SSCs), bedload, and annual sediment loads for selected rivers and streams in Minnesota based on data collected during 2007 through 2013. This study included the application of DSRC models developed for a small group of streams located in the San Juan River Basin near Pagosa Springs in southwestern Colorado to rivers in Minnesota. Regionally based DSRC models for Minnesota also were developed and compared to DSRC models from Pagosa Springs, Colorado, to evaluate which model provided more accurate predictions of SSCs and bedload in Minnesota.Multiple measures of goodness-of-fit were developed to assess the effectiveness of DSRC models in predicting SSC and bedload for rivers in Minnesota. More than 600 dimensionless ratio values of SSC, bedload, and streamflow were evaluated and delineated according to Pfankuch stream stability categories of “good/fair” and “poor” to develop four Minnesota-based DSRC models. The basis for Pagosa Springs and Minnesota DSRC model effectiveness was founded on measures of goodness-of-fit that included proximity of the model(s) fitted line to the 95-percent confidence intervals of the site-specific model, Nash-Sutcliffe Efficiency values, model biases, and deviation of annual sediment loads from each model to the annual sediment loads calculated from measured data.Composite plots comparing Pagosa Springs DSRCs, Minnesota DSRCs, site-specific regression models, and measured data indicated that regionally developed DSRCs (Minnesota DSRC models) more closely approximated measured data for nearly every site. Pagosa Springs DSRC models had markedly larger exponents (slopes) when compared to the Minnesota DSRC models and the site-specific regression models, and over-represent SSC and bedload at streamflows exceeding bankfull. The Nash-Sutcliffe Efficiency values for the Minnesota DSRC model for suspended-sediment concentrations closely matched Nash-Sutcliffe Efficiency values of the site-specific regression models for 12 out of 16 sites. Nash-Sutcliffe Efficiency values associated with Minnesota DSRCs were greater than those associated with Pagosa Springs DSRCs for every site except the Whitewater River near Beaver, Minnesota site. Pagosa Springs DSRC models were less accurate than the mean of the measured data at predicting SSC values for one-half of the sites for good/fair stability sites and one-half of the sites for poor stability sites. Relative model biases were calculated and determined to be substantial (greater than 5 percent) for Pagosa Springs and Minnesota models, with Minnesota models having a lower mean model bias. For predicted annual suspended-sediment loads (SSL), the Minnesota DSRC models for good/fair and poor stream stability sites more closely approximated the annual SSLs calculated from the measured data as compared to the Pagosa Springs DSRC model.Results of data analyses indicate that DSRC models developed using data collected in Minnesota were more effective at compensating for differences in individual stream characteristics across a variety of basin sizes and flow regimes than DSRC models developed using data collected for Pagosa Springs, Colorado. Minnesota DSRC models retained a substantial portion of the unique sediment signatures for most rivers, although deviations were observed for streams with limited sediment supply and for rivers in southeastern Minnesota, which had markedly larger regression exponents. Compared to Pagosa Springs DSRC models, Minnesota DSRC models had regression slopes that more closely matched the slopes of site-specific regression models, had greater Nash-Sutcliffe Efficiency values, had lower model biases, and approximated measured annual sediment loads more closely. The results presented in this report indicate that regionally based DSRCs can be used to estimate reasonably accurate values of SSC and bedload.Practitioners are cautioned that DSRC reliability is dependent on representative measures of bankfull streamflow, SSC, and bedload. It is, therefore, important that samples of SSC and bedload, which will be used for estimating SSC and bedload at the bankfull streamflow, are collected over a range of conditions that includes the ascending and descending limbs of the event hydrograph. The use of DSRC models may have substantial limitations for certain conditions. For example, DSRC models should not be used to predict SSC and sediment loads for extreme streamflows, such as those that exceed twice the bankfull streamflow value because this constitutes conditions beyond the realm of current (2016) empirical modeling capability. Also, if relations between SSC and streamflow and between bedload and streamflow are not statistically significant, DSRC models should not be used to predict SSC or bedload, as this could result in large errors. For streams that do not violate these conditions, DSRC estimates of SSC and bedload can be used for stream restoration planning and design, and for estimating annual sediment loads for streams where little or no sediment data are available.

Enabling comparative modeling of closely related genomes: Example genus Brucella

DOE PAGES

Faria, José P.; Edirisinghe, Janaka N.; Davis, James J.; ...

2014-03-08

For many scientific applications, it is highly desirable to be able to compare metabolic models of closely related genomes. In this study, we attempt to raise awareness to the fact that taking annotated genomes from public repositories and using them for metabolic model reconstructions is far from being trivial due to annotation inconsistencies. We are proposing a protocol for comparative analysis of metabolic models on closely related genomes, using fifteen strains of genus Brucella, which contains pathogens of both humans and livestock. This study lead to the identification and subsequent correction of inconsistent annotations in the SEED database, as wellmore » as the identification of 31 biochemical reactions that are common to Brucella, which are not originally identified by automated metabolic reconstructions. We are currently implementing this protocol for improving automated annotations within the SEED database and these improvements have been propagated into PATRIC, Model-SEED, KBase and RAST. This method is an enabling step for the future creation of consistent annotation systems and high-quality model reconstructions that will support in predicting accurate phenotypes such as pathogenicity, media requirements or type of respiration.« less

Enabling comparative modeling of closely related genomes: Example genus Brucella

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

Faria, José P.; Edirisinghe, Janaka N.; Davis, James J.

For many scientific applications, it is highly desirable to be able to compare metabolic models of closely related genomes. In this study, we attempt to raise awareness to the fact that taking annotated genomes from public repositories and using them for metabolic model reconstructions is far from being trivial due to annotation inconsistencies. We are proposing a protocol for comparative analysis of metabolic models on closely related genomes, using fifteen strains of genus Brucella, which contains pathogens of both humans and livestock. This study lead to the identification and subsequent correction of inconsistent annotations in the SEED database, as wellmore » as the identification of 31 biochemical reactions that are common to Brucella, which are not originally identified by automated metabolic reconstructions. We are currently implementing this protocol for improving automated annotations within the SEED database and these improvements have been propagated into PATRIC, Model-SEED, KBase and RAST. This method is an enabling step for the future creation of consistent annotation systems and high-quality model reconstructions that will support in predicting accurate phenotypes such as pathogenicity, media requirements or type of respiration.« less

Probing RNA tertiary structure: interhelical crosslinking of the hammerhead ribozyme.

PubMed Central

Sigurdsson, S T; Tuschl, T; Eckstein, F

1995-01-01

Distinct structural models for the hammerhead ribozyme derived from single-crystal X-ray diffraction and fluorescence resonance energy transfer (FRET) measurements have been compared. Both models predict the same overall geometry, a wishbone shape with helices II and III nearly colinear and helix I positioned close to helix II. However, the relative orientations of helices I and II are different. To establish whether one of the models represents a kinetically active structure, a new crosslinking procedure was developed in which helices I and II of hammerhead ribozymes were disulfide-crosslinked via the 2' positions of specific sugar residues. Crosslinking residues on helices I and II that are close according to the X-ray structure did not appreciably reduce the catalytic efficiency. In contrast, crosslinking residues closely situated according to the FRET model dramatically reduced the cleavage rate by at least three orders of magnitude. These correlations between catalytic efficiencies and spatial proximities are consistent with the X-ray structure. PMID:7489517

Application of an Elongated Kelvin Model to Space Shuttle Foams

NASA Technical Reports Server (NTRS)

Sullivan, Roy M.; Ghosn, Louis J.; Lerch, Bradley A.

2009-01-01

The space shuttle foams are rigid closed-cell polyurethane foams. The two foams used most-extensively oil space shuttle external tank are BX-265 and NCFL4-124. Because of the foaming and rising process, the foam microstructures are elongated in the rise direction. As a result, these two foams exhibit a nonisotropic mechanical behavior. A detailed microstructural characterization of the two foams is presented. Key features of the foam cells are described and the average cell dimensions in the two foams are summarized. Experimental studies are also conducted to measure the room temperature mechanical response of the two foams in the two principal material directions (parallel to the rise and perpendicular to the rise). The measured elastic modulus, proportional limit stress, ultimate tensile strength, and Poisson's ratios are reported. The generalized elongated Kelvin foam model previously developed by the authors is reviewed and the equations which result from this model are summarized. Using the measured microstructural dimensions and the measured stiffness ratio, the foam tensile strength ratio and Poisson's ratios are predicted for both foams and are compared with the experimental data. The predicted tensile strength ratio is in close agreement with the measured strength ratio for both BX-265 and NCFI24-124. The comparison between the predicted Poisson's ratios and the measured values is not as favorable.

Convergence of models of human ventricular myocyte electrophysiology after global optimization to recapitulate clinical long QT phenotypes.

PubMed

Mann, Stefan A; Imtiaz, Mohammad; Winbo, Annika; Rydberg, Annika; Perry, Matthew D; Couderc, Jean-Philippe; Polonsky, Bronislava; McNitt, Scott; Zareba, Wojciech; Hill, Adam P; Vandenberg, Jamie I

2016-11-01

In-silico models of human cardiac electrophysiology are now being considered for prediction of cardiotoxicity as part of the preclinical assessment phase of all new drugs. We ask the question whether any of the available models are actually fit for this purpose. We tested three models of the human ventricular action potential, the O'hara-Rudy (ORD11), the Grandi-Bers (GB10) and the Ten Tusscher (TT06) models. We extracted clinical QT data for LQTS1 and LQTS2 patients with nonsense mutations that would be predicted to cause 50% loss of function in I Ks and I Kr respectively. We also obtained clinical QT data for LQTS3 patients. We then used a global optimization approach to improve the existing in silico models so that they reproduced all three clinical data sets more closely. We also examined the effects of adrenergic stimulation in the different LQTS subsets. All models, in their original form, produce markedly different and unrealistic predictions of QT prolongation for LQTS1, 2 and 3. After global optimization of the maximum conductances for membrane channels, all models have similar current densities during the action potential, despite differences in kinetic properties of the channels in the different models, and more closely reproduce the prolongation of repolarization seen in all LQTS subtypes. In-silico models of cardiac electrophysiology have the potential to be tremendously useful in complementing traditional preclinical drug testing studies. However, our results demonstrate they should be carefully validated and optimized to clinical data before they can be used for this purpose. Copyright © 2016 Elsevier Ltd. All rights reserved.

Simulation and analysis of a model dinoflagellate predator-prey system

NASA Astrophysics Data System (ADS)

Mazzoleni, M. J.; Antonelli, T.; Coyne, K. J.; Rossi, L. F.

2015-12-01

This paper analyzes the dynamics of a model dinoflagellate predator-prey system and uses simulations to validate theoretical and experimental studies. A simple model for predator-prey interactions is derived by drawing upon analogies from chemical kinetics. This model is then modified to account for inefficiencies in predation. Simulation results are shown to closely match the model predictions. Additional simulations are then run which are based on experimental observations of predatory dinoflagellate behavior, and this study specifically investigates how the predatory dinoflagellate Karlodinium veneficum uses toxins to immobilize its prey and increase its feeding rate. These simulations account for complex dynamics that were not included in the basic models, and the results from these computational simulations closely match the experimentally observed predatory behavior of K. veneficum and reinforce the notion that predatory dinoflagellates utilize toxins to increase their feeding rate.

The Long and Viscous Road: Uncovering Nuclear Diffusion Barriers in Closed Mitosis

PubMed Central

Zavala, Eder; Marquez-Lago, Tatiana T.

2014-01-01

Diffusion barriers are effective means for constraining protein lateral exchange in cellular membranes. In Saccharomyces cerevisiae, they have been shown to sustain parental identity through asymmetric segregation of ageing factors during closed mitosis. Even though barriers have been extensively studied in the plasma membrane, their identity and organization within the nucleus remains poorly understood. Based on different lines of experimental evidence, we present a model of the composition and structural organization of a nuclear diffusion barrier during anaphase. By means of spatial stochastic simulations, we propose how specialised lipid domains, protein rings, and morphological changes of the nucleus may coordinate to restrict protein exchange between mother and daughter nuclear lobes. We explore distinct, plausible configurations of these diffusion barriers and offer testable predictions regarding their protein exclusion properties and the diffusion regimes they generate. Our model predicts that, while a specialised lipid domain and an immobile protein ring at the bud neck can compartmentalize the nucleus during early anaphase; a specialised lipid domain spanning the elongated bridge between lobes would be entirely sufficient during late anaphase. Our work shows how complex nuclear diffusion barriers in closed mitosis may arise from simple nanoscale biophysical interactions. PMID:25032937

Algorithms for a Closed-Loop Artificial Pancreas: The Case for Model Predictive Control

PubMed Central

Bequette, B. Wayne

2013-01-01

The relative merits of model predictive control (MPC) and proportional-integral-derivative (PID) control are discussed, with the end goal of a closed-loop artificial pancreas (AP). It is stressed that neither MPC nor PID are single algorithms, but rather are approaches or strategies that may be implemented very differently by different engineers. The primary advantages to MPC are that (i) constraints on the insulin delivery rate (and/or insulin on board) can be explicitly included in the control calculation; (ii) it is a general framework that makes it relatively easy to include the effect of meals, exercise, and other events that are a function of the time of day; and (iii) it is flexible enough to include many different objectives, from set-point tracking (target) to zone (control to range). In the end, however, it is recognized that the control algorithm, while important, represents only a portion of the effort required to develop a closed-loop AP. Thus, any number of algorithms/approaches can be successful—the engineers involved in the design must have experience with the particular technique, including the important experience of implementing the algorithm in human studies and not simply through simulation studies. PMID:24351190

On Theoretical Broadband Shock-Associated Noise Near-Field Cross-Spectra

NASA Technical Reports Server (NTRS)

Miller, Steven A. E.

2015-01-01

The cross-spectral acoustic analogy is used to predict auto-spectra and cross-spectra of broadband shock-associated noise in the near-field and far-field from a range of heated and unheated supersonic off-design jets. A single equivalent source model is proposed for the near-field, mid-field, and far-field terms, that contains flow-field statistics of the shock wave shear layer interactions. Flow-field statistics are modeled based upon experimental observation and computational fluid dynamics solutions. An axisymmetric assumption is used to reduce the model to a closed-form equation involving a double summation over the equivalent source at each shock wave shear layer interaction. Predictions are compared with a wide variety of measurements at numerous jet Mach numbers and temperature ratios from multiple facilities. Auto-spectral predictions of broadband shock-associated noise in the near-field and far-field capture trends observed in measurement and other prediction theories. Predictions of spatial coherence of broadband shock-associated noise accurately capture the peak coherent intensity, frequency, and spectral width.

Laboratory evaluation of a walleye (Sander vitreus) bioenergetics model

USGS Publications Warehouse

Madenjian, C.P.; Wang, C.; O'Brien, T. P.; Holuszko, M.J.; Ogilvie, L.M.; Stickel, R.G.

2010-01-01

Walleye (Sander vitreus) is an important game fish throughout much of North America. We evaluated the performance of the Wisconsin bioenergetics model for walleye in the laboratory. Walleyes were fed rainbow smelt (Osmerus mordax) in four laboratory tanks during a 126-day experiment. Based on a statistical comparison of bioenergetics model predictions of monthly consumption with the observed monthly consumption, we concluded that the bioenergetics model significantly underestimated food consumption by walleye in the laboratory. The degree of underestimation appeared to depend on the feeding rate. For the tank with the lowest feeding rate (1.4% of walleye body weight per day), the agreement between the bioenergetics model prediction of cumulative consumption over the entire 126-day experiment and the observed cumulative consumption was remarkably close, as the prediction was within 0.1% of the observed cumulative consumption. Feeding rates in the other three tanks ranged from 1.6% to 1.7% of walleye body weight per day, and bioenergetics model predictions of cumulative consumption over the 126-day experiment ranged between 11 and 15% less than the observed cumulative consumption. ?? 2008 Springer Science+Business Media B.V.

Translational Modeling to Guide Study Design and Dose Choice in Obesity Exemplified by AZD1979, a Melanin‐concentrating Hormone Receptor 1 Antagonist

PubMed Central

Trägårdh, M; Lindén, D; Ploj, K; Johansson, A; Turnbull, A; Carlsson, B; Antonsson, M

2017-01-01

In this study, we present the translational modeling used in the discovery of AZD1979, a melanin‐concentrating hormone receptor 1 (MCHr1) antagonist aimed for treatment of obesity. The model quantitatively connects the relevant biomarkers and thereby closes the scaling path from rodent to man, as well as from dose to effect level. The complexity of individual modeling steps depends on the quality and quantity of data as well as the prior information; from semimechanistic body‐composition models to standard linear regression. Key predictions are obtained by standard forward simulation (e.g., predicting effect from exposure), as well as non‐parametric input estimation (e.g., predicting energy intake from longitudinal body‐weight data), across species. The work illustrates how modeling integrates data from several species, fills critical gaps between biomarkers, and supports experimental design and human dose‐prediction. We believe this approach can be of general interest for translation in the obesity field, and might inspire translational reasoning more broadly. PMID:28556607

My Pride and Joy? Predicting Favoritism and Disfavoritism in Mother-Adult Child Relations.

PubMed

Suitor, J Jill; Gilligan, Megan; Peng, Siyun; Con, Gulcin; Rurka, Marissa; Pillemer, Karl

2016-08-01

In this article, we compare predictors of mothers' differentiation among their adult children regarding emotional closeness, pride, conflict, and disappointment. We distinguish between predictors of relational (closeness, conflict) and evaluative (pride, disappointment) dimensions of favoritism and disfavoritism. Multilevel modeling using data collected from 381 older mothers regarding their relationships with 1,421 adult children indicated that adult children's similarity of values played the most prominent role in predicting mothers' favoritism and disfavoritism, followed by children's gender. Children's deviant behaviors in adulthood predicted both pride and disappointment but neither relational dimension. Contrary to expectations, the quantitative analysis indicated that children's normative adult achievements were poor predictors of both relational and evaluative dimensions of mothers' differentiation. Qualitative data shed additional light on mothers' evaluations by revealing that disappointment was shaped by children's achievements relative to their mothers' values and expectations, rather than by the achievement of specific societal, educational, career, and marital milestones.

Diagnostics of seeded RF plasmas: An experimental study related to the gaseous core reactor

NASA Technical Reports Server (NTRS)

Thompson, S. D.; Clement, J. D.; Williams, J. R.

1974-01-01

Measurements of the temperature profiles in an RF argon plasma were made over magnetic field intensities ranging from 20 amp turns/cm to 80 amp turns/cm. The results were compared with a one-dimensional numerical treatment of the governing equations and with an approximate closed form analytical solution that neglected radiation losses. The average measured temperatures in the plasma compared well with the numerical treatment, though the experimental profile showed less of an off center temperature peak than predicted by theory. This may be a result of the complex turbulent flow pattern present in the experimental torch and not modeled in the numerical treatment. The radiation term cannot be neglected for argon at the power levels investigated. The closed form analytical approximation that neglected radiation led to temperature predictions on the order of 1000 K to 2000 K higher than measured or predicted by the numerical treatment which considered radiation losses.

An analytical model for light backscattering by coccoliths and coccospheres of Emiliania huxleyi.

PubMed

Fournier, Georges; Neukermans, Griet

2017-06-26

We present an analytical model for light backscattering by coccoliths and coccolithophores of the marine calcifying phytoplankter Emiliania huxleyi. The model is based on the separation of the effects of diffraction, refraction, and reflection on scattering, a valid assumption for particle sizes typical of coccoliths and coccolithophores. Our model results match closely with results from an exact scattering code that uses complex particle geometry and our model also mimics well abrupt transitions in scattering magnitude. Finally, we apply our model to predict changes in the spectral backscattering coefficient during an Emiliania huxleyi bloom with results that closely match in situ measurements. Because our model captures the key features that control the light backscattering process, it can be generalized to coccoliths and coccolithophores of different morphologies which can be obtained from size-calibrated electron microphotographs. Matlab codes of this model are provided as supplementary material.

Testing and Life Prediction for Composite Rotor Hub Flexbeams

NASA Technical Reports Server (NTRS)

Murri, Gretchen B.

2004-01-01

A summary of several studies of delamination in tapered composite laminates with internal ply-drops is presented. Initial studies used 2D FE models to calculate interlaminar stresses at the ply-ending locations in linear tapered laminates under tension loading. Strain energy release rates for delamination in these laminates indicated that delamination would likely start at the juncture of the tapered and thin regions and grow unstably in both directions. Tests of glass/epoxy and graphite/epoxy linear tapered laminates under axial tension delaminated as predicted. Nonlinear tapered specimens were cut from a full-size helicopter rotor hub and were tested under combined constant axial tension and cyclic transverse bending loading to simulate the loading experienced by a rotorhub flexbeam in flight. For all the tested specimens, delamination began at the tip of the outermost dropped ply group and grew first toward the tapered region. A 2D FE model was created that duplicated the test flexbeam layup, geometry, and loading. Surface strains calculated by the model agreed very closely with the measured surface strains in the specimens. The delamination patterns observed in the tests were simulated in the model by releasing pairs of MPCs along those interfaces. Strain energy release rates associated with the delamination growth were calculated for several configurations and using two different FE analysis codes. Calculations from the codes agreed very closely. The strain energy release rate results were used with material characterization data to predict fatigue delamination onset lives for nonlinear tapered flexbeams with two different ply-dropping schemes. The predicted curves agreed well with the test data for each case studied.

Experimental validation of a predicted feedback loop in the multi-oscillator clock of Arabidopsis thaliana

PubMed Central

Locke, James C W; Kozma-Bognár, László; Gould, Peter D; Fehér, Balázs; Kevei, Éva; Nagy, Ferenc; Turner, Matthew S; Hall, Anthony; Millar, Andrew J

2006-01-01

Our computational model of the circadian clock comprised the feedback loop between LATE ELONGATED HYPOCOTYL (LHY), CIRCADIAN CLOCK ASSOCIATED 1 (CCA1) and TIMING OF CAB EXPRESSION 1 (TOC1), and a predicted, interlocking feedback loop involving TOC1 and a hypothetical component Y. Experiments based on model predictions suggested GIGANTEA (GI) as a candidate for Y. We now extend the model to include a recently demonstrated feedback loop between the TOC1 homologues PSEUDO-RESPONSE REGULATOR 7 (PRR7), PRR9 and LHY and CCA1. This three-loop network explains the rhythmic phenotype of toc1 mutant alleles. Model predictions fit closely to new data on the gi;lhy;cca1 mutant, which confirm that GI is a major contributor to Y function. Analysis of the three-loop network suggests that the plant clock consists of morning and evening oscillators, coupled intracellularly, which may be analogous to coupled, morning and evening clock cells in Drosophila and the mouse. PMID:17102804

Validation of Models Used to Inform Colorectal Cancer Screening Guidelines: Accuracy and Implications.

PubMed

Rutter, Carolyn M; Knudsen, Amy B; Marsh, Tracey L; Doria-Rose, V Paul; Johnson, Eric; Pabiniak, Chester; Kuntz, Karen M; van Ballegooijen, Marjolein; Zauber, Ann G; Lansdorp-Vogelaar, Iris

2016-07-01

Microsimulation models synthesize evidence about disease processes and interventions, providing a method for predicting long-term benefits and harms of prevention, screening, and treatment strategies. Because models often require assumptions about unobservable processes, assessing a model's predictive accuracy is important. We validated 3 colorectal cancer (CRC) microsimulation models against outcomes from the United Kingdom Flexible Sigmoidoscopy Screening (UKFSS) Trial, a randomized controlled trial that examined the effectiveness of one-time flexible sigmoidoscopy screening to reduce CRC mortality. The models incorporate different assumptions about the time from adenoma initiation to development of preclinical and symptomatic CRC. Analyses compare model predictions to study estimates across a range of outcomes to provide insight into the accuracy of model assumptions. All 3 models accurately predicted the relative reduction in CRC mortality 10 years after screening (predicted hazard ratios, with 95% percentile intervals: 0.56 [0.44, 0.71], 0.63 [0.51, 0.75], 0.68 [0.53, 0.83]; estimated with 95% confidence interval: 0.56 [0.45, 0.69]). Two models with longer average preclinical duration accurately predicted the relative reduction in 10-year CRC incidence. Two models with longer mean sojourn time accurately predicted the number of screen-detected cancers. All 3 models predicted too many proximal adenomas among patients referred to colonoscopy. Model accuracy can only be established through external validation. Analyses such as these are therefore essential for any decision model. Results supported the assumptions that the average time from adenoma initiation to development of preclinical cancer is long (up to 25 years), and mean sojourn time is close to 4 years, suggesting the window for early detection and intervention by screening is relatively long. Variation in dwell time remains uncertain and could have important clinical and policy implications. © The Author(s) 2016.

Prediction of Phase Separation of Immiscible Ga-Tl Alloys

NASA Astrophysics Data System (ADS)

Kim, Yunkyum; Kim, Han Gyeol; Kang, Youn-Bae; Kaptay, George; Lee, Joonho

2017-06-01

Phase separation temperature of Ga-Tl liquid alloys was investigated using the constrained drop method. With this method, density and surface tension were investigated together. Despite strong repulsive interactions, molar volume showed ideal mixing behavior, whereas surface tension of the alloy was close to that of pure Tl due to preferential adsorption of Tl. Phase separation temperatures and surface tension values obtained with this method were close to the theoretically calculated values using three different thermodynamic models.

The effects of geometric uncertainties on computational modelling of knee biomechanics

NASA Astrophysics Data System (ADS)

Meng, Qingen; Fisher, John; Wilcox, Ruth

2017-08-01

The geometry of the articular components of the knee is an important factor in predicting joint mechanics in computational models. There are a number of uncertainties in the definition of the geometry of cartilage and meniscus, and evaluating the effects of these uncertainties is fundamental to understanding the level of reliability of the models. In this study, the sensitivity of knee mechanics to geometric uncertainties was investigated by comparing polynomial-based and image-based knee models and varying the size of meniscus. The results suggested that the geometric uncertainties in cartilage and meniscus resulting from the resolution of MRI and the accuracy of segmentation caused considerable effects on the predicted knee mechanics. Moreover, even if the mathematical geometric descriptors can be very close to the imaged-based articular surfaces, the detailed contact pressure distribution produced by the mathematical geometric descriptors was not the same as that of the image-based model. However, the trends predicted by the models based on mathematical geometric descriptors were similar to those of the imaged-based models.

Predicting wettability behavior of fluorosilica coated metal surface using optimum neural network

NASA Astrophysics Data System (ADS)

Taghipour-Gorjikolaie, Mehran; Valipour Motlagh, Naser

2018-02-01

The interaction between variables, which are effective on the surface wettability, is very complex to predict the contact angles and sliding angles of liquid drops. In this paper, in order to solve this complexity, artificial neural network was used to develop reliable models for predicting the angles of liquid drops. Experimental data are divided into training data and testing data. By using training data and feed forward structure for the neural network and using particle swarm optimization for training the neural network based models, the optimum models were developed. The obtained results showed that regression index for the proposed models for the contact angles and sliding angles are 0.9874 and 0.9920, respectively. As it can be seen, these values are close to unit and it means the reliable performance of the models. Also, it can be inferred from the results that the proposed model have more reliable performance than multi-layer perceptron and radial basis function based models.

Validation of Design and Analysis Techniques of Tailored Composite Structures

NASA Technical Reports Server (NTRS)

Jegley, Dawn C. (Technical Monitor); Wijayratne, Dulnath D.

2004-01-01

Aeroelasticity is the relationship between the elasticity of an aircraft structure and its aerodynamics. This relationship can cause instabilities such as flutter in a wing. Engineers have long studied aeroelasticity to ensure such instabilities do not become a problem within normal operating conditions. In recent decades structural tailoring has been used to take advantage of aeroelasticity. It is possible to tailor an aircraft structure to respond favorably to multiple different flight regimes such as takeoff, landing, cruise, 2-g pull up, etc. Structures can be designed so that these responses provide an aerodynamic advantage. This research investigates the ability to design and analyze tailored structures made from filamentary composites. Specifically the accuracy of tailored composite analysis must be verified if this design technique is to become feasible. To pursue this idea, a validation experiment has been performed on a small-scale filamentary composite wing box. The box is tailored such that its cover panels induce a global bend-twist coupling under an applied load. Two types of analysis were chosen for the experiment. The first is a closed form analysis based on a theoretical model of a single cell tailored box beam and the second is a finite element analysis. The predicted results are compared with the measured data to validate the analyses. The comparison of results show that the finite element analysis is capable of predicting displacements and strains to within 10% on the small-scale structure. The closed form code is consistently able to predict the wing box bending to 25% of the measured value. This error is expected due to simplifying assumptions in the closed form analysis. Differences between the closed form code representation and the wing box specimen caused large errors in the twist prediction. The closed form analysis prediction of twist has not been validated from this test.

Development of a Simulation Capability for the Space Station Active Rack Isolation System

NASA Technical Reports Server (NTRS)

Johnson, Terry L.; Tolson, Robert H.

1998-01-01

To realize quality microgravity science on the International Space Station, many microgravity facilities will utilize the Active Rack Isolation System (ARIS). Simulation capabilities for ARIS will be needed to predict the microgravity environment. This paper discusses the development of a simulation model for use in predicting the performance of the ARIS in attenuating disturbances with frequency content between 0.01 Hz and 10 Hz. The derivation of the model utilizes an energy-based approach. The complete simulation includes the dynamic model of the ISPR integrated with the model for the ARIS controller so that the entire closed-loop system is simulated. Preliminary performance predictions are made for the ARIS in attenuating both off-board disturbances as well as disturbances from hardware mounted onboard the microgravity facility. These predictions suggest that the ARIS does eliminate resonant behavior detrimental to microgravity experimentation. A limited comparison is made between the simulation predictions of ARIS attenuation of off-board disturbances and results from the ARIS flight test. These comparisons show promise, but further tuning of the simulation is needed.

A neighborhood statistics model for predicting stream pathogen indicator levels.

PubMed

Pandey, Pramod K; Pasternack, Gregory B; Majumder, Mahbubul; Soupir, Michelle L; Kaiser, Mark S

2015-03-01

Because elevated levels of water-borne Escherichia coli in streams are a leading cause of water quality impairments in the U.S., water-quality managers need tools for predicting aqueous E. coli levels. Presently, E. coli levels may be predicted using complex mechanistic models that have a high degree of unchecked uncertainty or simpler statistical models. To assess spatio-temporal patterns of instream E. coli levels, herein we measured E. coli, a pathogen indicator, at 16 sites (at four different times) within the Squaw Creek watershed, Iowa, and subsequently, the Markov Random Field model was exploited to develop a neighborhood statistics model for predicting instream E. coli levels. Two observed covariates, local water temperature (degrees Celsius) and mean cross-sectional depth (meters), were used as inputs to the model. Predictions of E. coli levels in the water column were compared with independent observational data collected from 16 in-stream locations. The results revealed that spatio-temporal averages of predicted and observed E. coli levels were extremely close. Approximately 66 % of individual predicted E. coli concentrations were within a factor of 2 of the observed values. In only one event, the difference between prediction and observation was beyond one order of magnitude. The mean of all predicted values at 16 locations was approximately 1 % higher than the mean of the observed values. The approach presented here will be useful while assessing instream contaminations such as pathogen/pathogen indicator levels at the watershed scale.

Testing Bayesian and heuristic predictions of mass judgments of colliding objects

PubMed Central

Sanborn, Adam N.

2014-01-01

Mass judgments of colliding objects have been used to explore people's understanding of the physical world because they are ecologically relevant, yet people display biases that are most easily explained by a small set of heuristics. Recent work has challenged the heuristic explanation, by producing the same biases from a model that copes with perceptual uncertainty by using Bayesian inference with a prior based on the correct combination rules from Newtonian mechanics (noisy Newton). Here I test the predictions of the leading heuristic model (Gilden and Proffitt, 1989) against the noisy Newton model using a novel manipulation of the standard mass judgment task: making one of the objects invisible post-collision. The noisy Newton model uses the remaining information to predict above-chance performance, while the leading heuristic model predicts chance performance when one or the other final velocity is occluded. An experiment using two different types of occlusion showed better-than-chance performance and response patterns that followed the predictions of the noisy Newton model. The results demonstrate that people can make sensible physical judgments even when information critical for the judgment is missing, and that a Bayesian model can serve as a guide in these situations. Possible algorithmic-level accounts of this task that more closely correspond to the noisy Newton model are explored. PMID:25206345

Genetic improvement in mastitis resistance: comparison of selection criteria from cross-sectional and random regression sire models for somatic cell score.

PubMed

Odegård, J; Klemetsdal, G; Heringstad, B

2005-04-01

Several selection criteria for reducing incidence of mastitis were developed from a random regression sire model for test-day somatic cell score (SCS). For comparison, sire transmitting abilities were also predicted based on a cross-sectional model for lactation mean SCS. Only first-crop daughters were used in genetic evaluation of SCS, and the different selection criteria were compared based on their correlation with incidence of clinical mastitis in second-crop daughters (measured as mean daughter deviations). Selection criteria were predicted based on both complete and reduced first-crop daughter groups (261 or 65 daughters per sire, respectively). For complete daughter groups, predicted transmitting abilities at around 30 d in milk showed the best predictive ability for incidence of clinical mastitis, closely followed by average predicted transmitting abilities over the entire lactation. Both of these criteria were derived from the random regression model. These selection criteria improved accuracy of selection by approximately 2% relative to a cross-sectional model. However, for reduced daughter groups, the cross-sectional model yielded increased predictive ability compared with the selection criteria based on the random regression model. This result may be explained by the cross-sectional model being more robust, i.e., less sensitive to precision of (co)variance components estimates and effects of data structure.

Schematic baryon models, their tight binding description and their microwave realization

NASA Astrophysics Data System (ADS)

Sadurní, E.; Franco-Villafañe, J. A.; Kuhl, U.; Mortessagne, F.; Seligman, T. H.

2013-12-01

A schematic model for baryon excitations is presented in terms of a symmetric Dirac gyroscope, a relativistic model solvable in closed form, that reduces to a rotor in the non-relativistic limit. The model is then mapped on a nearest neighbour tight binding model. In its simplest one-dimensional form this model yields a finite equidistant spectrum. This is experimentally implemented as a chain of dielectric resonators under conditions where their coupling is evanescent and a good agreement with the prediction is achieved.

Numerical model of spray combustion in a single cylinder diesel engine

NASA Astrophysics Data System (ADS)

Acampora, Luigi; Sequino, Luigi; Nigro, Giancarlo; Continillo, Gaetano; Vaglieco, Bianca Maria

2017-11-01

A numerical model is developed for predicting the pressure cycle from Intake Valve Closing (IVC) to the Exhaust Valve Opening (EVO) events. The model is based on a modified one-dimensional (1D) Musculus and Kattke spray model, coupled with a zero-dimensional (0D) non-adiabatic transient Fed-Batch reactor model. The 1D spray model provides an estimate of the fuel evaporation rate during the injection phenomenon, as a function of time. The 0D Fed-Batch reactor model describes combustion. The main goal of adopting a 0D (perfectly stirred) model is to use highly detailed reaction mechanisms for Diesel fuel combustion in air, while keeping the computational cost as low as possible. The proposed model is validated by comparing its predictions with experimental data of pressure obtained from an optical single cylinder Diesel engine.

Conformal Regression for Quantitative Structure-Activity Relationship Modeling-Quantifying Prediction Uncertainty.

PubMed

Svensson, Fredrik; Aniceto, Natalia; Norinder, Ulf; Cortes-Ciriano, Isidro; Spjuth, Ola; Carlsson, Lars; Bender, Andreas

2018-05-29

Making predictions with an associated confidence is highly desirable as it facilitates decision making and resource prioritization. Conformal regression is a machine learning framework that allows the user to define the required confidence and delivers predictions that are guaranteed to be correct to the selected extent. In this study, we apply conformal regression to model molecular properties and bioactivity values and investigate different ways to scale the resultant prediction intervals to create as efficient (i.e., narrow) regressors as possible. Different algorithms to estimate the prediction uncertainty were used to normalize the prediction ranges, and the different approaches were evaluated on 29 publicly available data sets. Our results show that the most efficient conformal regressors are obtained when using the natural exponential of the ensemble standard deviation from the underlying random forest to scale the prediction intervals, but other approaches were almost as efficient. This approach afforded an average prediction range of 1.65 pIC50 units at the 80% confidence level when applied to bioactivity modeling. The choice of nonconformity function has a pronounced impact on the average prediction range with a difference of close to one log unit in bioactivity between the tightest and widest prediction range. Overall, conformal regression is a robust approach to generate bioactivity predictions with associated confidence.

RANS modeling of scalar dispersion from localized sources within a simplified urban-area model

NASA Astrophysics Data System (ADS)

Rossi, Riccardo; Capra, Stefano; Iaccarino, Gianluca

2011-11-01

The dispersion of a passive scalar downstream a localized source within a simplified urban-like geometry is examined by means of RANS scalar flux models. The computations are conducted under conditions of neutral stability and for three different incoming wind directions (0°, 45°, 90°) at a roughness Reynolds number of Ret = 391. A Reynolds stress transport model is used to close the flow governing equations whereas both the standard eddy-diffusivity closure and algebraic flux models are employed to close the transport equation for the passive scalar. The comparison with a DNS database shows improved reliability from algebraic scalar flux models towards predicting both the mean concentration and the plume structure. Since algebraic flux models do not increase substantially the computational effort, the results indicate that the use of tensorial-diffusivity can be promising tool for dispersion simulations for the urban environment.

Recurrence predictive models for patients with hepatocellular carcinoma after radiofrequency ablation using support vector machines with feature selection methods.

PubMed

Liang, Ja-Der; Ping, Xiao-Ou; Tseng, Yi-Ju; Huang, Guan-Tarn; Lai, Feipei; Yang, Pei-Ming

2014-12-01

Recurrence of hepatocellular carcinoma (HCC) is an important issue despite effective treatments with tumor eradication. Identification of patients who are at high risk for recurrence may provide more efficacious screening and detection of tumor recurrence. The aim of this study was to develop recurrence predictive models for HCC patients who received radiofrequency ablation (RFA) treatment. From January 2007 to December 2009, 83 newly diagnosed HCC patients receiving RFA as their first treatment were enrolled. Five feature selection methods including genetic algorithm (GA), simulated annealing (SA) algorithm, random forests (RF) and hybrid methods (GA+RF and SA+RF) were utilized for selecting an important subset of features from a total of 16 clinical features. These feature selection methods were combined with support vector machine (SVM) for developing predictive models with better performance. Five-fold cross-validation was used to train and test SVM models. The developed SVM-based predictive models with hybrid feature selection methods and 5-fold cross-validation had averages of the sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and area under the ROC curve as 67%, 86%, 82%, 69%, 90%, and 0.69, respectively. The SVM derived predictive model can provide suggestive high-risk recurrent patients, who should be closely followed up after complete RFA treatment. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Stolen Base Physics

NASA Astrophysics Data System (ADS)

Kagan, David

2013-05-01

Few plays in baseball are as consistently close and exciting as the stolen base. While there are several studies of sprinting,2-4 the art of base stealing is much more nuanced. This article describes the motion of the base-stealing runner using a very basic kinematic model. The model will be compared to some data from a Major League game. The predictions of the model show consistency with the skills needed for effective base stealing.

Comprehensive Computational Pathological Image Analysis Predicts Lung Cancer Prognosis.

PubMed

Luo, Xin; Zang, Xiao; Yang, Lin; Huang, Junzhou; Liang, Faming; Rodriguez-Canales, Jaime; Wistuba, Ignacio I; Gazdar, Adi; Xie, Yang; Xiao, Guanghua

2017-03-01

Pathological examination of histopathological slides is a routine clinical procedure for lung cancer diagnosis and prognosis. Although the classification of lung cancer has been updated to become more specific, only a small subset of the total morphological features are taken into consideration. The vast majority of the detailed morphological features of tumor tissues, particularly tumor cells' surrounding microenvironment, are not fully analyzed. The heterogeneity of tumor cells and close interactions between tumor cells and their microenvironments are closely related to tumor development and progression. The goal of this study is to develop morphological feature-based prediction models for the prognosis of patients with lung cancer. We developed objective and quantitative computational approaches to analyze the morphological features of pathological images for patients with NSCLC. Tissue pathological images were analyzed for 523 patients with adenocarcinoma (ADC) and 511 patients with squamous cell carcinoma (SCC) from The Cancer Genome Atlas lung cancer cohorts. The features extracted from the pathological images were used to develop statistical models that predict patients' survival outcomes in ADC and SCC, respectively. We extracted 943 morphological features from pathological images of hematoxylin and eosin-stained tissue and identified morphological features that are significantly associated with prognosis in ADC and SCC, respectively. Statistical models based on these extracted features stratified NSCLC patients into high-risk and low-risk groups. The models were developed from training sets and validated in independent testing sets: a predicted high-risk group versus a predicted low-risk group (for patients with ADC: hazard ratio = 2.34, 95% confidence interval: 1.12-4.91, p = 0.024; for patients with SCC: hazard ratio = 2.22, 95% confidence interval: 1.15-4.27, p = 0.017) after adjustment for age, sex, smoking status, and pathologic tumor stage. The results suggest that the quantitative morphological features of tumor pathological images predict prognosis in patients with lung cancer. Copyright © 2016 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

Predicting Long-Term Global Outcome after Traumatic Brain Injury: Development of a Practical Prognostic Tool Using the Traumatic Brain Injury Model Systems National Database.

PubMed

Walker, William C; Stromberg, Katharine A; Marwitz, Jennifer H; Sima, Adam P; Agyemang, Amma A; Graham, Kristin M; Harrison-Felix, Cynthia; Hoffman, Jeanne M; Brown, Allen W; Kreutzer, Jeffrey S; Merchant, Randall

2018-05-16

For patients surviving serious traumatic brain injury (TBI), families and other stakeholders often desire information on long-term functional prognosis, but accurate and easy-to-use clinical tools are lacking. We aimed to build utilitarian decision trees from commonly collected clinical variables to predict Glasgow Outcome Scale (GOS) functional levels at 1, 2, and 5 years after moderate-to-severe closed TBI. Flexible classification tree statistical modeling was used on prospectively collected data from the TBI-Model Systems (TBIMS) inception cohort study. Enrollments occurred at 17 designated, or previously designated, TBIMS inpatient rehabilitation facilities. Analysis included all participants with nonpenetrating TBI injured between January 1997 and January 2017. Sample sizes were 10,125 (year-1), 8,821 (year-2), and 6,165 (year-5) after cross-sectional exclusions (death, vegetative state, insufficient post-injury time, and unavailable outcome). In our final models, post-traumatic amnesia (PTA) duration consistently dominated branching hierarchy and was the lone injury characteristic significantly contributing to GOS predictability. Lower-order variables that added predictability were age, pre-morbid education, productivity, and occupational category. Generally, patient outcomes improved with shorter PTA, younger age, greater pre-morbid productivity, and higher pre-morbid vocational or educational achievement. Across all prognostic groups, the best and worst good recovery rates were 65.7% and 10.9%, respectively, and the best and worst severe disability rates were 3.9% and 64.1%. Predictability in test data sets ranged from C-statistic of 0.691 (year-1; confidence interval [CI], 0.675, 0.711) to 0.731 (year-2; CI, 0.724, 0.738). In conclusion, we developed a clinically useful tool to provide prognostic information on long-term functional outcomes for adult survivors of moderate and severe closed TBI. Predictive accuracy for GOS level was demonstrated in an independent test sample. Length of PTA, a clinical marker of injury severity, was by far the most critical outcome determinant.

The impact of three recent coal-fired power plant closings on Pittsburgh air quality: A natural experiment.

PubMed

Russell, Marie C; Belle, Jessica H; Liu, Yang

2017-01-01

Relative to the rest of the United States, the region of southwestern Pennsylvania, including metropolitan Pittsburgh, experiences high ambient concentrations of fine particulate matter (PM 2.5 ), which is known to be associated with adverse respiratory and cardiovascular health impacts. This study evaluates whether the closing of three coal-fired power plants within the southwestern Pennsylvania region resulted in a significant decrease in PM 2.5 concentration. Both PM 2.5 data obtained from EPA ground stations in the study region and aerosol optical depth (AOD) data retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments onboard the Terra and Aqua satellites were used to investigate regional air quality from January 2011 through December 2014. The impact of the plant closings on PM 2.5 concentration and AOD was evaluated using a series of generalized additive models. The model results show that monthly fuel consumption of the Elrama plant, which closed in October of 2012, and monthly fuel consumption of both the Mitchell and Hatfield's Ferry plants, which closed in October of 2013, were significant predictors of both PM 2.5 concentration and AOD at EPA ground stations in the study region, after controlling for multiple meteorological factors and long-term, region-wide air quality improvements. The model's power to predict PM 2.5 concentration increased from an adjusted R 2 of 0.61 to 0.68 after excluding data from ground stations with higher uncertainty due to recent increases in unconventional natural gas extraction activities. After preliminary analyses of mean PM 2.5 concentration and AOD showed a downward trend following each power plant shutdown, results from a series of generalized additive models confirmed that the activity of the three plants that closed, measured by monthly fuel consumption, was highly significant in predicting both AOD and PM 2.5 at 12 EPA ground stations; further research on PM 2.5 emissions from unconventional natural gas extraction is needed. With many coal-fired power plants scheduled to close across the United States in the coming years, there is interest in the potential impact on regional PM 2.5 concentrations. In southwestern Pennsylvania, recent coal-fired power plant closings were coupled with a boom in unconventional natural gas extraction. Natural gas is currently seen as an economically viable bridge fuel between coal and renewable energy. This study provides policymakers with more information on the potential ambient concentration changes associated with coal-fired power plant closings as the nation's energy reliance shifts toward natural gas.

Efficient Hybrid Actuation Using Solid-State Actuators

NASA Technical Reports Server (NTRS)

Leo, Donald J.; Cudney, Harley H.; Horner, Garnett (Technical Monitor)

2001-01-01

Piezohydraulic actuation is the use of fluid to rectify the motion of a piezoelectric actuator for the purpose of overcoming the small stroke limitations of the material. In this work we study a closed piezohydraulic circuit that utilizes active valves to rectify the motion of a hydraulic end affector. A linear, lumped parameter model of the system is developed and correlated with experiments. Results demonstrate that the model accurately predicts the filtering of the piezoelectric motion caused by hydraulic compliance. Accurate results are also obtained for predicting the unidirectional motion of the cylinder when the active valves are phased with respect to the piezoelectric actuator. A time delay associated with the mechanical response of the valves is incorporated into the model to reflect the finite time required to open or close the valves. This time delay is found to be the primary limiting factor in achieving higher speed and greater power from the piezohydraulic unit. Experiments on the piezohydraulic unit demonstrate that blocked forces on the order of 100 N and unloaded velocities of 180 micrometers/sec are achieved.

Numerical simulation of the actuation system for the ALDF's propulsion control valve. [Aircraft Landing Dynamics Facility

NASA Technical Reports Server (NTRS)

Korte, John J.

1990-01-01

A numerical simulation of the actuation system for the propulsion control valve (PCV) of the NASA Langley Aircraft Landing Dynamics Facility was developed during the preliminary design of the PCV and used throughout the entire project. The simulation is based on a predictive model of the PCV which is used to evaluate and design the actuation system. The PCV controls a 1.7 million-pound thrust water jet used in propelling a 108,000-pound test carriage. The PCV can open and close in 0.300 second and deliver over 9,000 gallons of water per sec at pressures up to 3150 psi. The numerical simulation results are used to predict transient performance and valve opening characteristics, specify the hydraulic control system, define transient loadings on components, and evaluate failure modes. The mathematical model used for numerically simulating the mechanical fluid power system is described, and numerical results are demonstrated for a typical opening and closing cycle of the PCV. A summary is then given on how the model is used in the design process.

Exploratory Studies in Generalized Predictive Control for Active Gust Load Alleviation

NASA Technical Reports Server (NTRS)

Kvaternik, Raymond G.; Eure, Kenneth W.; Juang, Jer-Nan

2006-01-01

The results of numerical simulations aimed at assessing the efficacy of Generalized Predictive Control (GPC) for active gust load alleviation using trailing- and leading-edge control surfaces are presented. The equations underlying the method are presented and discussed, including system identification, calculation of control law matrices, and calculation of commands applied to the control effectors. Both embedded and explicit feedforward paths for inclusion of disturbance effects are addressed. Results from two types of simulations are shown. The first used a 3-DOF math model of a mass-spring-dashpot system subject to user-defined external disturbances. The second used open-loop data from a wind-tunnel test in which a wing model was excited by sinusoidal vertical gusts; closed-loop behavior was simulated in post-test calculations. Results obtained from these simulations have been decidedly positive. In particular, results of closed-loop simulations for the wing model showed reductions in root moments by factors as high as 1000, depending on whether the excitation is from a constant- or variable-frequency gust and on the direction of the response.

Predictive time-series modeling using artificial neural networks for Linac beam symmetry: an empirical study.

PubMed

Li, Qiongge; Chan, Maria F

2017-01-01

Over half of cancer patients receive radiotherapy (RT) as partial or full cancer treatment. Daily quality assurance (QA) of RT in cancer treatment closely monitors the performance of the medical linear accelerator (Linac) and is critical for continuous improvement of patient safety and quality of care. Cumulative longitudinal QA measurements are valuable for understanding the behavior of the Linac and allow physicists to identify trends in the output and take preventive actions. In this study, artificial neural networks (ANNs) and autoregressive moving average (ARMA) time-series prediction modeling techniques were both applied to 5-year daily Linac QA data. Verification tests and other evaluations were then performed for all models. Preliminary results showed that ANN time-series predictive modeling has more advantages over ARMA techniques for accurate and effective applicability in the dosimetry and QA field. © 2016 New York Academy of Sciences.

Model predictive control of non-linear systems over networks with data quantization and packet loss.

PubMed

Yu, Jimin; Nan, Liangsheng; Tang, Xiaoming; Wang, Ping

2015-11-01

This paper studies the approach of model predictive control (MPC) for the non-linear systems under networked environment where both data quantization and packet loss may occur. The non-linear controlled plant in the networked control system (NCS) is represented by a Tagaki-Sugeno (T-S) model. The sensed data and control signal are quantized in both links and described as sector bound uncertainties by applying sector bound approach. Then, the quantized data are transmitted in the communication networks and may suffer from the effect of packet losses, which are modeled as Bernoulli process. A fuzzy predictive controller which guarantees the stability of the closed-loop system is obtained by solving a set of linear matrix inequalities (LMIs). A numerical example is given to illustrate the effectiveness of the proposed method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Variational prediction of the mechanical behavior of shape memory alloys based on thermal experiments

NASA Astrophysics Data System (ADS)

Junker, Philipp; Jaeger, Stefanie; Kastner, Oliver; Eggeler, Gunther; Hackl, Klaus

2015-07-01

In this work, we present simulations of shape memory alloys which serve as first examples demonstrating the predicting character of energy-based material models. We begin with a theoretical approach for the derivation of the caloric parts of the Helmholtz free energy. Afterwards, experimental results for DSC measurements are presented. Then, we recall a micromechanical model based on the principle of the minimum of the dissipation potential for the simulation of polycrystalline shape memory alloys. The previously determined caloric parts of the Helmholtz free energy close the set of model parameters without the need of parameter fitting. All quantities are derived directly from experiments. Finally, we compare finite element results for tension tests to experimental data and show that the model identified by thermal measurements can predict mechanically induced phase transformations and thus rationalize global material behavior without any further assumptions.

Comparative study of two approaches to model the offshore fish cages

NASA Astrophysics Data System (ADS)

Zhao, Yun-peng; Wang, Xin-xin; Decew, Jud; Tsukrov, Igor; Bai, Xiao-dong; Bi, Chun-wei

2015-06-01

The goal of this paper is to provide a comparative analysis of two commonly used approaches to discretize offshore fish cages: the lumped-mass approach and the finite element technique. Two case studies are chosen to compare predictions of the LMA (lumped-mass approach) and FEA (finite element analysis) based numerical modeling techniques. In both case studies, we consider several loading conditions consisting of different uniform currents and monochromatic waves. We investigate motion of the cage, its deformation, and the resultant tension in the mooring lines. Both model predictions are sufficient close to the experimental data, but for the first experiment, the DUT-FlexSim predictions are slightly more accurate than the ones provided by Aqua-FE™. According to the comparisons, both models can be successfully utilized to the design and analysis of the offshore fish cages provided that an appropriate safety factor is chosen.

Cognitive processes and conflict in close relationships: an attribution-efficacy model.

PubMed

Fincham, F D; Bradbury, T N

1987-12-01

A recently proposed model of cognitive processes underlying conflict in close relationships (Doherty, 1978, 1981a, 1981b) is revised and tested in two studies. Central to the original model are the causal attributions made for conflict and the perceived efficacy or ability to resolve conflict. The model is revised to incorporate judgments of responsibility and to provide a closer link to self-efficacy theory. The first study examines attributions and efficacy expectations in mother-child relationships. As anticipated, only weak evidence was obtained for predictions retained from the original model, high-lighting the relationship-specific nature of cognitive processes for conflict in families. A second study examines husband-wife relationships and provides evidence for the usefulness of an attribution-efficacy model for marital conflict. The attributional component of the model received greater support than that pertaining to efficacy expectations. In both studies, support was obtained for the proposal that the relation between conflict dimensions (e.g., blame) and causal dimensions is mediated by judgments of responsibility. The significance of the revisions to Doherty's model for understanding conflict in close relationships is discussed, and several avenues for further research are outlined.

Explaining neural signals in human visual cortex with an associative learning model.

PubMed

Jiang, Jiefeng; Schmajuk, Nestor; Egner, Tobias

2012-08-01

"Predictive coding" models posit a key role for associative learning in visual cognition, viewing perceptual inference as a process of matching (learned) top-down predictions (or expectations) against bottom-up sensory evidence. At the neural level, these models propose that each region along the visual processing hierarchy entails one set of processing units encoding predictions of bottom-up input, and another set computing mismatches (prediction error or surprise) between predictions and evidence. This contrasts with traditional views of visual neurons operating purely as bottom-up feature detectors. In support of the predictive coding hypothesis, a recent human neuroimaging study (Egner, Monti, & Summerfield, 2010) showed that neural population responses to expected and unexpected face and house stimuli in the "fusiform face area" (FFA) could be well-described as a summation of hypothetical face-expectation and -surprise signals, but not by feature detector responses. Here, we used computer simulations to test whether these imaging data could be formally explained within the broader framework of a mathematical neural network model of associative learning (Schmajuk, Gray, & Lam, 1996). Results show that FFA responses could be fit very closely by model variables coding for conditional predictions (and their violations) of stimuli that unconditionally activate the FFA. These data document that neural population signals in the ventral visual stream that deviate from classic feature detection responses can formally be explained by associative prediction and surprise signals.

Merchant ships discharging unwanted marine species in close proximity of a French aquaculture area: risks involved.

PubMed

Masson, Daniel; Thomas, Gerard; Genauzeau, Sylvie; Le Moine, Olivier; Derrien, Annick

2013-12-15

The most important oyster farming area in Europe is in a close proximity of two medium size merchant ports. Cargo ships deballast in this area before loading, releasing unwanted or noxious marine species. During a sampling campaign aboard these arriving ships, we found in some ballast water samples a huge number of potentially toxic dinoflagellates and some potentially pathogenic bacteria. A model was applied to find the potential geographical spread of the discharged ballast water. This model predicts the water to reach highly vulnerable shellfish farmed areas in six to eight days. Copyright © 2013 Elsevier Ltd. All rights reserved.

Prediction of high temperature metal matrix composite ply properties

NASA Technical Reports Server (NTRS)

Caruso, J. J.; Chamis, C. C.

1988-01-01

The application of the finite element method (superelement technique) in conjunction with basic concepts from mechanics of materials theory is demonstrated to predict the thermomechanical behavior of high temperature metal matrix composites (HTMMC). The simulated behavior is used as a basis to establish characteristic properties of a unidirectional composite idealized an as equivalent homogeneous material. The ply properties predicted include: thermal properties (thermal conductivities and thermal expansion coefficients) and mechanical properties (moduli and Poisson's ratio). These properties are compared with those predicted by a simplified, analytical composite micromechanics model. The predictive capabilities of the finite element method and the simplified model are illustrated through the simulation of the thermomechanical behavior of a P100-graphite/copper unidirectional composite at room temperature and near matrix melting temperature. The advantage of the finite element analysis approach is its ability to more precisely represent the composite local geometry and hence capture the subtle effects that are dependent on this. The closed form micromechanics model does a good job at representing the average behavior of the constituents to predict composite behavior.

The influence of a prediction display on the quasi-linear describing function and remnant measured with an adaptive analog-pilot in a closed loop

NASA Technical Reports Server (NTRS)

Dey, D.

1972-01-01

The effect of a prediction display on the human transfer characteristics is explained with the aid of a quasi-linear model. The prediction display causes an increase of the gain factor and the lead factor, a diminishing of the lag factor and a decrease of the remnant. Altogether, these factors yield a smaller mean square value of the control deviation and a simultaneous decrease of the mean square value of the stick signal.

Biokinetics of yttrium and comparison with its geochemical twin holmium

DOE PAGES

Leggett, Rich

2017-06-01

The transition metal yttrium (Y, atomic number 39) is chemically similar to elements in the lanthanide family (atomic numbers 57-71, lanthanum through lutetium) and is always present with the lanthanides in rare earth ores. Yttrium and the lanthanide holmium are particularly close chemical and physical analogues and are referred to as geochemical twins because they typically show little fractionation in geological material. Extensive measurements on rocks, soils, and meteorites indicate that the Y/Ho mass concentration ratio rarely falls far from the “chondritic” or “solar system” ratio of ~26. Our paper presents a new biokinetic model for yttrium in adult humansmore » and examines whether yttrium and holmium may be biological as well as geochemical twins. Collected data on yttrium and holmium in plants and human tissues do not allow precise derivations of Y/Ho concentration ratios but with occasional exceptions yield ratios that are reasonably consistent with chondritic values. Predictions of the time-dependent behavior of yttrium in adult humans based on the yttrium model presented here closely approximate predictions of the behavior of holmium based on a previously developed model for holmium. We know that yttrium and holmium are close biological analogues, but the available comparative data are too limited and imprecise to reveal whether there are any significant differences in their biological behavior.« less

Probabilistic modeling of discourse-aware sentence processing.

PubMed

Dubey, Amit; Keller, Frank; Sturt, Patrick

2013-07-01

Probabilistic models of sentence comprehension are increasingly relevant to questions concerning human language processing. However, such models are often limited to syntactic factors. This restriction is unrealistic in light of experimental results suggesting interactions between syntax and other forms of linguistic information in human sentence processing. To address this limitation, this article introduces two sentence processing models that augment a syntactic component with information about discourse co-reference. The novel combination of probabilistic syntactic components with co-reference classifiers permits them to more closely mimic human behavior than existing models. The first model uses a deep model of linguistics, based in part on probabilistic logic, allowing it to make qualitative predictions on experimental data; the second model uses shallow processing to make quantitative predictions on a broad-coverage reading-time corpus. Copyright © 2013 Cognitive Science Society, Inc.

The string prediction models as invariants of time series in the forex market

NASA Astrophysics Data System (ADS)

Pincak, R.

2013-12-01

In this paper we apply a new approach of string theory to the real financial market. The models are constructed with an idea of prediction models based on the string invariants (PMBSI). The performance of PMBSI is compared to support vector machines (SVM) and artificial neural networks (ANN) on an artificial and a financial time series. A brief overview of the results and analysis is given. The first model is based on the correlation function as invariant and the second one is an application based on the deviations from the closed string/pattern form (PMBCS). We found the difference between these two approaches. The first model cannot predict the behavior of the forex market with good efficiency in comparison with the second one which is, in addition, able to make relevant profit per year. The presented string models could be useful for portfolio creation and financial risk management in the banking sector as well as for a nonlinear statistical approach to data optimization.

Kinetics of process of product separation in closed system with recirculation

NASA Astrophysics Data System (ADS)

Prokopenko, V. S.; Orekhova, T. N.; Goncharov, E. I.; Odobesko, I. A.

2018-03-01

The object of an article is the extrapolation of the process of classifying material while passing in a model with the separation of the products of milling in the cleaning system includes a separator, concentrator, cyclone and a recycle loop. The model allows for the given parameters to predict the coarseness of grading of the finished product.

A General and Efficient Method for Incorporating Precise Spike Times in Globally Time-Driven Simulations

PubMed Central

Hanuschkin, Alexander; Kunkel, Susanne; Helias, Moritz; Morrison, Abigail; Diesmann, Markus

2010-01-01

Traditionally, event-driven simulations have been limited to the very restricted class of neuronal models for which the timing of future spikes can be expressed in closed form. Recently, the class of models that is amenable to event-driven simulation has been extended by the development of techniques to accurately calculate firing times for some integrate-and-fire neuron models that do not enable the prediction of future spikes in closed form. The motivation of this development is the general perception that time-driven simulations are imprecise. Here, we demonstrate that a globally time-driven scheme can calculate firing times that cannot be discriminated from those calculated by an event-driven implementation of the same model; moreover, the time-driven scheme incurs lower computational costs. The key insight is that time-driven methods are based on identifying a threshold crossing in the recent past, which can be implemented by a much simpler algorithm than the techniques for predicting future threshold crossings that are necessary for event-driven approaches. As run time is dominated by the cost of the operations performed at each incoming spike, which includes spike prediction in the case of event-driven simulation and retrospective detection in the case of time-driven simulation, the simple time-driven algorithm outperforms the event-driven approaches. Additionally, our method is generally applicable to all commonly used integrate-and-fire neuronal models; we show that a non-linear model employing a standard adaptive solver can reproduce a reference spike train with a high degree of precision. PMID:21031031

A cost minimisation and Bayesian inference model predicts startle reflex modulation across species.

PubMed

Bach, Dominik R

2015-04-07

In many species, rapid defensive reflexes are paramount to escaping acute danger. These reflexes are modulated by the state of the environment. This is exemplified in fear-potentiated startle, a more vigorous startle response during conditioned anticipation of an unrelated threatening event. Extant explanations of this phenomenon build on descriptive models of underlying psychological states, or neural processes. Yet, they fail to predict invigorated startle during reward anticipation and instructed attention, and do not explain why startle reflex modulation evolved. Here, we fill this lacuna by developing a normative cost minimisation model based on Bayesian optimality principles. This model predicts the observed pattern of startle modification by rewards, punishments, instructed attention, and several other states. Moreover, the mathematical formalism furnishes predictions that can be tested experimentally. Comparing the model with existing data suggests a specific neural implementation of the underlying computations which yields close approximations to the optimal solution under most circumstances. This analysis puts startle modification into the framework of Bayesian decision theory and predictive coding, and illustrates the importance of an adaptive perspective to interpret defensive behaviour across species. Copyright © 2015 The Author. Published by Elsevier Ltd.. All rights reserved.

Bubble generation during transformer overload

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

Oommen, T.V.

1990-03-01

Bubble generation in transformers has been demonstrated under certain overload conditions. The release of large quantities of bubbles would pose a dielectric breakdown hazard. A bubble prediction model developed under EPRI Project 1289-4 attempts to predict the bubble evolution temperature under different overload conditions. This report details a verification study undertaken to confirm the validity of the above model using coil structures subjected to overload conditions. The test variables included moisture in paper insulation, gas content in oil, and the type of oil preservation system. Two aged coils were also tested. The results indicated that the observed bubble temperatures weremore » close to the predicted temperatures for models with low initial gas content in the oil. The predicted temperatures were significantly lower than the observed temperatures for models with high gas content. Some explanations are provided for the anomalous behavior at high gas levels in oil. It is suggested that the dissolved gas content is not a significant factor in bubble evolution. The dominant factor in bubble evolution appears to be the water vapor pressure which must reach critical levels before bubbles can be released. Further study is needed to make a meaningful revision of the bubble prediction model. 8 refs., 13 figs., 11 tabs.« less

A molecular model for cohesive slip at polymer melt/solid interfaces.

PubMed

Tchesnokov, M A; Molenaar, J; Slot, J J M; Stepanyan, R

2005-06-01

A molecular model is proposed which predicts wall slip by disentanglement of polymer chains adsorbed on a wall from those in the polymer bulk. The dynamics of the near-wall boundary layer is found to be governed by a nonlinear equation of motion, which accounts for such mechanisms on surface chains as convection, retraction, constraint release, and thermal fluctuations. This equation is valid over a wide range of grafting regimes, including those in which interactions between neighboring adsorbed molecules become essential. It is not closed since the dynamics of adsorbed chains is shown to be coupled to that of polymer chains in the bulk via constraint release. The constitutive equations for the layer and bulk, together with continuity of stress and velocity, are found to form a closed system of equations which governs the dynamics of the whole "bulk+boundary layer" ensemble. Its solution provides a stick-slip law in terms of the molecular parameters and extruder geometry. The model is quantitative and contains only those parameters that can be measured directly, or extracted from independent rheological measurements. The model predictions show a good agreement with available experimental data.

[Hypothesis on the equilibrium point and variability of amplitude, speed and time of single-joint movement].

PubMed

Latash, M; Gottleib, G

1990-01-01

Problems of single-joint movement variability are analysed in the framework of the equilibrium-point hypothesis (the lambda-model). Control of the movements is described with three parameters related to movement amplitude speed, and time. Three strategies emerge from this description. Only one of them is likely to lead to a Fitts' type speed-accuracy trade-off. Experiments were performed to test one of the predictions of the model. Subjects performed identical sets of single-joint fast movements with open or closed eyes and some-what different instructions. Movements performed with closed eyes were characterized with higher peak speeds and unchanged variability in seeming violation of the Fitt's law and in a good correspondence to the model.

Robust shrinking ellipsoid model predictive control for linear parameter varying system

PubMed Central

Yan, Yan

2017-01-01

In this paper, a new off-line model predictive control strategy is presented for a kind of linear parameter varying system with polytopic uncertainty. A nest of shrinking ellipsoids is constructed by solving linear matrix inequality. By splitting the objective function into two parts, the proposed strategy moves most computations off-line. The on-line computation is only calculating the current control to assure the system shrinking into the smaller ellipsoid. With the proposed formulation, the stability of the closed system is proved, followed with two numerical examples to demonstrate the proposed method’s effectiveness in the end. PMID:28575028

Ultrastrong Coupling Few-Photon Scattering Theory

NASA Astrophysics Data System (ADS)

Shi, Tao; Chang, Yue; García-Ripoll, Juan José

2018-04-01

We study the scattering of individual photons by a two-level system ultrastrongly coupled to a waveguide. The scattering is elastic for a broad range of couplings and can be described with an effective U (1 )-symmetric Hamiltonian. This simple model allows the prediction of scattering resonance line shapes, validated up to α =0.3 , and close to the Toulouse point α =1 /2 , where inelastic scattering becomes relevant. Our predictions model experiments with superconducting circuits [P. Forn-Díaz et al., Nat. Phys. 13, 39 (2017), 10.1038/nphys3905] and can be extended to study multiphoton scattering.

Ultrastrong Coupling Few-Photon Scattering Theory.

PubMed

Shi, Tao; Chang, Yue; García-Ripoll, Juan José

2018-04-13

We study the scattering of individual photons by a two-level system ultrastrongly coupled to a waveguide. The scattering is elastic for a broad range of couplings and can be described with an effective U(1)-symmetric Hamiltonian. This simple model allows the prediction of scattering resonance line shapes, validated up to α=0.3, and close to the Toulouse point α=1/2, where inelastic scattering becomes relevant. Our predictions model experiments with superconducting circuits [P. Forn-Díaz et al., Nat. Phys. 13, 39 (2017)NPAHAX1745-247310.1038/nphys3905] and can be extended to study multiphoton scattering.

A two-layer composite model of the vocal fold lamina propria for fundamental frequency regulation.

PubMed

Zhang, Kai; Siegmund, Thomas; Chan, Roger W

2007-08-01

The mechanical properties of the vocal fold lamina propria, including the vocal fold cover and the vocal ligament, play an important role in regulating the fundamental frequency of human phonation. This study examines the equilibrium hyperelastic tensile deformation behavior of cover and ligament specimens isolated from excised human larynges. Ogden's hyperelastic model is used to characterize the tensile stress-stretch behaviors at equilibrium. Several statistically significant differences in the mechanical response differentiating cover and ligament, as well as gender are found. Fundamental frequencies are predicted from a string model and a beam model, both accounting for the cover and the ligament. The beam model predicts nonzero F(0) for the unstretched state of the vocal fold. It is demonstrated that bending stiffness significantly contributes to the predicted F(0), with the ligament contributing to a higher F(0), especially in females. Despite the availability of only a small data set, the model predicts an age dependence of F(0) in males in agreement with experimental findings. Accounting for two mechanisms of fundamental frequency regulation--vocal fold posturing (stretching) and extended clamping--brings predicted F(0) close to the lower bound of the human phonatory range. Advantages and limitations of the current model are discussed.

Computation of Alfvèn eigenmode stability and saturation through a reduced fast ion transport model in the TRANSP tokamak transport code

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

Podestà, M.; Gorelenkova, M.; Gorelenkov, N. N.

Alfvénic instabilities (AEs) are well known as a potential cause of enhanced fast ion transport in fusion devices. Given a specific plasma scenario, quantitative predictions of (i) expected unstable AE spectrum and (ii) resulting fast ion transport are required to prevent or mitigate the AE-induced degradation in fusion performance. Reduced models are becoming an attractive tool to analyze existing scenarios as well as for scenario prediction in time-dependent simulations. Here, in this work, a neutral beam heated NSTX discharge is used as reference to illustrate the potential of a reduced fast ion transport model, known as kick model, that hasmore » been recently implemented for interpretive and predictive analysis within the framework of the time-dependent tokamak transport code TRANSP. Predictive capabilities for AE stability and saturation amplitude are first assessed, based on given thermal plasma profiles only. Predictions are then compared to experimental results, and the interpretive capabilities of the model further discussed. Overall, the reduced model captures the main properties of the instabilities and associated effects on the fast ion population. Finally, additional information from the actual experiment enables further tuning of the model's parameters to achieve a close match with measurements.« less

Computation of Alfvèn eigenmode stability and saturation through a reduced fast ion transport model in the TRANSP tokamak transport code

DOE PAGES

Podestà, M.; Gorelenkova, M.; Gorelenkov, N. N.; ...

2017-07-20

Alfvénic instabilities (AEs) are well known as a potential cause of enhanced fast ion transport in fusion devices. Given a specific plasma scenario, quantitative predictions of (i) expected unstable AE spectrum and (ii) resulting fast ion transport are required to prevent or mitigate the AE-induced degradation in fusion performance. Reduced models are becoming an attractive tool to analyze existing scenarios as well as for scenario prediction in time-dependent simulations. Here, in this work, a neutral beam heated NSTX discharge is used as reference to illustrate the potential of a reduced fast ion transport model, known as kick model, that hasmore » been recently implemented for interpretive and predictive analysis within the framework of the time-dependent tokamak transport code TRANSP. Predictive capabilities for AE stability and saturation amplitude are first assessed, based on given thermal plasma profiles only. Predictions are then compared to experimental results, and the interpretive capabilities of the model further discussed. Overall, the reduced model captures the main properties of the instabilities and associated effects on the fast ion population. Finally, additional information from the actual experiment enables further tuning of the model's parameters to achieve a close match with measurements.« less

Experimental investigations of stability of static liquid fillets and liquid-gas interface in capillary passages for gas-free liquid acquisition in zero gravity

NASA Astrophysics Data System (ADS)

Purohit, Ghanshyam Purshottamdas

Experimental investigations of static liquid fillets formed between small gaps of a cylindrical surface and a flat surface are carried out. The minimum volume of liquid required to form a stable fillet and the maximum liquid content the fillet can hold before becoming unstable are studied. Fillet shapes are captured in photographs obtained by a high speed image system. Experiments were conducted using water, UPA and PF 5060 on two surfaces-stand-blasted titanium and polished copper for different surface inclinations. Experimental data are generalized using appropriate non-dimensional groups. Analytical model are developed to describe the fillet curvature. Fillet curvature data are compared against model predictions and are found to be in close agreement. Bubble point experiments were carried out to measure the capillary pressure difference across the liquid-gas interface in the channels of photo-chemically etched disk stacks. Experiments were conducted using titanium stacks of five different geometrical configurations. Both well wetting liquids (IPA and PF5060) and partially wetting liquid (water) were used during experiments. Test results are found to be in close agreement with analytical predictions. Experiments were carried out to measure the frictional pressure drop across the stack as a function of liquid flow rate using two different liquids (water and IPA) and five stacks of different geometrical configurations. A channel pressure drop model is developed by treating the flow within stack channels as fully developed laminar flow between parallel plates and solving the one-dimensional Navier Stokes equation. An alternate model is developed by treating the flow in channels as flow within porous media. Expressions are developed for effective porosity and permeability for the stacks and the pressure drop is related to these parameters. Pressure drop test results are found to be in close agreement with model predictions. As a specific application of this work, a surface tension propellant management device (PMD) that uses photo-chemically etched disk stacks as capillary elements is examined. These PMDs are used in gas pressurized liquid propellant tanks to supply gas-free propellant to rocket engines in near zero-gravity environment. The experimentally validated models are integrated to perform key analyses for predicting PMD performance in zero gravity.

One-dimensional wave bottom boundary layer model comparison: specific eddy viscosity and turbulence closure models

USGS Publications Warehouse

Puleo, J.A.; Mouraenko, O.; Hanes, D.M.

2004-01-01

Six one-dimensional-vertical wave bottom boundary layer models are analyzed based on different methods for estimating the turbulent eddy viscosity: Laminar, linear, parabolic, k—one equation turbulence closure, k−ε—two equation turbulence closure, and k−ω—two equation turbulence closure. Resultant velocity profiles, bed shear stresses, and turbulent kinetic energy are compared to laboratory data of oscillatory flow over smooth and rough beds. Bed shear stress estimates for the smooth bed case were most closely predicted by the k−ω model. Normalized errors between model predictions and measurements of velocity profiles over the entire computational domain collected at 15° intervals for one-half a wave cycle show that overall the linear model was most accurate. The least accurate were the laminar and k−ε models. Normalized errors between model predictions and turbulence kinetic energy profiles showed that the k−ω model was most accurate. Based on these findings, when the smallest overall velocity profile prediction error is required, the processing requirements and error analysis suggest that the linear eddy viscosity model is adequate. However, if accurate estimates of bed shear stress and TKE are required then, of the models tested, the k−ω model should be used.

Evaluation of multivariate linear regression and artificial neural networks in prediction of water quality parameters

PubMed Central

2014-01-01

This paper examined the efficiency of multivariate linear regression (MLR) and artificial neural network (ANN) models in prediction of two major water quality parameters in a wastewater treatment plant. Biochemical oxygen demand (BOD) and chemical oxygen demand (COD) as well as indirect indicators of organic matters are representative parameters for sewer water quality. Performance of the ANN models was evaluated using coefficient of correlation (r), root mean square error (RMSE) and bias values. The computed values of BOD and COD by model, ANN method and regression analysis were in close agreement with their respective measured values. Results showed that the ANN performance model was better than the MLR model. Comparative indices of the optimized ANN with input values of temperature (T), pH, total suspended solid (TSS) and total suspended (TS) for prediction of BOD was RMSE = 25.1 mg/L, r = 0.83 and for prediction of COD was RMSE = 49.4 mg/L, r = 0.81. It was found that the ANN model could be employed successfully in estimating the BOD and COD in the inlet of wastewater biochemical treatment plants. Moreover, sensitive examination results showed that pH parameter have more effect on BOD and COD predicting to another parameters. Also, both implemented models have predicted BOD better than COD. PMID:24456676

Validation of a Clinical Scoring System for Outcome Prediction in Dogs with Acute Kidney Injury Managed by Hemodialysis.

PubMed

Segev, G; Langston, C; Takada, K; Kass, P H; Cowgill, L D

2016-05-01

A scoring system for outcome prediction in dogs with acute kidney injury (AKI) recently has been developed but has not been validated. The scoring system previously developed for outcome prediction will accurately predict outcome in a validation cohort of dogs with AKI managed with hemodialysis. One hundred fifteen client-owned dogs with AKI. Medical records of dogs with AKI treated by hemodialysis between 2011 and 2015 were reviewed. Dogs were included only if all variables required to calculate the final predictive score were available, and the 30-day outcome was known. A predictive score for 3 models was calculated for each dog. Logistic regression was used to evaluate the association of the final predictive score with each model's outcome. Receiver operating curve (ROC) analyses were performed to determine sensitivity and specificity for each model based on previously established cut-off values. Higher scores for each model were associated with decreased survival probability (P < .001). Based on previously established cut-off values, 3 models (models A, B, C) were associated with sensitivities/specificities of 73/75%, 71/80%, and 75/86%, respectively, and correctly classified 74-80% of the dogs. All models were simple to apply and allowed outcome prediction that closely corresponded with actual outcome in an independent cohort. As expected, accuracies were slightly lower compared with those from the previously reported cohort used initially to develop the models. Copyright © 2016 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.

Predictive ability of genomic selection models for breeding value estimation on growth traits of Pacific white shrimp Litopenaeus vannamei

NASA Astrophysics Data System (ADS)

Wang, Quanchao; Yu, Yang; Li, Fuhua; Zhang, Xiaojun; Xiang, Jianhai

2017-09-01

Genomic selection (GS) can be used to accelerate genetic improvement by shortening the selection interval. The successful application of GS depends largely on the accuracy of the prediction of genomic estimated breeding value (GEBV). This study is a first attempt to understand the practicality of GS in Litopenaeus vannamei and aims to evaluate models for GS on growth traits. The performance of GS models in L. vannamei was evaluated in a population consisting of 205 individuals, which were genotyped for 6 359 single nucleotide polymorphism (SNP) markers by specific length amplified fragment sequencing (SLAF-seq) and phenotyped for body length and body weight. Three GS models (RR-BLUP, BayesA, and Bayesian LASSO) were used to obtain the GEBV, and their predictive ability was assessed by the reliability of the GEBV and the bias of the predicted phenotypes. The mean reliability of the GEBVs for body length and body weight predicted by the different models was 0.296 and 0.411, respectively. For each trait, the performances of the three models were very similar to each other with respect to predictability. The regression coefficients estimated by the three models were close to one, suggesting near to zero bias for the predictions. Therefore, when GS was applied in a L. vannamei population for the studied scenarios, all three models appeared practicable. Further analyses suggested that improved estimation of the genomic prediction could be realized by increasing the size of the training population as well as the density of SNPs.

eShadow: A tool for comparing closely related sequences

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

Ovcharenko, Ivan; Boffelli, Dario; Loots, Gabriela G.

2004-01-15

Primate sequence comparisons are difficult to interpret due to the high degree of sequence similarity shared between such closely related species. Recently, a novel method, phylogenetic shadowing, has been pioneered for predicting functional elements in the human genome through the analysis of multiple primate sequence alignments. We have expanded this theoretical approach to create a computational tool, eShadow, for the identification of elements under selective pressure in multiple sequence alignments of closely related genomes, such as in comparisons of human to primate or mouse to rat DNA. This tool integrates two different statistical methods and allows for the dynamic visualizationmore » of the resulting conservation profile. eShadow also includes a versatile optimization module capable of training the underlying Hidden Markov Model to differentially predict functional sequences. This module grants the tool high flexibility in the analysis of multiple sequence alignments and in comparing sequences with different divergence rates. Here, we describe the eShadow comparative tool and its potential uses for analyzing both multiple nucleotide and protein alignments to predict putative functional elements. The eShadow tool is publicly available at http://eshadow.dcode.org/« less

Climatically-mediated landcover change: impacts on Brazilian territory.

PubMed

Zanin, Marina; Tessarolo, Geiziane; Machado, Nathália; Albernaz, Ana Luisa M

2017-01-01

In the face of climate change threats, governments are drawing attention to policies for mitigating its effects on biodiversity. However, the lack of distribution data makes predictions at species level a difficult task, mainly in regions of higher biodiversity. To overcome this problem, we use native landcover as a surrogate biodiversity, because it can represent specialized habitat for species, and investigate the effects of future climate change on Brazilian biomes. We characterize the climatic niches of native landcover and use ecological niche modeling to predict the potential distribution under current and future climate scenarios. Our results highlight expansion of the distribution of open vegetation and the contraction of closed forests. Drier Brazilian biomes, like Caatinga and Cerrado, are predicted to expand their distributions, being the most resistant to climate change impacts. However, these would also be affected by losses of their closed forest enclaves and their habitat-specific or endemic species. Replacement by open vegetation and overall reductions are a considerable risk for closed forest, threatening Amazon and Atlantic forest biomes. Here, we evidence the impacts of climate change on Brazilian biomes, and draw attention to the necessity for management and attenuation plans to guarantee the future of Brazilian biodiversity.

Axially grooved heat pipe study

NASA Technical Reports Server (NTRS)

1977-01-01

A technology evaluation study on axially grooved heat pipes is presented. The state-of-the-art is reviewed and present and future requirements are identified. Analytical models, the Groove Analysis Program (GAP) and a closed form solution, were developed to facilitate parametric performance evaluations. GAP provides a numerical solution of the differential equations which govern the hydrodynamic flow. The model accounts for liquid recession, liquid/vapor shear interaction, puddle flow as well as laminar and turbulent vapor flow conditions. The closed form solution was developed to reduce computation time and complexity in parametric evaluations. It is applicable to laminar and ideal charge conditions, liquid/vapor shear interaction, and an empirical liquid flow factor which accounts for groove geometry and liquid recession effects. The validity of the closed form solution is verified by comparison with GAP predictions and measured data.

A Monte Carlo Risk Analysis of Life Cycle Cost Prediction.

DTIC Science & Technology

1975-09-01

process which occurs with each FLU failure. With this in mind there is no alternative other than the binomial distribution. 24 GOR/SM/75D-6 With all of...Weibull distribution of failures as selected by user. For each failure of the ith FLU, the model then samples from the binomial distribution to deter- mine...which is sampled from the binomial . Neither of the two conditions for normality are met, i.e., that RTS Ie close to .5 and the number of samples close

Direct numerical simulation of turbulent H2-O2 combustion using reduced chemistry

NASA Technical Reports Server (NTRS)

Montgomery, Christopher J.; Kosaly, George; Riley, James J.

1993-01-01

Results of direct numerical simulations of hydrogen-oxygen combustion using a partial-equilibrium chemistry scheme in constant density, decaying, isotropic turbulence are reported. The simulations qualitatively reproduce many features of experimental results, such as superequilibrium radical species mole fractions, with temperature and major species mole fractions closer to chemical equilibrium. It was also observed that the peak reaction rates occur in narrow zones where the stoichiometric surface intersects regions of high scalar dissipation, as might be expected for combustion conditions close to chemical equilibrium. Another finding was that high OH mole fraction correspond more closely to the stoichiometric surface than to areas of high reaction rate for conditions of the simulations. Simulation results were compared to predictions of the Conditional Moment Closure model. This model was found to give good results for all quantities of interest when the conditionally averaged scalar dissipation was used in the prediction. When the nonconditioned average dissipation was used, the predictions compared well to the simulations for most of the species and temperature, but not for the reaction rate. The comparison would be expected to improve for higher Reynolds number flows, however.

Microstructure based model for sound absorption predictions of perforated closed-cell metallic foams.

PubMed

Chevillotte, Fabien; Perrot, Camille; Panneton, Raymond

2010-10-01

Closed-cell metallic foams are known for their rigidity, lightness, thermal conductivity as well as their low production cost compared to open-cell metallic foams. However, they are also poor sound absorbers. Similarly to a rigid solid, a method to enhance their sound absorption is to perforate them. This method has shown good preliminary results but has not yet been analyzed from a microstructure point of view. The objective of this work is to better understand how perforations interact with closed-cell foam microstructure and how it modifies the sound absorption of the foam. A simple two-dimensional microstructural model of the perforated closed-cell metallic foam is presented and numerically solved. A rough three-dimensional conversion of the two-dimensional results is proposed. The results obtained with the calculation method show that the perforated closed-cell foam behaves similarly to a perforated solid; however, its sound absorption is modulated by the foam microstructure, and most particularly by the diameters of both perforation and pore. A comparison with measurements demonstrates that the proposed calculation method yields realistic trends. Some design guides are also proposed.

Kinetics of Methane Production from Swine Manure and Buffalo Manure.

PubMed

Sun, Chen; Cao, Weixing; Liu, Ronghou

2015-10-01

The degradation kinetics of swine and buffalo manure for methane production was investigated. Six kinetic models were employed to describe the corresponding experimental data. These models were evaluated by two statistical measurements, which were root mean square prediction error (RMSPE) and Akaike's information criterion (AIC). The results showed that the logistic and Fitzhugh models could predict the experimental data very well for the digestion of swine and buffalo manure, respectively. The predicted methane yield potential for swine and buffalo manure was 487.9 and 340.4 mL CH4/g volatile solid (VS), respectively, which was close to experimental values, when the digestion temperature was 36 ± 1 °C in the biochemical methane potential assays. Besides, the rate constant revealed that swine manure had a much faster methane production rate than buffalo manure.

Thermokinetic Modeling of Phase Transformation in the Laser Powder Deposition Process

NASA Astrophysics Data System (ADS)

Foroozmehr, Ehsan; Kovacevic, Radovan

2009-08-01

A finite element model coupled with a thermokinetic model is developed to predict the phase transformation of the laser deposition of AISI 4140 on a substrate with the same material. Four different deposition patterns, long-bead, short-bead, spiral-in, and spiral-out, are used to cover a similar area. Using a finite element model, the temperature history of the laser powder deposition (LPD) process is determined. The martensite transformation as well as martensite tempering is considered to calculate the final fraction of martensite, ferrite, cementite, ɛ-carbide, and retained austenite. Comparing the surface hardness topography of different patterns reveals that path planning is a critical parameter in laser surface modification. The predicted results are in a close agreement with the experimental results.

SOYCHMBR.I - A model designed for the study of plant growth in a closed chamber

NASA Technical Reports Server (NTRS)

Reinhold, C.

1982-01-01

The analytical model SOYCHMBER.I, an update and alteration of the SOYMOD/OARDC model, for describing the total processes experienced by a plant in a controlled mass environment is outlined. The model is intended for use with growth chambers for examining plant growth in a completely controlled environment, leading toward a data base for the design of spacecraft food supply systems. SOYCHMBER.I accounts for the assimilation, respiration, and partitioning of photosynthate and nitrogen compounds among leaves, stems, roots, and potentially, flowers of the soybean plant. The derivation of the governing equations is traced, and the results of the prediction of CO2 dynamics for a seven day experiment with rice in a closed chamber are reported, together with data from three model runs for soybean. It is concluded that the model needs expansion to account for factors such as relative humidity.

On the nature of the cosmic ray positron spectrum

NASA Technical Reports Server (NTRS)

Protheroe, R. J.

1981-01-01

A calculation was made of the flux of secondary positrons above 100 MeV expected for various propagation models. The models investigated were the leaky box or homogeneous model, a disk halo diffusion model, a dynamical halo model, and the closed galaxy model. In each case the parameters of these models were adjusted for agreement with the observed secondary or primary ratios and Be 10 abundance. The positron flux predicted for these models was compared with the available data. The possibility of a primary positron component was considered.

Comparison of ionosphere characteristic parameters obtained by ionosonde with IRI-2007 model over Southeast Asia

NASA Astrophysics Data System (ADS)

Wichaipanich, N.; Supnithi, P.; Tsugawa, T.; Maruyama, T.; Nagatsuma, T.

2013-11-01

In this work, the foF2 and hmF2 parameters at the conjugate points near the magnetic equator of Southeast Asia are studied and compared with the International Reference Ionosphere (IRI) model. Three ionosondes are installed nearly along the magnetic meridian of 100°E; one at the magnetic equator, namely Chumphon (10.72°N, 99.37°E, dip angle 3.0°N), and the other two at the magnetic conjugate points, namely Chiang Mai (18.76°N, 98.93°E, dip angle 12.7°N) and Kototabang (0.2°S, 100.30°E, dip angle 10.1°S). The monthly hourly medians of the foF2 and hmF2 parameters are calculated and compared with the predictions obtained from the IRI-2007 model from January 2004 to February 2007. Our results show that: the variations of foF2 and hmF2 predicted by the IRI-2007 model generally show the similar feature to the observed data. Both parameters generally show better agreement with the IRI predictions during daytime than during nighttime. For foF2, most of the results show that the IRI model overestimates the observed foF2 at the magnetic equator (Chumphon), underestimates at the northern crest (Chiang Mai) and is close to the measured ones at the southern crest of the EIA (Kototabang). For hmF2, the predicted hmF2 values are close to the hmF2(M3000F2OBS) during daytime. During nighttime, the IRI model gives the underestimation at the magnetic equator and the overestimation at both EIA crests. The results are important for the future improvements of the IRI model for foF2 and hmF2 over Southeast Asia region.

Effects of number of training generations on genomic prediction for various traits in a layer chicken population.

PubMed

Weng, Ziqing; Wolc, Anna; Shen, Xia; Fernando, Rohan L; Dekkers, Jack C M; Arango, Jesus; Settar, Petek; Fulton, Janet E; O'Sullivan, Neil P; Garrick, Dorian J

2016-03-19

Genomic estimated breeding values (GEBV) based on single nucleotide polymorphism (SNP) genotypes are widely used in animal improvement programs. It is typically assumed that the larger the number of animals is in the training set, the higher is the prediction accuracy of GEBV. The aim of this study was to quantify genomic prediction accuracy depending on the number of ancestral generations included in the training set, and to determine the optimal number of training generations for different traits in an elite layer breeding line. Phenotypic records for 16 traits on 17,793 birds were used. All parents and some selection candidates from nine non-overlapping generations were genotyped for 23,098 segregating SNPs. An animal model with pedigree relationships (PBLUP) and the BayesB genomic prediction model were applied to predict EBV or GEBV at each validation generation (progeny of the most recent training generation) based on varying numbers of immediately preceding ancestral generations. Prediction accuracy of EBV or GEBV was assessed as the correlation between EBV and phenotypes adjusted for fixed effects, divided by the square root of trait heritability. The optimal number of training generations that resulted in the greatest prediction accuracy of GEBV was determined for each trait. The relationship between optimal number of training generations and heritability was investigated. On average, accuracies were higher with the BayesB model than with PBLUP. Prediction accuracies of GEBV increased as the number of closely-related ancestral generations included in the training set increased, but reached an asymptote or slightly decreased when distant ancestral generations were used in the training set. The optimal number of training generations was 4 or more for high heritability traits but less than that for low heritability traits. For less heritable traits, limiting the training datasets to individuals closely related to the validation population resulted in the best predictions. The effect of adding distant ancestral generations in the training set on prediction accuracy differed between traits and the optimal number of necessary training generations is associated with the heritability of traits.

Self-consistent core-pedestal transport simulations with neural network accelerated models

DOE PAGES

Meneghini, Orso; Smith, Sterling P.; Snyder, Philip B.; ...

2017-07-12

Fusion whole device modeling simulations require comprehensive models that are simultaneously physically accurate, fast, robust, and predictive. In this paper we describe the development of two neural-network (NN) based models as a means to perform a snon-linear multivariate regression of theory-based models for the core turbulent transport fluxes, and the pedestal structure. Specifically, we find that a NN-based approach can be used to consistently reproduce the results of the TGLF and EPED1 theory-based models over a broad range of plasma regimes, and with a computational speedup of several orders of magnitudes. These models are then integrated into a predictive workflowmore » that allows prediction with self-consistent core-pedestal coupling of the kinetic profiles within the last closed flux surface of the plasma. Finally, the NN paradigm is capable of breaking the speed-accuracy trade-off that is expected of traditional numerical physics models, and can provide the missing link towards self-consistent coupled core-pedestal whole device modeling simulations that are physically accurate and yet take only seconds to run.« less

Self-consistent core-pedestal transport simulations with neural network accelerated models

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

Meneghini, Orso; Smith, Sterling P.; Snyder, Philip B.

Fusion whole device modeling simulations require comprehensive models that are simultaneously physically accurate, fast, robust, and predictive. In this paper we describe the development of two neural-network (NN) based models as a means to perform a snon-linear multivariate regression of theory-based models for the core turbulent transport fluxes, and the pedestal structure. Specifically, we find that a NN-based approach can be used to consistently reproduce the results of the TGLF and EPED1 theory-based models over a broad range of plasma regimes, and with a computational speedup of several orders of magnitudes. These models are then integrated into a predictive workflowmore » that allows prediction with self-consistent core-pedestal coupling of the kinetic profiles within the last closed flux surface of the plasma. Finally, the NN paradigm is capable of breaking the speed-accuracy trade-off that is expected of traditional numerical physics models, and can provide the missing link towards self-consistent coupled core-pedestal whole device modeling simulations that are physically accurate and yet take only seconds to run.« less

Self-consistent core-pedestal transport simulations with neural network accelerated models

NASA Astrophysics Data System (ADS)

Meneghini, O.; Smith, S. P.; Snyder, P. B.; Staebler, G. M.; Candy, J.; Belli, E.; Lao, L.; Kostuk, M.; Luce, T.; Luda, T.; Park, J. M.; Poli, F.

2017-08-01

Fusion whole device modeling simulations require comprehensive models that are simultaneously physically accurate, fast, robust, and predictive. In this paper we describe the development of two neural-network (NN) based models as a means to perform a snon-linear multivariate regression of theory-based models for the core turbulent transport fluxes, and the pedestal structure. Specifically, we find that a NN-based approach can be used to consistently reproduce the results of the TGLF and EPED1 theory-based models over a broad range of plasma regimes, and with a computational speedup of several orders of magnitudes. These models are then integrated into a predictive workflow that allows prediction with self-consistent core-pedestal coupling of the kinetic profiles within the last closed flux surface of the plasma. The NN paradigm is capable of breaking the speed-accuracy trade-off that is expected of traditional numerical physics models, and can provide the missing link towards self-consistent coupled core-pedestal whole device modeling simulations that are physically accurate and yet take only seconds to run.

A neural network based computational model to predict the output power of different types of photovoltaic cells.

PubMed

Xiao, WenBo; Nazario, Gina; Wu, HuaMing; Zhang, HuaMing; Cheng, Feng

2017-01-01

In this article, we introduced an artificial neural network (ANN) based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-), multi-crystalline (multi-), and amorphous (amor-) crystalline. The prediction results are very close to the experimental data, and were also influenced by numbers of hidden neurons. The order of the solar generation power output influenced by the external conditions from smallest to biggest is: multi-, mono-, and amor- crystalline silicon cells. In addition, the dependences of power prediction on the number of hidden neurons were studied. For multi- and amorphous crystalline cell, three or four hidden layer units resulted in the high correlation coefficient and low MSEs. For mono-crystalline cell, the best results were achieved at the hidden layer unit of 8.

MELiSSA Food Characterization general approach and current status

NASA Astrophysics Data System (ADS)

Weihreter, Martin; Chaerle, Laury; Secco, Benjamin; Molders, Katrien; van der Straeten, Dominique; Duliere, Eric; Pieters, Serge; Maclean, Heather; Dochain, Denis; Quinet, Muriel; Lutts, Stanley; Graham, Thomas; Stasiak, Michael; Rondeau Vuk, Theresa; Zheng, Youbin; Dixon, Mike; Laniau, Martine; Larreture, Alain; Timsit, Michel; Aronne, Giovanna; Barbieri, Giancarlo; Buonomo, Roberta; Veronica; Paradiso, Roberta; de Pascale, Stafania; Galbiati, Massimo; Troia, A. R.; Nobili, Matteo; Bucchieri, Lorenzo; Page, Valérie; Feller, Urs; Lasseur, Christophe

Higher plants play an important role in closed ecological life support systems as oxygen pro-ducers, carbon dioxide and water recyclers, and as a food source. For an integration of higher plant chambers into the MELiSSA (Micro Ecological Life Support System Alternative) loop, a detailed characterization and optimization of the full food production and preparation chain is needed. This implies the prediction and control of the nutritional quality of the final products consumed by the crew, the prediction of the wastes quality and quantity produced along the chain for further waste treatment (MELiSSA waste treatment) and the optimization of overall efficiencies. To reach this goal several issues have to be studied in an integrated manner: the physiological responses of crops to a range of environmental parameters, crop yield efficiencies and respective ratio and composition of edible and inedible biomass, the processability and storability of the produced food and last but not least composition of wastes in view of further degradation (fiber content). Within the Food Characterization (FC) project several compar-ative plant growth bench tests were carried out to obtain preliminary data regarding these aspects. Four pre-selected cultivars of each of the four energy-rich crops with worldwide usage -wheat, durum wheat, potato and soybean -were grown under well-characterized environmental conditions. The different cultivars of each species are screened for their performance in view of a closed loop application by parameter ranking. This comprises the characterization of edi-ble/inedible biomass ratio, nutritional quality, processability and overall performance under the specific conditions of hydroponic cultivation and artificial illumination. A second closely linked goal of the FC project is to develop a mechanistic physiological plant model, which will ease the integration of higher plants compartments in the MELiSSA concept by virtue of its predictive abilities. Available MELiSSA closed environment crop growth data were used to develop a first photosynthetic model representing the basic carbon fixation mechanisms. This model will be further elaborated in the course of this study to predict yield, oxygen production and transpi-ration. As an ultimate goal the model is intended to simulate the composition of the different plant organs (root, shoot, fruit/seed or tuber) for each crop under various conditions. For the validation of this model an extensive amount of data sets are needed. Current plant growth bench test setups will provide part of the required data. To gain more precise and detailed datasets, a highly closed plant growth chamber (Plant Characterization Unit, PCU) is under development. The PCU will provide accurate mass balances for carbon, water, oxygen and other elements with statistical reliability. This reliability is achieved through a high degree of closure and environment homogeneity. The PCU will also provide data for the above described plant characterization studies. The general work approach, the current status and future steps will be illustrated.

Boosting Learning Algorithm for Stock Price Forecasting

NASA Astrophysics Data System (ADS)

Wang, Chengzhang; Bai, Xiaoming

2018-03-01

To tackle complexity and uncertainty of stock market behavior, more studies have introduced machine learning algorithms to forecast stock price. ANN (artificial neural network) is one of the most successful and promising applications. We propose a boosting-ANN model in this paper to predict the stock close price. On the basis of boosting theory, multiple weak predicting machines, i.e. ANNs, are assembled to build a stronger predictor, i.e. boosting-ANN model. New error criteria of the weak studying machine and rules of weights updating are adopted in this study. We select technical factors from financial markets as forecasting input variables. Final results demonstrate the boosting-ANN model works better than other ones for stock price forecasting.

Incorporating photon recycling into the analytical drift-diffusion model of high efficiency solar cells

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

Lumb, Matthew P.; Naval Research Laboratory, Washington, DC 20375; Steiner, Myles A.

The analytical drift-diffusion formalism is able to accurately simulate a wide range of solar cell architectures and was recently extended to include those with back surface reflectors. However, as solar cells approach the limits of material quality, photon recycling effects become increasingly important in predicting the behavior of these cells. In particular, the minority carrier diffusion length is significantly affected by the photon recycling, with consequences for the solar cell performance. In this paper, we outline an approach to account for photon recycling in the analytical Hovel model and compare analytical model predictions to GaAs-based experimental devices operating close tomore » the fundamental efficiency limit.« less

Haplotype-Based Genome-Wide Prediction Models Exploit Local Epistatic Interactions Among Markers

PubMed Central

Jiang, Yong; Schmidt, Renate H.; Reif, Jochen C.

2018-01-01

Genome-wide prediction approaches represent versatile tools for the analysis and prediction of complex traits. Mostly they rely on marker-based information, but scenarios have been reported in which models capitalizing on closely-linked markers that were combined into haplotypes outperformed marker-based models. Detailed comparisons were undertaken to reveal under which circumstances haplotype-based genome-wide prediction models are superior to marker-based models. Specifically, it was of interest to analyze whether and how haplotype-based models may take local epistatic effects between markers into account. Assuming that populations consisted of fully homozygous individuals, a marker-based model in which local epistatic effects inside haplotype blocks were exploited (LEGBLUP) was linearly transformable into a haplotype-based model (HGBLUP). This theoretical derivation formally revealed that haplotype-based genome-wide prediction models capitalize on local epistatic effects among markers. Simulation studies corroborated this finding. Due to its computational efficiency the HGBLUP model promises to be an interesting tool for studies in which ultra-high-density SNP data sets are studied. Applying the HGBLUP model to empirical data sets revealed higher prediction accuracies than for marker-based models for both traits studied using a mouse panel. In contrast, only a small subset of the traits analyzed in crop populations showed such a benefit. Cases in which higher prediction accuracies are observed for HGBLUP than for marker-based models are expected to be of immediate relevance for breeders, due to the tight linkage a beneficial haplotype will be preserved for many generations. In this respect the inheritance of local epistatic effects very much resembles the one of additive effects. PMID:29549092

Haplotype-Based Genome-Wide Prediction Models Exploit Local Epistatic Interactions Among Markers.

PubMed

Jiang, Yong; Schmidt, Renate H; Reif, Jochen C

2018-05-04

Genome-wide prediction approaches represent versatile tools for the analysis and prediction of complex traits. Mostly they rely on marker-based information, but scenarios have been reported in which models capitalizing on closely-linked markers that were combined into haplotypes outperformed marker-based models. Detailed comparisons were undertaken to reveal under which circumstances haplotype-based genome-wide prediction models are superior to marker-based models. Specifically, it was of interest to analyze whether and how haplotype-based models may take local epistatic effects between markers into account. Assuming that populations consisted of fully homozygous individuals, a marker-based model in which local epistatic effects inside haplotype blocks were exploited (LEGBLUP) was linearly transformable into a haplotype-based model (HGBLUP). This theoretical derivation formally revealed that haplotype-based genome-wide prediction models capitalize on local epistatic effects among markers. Simulation studies corroborated this finding. Due to its computational efficiency the HGBLUP model promises to be an interesting tool for studies in which ultra-high-density SNP data sets are studied. Applying the HGBLUP model to empirical data sets revealed higher prediction accuracies than for marker-based models for both traits studied using a mouse panel. In contrast, only a small subset of the traits analyzed in crop populations showed such a benefit. Cases in which higher prediction accuracies are observed for HGBLUP than for marker-based models are expected to be of immediate relevance for breeders, due to the tight linkage a beneficial haplotype will be preserved for many generations. In this respect the inheritance of local epistatic effects very much resembles the one of additive effects. Copyright © 2018 Jiang et al.

Simple model for piezoelectric ceramic/polymer 1-3 composites used in ultrasonic transducer applications.

PubMed

Chan, H W; Unsworth, J

1989-01-01

A theoretical model is presented for combining parameters of 1-3 ultrasonic composite materials in order to predict ultrasonic characteristics such as velocity, acoustic impedance, electromechanical coupling factor, and piezoelectric coefficients. Hence, the model allows the estimation of resonance frequencies of 1-3 composite transducers. This model has been extended to cover more material parameters, and they are compared to experimental results up to PZT volume fraction nu of 0.8. The model covers calculation of piezoelectric charge constants d(33) and d(31). Values are found to be in good agreement with experimental results obtained for PZT 7A/Araldite D 1-3 composites. The acoustic velocity, acoustic impedance, and electromechanical coupling factor are predicted and found to be close to the values determined experimentally.

Predictions of Poisson's ratio in cross-ply laminates containing matrix cracks and delaminations

NASA Technical Reports Server (NTRS)

Harris, Charles E.; Allen, David H.; Nottorf, Eric W.

1989-01-01

A damage-dependent constitutive model for laminated composites has been developed for the combined damage modes of matrix cracks and delaminations. The model is based on the concept of continuum damage mechanics and uses second-order tensor valued internal state variables to represent each mode of damage. The internal state variables are defined as the local volume average of the relative crack face displacements. Since the local volume for delaminations is specified at the laminate level, the constitutive model takes the form of laminate analysis equations modified by the internal state variables. Model implementation is demonstrated for the laminate engineering modulus E(x) and Poisson's ratio nu(xy) of quasi-isotropic and cross-ply laminates. The model predictions are in close agreement to experimental results obtained for graphite/epoxy laminates.

Predicting concrete corrosion of sewers using artificial neural network.

PubMed

Jiang, Guangming; Keller, Jurg; Bond, Philip L; Yuan, Zhiguo

2016-04-01

Corrosion is often a major failure mechanism for concrete sewers and under such circumstances the sewer service life is largely determined by the progression of microbially induced concrete corrosion. The modelling of sewer processes has become possible due to the improved understanding of in-sewer transformation. Recent systematic studies about the correlation between the corrosion processes and sewer environment factors should be utilized to improve the prediction capability of service life by sewer models. This paper presents an artificial neural network (ANN)-based approach for modelling the concrete corrosion processes in sewers. The approach included predicting the time for the corrosion to initiate and then predicting the corrosion rate after the initiation period. The ANN model was trained and validated with long-term (4.5 years) corrosion data obtained in laboratory corrosion chambers, and further verified with field measurements in real sewers across Australia. The trained model estimated the corrosion initiation time and corrosion rates very close to those measured in Australian sewers. The ANN model performed better than a multiple regression model also developed on the same dataset. Additionally, the ANN model can serve as a prediction framework for sewer service life, which can be progressively improved and expanded by including corrosion rates measured in different sewer conditions. Furthermore, the proposed methodology holds promise to facilitate the construction of analytical models associated with corrosion processes of concrete sewers. Copyright © 2016 Elsevier Ltd. All rights reserved.

Snow on Sea Ice Workshop - An Icy Meeting of the Minds: Modelers and Measurers

DTIC Science & Technology

2015-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Snow on Sea Ice Workshop - An Icy Meeting of the Minds...workshop was to promote more seamless and better integration between measurements and modeling of snow on sea ice , thereby improving our predictive...capabilities for sea ice . OBJECTIVES The key objective was to improve the ability of modelers and measurers work together closely. To that end, we

Improved Modeling of Midlatitude D-Region Ionospheric Absorption of High Frequency Radio Signals During Solar X-Ray Flares

DTIC Science & Technology

2009-06-01

a physics-based model which calculates mid - latitude ionospheric electron and ion density profiles for prediction of HF propagation and absorption...greatest in the summer due to longer periods of daylight and ionization. For times not close to sunrise or sunset, mid - latitude ionospheric ...IMPROVED MODELING OF MIDLATITUDE D-REGION IONOSPHERIC ABSORPTION OF HIGH FREQUENCY RADIO SIGNALS DURING SOLAR X-RAY FLARES 1

Predicting Space Weather Effects on Close Approach Events

NASA Technical Reports Server (NTRS)

Hejduk, Matthew D.; Newman, Lauri K.; Besser, Rebecca L.; Pachura, Daniel A.

2015-01-01

The NASA Robotic Conjunction Assessment Risk Analysis (CARA) team sends ephemeris data to the Joint Space Operations Center (JSpOC) for conjunction assessment screening against the JSpOC high accuracy catalog and then assesses risk posed to protected assets from predicted close approaches. Since most spacecraft supported by the CARA team are located in LEO orbits, atmospheric drag is the primary source of state estimate uncertainty. Drag magnitude and uncertainty is directly governed by atmospheric density and thus space weather. At present the actual effect of space weather on atmospheric density cannot be accurately predicted because most atmospheric density models are empirical in nature, which do not perform well in prediction. The Jacchia-Bowman-HASDM 2009 (JBH09) atmospheric density model used at the JSpOC employs a solar storm active compensation feature that predicts storm sizes and arrival times and thus the resulting neutral density alterations. With this feature, estimation errors can occur in either direction (i.e., over- or under-estimation of density and thus drag). Although the exact effect of a solar storm on atmospheric drag cannot be determined, one can explore the effects of JBH09 model error on conjuncting objects' trajectories to determine if a conjunction is likely to become riskier, less risky, or pass unaffected. The CARA team has constructed a Space Weather Trade-Space tool that systematically alters the drag situation for the conjuncting objects and recalculates the probability of collision for each case to determine the range of possible effects on the collision risk. In addition to a review of the theory and the particulars of the tool, the different types of observed output will be explained, along with statistics of their frequency.

Performance impact of stop lists and morphological decomposition on word-word corpus-based semantic space models.

PubMed

Keith, Jeff; Westbury, Chris; Goldman, James

2015-09-01

Corpus-based semantic space models, which primarily rely on lexical co-occurrence statistics, have proven effective in modeling and predicting human behavior in a number of experimental paradigms that explore semantic memory representation. The most widely studied extant models, however, are strongly influenced by orthographic word frequency (e.g., Shaoul & Westbury, Behavior Research Methods, 38, 190-195, 2006). This has the implication that high-frequency closed-class words can potentially bias co-occurrence statistics. Because these closed-class words are purported to carry primarily syntactic, rather than semantic, information, the performance of corpus-based semantic space models may be improved by excluding closed-class words (using stop lists) from co-occurrence statistics, while retaining their syntactic information through other means (e.g., part-of-speech tagging and/or affixes from inflected word forms). Additionally, very little work has been done to explore the effect of employing morphological decomposition on the inflected forms of words in corpora prior to compiling co-occurrence statistics, despite (controversial) evidence that humans perform early morphological decomposition in semantic processing. In this study, we explored the impact of these factors on corpus-based semantic space models. From this study, morphological decomposition appears to significantly improve performance in word-word co-occurrence semantic space models, providing some support for the claim that sublexical information-specifically, word morphology-plays a role in lexical semantic processing. An overall decrease in performance was observed in models employing stop lists (e.g., excluding closed-class words). Furthermore, we found some evidence that weakens the claim that closed-class words supply primarily syntactic information in word-word co-occurrence semantic space models.

Estimation of genomic prediction accuracy from reference populations with varying degrees of relationship.

PubMed

Lee, S Hong; Clark, Sam; van der Werf, Julius H J

2017-01-01

Genomic prediction is emerging in a wide range of fields including animal and plant breeding, risk prediction in human precision medicine and forensic. It is desirable to establish a theoretical framework for genomic prediction accuracy when the reference data consists of information sources with varying degrees of relationship to the target individuals. A reference set can contain both close and distant relatives as well as 'unrelated' individuals from the wider population in the genomic prediction. The various sources of information were modeled as different populations with different effective population sizes (Ne). Both the effective number of chromosome segments (Me) and Ne are considered to be a function of the data used for prediction. We validate our theory with analyses of simulated as well as real data, and illustrate that the variation in genomic relationships with the target is a predictor of the information content of the reference set. With a similar amount of data available for each source, we show that close relatives can have a substantially larger effect on genomic prediction accuracy than lesser related individuals. We also illustrate that when prediction relies on closer relatives, there is less improvement in prediction accuracy with an increase in training data or marker panel density. We release software that can estimate the expected prediction accuracy and power when combining different reference sources with various degrees of relationship to the target, which is useful when planning genomic prediction (before or after collecting data) in animal, plant and human genetics.

Investigation to advance prediction techniques of the low-speed aerodynamics of V/STOL aircraft

NASA Technical Reports Server (NTRS)

Maskew, B.; Strash, D.; Nathman, J.; Dvorak, F. A.

1985-01-01

A computer program, VSAERO, has been applied to a number of V/STOL configurations with a view to advancing prediction techniques for the low-speed aerodynamic characteristics. The program couples a low-order panel method with surface streamline calculation and integral boundary layer procedures. The panel method--which uses piecewise constant source and doublet panels-includes an iterative procedure for wake shape and models boundary layer displacement effect using the source transpiration technique. Certain improvements to a basic vortex tube jet model were installed in the code prior to evaluation. Very promising results were obtained for surface pressures near a jet issuing at 90 deg from a flat plate. A solid core model was used in the initial part of the jet with a simple entrainment model. Preliminary representation of the downstream separation zone significantly improve the correlation. The program accurately predicted the pressure distribution inside the inlet on the Grumman 698-411 design at a range of flight conditions. Furthermore, coupled viscous/potential flow calculations gave very close correlation with experimentally determined operational boundaries dictated by the onset of separation inside the inlet. Experimentally observed degradation of these operational boundaries between nacelle-alone tests and tests on the full configuration were also indicated by the calculation. Application of the program to the General Dynamics STOL fighter design were equally encouraging. Very close agreement was observed between experiment and calculation for the effects of power on pressure distribution, lift and lift curve slope.

Computation of Alfvèn eigenmode stability and saturation through a reduced fast ion transport model in the TRANSP tokamak transport code

NASA Astrophysics Data System (ADS)

Podestà, M.; Gorelenkova, M.; Gorelenkov, N. N.; White, R. B.

2017-09-01

Alfvénic instabilities (AEs) are well known as a potential cause of enhanced fast ion transport in fusion devices. Given a specific plasma scenario, quantitative predictions of (i) expected unstable AE spectrum and (ii) resulting fast ion transport are required to prevent or mitigate the AE-induced degradation in fusion performance. Reduced models are becoming an attractive tool to analyze existing scenarios as well as for scenario prediction in time-dependent simulations. In this work, a neutral beam heated NSTX discharge is used as reference to illustrate the potential of a reduced fast ion transport model, known as kick model, that has been recently implemented for interpretive and predictive analysis within the framework of the time-dependent tokamak transport code TRANSP. Predictive capabilities for AE stability and saturation amplitude are first assessed, based on given thermal plasma profiles only. Predictions are then compared to experimental results, and the interpretive capabilities of the model further discussed. Overall, the reduced model captures the main properties of the instabilities and associated effects on the fast ion population. Additional information from the actual experiment enables further tuning of the model’s parameters to achieve a close match with measurements.

I-TASSER: fully automated protein structure prediction in CASP8.

PubMed

Zhang, Yang

2009-01-01

The I-TASSER algorithm for 3D protein structure prediction was tested in CASP8, with the procedure fully automated in both the Server and Human sections. The quality of the server models is close to that of human ones but the human predictions incorporate more diverse templates from other servers which improve the human predictions in some of the distant homology targets. For the first time, the sequence-based contact predictions from machine learning techniques are found helpful for both template-based modeling (TBM) and template-free modeling (FM). In TBM, although the accuracy of the sequence based contact predictions is on average lower than that from template-based ones, the novel contacts in the sequence-based predictions, which are complementary to the threading templates in the weakly or unaligned regions, are important to improve the global and local packing in these regions. Moreover, the newly developed atomic structural refinement algorithm was tested in CASP8 and found to improve the hydrogen-bonding networks and the overall TM-score, which is mainly due to its ability of removing steric clashes so that the models can be generated from cluster centroids. Nevertheless, one of the major issues of the I-TASSER pipeline is the model selection where the best models could not be appropriately recognized when the correct templates are detected only by the minority of the threading algorithms. There are also problems related with domain-splitting and mirror image recognition which mainly influences the performance of I-TASSER modeling in the FM-based structure predictions. Copyright 2009 Wiley-Liss, Inc.

Single-layer model to predict the source/sink behavior of diffusion-controlled building materials.

PubMed

Kumar, Deept; Little, John C

2003-09-01

Building materials may act as both sources of and sinks forvolatile organic compounds (VOCs) in indoor air. A strategy to characterize the rate of absorption and desorption of VOCs by diffusion-controlled building materials is validated. A previously developed model that predicts mass transfer between a flat slab of material and the well-mixed air within a chamber or room is extended. The generalized model allows a nonuniform initial material-phase concentration and a transient influent gas-phase concentration to be simultaneously considered. An analytical solution to the more general model is developed. Experimental data are obtained by placing samples of vinyl flooring inside a small stainless steel chamber and exposing them to absorption/desorption cycles of n-dodecane and phenol. Measured values for the material-air partition coefficient and the material-phase diffusion coefficient were obtained previously in a series of completely independent experiments. The a priori model predictions are in close agreement with the observed experimental data.

Elements of a predictive model for determining beach closures on a real time basis: the case of 63rd Street Beach Chicago

USGS Publications Warehouse

Olyphant, Greg A.; Whitman, Richard L.

2004-01-01

Data on hydrometeorological conditions and E. coli concentration were simultaneously collected on 57 occasions during the summer of 2000 at 63rd Street Beach, Chicago, Illinois. The data were used to identify and calibrate a statistical regression model aimed at predicting when the bacterial concentration of the beach water was above or below the level considered safe for full body contact. A wide range of hydrological, meteorological, and water quality variables were evaluated as possible predictive variables. These included wind speed and direction, incoming solar radiation (insolation), various time frames of rainfall, air temperature, lake stage and wave height, and water temperature, specific conductance, dissolved oxygen, pH, and turbidity. The best-fit model combined real-time measurements of wind direction and speed (onshore component of resultant wind vector), rainfall, insolation, lake stage, water temperature and turbidity to predict the geometric mean E.coliconcentration in the swimming zone of the beach. The model, which contained both additive and multiplicative (interaction) terms, accounted for 71% of the observed variability in the log E. coliconcentrations. A comparison between model predictions of when the beach should be closed and when the actualbacterial concentrations were above or below the 235 cfu 100 ml-1 threshold value, indicated that the model accurately predicted openingsversus closures 88% of the time.

One-dimensional and two-dimensional hydrodynamic modelling derived flow properties: Impacts on aquatic habitat quality predictions

Treesearch

Rohan Benjankar; Daniele Tonina; James McKean

2014-01-01

Studies of the effects of hydrodynamic model dimensionality on simulated flow properties and derived quantities such as aquatic habitat quality are limited. It is important to close this knowledge gap especially now that entire river networks can be mapped at the microhabitat scale due to the advent of point-cloud techniques. This study compares flow properties, such...

Human grief: a model for prediction and intervention.

PubMed

Bugen, L A

1977-04-01

The prevalent approach to understanding of and clinical intervention in the process of mourning employs a model based on stages of bereavement. This paper suggests a theoretical conception that is not tied to a fixed order of emotional states. Two dimensions--closeness of relationship and mourner's perception of preventability of the death--are identified as prime predictors of the intensity and duration of bereavement.

El Nino winners and losers declared

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

Kerr, R.A.

Last spring human forecasters thought they saw signs of an imminent warming of the tropical Pacific, a classic El Nino, that could wreak havoc with weather around the globe. Researchers running computer models, on the other hand, saw a slight warming but not enough for an El Nino. The modelers were right. The season for El Ninos has ended and nothing happened. Since the models came online about 5 years ago, there have been two contests to predict El Ninos, which occur every 3 to 7 years, and the models have won both. The models are still experimental, but themore » general feeling is that they're indicating the right trends. The prospect of having reliable El Nino prediction models is good news beyond the small coterie of tropical Pacific specialists. Worldwide weather patterns are closely tied to El Nino cycles.« less

High Reynolds number turbulence model of rotating shear flows

NASA Astrophysics Data System (ADS)

Masuda, S.; Ariga, I.; Koyama, H. S.

1983-09-01

A Reynolds stress closure model for rotating turbulent shear flows is developed. Special attention is paid to keeping the model constants independent of rotation. First, general forms of the model of a Reynolds stress equation and a dissipation rate equation are derived, the only restrictions of which are high Reynolds number and incompressibility. The model equations are then applied to two-dimensional equilibrium boundary layers and the effects of Coriolis acceleration on turbulence structures are discussed. Comparisons with the experimental data and with previous results in other external force fields show that there exists a very close analogy between centrifugal, buoyancy and Coriolis force fields. Finally, the model is applied to predict the two-dimensional boundary layers on rotating plane walls. Comparisons with existing data confirmed its capability of predicting mean and turbulent quantities without employing any empirical relations in rotating fields.

Hydrodynamic models for slurry bubble column reactors

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

Gidaspow, D.

1995-12-31

The objective of this investigation is to convert a {open_quotes}learning gas-solid-liquid{close_quotes} fluidization model into a predictive design model. This model is capable of predicting local gas, liquid and solids hold-ups and the basic flow regimes: the uniform bubbling, the industrially practical churn-turbulent (bubble coalescence) and the slugging regimes. Current reactor models incorrectly assume that the gas and the particle hold-ups (volume fractions) are uniform in the reactor. They must be given in terms of empirical correlations determined under conditions that radically differ from reactor operation. In the proposed hydrodynamic approach these hold-ups are computed from separate phase momentum balances. Furthermore,more » the kinetic theory approach computes the high slurry viscosities from collisions of the catalyst particles. Thus particle rheology is not an input into the model.« less

The aerodynamic cost of flight in bats--comparing theory with measurement

NASA Astrophysics Data System (ADS)

von Busse, Rhea; Waldman, Rye M.; Swartz, Sharon M.; Breuer, Kenneth S.

2012-11-01

Aerodynamic theory has long been used to predict the aerodynamic power required for animal flight. However, even though the actuator disk model does not account for the flapping motion of a wing, it is used for lack of any better model. The question remains: how close are these predictions to reality? We designed a study to compare predicted aerodynamic power to measured power from the kinetic energy contained in the wake shed behind a bat flying in a wind tunnel. A high-accuracy displaced light-sheet stereo PIV system was used in the Trefftz plane to capture the wake behind four bats flown over a range of flight speeds (1-6m/s). The total power in the wake was computed from the wake vorticity and these estimates were compared with the power predicted using Pennycuick's model for bird flight as well as estimates derived from measurements of the metabolic cost of flight, previously acquired from the same individuals.

Relationship between body composition and postural control in prepubertal overweight/obese children: A cross-sectional study.

PubMed

Villarrasa-Sapiña, Israel; Álvarez-Pitti, Julio; Cabeza-Ruiz, Ruth; Redón, Pau; Lurbe, Empar; García-Massó, Xavier

2018-02-01

Excess body weight during childhood causes reduced motor functionality and problems in postural control, a negative influence which has been reported in the literature. Nevertheless, no information regarding the effect of body composition on the postural control of overweight and obese children is available. The objective of this study was therefore to establish these relationships. A cross-sectional design was used to establish relationships between body composition and postural control variables obtained in bipedal eyes-open and eyes-closed conditions in twenty-two children. Centre of pressure signals were analysed in the temporal and frequency domains. Pearson correlations were applied to establish relationships between variables. Principal component analysis was applied to the body composition variables to avoid potential multicollinearity in the regression models. These principal components were used to perform a multiple linear regression analysis, from which regression models were obtained to predict postural control. Height and leg mass were the body composition variables that showed the highest correlation with postural control. Multiple regression models were also obtained and several of these models showed a higher correlation coefficient in predicting postural control than simple correlations. These models revealed that leg and trunk mass were good predictors of postural control. More equations were found in the eyes-open than eyes-closed condition. Body weight and height are negatively correlated with postural control. However, leg and trunk mass are better postural control predictors than arm or body mass. Finally, body composition variables are more useful in predicting postural control when the eyes are open. Copyright © 2017 Elsevier Ltd. All rights reserved.

Real-time control of walking using recordings from dorsal root ganglia.

PubMed

Holinski, B J; Everaert, D G; Mushahwar, V K; Stein, R B

2013-10-01

The goal of this study was to decode sensory information from the dorsal root ganglia (DRG) in real time, and to use this information to adapt the control of unilateral stepping with a state-based control algorithm consisting of both feed-forward and feedback components. In five anesthetized cats, hind limb stepping on a walkway or treadmill was produced by patterned electrical stimulation of the spinal cord through implanted microwire arrays, while neuronal activity was recorded from the DRG. Different parameters, including distance and tilt of the vector between hip and limb endpoint, integrated gyroscope and ground reaction force were modelled from recorded neural firing rates. These models were then used for closed-loop feedback. Overall, firing-rate-based predictions of kinematic sensors (limb endpoint, integrated gyroscope) were the most accurate with variance accounted for >60% on average. Force prediction had the lowest prediction accuracy (48 ± 13%) but produced the greatest percentage of successful rule activations (96.3%) for stepping under closed-loop feedback control. The prediction of all sensor modalities degraded over time, with the exception of tilt. Sensory feedback from moving limbs would be a desirable component of any neuroprosthetic device designed to restore walking in people after a spinal cord injury. This study provides a proof-of-principle that real-time feedback from the DRG is possible and could form part of a fully implantable neuroprosthetic device with further development.

Longitudinal Associations Between Parental Monitoring Discrepancy and Delinquency: An Application of the Latent Congruency Model.

PubMed

Ksinan, Albert J; Vazsonyi, Alexander T

2016-12-01

Studies have shown that discrepancies (relative concordance or discordance) between parent and adolescent ratings are predictive of problem behaviors; monitoring, in particular, has been consistently linked to them. The current study tested whether discrepancies in perceptions of maternal monitoring, rated by mothers and youth at age 12, foretold delinquency (rule breaking) at age 15, and whether parental closeness and conflict predicted higher discrepancies, and indirectly, higher delinquency. The final study sample used the NICHD longitudinal dataset with N = 966 youth (50.1 % female) and their mothers (80.1 % European American, 12.9 % African American, 7 % other ethnicity). The analytic approach consisted of an extension and application of the Latent Congruency Model (LCM) to estimate monitoring discrepancies as well as age 15 delinquency scores. Findings showed that age 12 monitoring discrepancy was predictive of age 15 delinquency for both boys and girls based on youth reports, but not for maternal reports. Age 11 closeness predicted age 12 monitoring discrepancy, which served as a mediator for its effect on age 15 adolescent-reported delinquency. Thus, based on the rigorous LCM analytic approach which seeks to minimize the effects by competing explanations and to maximize precision in providing robust estimates, rates of perceived discordance in parenting behaviors during early adolescence matter in understanding variability in adolescent delinquency during middle adolescence.

Translational Modeling to Guide Study Design and Dose Choice in Obesity Exemplified by AZD1979, a Melanin-concentrating Hormone Receptor 1 Antagonist.

PubMed

Gennemark, P; Trägårdh, M; Lindén, D; Ploj, K; Johansson, A; Turnbull, A; Carlsson, B; Antonsson, M

2017-07-01

In this study, we present the translational modeling used in the discovery of AZD1979, a melanin-concentrating hormone receptor 1 (MCHr1) antagonist aimed for treatment of obesity. The model quantitatively connects the relevant biomarkers and thereby closes the scaling path from rodent to man, as well as from dose to effect level. The complexity of individual modeling steps depends on the quality and quantity of data as well as the prior information; from semimechanistic body-composition models to standard linear regression. Key predictions are obtained by standard forward simulation (e.g., predicting effect from exposure), as well as non-parametric input estimation (e.g., predicting energy intake from longitudinal body-weight data), across species. The work illustrates how modeling integrates data from several species, fills critical gaps between biomarkers, and supports experimental design and human dose-prediction. We believe this approach can be of general interest for translation in the obesity field, and might inspire translational reasoning more broadly. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Modelling growth of Penicillium expansum and Aspergillus niger at constant and fluctuating temperature conditions.

PubMed

Gougouli, Maria; Koutsoumanis, Konstantinos P

2010-06-15

The growth of Penicillium expansum and Aspergillus niger, isolated from yogurt production environment, was investigated on malt extract agar with pH=4.2 and a(w)=0.997, simulating yogurt, at isothermal conditions ranging from -1.3 to 35 degrees C and from 5 to 42.3 degrees C, respectively. The growth rate (mu) and (apparent) lag time (lambda) of the mycelium growth were modelled as a function of temperature using a Cardinal Model with Inflection (CMI). The results showed that the CMI can describe successfully the effect of temperature on fungal growth within the entire biokinetic range for both isolates. The estimated values of the CMI for mu were T(min)=-5.74 degrees C, T(max)=30.97 degrees C, T(opt)=22.08 degrees C and mu(opt)=0.221 mm/h for P. expansum and T(min)=10.13 degrees C, T(max)=43.13 degrees C, T(opt)=31.44 degrees C, and mu(opt)=0.840 mm/h for A. niger. The cardinal values for lambda were very close to the respective values for mu indicating similar temperature dependence of the growth rate and the lag time of the mycelium growth. The developed models were further validated under fluctuating temperature conditions using various dynamic temperature scenarios. The time-temperature conditions studied included single temperature shifts before or after the end of the lag time and continuous periodic temperature fluctuations. The prediction of growth at changing temperature was based on the assumption that after a temperature shift the growth rate is adopted instantaneously to the new temperature, while the lag time was predicted using a cumulative lag approach. The results showed that when the temperature shifts occurred before the end of the lag, they did not cause any significant additional lag and the observed total lag was very close to the cumulative lag predicted by the model. In experiments with temperature shifts after the end of the lag time, accurate predictions were obtained when the temperature profile included temperatures which were inside the region of growth, showing that the assumption that mu is adopted instantaneously to the current temperature is concrete. In contrast, for scenarios with temperatures close or outside the growth region the models overestimated growth, indicating that fungi were stressed by this type of temperature shifts. The present study provides useful data for understanding the behavior of P. expansum and A. niger at dynamic temperature conditions while the developed models can be used as effective tools in assessing the risk of fungal spoilage and predicting shelf life of foods. Copyright 2010. Published by Elsevier B.V.

Nonidentifiability of population size from capture-recapture data with heterogeneous detection probabilities

USGS Publications Warehouse

Link, W.A.

2003-01-01

Heterogeneity in detection probabilities has long been recognized as problematic in mark-recapture studies, and numerous models developed to accommodate its effects. Individual heterogeneity is especially problematic, in that reasonable alternative models may predict essentially identical observations from populations of substantially different sizes. Thus even with very large samples, the analyst will not be able to distinguish among reasonable models of heterogeneity, even though these yield quite distinct inferences about population size. The problem is illustrated with models for closed and open populations.

Perceptions of close and group relationships mediate the relationship between anxiety and depression over a decade later

PubMed Central

Jacobson, Nicholas C.; Newman, Michelle G.

2016-01-01

Background Previous research has demonstrated that anxiety reliably predicts later depression, but little has been uncovered about the mechanism underlying this connection. Interpersonal relationships appear to be a viable mechanism of the association as anxiety has been shown to predict later deficits in both close (e.g., “best friendships”) and group relationships (e.g., classroom peer groups), and deficits in both close and group relationships have been linked to later depressive symptoms. The current study examined close and group relationships as potential mediators between anxiety and depression 12–14 years later. Methods In a nationally representative sample of adolescents (N = 6,504), anxiety was measured at baseline, perceptions of close relationships (i.e., feeling loved) and perceptions of group relationships (i.e., feeling part of a group) were measured 6 months later, and depression levels and diagnosis were measured 12–14 years later. Results Using structural equation models, the results showed that adolescent perceptions of both close and group relationships significantly mediated the relationship between adolescent anxiety and adult levels of depression. Furthermore, perceptions of not being accepted/loved in close relationships significantly mediated the relationship between adolescent anxiety and clinical depression in adulthood. Conclusions These results suggest that a perception of not being accepted in group relationships may be a mechanism by which heightened anxiety in adolescents leads to heightened nonclinical depression in adulthood. On the other hand, adolescent perceptions of not feeling loved or accepted in close relationships may be a mechanism by which heightened anxiety in adolescence leads to clinical depression—in adulthood. PMID:26290461

PERCEPTIONS OF CLOSE AND GROUP RELATIONSHIPS MEDIATE THE RELATIONSHIP BETWEEN ANXIETY AND DEPRESSION OVER A DECADE LATER.

PubMed

Jacobson, Nicholas C; Newman, Michelle G

2016-01-01

Previous research has demonstrated that anxiety reliably predicts later depression, but little has been uncovered about the mechanism underlying this connection. Interpersonal relationships appear to be a viable mechanism of the association as anxiety has been shown to predict later deficits in both close (e.g., "best friendships") and group relationships (e.g., classroom peer groups), and deficits in both close and group relationships have been linked to later depressive symptoms. The current study examined close and group relationships as potential mediators between anxiety and depression 12-14 years later. In a nationally representative sample of adolescents (N = 6,504), anxiety was measured at baseline, perceptions of close relationships (i.e., feeling loved) and perceptions of group relationships (i.e., feeling part of a group) were measured 6 months later, and depression levels and diagnosis were measured 12-14 years later. Using structural equation models, the results showed that adolescent perceptions of both close and group relationships significantly mediated the relationship between adolescent anxiety and adult levels of depression. Furthermore, perceptions of not being accepted/loved in close relationships significantly mediated the relationship between adolescent anxiety and clinical depression in adulthood. These results suggest that a perception of not being accepted in group relationships may be a mechanism by which heightened anxiety in adolescents leads to heightened nonclinical depression in adulthood. On the other hand, adolescent perceptions of not feeling loved or accepted in close relationships may be a mechanism by which heightened anxiety in adolescence leads to clinical depression--in adulthood. © 2015 Wiley Periodicals, Inc.

Statistical learning and probabilistic prediction in music cognition: mechanisms of stylistic enculturation.

PubMed

Pearce, Marcus T

2018-05-11

Music perception depends on internal psychological models derived through exposure to a musical culture. It is hypothesized that this musical enculturation depends on two cognitive processes: (1) statistical learning, in which listeners acquire internal cognitive models of statistical regularities present in the music to which they are exposed; and (2) probabilistic prediction based on these learned models that enables listeners to organize and process their mental representations of music. To corroborate these hypotheses, I review research that uses a computational model of probabilistic prediction based on statistical learning (the information dynamics of music (IDyOM) model) to simulate data from empirical studies of human listeners. The results show that a broad range of psychological processes involved in music perception-expectation, emotion, memory, similarity, segmentation, and meter-can be understood in terms of a single, underlying process of probabilistic prediction using learned statistical models. Furthermore, IDyOM simulations of listeners from different musical cultures demonstrate that statistical learning can plausibly predict causal effects of differential cultural exposure to musical styles, providing a quantitative model of cultural distance. Understanding the neural basis of musical enculturation will benefit from close coordination between empirical neuroimaging and computational modeling of underlying mechanisms, as outlined here. © 2018 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals, Inc. on behalf of New York Academy of Sciences.

Macroscopic balance model for wave rotors

NASA Technical Reports Server (NTRS)

Welch, Gerard E.

1996-01-01

A mathematical model for multi-port wave rotors is described. The wave processes that effect energy exchange within the rotor passage are modeled using one-dimensional gas dynamics. Macroscopic mass and energy balances relate volume-averaged thermodynamic properties in the rotor passage control volume to the mass, momentum, and energy fluxes at the ports. Loss models account for entropy production in boundary layers and in separating flows caused by blade-blockage, incidence, and gradual opening and closing of rotor passages. The mathematical model provides a basis for predicting design-point wave rotor performance, port timing, and machine size. Model predictions are evaluated through comparisons with CFD calculations and three-port wave rotor experimental data. A four-port wave rotor design example is provided to demonstrate model applicability. The modeling approach is amenable to wave rotor optimization studies and rapid assessment of the trade-offs associated with integrating wave rotors into gas turbine engine systems.

Shape Transformation of the Nuclear Envelope during Closed Mitosis.

PubMed

Zhu, Qian; Zheng, Fan; Liu, Allen P; Qian, Jin; Fu, Chuanhai; Lin, Yuan

2016-11-15

The nuclear envelope (NE) in lower eukaryotes such as Schizosaccharomyces pombe undergoes large morphology changes during closed mitosis. However, which physical parameters are important in governing the shape evolution of the NE, and how defects in the dividing chromosomes/microtubules are reflected in those parameters, are fundamental questions that remain unresolved. In this study, we show that improper separation of chromosomes in genetically deficient cells leads to membrane tethering or asymmetric division in contrast to the formation of two equal-sized daughter nuclei in wild-type cells. We hypothesize that the poleward force is transmitted to the nuclear membrane through its physical contact with the separated sister chromatids at the two spindle poles. A theoretical model is developed to predict the morphology evolution of the NE where key factors such as the work done by the poleward force and bending and surface energies stored in the membrane have been taken into account. Interestingly, the predicted phase diagram, summarizing the dependence of nuclear shape on the size of the load transmission regions, and the pole-to-pole distance versus surface area relationship all quantitatively agree well with our experimental observations, suggesting that this model captures the essential physics involved in closed mitosis. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Disclosure of HIV-positive status to Latino gay men's social networks.

PubMed

Zea, María Cecilia; Reisen, Carol A; Poppen, Paul J; Echeverry, John J; Bianchi, Fernanda T

2004-03-01

This study explored disclosure of serostatus in a sample of 155 HIV-positive Latino gay men from New York City and Washington, DC. We examined rates of disclosure to different members of the social network: mothers, fathers, close friends, and primary sexual partners. There were high rates of disclosure of HIV-positive serostatus to main partners and closest friends and lower rates to fathers and mothers. We examined the role of 3 contextual target-dependent factors (emotional closeness to target, anticipated reactions from target, and target's knowledge of sexual orientation), as well as acculturation and time since diagnosis. Three separate logistic regression models were performed to predict disclosure of HIV-positive status to 3 targets: mothers, fathers, and closest friends. We found that disclosure was not a generalized tendency, but rather different factors were influential depending on the target. Whether the target was aware of participant's sexual orientation was associated with disclosure in all 3 models. Greater emotional closeness also predicted disclosure to mother and father; greater U.S. acculturation was associated with disclosure to father and marginally to mother. A longer time since diagnosis was associated with disclosure to the closest friend. These findings highlight the importance of taking into account roles and relationships, and their effect on disclosure.

The stabilities and electron structures of Al-Mg clusters with 18 and 20 valence electrons

NASA Astrophysics Data System (ADS)

Yang, Huihui; Chen, Hongshan

2017-07-01

The spherical jellium model predicts that metal clusters having 18 and 20 valence electrons correspond to the magic numbers and will show specific stabilities. We explore in detail the geometric structures, stabilities and electronic structures of Al-Mg clusters containing 18 and 20 valence electrons by using genetic algorithm combined with density functional theories. The stabilities of the clusters are governed by the electronic configurations and Mg/Al ratios. The clusters with lower Mg/Al ratios are more stable. The molecular orbitals accord with the shell structures predicted by the jellium model but the 2S level interweaves with the 1D levels and the 2S and 1D orbitals form a subgroup. The clusters having 20 valence electrons form closed 1S21P61D102S2 shells and show enhanced stability. The Al-Mg clusters with a valence electron count of 18 do not form closed shells because one 1D orbital is unoccupied. The ionization potential and electron affinity are closely related to the electronic configurations; their values are determined by the subgroups the HOMO or LUMO belong to. Supplementary material in the form of one pdf file available from the Journal web page at http://https://doi.org/10.1140/epjd/e2017-80042-9

Modeling thermal infrared (2-14 micrometer) reflectance spectra of frost and snow

NASA Technical Reports Server (NTRS)

Wald, Andrew E.

1994-01-01

Existing theories of radiative transfer in close-packed media assume that each particle scatters independently of its neighbors. For opaque particles, such as are common in the thermal infrared, this assumption is not valid, and these radiative transfer theories will not be accurate. A new method is proposed, called 'diffraction subtraction', which modifies the scattering cross section of close-packed large, opaque spheres to account for the effect of close packing on the diffraction cross section of a scattering particle. This method predicts the thermal infrared reflectance of coarse (greater than 50 micrometers radius), disaggregated granular snow. However, such coarse snow is typically old and metamorphosed, with adjacent grains welded together. The reflectance of such a welded block can be described as partly Fresnel in nature and cannot be predicted using Mie inputs to radiative transfer theory. Owing to the high absorption coefficient of ice in the thermal infrared, a rough surface reflectance model can be used to calculate reflectance from such a block. For very small (less than 50 micrometers), disaggregated particles, it is incorrect in principle to treat diffraction independently of reflection and refraction, and the theory fails. However, for particles larger than 50 micrometers, independent scattering is a valid assumption, and standard radiative transfer theory works.

Predictive discomfort in single- and combined-axis whole-body vibration considering different seated postures.

PubMed

DeShaw, Jonathan; Rahmatalla, Salam

2014-08-01

The aim of this study was to develop a predictive discomfort model in single-axis, 3-D, and 6-D combined-axis whole-body vibrations of seated occupants considering different postures. Non-neutral postures in seated whole-body vibration play a significant role in the resulting level of perceived discomfort and potential long-term injury. The current international standards address contact points but not postures. The proposed model computes discomfort on the basis of static deviation of human joints from their neutral positions and how fast humans rotate their joints under vibration. Four seated postures were investigated. For practical implications, the coefficients of the predictive discomfort model were changed into the Borg scale with psychophysical data from 12 volunteers in different vibration conditions (single-axis random fore-aft, lateral, and vertical and two magnitudes of 3-D). The model was tested under two magnitudes of 6-D vibration. Significant correlations (R = .93) were found between the predictive discomfort model and the reported discomfort with different postures and vibrations. The ISO 2631-1 correlated very well with discomfort (R2 = .89) but was not able to predict the effect of posture. Human discomfort in seated whole-body vibration with different non-neutral postures can be closely predicted by a combination of static posture and the angular velocities of the joint. The predictive discomfort model can assist ergonomists and human factors researchers design safer environments for seated operators under vibration. The model can be integrated with advanced computer biomechanical models to investigate the complex interaction between posture and vibration.

Recent Successes of Wave/Turbulence Driven Models of Solar Wind Acceleration

NASA Astrophysics Data System (ADS)

Cranmer, S. R.; Hollweg, J. V.; Chandran, B. D.; van Ballegooijen, A. A.

2010-12-01

A key obstacle in the way of producing realistic simulations of the Sun-heliosphere system is the lack of a first-principles understanding of coronal heating. Also, it is still unknown whether the solar wind is "fed" through flux tubes that remain open (and are energized by footpoint-driven wavelike fluctuations) or if mass and energy are input intermittently from closed loops into the open-field regions. In this presentation, we discuss self-consistent models that assume the energy comes from solar Alfven waves that are partially reflected, and then dissipated, by magnetohydrodynamic turbulence. These models have been found to reproduce many of the observed features of the fast and slow solar wind without the need for artificial "coronal heating functions" used by earlier models. For example, the models predict a variation with wind speed in commonly measured ratios of charge states and elemental abundances that agrees with observed trends. This contradicts a commonly held assertion that these ratios can only be produced by the injection of plasma from closed-field regions on the Sun. This presentation also reviews two recent comparisons between the models and empirical measurements: (1) The models successfully predict the amplitude and radial dependence of Faraday rotation fluctuations (FRFs) measured by the Helios probes for heliocentric distances between 2 and 15 solar radii. The FRFs are a particularly sensitive test of turbulence models because they depend not only on the plasma density and Alfven wave amplitude in the corona, but also on the turbulent correlation length. (2) The models predict the correct sense and magnitude of changes seen in the polar high-speed solar wind by Ulysses from the previous solar minimum (1996-1997) to the more recent peculiar minimum (2008-2009). By changing only the magnetic field along the polar magnetic flux tube, consistent with solar and heliospheric observations at the two epochs, the model correctly predicts that the wind speed remains relatively unchanged, but the in-situ density and temperature decrease by approximately 20 percent and 10 percent, respectively.

Langevin model of low-energy fission

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

Sierk, Arnold John

Since the earliest days of fission, stochastic models have been used to describe and model the process. For a quarter century, numerical solutions of Langevin equations have been used to model fission of highly excited nuclei, where microscopic potential-energy effects have been neglected. In this paper I present a Langevin model for the fission of nuclei with low to medium excitation energies, for which microscopic effects in the potential energy cannot be ignored. I solve Langevin equations in a five-dimensional space of nuclear deformations. The macroscopic-microscopic potential energy from a global nuclear structure model well benchmarked to nuclear masses ismore » tabulated on a mesh of approximately 10 7 points in this deformation space. The potential is defined continuously inside the mesh boundaries by use of a moving five-dimensional cubic spline approximation. Because of reflection symmetry, the effective mesh is nearly twice this size. For the inertia, I use a (possibly scaled) approximation to the inertia tensor defined by irrotational flow. A phenomenological dissipation tensor related to one-body dissipation is used. A normal-mode analysis of the dynamical system at the saddle point and the assumption of quasiequilibrium provide distributions of initial conditions appropriate to low excitation energies, and are extended to model spontaneous fission. A dynamical model of postscission fragment motion including dynamical deformations and separation allows the calculation of final mass and kinetic-energy distributions, along with other interesting quantities. The model makes quantitative predictions for fragment mass and kinetic-energy yields, some of which are very close to measured ones. Varying the energy of the incident neutron for induced fission allows the prediction of energy dependencies of fragment yields and average kinetic energies. With a simple approximation for spontaneous fission starting conditions, quantitative predictions are made for some observables which are close to measurements. In conclusion, this model is able to reproduce several mass and energy yield observables with a small number of physical parameters, some of which do not need to be varied after benchmarking to 235U (n, f) to predict results for other fissioning isotopes.« less

Langevin model of low-energy fission

DOE PAGES

Sierk, Arnold John

2017-09-05

Since the earliest days of fission, stochastic models have been used to describe and model the process. For a quarter century, numerical solutions of Langevin equations have been used to model fission of highly excited nuclei, where microscopic potential-energy effects have been neglected. In this paper I present a Langevin model for the fission of nuclei with low to medium excitation energies, for which microscopic effects in the potential energy cannot be ignored. I solve Langevin equations in a five-dimensional space of nuclear deformations. The macroscopic-microscopic potential energy from a global nuclear structure model well benchmarked to nuclear masses ismore » tabulated on a mesh of approximately 10 7 points in this deformation space. The potential is defined continuously inside the mesh boundaries by use of a moving five-dimensional cubic spline approximation. Because of reflection symmetry, the effective mesh is nearly twice this size. For the inertia, I use a (possibly scaled) approximation to the inertia tensor defined by irrotational flow. A phenomenological dissipation tensor related to one-body dissipation is used. A normal-mode analysis of the dynamical system at the saddle point and the assumption of quasiequilibrium provide distributions of initial conditions appropriate to low excitation energies, and are extended to model spontaneous fission. A dynamical model of postscission fragment motion including dynamical deformations and separation allows the calculation of final mass and kinetic-energy distributions, along with other interesting quantities. The model makes quantitative predictions for fragment mass and kinetic-energy yields, some of which are very close to measured ones. Varying the energy of the incident neutron for induced fission allows the prediction of energy dependencies of fragment yields and average kinetic energies. With a simple approximation for spontaneous fission starting conditions, quantitative predictions are made for some observables which are close to measurements. In conclusion, this model is able to reproduce several mass and energy yield observables with a small number of physical parameters, some of which do not need to be varied after benchmarking to 235U (n, f) to predict results for other fissioning isotopes.« less

A closed-loop hybrid physiological model relating to subjects under physical stress.

PubMed

El-Samahy, Emad; Mahfouf, Mahdi; Linkens, Derek A

2006-11-01

The objective of this research study is to derive a comprehensive physiological model relating to subjects under physical stress conditions. The model should describe the behaviour of the cardiovascular system, respiratory system, thermoregulation and brain activity in response to physical workload. An experimental testing rig was built which consists of recumbent high performance bicycle for inducing the physical load and a data acquisition system comprising monitors and PCs. The signals acquired and used within this study are the blood pressure, heart rate, respiration, body temperature, and EEG signals. The proposed model is based on a grey-box based modelling approach which was used because of the sufficient level of details it provides. Cardiovascular and EEG Data relating to 16 healthy subject volunteers (data from 12 subjects were used for training/validation and the data from 4 subjects were used for model testing) were collected using the Finapres and the ProComp+ monitors. For model validation, residual analysis via the computing of the confidence intervals as well as related histograms was performed. Closed-loop simulations for different subjects showed that the model can provide reliable predictions for heart rate, blood pressure, body temperature, respiration, and the EEG signals. These findings were also reinforced by the residual analyses data obtained, which suggested that the residuals were within the 90% confidence bands and that the corresponding histograms were of a normal distribution. A higher intelligent level was added to the model, based on neural networks, to extend the capabilities of the model to predict over a wide range of subjects dynamics. The elicited physiological model describing the effect of physiological stress on several physiological variables can be used to predict performance breakdown of operators in critical environments. Such a model architecture lends itself naturally to exploitation via feedback control in a 'reverse-engineering' fashion to control stress via the specification of a safe operating range for the psycho-physiological variables.

[Prediction of potential geographic distribution of Lyme disease in Qinghai province with Maximum Entropy model].

PubMed

Zhang, Lin; Hou, Xuexia; Liu, Huixin; Liu, Wei; Wan, Kanglin; Hao, Qin

2016-01-01

To predict the potential geographic distribution of Lyme disease in Qinghai by using Maximum Entropy model (MaxEnt). The sero-diagnosis data of Lyme disease in 6 counties (Huzhu, Zeku, Tongde, Datong, Qilian and Xunhua) and the environmental and anthropogenic data including altitude, human footprint, normalized difference vegetation index (NDVI) and temperature in Qinghai province since 1990 were collected. By using the data of Huzhu Zeku and Tongde, the prediction of potential distribution of Lyme disease in Qinghai was conducted with MaxEnt. The prediction results were compared with the human sero-prevalence of Lyme disease in Datong, Qilian and Xunhua counties in Qinghai. Three hot spots of Lyme disease were predicted in Qinghai, which were all in the east forest areas. Furthermore, the NDVI showed the most important role in the model prediction, followed by human footprint. Datong, Qilian and Xunhua counties were all in eastern Qinghai. Xunhua was in hot spot areaⅡ, Datong was close to the north of hot spot area Ⅲ, while Qilian with lowest sero-prevalence of Lyme disease was not in the hot spot areas. The data were well modeled in MaxEnt (Area Under Curve=0.980). The actual distribution of Lyme disease in Qinghai was in consistent with the results of the model prediction. MaxEnt could be used in predicting the potential distribution patterns of Lyme disease. The distribution of vegetation and the range and intensity of human activity might be related with Lyme disease distribution.

Deterrent Concentration Measurement with FTIR and Subsequent Ballistic Performance in Medium Caliber Propellant

NASA Technical Reports Server (NTRS)

Furrow, Keith W.; Ritchie, Steve J.; Morris, Amy

2000-01-01

To meet ballistic requirements, medium and small caliber propellants use deterrent coatings to obtain burn rate progressivity. The required amount and distribution of deterrent varies between gun systems, propellant types, and often between lots. Micro Fourier Transform Infrared (FTIR) spectroscopy was used to measure deterrent gradients in RP36 propellants coated with methyl centralite (MC) at different deterrent levels and different processing conditions. The aromatic C-C bonds at 1496 cm(exp -1) wavenumber were used to monitor the deterrent profiles through the grain. Deterrent gradients measured with FTIR spectroscopy were then used to estimate burn rate gradients in the deterred grains. Burn rates were calculated from literature models and from closed bomb data of RP36 containing uniform deterrent concentration. Finally, the burn rate gradients were input into an IBHFG2 model of a 200 cc-closed bomb. The early flame spreading portion of the closed bomb ballistic cycle (0 to 0.2 P/Pmax) was roughly modeled by dividing the charge up into five propellant decks and igniting them at different times in the ballistic cycle. Pressure traces and vivacity curves from closed bomb shots were compared to predictions. In addition to the burn rate gradient, the closed bomb pressure trace was heavily dependent on ignition and flame spread. These two phenomena were not readily distinguishable from one another in deterred grains. The same RP-36 propellant was shot in a 25 mm M793TP round which was again modeled with IBHVG2. Peak pressure and muzzle velocity were accurately modeled when erosive burning effects were empirically factored into the model.

Mechanism of Tacrine Block at Adult Human Muscle Nicotinic Acetylcholine Receptors

PubMed Central

Prince, Richard J.; Pennington, Richard A.; Sine, Steven M.

2002-01-01

We used single-channel kinetic analysis to study the inhibitory effects of tacrine on human adult nicotinic receptors (nAChRs) transiently expressed in HEK 293 cells. Single channel recording from cell-attached patches revealed concentration- and voltage-dependent decreases in mean channel open probability produced by tacrine (IC50 4.6 μM at −70 mV, 1.6 μM at −150 mV). Two main effects of tacrine were apparent in the open- and closed-time distributions. First, the mean channel open time decreased with increasing tacrine concentration in a voltage-dependent manner, strongly suggesting that tacrine acts as an open-channel blocker. Second, tacrine produced a new class of closings whose duration increased with increasing tacrine concentration. Concentration dependence of closed-times is not predicted by sequential models of channel block, suggesting that tacrine blocks the nAChR by an unusual mechanism. To probe tacrine's mechanism of action we fitted a series of kinetic models to our data using maximum likelihood techniques. Models incorporating two tacrine binding sites in the open receptor channel gave dramatically improved fits to our data compared with the classic sequential model, which contains one site. Improved fits relative to the sequential model were also obtained with schemes incorporating a binding site in the closed channel, but only if it is assumed that the channel cannot gate with tacrine bound. Overall, the best description of our data was obtained with a model that combined two binding sites in the open channel with a single site in the closed state of the receptor. PMID:12198092

Depiction of interfacial morphology in impact welded Ti/Cu bimetallic systems using smoothed particle hydrodynamics

NASA Astrophysics Data System (ADS)

Nassiri, Ali; Vivek, Anupam; Abke, Tim; Liu, Bert; Lee, Taeseon; Daehn, Glenn

2017-06-01

Numerical simulations of high-velocity impact welding are extremely challenging due to the coupled physics and highly dynamic nature of the process. Thus, conventional mesh-based numerical methodologies are not able to accurately model the process owing to the excessive mesh distortion close to the interface of two welded materials. A simulation platform was developed using smoothed particle hydrodynamics, implemented in a parallel architecture on a supercomputer. Then, the numerical simulations were compared to experimental tests conducted by vaporizing foil actuator welding. The close correspondence of the experiment and modeling in terms of interface characteristics allows the prediction of local temperature and strain distributions, which are not easily measured.

Investigations of VOCs in and around buildings close to service stations

NASA Astrophysics Data System (ADS)

Hicklin, William; Farrugia, Pierre S.; Sinagra, Emmanuel

2018-01-01

Gas service stations are one of the major sources of volatile organic compounds in urban environments. Their emissions are expected not only to affect the ambient air quality but also that in any nearby buildings. This is particularly the case in Malta where most service stations have been built within residential zones. For this reason, it is important to understand the dispersion of volatile organic compounds (VOCs) from service stations and their infiltration into nearby residences. Two models were considered; one to predict the dispersion of VOCs in the outdoor environment in the vicinity of the service station and another one to predict the filtration of the compounds indoors. The two models can be used in tandem to predict the concentration of indoor VOCs that originate from a service station in the vicinity. Outdoor and indoor concentrations of VOCs around a service station located in a street canyon were measured, and the results used to validate the models. Predictions made using the models were found to be in general agreement with the measured concentrations of the pollutants.

The effects of geometric uncertainties on computational modelling of knee biomechanics

PubMed Central

Fisher, John; Wilcox, Ruth

2017-01-01

The geometry of the articular components of the knee is an important factor in predicting joint mechanics in computational models. There are a number of uncertainties in the definition of the geometry of cartilage and meniscus, and evaluating the effects of these uncertainties is fundamental to understanding the level of reliability of the models. In this study, the sensitivity of knee mechanics to geometric uncertainties was investigated by comparing polynomial-based and image-based knee models and varying the size of meniscus. The results suggested that the geometric uncertainties in cartilage and meniscus resulting from the resolution of MRI and the accuracy of segmentation caused considerable effects on the predicted knee mechanics. Moreover, even if the mathematical geometric descriptors can be very close to the imaged-based articular surfaces, the detailed contact pressure distribution produced by the mathematical geometric descriptors was not the same as that of the image-based model. However, the trends predicted by the models based on mathematical geometric descriptors were similar to those of the imaged-based models. PMID:28879008

A Microstructure-Based Constitutive Model for Superplastic Forming

NASA Astrophysics Data System (ADS)

Jafari Nedoushan, Reza; Farzin, Mahmoud; Mashayekhi, Mohammad; Banabic, Dorel

2012-11-01

A constitutive model is proposed for simulations of hot metal forming processes. This model is constructed based on dominant mechanisms that take part in hot forming and includes intergranular deformation, grain boundary sliding, and grain boundary diffusion. A Taylor type polycrystalline model is used to predict intergranular deformation. Previous works on grain boundary sliding and grain boundary diffusion are extended to drive three-dimensional macro stress-strain rate relationships for each mechanism. In these relationships, the effect of grain size is also taken into account. The proposed model is first used to simulate step strain-rate tests and the results are compared with experimental data. It is shown that the model can be used to predict flow stresses for various grain sizes and strain rates. The yield locus is then predicted for multiaxial stress states, and it is observed that it is very close to the von Mises yield criterion. It is also shown that the proposed model can be directly used to simulate hot forming processes. Bulge forming process and gas pressure tray forming are simulated, and the results are compared with experimental data.

Glutamate receptor-channel gating. Maximum likelihood analysis of gigaohm seal recordings from locust muscle.

PubMed Central

Bates, S E; Sansom, M S; Ball, F G; Ramsey, R L; Usherwood, P N

1990-01-01

Gigaohm recordings have been made from glutamate receptor channels in excised, outside-out patches of collagenase-treated locust muscle membrane. The channels in the excised patches exhibit the kinetic state switching first seen in megaohm recordings from intact muscle fibers. Analysis of channel dwell time distributions reveals that the gating mechanism contains at least four open states and at least four closed states. Dwell time autocorrelation function analysis shows that there are at least three gateways linking the open states of the channel with the closed states. A maximum likelihood procedure has been used to fit six different gating models to the single channel data. Of these models, a cooperative model yields the best fit, and accurately predicts most features of the observed channel gating kinetics. PMID:1696510

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

PubMed

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

2018-03-28

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

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

PubMed Central

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

2018-01-01

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

Testing Feedback Models with Nearby Star Forming Regions

NASA Astrophysics Data System (ADS)

Doran, E.; Crowther, P.

2012-12-01

The feedback from massive stars plays a crucial role in the evolution of galaxies. Accurate modelling of this feedback is essential in understanding distant star forming regions. Young nearby, high mass (> 104 M⊙) clusters such as R136 (in the 30 Doradus region) are ideal test beds for population synthesis since they host large numbers of spatially resolved massive stars at a pre-supernovae stage. We present a quantitative comparison of empirical calibrations of radiative and mechanical feedback from individual stars in R136, with instantaneous burst predictions from the popular Starburst99 evolution synthesis code. We find that empirical results exceed predictions by factors of ˜3-9, as a result of limiting simulations to an upper limit of 100 M⊙. 100-300 M⊙ stars should to be incorporated in population synthesis models for high mass clusters to bring predictions into close agreement with empirical results.

Prediction of surface roughness and cutting force under MQL turning of AISI 4340 with nano fluid by using response surface methodology

NASA Astrophysics Data System (ADS)

Patole, Pralhad B.; Kulkarni, Vivek V.

2018-06-01

This paper presents an investigation into the minimum quantity lubrication mode with nano fluid during turning of alloy steel AISI 4340 work piece material with the objective of experimental model in order to predict surface roughness and cutting force and analyze effect of process parameters on machinability. Full factorial design matrix was used for experimental plan. According to design of experiment surface roughness and cutting force were measured. The relationship between the response variables and the process parameters is determined through the response surface methodology, using a quadratic regression model. Results show how much surface roughness is mainly influenced by feed rate and cutting speed. The depth of cut exhibits maximum influence on cutting force components as compared to the feed rate and cutting speed. The values predicted from the model and experimental values are very close to each other.

The relationship between language use and depression: illuminating the importance of self-reflection, self-rumination, and the need for absolute truth.

PubMed

Şimşek, Ömer Faruk

2013-01-01

The main aim of the present study was to provide additional knowledge about the mediatory processes through which language relates to depression. Although previous research gave clear evidence that language is closely related to depression, the research on intervening variables in the relationship has been limited. The present investigation tested a structural equation model in which self-concept clarity and self-consciousness mediated the relationship between personal perceptions of language and depression. Since "the need for absolute truth" construct has been shown to be important in providing greater consistency in estimates of the relationships among the variables, it has been added to the model as a control variable. The results supported the model and showed that personal perceptions of language predicted self-concept clarity, which in turn predicted the participants' self-reflection and self-rumination. Self-reflection and self-rumination, in turn, predicted depression.

Toward autonomous spacecraft

NASA Technical Reports Server (NTRS)

Fogel, L. J.; Calabrese, P. G.; Walsh, M. J.; Owens, A. J.

1982-01-01

Ways in which autonomous behavior of spacecraft can be extended to treat situations wherein a closed loop control by a human may not be appropriate or even possible are explored. Predictive models that minimize mean least squared error and arbitrary cost functions are discussed. A methodology for extracting cyclic components for an arbitrary environment with respect to usual and arbitrary criteria is developed. An approach to prediction and control based on evolutionary programming is outlined. A computer program capable of predicting time series is presented. A design of a control system for a robotic dense with partially unknown physical properties is presented.

A novel numerical model to predict the morphological behavior of magnetic liquid marbles using coarse grained molecular dynamics concepts

NASA Astrophysics Data System (ADS)

Polwaththe-Gallage, Hasitha-Nayanajith; Sauret, Emilie; Nguyen, Nam-Trung; Saha, Suvash C.; Gu, YuanTong

2018-01-01

Liquid marbles are liquid droplets coated with superhydrophobic powders whose morphology is governed by the gravitational and surface tension forces. Small liquid marbles take spherical shapes, while larger liquid marbles exhibit puddle shapes due to the dominance of gravitational forces. Liquid marbles coated with hydrophobic magnetic powders respond to an external magnetic field. This unique feature of magnetic liquid marbles is very attractive for digital microfluidics and drug delivery systems. Several experimental studies have reported the behavior of the liquid marbles. However, the complete behavior of liquid marbles under various environmental conditions is yet to be understood. Modeling techniques can be used to predict the properties and the behavior of the liquid marbles effectively and efficiently. A robust liquid marble model will inspire new experiments and provide new insights. This paper presents a novel numerical modeling technique to predict the morphology of magnetic liquid marbles based on coarse grained molecular dynamics concepts. The proposed model is employed to predict the changes in height of a magnetic liquid marble against its width and compared with the experimental data. The model predictions agree well with the experimental findings. Subsequently, the relationship between the morphology of a liquid marble with the properties of the liquid is investigated. Furthermore, the developed model is capable of simulating the reversible process of opening and closing of the magnetic liquid marble under the action of a magnetic force. The scaling analysis shows that the model predictions are consistent with the scaling laws. Finally, the proposed model is used to assess the compressibility of the liquid marbles. The proposed modeling approach has the potential to be a powerful tool to predict the behavior of magnetic liquid marbles serving as bioreactors.

Modeling of Compressive Strength for Self-Consolidating High-Strength Concrete Incorporating Palm Oil Fuel Ash

PubMed Central

Safiuddin, Md.; Raman, Sudharshan N.; Abdus Salam, Md.; Jumaat, Mohd. Zamin

2016-01-01

Modeling is a very useful method for the performance prediction of concrete. Most of the models available in literature are related to the compressive strength because it is a major mechanical property used in concrete design. Many attempts were taken to develop suitable mathematical models for the prediction of compressive strength of different concretes, but not for self-consolidating high-strength concrete (SCHSC) containing palm oil fuel ash (POFA). The present study has used artificial neural networks (ANN) to predict the compressive strength of SCHSC incorporating POFA. The ANN model has been developed and validated in this research using the mix proportioning and experimental strength data of 20 different SCHSC mixes. Seventy percent (70%) of the data were used to carry out the training of the ANN model. The remaining 30% of the data were used for testing the model. The training of the ANN model was stopped when the root mean square error (RMSE) and the percentage of good patterns was 0.001 and ≈100%, respectively. The predicted compressive strength values obtained from the trained ANN model were much closer to the experimental values of compressive strength. The coefficient of determination (R2) for the relationship between the predicted and experimental compressive strengths was 0.9486, which shows the higher degree of accuracy of the network pattern. Furthermore, the predicted compressive strength was found very close to the experimental compressive strength during the testing process of the ANN model. The absolute and percentage relative errors in the testing process were significantly low with a mean value of 1.74 MPa and 3.13%, respectively, which indicated that the compressive strength of SCHSC including POFA can be efficiently predicted by the ANN. PMID:28773520

Modeling of Compressive Strength for Self-Consolidating High-Strength Concrete Incorporating Palm Oil Fuel Ash.

PubMed

Safiuddin, Md; Raman, Sudharshan N; Abdus Salam, Md; Jumaat, Mohd Zamin

2016-05-20

Modeling is a very useful method for the performance prediction of concrete. Most of the models available in literature are related to the compressive strength because it is a major mechanical property used in concrete design. Many attempts were taken to develop suitable mathematical models for the prediction of compressive strength of different concretes, but not for self-consolidating high-strength concrete (SCHSC) containing palm oil fuel ash (POFA). The present study has used artificial neural networks (ANN) to predict the compressive strength of SCHSC incorporating POFA. The ANN model has been developed and validated in this research using the mix proportioning and experimental strength data of 20 different SCHSC mixes. Seventy percent (70%) of the data were used to carry out the training of the ANN model. The remaining 30% of the data were used for testing the model. The training of the ANN model was stopped when the root mean square error (RMSE) and the percentage of good patterns was 0.001 and ≈100%, respectively. The predicted compressive strength values obtained from the trained ANN model were much closer to the experimental values of compressive strength. The coefficient of determination ( R ²) for the relationship between the predicted and experimental compressive strengths was 0.9486, which shows the higher degree of accuracy of the network pattern. Furthermore, the predicted compressive strength was found very close to the experimental compressive strength during the testing process of the ANN model. The absolute and percentage relative errors in the testing process were significantly low with a mean value of 1.74 MPa and 3.13%, respectively, which indicated that the compressive strength of SCHSC including POFA can be efficiently predicted by the ANN.

Small-Caliber Projectile Target Impact Angle Determined From Close Proximity Radiographs

DTIC Science & Technology

2006-10-01

discrete motion data that can be numerically modeled using linear aerodynamic theory or 6-degrees-of- freedom equations of motion. The values of Fφ...Prediction Excel® Spreadsheet shown in figure 9. The Gamma at Impact Spreadsheet uses the linear aerodynamics model , equations 5 and 6, to calculate αT...trajectory angle error via consideration of the RMS fit errors of the actual firings. However, the linear aerodynamics model does not include this effect

Statistical mechanics of shell models for two-dimensional turbulence

NASA Astrophysics Data System (ADS)

Aurell, E.; Boffetta, G.; Crisanti, A.; Frick, P.; Paladin, G.; Vulpiani, A.

1994-12-01

We study shell models that conserve the analogs of energy and enstrophy and hence are designed to mimic fluid turbulence in two-dimensions (2D). The main result is that the observed state is well described as a formal statistical equilibrium, closely analogous to the approach to two-dimensional ideal hydrodynamics of Onsager [Nuovo Cimento Suppl. 6, 279 (1949)], Hopf [J. Rat. Mech. Anal. 1, 87 (1952)], and Lee [Q. Appl. Math. 10, 69 (1952)]. In the presence of forcing and dissipation we observe a forward flux of enstrophy and a backward flux of energy. These fluxes can be understood as mean diffusive drifts from a source to two sinks in a system which is close to local equilibrium with Lagrange multipliers (``shell temperatures'') changing slowly with scale. This is clear evidence that the simplest shell models are not adequate to reproduce the main features of two-dimensional turbulence. The dimensional predictions on the power spectra from a supposed forward cascade of enstrophy and from one branch of the formal statistical equilibrium coincide in these shell models in contrast to the corresponding predictions for the Navier-Stokes and Euler equations in 2D. This coincidence has previously led to the mistaken conclusion that shell models exhibit a forward cascade of enstrophy. We also study the dynamical properties of the models and the growth of perturbations.

Using Modeling to Predict Medical Requirements for Special Operations Missions

DTIC Science & Technology

2008-07-30

Ventilator 280 Patient Discharge Instructions 044 Setup Drainage Bottles/Pleurevac 359 Induce Local Anesthesia 046 Maintain Chest Tube Suction 453 Closed...Incision) Z094 Extremity Traction, Application/Adjust 110 Test Vision Z103 Re-Establish IV Access ( Intraosseous ) 121 Eye Irrigation Z277 Prepare For Evac

Satisfying Friendship Maintenance Expectations: The Role of Friendship Standards and Biological Sex

ERIC Educational Resources Information Center

Hall, Jeffrey A.; Larson, Kiley A.; Watts, Amber

2011-01-01

The ideal standards model predicts linear relationship among friendship standards, expectation fulfillment, and relationship satisfaction. Using a diary method, 197 participants reported on expectation fulfillment in interactions with one best, one close, and one casual friend (N = 591) over five days (2,388 interactions). Using multilevel…

Grief and the Role of the Inner Representation of the Deceased.

ERIC Educational Resources Information Center

Marwit, Samuel J.; Klass, Dennis

1995-01-01

Studied whether memories of deceased play active roles in ongoing lives of survivors. Seventy-one people described a significant death. Four roles were reliably identified and labeled role model, situation specific guidance, values clarification, and remembrance formation. Role adoption was predicted by closeness of relationship and suddenness of…

A Simple Close Range Photogrammetry Technique to Assess Soil Erosion in the Field

USDA-ARS?s Scientific Manuscript database

Evaluating the performance of a soil erosion prediction model depends on the ability to accurately measure the gain or loss of sediment in an area. Recent development in acquiring detailed surface elevation data (DEM) makes it feasible to assess soil erosion and deposition spatially. Digital photogr...

Testing the generality of above-ground biomass allometry across plant functional types at the continent scale.

PubMed

Paul, Keryn I; Roxburgh, Stephen H; Chave, Jerome; England, Jacqueline R; Zerihun, Ayalsew; Specht, Alison; Lewis, Tom; Bennett, Lauren T; Baker, Thomas G; Adams, Mark A; Huxtable, Dan; Montagu, Kelvin D; Falster, Daniel S; Feller, Mike; Sochacki, Stan; Ritson, Peter; Bastin, Gary; Bartle, John; Wildy, Dan; Hobbs, Trevor; Larmour, John; Waterworth, Rob; Stewart, Hugh T L; Jonson, Justin; Forrester, David I; Applegate, Grahame; Mendham, Daniel; Bradford, Matt; O'Grady, Anthony; Green, Daryl; Sudmeyer, Rob; Rance, Stan J; Turner, John; Barton, Craig; Wenk, Elizabeth H; Grove, Tim; Attiwill, Peter M; Pinkard, Elizabeth; Butler, Don; Brooksbank, Kim; Spencer, Beren; Snowdon, Peter; O'Brien, Nick; Battaglia, Michael; Cameron, David M; Hamilton, Steve; McAuthur, Geoff; Sinclair, Jenny

2016-06-01

Accurate ground-based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost-effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15 054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for above-ground biomass prediction. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multistemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power-law models explained 84-95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand-based biomass from allometric models of varying levels of generalization (species-specific, plant functional type) were validated using whole-plot harvest data from 17 contrasting stands (range: 9-356 Mg ha(-1) ). Losses in efficiency of prediction were <1% if generalized models were used in place of species-specific models. Furthermore, application of generalized multispecies models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand-level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost-effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species-specific models is only warranted when gains in accuracy of stand-based predictions are relatively high (e.g. high-value monocultures). © 2015 John Wiley & Sons Ltd.

The morphological state space revisited: what do phylogenetic patterns in homoplasy tell us about the number of possible character states?

PubMed Central

Hoyal Cuthill, Jennifer F.

2015-01-01

Biological variety and major evolutionary transitions suggest that the space of possible morphologies may have varied among lineages and through time. However, most models of phylogenetic character evolution assume that the potential state space is finite. Here, I explore what the morphological state space might be like, by analysing trends in homoplasy (repeated derivation of the same character state). Analyses of ten published character matrices are compared against computer simulations with different state space models: infinite states, finite states, ordered states and an ‘inertial' model, simulating phylogenetic constraints. Of these, only the infinite states model results in evolution without homoplasy, a prediction which is not generally met by real phylogenies. Many authors have interpreted the ubiquity of homoplasy as evidence that the number of evolutionary alternatives is finite. However, homoplasy is also predicted by phylogenetic constraints on the morphological distance that can be traversed between ancestor and descendent. Phylogenetic rarefaction (sub-sampling) shows that finite and inertial state spaces do produce contrasting trends in the distribution of homoplasy. Two clades show trends characteristic of phylogenetic inertia, with decreasing homoplasy (increasing consistency index) as we sub-sample more distantly related taxa. One clade shows increasing homoplasy, suggesting exhaustion of finite states. Different clades may, therefore, show different patterns of character evolution. However, when parsimony uninformative characters are excluded (which may occur without documentation in cladistic studies), it may no longer be possible to distinguish inertial and finite state spaces. Interestingly, inertial models predict that homoplasy should be clustered among comparatively close relatives (parallel evolution), whereas finite state models do not. If morphological evolution is often inertial in nature, then homoplasy (false homology) may primarily occur between close relatives, perhaps being replaced by functional analogy at higher taxonomic scales. PMID:26640650

Simulating closed- and open-loop voluntary movement: a nonlinear control-systems approach.

PubMed

Davidson, Paul R; Jones, Richard D; Andreae, John H; Sirisena, Harsha R

2002-11-01

In many recent human motor control models, including feedback-error learning and adaptive model theory (AMT), feedback control is used to correct errors while an inverse model is simultaneously tuned to provide accurate feedforward control. This popular and appealing hypothesis, based on a combination of psychophysical observations and engineering considerations, predicts that once the tuning of the inverse model is complete the role of feedback control is limited to the correction of disturbances. This hypothesis was tested by looking at the open-loop behavior of the human motor system during adaptation. An experiment was carried out involving 20 normal adult subjects who learned a novel visuomotor relationship on a pursuit tracking task with a steering wheel for input. During learning, the response cursor was periodically blanked, removing all feedback about the external system (i.e., about the relationship between hand motion and response cursor motion). Open-loop behavior was not consistent with a progressive transfer from closed- to open-loop control. Our recently developed computational model of the brain--a novel nonlinear implementation of AMT--was able to reproduce the observed closed- and open-loop results. In contrast, other control-systems models exhibited only minimal feedback control following adaptation, leading to incorrect open-loop behavior. This is because our model continues to use feedback to control slow movements after adaptation is complete. This behavior enhances the internal stability of the inverse model. In summary, our computational model is currently the only motor control model able to accurately simulate the closed- and open-loop characteristics of the experimental response trajectories.

Optical fiber sensors and signal processing for intelligent structure monitoring

NASA Technical Reports Server (NTRS)

Thomas, Daniel; Cox, Dave; Lindner, D. K.; Claus, R. O.

1989-01-01

Few mode optical fibers have been shown to produce predictable interference patterns when placed under strain. The use is described of a modal domain sensor in a vibration control experiment. An optical fiber is bonded along the length of a flexible beam. Output from the modal domain sensor is used to suppress vibrations induced in the beam. A distributed effect model for the modal domain sensor is developed. This model is combined with the beam and actuator dynamics to produce a system suitable for control design. Computer simulations predict open and closed loop dynamic responses. An experimental apparatus is described and experimental results are presented.

Fluorescence quenching near small metal nanoparticles.

PubMed

Pustovit, V N; Shahbazyan, T V

2012-05-28

We develop a microscopic model for fluorescence of a molecule (or semiconductor quantum dot) near a small metal nanoparticle. When a molecule is situated close to metal surface, its fluorescence is quenched due to energy transfer to the metal. We perform quantum-mechanical calculations of energy transfer rates for nanometer-sized Au nanoparticles and find that nonlocal and quantum-size effects significantly enhance dissipation in metal as compared to those predicted by semiclassical electromagnetic models. However, the dependence of transfer rates on molecule's distance to metal nanoparticle surface, d, is significantly weaker than the d(-4) behavior for flat metal surface with a sharp boundary predicted by previous calculations within random phase approximation.

Major Mergers in CANDELS up to z=3: Calibrating the Close-Pair Method Using Semi-Analytic Models and Baryonic Mass Ratio Estimates

NASA Astrophysics Data System (ADS)

Mantha, Kameswara; McIntosh, Daniel H.; Conselice, Christopher; Cook, Joshua S.; Croton, Darren J.; Dekel, Avishai; Ferguson, Henry C.; Hathi, Nimish; Kodra, Dritan; Koo, David C.; Lotz, Jennifer M.; Newman, Jeffrey A.; Popping, Gergo; Rafelski, Marc; Rodriguez-Gomez, Vicente; Simmons, Brooke D.; Somerville, Rachel; Straughn, Amber N.; Snyder, Gregory; Wuyts, Stijn; Yu, Lu; Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS) Team

2018-01-01

Cosmological simulations predict that the rate of merging between similar-mass massive galaxies should increase towards early cosmic-time. We study the incidence of major (stellar mass ratio SMR<4) close-pairs among log(Mstellar/Msun) > 10.3 galaxies spanning 01.5 in strong disagreement with theoretical merger rate predictions. On the other hand, if we compare to a simulation-tuned, evolving timescale prescription from Snyder et al., 2017, we find that the merger rate evolution agrees with theory out to z=3. These results highlight the need for robust calibrations on the complex and presumably redshift-dependent pair-to-merger-rate conversion factors to improve constraints of the empirical merger history. To address this, we use a unique compilation of mock datasets produced by three independent state-of-the-art Semi-Analytic Models (SAMs). We present preliminary calibrations of the close-pair observability timescale and outlier fraction as a function of redshift, stellar-mass, mass-ratio, and local over-density. Furthermore, to verify the hypothesis by previous empirical studies that SMR-selection of major pairs may be biased, we present a new analysis of the baryonic (gas+stars) mass ratios of a subset of close pairs in our sample. For the first time, our preliminary analysis highlights that a noticeable fraction of SMR-selected minor pairs (SMR>4) have major baryonic-mass ratios (BMR<4), which indicate that merger rates based on SMR selection may be under-estimated.

Predicting mutant selection in competition experiments with ciprofloxacin-exposed Escherichia coli.

PubMed

Khan, David D; Lagerbäck, Pernilla; Malmberg, Christer; Kristoffersson, Anders N; Wistrand-Yuen, Erik; Sha, Cao; Cars, Otto; Andersson, Dan I; Hughes, Diarmaid; Nielsen, Elisabet I; Friberg, Lena E

2018-03-01

Predicting competition between antibiotic-susceptible wild-type (WT) and less susceptible mutant (MT) bacteria is valuable for understanding how drug concentrations influence the emergence of resistance. Pharmacokinetic/pharmacodynamic (PK/PD) models predicting the rate and extent of takeover of resistant bacteria during different antibiotic pressures can thus be a valuable tool in improving treatment regimens. The aim of this study was to evaluate a previously developed mechanism-based PK/PD model for its ability to predict in vitro mixed-population experiments with competition between Escherichia coli (E. coli) WT and three well-defined E. coli resistant MTs when exposed to ciprofloxacin. Model predictions for each bacterial strain and ciprofloxacin concentration were made for in vitro static and dynamic time-kill experiments measuring CFU (colony forming units)/mL up to 24 h with concentrations close to or below the minimum inhibitory concentration (MIC), as well as for serial passage experiments with concentrations well below the MIC measuring ratios between the two strains with flow cytometry. The model was found to reasonably well predict the initial bacterial growth and killing of most static and dynamic time-kill competition experiments without need for parameter re-estimation. With parameter re-estimation of growth rates, an adequate fit was also obtained for the 6-day serial passage competition experiments. No bacterial interaction in growth was observed. This study demonstrates the predictive capacity of a PK/PD model and further supports the application of PK/PD modelling for prediction of bacterial kill in different settings, including resistance selection. Copyright © 2017 Elsevier B.V. and International Society of Chemotherapy. All rights reserved.

Predictive modeling: Solubility of C60 and C70 fullerenes in diverse solvents.

PubMed

Gupta, Shikha; Basant, Nikita

2018-06-01

Solubility of fullerenes imposes a major limitation to further advanced research and technological development using these novel materials. There have been continued efforts to discover better solvents and their properties that influence the solubility of fullerenes. Here, we have developed QSPR (quantitative structure-property relationship) models based on structural features of diverse solvents and large experimental data for predicting the solubility of C 60 and C 70 fullerenes. The developed models identified most relevant features of the solvents that encode the polarizability, polarity and lipophilicity properties which largely influence the solubilizing potential of the solvent for the fullerenes. We also established Inter-moieties solubility correlations (IMSC) based quantitative property-property relationship (QPPR) models for predicting solubility of C 60 and C 70 fullerenes. The QSPR and QPPR models were internally and externally validated deriving the most stringent statistical criteria and predicted C 60 and C 70 solubility values in different solvents were in close agreement with the experimental values. In test sets, the QSPR models yielded high correlations (R 2  > 0.964) and low root mean squared error of prediction errors (RMSEP< 0.25). Results of comparison with other studies indicated that the proposed models could effectively improve the accuracy and ability for predicting solubility of C 60 and C 70 fullerenes in solvents with diverse structures and would be useful in development of more effective solvents. Copyright © 2018 Elsevier Ltd. All rights reserved.

Groundwater depth prediction in a shallow aquifer in north China by a quantile regression model

NASA Astrophysics Data System (ADS)

Li, Fawen; Wei, Wan; Zhao, Yong; Qiao, Jiale

2017-01-01

There is a close relationship between groundwater level in a shallow aquifer and the surface ecological environment; hence, it is important to accurately simulate and predict the groundwater level in eco-environmental construction projects. The multiple linear regression (MLR) model is one of the most useful methods to predict groundwater level (depth); however, the predicted values by this model only reflect the mean distribution of the observations and cannot effectively fit the extreme distribution data (outliers). The study reported here builds a prediction model of groundwater-depth dynamics in a shallow aquifer using the quantile regression (QR) method on the basis of the observed data of groundwater depth and related factors. The proposed approach was applied to five sites in Tianjin city, north China, and the groundwater depth was calculated in different quantiles, from which the optimal quantile was screened out according to the box plot method and compared to the values predicted by the MLR model. The results showed that the related factors in the five sites did not follow the standard normal distribution and that there were outliers in the precipitation and last-month (initial state) groundwater-depth factors because the basic assumptions of the MLR model could not be achieved, thereby causing errors. Nevertheless, these conditions had no effect on the QR model, as it could more effectively describe the distribution of original data and had a higher precision in fitting the outliers.

Discrete Spring Model for Predicting Delamination Growth in Z-Fiber Reinforced DCB Specimens

NASA Technical Reports Server (NTRS)

Ratcliffe, James G.; OBrien, T. Kevin

2004-01-01

Beam theory analysis was applied to predict delamination growth in Double Cantilever Beam (DCB) specimens reinforced in the thickness direction with pultruded pins, known as Z-fibers. The specimen arms were modeled as cantilever beams supported by discrete springs, which were included to represent the pins. A bi-linear, irreversible damage law was used to represent Z-fiber damage, the parameters of which were obtained from previous experiments. Closed-form solutions were developed for specimen compliance and displacements corresponding to Z-fiber row locations. A solution strategy was formulated to predict delamination growth, in which the parent laminate mode I critical strain energy release rate was used as the criterion for delamination growth. The solution procedure was coded into FORTRAN 90, giving a dedicated software tool for performing the delamination prediction. Comparison of analysis results with previous analysis and experiment showed good agreement, yielding an initial verification for the analytical procedure.

Discrete Spring Model for Predicting Delamination Growth in Z-Fiber Reinforced DCB Specimens

NASA Technical Reports Server (NTRS)

Ratcliffe, James G.; O'Brien, T. Kevin

2004-01-01

Beam theory analysis was applied to predict delamination growth in DCB specimens reinforced in the thickness direction with pultruded pins, known as Z-fibers. The specimen arms were modeled as cantilever beams supported by discrete springs, which were included to represent the pins. A bi-linear, irreversible damage law was used to represent Z-fiber damage, the parameters of which were obtained from previous experiments. Closed-form solutions were developed for specimen compliance and displacements corresponding to Z-fiber row locations. A solution strategy was formulated to predict delamination growth, in which the parent laminate mode I fracture toughness was used as the criterion for delamination growth. The solution procedure was coded into FORTRAN 90, giving a dedicated software tool for performing the delamination prediction. Comparison of analysis results with previous analysis and experiment showed good agreement, yielding an initial verification for the analytical procedure.

Modeling the Effect of Summertime Heating on Urban Runoff Temperature

NASA Astrophysics Data System (ADS)

Thompson, A. M.; Gemechu, A. L.; Norman, J. M.; Roa-Espinosa, A.

2007-12-01

Urban impervious surfaces absorb and store thermal energy, particularly during warm summer months. During a rainfall/runoff event, thermal energy is transferred from the impervious surface to the runoff, causing it to become warmer. As this higher temperature runoff enters receiving waters, it can be harmful to coldwater habitat. A simple model has been developed for the net energy flux at the impervious surfaces of urban areas to account for the heat transferred to runoff. Runoff temperature is determined as a function of the physical characteristics of the impervious areas, the weather, and the heat transfer between the moving film of runoff and the heated impervious surfaces that commonly exist in urban areas. Runoff from pervious surfaces was predicted using the Green- Ampt Mein-Larson infiltration excess method. Theoretical results were compared to experimental results obtained from a plot-scale field study conducted at the University of Wisconsin's West Madison Agricultural Research Station. Surface temperatures and runoff temperatures from asphalt and sod plots were measured throughout 15 rainfall simulations under various climatic conditions during the summers of 2004 and 2005. Average asphalt runoff temperatures ranged from 23.2°C to 37.1°C. Predicted asphalt runoff temperatures were in close agreement with measured values for most of the simulations (average RMSE = 4.0°C). Average pervious runoff temperatures ranged from 19.7° to 29.9°C and were closely approximated by the rainfall temperature (RMSE = 2.8°C). Predicted combined asphalt and sod runoff temperatures using a flow-weighted average were in close agreement with observed values (average RMSE = 3.5°C).

Stress distribution in the temporo-mandibular joint discs during jaw closing: a high-resolution three-dimensional finite-element model analysis.

PubMed

Savoldelli, Charles; Bouchard, Pierre-Olivier; Loudad, Raounak; Baque, Patrick; Tillier, Yannick

2012-07-01

This study aims at analysing the stresses distribution in the temporomandibular joint (TMJ) using a complete high-resolution finite element model (FE Model). This model is used here to analyse the stresses distribution in the discs during a closing jaw cycle. In the end, this model enables the prediction of the stress evolution in the TMJ disc submitted to various loadings induced by mandibular trauma, surgery or parafunction. The geometric data for the model were obtained from MRI and CT scans images of a healthy male patient. Surface and volume meshes were successively obtained using a 3D image segmentation software (AMIRA(®)). Bone components of skull and mandible, both of joint discs, temporomandibular capsules and ligaments and dental arches were meshed as separate bodies. The volume meshes were transferred to the FE analysis software (FORGE(®)). Material properties were assigned for each region. Boundary conditions for closing jaw simulations were represented by different load directions of jaws muscles. The von Mises stresses distribution in both joint discs during closing conditions was analyzed. The pattern of von Mises stresses in the TMJ discs is non-symmetric and changed continuously during jaw movement. Maximal stress is reached on the surface disc in areas in contact with others bodies. The three-dimension finite element model of masticatory system will make it possible to simulate different conditions that appear to be important in the cascade of events leading to joint damage.

Towards Assessing the Human Trajectory Planning Horizon

PubMed Central

Nitsch, Verena; Meinzer, Dominik; Wollherr, Dirk

2016-01-01

Mobile robots are envisioned to cooperate closely with humans and to integrate seamlessly into a shared environment. For locomotion, these environments resemble traversable areas which are shared between multiple agents like humans and robots. The seamless integration of mobile robots into these environments requires accurate predictions of human locomotion. This work considers optimal control and model predictive control approaches for accurate trajectory prediction and proposes to integrate aspects of human behavior to improve their performance. Recently developed models are not able to reproduce accurately trajectories that result from sudden avoidance maneuvers. Particularly, the human locomotion behavior when handling disturbances from other agents poses a problem. The goal of this work is to investigate whether humans alter their trajectory planning horizon, in order to resolve abruptly emerging collision situations. By modeling humans as model predictive controllers, the influence of the planning horizon is investigated in simulations. Based on these results, an experiment is designed to identify, whether humans initiate a change in their locomotion planning behavior while moving in a complex environment. The results support the hypothesis, that humans employ a shorter planning horizon to avoid collisions that are triggered by unexpected disturbances. Observations presented in this work are expected to further improve the generalizability and accuracy of prediction methods based on dynamic models. PMID:27936015

Towards Assessing the Human Trajectory Planning Horizon.

PubMed

Carton, Daniel; Nitsch, Verena; Meinzer, Dominik; Wollherr, Dirk

2016-01-01

Mobile robots are envisioned to cooperate closely with humans and to integrate seamlessly into a shared environment. For locomotion, these environments resemble traversable areas which are shared between multiple agents like humans and robots. The seamless integration of mobile robots into these environments requires accurate predictions of human locomotion. This work considers optimal control and model predictive control approaches for accurate trajectory prediction and proposes to integrate aspects of human behavior to improve their performance. Recently developed models are not able to reproduce accurately trajectories that result from sudden avoidance maneuvers. Particularly, the human locomotion behavior when handling disturbances from other agents poses a problem. The goal of this work is to investigate whether humans alter their trajectory planning horizon, in order to resolve abruptly emerging collision situations. By modeling humans as model predictive controllers, the influence of the planning horizon is investigated in simulations. Based on these results, an experiment is designed to identify, whether humans initiate a change in their locomotion planning behavior while moving in a complex environment. The results support the hypothesis, that humans employ a shorter planning horizon to avoid collisions that are triggered by unexpected disturbances. Observations presented in this work are expected to further improve the generalizability and accuracy of prediction methods based on dynamic models.

An improved model to predict bandwidth enhancement in an inductively tuned common source amplifier.

PubMed

Reza, Ashif; Misra, Anuraag; Das, Parnika

2016-05-01

This paper presents an improved model for the prediction of bandwidth enhancement factor (BWEF) in an inductively tuned common source amplifier. In this model, we have included the effect of drain-source channel resistance of field effect transistor along with load inductance and output capacitance on BWEF of the amplifier. A frequency domain analysis of the model is performed and a closed-form expression is derived for BWEF of the amplifier. A prototype common source amplifier is designed and tested. The BWEF of amplifier is obtained from the measured frequency response as a function of drain current and load inductance. In the present work, we have clearly demonstrated that inclusion of drain-source channel resistance in the proposed model helps to estimate the BWEF, which is accurate to less than 5% as compared to the measured results.

Modeling daily discharge responses of a large karstic aquifer using soft computing methods: Artificial neural network and neuro-fuzzy

NASA Astrophysics Data System (ADS)

Kurtulus, Bedri; Razack, Moumtaz

2010-02-01

SummaryThis paper compares two methods for modeling karst aquifers, which are heterogeneous, highly non-linear, and hierarchical systems. There is a clear need to model these systems given the crucial role they play in water supply in many countries. In recent years, the main components of soft computing (fuzzy logic (FL), and Artificial Neural Networks, (ANNs)) have come to prevail in the modeling of complex non-linear systems in different scientific and technologic disciplines. In this study, Artificial Neural Networks and Adaptive Neuro-Fuzzy Interface System (ANFIS) methods were used for the prediction of daily discharge of karstic aquifers and their capability was compared. The approach was applied to 7 years of daily data of La Rochefoucauld karst system in south-western France. In order to predict the karst daily discharges, single-input (rainfall, piezometric level) vs. multiple-input (rainfall and piezometric level) series were used. In addition to these inputs, all models used measured or simulated discharges from the previous days with a specified delay. The models were designed in a Matlab™ environment. An automatic procedure was used to select the best calibrated models. Daily discharge predictions were then performed using the calibrated models. Comparing predicted and observed hydrographs indicates that both models (ANN and ANFIS) provide close predictions of the karst daily discharges. The summary statistics of both series (observed and predicted daily discharges) are comparable. The performance of both models is improved when the number of inputs is increased from one to two. The root mean square error between the observed and predicted series reaches a minimum for two-input models. However, the ANFIS model demonstrates a better performance than the ANN model to predict peak flow. The ANFIS approach demonstrates a better generalization capability and slightly higher performance than the ANN, especially for peak discharges.

Validating models of target acquisition performance in the dismounted soldier context

NASA Astrophysics Data System (ADS)

Glaholt, Mackenzie G.; Wong, Rachel K.; Hollands, Justin G.

2018-04-01

The problem of predicting real-world operator performance with digital imaging devices is of great interest within the military and commercial domains. There are several approaches to this problem, including: field trials with imaging devices, laboratory experiments using imagery captured from these devices, and models that predict human performance based on imaging device parameters. The modeling approach is desirable, as both field trials and laboratory experiments are costly and time-consuming. However, the data from these experiments is required for model validation. Here we considered this problem in the context of dismounted soldiering, for which detection and identification of human targets are essential tasks. Human performance data were obtained for two-alternative detection and identification decisions in a laboratory experiment in which photographs of human targets were presented on a computer monitor and the images were digitally magnified to simulate range-to-target. We then compared the predictions of different performance models within the NV-IPM software package: Targeting Task Performance (TTP) metric model and the Johnson model. We also introduced a modification to the TTP metric computation that incorporates an additional correction for target angular size. We examined model predictions using NV-IPM default values for a critical model constant, V50, and we also considered predictions when this value was optimized to fit the behavioral data. When using default values, certain model versions produced a reasonably close fit to the human performance data in the detection task, while for the identification task all models substantially overestimated performance. When using fitted V50 values the models produced improved predictions, though the slopes of the performance functions were still shallow compared to the behavioral data. These findings are discussed in relation to the models' designs and parameters, and the characteristics of the behavioral paradigm.

Prediction of stock market characteristics using neural networks

NASA Astrophysics Data System (ADS)

Pandya, Abhijit S.; Kondo, Tadashi; Shah, Trupti U.; Gandhi, Viraf R.

1999-03-01

International stocks trading, currency and derivative contracts play an increasingly important role for many investors. Neural network is playing a dominant role in predicting the trends in stock markets and in currency speculation. In most economic applications, the success rate using neural networks is limited to 70 - 80%. By means of the new approach of GMDH (Group Method of Data Handling) neural network predictions can be improved further by 10 - 15%. It was observed in our study, that using GMDH for short, noisy or inaccurate data sample resulted in the best-simplified model. In the GMDH model accuracy of prediction is higher and the structure is simpler than that of the usual full physical model. As an example, prediction of the activity on the stock exchange in New York was considered. On the basis of observations in the period of Jan '95 to July '98, several variables of the stock market (S&P 500, Small Cap, Dow Jones, etc.) were predicted. A model portfolio using various stocks (Amgen, Merck, Office Depot, etc.) was built and its performance was evaluated based on neural network forecasting of the closing prices. Comparison of results was made with various neural network models such as Multilayer Perceptrons with Back Propagation, and the GMDH neural network. Variations of GMDH were studied and analysis of their performance is reported in the paper.

Integrated identification, modeling and control with applications

NASA Astrophysics Data System (ADS)

Shi, Guojun

This thesis deals with the integration of system design, identification, modeling and control. In particular, six interdisciplinary engineering problems are addressed and investigated. Theoretical results are established and applied to structural vibration reduction and engine control problems. First, the data-based LQG control problem is formulated and solved. It is shown that a state space model is not necessary to solve this problem; rather a finite sequence from the impulse response is the only model data required to synthesize an optimal controller. The new theory avoids unnecessary reliance on a model, required in the conventional design procedure. The infinite horizon model predictive control problem is addressed for multivariable systems. The basic properties of the receding horizon implementation strategy is investigated and the complete framework for solving the problem is established. The new theory allows the accommodation of hard input constraints and time delays. The developed control algorithms guarantee the closed loop stability. A closed loop identification and infinite horizon model predictive control design procedure is established for engine speed regulation. The developed algorithms are tested on the Cummins Engine Simulator and desired results are obtained. A finite signal-to-noise ratio model is considered for noise signals. An information quality index is introduced which measures the essential information precision required for stabilization. The problems of minimum variance control and covariance control are formulated and investigated. Convergent algorithms are developed for solving the problems of interest. The problem of the integrated passive and active control design is addressed in order to improve the overall system performance. A design algorithm is developed, which simultaneously finds: (i) the optimal values of the stiffness and damping ratios for the structure, and (ii) an optimal output variance constrained stabilizing controller such that the active control energy is minimized. A weighted q-Markov COVER method is introduced for identification with measurement noise. The result is use to develop an iterative closed loop identification/control design algorithm. The effectiveness of the algorithm is illustrated by experimental results.

Sound radiation of a railway rail in close proximity to the ground

NASA Astrophysics Data System (ADS)

Zhang, Xianying; Squicciarini, Giacomo; Thompson, David J.

2016-02-01

The sound radiation of a railway in close to proximity to a ground (both rigid and absorptive) is predicted by the boundary element method (BEM) in two dimensions (2D). Results are given in terms of the radiation ratio for both vertical and lateral motion of the rail, when the effects of the acoustic boundary conditions due to the sleepers and ballast are taken into account in the numerical models. Allowance is made for the effect of wave propagation along the rail by applying a correction in the 2D modelling. It is shown that the 2D correction is necessary at low frequency, for both vertical and lateral motion of an unsupported rail, especially in the vicinity of the corresponding critical frequency. However, this correction is not applicable for a supported rail; for vertical motion no correction is needed to the 2D result while for lateral motion the corresponding correction would depend on the pad stiffness. Finally, the corresponding numerical predictions of the sound radiation from a rail are verified by comparison with experimental results obtained using a 1/5 scale rail model in different configurations.

Improved Speech Coding Based on Open-Loop Parameter Estimation

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Chen, Ya-Chin; Longman, Richard W.

2000-01-01

A nonlinear optimization algorithm for linear predictive speech coding was developed early that not only optimizes the linear model coefficients for the open loop predictor, but does the optimization including the effects of quantization of the transmitted residual. It also simultaneously optimizes the quantization levels used for each speech segment. In this paper, we present an improved method for initialization of this nonlinear algorithm, and demonstrate substantial improvements in performance. In addition, the new procedure produces monotonically improving speech quality with increasing numbers of bits used in the transmitted error residual. Examples of speech encoding and decoding are given for 8 speech segments and signal to noise levels as high as 47 dB are produced. As in typical linear predictive coding, the optimization is done on the open loop speech analysis model. Here we demonstrate that minimizing the error of the closed loop speech reconstruction, instead of the simpler open loop optimization, is likely to produce negligible improvement in speech quality. The examples suggest that the algorithm here is close to giving the best performance obtainable from a linear model, for the chosen order with the chosen number of bits for the codebook.

Extending Validated Human Performance Models to Explore NextGen Concepts

NASA Technical Reports Server (NTRS)

Gore, Brian Francis; Hooey, Becky Lee; Mahlstedt, Eric; Foyle, David C.

2012-01-01

To meet the expected increases in air traffic demands, NASA and FAA are researching and developing Next Generation Air Transportation System (NextGen) concepts. NextGen will require substantial increases in the data available to pilots on the flight deck (e.g., weather,wake, traffic trajectory predictions, etc.) to support more precise and closely coordinated operations (e.g., self-separation, RNAV/RNP, and closely spaced parallel operations, CSPOs). These NextGen procedures and operations, along with the pilot's roles and responsibilities, must be designed with consideration of the pilot's capabilities and limitations. Failure to do so will leave the pilots, and thus the entire aviation system, vulnerable to error. A validated Man-machine Integration and design Analysis System (MIDAS) v5 model was extended to evaluate anticipated changes to flight deck and controller roles and responsibilities in NextGen approach and Land operations. Compared to conditions when the controllers are responsible for separation on decent to land phase of flight, the output from these model predictions suggest that the flight deck response time to detect the lead aircraft blunder will decrease, pilot scans to the navigation display will increase, and workload will increase.

Application of empirical mode decomposition with local linear quantile regression in financial time series forecasting.

PubMed

Jaber, Abobaker M; Ismail, Mohd Tahir; Altaher, Alsaidi M

2014-01-01

This paper mainly forecasts the daily closing price of stock markets. We propose a two-stage technique that combines the empirical mode decomposition (EMD) with nonparametric methods of local linear quantile (LLQ). We use the proposed technique, EMD-LLQ, to forecast two stock index time series. Detailed experiments are implemented for the proposed method, in which EMD-LPQ, EMD, and Holt-Winter methods are compared. The proposed EMD-LPQ model is determined to be superior to the EMD and Holt-Winter methods in predicting the stock closing prices.

Localized magnetism in liquid Al80Mn20 alloys: A first-principles investigation

NASA Astrophysics Data System (ADS)

Jakse, N.; LeBacq, O.; Pasturel, A.

2006-04-01

We present first-principles investigations of the formation of magnetic moments in liquid Al80Mn20 alloys as a function of temperature. We predict the existence of large magnetic moments on Mn atoms which are close to that of the single-impurity limit. The wide distribution of moments can be understood in terms of fluctuations in the local environment. Our calculations also predict that thermal expansion effects within the single-impurity model mainly explain the striking increase of magnetism with temperature.

High Pressure Regenerative Turbine Engine: 21st Century Propulsion

NASA Technical Reports Server (NTRS)

Lear, W. E.; Laganelli, A. L.; Senick, Paul (Technical Monitor)

2001-01-01

A novel semi-closed cycle gas turbine engine was demonstrated and was found to meet the program goals. The proof-of-principle test of the High Pressure Regenerative Turbine Engine produced data that agreed well with models, enabling more confidence in designing future prototypes based on this concept. Emission levels were significantly reduced as predicted as a natural attribute of this power cycle. Engine testing over a portion of the operating range allowed verification of predicted power increases compared to the baseline.

Validation of Model-Based Prognostics for Pneumatic Valves in a Demonstration Testbed

DTIC Science & Technology

2014-10-02

predict end of life ( EOL ) and remaining useful life (RUL). The approach still follows the general estimation-prediction framework devel- oped in the...atmosphere, with linearly increasing leak area. kA2leak = Cleak (16) We define valve end of life ( EOL ) through open/close time limits of the valves, as in...represents end of life ( EOL ), and ∆kE represents remaining useful life (RUL). For valves, timing requirements are provided that de- fine the maximum

A nonlinear CDM based damage growth law for ductile materials

NASA Astrophysics Data System (ADS)

Gautam, Abhinav; Priya Ajit, K.; Sarkar, Prabir Kumar

2018-02-01

A nonlinear ductile damage growth criterion is proposed based on continuum damage mechanics (CDM) approach. The model is derived in the framework of thermodynamically consistent CDM assuming damage to be isotropic. In this study, the damage dissipation potential is also derived to be a function of varying strain hardening exponent in addition to damage strain energy release rate density. Uniaxial tensile tests and load-unload-cyclic tensile tests for AISI 1020 steel, AISI 1030 steel and Al 2024 aluminum alloy are considered for the determination of their respective damage variable D and other parameters required for the model(s). The experimental results are very closely predicted, with a deviation of 0%-3%, by the proposed model for each of the materials. The model is also tested with predictabilities of damage growth by other models in the literature. Present model detects the state of damage quantitatively at any level of plastic strain and uses simpler material tests to find the parameters of the model. So, it should be useful in metal forming industries to assess the damage growth for the desired deformation level a priori. The superiority of the new model is clarified by the deviations in the predictability of test results by other models.

Importance of positive feedbacks and overconfidence in a self-fulfilling Ising model of financial markets

NASA Astrophysics Data System (ADS)

Sornette, Didier; Zhou, Wei-Xing

2006-10-01

Following a long tradition of physicists who have noticed that the Ising model provides a general background to build realistic models of social interactions, we study a model of financial price dynamics resulting from the collective aggregate decisions of agents. This model incorporates imitation, the impact of external news and private information. It has the structure of a dynamical Ising model in which agents have two opinions (buy or sell) with coupling coefficients, which evolve in time with a memory of how past news have explained realized market returns. We study two versions of the model, which differ on how the agents interpret the predictive power of news. We show that the stylized facts of financial markets are reproduced only when agents are overconfident and mis-attribute the success of news to predict return to herding effects, thereby providing positive feedbacks leading to the model functioning close to the critical point. Our model exhibits a rich multifractal structure characterized by a continuous spectrum of exponents of the power law relaxation of endogenous bursts of volatility, in good agreement with previous analytical predictions obtained with the multifractal random walk model and with empirical facts.

Modeling and control for vibration suppression of a flexible smart structure

NASA Technical Reports Server (NTRS)

Dosch, J.; Leo, D.; Inman, D.

1993-01-01

Theoretical and experimental results of the modeling and control of a flexible ribbed antenna are presented. The antenna consists of eight flexible ribs which constitutes a smart antenna in the sense that the actuator and sensors are an integral part of the structure. The antenna exhibits closely space and repeated modes, thus multi-input multi-output (MIMO) control is necessary for controllability and observability of the structure. The structure also exhibits mode localization phenomenon and contains post buckled members making an accurate finite element model of the structure difficult to obtain. An identified MIMO minimum order model of the antenna is synthesized from identified single-input single-output (SISO) transfer functions curve fit in the frequency domain. The identified model is used to design a positive position feedback (PPF) controller that increases damping in all of the modes in the targeted frequency range. Due to the accuracy of the open loop model of the antenna, the closed loop response predicted by the identified model correlates well wtih experimental results.

New closed-form approximation for skin chromophore mapping.

PubMed

Välisuo, Petri; Kaartinen, Ilkka; Tuchin, Valery; Alander, Jarmo

2011-04-01

The concentrations of blood and melanin in skin can be estimated based on the reflectance of light. Many models for this estimation have been built, such as Monte Carlo simulation, diffusion models, and the differential modified Beer-Lambert law. The optimization-based methods are too slow for chromophore mapping of high-resolution spectral images, and the differential modified Beer-Lambert is not often accurate enough. Optimal coefficients for the differential Beer-Lambert model are calculated by differentiating the diffusion model, optimized to the normal skin spectrum. The derivatives are then used in predicting the difference in chromophore concentrations from the difference in absorption spectra. The accuracy of the method is tested both computationally and experimentally using a Monte Carlo multilayer simulation model, and the data are measured from the palm of a hand during an Allen's test, which modulates the blood content of skin. The correlations of the given and predicted blood, melanin, and oxygen saturation levels are correspondingly r = 0.94, r = 0.99, and r = 0.73. The prediction of the concentrations for all pixels in a 1-megapixel image would take ∼ 20 min, which is orders of magnitude faster than the methods based on optimization during the prediction.

A forecast for extinction debt in the presence of speciation.

PubMed

Sgardeli, Vasiliki; Iwasa, Yoh; Varvoglis, Harry; Halley, John M

2017-02-21

Predicting biodiversity relaxation following a disturbance is of great importance to conservation biology. Recently-developed models of stochastic community assembly allow us to predict the evolution of communities on the basis of mechanistic processes at the level of individuals. The neutral model of biodiversity, in particular, has provided closed-form solutions for the relaxation of biodiversity in isolated communities (no immigration or speciation). Here, we extend these results by deriving a relaxation curve for a neutral community in which new species are introduced through the mechanism of random fission speciation (RFS). The solution provides simple closed-form expressions for the equilibrium species richness, the relaxation time and the species-individual curve, which are good approximation to the more complicated formulas existing for the same model. The derivation of the relaxation curve is based on the assumption of a broken-stick species-abundance distribution (SAD) as an initial community configuration; yet for commonly observed SADs, the maximum deviation from the curve does not exceed 10%. Importantly, the solution confirms theoretical results and observations showing that the relaxation time increases with community size and thus habitat area. Such simple and analytically tractable models can help crystallize our ideas on the leading factors affecting biodiversity loss. Copyright © 2016 Elsevier Ltd. All rights reserved.

Software Tools for Developing and Simulating the NASA LaRC CMF Motion Base

NASA Technical Reports Server (NTRS)

Bryant, Richard B., Jr.; Carrelli, David J.

2006-01-01

The NASA Langley Research Center (LaRC) Cockpit Motion Facility (CMF) motion base has provided many design and analysis challenges. In the process of addressing these challenges, a comprehensive suite of software tools was developed. The software tools development began with a detailed MATLAB/Simulink model of the motion base which was used primarily for safety loads prediction, design of the closed loop compensator and development of the motion base safety systems1. A Simulink model of the digital control law, from which a portion of the embedded code is directly generated, was later added to this model to form a closed loop system model. Concurrently, software that runs on a PC was created to display and record motion base parameters. It includes a user interface for controlling time history displays, strip chart displays, data storage, and initializing of function generators used during motion base testing. Finally, a software tool was developed for kinematic analysis and prediction of mechanical clearances for the motion system. These tools work together in an integrated package to support normal operations of the motion base, simulate the end to end operation of the motion base system providing facilities for software-in-the-loop testing, mechanical geometry and sensor data visualizations, and function generator setup and evaluation.

A homogenized localizing gradient damage model with micro inertia effect

NASA Astrophysics Data System (ADS)

Wang, Zhao; Poh, Leong Hien

2018-07-01

The conventional gradient enhancement regularizes structural responses during material failure. However, it induces a spurious damage growth phenomenon, which is shown here to persist in dynamics. Similar issues were reported with the integral averaging approach. Consequently, the conventional nonlocal enhancement cannot adequately describe the dynamic fracture of quasi-brittle materials, particularly in the high strain rate regime, where a diffused damage profile precludes the development of closely spaced macrocracks. To this end, a homogenization theory is proposed to translate the micro processes onto the macro scale. Starting with simple elementary models at the micro scale to describe the fracture mechanisms, an additional kinematic field is introduced to capture the variations in deformation and velocity within a unit cell. An energetic equivalence between micro and macro is next imposed to ensure consistency at the two scales. The ensuing homogenized microforce balance resembles closely the conventional gradient expression, albeit with an interaction domain that decreases with damage, complemented by a micro inertia effect. Considering a direct single pressure bar example, the homogenized model is shown to resolve the non-physical responses obtained with conventional nonlocal enhancement. The predictive capability of the homogenized model is furthermore demonstrated by considering the spall tests of concrete, with good predictions on failure characteristics such as fragmentation profiles and dynamic tensile strengths, at three different loading rates.

A fuzzy logic model to forecast stock market momentum in Indonesia's property and real estate sector

NASA Astrophysics Data System (ADS)

Penawar, H. K.; Rustam, Z.

2017-07-01

The Capital market has the important role in Indonesia's economy. The capital market does not only support the economy of Indonesia but also being an indicator Indonesia's economy improvement. Something that has been traded in the capital market is stock (stock market). Nowadays, the stock market is full of uncertainty. That uncertainty values make predicting stock market is all that we have to do before we make a decision in the stock market. One that can be predicted in the stock market is momentum. To forecast stock market momentum, it can use fuzzy logic model. In the process of modeling, it will be used 14 days historical data that consisting the value of open, high, low, and close, to predict the next 5 days momentum categories. There are three momentum categories namely Bullish, Neutral, and Bearish. To illustrate the fuzzy logic model, we will use stocks data from several companies that listed on Indonesia Stock Exchange (IDX) in property and real estate sector.

Modeling Electrically Evoked Otoacoustic Emissions

NASA Astrophysics Data System (ADS)

Grosh, K.; Deo, N.; Parthasarathi, A. A.; Nuttall, A. L.; Zheng, J. F.; Ren, T. Y.

2003-02-01

Electrical evoked otoacoustic emissions (EEOAE) are used to investigate in vivo cochlear electromechanical function. Round window electrical stimulation gives rise to a broad frequency EEOAE response, from 100 Hz or below to 40 kHz in guinea pigs. Placing bipolar electrodes very close to the basilar membrane (in the scala vestibuli and scala tympani) gives rise to a much narrower frequency range of EEOAE, limited to around 20 kHz when the electrodes are placed near the 18 kHz best frequency place. Model predictions using a three dimensional fluid model in conjunction with a simple model for outer hair cell (OHC) activity are used to interpret the experimental results. The model is solved using a 2.5D finite-element formulation. Predictions show that the high-frequency limit of the excitation is determined by the spatial extent of the current stimulus (also called the current spread). The global peaks in the EEOAE spectra are interpreted as constructive interference between electrically evoked backward traveling waves and forward traveling waves reflected from the stapes. Steady-state response predictions of the model are presented.

A neuromathematical model of human information processing and its application to science content acquisition

NASA Astrophysics Data System (ADS)

Anderson, O. Roger

The rate of information processing during science learning and the efficiency of the learner in mobilizing relevant information in long-term memory as an aid in transmitting newly acquired information to stable storage in long-term memory are fundamental aspects of science content acquisition. These cognitive processes, moreover, may be substantially related in tempo and quality of organization to the efficiency of higher thought processes such as divergent thinking and problem-solving ability that characterize scientific thought. As a contribution to our quantitative understanding of these fundamental information processes, a mathematical model of information acquisition is presented and empirically evaluated in comparison to evidence obtained from experimental studies of science content acquisition. Computer-based models are used to simulate variations in learning parameters and to generate the theoretical predictions to be empirically tested. The initial tests of the predictive accuracy of the model show close agreement between predicted and actual mean recall scores in short-term learning tasks. Implications of the model for human information acquisition and possible future research are discussed in the context of the unique theoretical framework of the model.

Residue-Specific Side-Chain Polymorphisms via Particle Belief Propagation.

PubMed

Ghoraie, Laleh Soltan; Burkowski, Forbes; Li, Shuai Cheng; Zhu, Mu

2014-01-01

Protein side chains populate diverse conformational ensembles in crystals. Despite much evidence that there is widespread conformational polymorphism in protein side chains, most of the X-ray crystallography data are modeled by single conformations in the Protein Data Bank. The ability to extract or to predict these conformational polymorphisms is of crucial importance, as it facilitates deeper understanding of protein dynamics and functionality. In this paper, we describe a computational strategy capable of predicting side-chain polymorphisms. Our approach extends a particular class of algorithms for side-chain prediction by modeling the side-chain dihedral angles more appropriately as continuous rather than discrete variables. Employing a new inferential technique known as particle belief propagation, we predict residue-specific distributions that encode information about side-chain polymorphisms. Our predicted polymorphisms are in relatively close agreement with results from a state-of-the-art approach based on X-ray crystallography data, which characterizes the conformational polymorphisms of side chains using electron density information, and has successfully discovered previously unmodeled conformations.

A Combined Adaptive Neural Network and Nonlinear Model Predictive Control for Multirate Networked Industrial Process Control.

PubMed

Wang, Tong; Gao, Huijun; Qiu, Jianbin

2016-02-01

This paper investigates the multirate networked industrial process control problem in double-layer architecture. First, the output tracking problem for sampled-data nonlinear plant at device layer with sampling period T(d) is investigated using adaptive neural network (NN) control, and it is shown that the outputs of subsystems at device layer can track the decomposed setpoints. Then, the outputs and inputs of the device layer subsystems are sampled with sampling period T(u) at operation layer to form the index prediction, which is used to predict the overall performance index at lower frequency. Radial basis function NN is utilized as the prediction function due to its approximation ability. Then, considering the dynamics of the overall closed-loop system, nonlinear model predictive control method is proposed to guarantee the system stability and compensate the network-induced delays and packet dropouts. Finally, a continuous stirred tank reactor system is given in the simulation part to demonstrate the effectiveness of the proposed method.

A conceptual prediction model for seasonal drought processes using atmospheric and oceanic standardized anomalies and its application to four recent severe regional drought events in China

NASA Astrophysics Data System (ADS)

Liu, Z.; LU, G.; He, H.; Wu, Z.; He, J.

2017-12-01

Reliable drought prediction is fundamental for seasonal water management. Considering that drought development is closely related to the spatio-temporal evolution of large-scale circulation patterns, we develop a conceptual prediction model of seasonal drought processes based on atmospheric/oceanic Standardized Anomalies (SA). It is essentially the synchronous stepwise regression relationship between 90-day-accumulated atmospheric/oceanic SA-based predictors and 3-month SPI updated daily (SPI3). It is forced with forecasted atmospheric and oceanic variables retrieved from seasonal climate forecast systems, and it can make seamless drought prediction for operational use after a year-to-year calibration. Simulation and prediction of four severe seasonal regional drought processes in China were forced with the NCEP/NCAR reanalysis datasets and the NCEP Climate Forecast System Version 2 (CFSv2) operationally forecasted datasets, respectively. With the help of real-time correction for operational application, model application during four recent severe regional drought events in China revealed that the model is good at development prediction but weak in severity prediction. In addition to weakness in prediction of drought peak, the prediction of drought relief is possible to be predicted as drought recession. This weak performance may be associated with precipitation-causing weather patterns during drought relief. Based on initial virtual analysis on predicted 90-day prospective SPI3 curves, it shows that the 2009/2010 drought in Southwest China and 2014 drought in North China can be predicted and simulated well even for the prospective 1-75 day. In comparison, the prospective 1-45 day may be a feasible and acceptable lead time for simulation and prediction of the 2011 droughts in Southwest China and East China, after which the simulated and predicted developments clearly change.

Using Patient Demographics and Statistical Modeling to Predict Knee Tibia Component Sizing in Total Knee Arthroplasty.

PubMed

Ren, Anna N; Neher, Robert E; Bell, Tyler; Grimm, James

2018-06-01

Preoperative planning is important to achieve successful implantation in primary total knee arthroplasty (TKA). However, traditional TKA templating techniques are not accurate enough to predict the component size to a very close range. With the goal of developing a general predictive statistical model using patient demographic information, ordinal logistic regression was applied to build a proportional odds model to predict the tibia component size. The study retrospectively collected the data of 1992 primary Persona Knee System TKA procedures. Of them, 199 procedures were randomly selected as testing data and the rest of the data were randomly partitioned between model training data and model evaluation data with a ratio of 7:3. Different models were trained and evaluated on the training and validation data sets after data exploration. The final model had patient gender, age, weight, and height as independent variables and predicted the tibia size within 1 size difference 96% of the time on the validation data, 94% of the time on the testing data, and 92% on a prospective cadaver data set. The study results indicated the statistical model built by ordinal logistic regression can increase the accuracy of tibia sizing information for Persona Knee preoperative templating. This research shows statistical modeling may be used with radiographs to dramatically enhance the templating accuracy, efficiency, and quality. In general, this methodology can be applied to other TKA products when the data are applicable. Copyright © 2018 Elsevier Inc. All rights reserved.

Using demography and movement behavior to predict range expansion of the southern sea otter.

USGS Publications Warehouse

Tinker, M.T.; Doak, D.F.; Estes, J.A.

2008-01-01

In addition to forecasting population growth, basic demographic data combined with movement data provide a means for predicting rates of range expansion. Quantitative models of range expansion have rarely been applied to large vertebrates, although such tools could be useful for restoration and management of many threatened but recovering populations. Using the southern sea otter (Enhydra lutris nereis) as a case study, we utilized integro-difference equations in combination with a stage-structured projection matrix that incorporated spatial variation in dispersal and demography to make forecasts of population recovery and range recolonization. In addition to these basic predictions, we emphasize how to make these modeling predictions useful in a management context through the inclusion of parameter uncertainty and sensitivity analysis. Our models resulted in hind-cast (1989–2003) predictions of net population growth and range expansion that closely matched observed patterns. We next made projections of future range expansion and population growth, incorporating uncertainty in all model parameters, and explored the sensitivity of model predictions to variation in spatially explicit survival and dispersal rates. The predicted rate of southward range expansion (median = 5.2 km/yr) was sensitive to both dispersal and survival rates; elasticity analysis indicated that changes in adult survival would have the greatest potential effect on the rate of range expansion, while perturbation analysis showed that variation in subadult dispersal contributed most to variance in model predictions. Variation in survival and dispersal of females at the south end of the range contributed most of the variance in predicted southward range expansion. Our approach provides guidance for the acquisition of further data and a means of forecasting the consequence of specific management actions. Similar methods could aid in the management of other recovering populations.

Seasonal predictability of Arctic Sea Ice: assessing its limits and potential in a GCM and implications for observations.

NASA Astrophysics Data System (ADS)

Blanchard-Wrigglesworth, E.

2012-12-01

Arctic sea ice has exhibited a dramatic decrease both in area and thickness over the recent decades, particularly during the summer months. This decrease has led to growing interest in the potential predictability of summer sea ice, spurred in part by the socioeconomic implications. Here we present results of several parallel experiments designed to assess and understand the limits and potential for seasonal predictability of Arctic sea ice, with an emphasis on the summer minimum. Building on our experience from the SEARCH Outlook, we present results of a coupled general circulation model (GCM) hindcast simulation of Arctic summer sea ice variability for the satellite period (1979-present). These are initialized with spring sea ice volume anomalies obtained from a modelling and assimilation system, considered to be a close representation of reality. We show that there is significant predictability, yet the stochastic forcing imparted mainly by the atmosphere can lead to large errors in the hindcast. The model, however, can simulate anomalous runs that lie beyond a Gaussian distribution. Additionally, we investigate the regional characteristics of predictability and its links to sea ice dynamics and the spatio-temporal behavior of sea ice anomalies. We show a distinct difference between models. Unfortunately, observational data of thickness are not yet detailed enough to assess the models. Our results indicate the potential for detailed ice thickness observations in improving regional predictability. Finally, we discuss the importance of experiment design in predictability experiments, and show that predictions made with models that have a large mean state bias in sea ice require a careful initialization in order to fully capture all initial value predictability.

Field-scale Prediction of Enhanced DNAPL Dissolution Using Partitioning Tracers and Flow Pattern Effects

NASA Astrophysics Data System (ADS)

Wang, F.; Annable, M. D.; Jawitz, J. W.

2012-12-01

The equilibrium streamtube model (EST) has demonstrated the ability to accurately predict dense nonaqueous phase liquid (DNAPL) dissolution in laboratory experiments and numerical simulations. Here the model is applied to predict DNAPL dissolution at a PCE-contaminated dry cleaner site, located in Jacksonville, Florida. The EST is an analytical solution with field-measurable input parameters. Here, measured data from a field-scale partitioning tracer test were used to parameterize the EST model and the predicted PCE dissolution was compared to measured data from an in-situ alcohol (ethanol) flood. In addition, a simulated partitioning tracer test from a calibrated spatially explicit multiphase flow model (UTCHEM) was also used to parameterize the EST analytical solution. The ethanol prediction based on both the field partitioning tracer test and the UTCHEM tracer test simulation closely matched the field data. The PCE EST prediction showed a peak shift to an earlier arrival time that was concluded to be caused by well screen interval differences between the field tracer test and alcohol flood. This observation was based on a modeling assessment of potential factors that may influence predictions by using UTCHEM simulations. The imposed injection and pumping flow pattern at this site for both the partitioning tracer test and alcohol flood was more complex than the natural gradient flow pattern (NGFP). Both the EST model and UTCHEM were also used to predict PCE dissolution under natural gradient conditions, with much simpler flow patterns than the forced-gradient double five spot of the alcohol flood. The NGFP predictions based on parameters determined from tracer tests conducted with complex flow patterns underestimated PCE concentrations and total mass removal. This suggests that the flow patterns influence aqueous dissolution and that the aqueous dissolution under the NGFP is more efficient than dissolution under complex flow patterns.

Development of a Novel Simplified PBPK Absorption Model to Explain the Higher Relative Bioavailability of the OROS® Formulation of Oxybutynin.

PubMed

Olivares-Morales, Andrés; Ghosh, Avijit; Aarons, Leon; Rostami-Hodjegan, Amin

2016-11-01

A new minimal Segmented Transit and Absorption model (mSAT) model has been recently proposed and combined with intrinsic intestinal effective permeability (P eff,int ) to predict the regional gastrointestinal (GI) absorption (f abs ) of several drugs. Herein, this model was extended and applied for the prediction of oral bioavailability and pharmacokinetics of oxybutynin and its enantiomers to provide a mechanistic explanation of the higher relative bioavailability observed for oxybutynin's modified-release OROS® formulation compared to its immediate-release (IR) counterpart. The expansion of the model involved the incorporation of mechanistic equations for the prediction of release, transit, dissolution, permeation and first-pass metabolism. The predicted pharmacokinetics of oxybutynin enantiomers after oral administration for both the IR and OROS® formulations were in close agreement with the observed data. The predicted absolute bioavailability for the IR formulation was within 5% of the observed value, and the model adequately predicted the higher relative bioavailability observed for the OROS® formulation vs. the IR counterpart. From the model predictions, it can be noticed that the higher bioavailability observed for the OROS® formulation was mainly attributable to differences in the intestinal availability (F G ) rather than due to a higher colonic f abs , thus confirming previous hypotheses. The predicted f abs was almost 70% lower for the OROS® formulation compared to the IR formulation, whereas the F G was almost eightfold higher than in the IR formulation. These results provide further support to the hypothesis of an increased F G as the main factor responsible for the higher bioavailability of oxybutynin's OROS® formulation vs. the IR.

Computed tomography screening for lung cancer: results of ten years of annual screening and validation of cosmos prediction model.

PubMed

Veronesi, G; Maisonneuve, P; Rampinelli, C; Bertolotti, R; Petrella, F; Spaggiari, L; Bellomi, M

2013-12-01

It is unclear how long low-dose computed tomographic (LDCT) screening should continue in populations at high risk of lung cancer. We assessed outcomes and the predictive ability of the COSMOS prediction model in volunteers screened for 10 years. Smokers and former smokers (>20 pack-years), >50 years, were enrolled over one year (2000-2001), receiving annual LDCT for 10 years. The frequency of screening-detected lung cancers was compared with COSMOS and Bach risk model estimates. Among 1035 recruited volunteers (71% men, mean age 58 years) compliance was 65% at study end. Seventy-one (6.95%) lung cancers were diagnosed, 12 at baseline. Disease stage was: IA in 48 (66.6%); IB in 6; IIA in 5; IIB in 2; IIIA in 5; IIIB in 1; IV in 5; and limited small cell cancer in 3. Five- and ten-year survival were 64% and 57%, respectively, 84% and 65% for stage I. Ten (12.1%) received surgery for a benign lesion. The number of lung cancers detected during the first two screening rounds was close to that predicted by the COSMOS model, while the Bach model accurately predicted frequency from the third year on. Neither cancer frequency nor proportion at stage I decreased over 10 years, indicating that screening should not be discontinued. Most cancers were early stage, and overall survival was high. Only a limited number of invasive procedures for benign disease were performed. The Bach model - designed to predict symptomatic cancers - accurately predicted cancer frequency from the third year, suggesting that overdiagnosis is a minor problem in lung cancer screening. The COSMOS model - designed to estimate screening-detected lung cancers - accurately predicted cancer frequency at baseline and second screening round. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A closed-form solution for steady-state coupled phloem/xylem flow using the Lambert-W function.

PubMed

Hall, A J; Minchin, P E H

2013-12-01

A closed-form solution for steady-state coupled phloem/xylem flow is presented. This incorporates the basic Münch flow model of phloem transport, the cohesion model of xylem flow, and local variation in the xylem water potential and lateral water flow along the transport pathway. Use of the Lambert-W function allows this solution to be obtained under much more general and realistic conditions than has previously been possible. Variation in phloem resistance (i.e. viscosity) with solute concentration, and deviations from the Van't Hoff expression for osmotic potential are included. It is shown that the model predictions match those of the equilibrium solution of a numerical time-dependent model based upon the same mechanistic assumptions. The effect of xylem flow upon phloem flow can readily be calculated, which has not been possible in any previous analytical model. It is also shown how this new analytical solution can handle multiple sources and sinks within a complex architecture, and can describe competition between sinks. The model provides new insights into Münch flow by explicitly including interactions with xylem flow and water potential in the closed-form solution, and is expected to be useful as a component part of larger numerical models of entire plants. © 2013 John Wiley & Sons Ltd.

The close binary frequency of Wolf-Rayet stars as a function of metallicity in M31 and M33

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

Neugent, Kathryn F.; Massey, Philip, E-mail: kneugent@lowell.edu, E-mail: phil.massey@lowell.edu

Massive star evolutionary models generally predict the correct ratio of WC-type and WN-type Wolf-Rayet stars at low metallicities, but underestimate the ratio at higher (solar and above) metallicities. One possible explanation for this failure is perhaps single-star models are not sufficient and Roche-lobe overflow in close binaries is necessary to produce the 'extra' WC stars at higher metallicities. However, this would require the frequency of close massive binaries to be metallicity dependent. Here we test this hypothesis by searching for close Wolf-Rayet binaries in the high metallicity environments of M31 and the center of M33 as well as in themore » lower metallicity environments of the middle and outer regions of M33. After identifying ∼100 Wolf-Rayet binaries based on radial velocity variations, we conclude that the close binary frequency of Wolf-Rayets is not metallicity dependent and thus other factors must be responsible for the overabundance of WC stars at high metallicities. However, our initial identifications and observations of these close binaries have already been put to good use as we are currently observing additional epochs for eventual orbit and mass determinations.« less

Ratios of transfer coefficients for radiocesium transport in ruminants

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

Assimakopoulos, P.A.; Ioannides, K.G.; Karamanis, D.

1995-09-01

A corollary of the multiple-compartment model for the transport of trace elements through animals was tested for cows, goats, and sheep. According to this corollary, for a given body {open_quotes}compartment{close_quotes} k of the animal (soft tissue, lung, liver, etc.), the ratio a(k)=f(k)/f(blood) of the transfer coefficients f, should exhibit similar values for physiologically similar animals. In order to verify this prediction, two experiments were performed at the Agricultural Research Station of Ioannina and at the facilities of Ria Pripyat in Pripyat, Ukranine. Eight animals in the first experiment and eighteen in the second were housed in individual pens and weremore » artificially contaminated with a constant daily dose of radiocesium until equilibrium was reached. the animals were then sacrificed and transfer coefficients f(k) to twelve body {open_quotes}compartments{close_quotes} k were measured. These data were used to calculate the ratios a(k). The results were in accordance with predictions of the model and average values of a(k) were extracted for ruminants. It is concluded that these values may be employed for the prediction of animal contamination in any body compartment through the measurement of blood samples. 7 refs., 8 tabs.« less

The aerodynamic cost of flight in the short-tailed fruit bat (Carollia perspicillata): comparing theory with measurement

PubMed Central

von Busse, Rhea; Waldman, Rye M.; Swartz, Sharon M.; Voigt, Christian C.; Breuer, Kenneth S.

2014-01-01

Aerodynamic theory has long been used to predict the power required for animal flight, but widely used models contain many simplifications. It has been difficult to ascertain how closely biological reality matches model predictions, largely because of the technical challenges of accurately measuring the power expended when an animal flies. We designed a study to measure flight speed-dependent aerodynamic power directly from the kinetic energy contained in the wake of bats flying in a wind tunnel. We compared these measurements with two theoretical predictions that have been used for several decades in diverse fields of vertebrate biology and to metabolic measurements from a previous study using the same individuals. A high-accuracy displaced laser sheet stereo particle image velocimetry experimental design measured the wake velocities in the Trefftz plane behind four bats flying over a range of speeds (3–7 m s−1). We computed the aerodynamic power contained in the wake using a novel interpolation method and compared these results with the power predicted by Pennycuick's and Rayner's models. The measured aerodynamic power falls between the two theoretical predictions, demonstrating that the models effectively predict the appropriate range of flight power, but the models do not accurately predict minimum power or maximum range speeds. Mechanical efficiency—the ratio of aerodynamic power output to metabolic power input—varied from 5.9% to 9.8% for the same individuals, changing with flight speed. PMID:24718450

Nonlinear Reynolds stress model for turbulent shear flows

NASA Technical Reports Server (NTRS)

Barton, J. Michael; Rubinstein, R.; Kirtley, K. R.

1991-01-01

A nonlinear algebraic Reynolds stress model, derived using the renormalization group, is applied to equilibrium homogeneous shear flow and fully developed flow in a square duct. The model, which is quadratically nonlinear in the velocity gradients, successfully captures the large-scale inhomogeneity and anisotropy of the flows studied. The ratios of normal stresses, as well as the actual magnitudes of the stresses are correctly predicted for equilibrium homogeneous shear flow. Reynolds normal stress anisotropy and attendant turbulence driven secondary flow are predicted for a square duct. Profiles of mean velocity and normal stresses are in good agreement with measurements. Very close to walls, agreement with measurements diminishes. The model has the benefit of containing no arbitrary constants; all values are determined directly from the theory. It seems that near wall behavior is influenced by more than the large scale anisotropy accommodated in the current model. More accurate near wall calculations may well require a model for anisotropic dissipation.

Numerical modeling of cold room's hinged door opening and closing processes

NASA Astrophysics Data System (ADS)

Carneiro, R.; Gaspar, P. D.; Silva, P. D.; Domingues, L. C.

2016-06-01

The need of rationalize energy consumption in agrifood industry has fasten the development of methodologies to improve the thermal and energy performances of cold rooms. This paper presents a three-dimensional (3D) transient Computational Fluid Dynamics (CFD) modelling of a cold room to evaluate the air infiltration rate through hinged doors. A species transport model is used for modelling the tracer gas concentration decay technique. Numerical predictions indicate that air temperature difference between spaces affects the air infiltration. For this case study, the infiltration rate increases 0.016 m3 s-1 per K of air temperature difference. The knowledge about the evolution of air infiltration during door opening/closing times allows to draw some conclusions about its influence on the air conditions inside the cold room, as well as to suggest best practices and simple technical improvements that can minimize air infiltration, and consequently improve thermal performance and energy consumption rationalization.

Optimal reconstruction for closed-loop ground-layer adaptive optics with elongated spots.

PubMed

Béchet, Clémentine; Tallon, Michel; Tallon-Bosc, Isabelle; Thiébaut, Éric; Le Louarn, Miska; Clare, Richard M

2010-11-01

The design of the laser-guide-star-based adaptive optics (AO) systems for the Extremely Large Telescopes requires careful study of the issue of elongated spots produced on Shack-Hartmann wavefront sensors. The importance of a correct modeling of the nonuniformity and correlations of the noise induced by this elongation has already been demonstrated for wavefront reconstruction. We report here on the first (to our knowledge) end-to-end simulations of closed-loop ground-layer AO with laser guide stars with such an improved noise model. The results are compared with the level of performance predicted by a classical noise model for the reconstruction. The performance is studied in terms of ensquared energy and confirms that, thanks to the improved noise model, central or side launching of the lasers does not affect the performance with respect to the laser guide stars' flux. These two launching schemes also perform similarly whatever the atmospheric turbulence strength.

On rate-state and Coulomb failure models

USGS Publications Warehouse

Gomberg, J.; Beeler, N.; Blanpied, M.

2000-01-01

We examine the predictions of Coulomb failure stress and rate-state frictional models. We study the change in failure time (clock advance) Δt due to stress step perturbations (i.e., coseismic static stress increases) added to "background" stressing at a constant rate (i.e., tectonic loading) at time t0. The predictability of Δt implies a predictable change in seismicity rate r(t)/r0, testable using earthquake catalogs, where r0 is the constant rate resulting from tectonic stressing. Models of r(t)/r0, consistent with general properties of aftershock sequences, must predict an Omori law seismicity decay rate, a sequence duration that is less than a few percent of the mainshock cycle time and a return directly to the background rate. A Coulomb model requires that a fault remains locked during loading, that failure occur instantaneously, and that Δt is independent of t0. These characteristics imply an instantaneous infinite seismicity rate increase of zero duration. Numerical calculations of r(t)/r0 for different state evolution laws show that aftershocks occur on faults extremely close to failure at the mainshock origin time, that these faults must be "Coulomb-like," and that the slip evolution law can be precluded. Real aftershock population characteristics also may constrain rate-state constitutive parameters; a may be lower than laboratory values, the stiffness may be high, and/or normal stress may be lower than lithostatic. We also compare Coulomb and rate-state models theoretically. Rate-state model fault behavior becomes more Coulomb-like as constitutive parameter a decreases relative to parameter b. This is because the slip initially decelerates, representing an initial healing of fault contacts. The deceleration is more pronounced for smaller a, more closely simulating a locked fault. Even when the rate-state Δt has Coulomb characteristics, its magnitude may differ by some constant dependent on b. In this case, a rate-state model behaves like a modified Coulomb failure model in which the failure stress threshold is lowered due to weakening, increasing the clock advance. The deviation from a non-Coulomb response also depends on the loading rate, elastic stiffness, initial conditions, and assumptions about how state evolves.

The importance of accurate muscle modelling for biomechanical analyses: a case study with a lizard skull

PubMed Central

Gröning, Flora; Jones, Marc E. H.; Curtis, Neil; Herrel, Anthony; O'Higgins, Paul; Evans, Susan E.; Fagan, Michael J.

2013-01-01

Computer-based simulation techniques such as multi-body dynamics analysis are becoming increasingly popular in the field of skull mechanics. Multi-body models can be used for studying the relationships between skull architecture, muscle morphology and feeding performance. However, to be confident in the modelling results, models need to be validated against experimental data, and the effects of uncertainties or inaccuracies in the chosen model attributes need to be assessed with sensitivity analyses. Here, we compare the bite forces predicted by a multi-body model of a lizard (Tupinambis merianae) with in vivo measurements, using anatomical data collected from the same specimen. This subject-specific model predicts bite forces that are very close to the in vivo measurements and also shows a consistent increase in bite force as the bite position is moved posteriorly on the jaw. However, the model is very sensitive to changes in muscle attributes such as fibre length, intrinsic muscle strength and force orientation, with bite force predictions varying considerably when these three variables are altered. We conclude that accurate muscle measurements are crucial to building realistic multi-body models and that subject-specific data should be used whenever possible. PMID:23614944

Microscopic prediction of speech recognition for listeners with normal hearing in noise using an auditory model.

PubMed

Jürgens, Tim; Brand, Thomas

2009-11-01

This study compares the phoneme recognition performance in speech-shaped noise of a microscopic model for speech recognition with the performance of normal-hearing listeners. "Microscopic" is defined in terms of this model twofold. First, the speech recognition rate is predicted on a phoneme-by-phoneme basis. Second, microscopic modeling means that the signal waveforms to be recognized are processed by mimicking elementary parts of human's auditory processing. The model is based on an approach by Holube and Kollmeier [J. Acoust. Soc. Am. 100, 1703-1716 (1996)] and consists of a psychoacoustically and physiologically motivated preprocessing and a simple dynamic-time-warp speech recognizer. The model is evaluated while presenting nonsense speech in a closed-set paradigm. Averaged phoneme recognition rates, specific phoneme recognition rates, and phoneme confusions are analyzed. The influence of different perceptual distance measures and of the model's a-priori knowledge is investigated. The results show that human performance can be predicted by this model using an optimal detector, i.e., identical speech waveforms for both training of the recognizer and testing. The best model performance is yielded by distance measures which focus mainly on small perceptual distances and neglect outliers.

Non-invasive prediction of hematocrit levels by portable visible and near-infrared spectrophotometer.

PubMed

Sakudo, Akikazu; Kato, Yukiko Hakariya; Kuratsune, Hirohiko; Ikuta, Kazuyoshi

2009-10-01

After blood donation, in some individuals having polycythemia, dehydration causes anemia. Although the hematocrit (Ht) level is closely related to anemia, the current method of measuring Ht is performed after blood drawing. Furthermore, the monitoring of Ht levels contributes to a healthy life. Therefore, a non-invasive test for Ht is warranted for the safe donation of blood and good quality of life. A non-invasive procedure for the prediction of hematocrit levels was developed on the basis of a chemometric analysis of visible and near-infrared (Vis-NIR) spectra of the thumbs using portable spectrophotometer. Transmittance spectra in the 600- to 1100-nm region from thumbs of Japanese volunteers were subjected to a partial least squares regression (PLSR) analysis and leave-out cross-validation to develop chemometric models for predicting Ht levels. Ht levels of masked samples predicted by this model from Vis-NIR spectra provided a coefficient of determination in prediction of 0.6349 with a standard error of prediction of 3.704% and a detection limit in prediction of 17.14%, indicating that the model is applicable for normal and abnormal value in Ht level. These results suggest portable Vis-NIR spectrophotometer to have potential for the non-invasive measurement of Ht levels with a combination of PLSR analysis.

A proof-of-principle simulation for closed-loop control based on preexisting experimental thalamic DBS-enhanced instrumental learning.

PubMed

Wang, Ching-Fu; Yang, Shih-Hung; Lin, Sheng-Huang; Chen, Po-Chuan; Lo, Yu-Chun; Pan, Han-Chi; Lai, Hsin-Yi; Liao, Lun-De; Lin, Hui-Ching; Chen, Hsu-Yan; Huang, Wei-Chen; Huang, Wun-Jhu; Chen, You-Yin

Deep brain stimulation (DBS) has been applied as an effective therapy for treating Parkinson's disease or essential tremor. Several open-loop DBS control strategies have been developed for clinical experiments, but they are limited by short battery life and inefficient therapy. Therefore, many closed-loop DBS control systems have been designed to tackle these problems by automatically adjusting the stimulation parameters via feedback from neural signals, which has been reported to reduce the power consumption. However, when the association between the biomarkers of the model and stimulation is unclear, it is difficult to develop an optimal control scheme for other DBS applications, i.e., DBS-enhanced instrumental learning. Furthermore, few studies have investigated the effect of closed-loop DBS control for cognition function, such as instrumental skill learning, and have been implemented in simulation environments. In this paper, we proposed a proof-of-principle design for a closed-loop DBS system, cognitive-enhancing DBS (ceDBS), which enhanced skill learning based on in vivo experimental data. The ceDBS acquired local field potential (LFP) signal from the thalamic central lateral (CL) nuclei of animals through a neural signal processing system. A strong coupling of the theta oscillation (4-7 Hz) and the learning period was found in the water reward-related lever-pressing learning task. Therefore, the theta-band power ratio, which was the averaged theta band to averaged total band (1-55 Hz) power ratio, could be used as a physiological marker for enhancement of instrumental skill learning. The on-line extraction of the theta-band power ratio was implemented on a field-programmable gate array (FPGA). An autoregressive with exogenous inputs (ARX)-based predictor was designed to construct a CL-thalamic DBS model and forecast the future physiological marker according to the past physiological marker and applied DBS. The prediction could further assist the design of a closed-loop DBS controller. A DBS controller based on a fuzzy expert system was devised to automatically control DBS according to the predicted physiological marker via a set of rules. The simulated experimental results demonstrate that the ceDBS based on the closed-loop control architecture not only reduced power consumption using the predictive physiological marker, but also achieved a desired level of physiological marker through the DBS controller. Copyright © 2017 Elsevier Inc. All rights reserved.

Testing and extension of a sea lamprey feeding model

USGS Publications Warehouse

Cochran, Philip A.; Swink, William D.; Kinziger, Andrew P.

1999-01-01

A previous model of feeding by sea lamprey Petromyzon marinus predicted energy intake and growth by lampreys as a function of lamprey size, host size, and duration of feeding attachments, but it was applicable only to lampreys feeding at 10°C and it was tested against only a single small data set of limited scope. We extended the model to other temperatures and tested it against an extensive data set (more than 700 feeding bouts) accumulated during experiments with captive sea lampreys. Model predictions of instantaneous growth were highly correlated with observed growth, and a partitioning of mean squared error between model predictions and observed results showed that 88.5% of the variance was due to random variation rather than to systematic errors. However, deviations between observed and predicted values varied substantially, especially for short feeding bouts. Predicted and observed growth trajectories of individual lampreys during multiple feeding bouts during the summer tended to correspond closely, but predicted growth was generally much higher than observed growth late in the year. This suggests the possibility that large overwintering lampreys reduce their feeding rates while attached to hosts. Seasonal or size-related shifts in the fate of consumed energy may provide an alternative explanation. The lamprey feeding model offers great flexibility in assessing growth of captive lampreys within various experimental protocols (e.g., different host species or thermal regimes) because it controls for individual differences in feeding history.

Efficacy of monitoring and empirical predictive modeling at improving public health protection at Chicago beaches

USGS Publications Warehouse

Nevers, Meredith B.; Whitman, Richard L.

2011-01-01

Efforts to improve public health protection in recreational swimming waters have focused on obtaining real-time estimates of water quality. Current monitoring techniques rely on the time-intensive culturing of fecal indicator bacteria (FIB) from water samples, but rapidly changing FIB concentrations result in management errors that lead to the public being exposed to high FIB concentrations (type II error) or beaches being closed despite acceptable water quality (type I error). Empirical predictive models may provide a rapid solution, but their effectiveness at improving health protection has not been adequately assessed. We sought to determine if emerging monitoring approaches could effectively reduce risk of illness exposure by minimizing management errors. We examined four monitoring approaches (inactive, current protocol, a single predictive model for all beaches, and individual models for each beach) with increasing refinement at 14 Chicago beaches using historical monitoring and hydrometeorological data and compared management outcomes using different standards for decision-making. Predictability (R2) of FIB concentration improved with model refinement at all beaches but one. Predictive models did not always reduce the number of management errors and therefore the overall illness burden. Use of a Chicago-specific single-sample standard-rather than the default 235 E. coli CFU/100 ml widely used-together with predictive modeling resulted in the greatest number of open beach days without any increase in public health risk. These results emphasize that emerging monitoring approaches such as empirical models are not equally applicable at all beaches, and combining monitoring approaches may expand beach access.

Analysis of Physical and Numerical Factors for Prediction of UV Radiation from High Altitude Two-Phase Plumes

DTIC Science & Technology

2008-05-30

varies from continuum inside the nozzle, to transitional in the near field, to free molecular in the far field of the plume. The scales of interest vary...unity based on the rocket length. This results in the formation of a viscous shock layer characterized by a bimodal molecular velocity distribution. The...transfer model. Previous analysis21 have shown that the heat transfer model implemented in CFD++ is reproduced closely by the free molecular model

Modelling of capillary-driven flow for closed paper-based microfluidic channels

NASA Astrophysics Data System (ADS)

Songok, Joel; Toivakka, Martti

2017-06-01

Paper-based microfluidics is an emerging field focused on creating inexpensive devices, with simple fabrication methods for applications in various fields including healthcare, environmental monitoring and veterinary medicine. Understanding the flow of liquid is important in achieving consistent operation of the devices. This paper proposes capillary models to predict flow in paper-based microfluidic channels, which include a flow accelerating hydrophobic top cover. The models, which consider both non-absorbing and absorbing substrates, are in good agreement with the experimental results.

Development and application of Geobacillus stearothermophilus growth model for predicting spoilage of evaporated milk.

PubMed

Kakagianni, Myrsini; Gougouli, Maria; Koutsoumanis, Konstantinos P

2016-08-01

The presence of Geobacillus stearothermophilus spores in evaporated milk constitutes an important quality problem for the milk industry. This study was undertaken to provide an approach in modelling the effect of temperature on G. stearothermophilus ATCC 7953 growth and in predicting spoilage of evaporated milk. The growth of G. stearothermophilus was monitored in tryptone soy broth at isothermal conditions (35-67 °C). The data derived were used to model the effect of temperature on G. stearothermophilus growth with a cardinal type model. The cardinal values of the model for the maximum specific growth rate were Tmin = 33.76 °C, Tmax = 68.14 °C, Topt = 61.82 °C and μopt = 2.068/h. The growth of G. stearothermophilus was assessed in evaporated milk at Topt in order to adjust the model to milk. The efficiency of the model in predicting G. stearothermophilus growth at non-isothermal conditions was evaluated by comparing predictions with observed growth under dynamic conditions and the results showed a good performance of the model. The model was further used to predict the time-to-spoilage (tts) of evaporated milk. The spoilage of this product caused by acid coagulation when the pH approached a level around 5.2, eight generations after G. stearothermophilus reached the maximum population density (Nmax). Based on the above, the tts was predicted from the growth model as the sum of the time required for the microorganism to multiply from the initial to the maximum level ( [Formula: see text] ), plus the time required after the [Formula: see text] to complete eight generations. The observed tts was very close to the predicted one indicating that the model is able to describe satisfactorily the growth of G. stearothermophilus and to provide realistic predictions for evaporated milk spoilage. Copyright © 2016 Elsevier Ltd. All rights reserved.

A combined coarse-grained and all-atom simulation of TRPV1 channel gating and heat activation

PubMed Central

Qin, Feng

2015-01-01

The transient receptor potential (TRP) channels act as key sensors of various chemical and physical stimuli in eukaryotic cells. Despite years of study, the molecular mechanisms of TRP channel activation remain unclear. To elucidate the structural, dynamic, and energetic basis of gating in TRPV1 (a founding member of the TRPV subfamily), we performed coarse-grained modeling and all-atom molecular dynamics (MD) simulation based on the recently solved high resolution structures of the open and closed form of TRPV1. Our coarse-grained normal mode analysis captures two key modes of collective motions involved in the TRPV1 gating transition, featuring a quaternary twist motion of the transmembrane domains (TMDs) relative to the intracellular domains (ICDs). Our transition pathway modeling predicts a sequence of structural movements that propagate from the ICDs to the TMDs via key interface domains (including the membrane proximal domain and the C-terminal domain), leading to sequential opening of the selectivity filter followed by the lower gate in the channel pore (confirmed by modeling conformational changes induced by the activation of ICDs). The above findings of coarse-grained modeling are robust to perturbation by lipids. Finally, our MD simulation of the ICD identifies key residues that contribute differently to the nonpolar energy of the open and closed state, and these residues are predicted to control the temperature sensitivity of TRPV1 gating. These computational predictions offer new insights to the mechanism for heat activation of TRPV1 gating, and will guide our future electrophysiology and mutagenesis studies. PMID:25918362

Extreme close approaches in hierarchical triple systems with comparable masses

NASA Astrophysics Data System (ADS)

Haim, Niv; Katz, Boaz

2018-06-01

We study close approaches in hierarchical triple systems with comparable masses using full N-body simulations, motivated by a recent model for type Ia supernovae involving direct collisions of white dwarfs (WDs). For stable hierarchical systems where the inner binary components have equal masses, we show that the ability of the inner binary to achieve very close approaches, where the separation between the components of the inner binary reaches values which are orders of magnitude smaller than the semi-major axis, can be analytically predicted from initial conditions. The rate of close approaches is found to be roughly linear with the mass of the tertiary. The rate increases in systems with unequal inner binaries by a marginal factor of ≲ 2 for mass ratios 0.5 ≤ m1/m2 ≤ 1 relevant for the inner white-dwarf binaries. For an average tertiary mass of ˜0.3M⊙ which is representative of typical M-dwarfs, the chance for clean collisions is ˜1% setting challenging constraints on the collisional model for type Ia's.

An analysis of the North Rainier Elk Herd area, Washington: Change detection and habitat modeling with remote sensing and GIS

NASA Astrophysics Data System (ADS)

Benton, Joshua J.

The North Rainier Elk Herd (NREH) is one of ten designated herds in Washington State, all managed by the Washington Department of Fish and Wildlife (WDFW). To aid in the management of the herd, the WDFW has decided to implement a spatial ecosystem analysis. This thesis partially undertakes this analysis through the use of a suite of software tools, the Westside Elk Nutrition and Habitat Use Models (WENHUM). This model analyzes four covariates that have a strong correlation to elk habitat selection: dietary digestible energy (DDE); distance to roads open to the public; mean slope; and distance to cover-forage edge and returns areas of likely elk habitation or use. This thesis includes an update of the base vegetation layer from 2006 data to 2011, a series of clear cuts were identified as areas of change and fed into the WENHUM models. The addition of these clear cuts created improvements in the higher quality DDE levels and when the updated data is compared to the original, predictions of elk use are higher. The presence of open or closed roads was simulated by creating an area of possible closures, selecting candidate roads within that area and then modeling them as either "all open" or "all closed". The simulation of the road closures produced increases in the higher levels of predicted use.

Comparing models of Red Knot population dynamics

USGS Publications Warehouse

McGowan, Conor P.

2015-01-01

Predictive population modeling contributes to our basic scientific understanding of population dynamics, but can also inform management decisions by evaluating alternative actions in virtual environments. Quantitative models mathematically reflect scientific hypotheses about how a system functions. In Delaware Bay, mid-Atlantic Coast, USA, to more effectively manage horseshoe crab (Limulus polyphemus) harvests and protect Red Knot (Calidris canutus rufa) populations, models are used to compare harvest actions and predict the impacts on crab and knot populations. Management has been chiefly driven by the core hypothesis that horseshoe crab egg abundance governs the survival and reproduction of migrating Red Knots that stopover in the Bay during spring migration. However, recently, hypotheses proposing that knot dynamics are governed by cyclical lemming dynamics garnered some support in data analyses. In this paper, I present alternative models of Red Knot population dynamics to reflect alternative hypotheses. Using 2 models with different lemming population cycle lengths and 2 models with different horseshoe crab effects, I project the knot population into the future under environmental stochasticity and parametric uncertainty with each model. I then compare each model's predictions to 10 yr of population monitoring from Delaware Bay. Using Bayes' theorem and model weight updating, models can accrue weight or support for one or another hypothesis of population dynamics. With 4 models of Red Knot population dynamics and only 10 yr of data, no hypothesis clearly predicted population count data better than another. The collapsed lemming cycle model performed best, accruing ~35% of the model weight, followed closely by the horseshoe crab egg abundance model, which accrued ~30% of the weight. The models that predicted no decline or stable populations (i.e. the 4-yr lemming cycle model and the weak horseshoe crab effect model) were the most weakly supported.

Reactant conversion in homogeneous turbulence: Mathematical modeling, computational validations and practical applications

NASA Technical Reports Server (NTRS)

Madnia, C. K.; Frankel, S. H.; Givi, P.

1992-01-01

Closed form analytical expressions are obtained for predicting the limited rate of reactant conversion in a binary reaction of the type F + rO yields (1 + r) Product in unpremixed homogeneous turbulence. These relations are obtained by means of a single point Probability Density Function (PDF) method based on the Amplitude Mapping Closure. It is demonstrated that with this model, the maximum rate of the reactants' decay can be conveniently expressed in terms of definite integrals of the Parabolic Cylinder Functions. For the cases with complete initial segregation, it is shown that the results agree very closely with those predicted by employing a Beta density of the first kind for an appropriately defined Shvab-Zeldovich scalar variable. With this assumption, the final results can also be expressed in terms of closed form analytical expressions which are based on the Incomplete Beta Functions. With both models, the dependence of the results on the stoichiometric coefficient and the equivalence ratio can be expressed in an explicit manner. For a stoichiometric mixture, the analytical results simplify significantly. In the mapping closure, these results are expressed in terms of simple trigonometric functions. For the Beta density model, they are in the form of Gamma Functions. In all the cases considered, the results are shown to agree well with data generated by Direct Numerical Simulations (DNS). Due to the simplicity of these expressions and because of nice mathematical features of the Parabolic Cylinder and the Incomplete Beta Functions, these models are recommended for estimating the limiting rate of reactant conversion in homogeneous reacting flows. These results also provide useful insights in assessing the extent of validity of turbulence closures in the modeling of unpremixed reacting flows. Some discussions are provided on the extension of the model for treating more complicated reacting systems including realistic kinetics schemes and multi-scalar mixing with finite rate chemical reactions in more complex configurations.

PARALLEL MEASUREMENT AND MODELING OF TRANSPORT IN THE DARHT II BEAMLINE ON ETA II

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

Chambers, F W; Raymond, B A; Falabella, S

To successfully tune the DARHT II transport beamline requires the close coupling of a model of the beam transport and the measurement of the beam observables as the beam conditions and magnet settings are varied. For the ETA II experiment using the DARHT II beamline components this was achieved using the SUICIDE (Simple User Interface Connecting to an Integrated Data Environment) data analysis environment and the FITS (Fully Integrated Transport Simulation) model. The SUICIDE environment has direct access to the experimental beam transport data at acquisition and the FITS predictions of the transport for immediate comparison. The FITS model ismore » coupled into the control system where it can read magnet current settings for real time modeling. We find this integrated coupling is essential for model verification and the successful development of a tuning aid for the efficient convergence on a useable tune. We show the real time comparisons of simulation and experiment and explore the successes and limitations of this close coupled approach.« less

Experimentally validated mathematical model of analyte uptake by permeation passive samplers.

PubMed

Salim, F; Ioannidis, M; Górecki, T

2017-11-15

A mathematical model describing the sampling process in a permeation-based passive sampler was developed and evaluated numerically. The model was applied to the Waterloo Membrane Sampler (WMS), which employs a polydimethylsiloxane (PDMS) membrane as a permeation barrier, and an adsorbent as a receiving phase. Samplers of this kind are used for sampling volatile organic compounds (VOC) from air and soil gas. The model predicts the spatio-temporal variation of sorbed and free analyte concentrations within the sampler components (membrane, sorbent bed and dead volume), from which the uptake rate throughout the sampling process can be determined. A gradual decline in the uptake rate during the sampling process is predicted, which is more pronounced when sampling higher concentrations. Decline of the uptake rate can be attributed to diminishing analyte concentration gradient within the membrane, which results from resistance to mass transfer and the development of analyte concentration gradients within the sorbent bed. The effects of changing the sampler component dimensions on the rate of this decline in the uptake rate can be predicted from the model. Performance of the model was evaluated experimentally for sampling of toluene vapors under controlled conditions. The model predictions proved close to the experimental values. The model provides a valuable tool to predict changes in the uptake rate during sampling, to assign suitable exposure times at different analyte concentration levels, and to optimize the dimensions of the sampler in a manner that minimizes these changes during the sampling period.

Use of Fuzzy rainfall-runoff predictions for claypan watersheds with conservation buffers in Northeast Missouri

NASA Astrophysics Data System (ADS)

Anomaa Senaviratne, G. M. M. M.; Udawatta, Ranjith P.; Anderson, Stephen H.; Baffaut, Claire; Thompson, Allen

2014-09-01

Fuzzy rainfall-runoff models are often used to forecast flood or water supply in large catchments and applications at small/field scale agricultural watersheds are limited. The study objectives were to develop, calibrate, and validate a fuzzy rainfall-runoff model using long-term data of three adjacent field scale row crop watersheds (1.65-4.44 ha) with intermittent discharge in the claypan soils of Northeast Missouri. The watersheds were monitored for a six-year calibration period starting 1991 (pre-buffer period). Thereafter, two of them were treated with upland contour grass and agroforestry (tree + grass) buffers (4.5 m wide, 36.5 m apart) to study water quality benefits. The fuzzy system was based on Mamdani method using MATLAB 7.10.0. The model predicted event-based runoff with model performance coefficients of r2 and Nash-Sutcliffe Coefficient (NSC) values greater than 0.65 for calibration and validation. The pre-buffer fuzzy system predicted event-based runoff for 30-50 times larger corn/soybean watersheds with r2 values of 0.82 and 0.68 and NSC values of 0.77 and 0.53, respectively. The runoff predicted by the fuzzy system closely agreed with values predicted by physically-based Agricultural Policy Environmental eXtender model (APEX) for the pre-buffer watersheds. The fuzzy rainfall-runoff model has the potential for runoff predictions at field-scale watersheds with minimum input. It also could up-scale the predictions for large-scale watersheds to evaluate the benefits of conservation practices.

A model to forecast short-term snowmelt runoff using synoptic observations of streamflow, temperature, and precipitation

USGS Publications Warehouse

Tangborn, Wendell V.

1980-01-01

Snowmelt runoff is forecast with a statistical model that utilizes daily values of stream discharge, gaged precipitation, and maximum and minimum observations of air temperature. Synoptic observations of these variables are made at existing low- and medium-altitude weather stations, thus eliminating the difficulties and expense of new, high-altitude installations. Four model development steps are used to demonstrate the influence on prediction accuracy of basin storage, a preforecast test season, air temperature (to estimate ablation), and a prediction based on storage. Daily ablation is determined by a technique that employs both mean temperature and a radiative index. Radiation (both long- and short-wave components) is approximated by using the range in daily temperature, which is shown to be closely related to mean cloud cover. A technique based on the relationship between prediction error and prediction season weather utilizes short-term forecasts of precipitation and temperature to improve the final prediction. Verification of the model is accomplished by a split sampling technique for the 1960–1977 period. Short- term (5–15 days) predictions of runoff throughout the main snowmelt season are demonstrated for mountain drainages in western Washington, south-central Arizona, western Montana, and central California. The coefficient of prediction (Cp) based on actual, short-term predictions for 18 years is for Thunder Creek (Washington), 0.69; for South Fork Flathead River (Montana), 0.45; for the Black River (Arizona), 0.80; and for the Kings River (California), 0.80.

A detailed comparison of optimality and simplicity in perceptual decision-making

PubMed Central

Shen, Shan; Ma, Wei Ji

2017-01-01

Two prominent ideas in the study of decision-making have been that organisms behave near-optimally, and that they use simple heuristic rules. These principles might be operating in different types of tasks, but this possibility cannot be fully investigated without a direct, rigorous comparison within a single task. Such a comparison was lacking in most previous studies, because a) the optimal decision rule was simple; b) no simple suboptimal rules were considered; c) it was unclear what was optimal, or d) a simple rule could closely approximate the optimal rule. Here, we used a perceptual decision-making task in which the optimal decision rule is well-defined and complex, and makes qualitatively distinct predictions from many simple suboptimal rules. We find that all simple rules tested fail to describe human behavior, that the optimal rule accounts well for the data, and that several complex suboptimal rules are indistinguishable from the optimal one. Moreover, we found evidence that the optimal model is close to the true model: first, the better the trial-to-trial predictions of a suboptimal model agree with those of the optimal model, the better that suboptimal model fits; second, our estimate of the Kullback-Leibler divergence between the optimal model and the true model is not significantly different from zero. When observers receive no feedback, the optimal model still describes behavior best, suggesting that sensory uncertainty is implicitly represented and taken into account. Beyond the task and models studied here, our results have implications for best practices of model comparison. PMID:27177259

External prognostic validations and comparisons of age- and gender-adjusted exercise capacity predictions.

PubMed

Kim, Esther S H; Ishwaran, Hemant; Blackstone, Eugene; Lauer, Michael S

2007-11-06

The purpose of this study was to externally validate the prognostic value of age- and gender-based nomograms and categorical definitions of impaired exercise capacity (EC). Exercise capacity predicts death, but its use in routine clinical practice is hampered by its close correlation with age and gender. For a median of 5 years, we followed 22,275 patients without known heart disease who underwent symptom-limited stress testing. Models for predicted or impaired EC were identified by literature search. Gender-specific multivariable proportional hazards models were constructed. Four methods were used to assess validity: Akaike Information Criterion (AIC), right-censored c-index in 100 out-of-bootstrap samples, the Nagelkerke Index R2, and calculation of calibration error in 100 bootstrap samples. There were 646 and 430 deaths in 13,098 men and 9,177 women, respectively. Of the 7 models tested in men, a model based on a Veterans Affairs cohort (predicted metabolic equivalents [METs] = 18 - [0.15 x age]) had the highest AIC and R2. In women, a model based on the St. James Take Heart Project (predicted METs = 14.7 - [0.13 x age]) performed best. Categorical definitions of fitness performed less well. Even after accounting for age and gender, there was still an important interaction with age, whereby predicted EC was a weaker predictor in older subjects (p for interaction <0.001 in men and 0.003 in women). Several methods describe EC accounting for age and gender-related differences, but their ability to predict mortality differ. Simple cutoff values fail to fully describe EC's strong predictive value.

Close-packed structure dynamics with finite-range interaction: computational mechanics with individual layer interaction.

PubMed

Rodriguez-Horta, Edwin; Estevez-Rams, Ernesto; Lora-Serrano, Raimundo; Neder, Reinhard

2017-09-01

This is the second contribution in a series of papers dealing with dynamical models in equilibrium theories of polytypism. A Hamiltonian introduced by Ahmad & Khan [Phys. Status Solidi B (2000), 218, 425-430] avoids the unphysical assignment of interaction terms to fictitious entities given by spins in the Hägg coding of the stacking arrangement. In this paper an analysis of polytype generation and disorder in close-packed structures is made for such a Hamiltonian. Results are compared with a previous analysis using the Ising model. Computational mechanics is the framework under which the analysis is performed. The competing effects of disorder and structure, as given by entropy density and excess entropy, respectively, are discussed. It is argued that the Ahmad & Khan model is simpler and predicts a larger set of polytypes than previous treatments.

Partial synchronization of relaxation oscillators with repulsive coupling in autocatalytic integrate-and-fire model and electrochemical experiments

NASA Astrophysics Data System (ADS)

Kori, Hiroshi; Kiss, István Z.; Jain, Swati; Hudson, John L.

2018-04-01

Experiments and supporting theoretical analysis are presented to describe the synchronization patterns that can be observed with a population of globally coupled electrochemical oscillators close to a homoclinic, saddle-loop bifurcation, where the coupling is repulsive in the electrode potential. While attractive coupling generates phase clusters and desynchronized states, repulsive coupling results in synchronized oscillations. The experiments are interpreted with a phenomenological model that captures the waveform of the oscillations (exponential increase) followed by a refractory period. The globally coupled autocatalytic integrate-and-fire model predicts the development of partially synchronized states that occur through attracting heteroclinic cycles between out-of-phase two-cluster states. Similar behavior can be expected in many other systems where the oscillations occur close to a saddle-loop bifurcation, e.g., with Morris-Lecar neurons.

Experimental validation study of an analytical model of discrete frequency sound propagation in closed-test-section wind tunnels

NASA Technical Reports Server (NTRS)

Mosher, Marianne

1990-01-01

The principal objective is to assess the adequacy of linear acoustic theory with an impedence wall boundary condition to model the detailed sound field of an acoustic source in a duct. Measurements and calculations are compared of a simple acoustic source in a rectangular concrete duct lined with foam on the walls and anechoic end terminations. Measurement of acoustic pressure for twelve wave numbers provides variation in frequency and absorption characteristics of the duct walls. Close to the source, where the interference of wall reflections is minimal, correlation is very good. Away from the source, correlation degrades, especially for the lower frequencies. Sensitivity studies show little effect on the predicted results for changes in impedance boundary condition values, source location, measurement location, temperature, and source model for variations spanning the expected measurement error.

Extinction threshold for spatial forest dynamics with height structure.

PubMed

Garcia-Domingo, Josep L; Saldaña, Joan

2011-05-07

We present a pair-approximation model for spatial forest dynamics defined on a regular lattice. The model assumes three possible states for a lattice site: empty (gap site), occupied by an immature tree, and occupied by a mature tree, and considers three nonlinearities in the dynamics associated to the processes of light interference, gap expansion, and recruitment. We obtain an expression of the basic reproduction number R(0) which, in contrast to the one obtained under the mean-field approach, uses information about the spatial arrangement of individuals close to extinction. Moreover, we analyze the corresponding survival-extinction transition of the forest and the spatial correlations among gaps, immature and mature trees close to this critical point. Predictions of the pair-approximation model are compared with those of a cellular automaton. Copyright © 2011 Elsevier Ltd. All rights reserved.

Effects of Career-Related Continuous Learning: A Case Study

ERIC Educational Resources Information Center

Rowold, Jens; Hochholdinger, Sabine; Schilling, Jan

2008-01-01

Purpose: Although proposed from theory, the assumption that career-related continuous learning (CRCL) has a positive impact on subsequent job performance has not been tested empirically. The present study aims to close this gap in the literature. A model is derived from theory that predicts a positive impact of CRCL, learning climate, and initial…

Potential predictability and actual skill of Boreal Summer Tropical SST and Indian summer monsoon rainfall in CFSv2-T382: Role of initial SST and teleconnections

NASA Astrophysics Data System (ADS)

Pillai, Prasanth A.; Rao, Suryachandra A.; Das, Renu S.; Salunke, Kiran; Dhakate, Ashish

2017-10-01

The present study assess the potential predictability of boreal summer (June through September, JJAS) tropical sea surface temperature (SST) and Indian summer monsoon rainfall (ISMR) using high resolution climate forecast system (CFSv2-T382) hindcasts. Potential predictability is computed using relative entropy (RE), which is the combined effect of signal strength and model spread, while the correlation between ensemble mean and observations represents the actual skill. Both actual and potential skills increase as lead time decreases for Niño3 index and equatorial East Indian Ocean (EEIO) SST anomaly and both the skills are close to each other for May IC hindcasts at zero lead. At the same time the actual skill of ISMR and El Niño Modoki index (EMI) are close to potential skill for Feb IC hindcasts (3 month lead). It is interesting to note that, both actual and potential skills are nearly equal, when RE has maximum contribution to individual year's prediction skill and its relationship with absolute error is insignificant or out of phase. The major contribution to potential predictability is from ensemble mean and the role of ensemble spread is limited for Pacific SST and ISMR hindcasts. RE values are able to capture the predictability contribution from both initial SST and simultaneous boundary forcing better than ensemble mean, resulting in higher potential skill compared to actual skill for all ICs. For Feb IC hindcasts at 3 month lead time, initial month SST (Feb SST) has important predictive component for El Niño Modoki and ISMR leading to higher value of actual skill which is close to potential skill. This study points out that even though the simultaneous relationship between ensemble mean ISMR and global SST is similar for all ICs, the predictive component from initial SST anomalies are captured well by Feb IC (3 month lead) hindcasts only. This resulted in better skill of ISMR for Feb IC (3 month lead) hindcasts compared to May IC (0 month lead) hindcasts. Lack of proper contribution from initial SST and teleconnections induces large absolute error for ISMR in May IC hindcasts resulting in very low actual skill. Thus the use of potential predictability skill and actual skill collectively help to understand the fidelity of the model for further improvement by differentiating the role of initial SST and simultaneous boundary forcing to some extent.

Orbit Determination for the Lunar Reconnaissance Orbiter Using an Extended Kalman Filter

NASA Technical Reports Server (NTRS)

Slojkowski, Steven; Lowe, Jonathan; Woodburn, James

2015-01-01

Orbit determination (OD) analysis results are presented for the Lunar Reconnaissance Orbiter (LRO) using a commercially available Extended Kalman Filter, Analytical Graphics' Orbit Determination Tool Kit (ODTK). Process noise models for lunar gravity and solar radiation pressure (SRP) are described and OD results employing the models are presented. Definitive accuracy using ODTK meets mission requirements and is better than that achieved using the operational LRO OD tool, the Goddard Trajectory Determination System (GTDS). Results demonstrate that a Vasicek stochastic model produces better estimates of the coefficient of solar radiation pressure than a Gauss-Markov model, and prediction accuracy using a Vasicek model meets mission requirements over the analysis span. Modeling the effect of antenna motion on range-rate tracking considerably improves residuals and filter-smoother consistency. Inclusion of off-axis SRP process noise and generalized process noise improves filter performance for both definitive and predicted accuracy. Definitive accuracy from the smoother is better than achieved using GTDS and is close to that achieved by precision OD methods used to generate definitive science orbits. Use of a multi-plate dynamic spacecraft area model with ODTK's force model plugin capability provides additional improvements in predicted accuracy.

Interpreting electrically evoked emissions using a finite-element model of the cochlea

NASA Astrophysics Data System (ADS)

Deo, Niranjan V.; Grosh, Karl; Parthasarathi, Anand

2003-10-01

Electrically evoked otoacoustic emissions (EEOAEs) are used to investigate in vivo cochlear electromechanical function. Electrical stimulation through bipolar electrodes placed very close to the basilar membrane (in the scala vestibuli and scala tympani) gives rise to a narrow frequency range of EEOAEs, limited to around 20 kHz when the electrodes are placed near the 18-kHz best frequency place. Model predictions using a three-dimensional inviscid fluid model in conjunction with a middle ear model [S. Puria and J. B. Allen, J. Acoust. Soc. Am. 104, 3463-3481 (1998)] and a simple model for outer hair cell activity [S. Neely and D. Kim, J. Acoust. Soc. Am. 94, 137-146 (1993)] are used to interpret the experimental results. To estimate effect of viscosity, model results are compared with those obtained for a viscous fluid. The models are solved using a 2.5-D finite-element formulation. Predictions show that the high frequency limit of the excitation is determined by the spatial extent of the current stimulus. The global peaks in the EEOAE spectra are interpreted as constructive interference between electrically evoked backward traveling waves and forward traveling waves reflected from the stapes. Steady state response predictions of the model are presented.

Impact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven Analysis.

PubMed

Agarwal, Vibhu; Zhang, Liangliang; Zhu, Josh; Fang, Shiyuan; Cheng, Tim; Hong, Chloe; Shah, Nigam H

2016-09-21

By recent estimates, the steady rise in health care costs has deprived more than 45 million Americans of health care services and has encouraged health care providers to better understand the key drivers of health care utilization from a population health management perspective. Prior studies suggest the feasibility of mining population-level patterns of health care resource utilization from observational analysis of Internet search logs; however, the utility of the endeavor to the various stakeholders in a health ecosystem remains unclear. The aim was to carry out a closed-loop evaluation of the utility of health care use predictions using the conversion rates of advertisements that were displayed to the predicted future utilizers as a surrogate. The statistical models to predict the probability of user's future visit to a medical facility were built using effective predictors of health care resource utilization, extracted from a deidentified dataset of geotagged mobile Internet search logs representing searches made by users of the Baidu search engine between March 2015 and May 2015. We inferred presence within the geofence of a medical facility from location and duration information from users' search logs and putatively assigned medical facility visit labels to qualifying search logs. We constructed a matrix of general, semantic, and location-based features from search logs of users that had 42 or more search days preceding a medical facility visit as well as from search logs of users that had no medical visits and trained statistical learners for predicting future medical visits. We then carried out a closed-loop evaluation of the utility of health care use predictions using the show conversion rates of advertisements displayed to the predicted future utilizers. In the context of behaviorally targeted advertising, wherein health care providers are interested in minimizing their cost per conversion, the association between show conversion rate and predicted utilization score, served as a surrogate measure of the model's utility. We obtained the highest area under the curve (0.796) in medical visit prediction with our random forests model and daywise features. Ablating feature categories one at a time showed that the model performance worsened the most when location features were dropped. An online evaluation in which advertisements were served to users who had a high predicted probability of a future medical visit showed a 3.96% increase in the show conversion rate. Results from our experiments done in a research setting suggest that it is possible to accurately predict future patient visits from geotagged mobile search logs. Results from the offline and online experiments on the utility of health utilization predictions suggest that such prediction can have utility for health care providers.

Flight simulator fidelity assessment in a rotorcraft lateral translation maneuver

NASA Technical Reports Server (NTRS)

Hess, R. A.; Malsbury, T.; Atencio, A., Jr.

1992-01-01

A model-based methodology for assessing flight simulator fidelity in closed-loop fashion is exercised in analyzing a rotorcraft low-altitude maneuver for which flight test and simulation results were available. The addition of a handling qualities sensitivity function to a previously developed model-based assessment criteria allows an analytical comparison of both performance and handling qualities between simulation and flight test. Model predictions regarding the existence of simulator fidelity problems are corroborated by experiment. The modeling approach is used to assess analytically the effects of modifying simulator characteristics on simulator fidelity.

F-14 modeling study

NASA Technical Reports Server (NTRS)

Levison, William H.

1988-01-01

This study explored application of a closed loop pilot/simulator model to the analysis of some simulator fidelity issues. The model was applied to two data bases: (1) a NASA ground based simulation of an air-to-air tracking task in which nonvisual cueing devices were explored, and (2) a ground based and inflight study performed by the Calspan Corporation to explore the effects of simulator delay on attitude tracking performance. The model predicted the major performance trends obtained in both studies. A combined analytical and experimental procedure for exploring simulator fidelity issues is outlined.

Maripa Hantavirus in French Guiana: Phylogenetic Position and Predicted Spatial Distribution of Rodent Hosts

PubMed Central

de Thoisy, Benoît; Matheus, Séverine; Catzeflis, François; Clément, Luc; Barrioz, Sébastien; Guidez, Amandine; Donato, Damien; Cornu, Jean-François; Brunaux, Olivier; Guitet, Stéphane; Lacoste, Vincent; Lavergne, Anne

2014-01-01

A molecular screening of wild-caught rodents was conducted in French Guiana, South America to identify hosts of the hantavirus Maripa described in 2008 in a hantavirus pulmonary syndrome (HPS) case. Over a 9-year period, 418 echimyids and murids were captured. Viral RNA was detected in two sigmodontine rodents, Oligoryzomys fulvescens and Zygodontomys brevicauda, trapped close to the house of a second HPS case that occurred in 2009 and an O. fulvescens close to the fourth HPS case identified in 2013. Sequences from the rodents had 96% and 97% nucleotide identity (fragment of S and M segments, respectively) with the sequence of the first human HPS case. Phylogenetic reconstructions based on the complete sequence of the S segment show that Maripa virus is closely related to Rio Mamore hantavirus. Using environmental descriptors of trapping sites, including vegetation, landscape units, rain, and human disturbance, a maximal entropy-based species distribution model allowed for identification of areas of higher predicted occurrence of the two rodents, where emergence risks of Maripa virus are expected to be higher. PMID:24752689

Maripa hantavirus in French Guiana: phylogenetic position and predicted spatial distribution of rodent hosts.

PubMed

de Thoisy, Benoît; Matheus, Séverine; Catzeflis, François; Clément, Luc; Barrioz, Sébastien; Guidez, Amandine; Donato, Damien; Cornu, Jean-François; Brunaux, Olivier; Guitet, Stéphane; Lacoste, Vincent; Lavergne, Anne

2014-06-01

A molecular screening of wild-caught rodents was conducted in French Guiana, South America to identify hosts of the hantavirus Maripa described in 2008 in a hantavirus pulmonary syndrome (HPS) case. Over a 9-year period, 418 echimyids and murids were captured. Viral RNA was detected in two sigmodontine rodents, Oligoryzomys fulvescens and Zygodontomys brevicauda, trapped close to the house of a second HPS case that occurred in 2009 and an O. fulvescens close to the fourth HPS case identified in 2013. Sequences from the rodents had 96% and 97% nucleotide identity (fragment of S and M segments, respectively) with the sequence of the first human HPS case. Phylogenetic reconstructions based on the complete sequence of the S segment show that Maripa virus is closely related to Rio Mamore hantavirus. Using environmental descriptors of trapping sites, including vegetation, landscape units, rain, and human disturbance, a maximal entropy-based species distribution model allowed for identification of areas of higher predicted occurrence of the two rodents, where emergence risks of Maripa virus are expected to be higher. © The American Society of Tropical Medicine and Hygiene.

Cloud regimes as phase transitions

NASA Astrophysics Data System (ADS)

Stechmann, Samuel; Hottovy, Scott

2017-11-01

Clouds are repeatedly identified as a leading source of uncertainty in future climate predictions. Of particular importance are stratocumulus clouds, which can appear as either (i) closed cells that reflect solar radiation back to space or (ii) open cells that allow solar radiation to reach the Earth's surface. Here we show that these clouds regimes - open versus closed cells - fit the paradigm of a phase transition. In addition, this paradigm characterizes pockets of open cells (POCs) as the interface between the open- and closed-cell regimes, and it identifies shallow cumulus clouds as a regime of higher variability. This behavior can be understood using an idealized model for the dynamics of atmospheric water as a stochastic diffusion process. Similar viewpoints of deep convection and self-organized criticality will also be discussed. With these new conceptual viewpoints, ideas from statistical mechanics could potentially be used for understanding uncertainties related to clouds in the climate system and climate predictions. The research of S.N.S. is partially supported by a Sloan Research Fellowship, ONR Young Investigator Award N00014-12-1-0744, and ONR MURI Grant N00014-12-1-0912.

Coupled Riccati equations for complex plane constraint

NASA Technical Reports Server (NTRS)

Strong, Kristin M.; Sesak, John R.

1991-01-01

A new Linear Quadratic Gaussian design method is presented which provides prescribed imaginary axis pole placement for optimal control and estimation systems. This procedure contributes another degree of design freedom to flexible spacecraft control. Current design methods which interject modal damping into the system tend to have little affect on modal frequencies, i.e., they predictably shift open plant poles horizontally in the complex plane to form the closed loop controller or estimator pole constellation, but make little provision for vertical (imaginary axis) pole shifts. Imaginary axis shifts which reduce the closed loop model frequencies (the bandwidths) are desirable since they reduce the sensitivity of the system to noise disturbances. The new method drives the closed loop modal frequencies to predictable (specified) levels, frequencies as low as zero rad/sec (real axis pole placement) can be achieved. The design procedure works through rotational and translational destabilizations of the plant, and a coupling of two independently solved algebraic Riccati equations through a structured state weighting matrix. Two new concepts, gain transference and Q equivalency, are introduced and their use shown.

The effects of parental education and family income on mother-child relationships, father-child relationships, and family environments in the People's Republic of China.

PubMed

Zhang, Xiao

2012-12-01

Using a cross-sectional design with 407 Chinese children aged 3-5 years and their parents, this study examined the effects of socioeconomic status, specifically parents' education and family income, on the children's mother-child relationships, father-child relationships, and the social environment in their families. The results indicated that income negatively predicted conflict in father-child relationships and positively predicted family active-recreational environments. Income also positively predicted family cohesion among girls but not boys. Maternal education negatively predicted conflict in mother-child relationships and positively predicted closeness in mother-child and father-child relationships, family cohesion, and the intellectual-cultural and active-recreational environments in the family. Paternal education positively predicted family cohesion and intellectual-cultural and active-recreational environments. Income was found to partially mediate the effects of both maternal and paternal education on family active-recreational environments. Findings are discussed in the frameworks of the family stress model and the family investment model. © FPI, Inc.

Real-time control of walking using recordings from dorsal root ganglia

NASA Astrophysics Data System (ADS)

Holinski, B. J.; Everaert, D. G.; Mushahwar, V. K.; Stein, R. B.

2013-10-01

Objective. The goal of this study was to decode sensory information from the dorsal root ganglia (DRG) in real time, and to use this information to adapt the control of unilateral stepping with a state-based control algorithm consisting of both feed-forward and feedback components. Approach. In five anesthetized cats, hind limb stepping on a walkway or treadmill was produced by patterned electrical stimulation of the spinal cord through implanted microwire arrays, while neuronal activity was recorded from the DRG. Different parameters, including distance and tilt of the vector between hip and limb endpoint, integrated gyroscope and ground reaction force were modelled from recorded neural firing rates. These models were then used for closed-loop feedback. Main results. Overall, firing-rate-based predictions of kinematic sensors (limb endpoint, integrated gyroscope) were the most accurate with variance accounted for >60% on average. Force prediction had the lowest prediction accuracy (48 ± 13%) but produced the greatest percentage of successful rule activations (96.3%) for stepping under closed-loop feedback control. The prediction of all sensor modalities degraded over time, with the exception of tilt. Significance. Sensory feedback from moving limbs would be a desirable component of any neuroprosthetic device designed to restore walking in people after a spinal cord injury. This study provides a proof-of-principle that real-time feedback from the DRG is possible and could form part of a fully implantable neuroprosthetic device with further development.

Real-time control of walking using recordings from dorsal root ganglia

PubMed Central

Holinski, B J; Everaert, D G; Mushahwar, V K; Stein, R B

2013-01-01

Objective The goal of this study was to decode sensory information from the dorsal root ganglia (DRG) in real time, and to use this information to adapt the control of unilateral stepping with a state-based control algorithm consisting of both feed-forward and feedback components. Approach In five anesthetized cats, hind limb stepping on a walkway or treadmill was produced by patterned electrical stimulation of the spinal cord through implanted microwire arrays, while neuronal activity was recorded from the dorsal root ganglia. Different parameters, including distance and tilt of the vector between hip and limb endpoint, integrated gyroscope and ground reaction force were modeled from recorded neural firing rates. These models were then used for closed-loop feedback. Main Results Overall, firing-rate based predictions of kinematic sensors (limb endpoint, integrated gyroscope) were the most accurate with variance accounted for >60% on average. Force prediction had the lowest prediction accuracy (48±13%) but produced the greatest percentage of successful rule activations (96.3%) for stepping under closed-loop feedback control. The prediction of all sensor modalities degraded over time, with the exception of tilt. Significance Sensory feedback from moving limbs would be a desirable component of any neuroprosthetic device designed to restore walking in people after a spinal cord injury. This study provides a proof-of-principle that real-time feedback from the DRG is possible and could form part of a fully implantable neuroprosthetic device with further development. PMID:23928579

Lower extremity EMG-driven modeling of walking with automated adjustment of musculoskeletal geometry

PubMed Central

Meyer, Andrew J.; Patten, Carolynn

2017-01-01

Neuromusculoskeletal disorders affecting walking ability are often difficult to manage, in part due to limited understanding of how a patient’s lower extremity muscle excitations contribute to the patient’s lower extremity joint moments. To assist in the study of these disorders, researchers have developed electromyography (EMG) driven neuromusculoskeletal models utilizing scaled generic musculoskeletal geometry. While these models can predict individual muscle contributions to lower extremity joint moments during walking, the accuracy of the predictions can be hindered by errors in the scaled geometry. This study presents a novel EMG-driven modeling method that automatically adjusts surrogate representations of the patient’s musculoskeletal geometry to improve prediction of lower extremity joint moments during walking. In addition to commonly adjusted neuromusculoskeletal model parameters, the proposed method adjusts model parameters defining muscle-tendon lengths, velocities, and moment arms. We evaluated our EMG-driven modeling method using data collected from a high-functioning hemiparetic subject walking on an instrumented treadmill at speeds ranging from 0.4 to 0.8 m/s. EMG-driven model parameter values were calibrated to match inverse dynamic moments for five degrees of freedom in each leg while keeping musculoskeletal geometry close to that of an initial scaled musculoskeletal model. We found that our EMG-driven modeling method incorporating automated adjustment of musculoskeletal geometry predicted net joint moments during walking more accurately than did the same method without geometric adjustments. Geometric adjustments improved moment prediction errors by 25% on average and up to 52%, with the largest improvements occurring at the hip. Predicted adjustments to musculoskeletal geometry were comparable to errors reported in the literature between scaled generic geometric models and measurements made from imaging data. Our results demonstrate that with appropriate experimental data, joint moment predictions for walking generated by an EMG-driven model can be improved significantly when automated adjustment of musculoskeletal geometry is included in the model calibration process. PMID:28700708

Fingerstroke time estimates for touchscreen-based mobile gaming interaction.

PubMed

Lee, Ahreum; Song, Kiburm; Ryu, Hokyoung Blake; Kim, Jieun; Kwon, Gyuhyun

2015-12-01

The growing popularity of gaming applications and ever-faster mobile carrier networks have called attention to an intriguing issue that is closely related to command input performance. A challenging mirroring game service, which simultaneously provides game service to both PC and mobile phone users, allows them to play games against each other with very different control interfaces. Thus, for efficient mobile game design, it is essential to apply a new predictive model for measuring how potential touch input compares to the PC interfaces. The present study empirically tests the keystroke-level model (KLM) for predicting the time performance of basic interaction controls on the touch-sensitive smartphone interface (i.e., tapping, pointing, dragging, and flicking). A modified KLM, tentatively called the fingerstroke-level model (FLM), is proposed using time estimates on regression models. Copyright © 2015 Elsevier B.V. All rights reserved.

Weakly Nonlinear Model with Exact Coefficients for the Fluttering and Spiraling Motion of Buoyancy-Driven Bodies

NASA Astrophysics Data System (ADS)

Tchoufag, Joël; Fabre, David; Magnaudet, Jacques

2015-09-01

Gravity- or buoyancy-driven bodies moving in a slightly viscous fluid frequently follow fluttering or helical paths. Current models of such systems are largely empirical and fail to predict several of the key features of their evolution, especially close to the onset of path instability. Here, using a weakly nonlinear expansion of the full set of governing equations, we present a new generic reduced-order model based on a pair of amplitude equations with exact coefficients that drive the evolution of the first pair of unstable modes. We show that the predictions of this model for the style (e.g., fluttering or spiraling) and characteristics (e.g., frequency and maximum inclination angle) of path oscillations compare well with various recent data for both solid disks and air bubbles.

A weakly nonlinear model with exact coefficients for the fluttering and spiraling motions of buoyancy-driven bodies

NASA Astrophysics Data System (ADS)

Magnaudet, Jacques; Tchoufag, Joel; Fabre, David

2015-11-01

Gravity/buoyancy-driven bodies moving in a slightly viscous fluid frequently follow fluttering or helical paths. Current models of such systems are largely empirical and fail to predict several of the key features of their evolution, especially close to the onset of path instability. Using a weakly nonlinear expansion of the full set of governing equations, we derive a new generic reduced-order model of this class of phenomena based on a pair of amplitude equations with exact coefficients that drive the evolution of the first pair of unstable modes. We show that the predictions of this model for the style (eg. fluttering or spiraling) and characteristics (eg. frequency and maximum inclination angle) of path oscillations compare well with various recent data for both solid disks and air bubbles.

InGaAs tunnel diodes for the calibration of semi-classical and quantum mechanical band-to-band tunneling models

NASA Astrophysics Data System (ADS)

Smets, Quentin; Verreck, Devin; Verhulst, Anne S.; Rooyackers, Rita; Merckling, Clément; Van De Put, Maarten; Simoen, Eddy; Vandervorst, Wilfried; Collaert, Nadine; Thean, Voon Y.; Sorée, Bart; Groeseneken, Guido; Heyns, Marc M.

2014-05-01

Promising predictions are made for III-V tunnel-field-effect transistor (FET), but there is still uncertainty on the parameters used in the band-to-band tunneling models. Therefore, two simulators are calibrated in this paper; the first one uses a semi-classical tunneling model based on Kane's formalism, and the second one is a quantum mechanical simulator implemented with an envelope function formalism. The calibration is done for In0.53Ga0.47As using several p+/intrinsic/n+ diodes with different intrinsic region thicknesses. The dopant profile is determined by SIMS and capacitance-voltage measurements. Error bars are used based on statistical and systematic uncertainties in the measurement techniques. The obtained parameters are in close agreement with theoretically predicted values and validate the semi-classical and quantum mechanical models. Finally, the models are applied to predict the input characteristics of In0.53Ga0.47As n- and p-lineTFET, with the n-lineTFET showing competitive performance compared to MOSFET.

Conditional dissipation of scalars in homogeneous turbulence: Closure for MMC modelling

NASA Astrophysics Data System (ADS)

Wandel, Andrew P.

2013-08-01

While the mean and unconditional variance are to be predicted well by any reasonable turbulent combustion model, these are generally not sufficient for the accurate modelling of complex phenomena such as extinction/reignition. An additional criterion has been recently introduced: accurate modelling of the dissipation timescales associated with fluctuations of scalars about their conditional mean (conditional dissipation timescales). Analysis of Direct Numerical Simulation (DNS) results for a passive scalar shows that the conditional dissipation timescale is of the order of the integral timescale and smaller than the unconditional dissipation timescale. A model is proposed: the conditional dissipation timescale is proportional to the integral timescale. This model is used in Multiple Mapping Conditioning (MMC) modelling for a passive scalar case and a reactive scalar case, comparing to DNS results for both. The results show that this model improves the accuracy of MMC predictions so as to match the DNS results more closely using a relatively-coarse spatial resolution compared to other turbulent combustion models.

Directional stability of crack propagation

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

Streit, R.D.; Finnie, I.

Despite many alternative models, the original Erdogan and Sih (1963) hypothesis that a crack will grow in the direction perpendicular to the maximum circumferential stress sigma/sub theta/ is seen to be adequate for predicting the angle of crack growth under the condition of mixed mode loading. Their predictions, which were based on the singularity terms in the series expansion for the Mode I and Mode II stress fields, can be improved if the second term in the series is also included. Although conceptually simple, their predictions of the crack growth direction fit very closely to the data obtained from manymore » sources.« less

Trend extraction using empirical mode decomposition and statistical empirical mode decomposition: Case study: Kuala Lumpur stock market

NASA Astrophysics Data System (ADS)

Jaber, Abobaker M.

2014-12-01

Two nonparametric methods for prediction and modeling of financial time series signals are proposed. The proposed techniques are designed to handle non-stationary and non-linearity behave and to extract meaningful signals for reliable prediction. Due to Fourier Transform (FT), the methods select significant decomposed signals that will be employed for signal prediction. The proposed techniques developed by coupling Holt-winter method with Empirical Mode Decomposition (EMD) and it is Extending the scope of empirical mode decomposition by smoothing (SEMD). To show performance of proposed techniques, we analyze daily closed price of Kuala Lumpur stock market index.

BetaSCPWeb: side-chain prediction for protein structures using Voronoi diagrams and geometry prioritization

PubMed Central

Ryu, Joonghyun; Lee, Mokwon; Cha, Jehyun; Laskowski, Roman A.; Ryu, Seong Eon; Kim, Deok-Soo

2016-01-01

Many applications, such as protein design, homology modeling, flexible docking, etc. require the prediction of a protein's optimal side-chain conformations from just its amino acid sequence and backbone structure. Side-chain prediction (SCP) is an NP-hard energy minimization problem. Here, we present BetaSCPWeb which efficiently computes a conformation close to optimal using a geometry-prioritization method based on the Voronoi diagram of spherical atoms. Its outputs are visual, textual and PDB file format. The web server is free and open to all users at http://voronoi.hanyang.ac.kr/betascpweb with no login requirement. PMID:27151195

The Predictive Capability of Conditioned Simulation of Discrete Fracture Networks using Structural and Hydraulic Data from the ONKALO Underground Research Facility, Finland

NASA Astrophysics Data System (ADS)

Williams, T. R. N.; Baxter, S.; Hartley, L.; Appleyard, P.; Koskinen, L.; Vanhanarkaus, O.; Selroos, J. O.; Munier, R.

2017-12-01

Discrete fracture network (DFN) models provide a natural analysis framework for rock conditions where flow is predominately through a series of connected discrete features. Mechanistic models to predict the structural patterns of networks are generally intractable due to inherent uncertainties (e.g. deformation history) and as such fracture characterisation typically involves empirical descriptions of fracture statistics for location, intensity, orientation, size, aperture etc. from analyses of field data. These DFN models are used to make probabilistic predictions of likely flow or solute transport conditions for a range of applications in underground resource and construction projects. However, there are many instances when the volumes in which predictions are most valuable are close to data sources. For example, in the disposal of hazardous materials such as radioactive waste, accurate predictions of flow-rates and network connectivity around disposal areas are required for long-term safety evaluation. The problem at hand is thus: how can probabilistic predictions be conditioned on local-scale measurements? This presentation demonstrates conditioning of a DFN model based on the current structural and hydraulic characterisation of the Demonstration Area at the ONKALO underground research facility. The conditioned realisations honour (to a required level of similarity) the locations, orientations and trace lengths of fractures mapped on the surfaces of the nearby ONKALO tunnels and pilot drillholes. Other data used as constraints include measurements from hydraulic injection tests performed in pilot drillholes and inflows to the subsequently reamed experimental deposition holes. Numerical simulations using this suite of conditioned DFN models provides a series of prediction-outcome exercises detailing the reliability of the DFN model to make local-scale predictions of measured geometric and hydraulic properties of the fracture system; and provides an understanding of the reduction in uncertainty in model predictions for conditioned DFN models honouring different aspects of this data.

Fast image-based mitral valve simulation from individualized geometry.

PubMed

Villard, Pierre-Frederic; Hammer, Peter E; Perrin, Douglas P; Del Nido, Pedro J; Howe, Robert D

2018-04-01

Common surgical procedures on the mitral valve of the heart include modifications to the chordae tendineae. Such interventions are used when there is extensive leaflet prolapse caused by chordae rupture or elongation. Understanding the role of individual chordae tendineae before operating could be helpful to predict whether the mitral valve will be competent at peak systole. Biomechanical modelling and simulation can achieve this goal. We present a method to semi-automatically build a computational model of a mitral valve from micro CT (computed tomography) scans: after manually picking chordae fiducial points, the leaflets are segmented and the boundary conditions as well as the loading conditions are automatically defined. Fast finite element method (FEM) simulation is carried out using Simulation Open Framework Architecture (SOFA) to reproduce leaflet closure at peak systole. We develop three metrics to evaluate simulation results: (i) point-to-surface error with the ground truth reference extracted from the CT image, (ii) coaptation surface area of the leaflets and (iii) an indication of whether the simulated closed leaflets leak. We validate our method on three explanted porcine hearts and show that our model predicts the closed valve surface with point-to-surface error of approximately 1 mm, a reasonable coaptation surface area, and absence of any leak at peak systole (maximum closed pressure). We also evaluate the sensitivity of our model to changes in various parameters (tissue elasticity, mesh accuracy, and the transformation matrix used for CT scan registration). We also measure the influence of the positions of the chordae tendineae on simulation results and show that marginal chordae have a greater influence on the final shape than intermediate chordae. The mitral valve simulation can help the surgeon understand valve behaviour and anticipate the outcome of a procedure. Copyright © 2018 John Wiley & Sons, Ltd.

Theoretical model of impact damage in structural ceramics

NASA Technical Reports Server (NTRS)

Liaw, B. M.; Kobayashi, A. S.; Emery, A. G.

1984-01-01

This paper presents a mechanistically consistent model of impact damage based on elastic failures due to tensile and shear overloading. An elastic axisymmetric finite element model is used to determine the dynamic stresses generated by a single particle impact. Local failures in a finite element are assumed to occur when the primary/secondary principal stresses or the maximum shear stress reach critical tensile or shear stresses, respectively. The succession of failed elements thus models macrocrack growth. Sliding motions of cracks, which closed during unloading, are resisted by friction and the unrecovered deformation represents the 'plastic deformation' reported in the literature. The predicted ring cracks on the contact surface, as well as the cone cracks, median cracks, radial cracks, lateral cracks, and damage-induced porous zones in the interior of hot-pressed silicon nitride plates, matched those observed experimentally. The finite element model also predicted the uplifting of the free surface surrounding the impact site.

Shape Phase Transition from Octupole Deformation to Octupole Vibrations: The Analytic Quadrupole Octupole Axially Symmetric Model

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

Bonatsos, Dennis; Lenis, D.; Petrellis, D.

An analytic collective model in which the relative presence of the quadrupole and octupole deformations is determined by a parameter ({phi}0), while axial symmetry is obeyed, is developed. The model [to be called the Analytic Quadrupole Octupole Axially symmetric model (AQOA)] involves an infinite well potential, provides predictions for energy and B(EL) ratios which depend only on {phi}0, draws the border between the regions of octupole deformation and octupole vibrations in an essentially parameter-independent way, and in the actinide region describes well 226Th and 226Ra, for which experimental energy data are shown to suggest that they lie close to thismore » border. The similarity of the AQOA results with {phi}0 = 45 deg. for ground state band spectra and B(E2) transition rates to the predictions of the X(5) model is pointed out.« less

Winds from T Tauri stars. I - Spherically symmetric models

NASA Technical Reports Server (NTRS)

Hartmann, Lee; Avrett, Eugene H.; Loeser, Rudolf; Calvet, Nuria

1990-01-01

Line fluxes and profiles are computed for a sequence of spherically symmetric T Tauri wind models. The calculations indicate that the H-alpha emission of T Tauri stars arises in an extended and probably turbulent circumstellar envelope at temperatures above about 8000 K. The models predict that Mg II resonance line emission should be strongly correlated with H-alpha fluxes; observed Mg II/H-alpha ratios are inconsistent with the models unless extinction corrections have been underestimated. The models predict that most of the Ca II resonance line and IR triplet emission arises in dense layers close to the star rather than in the wind. H-alpha emission levels suggest mass loss rates of about 10 to the -8th solar mass/yr for most T Tauri stars, in reasonable agreement with independent analysis of forbidden emission lines. These results should be useful for interpreting observed line profiles in terms of wind densities, temperatures, and velocity fields.

Specimen-specific modeling of hip fracture pattern and repair.

PubMed

Ali, Azhar A; Cristofolini, Luca; Schileo, Enrico; Hu, Haixiang; Taddei, Fulvia; Kim, Raymond H; Rullkoetter, Paul J; Laz, Peter J

2014-01-22

Hip fracture remains a major health problem for the elderly. Clinical studies have assessed fracture risk based on bone quality in the aging population and cadaveric testing has quantified bone strength and fracture loads. Prior modeling has primarily focused on quantifying the strain distribution in bone as an indicator of fracture risk. Recent advances in the extended finite element method (XFEM) enable prediction of the initiation and propagation of cracks without requiring a priori knowledge of the crack path. Accordingly, the objectives of this study were to predict femoral fracture in specimen-specific models using the XFEM approach, to perform one-to-one comparisons of predicted and in vitro fracture patterns, and to develop a framework to assess the mechanics and load transfer in the fractured femur when it is repaired with an osteosynthesis implant. Five specimen-specific femur models were developed from in vitro experiments under a simulated stance loading condition. Predicted fracture patterns closely matched the in vitro patterns; however, predictions of fracture load differed by approximately 50% due to sensitivity to local material properties. Specimen-specific intertrochanteric fractures were induced by subjecting the femur models to a sideways fall and repaired with a contemporary implant. Under a post-surgical stance loading, model-predicted load sharing between the implant and bone across the fracture surface varied from 59%:41% to 89%:11%, underscoring the importance of considering anatomic and fracture variability in the evaluation of implants. XFEM modeling shows potential as a macro-level analysis enabling fracture investigations of clinical cohorts, including at-risk groups, and the design of robust implants. © 2013 Published by Elsevier Ltd.

Biogeochemical modeling of CO2 and CH4 production in anoxic Arctic soil microcosms

NASA Astrophysics Data System (ADS)

Tang, Guoping; Zheng, Jianqiu; Xu, Xiaofeng; Yang, Ziming; Graham, David E.; Gu, Baohua; Painter, Scott L.; Thornton, Peter E.

2016-09-01

Soil organic carbon turnover to CO2 and CH4 is sensitive to soil redox potential and pH conditions. However, land surface models do not consider redox and pH in the aqueous phase explicitly, thereby limiting their use for making predictions in anoxic environments. Using recent data from incubations of Arctic soils, we extend the Community Land Model with coupled carbon and nitrogen (CLM-CN) decomposition cascade to include simple organic substrate turnover, fermentation, Fe(III) reduction, and methanogenesis reactions, and assess the efficacy of various temperature and pH response functions. Incorporating the Windermere Humic Aqueous Model (WHAM) enables us to approximately describe the observed pH evolution without additional parameterization. Although Fe(III) reduction is normally assumed to compete with methanogenesis, the model predicts that Fe(III) reduction raises the pH from acidic to neutral, thereby reducing environmental stress to methanogens and accelerating methane production when substrates are not limiting. The equilibrium speciation predicts a substantial increase in CO2 solubility as pH increases, and taking into account CO2 adsorption to surface sites of metal oxides further decreases the predicted headspace gas-phase fraction at low pH. Without adequate representation of these speciation reactions, as well as the impacts of pH, temperature, and pressure, the CO2 production from closed microcosms can be substantially underestimated based on headspace CO2 measurements only. Our results demonstrate the efficacy of geochemical models for simulating soil biogeochemistry and provide predictive understanding and mechanistic representations that can be incorporated into land surface models to improve climate predictions.

Gravitational effects on global hemodynamics in different postures: A closed-loop multiscale mathematical analysis

NASA Astrophysics Data System (ADS)

Zhang, Xiancheng; Noda, Shigeho; Himeno, Ryutaro; Liu, Hao

2017-06-01

We present a novel methodology and strategy to predict pressures and flow rates in the global cardiovascular network in different postures varying from supine to upright. A closed-loop, multiscale mathematical model of the entire cardiovascular system (CVS) is developed through an integration of one-dimensional (1D) modeling of the large systemic arteries and veins, and zero-dimensional (0D) lumped-parameter modeling of the heart, the cardiac-pulmonary circulation, the cardiac and venous valves, as well as the microcirculation. A versatile junction model is proposed and incorporated into the 1D model to cope with splitting and/or merging flows across a multibranched junction, which is validated to be capable of estimating both subcritical and supercritical flows while ensuring the mass conservation and total pressure continuity. To model gravitational effects on global hemodynamics during postural change, a robust venous valve model is further established for the 1D venous flows and distributed throughout the entire venous network with consideration of its anatomically realistic numbers and locations. The present integrated model is proven to enable reasonable prediction of pressure and flow rate waveforms associated with cardiopulmonary circulation, systemic circulation in arteries and veins, as well as microcirculation within normal physiological ranges, particularly in mean venous pressures, which well match the in vivo measurements. Applications of the cardiovascular model at different postures demonstrate that gravity exerts remarkable influence on arterial and venous pressures, venous returns and cardiac outputs whereas venous pressures below the heart level show a specific correlation between central venous and hydrostatic pressures in right atrium and veins.

A Closed-Loop Model of Operator Visual Attention, Situation Awareness, and Performance Across Automation Mode Transitions.

PubMed

Johnson, Aaron W; Duda, Kevin R; Sheridan, Thomas B; Oman, Charles M

2017-03-01

This article describes a closed-loop, integrated human-vehicle model designed to help understand the underlying cognitive processes that influenced changes in subject visual attention, mental workload, and situation awareness across control mode transitions in a simulated human-in-the-loop lunar landing experiment. Control mode transitions from autopilot to manual flight may cause total attentional demands to exceed operator capacity. Attentional resources must be reallocated and reprioritized, which can increase the average uncertainty in the operator's estimates of low-priority system states. We define this increase in uncertainty as a reduction in situation awareness. We present a model built upon the optimal control model for state estimation, the crossover model for manual control, and the SEEV (salience, effort, expectancy, value) model for visual attention. We modify the SEEV attention executive to direct visual attention based, in part, on the uncertainty in the operator's estimates of system states. The model was validated using the simulated lunar landing experimental data, demonstrating an average difference in the percentage of attention ≤3.6% for all simulator instruments. The model's predictions of mental workload and situation awareness, measured by task performance and system state uncertainty, also mimicked the experimental data. Our model supports the hypothesis that visual attention is influenced by the uncertainty in system state estimates. Conceptualizing situation awareness around the metric of system state uncertainty is a valuable way for system designers to understand and predict how reallocations in the operator's visual attention during control mode transitions can produce reallocations in situation awareness of certain states.

Modeling and simulation of viscoelastic biological particles' 3D manipulation using atomic force microscopy

NASA Astrophysics Data System (ADS)

Korayem, M. H.; Habibi Sooha, Y.; Rastegar, Z.

2018-05-01

Manipulation of the biological particles by atomic force microscopy is used to transfer these particles inside body's cells, diagnosis and destruction of the cancer cells and drug delivery to damaged cells. According to the impossibility of simultaneous observation of this process, the importance of modeling and simulation can be realized. The contact of the tip with biological particle is important during manipulation, therefore, the first step of the modeling is choosing appropriate contact model. Most of the studies about contact between atomic force microscopy and biological particles, consider the biological particle as an elastic material. This is not an appropriate assumption because biological cells are basically soft and this assumption ignores loading history. In this paper, elastic and viscoelastic JKR theories were used in modeling and simulation of the 3D manipulation for three modes of tip-particle sliding, particle-substrate sliding and particle-substrate rolling. Results showed that critical force and time in motion modes (sliding and rolling) for two elastic and viscoelastic states are very close but these magnitudes were lower in the viscoelastic state. Then, three friction models, Coulomb, LuGre and HK, were used for tip-particle sliding mode in the first phase of manipulation to make results closer to reality. In both Coulomb and LuGre models, critical force and time are very close for elastic and viscoelastic states but in general critical force and time prediction of HK model was higher than LuGre and the LuGre model itself had higher prediction than Coulomb.

A three-pathway pore model describes extensive transport data from Mammalian microvascular beds and frog microvessels.

PubMed

Wolf, Matthew B

2002-12-01

To show that a three-pathway pore model can describe extensive transport data in cat and rat skeletal muscle microvascular beds and in frog mesenteric microvessels. A three-pathway pore model was used to predict transport data measured in various microcirculatory preparations. The pathways consist of 4- and 24-nm radii pore systems with a 2.5:1 ratio of hydraulic conductivities and a water-only pathway of variable conductivity. The pore sizes and relative hydraulic conductivities of the small- and large-pore systems were derived from a model fit to reflection coefficient (sigma) data in the cat hindlimb. The fraction (alpha(w)) of total hydraulic conductivity (L(p)) or hydraulic capacity (L(p)S) contributed by the water-only pathway was uniquely determined for each preparation by a fit of the three-pathway model (parameters fixed as above) to sigma data measured in that preparation. These parameter values were unchanged when the model was used to predict diffusion capacity (permeability-surface area product, P(d)S) data in the cat or rat preparations or diffusional permeability (P(d)) data in frog microvessels. The values for L(p) or L(p)S used to predict diffusional data in each preparation were taken from the literature. Predictions of P(d) ratios for solute pairs were also compared with experimental data. The three-pathway model closely predicted the trend of P(d)S or P(d) experimental data in all three preparations; in general, predicted P(d) ratios for paired solutes were quite similar to experimental data. For these comparisons, the only parameter varied between these preparations was alpha(w). It varied considerably, from 7 to 16 to 41% of total in frog, rat, and cat preparations. Individual P(d)S or P(d) experimental data were closely predicted in the cat but somewhat overestimated in the frog and rat. This result could be due the use of L(p) or L(p)S values in the model that were affected by methodological problems. Calculated hydraulic conductivities of the water-only pathway in the three preparations were quite similar. : These results support the hypothesis of a common structure of the transmembrane pathways in these three, very different, microcirculatory preparations. What varies considerably between them is the total number of solute-conducting pathways, but not their dimensions, nor the hydraulic conductivities of their water-only pathways. Because of the wide variation of alpha(w) among these preparations, the ratio of P(d) to L(p) for any solute is not constant, but the deviation from constancy may not be detectable because of errors in the experimental data.

Synergies Between Quantum Mechanics and Machine Learning in Reaction Prediction.

PubMed

Sadowski, Peter; Fooshee, David; Subrahmanya, Niranjan; Baldi, Pierre

2016-11-28

Machine learning (ML) and quantum mechanical (QM) methods can be used in two-way synergy to build chemical reaction expert systems. The proposed ML approach identifies electron sources and sinks among reactants and then ranks all source-sink pairs. This addresses a bottleneck of QM calculations by providing a prioritized list of mechanistic reaction steps. QM modeling can then be used to compute the transition states and activation energies of the top-ranked reactions, providing additional or improved examples of ranked source-sink pairs. Retraining the ML model closes the loop, producing more accurate predictions from a larger training set. The approach is demonstrated in detail using a small set of organic radical reactions.

Automated assessment of imaging biomarkers for the PanCan lung cancer risk prediction model with validation on NLST data

NASA Astrophysics Data System (ADS)

Wiemker, Rafael; Sevenster, Merlijn; MacMahon, Heber; Li, Feng; Dalal, Sandeep; Tahmasebi, Amir; Klinder, Tobias

2017-03-01

The imaging biomarkers EmphysemaPresence and NoduleSpiculation are crucial inputs for most models aiming to predict the risk of indeterminate pulmonary nodules detected at CT screening. To increase reproducibility and to accelerate screening workflow it is desirable to assess these biomarkers automatically. Validation on NLST images indicates that standard histogram measures are not sufficient to assess EmphysemaPresence in screenees. However, automatic scoring of bulla-resembling low attenuation areas can achieve agreement with experts with close to 80% sensitivity and specificity. NoduleSpiculation can be automatically assessed with similar accuracy. We find a dedicated spiculi tracing score to slightly outperform generic combinations of texture features with classifiers.

Puffing flame instability - Part II: Predicting the onset and frequency

NASA Astrophysics Data System (ADS)

Boettcher, Philipp; Shepherd, Joseph; Menon, Shyam; Blanquart, Guillaume

2011-11-01

Experiments and simulations have been performed on fuel rich n- hexane air mixtures in a closed vessel. Both experiments and simulations show a distinct cyclic combustion or ``puffing'' mode. The misalignment of buoyancy induced pressure gradients and density gradients across the flame front is responsible for the generation of vorticity and its subsequent roll-up into vortex rings. In the present work, a simplified model is proposed based on the fundamental interactions between fluid mechanical and chemical parameters. This simplified fluid mechanics model is based on dimensional analysis and is used to predict the onset and frequency of the puffing behavior. This work was sponsored by The Boeing Company through CTBA-GTA-1.

Antihydrogen-hydrogen elastic scattering at thermal energies using an atomic-orbital technique

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

Sinha, Prabal K.; Chaudhuri, Puspitapallab; Ghosh, A.S.

2003-05-01

In view of the recent interest in the trapping of antihydrogen atom H(bar sign), at very low temperatures, H-bar-H scattering has been investigated at low incident energies using a close-coupling model with the basis set H-bar(1s,2s,2p-bar)+H(1s,2s,2p-bar). The predicted s-wave elastic phase shifts, scattering length, and effective range are in a good agreement with the other recent predictions of Jonsell et al. and of Armour and Chamberlain. The results indicate that the atomic orbital expansion model is suitable to study the H-bar-H scattering at ultracold temperatures.

Dynamic performance analysis of permanent magnet contactor with a flux-weakening control strategy

NASA Astrophysics Data System (ADS)

Wang, Xianbing; Lin, Heyun; Fang, Shuhua; Jin, Ping; Wang, Junhua; Ho, S. L.

2011-04-01

A new flux-weakening control strategy for permanent magnet contactors is proposed. By matching the dynamic attraction force and the antiforce, the terminal velocity and collision energy of the movable iron in the closing process are significantly reduced. The movable iron displacement is estimated by detecting the closing voltage and current with the proposed control. A dynamic mathematical model is also established under four kinds of excitation scenarios. The attraction force and flux linkage are predicted by finite element method and the dynamics of the closing process is simulated using the 4th-order Runge-Kutta algorithm. Experiments are carried out on a 250A prototype with an intelligent control unit to verify the proposed control strategy.

Online EEG-Based Workload Adaptation of an Arithmetic Learning Environment.

PubMed

Walter, Carina; Rosenstiel, Wolfgang; Bogdan, Martin; Gerjets, Peter; Spüler, Martin

2017-01-01

In this paper, we demonstrate a closed-loop EEG-based learning environment, that adapts instructional learning material online, to improve learning success in students during arithmetic learning. The amount of cognitive workload during learning is crucial for successful learning and should be held in the optimal range for each learner. Based on EEG data from 10 subjects, we created a prediction model that estimates the learner's workload to obtain an unobtrusive workload measure. Furthermore, we developed an interactive learning environment that uses the prediction model to estimate the learner's workload online based on the EEG data and adapt the difficulty of the learning material to keep the learner's workload in an optimal range. The EEG-based learning environment was used by 13 subjects to learn arithmetic addition in the octal number system, leading to a significant learning effect. The results suggest that it is feasible to use EEG as an unobtrusive measure of cognitive workload to adapt the learning content. Further it demonstrates that a promptly workload prediction is possible using a generalized prediction model without the need for a user-specific calibration.

[The value of 5-HTT gene polymorphism for the assessment and prediction of male adolescence violence].

PubMed

Yu, Yue; Liu, Xiang; Yang, Zhen-xing; Qiu, Chang-jian; Ma, Xiao-hong

2012-08-01

To establish an adolescent violence crime prediction model, and to assess the value of serotonin transporter (5-HTT) gene polymorphism for the assessment and prediction of violent crime. Investigative tools were used to analyze the difference in personality dimensions, social support, coping styles, aggressiveness, impulsivity, and family condition scale between 223 adolescents with violence behavior and 148 adolescents without violence behavior. The distribution of 5-HTT gene polymorphisms (5-HTTLPR and 5-HTTVNTR) was compared between the two groups. The role of 5-HTT gene polymorphism on adolescent personality, impulsion and aggression scale also was also analyzed. Stepwise logistic regression was used to establish a predictive model for adolescent violent crime. Significant difference was found between the violence group and the control group on multiple dimensions of psychology and environment scales. However, no statistical difference was found with regard to the 5-HTT genotypes and alleles between adolescents with violent behaviors and normal controls. The rate of prediction accuracy was not significantly improved when 5-HTT gene polymorphism was taken into the model. The violent crime of adolescents was closely related with social and environmental factors. No association was found between 5-HTT polymorphisms and adolescent violence criminal behavior.

Numerical modeling analysis of the mesoscale environment conducive to two tornado events using the COSMO.Gr model over Greece

NASA Astrophysics Data System (ADS)

Avgoustoglou, E.; Matsangouras, I. T.; Pytharoulis, I.; Kamperakis, N.; Mylonas, M.; Nastos, P. T.; Bluestein, H. W.

2018-08-01

The COnsortium for Small-scale MOdeling (COSMO) was formed in October 1998, and its general goal is to develop, improve and maintain a non-hydrostatic limited-area atmospheric model. The COSMO model has been designed both for operational numerical weather prediction (NWP) as well as various scientific applications on the meso-β and meso-γ scale. Two tornado case studies were selected to investigate the ability of COSMO model to depict the characteristics of severe convective weather, which favoured the development of the associated storms. The first tornado (TR01) occurred, close to Ag. Ilias village, 8 Km north-western of Aitoliko city over western Greece on February 7, 2013, while the second tornado (TR02) was developed close to Palio Katramio village, 8 Km southern from Xanthi city over northern Greece on November 25, 2015. Although both tornadoes had a short lifetime, they caused significant damages. The COSMO.GR atmospheric model was initialized with analysis from the European Centre for Medium-Range Weather Forecasts (ECMWF). The resulting numerical products with spatial resolution of 0.02° (∼ 2 km) over the geographical domain of Greece depicted very well the severe convective conditions close to tornadoes formation. The Energy Helicity Index (EHI) diagnostic variable in both numerical simulations showed a gradual increase of values closing to the location and time of the tornadogenesis. Similar to EHI, the storm relative helicity (SRH) spatio-temporal analysis followed a gradual increase prior to the tornadogenesis events and was reduced after them.

Improved prediction of biochemical recurrence after radical prostatectomy by genetic polymorphisms.

PubMed

Morote, Juan; Del Amo, Jokin; Borque, Angel; Ars, Elisabet; Hernández, Carlos; Herranz, Felipe; Arruza, Antonio; Llarena, Roberto; Planas, Jacques; Viso, María J; Palou, Joan; Raventós, Carles X; Tejedor, Diego; Artieda, Marta; Simón, Laureano; Martínez, Antonio; Rioja, Luis A

2010-08-01

Single nucleotide polymorphisms are inherited genetic variations that can predispose or protect individuals against clinical events. We hypothesized that single nucleotide polymorphism profiling may improve the prediction of biochemical recurrence after radical prostatectomy. We performed a retrospective, multi-institutional study of 703 patients treated with radical prostatectomy for clinically localized prostate cancer who had at least 5 years of followup after surgery. All patients were genotyped for 83 prostate cancer related single nucleotide polymorphisms using a low density oligonucleotide microarray. Baseline clinicopathological variables and single nucleotide polymorphisms were analyzed to predict biochemical recurrence within 5 years using stepwise logistic regression. Discrimination was measured by ROC curve AUC, specificity, sensitivity, predictive values, net reclassification improvement and integrated discrimination index. The overall biochemical recurrence rate was 35%. The model with the best fit combined 8 covariates, including the 5 clinicopathological variables prostate specific antigen, Gleason score, pathological stage, lymph node involvement and margin status, and 3 single nucleotide polymorphisms at the KLK2, SULT1A1 and TLR4 genes. Model predictive power was defined by 80% positive predictive value, 74% negative predictive value and an AUC of 0.78. The model based on clinicopathological variables plus single nucleotide polymorphisms showed significant improvement over the model without single nucleotide polymorphisms, as indicated by 23.3% net reclassification improvement (p = 0.003), integrated discrimination index (p <0.001) and likelihood ratio test (p <0.001). Internal validation proved model robustness (bootstrap corrected AUC 0.78, range 0.74 to 0.82). The calibration plot showed close agreement between biochemical recurrence observed and predicted probabilities. Predicting biochemical recurrence after radical prostatectomy based on clinicopathological data can be significantly improved by including patient genetic information. Copyright (c) 2010 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

An evaluation of the predictive capabilities of CTRW and MRMT

NASA Astrophysics Data System (ADS)

Fiori, Aldo; Zarlenga, Antonio; Gotovac, Hrvoje; Jankovic, Igor; Cvetkovic, Vladimir; Dagan, Gedeon

2016-04-01

The prediction capability of two approximate models of non-Fickian transport in highly heterogeneous aquifers is checked by comparison with accurate numerical simulations, for mean uniform flow of velocity U. The two models considered are the MRMT (Multi Rate Mass Transfer) and CTRW (Continuous Time Random Walk) models. Both circumvent the need to solve the flow and transport equations by using proxy models, which provide the BTC μ(x,t) depending on a vector a of unknown 5 parameters. Although underlain by different conceptualisations, the two models have a similar mathematical structure. The proponents of the models suggest using field transport experiments at a small scale to calibrate a, toward predicting transport at larger scale. The strategy was tested with the aid of accurate numerical simulations in two and three dimensions from the literature. First, the 5 parameter values were calibrated by using the simulated μ at a control plane close to the injection one and subsequently using these same parameters for predicting μ at further 10 control planes. It is found that the two methods perform equally well, though the parameters identification is nonunique, with a large set of parameters providing similar fitting. Also, errors in the determination of the mean eulerian velocity may lead to significant shifts of the predicted BTC. It is found that the simulated BTCs satisfy Markovianity: they can be found as n-fold convolutions of a "kernel", in line with the models' main assumption.

The interplanetary magnetic field B[sub y] effects on large-scale field-aligned currents near local noon: Contributions from cusp part and noncusp part

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

Yamauchi, M.; Lundin, R.; Woch, J.

1993-04-01

latitudinals develop a model to account for the effect of the interplanetary magnetic field (IMF) B[sub y] component on the dayside field-aligned currents (FACs). As part of the model the FACs are divided into a [open quotes]cusp part[close quotes] and a [open quotes]noncusp part[close quotes]. The authors then propose that the cusp part FACs shift in the longitudinal direction while the noncusplike part FACs shift in both longitudinal and latitudinal directions in response to the y component of the IMF. If combined, it is observed that the noncusp part FAC is found poleward of the cusp part FAC system whenmore » the y component of the IMF is large. These two FAC systems flow in the same direction. They reinforce one another, creating a strong FAC, termed the DPY-FAC. The model also predicts that the polewardmost part of the DPY-FAC flows on closed field lines, even in regions conventionally occupied by the polar cap. Results of the model are successfully compared with particle and magnetic field data from Viking missions.« less

Home-Based Risk of Falling Assessment Test Using a Closed-Loop Balance Model.

PubMed

Ayena, Johannes C; Zaibi, Helmi; Otis, Martin J-D; Menelas, Bob-Antoine J

2016-12-01

The aim of this study is to improve and facilitate the methods used to assess risk of falling at home among older people through the computation of a risk of falling in real time in daily activities. In order to increase a real time computation of the risk of falling, a closed-loop balance model is proposed and compared with One-Leg Standing Test (OLST). This balance model allows studying the postural response of a person having an unpredictable perturbation. Twenty-nine volunteers participated in this study for evaluating the effectiveness of the proposed system which includes seventeen elder participants: ten healthy elderly ( 68.4 ±5.5 years), seven Parkinson's disease (PD) subjects ( 66.28 ±8.9 years), and twelve healthy young adults ( 28.27 ±3.74 years). Our work suggests that there is a relationship between OLST score and the risk of falling based on center of pressure measurement with four low cost force sensors located inside an instrumented insole, which could be predicted using our suggested closed-loop balance model. For long term monitoring at home, this system could be included in a medical electronic record and could be useful as a diagnostic aid tool.

Forecasting cyanobacteria dominance in Canadian temperate lakes.

PubMed

Persaud, Anurani D; Paterson, Andrew M; Dillon, Peter J; Winter, Jennifer G; Palmer, Michelle; Somers, Keith M

2015-03-15

Predictive models based on broad scale, spatial surveys typically identify nutrients and climate as the most important predictors of cyanobacteria abundance; however these models generally have low predictive power because at smaller geographic scales numerous other factors may be equally or more important. At the lake level, for example, the ability to forecast cyanobacteria dominance is of tremendous value to lake managers as they can use such models to communicate exposure risks associated with recreational and drinking water use, and possible exposure to algal toxins, in advance of bloom occurrence. We used detailed algal, limnological and meteorological data from two temperate lakes in south-central Ontario, Canada to determine the factors that are closely linked to cyanobacteria dominance, and to develop easy to use models to forecast cyanobacteria biovolume. For Brandy Lake (BL), the strongest and most parsimonious model for forecasting % cyanobacteria biovolume (% CB) included water column stability, hypolimnetic TP, and % cyanobacteria biovolume two weeks prior. For Three Mile Lake (TML), the best model for forecasting % CB included water column stability, hypolimnetic TP concentration, and 7-d mean wind speed. The models for forecasting % CB in BL and TML are fundamentally different in their lag periods (BL = lag 1 model and TML = lag 2 model) and in some predictor variables despite the close proximity of the study lakes. We speculate that three main factors (nutrient concentrations, water transparency and lake morphometry) may have contributed to differences in the models developed, and may account for variation observed in models derived from large spatial surveys. Our results illustrate that while forecast models can be developed to determine when cyanobacteria will dominate within two temperate lakes, the models require detailed, lake-specific calibration to be effective as risk-management tools. Copyright © 2015 Elsevier Ltd. All rights reserved.

Forecasting mortality of road traffic injuries in China using seasonal autoregressive integrated moving average model.

PubMed

Zhang, Xujun; Pang, Yuanyuan; Cui, Mengjing; Stallones, Lorann; Xiang, Huiyun

2015-02-01

Road traffic injuries have become a major public health problem in China. This study aimed to develop statistical models for predicting road traffic deaths and to analyze seasonality of deaths in China. A seasonal autoregressive integrated moving average (SARIMA) model was used to fit the data from 2000 to 2011. Akaike Information Criterion, Bayesian Information Criterion, and mean absolute percentage error were used to evaluate the constructed models. Autocorrelation function and partial autocorrelation function of residuals and Ljung-Box test were used to compare the goodness-of-fit between the different models. The SARIMA model was used to forecast monthly road traffic deaths in 2012. The seasonal pattern of road traffic mortality data was statistically significant in China. SARIMA (1, 1, 1) (0, 1, 1)12 model was the best fitting model among various candidate models; the Akaike Information Criterion, Bayesian Information Criterion, and mean absolute percentage error were -483.679, -475.053, and 4.937, respectively. Goodness-of-fit testing showed nonautocorrelations in the residuals of the model (Ljung-Box test, Q = 4.86, P = .993). The fitted deaths using the SARIMA (1, 1, 1) (0, 1, 1)12 model for years 2000 to 2011 closely followed the observed number of road traffic deaths for the same years. The predicted and observed deaths were also very close for 2012. This study suggests that accurate forecasting of road traffic death incidence is possible using SARIMA model. The SARIMA model applied to historical road traffic deaths data could provide important evidence of burden of road traffic injuries in China. Copyright © 2015 Elsevier Inc. All rights reserved.

Towards predictive models for transitionally rough surfaces

NASA Astrophysics Data System (ADS)

Abderrahaman-Elena, Nabil; Garcia-Mayoral, Ricardo

2017-11-01

We analyze and model the previously presented decomposition for flow variables in DNS of turbulence over transitionally rough surfaces. The flow is decomposed into two contributions: one produced by the overlying turbulence, which has no footprint of the surface texture, and one induced by the roughness, which is essentially the time-averaged flow around the surface obstacles, but modulated in amplitude by the first component. The roughness-induced component closely resembles the laminar steady flow around the roughness elements at the same non-dimensional roughness size. For small - yet transitionally rough - textures, the roughness-free component is essentially the same as over a smooth wall. Based on these findings, we propose predictive models for the onset of the transitionally rough regime. Project supported by the Engineering and Physical Sciences Research Council (EPSRC).

Robust distributed model predictive control of linear systems with structured time-varying uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Langwen; Xie, Wei; Wang, Jingcheng

2017-11-01

In this work, synthesis of robust distributed model predictive control (MPC) is presented for a class of linear systems subject to structured time-varying uncertainties. By decomposing a global system into smaller dimensional subsystems, a set of distributed MPC controllers, instead of a centralised controller, are designed. To ensure the robust stability of the closed-loop system with respect to model uncertainties, distributed state feedback laws are obtained by solving a min-max optimisation problem. The design of robust distributed MPC is then transformed into solving a minimisation optimisation problem with linear matrix inequality constraints. An iterative online algorithm with adjustable maximum iteration is proposed to coordinate the distributed controllers to achieve a global performance. The simulation results show the effectiveness of the proposed robust distributed MPC algorithm.

Damage Simulation in Non-Crimp Fabric Composite Plates Subjected to Impact Loads

NASA Technical Reports Server (NTRS)

Satyanarayana, Arunkumar; Bogert, Philip B.; Aitharaju, Venkat; Aashat, Satvir; Kia, Hamid

2014-01-01

Progressive failure analysis (PFA) of non-crimp fabric (NCF) composite laminates subjected to low velocity impact loads was performed using the COmplete STress Reduction (COSTR) damage model implemented through VUMAT and UMAT41 user subroutines in the frame works of the commercial finite element programs ABAQUS/Explicit and LS-DYNA, respectively. To validate the model, low velocity experiments were conducted and detailed correlations between the predictions and measurements for both intra-laminar and inter-laminar failures were made. The developed material and damage model predicts the peak impact load and duration very close with the experimental results. Also, the simulation results of delamination damage between the ply interfaces, in-plane matrix damages and fiber damages were all in good agreement with the measurements from the non-destructive evaluation data.

Yarkovsky-driven Impact Predictions: Apophis and 1950 DA

NASA Astrophysics Data System (ADS)

Farnocchia, Davide; Chesley, S. R.; Chodas, P.; Milani, A.

2013-05-01

Abstract (2,250 Maximum Characters): Orbit determination for Near-Earth Asteroids presents unique technical challenges due to the imperative of early detection and careful assessment of the risk posed by specific Earth close approaches. The occurrence of an Earth impact can be decisively driven by the Yarkovsky effect, which is the most important nongravitational perturbation as it causes asteroids to undergo a secular variation in semimajor axis resulting in a quadratic effect in anomaly. We discuss the cases of (99942) Apophis and (29075) 1950 DA. The relevance of the Yarkovsky effect for Apophis is due to a scattering close approach in 2029 with minimum geocentric distance ~38000 km. For 1950 DA the influence of the Yarkovsky effect in 2880 is due to the long time interval preceding the impact. We use the available information on the asteroids' physical models as a starting point for a Monte Carlo method that allow us to measure how the Yarkovsky effect affects orbital predictions. For Apophis we map onto the 2029 close approach b-plane and analyze the keyholes corresponding to resonant close approaches. For 1950 DA we use the b-plane corresponding to the possible impact in 2880. We finally compute the impact probability from the mapped probability density function on the considered b-plane.

Investigation of energy transport in DIII-D high- β P EAST-demonstration discharges with the TGLF turbulent and NEO neoclassical transport models [Investigation of energy transport in DIII-D high- β P EAST-demonstration discharges with turbulent and neoclassical transport models

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

Pan, Chengkang; Staebler, Gary M.; Lao, Lang L.

Here, energy transport analyses of DIII-D high-β P EAST-demonstration discharges have been performed using the TGYRO transport package with TGLF turbulent and NEO neoclassical transport models under the OMFIT integrated modeling framework. Ion energy transport is shown to be dominated by neoclassical transport and ion temperature profiles predicted by TGYRO agree closely with the experimental measured profiles for these high-β P discharges. Ion energy transport is largely insensitive to reductions in the E × B flow shear stabilization. The Shafranov shift is shown to play a role in the suppression of the ion turbulent energy transport below the neoclassical level.more » Electron turbulent energy transport is under-predicted by TGLF and a significant shortfall in the electron energy transport over the whole core plasma is found with TGLF predictions for these high-β P discharges. TGYRO can successfully predict the experimental ion and electron temperature profiles by artificially increasing the saturated turbulence level for ETG driven modes used in TGLF.« less

Estimation of the viscosities of liquid binary alloys

NASA Astrophysics Data System (ADS)

Wu, Min; Su, Xiang-Yu

2018-01-01

As one of the most important physical and chemical properties, viscosity plays a critical role in physics and materials as a key parameter to quantitatively understanding the fluid transport process and reaction kinetics in metallurgical process design. Experimental and theoretical studies on liquid metals are problematic. Today, there are many empirical and semi-empirical models available with which to evaluate the viscosity of liquid metals and alloys. However, the parameter of mixed energy in these models is not easily determined, and most predictive models have been poorly applied. In the present study, a new thermodynamic parameter Δ G is proposed to predict liquid alloy viscosity. The prediction equation depends on basic physical and thermodynamic parameters, namely density, melting temperature, absolute atomic mass, electro-negativity, electron density, molar volume, Pauling radius, and mixing enthalpy. Our results show that the liquid alloy viscosity predicted using the proposed model is closely in line with the experimental values. In addition, if the component radius difference is greater than 0.03 nm at a certain temperature, the atomic size factor has a significant effect on the interaction of the binary liquid metal atoms. The proposed thermodynamic parameter Δ G also facilitates the study of other physical properties of liquid metals.

Investigation of energy transport in DIII-D high- β P EAST-demonstration discharges with the TGLF turbulent and NEO neoclassical transport models [Investigation of energy transport in DIII-D high- β P EAST-demonstration discharges with turbulent and neoclassical transport models

DOE PAGES

Pan, Chengkang; Staebler, Gary M.; Lao, Lang L.; ...

2017-01-11

Here, energy transport analyses of DIII-D high-β P EAST-demonstration discharges have been performed using the TGYRO transport package with TGLF turbulent and NEO neoclassical transport models under the OMFIT integrated modeling framework. Ion energy transport is shown to be dominated by neoclassical transport and ion temperature profiles predicted by TGYRO agree closely with the experimental measured profiles for these high-β P discharges. Ion energy transport is largely insensitive to reductions in the E × B flow shear stabilization. The Shafranov shift is shown to play a role in the suppression of the ion turbulent energy transport below the neoclassical level.more » Electron turbulent energy transport is under-predicted by TGLF and a significant shortfall in the electron energy transport over the whole core plasma is found with TGLF predictions for these high-β P discharges. TGYRO can successfully predict the experimental ion and electron temperature profiles by artificially increasing the saturated turbulence level for ETG driven modes used in TGLF.« less

Accurate SHAPE-directed RNA secondary structure modeling, including pseudoknots.

PubMed

Hajdin, Christine E; Bellaousov, Stanislav; Huggins, Wayne; Leonard, Christopher W; Mathews, David H; Weeks, Kevin M

2013-04-02

A pseudoknot forms in an RNA when nucleotides in a loop pair with a region outside the helices that close the loop. Pseudoknots occur relatively rarely in RNA but are highly overrepresented in functionally critical motifs in large catalytic RNAs, in riboswitches, and in regulatory elements of viruses. Pseudoknots are usually excluded from RNA structure prediction algorithms. When included, these pairings are difficult to model accurately, especially in large RNAs, because allowing this structure dramatically increases the number of possible incorrect folds and because it is difficult to search the fold space for an optimal structure. We have developed a concise secondary structure modeling approach that combines SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension) experimental chemical probing information and a simple, but robust, energy model for the entropic cost of single pseudoknot formation. Structures are predicted with iterative refinement, using a dynamic programming algorithm. This melded experimental and thermodynamic energy function predicted the secondary structures and the pseudoknots for a set of 21 challenging RNAs of known structure ranging in size from 34 to 530 nt. On average, 93% of known base pairs were predicted, and all pseudoknots in well-folded RNAs were identified.

Chemical kinetic modeling of propene oxidation at low and intermediate temperatures

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

Wilk, R.D.; Cernansky, N.P.; Pitz, W.J.

1986-01-13

A detailed chemical kinetic mechanism for propene oxidation is developed and used to model reactions in a static reactor at temperatures of 590 to 740/sup 0/K, equivalence ratios of 0.8 to 2.0, and a pressure of 600 torr. Modeling of hydrocarbon oxidation in this temperature range is important for the validation of detailed models to be used for performing calculations related to automotive engine knock. The model predicted induction periods and species concentrations for all the species measured experimentally in a static reactor by Wilk, Cernansky, and Cohen. The detailed model predicted a temperature region of approximately constant induction periodmore » which corresponded very closely to the region of negative temperature coefficient behavior found in the experiment. Overall, the calculated concentrations of acetaldehyde, ethene, and methane were somewhat low compared to the experimental measurements, and the calculated concentrations of formaldehyde and methanol were high. The characteristic s-shape of the fuel concentration history was well predicted. The importance of OH+C/sub 3/H/sub 6/ and related rections in determining product distributions and the importance of consumption reactions for allyl radicals was demonstrated by the modeling calculations. 18 refs., 4 figs., 1 tab.« less

Blind prediction of natural video quality.

PubMed

Saad, Michele A; Bovik, Alan C; Charrier, Christophe

2014-03-01

We propose a blind (no reference or NR) video quality evaluation model that is nondistortion specific. The approach relies on a spatio-temporal model of video scenes in the discrete cosine transform domain, and on a model that characterizes the type of motion occurring in the scenes, to predict video quality. We use the models to define video statistics and perceptual features that are the basis of a video quality assessment (VQA) algorithm that does not require the presence of a pristine video to compare against in order to predict a perceptual quality score. The contributions of this paper are threefold. 1) We propose a spatio-temporal natural scene statistics (NSS) model for videos. 2) We propose a motion model that quantifies motion coherency in video scenes. 3) We show that the proposed NSS and motion coherency models are appropriate for quality assessment of videos, and we utilize them to design a blind VQA algorithm that correlates highly with human judgments of quality. The proposed algorithm, called video BLIINDS, is tested on the LIVE VQA database and on the EPFL-PoliMi video database and shown to perform close to the level of top performing reduced and full reference VQA algorithms.

Suprathermal Electrons in the Solar Corona: Can Nonlocal Transport Explain Heliospheric Charge States?

NASA Astrophysics Data System (ADS)

Cranmer, Steven R.

2014-08-01

There have been several ideas proposed to explain how the Sun's corona is heated and how the solar wind is accelerated. Some models assume that open magnetic field lines are heated by Alfvén waves driven by photospheric motions and dissipated after undergoing a turbulent cascade. Other models posit that much of the solar wind's mass and energy is injected via magnetic reconnection from closed coronal loops. The latter idea is motivated by observations of reconnecting jets and also by similarities of ion composition between closed loops and the slow wind. Wave/turbulence models have also succeeded in reproducing observed trends in ion composition signatures versus wind speed. However, the absolute values of the charge-state ratios predicted by those models tended to be too low in comparison with observations. This Letter refines these predictions by taking better account of weak Coulomb collisions for coronal electrons, whose thermodynamic properties determine the ion charge states in the low corona. A perturbative description of nonlocal electron transport is applied to an existing set of wave/turbulence models. The resulting electron velocity distributions in the low corona exhibit mild suprathermal tails characterized by "kappa" exponents between 10 and 25. These suprathermal electrons are found to be sufficiently energetic to enhance the charge states of oxygen ions, while maintaining the same relative trend with wind speed that was found when the distribution was assumed to be Maxwellian. The updated wave/turbulence models are in excellent agreement with solar wind ion composition measurements.

Brayton Power Conversion System Parametric Design Modelling for Nuclear Electric Propulsion

NASA Technical Reports Server (NTRS)

Ashe, Thomas L.; Otting, William D.

1993-01-01

The parametrically based closed Brayton cycle (CBC) computer design model was developed for inclusion into the NASA LeRC overall Nuclear Electric Propulsion (NEP) end-to-end systems model. The code is intended to provide greater depth to the NEP system modeling which is required to more accurately predict the impact of specific technology on system performance. The CBC model is parametrically based to allow for conducting detailed optimization studies and to provide for easy integration into an overall optimizer driver routine. The power conversion model includes the modeling of the turbines, alternators, compressors, ducting, and heat exchangers (hot-side heat exchanger and recuperator). The code predicts performance to significant detail. The system characteristics determined include estimates of mass, efficiency, and the characteristic dimensions of the major power conversion system components. These characteristics are parametrically modeled as a function of input parameters such as the aerodynamic configuration (axial or radial), turbine inlet temperature, cycle temperature ratio, power level, lifetime, materials, and redundancy.

Evaluation of theoretical and empirical water vapor sorption isotherm models for soils

NASA Astrophysics Data System (ADS)

Arthur, Emmanuel; Tuller, Markus; Moldrup, Per; de Jonge, Lis W.

2016-01-01

The mathematical characterization of water vapor sorption isotherms of soils is crucial for modeling processes such as volatilization of pesticides and diffusive and convective water vapor transport. Although numerous physically based and empirical models were previously proposed to describe sorption isotherms of building materials, food, and other industrial products, knowledge about the applicability of these functions for soils is noticeably lacking. We present an evaluation of nine models for characterizing adsorption/desorption isotherms for a water activity range from 0.03 to 0.93 based on measured data of 207 soils with widely varying textures, organic carbon contents, and clay mineralogy. In addition, the potential applicability of the models for prediction of sorption isotherms from known clay content was investigated. While in general, all investigated models described measured adsorption and desorption isotherms reasonably well, distinct differences were observed between physical and empirical models and due to the different degrees of freedom of the model equations. There were also considerable differences in model performance for adsorption and desorption data. While regression analysis relating model parameters and clay content and subsequent model application for prediction of measured isotherms showed promise for the majority of investigated soils, for soils with distinct kaolinitic and smectitic clay mineralogy predicted isotherms did not closely match the measurements.

Analysis and Validation of a Predictive Model for Growth and Death of Aeromonas hydrophila under Modified Atmospheres at Refrigeration Temperatures

PubMed Central

Pin, Carmen; Velasco de Diego, Raquel; George, Susan; García de Fernando, Gonzalo D.; Baranyi, József

2004-01-01

Specific growth and death rates of Aeromonas hydrophila were measured in laboratory media under various combinations of temperature, pH, and percent CO2 and O2 in the atmosphere. Predictive models were developed from the data and validated by means of observations obtained from (i) seafood experiments set up for this purpose and (ii) the ComBase database (http://www.combase.cc; http://wyndmoor.arserrc.gov/combase/).Two main reasons were identified for the differences between the predicted and observed growth in food: they were the variability of the growth rates in food and the bias of the model predictions when applied to food environments. A statistical method is presented to quantitatively analyze these differences. The method was also used to extend the interpolation region of the model. In this extension, the concept of generalized Z values (C. Pin, G. García de Fernando, J. A. Ordóñez, and J. Baranyi, Food Microbiol. 18:539-545, 2001) played an important role. The extension depended partly on the density of the model-generating observations and partly on the accuracy of extrapolated predictions close to the boundary of the interpolation region. The boundary of the growth region of the organism was also estimated by means of experimental results for growth and death rates. PMID:15240265