Accurate calculation of conductive conductances in complex geometries for spacecrafts thermal models
NASA Astrophysics Data System (ADS)
Garmendia, Iñaki; Anglada, Eva; Vallejo, Haritz; Seco, Miguel
2016-02-01
The thermal subsystem of spacecrafts and payloads is always designed with the help of Thermal Mathematical Models. In the case of the Thermal Lumped Parameter (TLP) method, the non-linear system of equations that is created is solved to calculate the temperature distribution and the heat power that goes between nodes. The accuracy of the results depends largely on the appropriate calculation of the conductive and radiative conductances. Several established methods for the determination of conductive conductances exist but they present some limitations for complex geometries. Two new methods are proposed in this paper to calculate accurately these conductive conductances: The Extended Far Field method and the Mid-Section method. Both are based on a finite element calculation but while the Extended Far Field method uses the calculation of node mean temperatures, the Mid-Section method is based on assuming specific temperature values. They are compared with traditionally used methods showing the advantages of these two new methods.
Reynolds, Andrew M.; Lihoreau, Mathieu; Chittka, Lars
2013-01-01
Pollinating bees develop foraging circuits (traplines) to visit multiple flowers in a manner that minimizes overall travel distance, a task analogous to the travelling salesman problem. We report on an in-depth exploration of an iterative improvement heuristic model of bumblebee traplining previously found to accurately replicate the establishment of stable routes by bees between flowers distributed over several hectares. The critical test for a model is its predictive power for empirical data for which the model has not been specifically developed, and here the model is shown to be consistent with observations from different research groups made at several spatial scales and using multiple configurations of flowers. We refine the model to account for the spatial search strategy of bees exploring their environment, and test several previously unexplored predictions. We find that the model predicts accurately 1) the increasing propensity of bees to optimize their foraging routes with increasing spatial scale; 2) that bees cannot establish stable optimal traplines for all spatial configurations of rewarding flowers; 3) the observed trade-off between travel distance and prioritization of high-reward sites (with a slight modification of the model); 4) the temporal pattern with which bees acquire approximate solutions to travelling salesman-like problems over several dozen foraging bouts; 5) the instability of visitation schedules in some spatial configurations of flowers; 6) the observation that in some flower arrays, bees' visitation schedules are highly individually different; 7) the searching behaviour that leads to efficient location of flowers and routes between them. Our model constitutes a robust theoretical platform to generate novel hypotheses and refine our understanding about how small-brained insects develop a representation of space and use it to navigate in complex and dynamic environments. PMID:23505353
Zeinali-Rafsanjani, B.; Mosleh-Shirazi, M. A.; Faghihi, R.; Karbasi, S.; Mosalaei, A.
2015-01-01
To accurately recompute dose distributions in chest-wall radiotherapy with 120 kVp kilovoltage X-rays, an MCNP4C Monte Carlo model is presented using a fast method that obviates the need to fully model the tube components. To validate the model, half-value layer (HVL), percentage depth doses (PDDs) and beam profiles were measured. Dose measurements were performed for a more complex situation using thermoluminescence dosimeters (TLDs) placed within a Rando phantom. The measured and computed first and second HVLs were 3.8, 10.3 mm Al and 3.8, 10.6 mm Al, respectively. The differences between measured and calculated PDDs and beam profiles in water were within 2 mm/2% for all data points. In the Rando phantom, differences for majority of data points were within 2%. The proposed model offered an approximately 9500-fold reduced run time compared to the conventional full simulation. The acceptable agreement, based on international criteria, between the simulations and the measurements validates the accuracy of the model for its use in treatment planning and radiobiological modeling studies of superficial therapies including chest-wall irradiation using kilovoltage beam. PMID:26170553
Zeinali-Rafsanjani, B; Mosleh-Shirazi, M A; Faghihi, R; Karbasi, S; Mosalaei, A
2015-01-01
To accurately recompute dose distributions in chest-wall radiotherapy with 120 kVp kilovoltage X-rays, an MCNP4C Monte Carlo model is presented using a fast method that obviates the need to fully model the tube components. To validate the model, half-value layer (HVL), percentage depth doses (PDDs) and beam profiles were measured. Dose measurements were performed for a more complex situation using thermoluminescence dosimeters (TLDs) placed within a Rando phantom. The measured and computed first and second HVLs were 3.8, 10.3 mm Al and 3.8, 10.6 mm Al, respectively. The differences between measured and calculated PDDs and beam profiles in water were within 2 mm/2% for all data points. In the Rando phantom, differences for majority of data points were within 2%. The proposed model offered an approximately 9500-fold reduced run time compared to the conventional full simulation. The acceptable agreement, based on international criteria, between the simulations and the measurements validates the accuracy of the model for its use in treatment planning and radiobiological modeling studies of superficial therapies including chest-wall irradiation using kilovoltage beam. PMID:26170553
Accurate complex scaling of three dimensional numerical potentials
Cerioni, Alessandro; Genovese, Luigi; Duchemin, Ivan; Deutsch, Thierry
2013-05-28
The complex scaling method, which consists in continuing spatial coordinates into the complex plane, is a well-established method that allows to compute resonant eigenfunctions of the time-independent Schroedinger operator. Whenever it is desirable to apply the complex scaling to investigate resonances in physical systems defined on numerical discrete grids, the most direct approach relies on the application of a similarity transformation to the original, unscaled Hamiltonian. We show that such an approach can be conveniently implemented in the Daubechies wavelet basis set, featuring a very promising level of generality, high accuracy, and no need for artificial convergence parameters. Complex scaling of three dimensional numerical potentials can be efficiently and accurately performed. By carrying out an illustrative resonant state computation in the case of a one-dimensional model potential, we then show that our wavelet-based approach may disclose new exciting opportunities in the field of computational non-Hermitian quantum mechanics.
Anatomically accurate individual face modeling.
Zhang, Yu; Prakash, Edmond C; Sung, Eric
2003-01-01
This paper presents a new 3D face model of a specific person constructed from the anatomical perspective. By exploiting the laser range data, a 3D facial mesh precisely representing the skin geometry is reconstructed. Based on the geometric facial mesh, we develop a deformable multi-layer skin model. It takes into account the nonlinear stress-strain relationship and dynamically simulates the non-homogenous behavior of the real skin. The face model also incorporates a set of anatomically-motivated facial muscle actuators and underlying skull structure. Lagrangian mechanics governs the facial motion dynamics, dictating the dynamic deformation of facial skin in response to the muscle contraction. PMID:15455936
Accurate mask model for advanced nodes
NASA Astrophysics Data System (ADS)
Zine El Abidine, Nacer; Sundermann, Frank; Yesilada, Emek; Ndiaye, El Hadji Omar; Mishra, Kushlendra; Paninjath, Sankaranarayanan; Bork, Ingo; Buck, Peter; Toublan, Olivier; Schanen, Isabelle
2014-07-01
Standard OPC models consist of a physical optical model and an empirical resist model. The resist model compensates the optical model imprecision on top of modeling resist development. The optical model imprecision may result from mask topography effects and real mask information including mask ebeam writing and mask process contributions. For advanced technology nodes, significant progress has been made to model mask topography to improve optical model accuracy. However, mask information is difficult to decorrelate from standard OPC model. Our goal is to establish an accurate mask model through a dedicated calibration exercise. In this paper, we present a flow to calibrate an accurate mask enabling its implementation. The study covers the different effects that should be embedded in the mask model as well as the experiment required to model them.
Pre-Modeling Ensures Accurate Solid Models
ERIC Educational Resources Information Center
Gow, George
2010-01-01
Successful solid modeling requires a well-organized design tree. The design tree is a list of all the object's features and the sequential order in which they are modeled. The solid-modeling process is faster and less prone to modeling errors when the design tree is a simple and geometrically logical definition of the modeled object. Few high…
New model accurately predicts reformate composition
Ancheyta-Juarez, J.; Aguilar-Rodriguez, E. )
1994-01-31
Although naphtha reforming is a well-known process, the evolution of catalyst formulation, as well as new trends in gasoline specifications, have led to rapid evolution of the process, including: reactor design, regeneration mode, and operating conditions. Mathematical modeling of the reforming process is an increasingly important tool. It is fundamental to the proper design of new reactors and revamp of existing ones. Modeling can be used to optimize operating conditions, analyze the effects of process variables, and enhance unit performance. Instituto Mexicano del Petroleo has developed a model of the catalytic reforming process that accurately predicts reformate composition at the higher-severity conditions at which new reformers are being designed. The new AA model is more accurate than previous proposals because it takes into account the effects of temperature and pressure on the rate constants of each chemical reaction.
Accurate modeling of parallel scientific computations
NASA Technical Reports Server (NTRS)
Nicol, David M.; Townsend, James C.
1988-01-01
Scientific codes are usually parallelized by partitioning a grid among processors. To achieve top performance it is necessary to partition the grid so as to balance workload and minimize communication/synchronization costs. This problem is particularly acute when the grid is irregular, changes over the course of the computation, and is not known until load time. Critical mapping and remapping decisions rest on the ability to accurately predict performance, given a description of a grid and its partition. This paper discusses one approach to this problem, and illustrates its use on a one-dimensional fluids code. The models constructed are shown to be accurate, and are used to find optimal remapping schedules.
The importance of accurate atmospheric modeling
NASA Astrophysics Data System (ADS)
Payne, Dylan; Schroeder, John; Liang, Pang
2014-11-01
This paper will focus on the effect of atmospheric conditions on EO sensor performance using computer models. We have shown the importance of accurately modeling atmospheric effects for predicting the performance of an EO sensor. A simple example will demonstrated how real conditions for several sites in China will significantly impact on image correction, hyperspectral imaging, and remote sensing. The current state-of-the-art model for computing atmospheric transmission and radiance is, MODTRAN® 5, developed by the US Air Force Research Laboratory and Spectral Science, Inc. Research by the US Air Force, Navy and Army resulted in the public release of LOWTRAN 2 in the early 1970's. Subsequent releases of LOWTRAN and MODTRAN® have continued until the present. Please verify that (1) all pages are present, (2) all figures are correct, (3) all fonts and special characters are correct, and (4) all text and figures fit within the red margin lines shown on this review document. Complete formatting information is available at http://SPIE.org/manuscripts Return to the Manage Active Submissions page at http://spie.org/submissions/tasks.aspx and approve or disapprove this submission. Your manuscript will not be published without this approval. Please contact author_help@spie.org with any questions or concerns. The paper will demonstrate the importance of using validated models and local measured meteorological, atmospheric and aerosol conditions to accurately simulate the atmospheric transmission and radiance. Frequently default conditions are used which can produce errors of as much as 75% in these values. This can have significant impact on remote sensing applications.
NASA Astrophysics Data System (ADS)
Rosati, Dora P.; Molina, Chai; Earn, David J. D.
2015-12-01
Human behaviour and disease dynamics can greatly influence each other. In particular, people often engage in self-protective behaviours that affect epidemic patterns (e.g., vaccination, use of barrier precautions, isolation, etc.). Self-protective measures usually have a mitigating effect on an epidemic [16], but can in principle have negative impacts at the population level [12,15,18]. The structure of underlying social and biological contact networks can significantly influence the specific ways in which population-level effects are manifested. Using a different contact network in a disease dynamics model-keeping all else equal-can yield very different epidemic patterns. For example, it has been shown that when individuals imitate their neighbours' vaccination decisions with some probability, this can lead to herd immunity in some networks [9], yet for other networks it can preserve clusters of susceptible individuals that can drive further outbreaks of infectious disease [12].
More-Accurate Model of Flows in Rocket Injectors
NASA Technical Reports Server (NTRS)
Hosangadi, Ashvin; Chenoweth, James; Brinckman, Kevin; Dash, Sanford
2011-01-01
An improved computational model for simulating flows in liquid-propellant injectors in rocket engines has been developed. Models like this one are needed for predicting fluxes of heat in, and performances of, the engines. An important part of predicting performance is predicting fluctuations of temperature, fluctuations of concentrations of chemical species, and effects of turbulence on diffusion of heat and chemical species. Customarily, diffusion effects are represented by parameters known in the art as the Prandtl and Schmidt numbers. Prior formulations include ad hoc assumptions of constant values of these parameters, but these assumptions and, hence, the formulations, are inaccurate for complex flows. In the improved model, these parameters are neither constant nor specified in advance: instead, they are variables obtained as part of the solution. Consequently, this model represents the effects of turbulence on diffusion of heat and chemical species more accurately than prior formulations do, and may enable more-accurate prediction of mixing and flows of heat in rocket-engine combustion chambers. The model has been implemented within CRUNCH CFD, a proprietary computational fluid dynamics (CFD) computer program, and has been tested within that program. The model could also be implemented within other CFD programs.
Accurate astronomical atmospheric dispersion models in ZEMAX
NASA Astrophysics Data System (ADS)
Spanò, P.
2014-07-01
ZEMAX provides a standard built-in atmospheric model to simulate atmospheric refraction and dispersion. This model has been compared with other ones to assess its intrinsic accuracy, critical for very demanding application like ADCs for AO-assisted extremely large telescopes. A revised simple model, based on updated published data of the air refractivity, is proposed by using the "Gradient 5" surface of Zemax. At large zenith angles (65 deg), discrepancies up to 100 mas in the differential refraction are expected near the UV atmospheric transmission cutoff. When high-accuracy modeling is required, the latter model should be preferred.
Nakhleh, Luay
2014-03-12
I proposed to develop computationally efficient tools for accurate detection and reconstruction of microbes' complex evolutionary mechanisms, thus enabling rapid and accurate annotation, analysis and understanding of their genomes. To achieve this goal, I proposed to address three aspects. (1) Mathematical modeling. A major challenge facing the accurate detection of HGT is that of distinguishing between these two events on the one hand and other events that have similar "effects." I proposed to develop a novel mathematical approach for distinguishing among these events. Further, I proposed to develop a set of novel optimization criteria for the evolutionary analysis of microbial genomes in the presence of these complex evolutionary events. (2) Algorithm design. In this aspect of the project, I proposed to develop an array of e cient and accurate algorithms for analyzing microbial genomes based on the formulated optimization criteria. Further, I proposed to test the viability of the criteria and the accuracy of the algorithms in an experimental setting using both synthetic as well as biological data. (3) Software development. I proposed the nal outcome to be a suite of software tools which implements the mathematical models as well as the algorithms developed.
Accurate spectral modeling for infrared radiation
NASA Technical Reports Server (NTRS)
Tiwari, S. N.; Gupta, S. K.
1977-01-01
Direct line-by-line integration and quasi-random band model techniques are employed to calculate the spectral transmittance and total band absorptance of 4.7 micron CO, 4.3 micron CO2, 15 micron CO2, and 5.35 micron NO bands. Results are obtained for different pressures, temperatures, and path lengths. These are compared with available theoretical and experimental investigations. For each gas, extensive tabulations of results are presented for comparative purposes. In almost all cases, line-by-line results are found to be in excellent agreement with the experimental values. The range of validity of other models and correlations are discussed.
Accurate theoretical chemistry with coupled pair models.
Neese, Frank; Hansen, Andreas; Wennmohs, Frank; Grimme, Stefan
2009-05-19
Quantum chemistry has found its way into the everyday work of many experimental chemists. Calculations can predict the outcome of chemical reactions, afford insight into reaction mechanisms, and be used to interpret structure and bonding in molecules. Thus, contemporary theory offers tremendous opportunities in experimental chemical research. However, even with present-day computers and algorithms, we cannot solve the many particle Schrodinger equation exactly; inevitably some error is introduced in approximating the solutions of this equation. Thus, the accuracy of quantum chemical calculations is of critical importance. The affordable accuracy depends on molecular size and particularly on the total number of atoms: for orientation, ethanol has 9 atoms, aspirin 21 atoms, morphine 40 atoms, sildenafil 63 atoms, paclitaxel 113 atoms, insulin nearly 800 atoms, and quaternary hemoglobin almost 12,000 atoms. Currently, molecules with up to approximately 10 atoms can be very accurately studied by coupled cluster (CC) theory, approximately 100 atoms with second-order Møller-Plesset perturbation theory (MP2), approximately 1000 atoms with density functional theory (DFT), and beyond that number with semiempirical quantum chemistry and force-field methods. The overwhelming majority of present-day calculations in the 100-atom range use DFT. Although these methods have been very successful in quantum chemistry, they do not offer a well-defined hierarchy of calculations that allows one to systematically converge to the correct answer. Recently a number of rather spectacular failures of DFT methods have been found-even for seemingly simple systems such as hydrocarbons, fueling renewed interest in wave function-based methods that incorporate the relevant physics of electron correlation in a more systematic way. Thus, it would be highly desirable to fill the gap between 10 and 100 atoms with highly correlated ab initio methods. We have found that one of the earliest (and now
Accurate thermodynamic properties of gas phase hydrogen bonded complexes.
Hansen, Anne S; Maroun, Zeina; Mackeprang, Kasper; Frandsen, Benjamin N; Kjaergaard, Henrik G
2016-08-24
We have measured the infrared spectra of ethanol·dimethylamine and methanol·dimethylamine complexes in the 299-374 K temperature range, and have determined the enthalpy of complex formation (ΔH) to be -31.1 ± 2 and -29.5 ± 2 kJ mol(-1), respectively. The corresponding values of the Gibbs free energy (ΔG) are determined from the experimental integrated absorbance and a calculated oscillator strength of the OH-stretching vibrational transition to be 4.1 ± 0.3 and 3.9 ± 0.3 kJ mol(-1) at 302 and 300 K, respectively. The entropy, ΔS is determined from the values of ΔH and ΔG to be -117 ± 7 and -111 ± 10 J (mol K)(-1) for the ethanol·dimethylamine and methanol·dimethylamine complexes, respectively. The determined ΔH, ΔG and ΔS values of the two complexes are similar, as expected by the similarity to their donor molecules ethanol and methanol. Values of ΔH, ΔG and ΔS in chemical reactions are often obtained from quantum chemical calculations. However, these calculated values have limited accuracy and large variations are found using different methods. The accuracy of the present ΔH, ΔG and ΔS values is such that the benchmarking of theoretical methods is possible. PMID:27523902
Generating Facial Expressions Using an Anatomically Accurate Biomechanical Model.
Wu, Tim; Hung, Alice; Mithraratne, Kumar
2014-11-01
This paper presents a computational framework for modelling the biomechanics of human facial expressions. A detailed high-order (Cubic-Hermite) finite element model of the human head was constructed using anatomical data segmented from magnetic resonance images. The model includes a superficial soft-tissue continuum consisting of skin, the subcutaneous layer and the superficial Musculo-Aponeurotic system. Embedded within this continuum mesh, are 20 pairs of facial muscles which drive facial expressions. These muscles were treated as transversely-isotropic and their anatomical geometries and fibre orientations were accurately depicted. In order to capture the relative composition of muscles and fat, material heterogeneity was also introduced into the model. Complex contact interactions between the lips, eyelids, and between superficial soft tissue continuum and deep rigid skeletal bones were also computed. In addition, this paper investigates the impact of incorporating material heterogeneity and contact interactions, which are often neglected in similar studies. Four facial expressions were simulated using the developed model and the results were compared with surface data obtained from a 3D structured-light scanner. Predicted expressions showed good agreement with the experimental data. PMID:26355331
Accurate Wind Characterization in Complex Terrain Using the Immersed Boundary Method
Lundquist, K A; Chow, F K; Lundquist, J K; Kosovic, B
2009-09-30
This paper describes an immersed boundary method (IBM) that facilitates the explicit resolution of complex terrain within the Weather Research and Forecasting (WRF) model. Two different interpolation methods, trilinear and inverse distance weighting, are used at the core of the IBM algorithm. Functional aspects of the algorithm's implementation and the accuracy of results are considered. Simulations of flow over a three-dimensional hill with shallow terrain slopes are preformed with both WRF's native terrain-following coordinate and with both IB methods. Comparisons of flow fields from the three simulations show excellent agreement, indicating that both IB methods produce accurate results. However, when ease of implementation is considered, inverse distance weighting is superior. Furthermore, inverse distance weighting is shown to be more adept at handling highly complex urban terrain, where the trilinear interpolation algorithm breaks down. This capability is demonstrated by using the inverse distance weighting core of the IBM to model atmospheric flow in downtown Oklahoma City.
NASA Technical Reports Server (NTRS)
Cao, Fang; Fichot, Cedric G.; Hooker, Stanford B.; Miller, William L.
2014-01-01
Photochemical processes driven by high-energy ultraviolet radiation (UVR) in inshore, estuarine, and coastal waters play an important role in global bio geochemical cycles and biological systems. A key to modeling photochemical processes in these optically complex waters is an accurate description of the vertical distribution of UVR in the water column which can be obtained using the diffuse attenuation coefficients of down welling irradiance (Kd()). The Sea UV Sea UVc algorithms (Fichot et al., 2008) can accurately retrieve Kd ( 320, 340, 380,412, 443 and 490 nm) in oceanic and coastal waters using multispectral remote sensing reflectances (Rrs(), Sea WiFS bands). However, SeaUVSeaUVc algorithms are currently not optimized for use in optically complex, inshore waters, where they tend to severely underestimate Kd(). Here, a new training data set of optical properties collected in optically complex, inshore waters was used to re-parameterize the published SeaUVSeaUVc algorithms, resulting in improved Kd() retrievals for turbid, estuarine waters. Although the updated SeaUVSeaUVc algorithms perform best in optically complex waters, the published SeaUVSeaUVc models still perform well in most coastal and oceanic waters. Therefore, we propose a composite set of SeaUVSeaUVc algorithms, optimized for Kd() retrieval in almost all marine systems, ranging from oceanic to inshore waters. The composite algorithm set can retrieve Kd from ocean color with good accuracy across this wide range of water types (e.g., within 13 mean relative error for Kd(340)). A validation step using three independent, in situ data sets indicates that the composite SeaUVSeaUVc can generate accurate Kd values from 320 490 nm using satellite imagery on a global scale. Taking advantage of the inherent benefits of our statistical methods, we pooled the validation data with the training set, obtaining an optimized composite model for estimating Kd() in UV wavelengths for almost all marine waters. This
Hand, Laurence H; Marshall, Samantha J; Saeed, Mansoor; Earll, Mark; Hadfield, Stephen T; Richardson, Kevan; Rawlinson, Paul
2016-06-01
Lysimeter studies can be used to identify and quantify soil degradates of agrochemicals (metabolites) that have the potential to leach to groundwater. However, the apparent metabolic profile of such lysimeter leachate samples will often be significantly more complex than would be expected in true groundwater samples. This is particularly true for S-metolachlor, which has an extremely complex metabolic pathway. Consequently, it was not practically possible to apply a conventional analytical approach to identify all metabolites in an S-metolachlor lysimeter study, because there was insufficient mass to enable the use of techniques such as nuclear magnetic resonance. Recent advances in high-resolution accurate mass spectrometry, however, allow innovative screening approaches to characterize leachate samples to a greater extent than previously possible. Leachate from the S-metolachlor study was screened for accurate masses (±5 ppm of the nominal mass) corresponding to more than 400 hypothetical metabolite structures. A refined list of plausible metabolites was constructed from these data to provide a comprehensive description of the most likely metabolites present. The properties of these metabolites were then evaluated using a principal component analysis model, based on molecular descriptors, to visualize the entire chemical space and to cluster the metabolites into a number of subclasses. This characterization and principal component analysis evaluation enabled the selection of suitable representative metabolites that were subsequently used as exemplars to assess the toxicological relevance of the leachate as a whole. Environ Toxicol Chem 2016;35:1401-1412. © 2015 SETAC. PMID:26627902
Accurate acoustic and elastic beam migration without slant stack for complex topography
NASA Astrophysics Data System (ADS)
Huang, Jianping; Yuan, Maolin; Liao, Wenyuan; Li, Zhenchun; Yue, Yubo
2015-06-01
Recent trends in seismic exploration have led to the collection of more surveys, often with multi-component recording, in onshore settings where both topography and subsurface targets are complex, leading to challenges for processing methods. Gaussian beam migration (GBM) is an alternative to single-arrival Kirchhoff migration, although there are some issues resulting in unsatisfactory GBM images. For example, static correction will give rise to the distortion of wavefields when near-surface elevation and velocity vary rapidly. Moreover, Green’s function compensated for phase changes from the beam center to receivers is inaccurate when receivers are not placed within some neighborhood of the beam center, that is, GBM is slightly inflexible for irregular acquisition system and complex topography. As a result, the differences of both the near-surface velocity and the surface slope from the beam center to the receivers and the poor spatial sampling of the land data lead to inaccuracy and aliasing of the slant stack, respectively. In order to improve the flexibility and accuracy of GBM, we propose accurate acoustic, PP and polarity-corrected PS beam migration without slant stack for complex topography. The applications of this method to one-component synthetic data from a 2D Canadian Foothills model and a Zhongyuan oilfield fault model, one-component field data and an unseparated multi-component synthetic data demonstrate that the method is effective for structural and relatively amplitude-preserved imaging, but significantly more time-consuming.
Accurate FDTD modelling for dispersive media using rational function and particle swarm optimisation
NASA Astrophysics Data System (ADS)
Chung, Haejun; Ha, Sang-Gyu; Choi, Jaehoon; Jung, Kyung-Young
2015-07-01
This article presents an accurate finite-difference time domain (FDTD) dispersive modelling suitable for complex dispersive media. A quadratic complex rational function (QCRF) is used to characterise their dispersive relations. To obtain accurate coefficients of QCRF, in this work, we use an analytical approach and a particle swarm optimisation (PSO) simultaneously. In specific, an analytical approach is used to obtain the QCRF matrix-solving equation and PSO is applied to adjust a weighting function of this equation. Numerical examples are used to illustrate the validity of the proposed FDTD dispersion model.
Accurate in situ measurement of complex refractive index and particle size in intralipid emulsions.
Dong, Miao L; Goyal, Kashika G; Worth, Bradley W; Makkar, Sorab S; Calhoun, William R; Bali, Lalit M; Bali, Samir
2013-08-01
A first accurate measurement of the complex refractive index in an intralipid emulsion is demonstrated, and thereby the average scatterer particle size using standard Mie scattering calculations is extracted. Our method is based on measurement and modeling of the reflectance of a divergent laser beam from the sample surface. In the absence of any definitive reference data for the complex refractive index or particle size in highly turbid intralipid emulsions, we base our claim of accuracy on the fact that our work offers several critically important advantages over previously reported attempts. First, our measurements are in situ in the sense that they do not require any sample dilution, thus eliminating dilution errors. Second, our theoretical model does not employ any fitting parameters other than the two quantities we seek to determine, i.e., the real and imaginary parts of the refractive index, thus eliminating ambiguities arising from multiple extraneous fitting parameters. Third, we fit the entire reflectance-versus-incident-angle data curve instead of focusing on only the critical angle region, which is just a small subset of the data. Finally, despite our use of highly scattering opaque samples, our experiment uniquely satisfies a key assumption behind the Mie scattering formalism, namely, no multiple scattering occurs. Further proof of our method's validity is given by the fact that our measured particle size finds good agreement with the value obtained by dynamic light scattering. PMID:23922125
Water wave model with accurate dispersion and vertical vorticity
NASA Astrophysics Data System (ADS)
Bokhove, Onno
2010-05-01
Cotter and Bokhove (Journal of Engineering Mathematics 2010) derived a variational water wave model with accurate dispersion and vertical vorticity. In one limit, it leads to Luke's variational principle for potential flow water waves. In the another limit it leads to the depth-averaged shallow water equations including vertical vorticity. Presently, focus will be put on the Hamiltonian formulation of the variational model and its boundary conditions.
An Accurate and Dynamic Computer Graphics Muscle Model
NASA Technical Reports Server (NTRS)
Levine, David Asher
1997-01-01
A computer based musculo-skeletal model was developed at the University in the departments of Mechanical and Biomedical Engineering. This model accurately represents human shoulder kinematics. The result of this model is the graphical display of bones moving through an appropriate range of motion based on inputs of EMGs and external forces. The need existed to incorporate a geometric muscle model in the larger musculo-skeletal model. Previous muscle models did not accurately represent muscle geometries, nor did they account for the kinematics of tendons. This thesis covers the creation of a new muscle model for use in the above musculo-skeletal model. This muscle model was based on anatomical data from the Visible Human Project (VHP) cadaver study. Two-dimensional digital images from the VHP were analyzed and reconstructed to recreate the three-dimensional muscle geometries. The recreated geometries were smoothed, reduced, and sliced to form data files defining the surfaces of each muscle. The muscle modeling function opened these files during run-time and recreated the muscle surface. The modeling function applied constant volume limitations to the muscle and constant geometry limitations to the tendons.
Local Debonding and Fiber Breakage in Composite Materials Modeled Accurately
NASA Technical Reports Server (NTRS)
Bednarcyk, Brett A.; Arnold, Steven M.
2001-01-01
A prerequisite for full utilization of composite materials in aerospace components is accurate design and life prediction tools that enable the assessment of component performance and reliability. Such tools assist both structural analysts, who design and optimize structures composed of composite materials, and materials scientists who design and optimize the composite materials themselves. NASA Glenn Research Center's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) software package (http://www.grc.nasa.gov/WWW/LPB/mac) addresses this need for composite design and life prediction tools by providing a widely applicable and accurate approach to modeling composite materials. Furthermore, MAC/GMC serves as a platform for incorporating new local models and capabilities that are under development at NASA, thus enabling these new capabilities to progress rapidly to a stage in which they can be employed by the code's end users.
An Accurate Temperature Correction Model for Thermocouple Hygrometers 1
Savage, Michael J.; Cass, Alfred; de Jager, James M.
1982-01-01
Numerous water relation studies have used thermocouple hygrometers routinely. However, the accurate temperature correction of hygrometer calibration curve slopes seems to have been largely neglected in both psychrometric and dewpoint techniques. In the case of thermocouple psychrometers, two temperature correction models are proposed, each based on measurement of the thermojunction radius and calculation of the theoretical voltage sensitivity to changes in water potential. The first model relies on calibration at a single temperature and the second at two temperatures. Both these models were more accurate than the temperature correction models currently in use for four psychrometers calibrated over a range of temperatures (15-38°C). The model based on calibration at two temperatures is superior to that based on only one calibration. The model proposed for dewpoint hygrometers is similar to that for psychrometers. It is based on the theoretical voltage sensitivity to changes in water potential. Comparison with empirical data from three dewpoint hygrometers calibrated at four different temperatures indicates that these instruments need only be calibrated at, e.g. 25°C, if the calibration slopes are corrected for temperature. PMID:16662241
An accurate temperature correction model for thermocouple hygrometers.
Savage, M J; Cass, A; de Jager, J M
1982-02-01
Numerous water relation studies have used thermocouple hygrometers routinely. However, the accurate temperature correction of hygrometer calibration curve slopes seems to have been largely neglected in both psychrometric and dewpoint techniques.In the case of thermocouple psychrometers, two temperature correction models are proposed, each based on measurement of the thermojunction radius and calculation of the theoretical voltage sensitivity to changes in water potential. The first model relies on calibration at a single temperature and the second at two temperatures. Both these models were more accurate than the temperature correction models currently in use for four psychrometers calibrated over a range of temperatures (15-38 degrees C). The model based on calibration at two temperatures is superior to that based on only one calibration.The model proposed for dewpoint hygrometers is similar to that for psychrometers. It is based on the theoretical voltage sensitivity to changes in water potential. Comparison with empirical data from three dewpoint hygrometers calibrated at four different temperatures indicates that these instruments need only be calibrated at, e.g. 25 degrees C, if the calibration slopes are corrected for temperature. PMID:16662241
On the importance of having accurate data for astrophysical modelling
NASA Astrophysics Data System (ADS)
Lique, Francois
2016-06-01
The Herschel telescope and the ALMA and NOEMA interferometers have opened new windows of observation for wavelengths ranging from far infrared to sub-millimeter with spatial and spectral resolutions previously unmatched. To make the most of these observations, an accurate knowledge of the physical and chemical processes occurring in the interstellar and circumstellar media is essential.In this presentation, I will discuss what are the current needs of astrophysics in terms of molecular data and I will show that accurate molecular data are crucial for the proper determination of the physical conditions in molecular clouds.First, I will focus on collisional excitation studies that are needed for molecular lines modelling beyond the Local Thermodynamic Equilibrium (LTE) approach. In particular, I will show how new collisional data for the HCN and HNC isomers, two tracers of star forming conditions, have allowed solving the problem of their respective abundance in cold molecular clouds. I will also present the last collisional data that have been computed in order to analyse new highly resolved observations provided by the ALMA interferometer.Then, I will present the calculation of accurate rate constants for the F+H2 → HF+H and Cl+H2 ↔ HCl+H reactions, which have allowed a more accurate determination of the physical conditions in diffuse molecular clouds. I will also present the recent work on the ortho-para-H2 conversion due to hydrogen exchange that allow more accurate determination of the ortho-to-para-H2 ratio in the universe and that imply a significant revision of the cooling mechanism in astrophysical media.
Accurate method of modeling cluster scaling relations in modified gravity
NASA Astrophysics Data System (ADS)
He, Jian-hua; Li, Baojiu
2016-06-01
We propose a new method to model cluster scaling relations in modified gravity. Using a suite of nonradiative hydrodynamical simulations, we show that the scaling relations of accumulated gas quantities, such as the Sunyaev-Zel'dovich effect (Compton-y parameter) and the x-ray Compton-y parameter, can be accurately predicted using the known results in the Λ CDM model with a precision of ˜3 % . This method provides a reliable way to analyze the gas physics in modified gravity using the less demanding and much more efficient pure cold dark matter simulations. Our results therefore have important theoretical and practical implications in constraining gravity using cluster surveys.
Accurate refinement of docked protein complexes using evolutionary information and deep learning.
Akbal-Delibas, Bahar; Farhoodi, Roshanak; Pomplun, Marc; Haspel, Nurit
2016-06-01
One of the major challenges for protein docking methods is to accurately discriminate native-like structures from false positives. Docking methods are often inaccurate and the results have to be refined and re-ranked to obtain native-like complexes and remove outliers. In a previous work, we introduced AccuRefiner, a machine learning based tool for refining protein-protein complexes. Given a docked complex, the refinement tool produces a small set of refined versions of the input complex, with lower root-mean-square-deviation (RMSD) of atomic positions with respect to the native structure. The method employs a unique ranking tool that accurately predicts the RMSD of docked complexes with respect to the native structure. In this work, we use a deep learning network with a similar set of features and five layers. We show that a properly trained deep learning network can accurately predict the RMSD of a docked complex with 1.40 Å error margin on average, by approximating the complex relationship between a wide set of scoring function terms and the RMSD of a docked structure. The network was trained on 35000 unbound docking complexes generated by RosettaDock. We tested our method on 25 different putative docked complexes produced also by RosettaDock for five proteins that were not included in the training data. The results demonstrate that the high accuracy of the ranking tool enables AccuRefiner to consistently choose the refinement candidates with lower RMSD values compared to the coarsely docked input structures. PMID:26846813
Brown, T. W.
2011-04-15
The same complex matrix model calculates both tachyon scattering for the c=1 noncritical string at the self-dual radius and certain correlation functions of operators which preserve half the supersymmetry in N=4 super-Yang-Mills theory. It is dual to another complex matrix model where the couplings of the first model are encoded in the Kontsevich-like variables of the second. The duality between the theories is mirrored by the duality of their Feynman diagrams. Analogously to the Hermitian Kontsevich-Penner model, the correlation functions of the second model can be written as sums over discrete points in subspaces of the moduli space of punctured Riemann surfaces.
Anisotropic Turbulence Modeling for Accurate Rod Bundle Simulations
Baglietto, Emilio
2006-07-01
An improved anisotropic eddy viscosity model has been developed for accurate predictions of the thermal hydraulic performances of nuclear reactor fuel assemblies. The proposed model adopts a non-linear formulation of the stress-strain relationship in order to include the reproduction of the anisotropic phenomena, and in combination with an optimized low-Reynolds-number formulation based on Direct Numerical Simulation (DNS) to produce correct damping of the turbulent viscosity in the near wall region. This work underlines the importance of accurate anisotropic modeling to faithfully reproduce the scale of the turbulence driven secondary flows inside the bundle subchannels, by comparison with various isothermal and heated experimental cases. The very low scale secondary motion is responsible for the increased turbulence transport which produces a noticeable homogenization of the velocity distribution and consequently of the circumferential cladding temperature distribution, which is of main interest in bundle design. Various fully developed bare bundles test cases are shown for different geometrical and flow conditions, where the proposed model shows clearly improved predictions, in close agreement with experimental findings, for regular as well as distorted geometries. Finally the applicability of the model for practical bundle calculations is evaluated through its application in the high-Reynolds form on coarse grids, with excellent results. (author)
Technology Transfer Automated Retrieval System (TEKTRAN)
Adsorption-desorption reactions are important processes that affect the transport of contaminants in the environment. Surface complexation models are chemical models that can account for the effects of variable chemical conditions, such as pH, on adsorption reactions. These models define specific ...
The utility of accurate mass and LC elution time information in the analysis of complex proteomes
Norbeck, Angela D.; Monroe, Matthew E.; Adkins, Joshua N.; Anderson, Kevin K.; Daly, Don S.; Smith, Richard D.
2005-08-01
Theoretical tryptic digests of all predicted proteins from the genomes of three organisms of varying complexity were evaluated for specificity and possible utility of combined peptide accurate mass and predicted LC normalized elution time (NET) information. The uniqueness of each peptide was evaluated using its combined mass (+/- 5 ppm and 1 ppm) and NET value (no constraint, +/- 0.05 and 0.01 on a 0-1 NET scale). The set of peptides both underestimates actual biological complexity due to the lack of specific modifications, and overestimates the expected complexity since many proteins will not be present in the sample or observable on the mass spectrometer because of dynamic range limitations. Once a peptide is identified from an LCMS/MS experiment, its mass and elution time is representative of a unique fingerprint for that peptide. The uniqueness of that fingerprint in comparison to that for the other peptides present is indicative of the ability to confidently identify that peptide based on accurate mass and NET measurements. These measurements can be made using HPLC coupled with high resolution MS in a high-throughput manner. Results show that for organisms with comparatively small proteomes, such as Deinococcus radiodurans, modest mass and elution time accuracies are generally adequate for peptide identifications. For more complex proteomes, increasingly accurate easurements are required. However, the majority of proteins should be uniquely identifiable by using LC-MS with mass accuracies within +/- 1 ppm and elution time easurements within +/- 0.01 NET.
Accurate pressure gradient calculations in hydrostatic atmospheric models
NASA Technical Reports Server (NTRS)
Carroll, John J.; Mendez-Nunez, Luis R.; Tanrikulu, Saffet
1987-01-01
A method for the accurate calculation of the horizontal pressure gradient acceleration in hydrostatic atmospheric models is presented which is especially useful in situations where the isothermal surfaces are not parallel to the vertical coordinate surfaces. The present method is shown to be exact if the potential temperature lapse rate is constant between the vertical pressure integration limits. The technique is applied to both the integration of the hydrostatic equation and the computation of the slope correction term in the horizontal pressure gradient. A fixed vertical grid and a dynamic grid defined by the significant levels in the vertical temperature distribution are employed.
Mouse models of human AML accurately predict chemotherapy response
Zuber, Johannes; Radtke, Ina; Pardee, Timothy S.; Zhao, Zhen; Rappaport, Amy R.; Luo, Weijun; McCurrach, Mila E.; Yang, Miao-Miao; Dolan, M. Eileen; Kogan, Scott C.; Downing, James R.; Lowe, Scott W.
2009-01-01
The genetic heterogeneity of cancer influences the trajectory of tumor progression and may underlie clinical variation in therapy response. To model such heterogeneity, we produced genetically and pathologically accurate mouse models of common forms of human acute myeloid leukemia (AML) and developed methods to mimic standard induction chemotherapy and efficiently monitor therapy response. We see that murine AMLs harboring two common human AML genotypes show remarkably diverse responses to conventional therapy that mirror clinical experience. Specifically, murine leukemias expressing the AML1/ETO fusion oncoprotein, associated with a favorable prognosis in patients, show a dramatic response to induction chemotherapy owing to robust activation of the p53 tumor suppressor network. Conversely, murine leukemias expressing MLL fusion proteins, associated with a dismal prognosis in patients, are drug-resistant due to an attenuated p53 response. Our studies highlight the importance of genetic information in guiding the treatment of human AML, functionally establish the p53 network as a central determinant of chemotherapy response in AML, and demonstrate that genetically engineered mouse models of human cancer can accurately predict therapy response in patients. PMID:19339691
Mouse models of human AML accurately predict chemotherapy response.
Zuber, Johannes; Radtke, Ina; Pardee, Timothy S; Zhao, Zhen; Rappaport, Amy R; Luo, Weijun; McCurrach, Mila E; Yang, Miao-Miao; Dolan, M Eileen; Kogan, Scott C; Downing, James R; Lowe, Scott W
2009-04-01
The genetic heterogeneity of cancer influences the trajectory of tumor progression and may underlie clinical variation in therapy response. To model such heterogeneity, we produced genetically and pathologically accurate mouse models of common forms of human acute myeloid leukemia (AML) and developed methods to mimic standard induction chemotherapy and efficiently monitor therapy response. We see that murine AMLs harboring two common human AML genotypes show remarkably diverse responses to conventional therapy that mirror clinical experience. Specifically, murine leukemias expressing the AML1/ETO fusion oncoprotein, associated with a favorable prognosis in patients, show a dramatic response to induction chemotherapy owing to robust activation of the p53 tumor suppressor network. Conversely, murine leukemias expressing MLL fusion proteins, associated with a dismal prognosis in patients, are drug-resistant due to an attenuated p53 response. Our studies highlight the importance of genetic information in guiding the treatment of human AML, functionally establish the p53 network as a central determinant of chemotherapy response in AML, and demonstrate that genetically engineered mouse models of human cancer can accurately predict therapy response in patients. PMID:19339691
An accurate model potential for alkali neon systems.
Zanuttini, D; Jacquet, E; Giglio, E; Douady, J; Gervais, B
2009-12-01
We present a detailed investigation of the ground and lowest excited states of M-Ne dimers, for M=Li, Na, and K. We show that the potential energy curves of these Van der Waals dimers can be obtained accurately by considering the alkali neon systems as one-electron systems. Following previous authors, the model describes the evolution of the alkali valence electron in the combined potentials of the alkali and neon cores by means of core polarization pseudopotentials. The key parameter for an accurate model is the M(+)-Ne potential energy curve, which was obtained by means of ab initio CCSD(T) calculation using a large basis set. For each MNe dimer, a systematic comparison with ab initio computation of the potential energy curve for the X, A, and B states shows the remarkable accuracy of the model. The vibrational analysis and the comparison with existing experimental data strengthens this conclusion and allows for a precise assignment of the vibrational levels. PMID:19968334
NASA Technical Reports Server (NTRS)
Figueroa-Feliciano, Enectali
2004-01-01
We have developed a software suite that models complex calorimeters in the time and frequency domain. These models can reproduce all measurements that we currently do in a lab setting, like IV curves, impedance measurements, noise measurements, and pulse generation. Since all these measurements are modeled from one set of parameters, we can fully describe a detector and characterize its behavior. This leads to a model than can be used effectively for engineering and design of detectors for particular applications.
Granata, Daniele; Carnevale, Vincenzo
2016-01-01
The collective behavior of a large number of degrees of freedom can be often described by a handful of variables. This observation justifies the use of dimensionality reduction approaches to model complex systems and motivates the search for a small set of relevant “collective” variables. Here, we analyze this issue by focusing on the optimal number of variable needed to capture the salient features of a generic dataset and develop a novel estimator for the intrinsic dimension (ID). By approximating geodesics with minimum distance paths on a graph, we analyze the distribution of pairwise distances around the maximum and exploit its dependency on the dimensionality to obtain an ID estimate. We show that the estimator does not depend on the shape of the intrinsic manifold and is highly accurate, even for exceedingly small sample sizes. We apply the method to several relevant datasets from image recognition databases and protein multiple sequence alignments and discuss possible interpretations for the estimated dimension in light of the correlations among input variables and of the information content of the dataset. PMID:27510265
Granata, Daniele; Carnevale, Vincenzo
2016-01-01
The collective behavior of a large number of degrees of freedom can be often described by a handful of variables. This observation justifies the use of dimensionality reduction approaches to model complex systems and motivates the search for a small set of relevant "collective" variables. Here, we analyze this issue by focusing on the optimal number of variable needed to capture the salient features of a generic dataset and develop a novel estimator for the intrinsic dimension (ID). By approximating geodesics with minimum distance paths on a graph, we analyze the distribution of pairwise distances around the maximum and exploit its dependency on the dimensionality to obtain an ID estimate. We show that the estimator does not depend on the shape of the intrinsic manifold and is highly accurate, even for exceedingly small sample sizes. We apply the method to several relevant datasets from image recognition databases and protein multiple sequence alignments and discuss possible interpretations for the estimated dimension in light of the correlations among input variables and of the information content of the dataset. PMID:27510265
Turbulence Models for Accurate Aerothermal Prediction in Hypersonic Flows
NASA Astrophysics Data System (ADS)
Zhang, Xiang-Hong; Wu, Yi-Zao; Wang, Jiang-Feng
Accurate description of the aerodynamic and aerothermal environment is crucial to the integrated design and optimization for high performance hypersonic vehicles. In the simulation of aerothermal environment, the effect of viscosity is crucial. The turbulence modeling remains a major source of uncertainty in the computational prediction of aerodynamic forces and heating. In this paper, three turbulent models were studied: the one-equation eddy viscosity transport model of Spalart-Allmaras, the Wilcox k-ω model and the Menter SST model. For the k-ω model and SST model, the compressibility correction, press dilatation and low Reynolds number correction were considered. The influence of these corrections for flow properties were discussed by comparing with the results without corrections. In this paper the emphasis is on the assessment and evaluation of the turbulence models in prediction of heat transfer as applied to a range of hypersonic flows with comparison to experimental data. This will enable establishing factor of safety for the design of thermal protection systems of hypersonic vehicle.
A calibration-independent method for accurate complex permittivity determination of liquid materials
Hasar, U. C.
2008-08-15
This note presents a calibration-independent method for accurate complex permittivity determination of liquid materials. There are two main advantages of the proposed method over those in the literature, which require measurements of two cells with different lengths loaded by the same liquid material. First, it eliminates any inhomogeneity or impurity present in the second sample and decreases the uncertainty in sample thickness. Second, it removes the undesired impacts of measurement plane deterioration on measurements of liquid materials. For validation of the proposed method, we measure the complex permittivity of distilled water and compare its extracted permittivity with the theoretical datum obtained from the Debye equation.
Inverter Modeling For Accurate Energy Predictions Of Tracking HCPV Installations
NASA Astrophysics Data System (ADS)
Bowman, J.; Jensen, S.; McDonald, Mark
2010-10-01
High efficiency high concentration photovoltaic (HCPV) solar plants of megawatt scale are now operational, and opportunities for expanded adoption are plentiful. However, effective bidding for sites requires reliable prediction of energy production. HCPV module nameplate power is rated for specific test conditions; however, instantaneous HCPV power varies due to site specific irradiance and operating temperature, and is degraded by soiling, protective stowing, shading, and electrical connectivity. These factors interact with the selection of equipment typically supplied by third parties, e.g., wire gauge and inverters. We describe a time sequence model accurately accounting for these effects that predicts annual energy production, with specific reference to the impact of the inverter on energy output and interactions between system-level design decisions and the inverter. We will also show two examples, based on an actual field design, of inverter efficiency calculations and the interaction between string arrangements and inverter selection.
Identification of accurate nonlinear rainfall-runoff models with unique parameters
NASA Astrophysics Data System (ADS)
Schoups, G.; Vrugt, J. A.; Fenicia, F.; van de Giesen, N.
2009-04-01
We propose a strategy to identify models with unique parameters that yield accurate streamflow predictions, given a time-series of rainfall inputs. The procedure consists of five general steps. First, an a priori range of model structures is specified based on prior general and site-specific hydrologic knowledge. To this end, we rely on a flexible model code that allows a specification of a wide range of model structures, from simple to complex. Second, using global optimization each model structure is calibrated to a record of rainfall-runoff data, yielding optimal parameter values for each model structure. Third, accuracy of each model structure is determined by estimating model prediction errors using independent validation and statistical theory. Fourth, parameter identifiability of each calibrated model structure is estimated by means of Monte Carlo Markov Chain simulation. Finally, an assessment is made about each model structure in terms of its accuracy of mimicking rainfall-runoff processes (step 3), and the uniqueness of its parameters (step 4). The procedure results in the identification of the most complex and accurate model supported by the data, without causing parameter equifinality. As such, it provides insight into the information content of the data for identifying nonlinear rainfall-runoff models. We illustrate the method using rainfall-runoff data records from several MOPEX basins in the US.
Accurate, low-cost 3D-models of gullies
NASA Astrophysics Data System (ADS)
Onnen, Nils; Gronz, Oliver; Ries, Johannes B.; Brings, Christine
2015-04-01
Soil erosion is a widespread problem in arid and semi-arid areas. The most severe form is the gully erosion. They often cut into agricultural farmland and can make a certain area completely unproductive. To understand the development and processes inside and around gullies, we calculated detailed 3D-models of gullies in the Souss Valley in South Morocco. Near Taroudant, we had four study areas with five gullies different in size, volume and activity. By using a Canon HF G30 Camcorder, we made varying series of Full HD videos with 25fps. Afterwards, we used the method Structure from Motion (SfM) to create the models. To generate accurate models maintaining feasible runtimes, it is necessary to select around 1500-1700 images from the video, while the overlap of neighboring images should be at least 80%. In addition, it is very important to avoid selecting photos that are blurry or out of focus. Nearby pixels of a blurry image tend to have similar color values. That is why we used a MATLAB script to compare the derivatives of the images. The higher the sum of the derivative, the sharper an image of similar objects. MATLAB subdivides the video into image intervals. From each interval, the image with the highest sum is selected. E.g.: 20min. video at 25fps equals 30.000 single images. The program now inspects the first 20 images, saves the sharpest and moves on to the next 20 images etc. Using this algorithm, we selected 1500 images for our modeling. With VisualSFM, we calculated features and the matches between all images and produced a point cloud. Then, MeshLab has been used to build a surface out of it using the Poisson surface reconstruction approach. Afterwards we are able to calculate the size and the volume of the gullies. It is also possible to determine soil erosion rates, if we compare the data with old recordings. The final step would be the combination of the terrestrial data with the data from our aerial photography. So far, the method works well and we
Towards Accurate Molecular Modeling of Plastic Bonded Explosives
NASA Astrophysics Data System (ADS)
Chantawansri, T. L.; Andzelm, J.; Taylor, D.; Byrd, E.; Rice, B.
2010-03-01
There is substantial interest in identifying the controlling factors that influence the susceptibility of polymer bonded explosives (PBXs) to accidental initiation. Numerous Molecular Dynamics (MD) simulations of PBXs using the COMPASS force field have been reported in recent years, where the validity of the force field in modeling the solid EM fill has been judged solely on its ability to reproduce lattice parameters, which is an insufficient metric. Performance of the COMPASS force field in modeling EMs and the polymeric binder has been assessed by calculating structural, thermal, and mechanical properties, where only fair agreement with experimental data is obtained. We performed MD simulations using the COMPASS force field for the polymer binder hydroxyl-terminated polybutadiene and five EMs: cyclotrimethylenetrinitramine, 1,3,5,7-tetranitro-1,3,5,7-tetra-azacyclo-octane, 2,4,6,8,10,12-hexantirohexaazazisowurzitane, 2,4,6-trinitro-1,3,5-benzenetriamine, and pentaerythritol tetranitate. Predicted EM crystallographic and molecular structural parameters, as well as calculated properties for the binder will be compared with experimental results for different simulation conditions. We also present novel simulation protocols, which improve agreement between experimental and computation results thus leading to the accurate modeling of PBXs.
An accurate and simple quantum model for liquid water.
Paesani, Francesco; Zhang, Wei; Case, David A; Cheatham, Thomas E; Voth, Gregory A
2006-11-14
The path-integral molecular dynamics and centroid molecular dynamics methods have been applied to investigate the behavior of liquid water at ambient conditions starting from a recently developed simple point charge/flexible (SPC/Fw) model. Several quantum structural, thermodynamic, and dynamical properties have been computed and compared to the corresponding classical values, as well as to the available experimental data. The path-integral molecular dynamics simulations show that the inclusion of quantum effects results in a less structured liquid with a reduced amount of hydrogen bonding in comparison to its classical analog. The nuclear quantization also leads to a smaller dielectric constant and a larger diffusion coefficient relative to the corresponding classical values. Collective and single molecule time correlation functions show a faster decay than their classical counterparts. Good agreement with the experimental measurements in the low-frequency region is obtained for the quantum infrared spectrum, which also shows a higher intensity and a redshift relative to its classical analog. A modification of the original parametrization of the SPC/Fw model is suggested and tested in order to construct an accurate quantum model, called q-SPC/Fw, for liquid water. The quantum results for several thermodynamic and dynamical properties computed with the new model are shown to be in a significantly better agreement with the experimental data. Finally, a force-matching approach was applied to the q-SPC/Fw model to derive an effective quantum force field for liquid water in which the effects due to the nuclear quantization are explicitly distinguished from those due to the underlying molecular interactions. Thermodynamic and dynamical properties computed using standard classical simulations with this effective quantum potential are found in excellent agreement with those obtained from significantly more computationally demanding full centroid molecular dynamics
An Accurate In Vitro Model of the E. coli Envelope
Clifton, Luke A; Holt, Stephen A; Hughes, Arwel V; Daulton, Emma L; Arunmanee, Wanatchaporn; Heinrich, Frank; Khalid, Syma; Jefferies, Damien; Charlton, Timothy R; Webster, John R P; Kinane, Christian J; Lakey, Jeremy H
2015-01-01
Gram-negative bacteria are an increasingly serious source of antibiotic-resistant infections, partly owing to their characteristic protective envelope. This complex, 20 nm thick barrier includes a highly impermeable, asymmetric bilayer outer membrane (OM), which plays a pivotal role in resisting antibacterial chemotherapy. Nevertheless, the OM molecular structure and its dynamics are poorly understood because the structure is difficult to recreate or study in vitro. The successful formation and characterization of a fully asymmetric model envelope using Langmuir–Blodgett and Langmuir–Schaefer methods is now reported. Neutron reflectivity and isotopic labeling confirmed the expected structure and asymmetry and showed that experiments with antibacterial proteins reproduced published in vivo behavior. By closely recreating natural OM behavior, this model provides a much needed robust system for antibiotic development. PMID:26331292
Kang, Dongwan D.; Froula, Jeff; Egan, Rob; Wang, Zhong
2015-01-01
Grouping large genomic fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions. Because of the complex nature of these communities, existing metagenome binning methods often miss a large number of microbial species. In addition, most of the tools are not scalable to large datasets. Here we introduce automated software called MetaBAT that integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency for accurate metagenome binning. MetaBAT outperforms alternative methods in accuracy and computational efficiency on both synthetic and real metagenome datasets. Lastly, it automatically formsmore » hundreds of high quality genome bins on a very large assembly consisting millions of contigs in a matter of hours on a single node. MetaBAT is open source software and available at https://bitbucket.org/berkeleylab/metabat.« less
Kang, Dongwan D.; Froula, Jeff; Egan, Rob; Wang, Zhong
2015-01-01
Grouping large genomic fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions. Because of the complex nature of these communities, existing metagenome binning methods often miss a large number of microbial species. In addition, most of the tools are not scalable to large datasets. Here we introduce automated software called MetaBAT that integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency for accurate metagenome binning. MetaBAT outperforms alternative methods in accuracy and computational efficiency on both synthetic and real metagenome datasets. Lastly, it automatically forms hundreds of high quality genome bins on a very large assembly consisting millions of contigs in a matter of hours on a single node. MetaBAT is open source software and available at https://bitbucket.org/berkeleylab/metabat.
NASA Astrophysics Data System (ADS)
Rumple, Christopher; Krane, Michael; Richter, Joseph; Craven, Brent
2013-11-01
The mammalian nose is a multi-purpose organ that houses a convoluted airway labyrinth responsible for respiratory air conditioning, filtering of environmental contaminants, and chemical sensing. Because of the complexity of the nasal cavity, the anatomy and function of these upper airways remain poorly understood in most mammals. However, recent advances in high-resolution medical imaging, computational modeling, and experimental flow measurement techniques are now permitting the study of respiratory airflow and olfactory transport phenomena in anatomically-accurate reconstructions of the nasal cavity. Here, we focus on efforts to manufacture an anatomically-accurate transparent model for stereoscopic particle image velocimetry (SPIV) measurements. Challenges in the design and manufacture of an index-matched anatomical model are addressed. PIV measurements are presented, which are used to validate concurrent computational fluid dynamics (CFD) simulations of mammalian nasal airflow. Supported by the National Science Foundation.
NASA Astrophysics Data System (ADS)
Eaton, M.; Pearson, M.; Lee, W.; Pullin, R.
2015-07-01
The ability to accurately locate damage in any given structure is a highly desirable attribute for an effective structural health monitoring system and could help to reduce operating costs and improve safety. This becomes a far greater challenge in complex geometries and materials, such as modern composite airframes. The poor translation of promising laboratory based SHM demonstrators to industrial environments forms a barrier to commercial up take of technology. The acoustic emission (AE) technique is a passive NDT method that detects elastic stress waves released by the growth of damage. It offers very sensitive damage detection, using a sparse array of sensors to detect and globally locate damage within a structure. However its application to complex structures commonly yields poor accuracy due to anisotropic wave propagation and the interruption of wave propagation by structural features such as holes and thickness changes. This work adopts an empirical mapping technique for AE location, known as Delta T Mapping, which uses experimental training data to account for such structural complexities. The technique is applied to a complex geometry composite aerospace structure undergoing certification testing. The component consists of a carbon fibre composite tube with varying wall thickness and multiple holes, that was loaded under bending. The damage location was validated using X-ray CT scanning and the Delta T Mapping technique was shown to improve location accuracy when compared with commercial algorithms. The onset and progression of damage were monitored throughout the test and used to inform future design iterations.
Accurate modelling of flow induced stresses in rigid colloidal aggregates
NASA Astrophysics Data System (ADS)
Vanni, Marco
2015-07-01
A method has been developed to estimate the motion and the internal stresses induced by a fluid flow on a rigid aggregate. The approach couples Stokesian dynamics and structural mechanics in order to take into account accurately the effect of the complex geometry of the aggregates on hydrodynamic forces and the internal redistribution of stresses. The intrinsic error of the method, due to the low-order truncation of the multipole expansion of the Stokes solution, has been assessed by comparison with the analytical solution for the case of a doublet in a shear flow. In addition, it has been shown that the error becomes smaller as the number of primary particles in the aggregate increases and hence it is expected to be negligible for realistic reproductions of large aggregates. The evaluation of internal forces is performed by an adaptation of the matrix methods of structural mechanics to the geometric features of the aggregates and to the particular stress-strain relationship that occurs at intermonomer contacts. A preliminary investigation on the stress distribution in rigid aggregates and their mode of breakup has been performed by studying the response to an elongational flow of both realistic reproductions of colloidal aggregates (made of several hundreds monomers) and highly simplified structures. A very different behaviour has been evidenced between low-density aggregates with isostatic or weakly hyperstatic structures and compact aggregates with highly hyperstatic configuration. In low-density clusters breakup is caused directly by the failure of the most stressed intermonomer contact, which is typically located in the inner region of the aggregate and hence originates the birth of fragments of similar size. On the contrary, breakup of compact and highly cross-linked clusters is seldom caused by the failure of a single bond. When this happens, it proceeds through the removal of a tiny fragment from the external part of the structure. More commonly, however
Debating complexity in modeling
Hunt, Randall J.; Zheng, Chunmiao
1999-01-01
As scientists trying to understand the natural world, how should our effort be apportioned? We know that the natural world is characterized by complex and interrelated processes. Yet do we need to explicitly incorporate these intricacies to perform the tasks we are charged with? In this era of expanding computer power and development of sophisticated preprocessors and postprocessors, are bigger machines making better models? Put another way, do we understand the natural world better now with all these advancements in our simulation ability? Today the public's patience for long-term projects producing indeterminate results is wearing thin. This increases pressure on the investigator to use the appropriate technology efficiently. On the other hand, bringing scientific results into the legal arena opens up a new dimension to the issue: to the layperson, a tool that includes more of the complexity known to exist in the real world is expected to provide the more scientifically valid answer.
Accurate Analytic Results for the Steady State Distribution of the Eigen Model
NASA Astrophysics Data System (ADS)
Huang, Guan-Rong; Saakian, David B.; Hu, Chin-Kun
2016-04-01
Eigen model of molecular evolution is popular in studying complex biological and biomedical systems. Using the Hamilton-Jacobi equation method, we have calculated analytic equations for the steady state distribution of the Eigen model with a relative accuracy of O(1/N), where N is the length of genome. Our results can be applied for the case of small genome length N, as well as the cases where the direct numerics can not give accurate result, e.g., the tail of distribution.
2014-01-01
Predicting the binding affinities of large sets of diverse molecules against a range of macromolecular targets is an extremely challenging task. The scoring functions that attempt such computational prediction are essential for exploiting and analyzing the outputs of docking, which is in turn an important tool in problems such as structure-based drug design. Classical scoring functions assume a predetermined theory-inspired functional form for the relationship between the variables that describe an experimentally determined or modeled structure of a protein–ligand complex and its binding affinity. The inherent problem of this approach is in the difficulty of explicitly modeling the various contributions of intermolecular interactions to binding affinity. New scoring functions based on machine-learning regression models, which are able to exploit effectively much larger amounts of experimental data and circumvent the need for a predetermined functional form, have already been shown to outperform a broad range of state-of-the-art scoring functions in a widely used benchmark. Here, we investigate the impact of the chemical description of the complex on the predictive power of the resulting scoring function using a systematic battery of numerical experiments. The latter resulted in the most accurate scoring function to date on the benchmark. Strikingly, we also found that a more precise chemical description of the protein–ligand complex does not generally lead to a more accurate prediction of binding affinity. We discuss four factors that may contribute to this result: modeling assumptions, codependence of representation and regression, data restricted to the bound state, and conformational heterogeneity in data. PMID:24528282
Hughes, Timothy J; Kandathil, Shaun M; Popelier, Paul L A
2015-02-01
As intermolecular interactions such as the hydrogen bond are electrostatic in origin, rigorous treatment of this term within force field methodologies should be mandatory. We present a method able of accurately reproducing such interactions for seven van der Waals complexes. It uses atomic multipole moments up to hexadecupole moment mapped to the positions of the nuclear coordinates by the machine learning method kriging. Models were built at three levels of theory: HF/6-31G(**), B3LYP/aug-cc-pVDZ and M06-2X/aug-cc-pVDZ. The quality of the kriging models was measured by their ability to predict the electrostatic interaction energy between atoms in external test examples for which the true energies are known. At all levels of theory, >90% of test cases for small van der Waals complexes were predicted within 1 kJ mol(-1), decreasing to 60-70% of test cases for larger base pair complexes. Models built on moments obtained at B3LYP and M06-2X level generally outperformed those at HF level. For all systems the individual interactions were predicted with a mean unsigned error of less than 1 kJ mol(-1). PMID:24274986
Calbo, Joaquín; Ortí, Enrique; Sancho-García, Juan C; Aragó, Juan
2015-03-10
In this work, we present a thorough assessment of the performance of some representative double-hybrid density functionals (revPBE0-DH-NL and B2PLYP-NL) as well as their parent hybrid and GGA counterparts, in combination with the most modern version of the nonlocal (NL) van der Waals correction to describe very large weakly interacting molecular systems dominated by noncovalent interactions. Prior to the assessment, an accurate and homogeneous set of reference interaction energies was computed for the supramolecular complexes constituting the L7 and S12L data sets by using the novel, precise, and efficient DLPNO-CCSD(T) method at the complete basis set limit (CBS). The correction of the basis set superposition error and the inclusion of the deformation energies (for the S12L set) have been crucial for obtaining precise DLPNO-CCSD(T)/CBS interaction energies. Among the density functionals evaluated, the double-hybrid revPBE0-DH-NL and B2PLYP-NL with the three-body dispersion correction provide remarkably accurate association energies very close to the chemical accuracy. Overall, the NL van der Waals approach combined with proper density functionals can be seen as an accurate and affordable computational tool for the modeling of large weakly bonded supramolecular systems. PMID:26579747
Xiao, Suzhi; Tao, Wei; Zhao, Hui
2016-01-01
In order to acquire an accurate three-dimensional (3D) measurement, the traditional fringe projection technique applies complex and laborious procedures to compensate for the errors that exist in the vision system. However, the error sources in the vision system are very complex, such as lens distortion, lens defocus, and fringe pattern nonsinusoidality. Some errors cannot even be explained or rendered with clear expressions and are difficult to compensate directly as a result. In this paper, an approach is proposed that avoids the complex and laborious compensation procedure for error sources but still promises accurate 3D measurement. It is realized by the mathematical model extension technique. The parameters of the extended mathematical model for the ’phase to 3D coordinates transformation’ are derived using the least-squares parameter estimation algorithm. In addition, a phase-coding method based on a frequency analysis is proposed for the absolute phase map retrieval to spatially isolated objects. The results demonstrate the validity and the accuracy of the proposed flexible fringe projection vision system on spatially continuous and discontinuous objects for 3D measurement. PMID:27136553
Highly accurate incremental CCSD(T) calculations on aqua- and amine-complexes
NASA Astrophysics Data System (ADS)
Anacker, Tony; Friedrich, Joachim
2013-07-01
In this work, the accuracy of the second-order incremental expansion using the domain-specific basis set approach is tested for 20 cationic metal-aqua and 25 cationic metal-amine complexes. The accuracy of the approach is analysed by the statistical measures range, arithmetic mean, mean absolute deviation, root mean square deviation and standard deviation. Using these measures we find that the error due to the local approximations decreases with increasing basis set. Next we construct a local virtual space using projected atomic orbitals (PAOs). The accuracy of the incremental series in combination with a distance-based truncation of the PAO space is analysed and compared to the convergence of the incremental series within the domain-specific basis set approach. Furthermore, we establish the recently proposed incremental CCSD(T)|MP2 method as a benchmark method to obtain highly accurate CCSD(T) energies. In combination with a basis set of quintuple-ζ quality we establish benchmarks for the binding energies of the investigated complexes. Finally, we use the inc-CCSD(T)|MP2/aV5Z' binding energies of 45 complexes and 34 dissociation reactions to compute the accuracy of several state of the art density functional theory (DFT) functionals like BP86, B3LYP, CAM-B3LYP, M06, PBE0 and TPSSh. With our implementation of the incremental scheme it was possible to compute the inc-CCSD(T)|MP2/aV5Z' energy for Al(H2O)3+ 25 (6106 AOs).
Coarse-grained red blood cell model with accurate mechanical properties, rheology and dynamics.
Fedosov, Dmitry A; Caswell, Bruce; Karniadakis, George E
2009-01-01
We present a coarse-grained red blood cell (RBC) model with accurate and realistic mechanical properties, rheology and dynamics. The modeled membrane is represented by a triangular mesh which incorporates shear inplane energy, bending energy, and area and volume conservation constraints. The macroscopic membrane elastic properties are imposed through semi-analytic theory, and are matched with those obtained in optical tweezers stretching experiments. Rheological measurements characterized by time-dependent complex modulus are extracted from the membrane thermal fluctuations, and compared with those obtained from the optical magnetic twisting cytometry results. The results allow us to define a meaningful characteristic time of the membrane. The dynamics of RBCs observed in shear flow suggests that a purely elastic model for the RBC membrane is not appropriate, and therefore a viscoelastic model is required. The set of proposed analyses and numerical tests can be used as a complete model testbed in order to calibrate the modeled viscoelastic membranes to accurately represent RBCs in health and disease. PMID:19965026
NASA Astrophysics Data System (ADS)
Shu, Yu-Chen; Chern, I.-Liang; Chang, Chien C.
2014-10-01
Most elliptic interface solvers become complicated for complex interface problems at those “exceptional points” where there are not enough neighboring interior points for high order interpolation. Such complication increases especially in three dimensions. Usually, the solvers are thus reduced to low order accuracy. In this paper, we classify these exceptional points and propose two recipes to maintain order of accuracy there, aiming at improving the previous coupling interface method [26]. Yet the idea is also applicable to other interface solvers. The main idea is to have at least first order approximations for second order derivatives at those exceptional points. Recipe 1 is to use the finite difference approximation for the second order derivatives at a nearby interior grid point, whenever this is possible. Recipe 2 is to flip domain signatures and introduce a ghost state so that a second-order method can be applied. This ghost state is a smooth extension of the solution at the exceptional point from the other side of the interface. The original state is recovered by a post-processing using nearby states and jump conditions. The choice of recipes is determined by a classification scheme of the exceptional points. The method renders the solution and its gradient uniformly second-order accurate in the entire computed domain. Numerical examples are provided to illustrate the second order accuracy of the presently proposed method in approximating the gradients of the original states for some complex interfaces which we had tested previous in two and three dimensions, and a real molecule (1D63) which is double-helix shape and composed of hundreds of atoms.
Shu, Yu-Chen; Chern, I-Liang; Chang, Chien C.
2014-10-15
Most elliptic interface solvers become complicated for complex interface problems at those “exceptional points” where there are not enough neighboring interior points for high order interpolation. Such complication increases especially in three dimensions. Usually, the solvers are thus reduced to low order accuracy. In this paper, we classify these exceptional points and propose two recipes to maintain order of accuracy there, aiming at improving the previous coupling interface method [26]. Yet the idea is also applicable to other interface solvers. The main idea is to have at least first order approximations for second order derivatives at those exceptional points. Recipe 1 is to use the finite difference approximation for the second order derivatives at a nearby interior grid point, whenever this is possible. Recipe 2 is to flip domain signatures and introduce a ghost state so that a second-order method can be applied. This ghost state is a smooth extension of the solution at the exceptional point from the other side of the interface. The original state is recovered by a post-processing using nearby states and jump conditions. The choice of recipes is determined by a classification scheme of the exceptional points. The method renders the solution and its gradient uniformly second-order accurate in the entire computed domain. Numerical examples are provided to illustrate the second order accuracy of the presently proposed method in approximating the gradients of the original states for some complex interfaces which we had tested previous in two and three dimensions, and a real molecule ( (1D63)) which is double-helix shape and composed of hundreds of atoms.
Fast and accurate analytical model to solve inverse problem in SHM using Lamb wave propagation
NASA Astrophysics Data System (ADS)
Poddar, Banibrata; Giurgiutiu, Victor
2016-04-01
Lamb wave propagation is at the center of attention of researchers for structural health monitoring of thin walled structures. This is due to the fact that Lamb wave modes are natural modes of wave propagation in these structures with long travel distances and without much attenuation. This brings the prospect of monitoring large structure with few sensors/actuators. However the problem of damage detection and identification is an "inverse problem" where we do not have the luxury to know the exact mathematical model of the system. On top of that the problem is more challenging due to the confounding factors of statistical variation of the material and geometric properties. Typically this problem may also be ill posed. Due to all these complexities the direct solution of the problem of damage detection and identification in SHM is impossible. Therefore an indirect method using the solution of the "forward problem" is popular for solving the "inverse problem". This requires a fast forward problem solver. Due to the complexities involved with the forward problem of scattering of Lamb waves from damages researchers rely primarily on numerical techniques such as FEM, BEM, etc. But these methods are slow and practically impossible to be used in structural health monitoring. We have developed a fast and accurate analytical forward problem solver for this purpose. This solver, CMEP (complex modes expansion and vector projection), can simulate scattering of Lamb waves from all types of damages in thin walled structures fast and accurately to assist the inverse problem solver.
Accurate determination of the complex refractive index of solid tissue-equivalent phantom
NASA Astrophysics Data System (ADS)
Wang, Jin; Ye, Qing; Deng, Zhichao; Zhou, Wenyuan; Zhang, Chunping; Tian, Jianguo
2012-06-01
Tissue-equivalent phantom is becoming widespread as a substitute in the biological field to verify optical theories, test measuring systems and study the tissue performances for varying boundary conditions, sample size and shape at a quantitative level. Compared with phantoms made with Intralipid solution, ink and other liquid substances, phantom in solid state is stable over time, reproducible, easy to handle and has been testified to be a suitable optical simulator in the visible and near-infrared region. We present accurate determination of the complex refractive index (RI) of a solid tissueequivalent phantom using extended derivative total reflection method (EDTRM). Scattering phantoms in solid state were measured for p-polarized and s-polarized incident light respectively. The reflectance curves of the sample as a function of incident angle were recorded. The real part of RI is directly determined by derivative of the reflectance curve, and the imaginary part is obtained from nonlinear fitting based on the Fresnel equation and Nelder-Mead simplex method. The EDTRM method is applicable for RI measurement of high scattering media such as biotissue, solid tissue-equivalent phantom and bulk material. The obtained RI information can be used in the study of tissue optics and biomedical field.
Subramanian, K R; Thubrikar, M J; Fowler, B; Mostafavi, M T; Funk, M W
2000-01-01
We present a technique that accurately reconstructs complex three dimensional blood vessel geometry from 2D intravascular ultrasound (IVUS) images. Biplane x-ray fluoroscopy is used to image the ultrasound catheter tip at a few key points along its path as the catheter is pulled through the blood vessel. An interpolating spline describes the continuous catheter path. The IVUS images are located orthogonal to the path, resulting in a non-uniform structured scalar volume of echo densities. Isocontour surfaces are used to view the vessel geometry, while transparency and clipping enable interactive exploration of interior structures. The two geometries studied are a bovine artery vascular graft having U-shape and a constriction, and a canine carotid artery having multiple branches and a constriction. Accuracy of the reconstructions is established by comparing the reconstructions to (1) silicone moulds of the vessel interior, (2) biplane x-ray images, and (3) the original echo images. Excellent shape and geometry correspondence was observed in both geometries. Quantitative measurements made at key locations of the 3D reconstructions also were in good agreement with those made in silicone moulds. The proposed technique is easily adoptable in clinical practice, since it uses x-rays with minimal exposure and existing IVUS technology. PMID:11105284
Dicer–TRBP complex formation ensures accurate mammalian microRNA biogenesis
Wilson, Ross C.; Tambe, Akshay; Kidwell, Mary Anne; Noland, Cameron L.; Schneider, Catherine P.; Doudna, Jennifer A.
2014-01-01
Summary RNA-mediated gene silencing in human cells requires the accurate generation of ∼22-nucleotide microRNAs (miRNAs) from double-stranded RNA substrates by the endonuclease Dicer. Although the phylogenetically conserved RNA-binding proteins TRBP and PACT are known to contribute to this process, their mode of Dicer binding and their genome-wide effects on miRNA processing have not been determined. We solved the crystal structure of a human Dicer–TRBP interaction complex comprising two domains of previously unknown structure. Interface residues conserved between TRBP and PACT show that the proteins bind to Dicer in a similar manner and by mutual exclusion. Based on the structure, a catalytically active Dicer that cannot bind TRBP or PACT was designed and introduced into Dicer-deficient mammalian cells, revealing selective defects in guide strand selection. These results demonstrate the role of Dicer-associated RNA binding proteins in maintenance of gene silencing fidelity. PMID:25557550
New process model proves accurate in tests on catalytic reformer
Aguilar-Rodriguez, E.; Ancheyta-Juarez, J. )
1994-07-25
A mathematical model has been devised to represent the process that takes place in a fixed-bed, tubular, adiabatic catalytic reforming reactor. Since its development, the model has been applied to the simulation of a commercial semiregenerative reformer. The development of mass and energy balances for this reformer led to a model that predicts both concentration and temperature profiles along the reactor. A comparison of the model's results with experimental data illustrates its accuracy at predicting product profiles. Simple steps show how the model can be applied to simulate any fixed-bed catalytic reformer.
Coupling Efforts to the Accurate and Efficient Tsunami Modelling System
NASA Astrophysics Data System (ADS)
Son, S.
2015-12-01
In the present study, we couple two different types of tsunami models, i.e., nondispersive shallow water model of characteristic form(MOST ver.4) and dispersive Boussinesq model of non-characteristic form(Son et al. (2011)) in an attempt to improve modelling accuracy and efficiency. Since each model deals with different type of primary variables, additional care on matching boundary condition is required. Using an absorbing-generating boundary condition developed by Van Dongeren and Svendsen(1997), model coupling and integration is achieved. Characteristic variables(i.e., Riemann invariants) in MOST are converted to non-characteristic variables for Boussinesq solver without any loss of physical consistency. Established modelling system has been validated through typical test problems to realistic tsunami events. Simulated results reveal good performance of developed modelling system. Since coupled modelling system provides advantageous flexibility feature during implementation, great efficiencies and accuracies are expected to be gained through spot-focusing application of Boussinesq model inside the entire domain of tsunami propagation.
An Approach to More Accurate Model Systems for Purple Acid Phosphatases (PAPs).
Bernhardt, Paul V; Bosch, Simone; Comba, Peter; Gahan, Lawrence R; Hanson, Graeme R; Mereacre, Valeriu; Noble, Christopher J; Powell, Annie K; Schenk, Gerhard; Wadepohl, Hubert
2015-08-01
The active site of mammalian purple acid phosphatases (PAPs) have a dinuclear iron site in two accessible oxidation states (Fe(III)2 and Fe(III)Fe(II)), and the heterovalent is the active form, involved in the regulation of phosphate and phosphorylated metabolite levels in a wide range of organisms. Therefore, two sites with different coordination geometries to stabilize the heterovalent active form and, in addition, with hydrogen bond donors to enable the fixation of the substrate and release of the product, are believed to be required for catalytically competent model systems. Two ligands and their dinuclear iron complexes have been studied in detail. The solid-state structures and properties, studied by X-ray crystallography, magnetism, and Mössbauer spectroscopy, and the solution structural and electronic properties, investigated by mass spectrometry, electronic, nuclear magnetic resonance (NMR), electron paramagnetic resonance (EPR), and Mössbauer spectroscopies and electrochemistry, are discussed in detail in order to understand the structures and relative stabilities in solution. In particular, with one of the ligands, a heterovalent Fe(III)Fe(II) species has been produced by chemical oxidation of the Fe(II)2 precursor. The phosphatase reactivities of the complexes, in particular, also of the heterovalent complex, are reported. These studies include pH-dependent as well as substrate concentration dependent studies, leading to pH profiles, catalytic efficiencies and turnover numbers, and indicate that the heterovalent diiron complex discussed here is an accurate PAP model system. PMID:26196255
When do perturbative approaches accurately capture the dynamics of complex quantum systems?
Fruchtman, Amir; Lambert, Neill; Gauger, Erik M.
2016-01-01
Understanding the dynamics of higher-dimensional quantum systems embedded in a complex environment remains a significant theoretical challenge. While several approaches yielding numerically converged solutions exist, these are computationally expensive and often provide only limited physical insight. Here we address the question: when do more intuitive and simpler-to-compute second-order perturbative approaches provide adequate accuracy? We develop a simple analytical criterion and verify its validity for the case of the much-studied FMO dynamics as well as the canonical spin-boson model. PMID:27335176
Accurate, multi-kb reads resolve complex populations and detect rare microorganisms
Sharon, Itai; Kertesz, Michael; Hug, Laura A.; Pushkarev, Dmitry; Blauwkamp, Timothy A.; Castelle, Cindy J.; Amirebrahimi, Mojgan; Thomas, Brian C.; Burstein, David; Tringe, Susannah G.; Williams, Kenneth H.
2015-01-01
Accurate evaluation of microbial communities is essential for understanding global biogeochemical processes and can guide bioremediation and medical treatments. Metagenomics is most commonly used to analyze microbial diversity and metabolic potential, but assemblies of the short reads generated by current sequencing platforms may fail to recover heterogeneous strain populations and rare organisms. Here we used short (150-bp) and long (multi-kb) synthetic reads to evaluate strain heterogeneity and study microorganisms at low abundance in complex microbial communities from terrestrial sediments. The long-read data revealed multiple (probably dozens of) closely related species and strains from previously undescribed Deltaproteobacteria and Aminicenantes (candidate phylum OP8). Notably, these are the most abundant organisms in the communities, yet short-read assemblies achieved only partial genome coverage, mostly in the form of short scaffolds (N50 = ∼2200 bp). Genome architecture and metabolic potential for these lineages were reconstructed using a new synteny-based method. Analysis of long-read data also revealed thousands of species whose abundances were <0.1% in all samples. Most of the organisms in this “long tail” of rare organisms belong to phyla that are also represented by abundant organisms. Genes encoding glycosyl hydrolases are significantly more abundant than expected in rare genomes, suggesting that rare species may augment the capability for carbon turnover and confer resilience to changing environmental conditions. Overall, the study showed that a diversity of closely related strains and rare organisms account for a major portion of the communities. These are probably common features of many microbial communities and can be effectively studied using a combination of long and short reads. PMID:25665577
Felmy, Andrew R.; Mason, Marvin; Qafoku, Odeta; Xia, Yuanxian; Wang, Zheming; MacLean, Graham
2003-03-27
Developing accurate thermodynamic models for predicting the chemistry of the high-level waste tanks at Hanford is an extremely daunting challenge in electrolyte and radionuclide chemistry. These challenges stem from the extremely high ionic strength of the tank waste supernatants, presence of chelating agents in selected tanks, wide temperature range in processing conditions and the presence of important actinide species in multiple oxidation states. This presentation summarizes progress made to date in developing accurate models for these tank waste solutions, how these data are being used at Hanford and the important challenges that remain. New thermodynamic measurements on Sr and actinide complexation with specific chelating agents (EDTA, HEDTA and gluconate) will also be presented.
Beyond Ellipse(s): Accurately Modelling the Isophotal Structure of Galaxies with ISOFIT and CMODEL
NASA Astrophysics Data System (ADS)
Ciambur, B. C.
2015-09-01
This work introduces a new fitting formalism for isophotes that enables more accurate modeling of galaxies with non-elliptical shapes, such as disk galaxies viewed edge-on or galaxies with X-shaped/peanut bulges. Within this scheme, the angular parameter that defines quasi-elliptical isophotes is transformed from the commonly used, but inappropriate, polar coordinate to the “eccentric anomaly.” This provides a superior description of deviations from ellipticity, better capturing the true isophotal shape. Furthermore, this makes it possible to accurately recover both the surface brightness profile, using the correct azimuthally averaged isophote, and the two-dimensional model of any galaxy: the hitherto ubiquitous, but artificial, cross-like features in residual images are completely removed. The formalism has been implemented into the Image Reduction and Analysis Facility tasks Ellipse and Bmodel to create the new tasks “Isofit,” and “Cmodel.” The new tools are demonstrated here with application to five galaxies, chosen to be representative case-studies for several areas where this technique makes it possible to gain new scientific insight. Specifically: properly quantifying boxy/disky isophotes via the fourth harmonic order in edge-on galaxies, quantifying X-shaped/peanut bulges, higher-order Fourier moments for modeling bars in disks, and complex isophote shapes. Higher order (n > 4) harmonics now become meaningful and may correlate with structural properties, as boxyness/diskyness is known to do. This work also illustrates how the accurate construction, and subtraction, of a model from a galaxy image facilitates the identification and recovery of over-lapping sources such as globular clusters and the optical counterparts of X-ray sources.
Magnetic field models of nine CP stars from "accurate" measurements
NASA Astrophysics Data System (ADS)
Glagolevskij, Yu. V.
2013-01-01
The dipole models of magnetic fields in nine CP stars are constructed based on the measurements of metal lines taken from the literature, and performed by the LSD method with an accuracy of 10-80 G. The model parameters are compared with the parameters obtained for the same stars from the hydrogen line measurements. For six out of nine stars the same type of structure was obtained. Some parameters, such as the field strength at the poles B p and the average surface magnetic field B s differ considerably in some stars due to differences in the amplitudes of phase dependences B e (Φ) and B s (Φ), obtained by different authors. It is noted that a significant increase in the measurement accuracy has little effect on the modelling of the large-scale structures of the field. By contrast, it is more important to construct the shape of the phase dependence based on a fairly large number of field measurements, evenly distributed by the rotation period phases. It is concluded that the Zeeman component measurement methods have a strong effect on the shape of the phase dependence, and that the measurements of the magnetic field based on the lines of hydrogen are more preferable for modelling the large-scale structures of the field.
NASA Astrophysics Data System (ADS)
Akdim, Mohamed Reda
2003-09-01
Nowadays plasmas are used for various applications such as the fabrication of silicon solar cells, integrated circuits, coatings and dental cleaning. In the case of a processing plasma, e.g. for the fabrication of amorphous silicon solar cells, a mixture of silane and hydrogen gas is injected in a reactor. These gases are decomposed by making a plasma. A plasma with a low degree of ionization (typically 10_5) is usually made in a reactor containing two electrodes driven by a radio-frequency (RF) power source in the megahertz range. Under the right circumstances the radicals, neutrals and ions can react further to produce nanometer sized dust particles. The particles can stick to the surface and thereby contribute to a higher deposition rate. Another possibility is that the nanometer sized particles coagulate and form larger micron sized particles. These particles obtain a high negative charge, due to their large radius and are usually trapped in a radiofrequency plasma. The electric field present in the discharge sheaths causes the entrapment. Such plasmas are called dusty or complex plasmas. In this thesis numerical models are presented which describe dusty plasmas in reactive and nonreactive plasmas. We started first with the development of a simple one-dimensional silane fluid model where a dusty radio-frequency silane/hydrogen discharge is simulated. In the model, discharge quantities like the fluxes, densities and electric field are calculated self-consistently. A radius and an initial density profile for the spherical dust particles are given and the charge and the density of the dust are calculated with an iterative method. During the transport of the dust, its charge is kept constant in time. The dust influences the electric field distribution through its charge and the density of the plasma through recombination of positive ions and electrons at its surface. In the model this process gives an extra production of silane radicals, since the growth of dust is
NASA Astrophysics Data System (ADS)
Rumple, C.; Richter, J.; Craven, B. A.; Krane, M.
2012-11-01
A summary of the research being carried out by our multidisciplinary team to better understand the form and function of the nose in different mammalian species that include humans, carnivores, ungulates, rodents, and marine animals will be presented. The mammalian nose houses a convoluted airway labyrinth, where two hallmark features of mammals occur, endothermy and olfaction. Because of the complexity of the nasal cavity, the anatomy and function of these upper airways remain poorly understood in most mammals. However, recent advances in high-resolution medical imaging, computational modeling, and experimental flow measurement techniques are now permitting the study of airflow and respiratory and olfactory transport phenomena in anatomically-accurate reconstructions of the nasal cavity. Here, we focus on efforts to manufacture transparent, anatomically-accurate models for stereo particle image velocimetry (SPIV) measurements of nasal airflow. Challenges in the design and manufacture of index-matched anatomical models are addressed and preliminary SPIV measurements are presented. Such measurements will constitute a validation database for concurrent computational fluid dynamics (CFD) simulations of mammalian respiration and olfaction. Supported by the National Science Foundation.
Leidenfrost effect: accurate drop shape modeling and new scaling laws
NASA Astrophysics Data System (ADS)
Sobac, Benjamin; Rednikov, Alexey; Dorbolo, Stéphane; Colinet, Pierre
2014-11-01
In this study, we theoretically investigate the shape of a drop in a Leidenfrost state, focusing on the geometry of the vapor layer. The drop geometry is modeled by numerically matching the solution of the hydrostatic shape of a superhydrophobic drop (for the upper part) with the solution of the lubrication equation of the vapor flow underlying the drop (for the bottom part). The results highlight that the vapor layer, fed by evaporation, forms a concave depression in the drop interface that becomes increasingly marked with the drop size. The vapor layer then consists of a gas pocket in the center and a thin annular neck surrounding it. The film thickness increases with the size of the drop, and the thickness at the neck appears to be of the order of 10--100 μm in the case of water. The model is compared to recent experimental results [Burton et al., Phys. Rev. Lett., 074301 (2012)] and shows an excellent agreement, without any fitting parameter. New scaling laws also emerge from this model. The geometry of the vapor pocket is only weakly dependent on the superheat (and thus on the evaporation rate), this weak dependence being more pronounced in the neck region. In turn, the vapor layer characteristics strongly depend on the drop size.
Accurate structure prediction of peptide–MHC complexes for identifying highly immunogenic antigens
Park, Min-Sun; Park, Sung Yong; Miller, Keith R.; Collins, Edward J.; Lee, Ha Youn
2013-11-01
Designing an optimal HIV-1 vaccine faces the challenge of identifying antigens that induce a broad immune capacity. One factor to control the breadth of T cell responses is the surface morphology of a peptide–MHC complex. Here, we present an in silico protocol for predicting peptide–MHC structure. A robust signature of a conformational transition was identified during all-atom molecular dynamics, which results in a model with high accuracy. A large test set was used in constructing our protocol and we went another step further using a blind test with a wild-type peptide and two highly immunogenic mutants, which predicted substantial conformational changes in both mutants. The center residues at position five of the analogs were configured to be accessible to solvent, forming a prominent surface, while the residue of the wild-type peptide was to point laterally toward the side of the binding cleft. We then experimentally determined the structures of the blind test set, using high resolution of X-ray crystallography, which verified predicted conformational changes. Our observation strongly supports a positive association of the surface morphology of a peptide–MHC complex to its immunogenicity. Our study offers the prospect of enhancing immunogenicity of vaccines by identifying MHC binding immunogens.
Ye, Jing; Wang, Jianling; Li, Qiwei; Dong, Xiawei; Ge, Wei; Chen, Yun; Jiang, Xuerui; Liu, Hongde; Jiang, Hui; Wang, Xuemei
2016-04-22
A new and facile method for rapidly and accurately achieving tumor targeting fluorescent images has been explored using a specifically biosynthesized europium (Eu) complex in vivo and in vitro. It demonstrated that a fluorescent Eu complex could be bio-synthesized through a spontaneous molecular process in cancerous cells and tumors, but not prepared in normal cells and tissues. In addition, the proteomics analyses show that some biological pathways of metabolism, especially for NADPH production and glutamine metabolism, are remarkably affected during the relevant biosynthesis process, where molecular precursors of europium ions are reduced to fluorescent europium complexes inside cancerous cells or tumor tissues. These results proved that the specific self-biosynthesis of a fluorescent Eu complex by cancer cells or tumor tissues can provide a new strategy for accurate diagnosis and treatment strategies in the early stages of cancers and thus is beneficial for realizing precise surgical intervention based on the relevant cheap and readily available agents. PMID:26810592
NASA Astrophysics Data System (ADS)
Mead, A. J.; Peacock, J. A.; Heymans, C.; Joudaki, S.; Heavens, A. F.
2015-12-01
We present an optimized variant of the halo model, designed to produce accurate matter power spectra well into the non-linear regime for a wide range of cosmological models. To do this, we introduce physically motivated free parameters into the halo-model formalism and fit these to data from high-resolution N-body simulations. For a variety of Λ cold dark matter (ΛCDM) and wCDM models, the halo-model power is accurate to ≃ 5 per cent for k ≤ 10h Mpc-1 and z ≤ 2. An advantage of our new halo model is that it can be adapted to account for the effects of baryonic feedback on the power spectrum. We demonstrate this by fitting the halo model to power spectra from the OWLS (OverWhelmingly Large Simulations) hydrodynamical simulation suite via parameters that govern halo internal structure. We are able to fit all feedback models investigated at the 5 per cent level using only two free parameters, and we place limits on the range of these halo parameters for feedback models investigated by the OWLS simulations. Accurate predictions to high k are vital for weak-lensing surveys, and these halo parameters could be considered nuisance parameters to marginalize over in future analyses to mitigate uncertainty regarding the details of feedback. Finally, we investigate how lensing observables predicted by our model compare to those from simulations and from HALOFIT for a range of k-cuts and feedback models and quantify the angular scales at which these effects become important. Code to calculate power spectra from the model presented in this paper can be found at https://github.com/alexander-mead/hmcode.
Modelling Canopy Flows over Complex Terrain
NASA Astrophysics Data System (ADS)
Grant, Eleanor R.; Ross, Andrew N.; Gardiner, Barry A.
2016-06-01
Recent studies of flow over forested hills have been motivated by a number of important applications including understanding CO_2 and other gaseous fluxes over forests in complex terrain, predicting wind damage to trees, and modelling wind energy potential at forested sites. Current modelling studies have focussed almost exclusively on highly idealized, and usually fully forested, hills. Here, we present model results for a site on the Isle of Arran, Scotland with complex terrain and heterogeneous forest canopy. The model uses an explicit representation of the canopy and a 1.5-order turbulence closure for flow within and above the canopy. The validity of the closure scheme is assessed using turbulence data from a field experiment before comparing predictions of the full model with field observations. For near-neutral stability, the results compare well with the observations, showing that such a relatively simple canopy model can accurately reproduce the flow patterns observed over complex terrain and realistic, variable forest cover, while at the same time remaining computationally feasible for real case studies. The model allows closer examination of the flow separation observed over complex forested terrain. Comparisons with model simulations using a roughness length parametrization show significant differences, particularly with respect to flow separation, highlighting the need to explicitly model the forest canopy if detailed predictions of near-surface flow around forests are required.
Digitalized accurate modeling of SPCB with multi-spiral surface based on CPC algorithm
NASA Astrophysics Data System (ADS)
Huang, Yanhua; Gu, Lizhi
2015-09-01
The main methods of the existing multi-spiral surface geometry modeling include spatial analytic geometry algorithms, graphical method, interpolation and approximation algorithms. However, there are some shortcomings in these modeling methods, such as large amount of calculation, complex process, visible errors, and so on. The above methods have, to some extent, restricted the design and manufacture of the premium and high-precision products with spiral surface considerably. This paper introduces the concepts of the spatially parallel coupling with multi-spiral surface and spatially parallel coupling body. The typical geometry and topological features of each spiral surface forming the multi-spiral surface body are determined, by using the extraction principle of datum point cluster, the algorithm of coupling point cluster by removing singular point, and the "spatially parallel coupling" principle based on the non-uniform B-spline for each spiral surface. The orientation and quantitative relationships of datum point cluster and coupling point cluster in Euclidean space are determined accurately and in digital description and expression, coupling coalescence of the surfaces with multi-coupling point clusters under the Pro/E environment. The digitally accurate modeling of spatially parallel coupling body with multi-spiral surface is realized. The smooth and fairing processing is done to the three-blade end-milling cutter's end section area by applying the principle of spatially parallel coupling with multi-spiral surface, and the alternative entity model is processed in the four axis machining center after the end mill is disposed. And the algorithm is verified and then applied effectively to the transition area among the multi-spiral surface. The proposed model and algorithms may be used in design and manufacture of the multi-spiral surface body products, as well as in solving essentially the problems of considerable modeling errors in computer graphics and
Wijma, Hein J; Marrink, Siewert J; Janssen, Dick B
2014-07-28
Computational approaches could decrease the need for the laborious high-throughput experimental screening that is often required to improve enzymes by mutagenesis. Here, we report that using multiple short molecular dynamics (MD) simulations makes it possible to accurately model enantioselectivity for large numbers of enzyme-substrate combinations at low computational costs. We chose four different haloalkane dehalogenases as model systems because of the availability of a large set of experimental data on the enantioselective conversion of 45 different substrates. To model the enantioselectivity, we quantified the frequency of occurrence of catalytically productive conformations (near attack conformations) for pairs of enantiomers during MD simulations. We found that the angle of nucleophilic attack that leads to carbon-halogen bond cleavage was a critical variable that limited the occurrence of productive conformations; enantiomers for which this angle reached values close to 180° were preferentially converted. A cluster of 20-40 very short (10 ps) MD simulations allowed adequate conformational sampling and resulted in much better agreement to experimental enantioselectivities than single long MD simulations (22 ns), while the computational costs were 50-100 fold lower. With single long MD simulations, the dynamics of enzyme-substrate complexes remained confined to a conformational subspace that rarely changed significantly, whereas with multiple short MD simulations a larger diversity of conformations of enzyme-substrate complexes was observed. PMID:24916632
Construction of feasible and accurate kinetic models of metabolism: A Bayesian approach
Saa, Pedro A.; Nielsen, Lars K.
2016-01-01
Kinetic models are essential to quantitatively understand and predict the behaviour of metabolic networks. Detailed and thermodynamically feasible kinetic models of metabolism are inherently difficult to formulate and fit. They have a large number of heterogeneous parameters, are non-linear and have complex interactions. Many powerful fitting strategies are ruled out by the intractability of the likelihood function. Here, we have developed a computational framework capable of fitting feasible and accurate kinetic models using Approximate Bayesian Computation. This framework readily supports advanced modelling features such as model selection and model-based experimental design. We illustrate this approach on the tightly-regulated mammalian methionine cycle. Sampling from the posterior distribution, the proposed framework generated thermodynamically feasible parameter samples that converged on the true values, and displayed remarkable prediction accuracy in several validation tests. Furthermore, a posteriori analysis of the parameter distributions enabled appraisal of the systems properties of the network (e.g., control structure) and key metabolic regulations. Finally, the framework was used to predict missing allosteric interactions. PMID:27417285
An Accurate Model for Biomolecular Helices and Its Application to Helix Visualization
Wang, Lincong; Qiao, Hui; Cao, Chen; Xu, Shutan; Zou, Shuxue
2015-01-01
Helices are the most abundant secondary structural elements in proteins and the structural forms assumed by double stranded DNAs (dsDNA). Though the mathematical expression for a helical curve is simple, none of the previous models for the biomolecular helices in either proteins or DNAs use a genuine helical curve, likely because of the complexity of fitting backbone atoms to helical curves. In this paper we model a helix as a series of different but all bona fide helical curves; each one best fits the coordinates of four consecutive backbone Cα atoms for a protein or P atoms for a DNA molecule. An implementation of the model demonstrates that it is more accurate than the previous ones for the description of the deviation of a helix from a standard helical curve. Furthermore, the accuracy of the model makes it possible to correlate deviations with structural and functional significance. When applied to helix visualization, the ribbon diagrams generated by the model are less choppy or have smaller side chain detachment than those by the previous visualization programs that typically model a helix as a series of low-degree splines. PMID:26126117
Davis, J.L.; Grant, J.W.
2014-01-01
Anatomically correct turtle utricle geometry was incorporated into two finite element models. The geometrically accurate model included appropriately shaped macular surface and otoconial layer, compact gel and column filament (or shear) layer thicknesses and thickness distributions. The first model included a shear layer where the effects of hair bundle stiffness was included as part of the shear layer modulus. This solid model’s undamped natural frequency was matched to an experimentally measured value. This frequency match established a realistic value of the effective shear layer Young’s modulus of 16 Pascals. We feel this is the most accurate prediction of this shear layer modulus and fits with other estimates (Kondrachuk, 2001b). The second model incorporated only beam elements in the shear layer to represent hair cell bundle stiffness. The beam element stiffness’s were further distributed to represent their location on the neuroepithelial surface. Experimentally measured striola hair cell bundles mean stiffness values were used in the striolar region and the mean extrastriola hair cell bundles stiffness values were used in this region. The results from this second model indicated that hair cell bundle stiffness contributes approximately 40% to the overall stiffness of the shear layer– hair cell bundle complex. This analysis shows that high mass saccules, in general, achieve high gain at the sacrifice of frequency bandwidth. We propose the mechanism by which this can be achieved is through increase the otoconial layer mass. The theoretical difference in gain (deflection per acceleration) is shown for saccules with large otoconial layer mass relative to saccules and utricles with small otoconial layer mass. Also discussed is the necessity of these high mass saccules to increase their overall system shear layer stiffness. Undamped natural frequencies and mode shapes for these sensors are shown. PMID:25445820
Constructing minimal models for complex system dynamics
NASA Astrophysics Data System (ADS)
Barzel, Baruch; Liu, Yang-Yu; Barabási, Albert-László
2015-05-01
One of the strengths of statistical physics is the ability to reduce macroscopic observations into microscopic models, offering a mechanistic description of a system's dynamics. This paradigm, rooted in Boltzmann's gas theory, has found applications from magnetic phenomena to subcellular processes and epidemic spreading. Yet, each of these advances were the result of decades of meticulous model building and validation, which are impossible to replicate in most complex biological, social or technological systems that lack accurate microscopic models. Here we develop a method to infer the microscopic dynamics of a complex system from observations of its response to external perturbations, allowing us to construct the most general class of nonlinear pairwise dynamics that are guaranteed to recover the observed behaviour. The result, which we test against both numerical and empirical data, is an effective dynamic model that can predict the system's behaviour and provide crucial insights into its inner workings.
Seth, Ajay; Matias, Ricardo; Veloso, António P.; Delp, Scott L.
2016-01-01
The complexity of shoulder mechanics combined with the movement of skin relative to the scapula makes it difficult to measure shoulder kinematics with sufficient accuracy to distinguish between symptomatic and asymptomatic individuals. Multibody skeletal models can improve motion capture accuracy by reducing the space of possible joint movements, and models are used widely to improve measurement of lower limb kinematics. In this study, we developed a rigid-body model of a scapulothoracic joint to describe the kinematics of the scapula relative to the thorax. This model describes scapular kinematics with four degrees of freedom: 1) elevation and 2) abduction of the scapula on an ellipsoidal thoracic surface, 3) upward rotation of the scapula normal to the thoracic surface, and 4) internal rotation of the scapula to lift the medial border of the scapula off the surface of the thorax. The surface dimensions and joint axes can be customized to match an individual’s anthropometry. We compared the model to “gold standard” bone-pin kinematics collected during three shoulder tasks and found modeled scapular kinematics to be accurate to within 2mm root-mean-squared error for individual bone-pin markers across all markers and movement tasks. As an additional test, we added random and systematic noise to the bone-pin marker data and found that the model reduced kinematic variability due to noise by 65% compared to Euler angles computed without the model. Our scapulothoracic joint model can be used for inverse and forward dynamics analyses and to compute joint reaction loads. The computational performance of the scapulothoracic joint model is well suited for real-time applications; it is freely available for use with OpenSim 3.2, and is customizable and usable with other OpenSim models. PMID:26734761
Seth, Ajay; Matias, Ricardo; Veloso, António P; Delp, Scott L
2016-01-01
The complexity of shoulder mechanics combined with the movement of skin relative to the scapula makes it difficult to measure shoulder kinematics with sufficient accuracy to distinguish between symptomatic and asymptomatic individuals. Multibody skeletal models can improve motion capture accuracy by reducing the space of possible joint movements, and models are used widely to improve measurement of lower limb kinematics. In this study, we developed a rigid-body model of a scapulothoracic joint to describe the kinematics of the scapula relative to the thorax. This model describes scapular kinematics with four degrees of freedom: 1) elevation and 2) abduction of the scapula on an ellipsoidal thoracic surface, 3) upward rotation of the scapula normal to the thoracic surface, and 4) internal rotation of the scapula to lift the medial border of the scapula off the surface of the thorax. The surface dimensions and joint axes can be customized to match an individual's anthropometry. We compared the model to "gold standard" bone-pin kinematics collected during three shoulder tasks and found modeled scapular kinematics to be accurate to within 2 mm root-mean-squared error for individual bone-pin markers across all markers and movement tasks. As an additional test, we added random and systematic noise to the bone-pin marker data and found that the model reduced kinematic variability due to noise by 65% compared to Euler angles computed without the model. Our scapulothoracic joint model can be used for inverse and forward dynamics analyses and to compute joint reaction loads. The computational performance of the scapulothoracic joint model is well suited for real-time applications; it is freely available for use with OpenSim 3.2, and is customizable and usable with other OpenSim models. PMID:26734761
2011-01-01
Background Data assimilation refers to methods for updating the state vector (initial condition) of a complex spatiotemporal model (such as a numerical weather model) by combining new observations with one or more prior forecasts. We consider the potential feasibility of this approach for making short-term (60-day) forecasts of the growth and spread of a malignant brain cancer (glioblastoma multiforme) in individual patient cases, where the observations are synthetic magnetic resonance images of a hypothetical tumor. Results We apply a modern state estimation algorithm (the Local Ensemble Transform Kalman Filter), previously developed for numerical weather prediction, to two different mathematical models of glioblastoma, taking into account likely errors in model parameters and measurement uncertainties in magnetic resonance imaging. The filter can accurately shadow the growth of a representative synthetic tumor for 360 days (six 60-day forecast/update cycles) in the presence of a moderate degree of systematic model error and measurement noise. Conclusions The mathematical methodology described here may prove useful for other modeling efforts in biology and oncology. An accurate forecast system for glioblastoma may prove useful in clinical settings for treatment planning and patient counseling. Reviewers This article was reviewed by Anthony Almudevar, Tomas Radivoyevitch, and Kristin Swanson (nominated by Georg Luebeck). PMID:22185645
Accurate design of megadalton-scale two-component icosahedral protein complexes.
Bale, Jacob B; Gonen, Shane; Liu, Yuxi; Sheffler, William; Ellis, Daniel; Thomas, Chantz; Cascio, Duilio; Yeates, Todd O; Gonen, Tamir; King, Neil P; Baker, David
2016-07-22
Nature provides many examples of self- and co-assembling protein-based molecular machines, including icosahedral protein cages that serve as scaffolds, enzymes, and compartments for essential biochemical reactions and icosahedral virus capsids, which encapsidate and protect viral genomes and mediate entry into host cells. Inspired by these natural materials, we report the computational design and experimental characterization of co-assembling, two-component, 120-subunit icosahedral protein nanostructures with molecular weights (1.8 to 2.8 megadaltons) and dimensions (24 to 40 nanometers in diameter) comparable to those of small viral capsids. Electron microscopy, small-angle x-ray scattering, and x-ray crystallography show that 10 designs spanning three distinct icosahedral architectures form materials closely matching the design models. In vitro assembly of icosahedral complexes from independently purified components occurs rapidly, at rates comparable to those of viral capsids, and enables controlled packaging of molecular cargo through charge complementarity. The ability to design megadalton-scale materials with atomic-level accuracy and controllable assembly opens the door to a new generation of genetically programmable protein-based molecular machines. PMID:27463675
Modeling complexity in biology
NASA Astrophysics Data System (ADS)
Louzoun, Yoram; Solomon, Sorin; Atlan, Henri; Cohen, Irun. R.
2001-08-01
Biological systems, unlike physical or chemical systems, are characterized by the very inhomogeneous distribution of their components. The immune system, in particular, is notable for self-organizing its structure. Classically, the dynamics of natural systems have been described using differential equations. But, differential equation models fail to account for the emergence of large-scale inhomogeneities and for the influence of inhomogeneity on the overall dynamics of biological systems. Here, we show that a microscopic simulation methodology enables us to model the emergence of large-scale objects and to extend the scope of mathematical modeling in biology. We take a simple example from immunology and illustrate that the methods of classical differential equations and microscopic simulation generate contradictory results. Microscopic simulations generate a more faithful approximation of the reality of the immune system.
Discrete state model and accurate estimation of loop entropy of RNA secondary structures.
Zhang, Jian; Lin, Ming; Chen, Rong; Wang, Wei; Liang, Jie
2008-03-28
Conformational entropy makes important contribution to the stability and folding of RNA molecule, but it is challenging to either measure or compute conformational entropy associated with long loops. We develop optimized discrete k-state models of RNA backbone based on known RNA structures for computing entropy of loops, which are modeled as self-avoiding walks. To estimate entropy of hairpin, bulge, internal loop, and multibranch loop of long length (up to 50), we develop an efficient sampling method based on the sequential Monte Carlo principle. Our method considers excluded volume effect. It is general and can be applied to calculating entropy of loops with longer length and arbitrary complexity. For loops of short length, our results are in good agreement with a recent theoretical model and experimental measurement. For long loops, our estimated entropy of hairpin loops is in excellent agreement with the Jacobson-Stockmayer extrapolation model. However, for bulge loops and more complex secondary structures such as internal and multibranch loops, we find that the Jacobson-Stockmayer extrapolation model has large errors. Based on estimated entropy, we have developed empirical formulae for accurate calculation of entropy of long loops in different secondary structures. Our study on the effect of asymmetric size of loops suggest that loop entropy of internal loops is largely determined by the total loop length, and is only marginally affected by the asymmetric size of the two loops. Our finding suggests that the significant asymmetric effects of loop length in internal loops measured by experiments are likely to be partially enthalpic. Our method can be applied to develop improved energy parameters important for studying RNA stability and folding, and for predicting RNA secondary and tertiary structures. The discrete model and the program used to calculate loop entropy can be downloaded at http://gila.bioengr.uic.edu/resources/RNA.html. PMID:18376982
Validation of an Accurate Three-Dimensional Helical Slow-Wave Circuit Model
NASA Technical Reports Server (NTRS)
Kory, Carol L.
1997-01-01
The helical slow-wave circuit embodies a helical coil of rectangular tape supported in a metal barrel by dielectric support rods. Although the helix slow-wave circuit remains the mainstay of the traveling-wave tube (TWT) industry because of its exceptionally wide bandwidth, a full helical circuit, without significant dimensional approximations, has not been successfully modeled until now. Numerous attempts have been made to analyze the helical slow-wave circuit so that the performance could be accurately predicted without actually building it, but because of its complex geometry, many geometrical approximations became necessary rendering the previous models inaccurate. In the course of this research it has been demonstrated that using the simulation code, MAFIA, the helical structure can be modeled with actual tape width and thickness, dielectric support rod geometry and materials. To demonstrate the accuracy of the MAFIA model, the cold-test parameters including dispersion, on-axis interaction impedance and attenuation have been calculated for several helical TWT slow-wave circuits with a variety of support rod geometries including rectangular and T-shaped rods, as well as various support rod materials including isotropic, anisotropic and partially metal coated dielectrics. Compared with experimentally measured results, the agreement is excellent. With the accuracy of the MAFIA helical model validated, the code was used to investigate several conventional geometric approximations in an attempt to obtain the most computationally efficient model. Several simplifications were made to a standard model including replacing the helical tape with filaments, and replacing rectangular support rods with shapes conforming to the cylindrical coordinate system with effective permittivity. The approximate models are compared with the standard model in terms of cold-test characteristics and computational time. The model was also used to determine the sensitivity of various
Development and application of accurate analytical models for single active electron potentials
NASA Astrophysics Data System (ADS)
Miller, Michelle; Jaron-Becker, Agnieszka; Becker, Andreas
2015-05-01
The single active electron (SAE) approximation is a theoretical model frequently employed to study scenarios in which inner-shell electrons may productively be treated as frozen spectators to a physical process of interest, and accurate analytical approximations for these potentials are sought as a useful simulation tool. Density function theory is often used to construct a SAE potential, requiring that a further approximation for the exchange correlation functional be enacted. In this study, we employ the Krieger, Li, and Iafrate (KLI) modification to the optimized-effective-potential (OEP) method to reduce the complexity of the problem to the straightforward solution of a system of linear equations through simple arguments regarding the behavior of the exchange-correlation potential in regions where a single orbital dominates. We employ this method for the solution of atomic and molecular potentials, and use the resultant curve to devise a systematic construction for highly accurate and useful analytical approximations for several systems. Supported by the U.S. Department of Energy (Grant No. DE-FG02-09ER16103), and the U.S. National Science Foundation (Graduate Research Fellowship, Grants No. PHY-1125844 and No. PHY-1068706).
An accurate and efficient Lagrangian sub-grid model for multi-particle dispersion
NASA Astrophysics Data System (ADS)
Toschi, Federico; Mazzitelli, Irene; Lanotte, Alessandra S.
2014-11-01
Many natural and industrial processes involve the dispersion of particle in turbulent flows. Despite recent theoretical progresses in the understanding of particle dynamics in simple turbulent flows, complex geometries often call for numerical approaches based on eulerian Large Eddy Simulation (LES). One important issue related to the Lagrangian integration of tracers in under-resolved velocity fields is connected to the lack of spatial correlations at unresolved scales. Here we propose a computationally efficient Lagrangian model for the sub-grid velocity of tracers dispersed in statistically homogeneous and isotropic turbulent flows. The model incorporates the multi-scale nature of turbulent temporal and spatial correlations that are essential to correctly reproduce the dynamics of multi-particle dispersion. The new model is able to describe the Lagrangian temporal and spatial correlations in clouds of particles. In particular we show that pairs and tetrads dispersion compare well with results from Direct Numerical Simulations of statistically isotropic and homogeneous 3d turbulence. This model may offer an accurate and efficient way to describe multi-particle dispersion in under resolved turbulent velocity fields such as the one employed in eulerian LES. This work is part of the research programmes FP112 of the Foundation for Fundamental Research on Matter (FOM), which is part of the Netherlands Organisation for Scientific Research (NWO). We acknowledge support from the EU COST Action MP0806.
Accurate Measurement of the Relative Abundance of Different DNA Species in Complex DNA Mixtures
Jeong, Sangkyun; Yu, Hyunjoo; Pfeifer, Karl
2012-01-01
A molecular tool that can compare the abundances of different DNA sequences is necessary for comparing intergenic or interspecific gene expression. We devised and verified such a tool using a quantitative competitive polymerase chain reaction approach. For this approach, we adapted a competitor array, an artificially made plasmid DNA in which all the competitor templates for the target DNAs are arranged with a defined ratio, and melting analysis for allele quantitation for accurate quantitation of the fractional ratios of competitively amplified DNAs. Assays on two sets of DNA mixtures with explicitly known compositional structures of the test sequences were performed. The resultant average relative errors of 0.059 and 0.021 emphasize the highly accurate nature of this method. Furthermore, the method's capability of obtaining biological data is demonstrated by the fact that it can illustrate the tissue-specific quantitative expression signatures of the three housekeeping genes G6pdx, Ubc, and Rps27 by using the forms of the relative abundances of their transcripts, and the differential preferences of Igf2 enhancers for each of the multiple Igf2 promoters for the transcription. PMID:22334570
Technology Transfer Automated Retrieval System (TEKTRAN)
The three evapotranspiration (ET) measurement/retrieval techniques used in this study, lysimeter, scintillometer and remote sensing vary in their level of complexity, accuracy, resolution and applicability. The lysimeter with its point measurement is the most accurate and direct method to measure ET...
MONA: An accurate two-phase well flow model based on phase slippage
Asheim, H.
1984-10-01
In two phase flow, holdup and pressure loss are related to interfacial slippage. A model based on the slippage concept has been developed and tested using production well data from Forties, the Ekofisk area, and flowline data from Prudhoe Bay. The model developed turned out considerably more accurate than the standard models used for comparison.
Creation of Anatomically Accurate Computer-Aided Design (CAD) Solid Models from Medical Images
NASA Technical Reports Server (NTRS)
Stewart, John E.; Graham, R. Scott; Samareh, Jamshid A.; Oberlander, Eric J.; Broaddus, William C.
1999-01-01
Most surgical instrumentation and implants used in the world today are designed with sophisticated Computer-Aided Design (CAD)/Computer-Aided Manufacturing (CAM) software. This software automates the mechanical development of a product from its conceptual design through manufacturing. CAD software also provides a means of manipulating solid models prior to Finite Element Modeling (FEM). Few surgical products are designed in conjunction with accurate CAD models of human anatomy because of the difficulty with which these models are created. We have developed a novel technique that creates anatomically accurate, patient specific CAD solids from medical images in a matter of minutes.
NASA Astrophysics Data System (ADS)
Grasso, Robert J.; Russo, Leonard P.; Barrett, John L.; Odhner, Jefferson E.; Egbert, Paul I.
2007-09-01
BAE Systems presents the results of a program to model the performance of Raman LIDAR systems for the remote detection of atmospheric gases, air polluting hydrocarbons, chemical and biological weapons, and other molecular species of interest. Our model, which integrates remote Raman spectroscopy, 2D and 3D LADAR, and USAF atmospheric propagation codes permits accurate determination of the performance of a Raman LIDAR system. The very high predictive performance accuracy of our model is due to the very accurate calculation of the differential scattering cross section for the specie of interest at user selected wavelengths. We show excellent correlation of our calculated cross section data, used in our model, with experimental data obtained from both laboratory measurements and the published literature. In addition, the use of standard USAF atmospheric models provides very accurate determination of the atmospheric extinction at both the excitation and Raman shifted wavelengths.
Modeling acuity for optotypes varying in complexity.
Watson, Andrew B; Ahumada, Albert J
2012-01-01
Watson and Ahumada (2008) described a template model of visual acuity based on an ideal-observer limited by optical filtering, neural filtering, and noise. They computed predictions for selected optotypes and optical aberrations. Here we compare this model's predictions to acuity data for six human observers, each viewing seven different optotype sets, consisting of one set of Sloan letters and six sets of Chinese characters, differing in complexity (Zhang, Zhang, Xue, Liu, & Yu, 2007). Since optical aberrations for the six observers were unknown, we constructed 200 model observers using aberrations collected from 200 normal human eyes (Thibos, Hong, Bradley, & Cheng, 2002). For each condition (observer, optotype set, model observer) we estimated the model noise required to match the data. Expressed as efficiency, performance for Chinese characters was 1.4 to 2.7 times lower than for Sloan letters. Efficiency was weakly and inversely related to perimetric complexity of optotype set. We also compared confusion matrices for human and model observers. Correlations for off-diagonal elements ranged from 0.5 to 0.8 for different sets, and the average correlation for the template model was superior to a geometrical moment model with a comparable number of parameters (Liu, Klein, Xue, Zhang, & Yu, 2009). The template model performed well overall. Estimated psychometric function slopes matched the data, and noise estimates agreed roughly with those obtained independently from contrast sensitivity to Gabor targets. For optotypes of low complexity, the model accurately predicted relative performance. This suggests the model may be used to compare acuities measured with different sets of simple optotypes. PMID:23024356
NASA Astrophysics Data System (ADS)
Yoshidome, Takashi; Ekimoto, Toru; Matubayasi, Nobuyuki; Harano, Yuichi; Kinoshita, Masahiro; Ikeguchi, Mitsunori
2015-05-01
The hydration free energy (HFE) is a crucially important physical quantity to discuss various chemical processes in aqueous solutions. Although an explicit-solvent computation with molecular dynamics (MD) simulations is a preferable treatment of the HFE, huge computational load has been inevitable for large, complex solutes like proteins. In the present paper, we propose an efficient computation method for the HFE. In our method, the HFE is computed as a sum of
Leng, Wei; Ju, Lili; Gunzburger, Max; Price, Stephen; Ringler, Todd
2012-01-01
The numerical modeling of glacier and ice sheet evolution is a subject of growing interest, in part because of the potential for models to inform estimates of global sea level change. This paper focuses on the development of a numerical model that determines the velocity and pressure fields within an ice sheet. Our numerical model features a high-fidelity mathematical model involving the nonlinear Stokes system and combinations of no-sliding and sliding basal boundary conditions, high-order accurate finite element discretizations based on variable resolution grids, and highly scalable parallel solution strategies, all of which contribute to a numerical model that can achieve accurate velocity and pressure approximations in a highly efficient manner. We demonstrate the accuracy and efficiency of our model by analytical solution tests, established ice sheet benchmark experiments, and comparisons with other well-established ice sheet models.
Parida, Girish Kumar; Dhull, Varun Singh; Karunanithi, Sellam; Arora, Saurabh; Sharma, Anshul; Shamim, Shamim Ahmed
2015-09-01
We report a 15-year-old patient with tuberous sclerosis complex or Bourneville's disease with history of generalized tonic-clonic seizure for last 2 years and was currently on antiepileptic medication. He also had a history of left nephrectomy for renal cell carcinoma clear cell type. The patient had multiple adenoma sebaceum over the nasolabial region, ash leaf spots over the lower limbs, a Shagreen patch over the back, and multiple calcified tubers in the subependymal region. He was then referred for the skeletal scintigraphy to look for skeletal lesions, which revealed involvement of bilateral humeri, tibiae, and iliac bones accurately characterized on SPECT/CT. PMID:26098284
Efficient and accurate approach to modeling the microstructure and defect properties of LaCoO3
NASA Astrophysics Data System (ADS)
Buckeridge, J.; Taylor, F. H.; Catlow, C. R. A.
2016-04-01
Complex perovskite oxides are promising materials for cathode layers in solid oxide fuel cells. Such materials have intricate electronic, magnetic, and crystalline structures that prove challenging to model accurately. We analyze a wide range of standard density functional theory approaches to modeling a highly promising system, the perovskite LaCoO3, focusing on optimizing the Hubbard U parameter to treat the self-interaction of the B-site cation's d states, in order to determine the most appropriate method to study defect formation and the effect of spin on local structure. By calculating structural and electronic properties for different magnetic states we determine that U =4 eV for Co in LaCoO3 agrees best with available experiments. We demonstrate that the generalized gradient approximation (PBEsol +U ) is most appropriate for studying structure versus spin state, while the local density approximation (LDA +U ) is most appropriate for determining accurate energetics for defect properties.
2011-01-01
Background Genes of the Major Histocompatibility Complex (MHC) are very popular genetic markers among evolutionary biologists because of their potential role in pathogen confrontation and sexual selection. However, MHC genotyping still remains challenging and time-consuming in spite of substantial methodological advances. Although computational haplotype inference has brought into focus interesting alternatives, high heterozygosity, extensive genetic variation and population admixture are known to cause inaccuracies. We have investigated the role of sample size, genetic polymorphism and genetic structuring on the performance of the popular Bayesian PHASE algorithm. To cover this aim, we took advantage of a large database of known genotypes (using traditional laboratory-based techniques) at single MHC class I (N = 56 individuals and 50 alleles) and MHC class II B (N = 103 individuals and 62 alleles) loci in the lesser kestrel Falco naumanni. Findings Analyses carried out over real MHC genotypes showed that the accuracy of gametic phase reconstruction improved with sample size as a result of the reduction in the allele to individual ratio. We then simulated different data sets introducing variations in this parameter to define an optimal ratio. Conclusions Our results demonstrate a critical influence of the allele to individual ratio on PHASE performance. We found that a minimum allele to individual ratio (1:2) yielded 100% accuracy for both MHC loci. Sampling effort is therefore a crucial step to obtain reliable MHC haplotype reconstructions and must be accomplished accordingly to the degree of MHC polymorphism. We expect our findings provide a foothold into the design of straightforward and cost-effective genotyping strategies of those MHC loci from which locus-specific primers are available. PMID:21615903
Improving light propagation Monte Carlo simulations with accurate 3D modeling of skin tissue
Paquit, Vincent C; Price, Jeffery R; Meriaudeau, Fabrice; Tobin Jr, Kenneth William
2008-01-01
In this paper, we present a 3D light propagation model to simulate multispectral reflectance images of large skin surface areas. In particular, we aim to simulate more accurately the effects of various physiological properties of the skin in the case of subcutaneous vein imaging compared to existing models. Our method combines a Monte Carlo light propagation model, a realistic three-dimensional model of the skin using parametric surfaces and a vision system for data acquisition. We describe our model in detail, present results from the Monte Carlo modeling and compare our results with those obtained with a well established Monte Carlo model and with real skin reflectance images.
Complex Networks in Psychological Models
NASA Astrophysics Data System (ADS)
Wedemann, R. S.; Carvalho, L. S. A. V. D.; Donangelo, R.
We develop schematic, self-organizing, neural-network models to describe mechanisms associated with mental processes, by a neurocomputational substrate. These models are examples of real world complex networks with interesting general topological structures. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose neural network models to explain development of cortical map structure and dynamics of memory access, and unify different mental processes into a single neurocomputational substrate. Based on our neural network models, neurotic behavior may be understood as an associative memory process in the brain, and the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The models are illustrated through computer simulations, where we varied dopaminergic modulation and observed the self-organizing emergent patterns at the resulting semantic map, interpreting them as different manifestations of mental functioning, from psychotic through to normal and neurotic behavior, and creativity.
Victora, Andrea; Möller, Heiko M.; Exner, Thomas E.
2014-01-01
NMR chemical shift predictions based on empirical methods are nowadays indispensable tools during resonance assignment and 3D structure calculation of proteins. However, owing to the very limited statistical data basis, such methods are still in their infancy in the field of nucleic acids, especially when non-canonical structures and nucleic acid complexes are considered. Here, we present an ab initio approach for predicting proton chemical shifts of arbitrary nucleic acid structures based on state-of-the-art fragment-based quantum chemical calculations. We tested our prediction method on a diverse set of nucleic acid structures including double-stranded DNA, hairpins, DNA/protein complexes and chemically-modified DNA. Overall, our quantum chemical calculations yield highly/very accurate predictions with mean absolute deviations of 0.3–0.6 ppm and correlation coefficients (r2) usually above 0.9. This will allow for identifying misassignments and validating 3D structures. Furthermore, our calculations reveal that chemical shifts of protons involved in hydrogen bonding are predicted significantly less accurately. This is in part caused by insufficient inclusion of solvation effects. However, it also points toward shortcomings of current force fields used for structure determination of nucleic acids. Our quantum chemical calculations could therefore provide input for force field optimization. PMID:25404135
Victora, Andrea; Möller, Heiko M; Exner, Thomas E
2014-12-16
NMR chemical shift predictions based on empirical methods are nowadays indispensable tools during resonance assignment and 3D structure calculation of proteins. However, owing to the very limited statistical data basis, such methods are still in their infancy in the field of nucleic acids, especially when non-canonical structures and nucleic acid complexes are considered. Here, we present an ab initio approach for predicting proton chemical shifts of arbitrary nucleic acid structures based on state-of-the-art fragment-based quantum chemical calculations. We tested our prediction method on a diverse set of nucleic acid structures including double-stranded DNA, hairpins, DNA/protein complexes and chemically-modified DNA. Overall, our quantum chemical calculations yield highly/very accurate predictions with mean absolute deviations of 0.3-0.6 ppm and correlation coefficients (r(2)) usually above 0.9. This will allow for identifying misassignments and validating 3D structures. Furthermore, our calculations reveal that chemical shifts of protons involved in hydrogen bonding are predicted significantly less accurately. This is in part caused by insufficient inclusion of solvation effects. However, it also points toward shortcomings of current force fields used for structure determination of nucleic acids. Our quantum chemical calculations could therefore provide input for force field optimization. PMID:25404135
Optimal Complexity of Nonlinear Rainfall-Runoff Models
NASA Astrophysics Data System (ADS)
Schoups, G.; Vrugt, J.; van de Giesen, N.; Fenicia, F.
2008-12-01
Identification of an appropriate level of model complexity to accurately translate rainfall into runoff remains an unresolved issue. The model has to be complex enough to generate accurate predictions, but not too complex such that its parameters cannot be reliably estimated from the data. Earlier work with linear models (Jakeman and Hornberger, 1993) concluded that a model with 4 to 5 parameters is sufficient. However, more recent results with a nonlinear model (Vrugt et al., 2006) suggest that 10 or more parameters may be identified from daily rainfall-runoff time-series. The goal here is to systematically investigate optimal complexity of nonlinear rainfall-runoff models, yielding accurate models with identifiable parameters. Our methodology consists of four steps: (i) a priori specification of a family of model structures from which to pick an optimal one, (ii) parameter optimization of each model structure to estimate empirical or calibration error, (iii) estimation of parameter uncertainty of each calibrated model structure, and (iv) estimation of prediction error of each calibrated model structure. For the first step we formulate a flexible model structure that allows us to systematically vary the complexity with which physical processes are simulated. The second and third steps are achieved using a recently developed Markov chain Monte Carlo algorithm (DREAM), which minimizes calibration error yielding optimal parameter values and their underlying posterior probability density function. Finally, we compare several methods for estimating prediction error of each model structure, including statistical methods based on information criteria and split-sample calibration-validation. Estimates of parameter uncertainty and prediction error are then used to identify optimal complexity for rainfall-runoff modeling, using data from dry and wet MOPEX catchments as case studies.
Describing Ecosystem Complexity through Integrated Catchment Modeling
NASA Astrophysics Data System (ADS)
Shope, C. L.; Tenhunen, J. D.; Peiffer, S.
2011-12-01
Land use and climate change have been implicated in reduced ecosystem services (ie: high quality water yield, biodiversity, and agricultural yield. The prediction of ecosystem services expected under future land use decisions and changing climate conditions has become increasingly important. Complex policy and management decisions require the integration of physical, economic, and social data over several scales to assess effects on water resources and ecology. Field-based meteorology, hydrology, soil physics, plant production, solute and sediment transport, economic, and social behavior data were measured in a South Korean catchment. A variety of models are being used to simulate plot and field scale experiments within the catchment. Results from each of the local-scale models provide identification of sensitive, local-scale parameters which are then used as inputs into a large-scale watershed model. We used the spatially distributed SWAT model to synthesize the experimental field data throughout the catchment. The approach of our study was that the range in local-scale model parameter results can be used to define the sensitivity and uncertainty in the large-scale watershed model. Further, this example shows how research can be structured for scientific results describing complex ecosystems and landscapes where cross-disciplinary linkages benefit the end result. The field-based and modeling framework described is being used to develop scenarios to examine spatial and temporal changes in land use practices and climatic effects on water quantity, water quality, and sediment transport. Development of accurate modeling scenarios requires understanding the social relationship between individual and policy driven land management practices and the value of sustainable resources to all shareholders.
Modeling Wildfire Incident Complexity Dynamics
Thompson, Matthew P.
2013-01-01
Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management. PMID:23691014
Material Models for Accurate Simulation of Sheet Metal Forming and Springback
NASA Astrophysics Data System (ADS)
Yoshida, Fusahito
2010-06-01
For anisotropic sheet metals, modeling of anisotropy and the Bauschinger effect is discussed in the framework of Yoshida-Uemori kinematic hardening model incorporating with anisotropic yield functions. The performances of the models in predicting yield loci, cyclic stress-strain responses on several types of steel and aluminum sheets are demonstrated by comparing the numerical simulation results with the corresponding experimental observations. From some examples of FE simulation of sheet metal forming and springback, it is concluded that modeling of both the anisotropy and the Bauschinger effect is essential for the accurate numerical simulation.
Development of modified cable models to simulate accurate neuronal active behaviors
2014-01-01
In large network and single three-dimensional (3-D) neuron simulations, high computing speed dictates using reduced cable models to simulate neuronal firing behaviors. However, these models are unwarranted under active conditions and lack accurate representation of dendritic active conductances that greatly shape neuronal firing. Here, realistic 3-D (R3D) models (which contain full anatomical details of dendrites) of spinal motoneurons were systematically compared with their reduced single unbranched cable (SUC, which reduces the dendrites to a single electrically equivalent cable) counterpart under passive and active conditions. The SUC models matched the R3D model's passive properties but failed to match key active properties, especially active behaviors originating from dendrites. For instance, persistent inward currents (PIC) hysteresis, frequency-current (FI) relationship secondary range slope, firing hysteresis, plateau potential partial deactivation, staircase currents, synaptic current transfer ratio, and regional FI relationships were not accurately reproduced by the SUC models. The dendritic morphology oversimplification and lack of dendritic active conductances spatial segregation in the SUC models caused significant underestimation of those behaviors. Next, SUC models were modified by adding key branching features in an attempt to restore their active behaviors. The addition of primary dendritic branching only partially restored some active behaviors, whereas the addition of secondary dendritic branching restored most behaviors. Importantly, the proposed modified models successfully replicated the active properties without sacrificing model simplicity, making them attractive candidates for running R3D single neuron and network simulations with accurate firing behaviors. The present results indicate that using reduced models to examine PIC behaviors in spinal motoneurons is unwarranted. PMID:25277743
Methodology to set up accurate OPC model using optical CD metrology and atomic force microscopy
NASA Astrophysics Data System (ADS)
Shim, Yeon-Ah; Kang, Jaehyun; Lee, Sang-Uk; Kim, Jeahee; Kim, Keeho
2007-03-01
For the 90nm node and beyond, smaller Critical Dimension(CD) control budget is required and the ways to control good CD uniformity are needed. Moreover Optical Proximity Correction(OPC) for the sub-90nm node demands more accurate wafer CD data in order to improve accuracy of OPC model. Scanning Electron Microscope (SEM) is the typical method for measuring CD until ArF process. However SEM can give serious attack such as shrinkage of Photo Resist(PR) by burning of weak chemical structure of ArF PR due to high energy electron beam. In fact about 5nm CD narrowing occur when we measure CD by using CD-SEM in ArF photo process. Optical CD Metrology(OCD) and Atomic Force Microscopy(AFM) has been considered to the method for measuring CD without attack of organic materials. Also the OCD and AFM measurement system have the merits of speed, easiness and accurate data. For model-based OPC, the model is generated using CD data of test patterns transferred onto the wafer. In this study we discuss to generate accurate OPC model using OCD and AFM measurement system.
Explosion modelling for complex geometries
NASA Astrophysics Data System (ADS)
Nehzat, Naser
A literature review suggested that the combined effects of fuel reactivity, obstacle density, ignition strength, and confinement result in flame acceleration and subsequent pressure build-up during a vapour cloud explosion (VCE). Models for the prediction of propagating flames in hazardous areas, such as coal mines, oil platforms, storage and process chemical areas etc. fall into two classes. One class involves use of Computation Fluid Dynamics (CFD). This approach has been utilised by several researchers. The other approach relies upon a lumped parameter approach as developed by Baker (1983). The former approach is restricted by the appropriateness of sub-models and numerical stability requirements inherent in the computational solution. The latter approach raises significant questions regarding the validity of the simplification involved in representing the complexities of a propagating explosion. This study was conducted to investigate and improve the Computational Fluid Dynamic (CFD) code EXPLODE which has been developed by Green et al., (1993) for use on practical gas explosion hazard assessments. The code employs a numerical method for solving partial differential equations by using finite volume techniques. Verification exercises, involving comparison with analytical solutions for the classical shock-tube and with experimental (small-scale, medium and large-scale) results, demonstrate the accuracy of the code and the new combustion models but also identify differences between predictions and the experimental results. The project has resulted in a developed version of the code (EXPLODE2) with new combustion models for simulating gas explosions. Additional features of this program include the physical models necessary to simulate the combustion process using alternative combustion models, improvement to the numerical accuracy and robustness of the code, and special input for simulation of different gas explosions. The present code has the capability of
Flynn, Jullien M; Brown, Emily A; Chain, Frédéric J J; MacIsaac, Hugh J; Cristescu, Melania E
2015-01-01
Metabarcoding has the potential to become a rapid, sensitive, and effective approach for identifying species in complex environmental samples. Accurate molecular identification of species depends on the ability to generate operational taxonomic units (OTUs) that correspond to biological species. Due to the sometimes enormous estimates of biodiversity using this method, there is a great need to test the efficacy of data analysis methods used to derive OTUs. Here, we evaluate the performance of various methods for clustering length variable 18S amplicons from complex samples into OTUs using a mock community and a natural community of zooplankton species. We compare analytic procedures consisting of a combination of (1) stringent and relaxed data filtering, (2) singleton sequences included and removed, (3) three commonly used clustering algorithms (mothur, UCLUST, and UPARSE), and (4) three methods of treating alignment gaps when calculating sequence divergence. Depending on the combination of methods used, the number of OTUs varied by nearly two orders of magnitude for the mock community (60–5068 OTUs) and three orders of magnitude for the natural community (22–22191 OTUs). The use of relaxed filtering and the inclusion of singletons greatly inflated OTU numbers without increasing the ability to recover species. Our results also suggest that the method used to treat gaps when calculating sequence divergence can have a great impact on the number of OTUs. Our findings are particularly relevant to studies that cover taxonomically diverse species and employ markers such as rRNA genes in which length variation is extensive. PMID:26078860
Can phenological models predict tree phenology accurately under climate change conditions?
NASA Astrophysics Data System (ADS)
Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry
2014-05-01
The onset of the growing season of trees has been globally earlier by 2.3 days/decade during the last 50 years because of global warming and this trend is predicted to continue according to climate forecast. The effect of temperature on plant phenology is however not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud dormancy, and on the other hand higher temperatures are necessary to promote bud cells growth afterwards. Increasing phenological changes in temperate woody species have strong impacts on forest trees distribution and productivity, as well as crops cultivation areas. Accurate predictions of trees phenology are therefore a prerequisite to understand and foresee the impacts of climate change on forests and agrosystems. Different process-based models have been developed in the last two decades to predict the date of budburst or flowering of woody species. They are two main families: (1) one-phase models which consider only the ecodormancy phase and make the assumption that endodormancy is always broken before adequate climatic conditions for cell growth occur; and (2) two-phase models which consider both the endodormancy and ecodormancy phases and predict a date of dormancy break which varies from year to year. So far, one-phase models have been able to predict accurately tree bud break and flowering under historical climate. However, because they do not consider what happens prior to ecodormancy, and especially the possible negative effect of winter temperature warming on dormancy break, it seems unlikely that they can provide accurate predictions in future climate conditions. It is indeed well known that a lack of low temperature results in abnormal pattern of bud break and development in temperate fruit trees. An accurate modelling of the dormancy break date has thus become a major issue in phenology modelling. Two-phases phenological models predict that global warming should delay
Building an accurate 3D model of a circular feature for robot vision
NASA Astrophysics Data System (ADS)
Li, L.
2012-06-01
In this paper, an accurate 3D model analysis of a circular feature is built with error compensation for robot vision. We propose an efficient method of fitting ellipses to data points by minimizing the algebraic distance subject to the constraint that a conic should be an ellipse and solving the ellipse parameters through a direct ellipse fitting method by analysing the 3D geometrical representation in a perspective projection scheme, the 3D position of a circular feature with known radius can be obtained. A set of identical circles, machined on a calibration board whose centres were known, was calibrated with a camera and did the model analysis that our method developed. Experimental results show that our method is more accurate than other methods.
Seth A Veitzer
2008-10-21
Effects of stray electrons are a main factor limiting performance of many accelerators. Because heavy-ion fusion (HIF) accelerators will operate in regimes of higher current and with walls much closer to the beam than accelerators operating today, stray electrons might have a large, detrimental effect on the performance of an HIF accelerator. A primary source of stray electrons is electrons generated when halo ions strike the beam pipe walls. There is some research on these types of secondary electrons for the HIF community to draw upon, but this work is missing one crucial ingredient: the effect of grazing incidence. The overall goal of this project was to develop the numerical tools necessary to accurately model the effect of grazing incidence on the behavior of halo ions in a HIF accelerator, and further, to provide accurate models of heavy ion stopping powers with applications to ICF, WDM, and HEDP experiments.
Oksel, Ceyda; Winkler, David A; Ma, Cai Y; Wilkins, Terry; Wang, Xue Z
2016-09-01
The number of engineered nanomaterials (ENMs) being exploited commercially is growing rapidly, due to the novel properties they exhibit. Clearly, it is important to understand and minimize any risks to health or the environment posed by the presence of ENMs. Data-driven models that decode the relationships between the biological activities of ENMs and their physicochemical characteristics provide an attractive means of maximizing the value of scarce and expensive experimental data. Although such structure-activity relationship (SAR) methods have become very useful tools for modelling nanotoxicity endpoints (nanoSAR), they have limited robustness and predictivity and, most importantly, interpretation of the models they generate is often very difficult. New computational modelling tools or new ways of using existing tools are required to model the relatively sparse and sometimes lower quality data on the biological effects of ENMs. The most commonly used SAR modelling methods work best with large datasets, are not particularly good at feature selection, can be relatively opaque to interpretation, and may not account for nonlinearity in the structure-property relationships. To overcome these limitations, we describe the application of a novel algorithm, a genetic programming-based decision tree construction tool (GPTree) to nanoSAR modelling. We demonstrate the use of GPTree in the construction of accurate and interpretable nanoSAR models by applying it to four diverse literature datasets. We describe the algorithm and compare model results across the four studies. We show that GPTree generates models with accuracies equivalent to or superior to those of prior modelling studies on the same datasets. GPTree is a robust, automatic method for generation of accurate nanoSAR models with important advantages that it works with small datasets, automatically selects descriptors, and provides significantly improved interpretability of models. PMID:26956430
Li, Rui; Ye, Hongfei; Zhang, Weisheng; Ma, Guojun; Su, Yewang
2015-01-01
Spring constant calibration of the atomic force microscope (AFM) cantilever is of fundamental importance for quantifying the force between the AFM cantilever tip and the sample. The calibration within the framework of thin plate theory undoubtedly has a higher accuracy and broader scope than that within the well-established beam theory. However, thin plate theory-based accurate analytic determination of the constant has been perceived as an extremely difficult issue. In this paper, we implement the thin plate theory-based analytic modeling for the static behavior of rectangular AFM cantilevers, which reveals that the three-dimensional effect and Poisson effect play important roles in accurate determination of the spring constants. A quantitative scaling law is found that the normalized spring constant depends only on the Poisson’s ratio, normalized dimension and normalized load coordinate. Both the literature and our refined finite element model validate the present results. The developed model is expected to serve as the benchmark for accurate calibration of rectangular AFM cantilevers. PMID:26510769
Li, Rui; Ye, Hongfei; Zhang, Weisheng; Ma, Guojun; Su, Yewang
2015-01-01
Spring constant calibration of the atomic force microscope (AFM) cantilever is of fundamental importance for quantifying the force between the AFM cantilever tip and the sample. The calibration within the framework of thin plate theory undoubtedly has a higher accuracy and broader scope than that within the well-established beam theory. However, thin plate theory-based accurate analytic determination of the constant has been perceived as an extremely difficult issue. In this paper, we implement the thin plate theory-based analytic modeling for the static behavior of rectangular AFM cantilevers, which reveals that the three-dimensional effect and Poisson effect play important roles in accurate determination of the spring constants. A quantitative scaling law is found that the normalized spring constant depends only on the Poisson's ratio, normalized dimension and normalized load coordinate. Both the literature and our refined finite element model validate the present results. The developed model is expected to serve as the benchmark for accurate calibration of rectangular AFM cantilevers. PMID:26510769
NASA Astrophysics Data System (ADS)
Li, Rui; Ye, Hongfei; Zhang, Weisheng; Ma, Guojun; Su, Yewang
2015-10-01
Spring constant calibration of the atomic force microscope (AFM) cantilever is of fundamental importance for quantifying the force between the AFM cantilever tip and the sample. The calibration within the framework of thin plate theory undoubtedly has a higher accuracy and broader scope than that within the well-established beam theory. However, thin plate theory-based accurate analytic determination of the constant has been perceived as an extremely difficult issue. In this paper, we implement the thin plate theory-based analytic modeling for the static behavior of rectangular AFM cantilevers, which reveals that the three-dimensional effect and Poisson effect play important roles in accurate determination of the spring constants. A quantitative scaling law is found that the normalized spring constant depends only on the Poisson’s ratio, normalized dimension and normalized load coordinate. Both the literature and our refined finite element model validate the present results. The developed model is expected to serve as the benchmark for accurate calibration of rectangular AFM cantilevers.
Accurate and efficient halo-based galaxy clustering modelling with simulations
NASA Astrophysics Data System (ADS)
Zheng, Zheng; Guo, Hong
2016-06-01
Small- and intermediate-scale galaxy clustering can be used to establish the galaxy-halo connection to study galaxy formation and evolution and to tighten constraints on cosmological parameters. With the increasing precision of galaxy clustering measurements from ongoing and forthcoming large galaxy surveys, accurate models are required to interpret the data and extract relevant information. We introduce a method based on high-resolution N-body simulations to accurately and efficiently model the galaxy two-point correlation functions (2PCFs) in projected and redshift spaces. The basic idea is to tabulate all information of haloes in the simulations necessary for computing the galaxy 2PCFs within the framework of halo occupation distribution or conditional luminosity function. It is equivalent to populating galaxies to dark matter haloes and using the mock 2PCF measurements as the model predictions. Besides the accurate 2PCF calculations, the method is also fast and therefore enables an efficient exploration of the parameter space. As an example of the method, we decompose the redshift-space galaxy 2PCF into different components based on the type of galaxy pairs and show the redshift-space distortion effect in each component. The generalizations and limitations of the method are discussed.
NASA Astrophysics Data System (ADS)
Blackman, Jonathan; Field, Scott E.; Galley, Chad R.; Szilágyi, Béla; Scheel, Mark A.; Tiglio, Manuel; Hemberger, Daniel A.
2015-09-01
Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. Using reduced order modeling techniques, we construct an accurate surrogate model, which is evaluated in a millisecond to a second, for numerical relativity (NR) waveforms from nonspinning binary black hole coalescences with mass ratios in [1, 10] and durations corresponding to about 15 orbits before merger. We assess the model's uncertainty and show that our modeling strategy predicts NR waveforms not used for the surrogate's training with errors nearly as small as the numerical error of the NR code. Our model includes all spherical-harmonic -2Yℓm waveform modes resolved by the NR code up to ℓ=8 . We compare our surrogate model to effective one body waveforms from 50 M⊙ to 300 M⊙ for advanced LIGO detectors and find that the surrogate is always more faithful (by at least an order of magnitude in most cases).
Chuine, Isabelle; Bonhomme, Marc; Legave, Jean-Michel; García de Cortázar-Atauri, Iñaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry
2016-10-01
The onset of the growing season of trees has been earlier by 2.3 days per decade during the last 40 years in temperate Europe because of global warming. The effect of temperature on plant phenology is, however, not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud endodormancy, and, on the other hand, higher temperatures are necessary to promote bud cell growth afterward. Different process-based models have been developed in the last decades to predict the date of budbreak of woody species. They predict that global warming should delay or compromise endodormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budbreak dates only, with no information on the endodormancy break date because this information is very scarce. Here, we evaluated the efficiency of a set of phenological models to accurately predict the endodormancy break dates of three fruit trees. Our results show that models calibrated solely with budbreak dates usually do not accurately predict the endodormancy break date. Providing endodormancy break date for the model parameterization results in much more accurate prediction of this latter, with, however, a higher error than that on budbreak dates. Most importantly, we show that models not calibrated with endodormancy break dates can generate large discrepancies in forecasted budbreak dates when using climate scenarios as compared to models calibrated with endodormancy break dates. This discrepancy increases with mean annual temperature and is therefore the strongest after 2050 in the southernmost regions. Our results claim for the urgent need of massive measurements of endodormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future. PMID:27272707
Accurate protein structure modeling using sparse NMR data and homologous structure information
Thompson, James M.; Sgourakis, Nikolaos G.; Liu, Gaohua; Rossi, Paolo; Tang, Yuefeng; Mills, Jeffrey L.; Szyperski, Thomas; Montelione, Gaetano T.; Baker, David
2012-01-01
While information from homologous structures plays a central role in X-ray structure determination by molecular replacement, such information is rarely used in NMR structure determination because it can be incorrect, both locally and globally, when evolutionary relationships are inferred incorrectly or there has been considerable evolutionary structural divergence. Here we describe a method that allows robust modeling of protein structures of up to 225 residues by combining , 13C, and 15N backbone and 13Cβ chemical shift data, distance restraints derived from homologous structures, and a physically realistic all-atom energy function. Accurate models are distinguished from inaccurate models generated using incorrect sequence alignments by requiring that (i) the all-atom energies of models generated using the restraints are lower than models generated in unrestrained calculations and (ii) the low-energy structures converge to within 2.0 Å backbone rmsd over 75% of the protein. Benchmark calculations on known structures and blind targets show that the method can accurately model protein structures, even with very remote homology information, to a backbone rmsd of 1.2–1.9 Å relative to the conventional determined NMR ensembles and of 0.9–1.6 Å relative to X-ray structures for well-defined regions of the protein structures. This approach facilitates the accurate modeling of protein structures using backbone chemical shift data without need for side-chain resonance assignments and extensive analysis of NOESY cross-peak assignments. PMID:22665781
Monte Carlo modeling provides accurate calibration factors for radionuclide activity meters.
Zagni, F; Cicoria, G; Lucconi, G; Infantino, A; Lodi, F; Marengo, M
2014-12-01
Accurate determination of calibration factors for radionuclide activity meters is crucial for quantitative studies and in the optimization step of radiation protection, as these detectors are widespread in radiopharmacy and nuclear medicine facilities. In this work we developed the Monte Carlo model of a widely used activity meter, using the Geant4 simulation toolkit. More precisely the "PENELOPE" EM physics models were employed. The model was validated by means of several certified sources, traceable to primary activity standards, and other sources locally standardized with spectrometry measurements, plus other experimental tests. Great care was taken in order to accurately reproduce the geometrical details of the gas chamber and the activity sources, each of which is different in shape and enclosed in a unique container. Both relative calibration factors and ionization current obtained with simulations were compared against experimental measurements; further tests were carried out, such as the comparison of the relative response of the chamber for a source placed at different positions. The results showed a satisfactory level of accuracy in the energy range of interest, with the discrepancies lower than 4% for all the tested parameters. This shows that an accurate Monte Carlo modeling of this type of detector is feasible using the low-energy physics models embedded in Geant4. The obtained Monte Carlo model establishes a powerful tool for first instance determination of new calibration factors for non-standard radionuclides, for custom containers, when a reference source is not available. Moreover, the model provides an experimental setup for further research and optimization with regards to materials and geometrical details of the measuring setup, such as the ionization chamber itself or the containers configuration. PMID:25195174
2013-01-01
Background Although prokaryotic gene transcription has been studied over decades, many aspects of the process remain poorly understood. Particularly, recent studies have revealed that transcriptomes in many prokaryotes are far more complex than previously thought. Genes in an operon are often alternatively and dynamically transcribed under different conditions, and a large portion of genes and intergenic regions have antisense RNA (asRNA) and non-coding RNA (ncRNA) transcripts, respectively. Ironically, similar studies have not been conducted in the model bacterium E coli K12, thus it is unknown whether or not the bacterium possesses similar complex transcriptomes. Furthermore, although RNA-seq becomes the major method for analyzing the complexity of prokaryotic transcriptome, it is still a challenging task to accurately assemble full length transcripts using short RNA-seq reads. Results To fill these gaps, we have profiled the transcriptomes of E. coli K12 under different culture conditions and growth phases using a highly specific directional RNA-seq technique that can capture various types of transcripts in the bacterial cells, combined with a highly accurate and robust algorithm and tool TruHMM (http://bioinfolab.uncc.edu/TruHmm_package/) for assembling full length transcripts. We found that 46.9 ~ 63.4% of expressed operons were utilized in their putative alternative forms, 72.23 ~ 89.54% genes had putative asRNA transcripts and 51.37 ~ 72.74% intergenic regions had putative ncRNA transcripts under different culture conditions and growth phases. Conclusions As has been demonstrated in many other prokaryotes, E. coli K12 also has a highly complex and dynamic transcriptomes under different culture conditions and growth phases. Such complex and dynamic transcriptomes might play important roles in the physiology of the bacterium. TruHMM is a highly accurate and robust algorithm for assembling full-length transcripts in prokaryotes using directional RNA
A physical interpretation of hydrologic model complexity
NASA Astrophysics Data System (ADS)
Moayeri, MohamadMehdi; Pande, Saket
2015-04-01
It is intuitive that instability of hydrological system representation, in the sense of how perturbations in input forcings translate into perturbation in a hydrologic response, may depend on its hydrological characteristics. Responses of unstable systems are thus complex to model. We interpret complexity in this context and define complexity as a measure of instability in hydrological system representation. We provide algorithms to quantify model complexity in this context. We use Sacramento soil moisture accounting model (SAC-SMA) parameterized for MOPEX basins and quantify complexities of corresponding models. Relationships between hydrologic characteristics of MOPEX basins such as location, precipitation seasonality index, slope, hydrologic ratios, saturated hydraulic conductivity and NDVI and respective model complexities are then investigated. We hypothesize that complexities of basin specific SAC-SMA models correspond to aforementioned hydrologic characteristics, thereby suggesting that model complexity, in the context presented here, may have a physical interpretation.
NASA Astrophysics Data System (ADS)
Tao, Jianmin; Rappe, Andrew M.
2016-01-01
Due to the absence of the long-range van der Waals (vdW) interaction, conventional density functional theory (DFT) often fails in the description of molecular complexes and solids. In recent years, considerable progress has been made in the development of the vdW correction. However, the vdW correction based on the leading-order coefficient C6 alone can only achieve limited accuracy, while accurate modeling of higher-order coefficients remains a formidable task, due to the strong non-additivity effect. Here, we apply a model dynamic multipole polarizability within a modified single-frequency approximation to calculate C8 and C10 between small molecules. We find that the higher-order vdW coefficients from this model can achieve remarkable accuracy, with mean absolute relative deviations of 5% for C8 and 7% for C10. Inclusion of accurate higher-order contributions in the vdW correction will effectively enhance the predictive power of DFT in condensed matter physics and quantum chemistry.
NASA Astrophysics Data System (ADS)
Mead, A. J.; Heymans, C.; Lombriser, L.; Peacock, J. A.; Steele, O. I.; Winther, H. A.
2016-06-01
We present an accurate non-linear matter power spectrum prediction scheme for a variety of extensions to the standard cosmological paradigm, which uses the tuned halo model previously developed in Mead et al. We consider dark energy models that are both minimally and non-minimally coupled, massive neutrinos and modified gravitational forces with chameleon and Vainshtein screening mechanisms. In all cases, we compare halo-model power spectra to measurements from high-resolution simulations. We show that the tuned halo-model method can predict the non-linear matter power spectrum measured from simulations of parametrized w(a) dark energy models at the few per cent level for k < 10 h Mpc-1, and we present theoretically motivated extensions to cover non-minimally coupled scalar fields, massive neutrinos and Vainshtein screened modified gravity models that result in few per cent accurate power spectra for k < 10 h Mpc-1. For chameleon screened models, we achieve only 10 per cent accuracy for the same range of scales. Finally, we use our halo model to investigate degeneracies between different extensions to the standard cosmological model, finding that the impact of baryonic feedback on the non-linear matter power spectrum can be considered independently of modified gravity or massive neutrino extensions. In contrast, considering the impact of modified gravity and massive neutrinos independently results in biased estimates of power at the level of 5 per cent at scales k > 0.5 h Mpc-1. An updated version of our publicly available HMCODE can be found at https://github.com/alexander-mead/hmcode.
2015-01-01
Background Accurately predicting the binding affinities of large sets of protein-ligand complexes is a key challenge in computational biomolecular science, with applications in drug discovery, chemical biology, and structural biology. Since a scoring function (SF) is used to score, rank, and identify drug leads, the fidelity with which it predicts the affinity of a ligand candidate for a protein's binding site has a significant bearing on the accuracy of virtual screening. Despite intense efforts in developing conventional SFs, which are either force-field based, knowledge-based, or empirical, their limited predictive power has been a major roadblock toward cost-effective drug discovery. Therefore, in this work, we present novel SFs employing a large ensemble of neural networks (NN) in conjunction with a diverse set of physicochemical and geometrical features characterizing protein-ligand complexes to predict binding affinity. Results We assess the scoring accuracies of two new ensemble NN SFs based on bagging (BgN-Score) and boosting (BsN-Score), as well as those of conventional SFs in the context of the 2007 PDBbind benchmark that encompasses a diverse set of high-quality protein families. We find that BgN-Score and BsN-Score have more than 25% better Pearson's correlation coefficient (0.804 and 0.816 vs. 0.644) between predicted and measured binding affinities compared to that achieved by a state-of-the-art conventional SF. In addition, these ensemble NN SFs are also at least 19% more accurate (0.804 and 0.816 vs. 0.675) than SFs based on a single neural network that has been traditionally used in drug discovery applications. We further find that ensemble models based on NNs surpass SFs based on the decision-tree ensemble technique Random Forests. Conclusions Ensemble neural networks SFs, BgN-Score and BsN-Score, are the most accurate in predicting binding affinity of protein-ligand complexes among the considered SFs. Moreover, their accuracies are even higher
Accurate modeling of switched reluctance machine based on hybrid trained WNN
Song, Shoujun Ge, Lefei; Ma, Shaojie; Zhang, Man
2014-04-15
According to the strong nonlinear electromagnetic characteristics of switched reluctance machine (SRM), a novel accurate modeling method is proposed based on hybrid trained wavelet neural network (WNN) which combines improved genetic algorithm (GA) with gradient descent (GD) method to train the network. In the novel method, WNN is trained by GD method based on the initial weights obtained per improved GA optimization, and the global parallel searching capability of stochastic algorithm and local convergence speed of deterministic algorithm are combined to enhance the training accuracy, stability and speed. Based on the measured electromagnetic characteristics of a 3-phase 12/8-pole SRM, the nonlinear simulation model is built by hybrid trained WNN in Matlab. The phase current and mechanical characteristics from simulation under different working conditions meet well with those from experiments, which indicates the accuracy of the model for dynamic and static performance evaluation of SRM and verifies the effectiveness of the proposed modeling method.
Accurate, efficient, and (iso)geometrically flexible collocation methods for phase-field models
NASA Astrophysics Data System (ADS)
Gomez, Hector; Reali, Alessandro; Sangalli, Giancarlo
2014-04-01
We propose new collocation methods for phase-field models. Our algorithms are based on isogeometric analysis, a new technology that makes use of functions from computational geometry, such as, for example, Non-Uniform Rational B-Splines (NURBS). NURBS exhibit excellent approximability and controllable global smoothness, and can represent exactly most geometries encapsulated in Computer Aided Design (CAD) models. These attributes permitted us to derive accurate, efficient, and geometrically flexible collocation methods for phase-field models. The performance of our method is demonstrated by several numerical examples of phase separation modeled by the Cahn-Hilliard equation. We feel that our method successfully combines the geometrical flexibility of finite elements with the accuracy and simplicity of pseudo-spectral collocation methods, and is a viable alternative to classical collocation methods.
Khan, Usman; Falconi, Christian
2014-01-01
Ideally, the design of high-performance micro-hotplates would require a large number of simulations because of the existence of many important design parameters as well as the possibly crucial effects of both spread and drift. However, the computational cost of FEM simulations, which are the only available tool for accurately predicting the temperature in micro-hotplates, is very high. As a result, micro-hotplate designers generally have no effective simulation-tools for the optimization. In order to circumvent these issues, here, we propose a model for practical circular-symmetric micro-hot-plates which takes advantage of modified Bessel functions, computationally efficient matrix-approach for considering the relevant boundary conditions, Taylor linearization for modeling the Joule heating and radiation losses, and external-region-segmentation strategy in order to accurately take into account radiation losses in the entire micro-hotplate. The proposed model is almost as accurate as FEM simulations and two to three orders of magnitude more computationally efficient (e.g., 45 s versus more than 8 h). The residual errors, which are mainly associated to the undesired heating in the electrical contacts, are small (e.g., few degrees Celsius for an 800 °C operating temperature) and, for important analyses, almost constant. Therefore, we also introduce a computationally-easy single-FEM-compensation strategy in order to reduce the residual errors to about 1 °C. As illustrative examples of the power of our approach, we report the systematic investigation of a spread in the membrane thermal conductivity and of combined variations of both ambient and bulk temperatures. Our model enables a much faster characterization of micro-hotplates and, thus, a much more effective optimization prior to fabrication. PMID:24763214
An Accurate and Computationally Efficient Model for Membrane-Type Circular-Symmetric Micro-Hotplates
Khan, Usman; Falconi, Christian
2014-01-01
Ideally, the design of high-performance micro-hotplates would require a large number of simulations because of the existence of many important design parameters as well as the possibly crucial effects of both spread and drift. However, the computational cost of FEM simulations, which are the only available tool for accurately predicting the temperature in micro-hotplates, is very high. As a result, micro-hotplate designers generally have no effective simulation-tools for the optimization. In order to circumvent these issues, here, we propose a model for practical circular-symmetric micro-hot-plates which takes advantage of modified Bessel functions, computationally efficient matrix-approach for considering the relevant boundary conditions, Taylor linearization for modeling the Joule heating and radiation losses, and external-region-segmentation strategy in order to accurately take into account radiation losses in the entire micro-hotplate. The proposed model is almost as accurate as FEM simulations and two to three orders of magnitude more computationally efficient (e.g., 45 s versus more than 8 h). The residual errors, which are mainly associated to the undesired heating in the electrical contacts, are small (e.g., few degrees Celsius for an 800 °C operating temperature) and, for important analyses, almost constant. Therefore, we also introduce a computationally-easy single-FEM-compensation strategy in order to reduce the residual errors to about 1 °C. As illustrative examples of the power of our approach, we report the systematic investigation of a spread in the membrane thermal conductivity and of combined variations of both ambient and bulk temperatures. Our model enables a much faster characterization of micro-hotplates and, thus, a much more effective optimization prior to fabrication. PMID:24763214
A Method for Accurate in silico modeling of Ultrasound Transducer Arrays
Guenther, Drake A.; Walker, William F.
2009-01-01
This paper presents a new approach to improve the in silico modeling of ultrasound transducer arrays. While current simulation tools accurately predict the theoretical element spatio-temporal pressure response, transducers do not always behave as theorized. In practice, using the probe's physical dimensions and published specifications in silico, often results in unsatisfactory agreement between simulation and experiment. We describe a general optimization procedure used to maximize the correlation between the observed and simulated spatio-temporal response of a pulsed single element in a commercial ultrasound probe. A linear systems approach is employed to model element angular sensitivity, lens effects, and diffraction phenomena. A numerical deconvolution method is described to characterize the intrinsic electro-mechanical impulse response of the element. Once the response of the element and optimal element characteristics are known, prediction of the pressure response for arbitrary apertures and excitation signals is performed through direct convolution using available tools. We achieve a correlation of 0.846 between the experimental emitted waveform and simulated waveform when using the probe's physical specifications in silico. A far superior correlation of 0.988 is achieved when using the optimized in silico model. Electronic noise appears to be the main effect preventing the realization of higher correlation coefficients. More accurate in silico modeling will improve the evaluation and design of ultrasound transducers as well as aid in the development of sophisticated beamforming strategies. PMID:19041997
Towards more accurate numerical modeling of impedance based high frequency harmonic vibration
NASA Astrophysics Data System (ADS)
Lim, Yee Yan; Kiong Soh, Chee
2014-03-01
The application of smart materials in various fields of engineering has recently become increasingly popular. For instance, the high frequency based electromechanical impedance (EMI) technique employing smart piezoelectric materials is found to be versatile in structural health monitoring (SHM). Thus far, considerable efforts have been made to study and improve the technique. Various theoretical models of the EMI technique have been proposed in an attempt to better understand its behavior. So far, the three-dimensional (3D) coupled field finite element (FE) model has proved to be the most accurate. However, large discrepancies between the results of the FE model and experimental tests, especially in terms of the slope and magnitude of the admittance signatures, continue to exist and are yet to be resolved. This paper presents a series of parametric studies using the 3D coupled field finite element method (FEM) on all properties of materials involved in the lead zirconate titanate (PZT) structure interaction of the EMI technique, to investigate their effect on the admittance signatures acquired. FE model updating is then performed by adjusting the parameters to match the experimental results. One of the main reasons for the lower accuracy, especially in terms of magnitude and slope, of previous FE models is the difficulty in determining the damping related coefficients and the stiffness of the bonding layer. In this study, using the hysteretic damping model in place of Rayleigh damping, which is used by most researchers in this field, and updated bonding stiffness, an improved and more accurate FE model is achieved. The results of this paper are expected to be useful for future study of the subject area in terms of research and application, such as modeling, design and optimization.
Teacher Modeling Using Complex Informational Texts
ERIC Educational Resources Information Center
Fisher, Douglas; Frey, Nancy
2015-01-01
Modeling in complex texts requires that teachers analyze the text for factors of qualitative complexity and then design lessons that introduce students to that complexity. In addition, teachers can model the disciplinary nature of content area texts as well as word solving and comprehension strategies. Included is a planning guide for think aloud.
Beekhuizen, Johan; Kromhout, Hans; Bürgi, Alfred; Huss, Anke; Vermeulen, Roel
2015-01-01
The increase in mobile communication technology has led to concern about potential health effects of radio frequency electromagnetic fields (RF-EMFs) from mobile phone base stations. Different RF-EMF prediction models have been applied to assess population exposure to RF-EMF. Our study examines what input data are needed to accurately model RF-EMF, as detailed data are not always available for epidemiological studies. We used NISMap, a 3D radio wave propagation model, to test models with various levels of detail in building and antenna input data. The model outcomes were compared with outdoor measurements taken in Amsterdam, the Netherlands. Results showed good agreement between modelled and measured RF-EMF when 3D building data and basic antenna information (location, height, frequency and direction) were used: Spearman correlations were >0.6. Model performance was not sensitive to changes in building damping parameters. Antenna-specific information about down-tilt, type and output power did not significantly improve model performance compared with using average down-tilt and power values, or assuming one standard antenna type. We conclude that 3D radio wave propagation modelling is a feasible approach to predict outdoor RF-EMF levels for ranking exposure levels in epidemiological studies, when 3D building data and information on the antenna height, frequency, location and direction are available. PMID:24472756
Panagiotopoulou, O; Wilshin, S D; Rayfield, E J; Shefelbine, S J; Hutchinson, J R
2012-02-01
Finite element modelling is well entrenched in comparative vertebrate biomechanics as a tool to assess the mechanical design of skeletal structures and to better comprehend the complex interaction of their form-function relationships. But what makes a reliable subject-specific finite element model? To approach this question, we here present a set of convergence and sensitivity analyses and a validation study as an example, for finite element analysis (FEA) in general, of ways to ensure a reliable model. We detail how choices of element size, type and material properties in FEA influence the results of simulations. We also present an empirical model for estimating heterogeneous material properties throughout an elephant femur (but of broad applicability to FEA). We then use an ex vivo experimental validation test of a cadaveric femur to check our FEA results and find that the heterogeneous model matches the experimental results extremely well, and far better than the homogeneous model. We emphasize how considering heterogeneous material properties in FEA may be critical, so this should become standard practice in comparative FEA studies along with convergence analyses, consideration of element size, type and experimental validation. These steps may be required to obtain accurate models and derive reliable conclusions from them. PMID:21752810
Accurate verification of the conserved-vector-current and standard-model predictions
Sirlin, A.; Zucchini, R.
1986-10-20
An approximate analytic calculation of O(Z..cap alpha../sup 2/) corrections to Fermi decays is presented. When the analysis of Koslowsky et al. is modified to take into account the new results, it is found that each of the eight accurately studied scrFt values differs from the average by approx. <1sigma, thus significantly improving the comparison of experiments with conserved-vector-current predictions. The new scrFt values are lower than before, which also brings experiments into very good agreement with the three-generation standard model, at the level of its quantum corrections.
Double Cluster Heads Model for Secure and Accurate Data Fusion in Wireless Sensor Networks
Fu, Jun-Song; Liu, Yun
2015-01-01
Secure and accurate data fusion is an important issue in wireless sensor networks (WSNs) and has been extensively researched in the literature. In this paper, by combining clustering techniques, reputation and trust systems, and data fusion algorithms, we propose a novel cluster-based data fusion model called Double Cluster Heads Model (DCHM) for secure and accurate data fusion in WSNs. Different from traditional clustering models in WSNs, two cluster heads are selected after clustering for each cluster based on the reputation and trust system and they perform data fusion independently of each other. Then, the results are sent to the base station where the dissimilarity coefficient is computed. If the dissimilarity coefficient of the two data fusion results exceeds the threshold preset by the users, the cluster heads will be added to blacklist, and the cluster heads must be reelected by the sensor nodes in a cluster. Meanwhile, feedback is sent from the base station to the reputation and trust system, which can help us to identify and delete the compromised sensor nodes in time. Through a series of extensive simulations, we found that the DCHM performed very well in data fusion security and accuracy. PMID:25608211
Applying an accurate spherical model to gamma-ray burst afterglow observations
NASA Astrophysics Data System (ADS)
Leventis, K.; van der Horst, A. J.; van Eerten, H. J.; Wijers, R. A. M. J.
2013-05-01
We present results of model fits to afterglow data sets of GRB 970508, GRB 980703 and GRB 070125, characterized by long and broad-band coverage. The model assumes synchrotron radiation (including self-absorption) from a spherical adiabatic blast wave and consists of analytic flux prescriptions based on numerical results. For the first time it combines the accuracy of hydrodynamic simulations through different stages of the outflow dynamics with the flexibility of simple heuristic formulas. The prescriptions are especially geared towards accurate description of the dynamical transition of the outflow from relativistic to Newtonian velocities in an arbitrary power-law density environment. We show that the spherical model can accurately describe the data only in the case of GRB 970508, for which we find a circumburst medium density n ∝ r-2. We investigate in detail the implied spectra and physical parameters of that burst. For the microphysics we show evidence for equipartition between the fraction of energy density carried by relativistic electrons and magnetic field. We also find that for the blast wave to be adiabatic, the fraction of electrons accelerated at the shock has to be smaller than 1. We present best-fitting parameters for the afterglows of all three bursts, including uncertainties in the parameters of GRB 970508, and compare the inferred values to those obtained by different authors.
NASA Astrophysics Data System (ADS)
Wohlfeil, J.; Hirschmüller, H.; Piltz, B.; Börner, A.; Suppa, M.
2012-07-01
Modern pixel-wise image matching algorithms like Semi-Global Matching (SGM) are able to compute high resolution digital surface models from airborne and spaceborne stereo imagery. Although image matching itself can be performed automatically, there are prerequisites, like high geometric accuracy, which are essential for ensuring the high quality of resulting surface models. Especially for line cameras, these prerequisites currently require laborious manual interaction using standard tools, which is a growing problem due to continually increasing demand for such surface models. The tedious work includes partly or fully manual selection of tie- and/or ground control points for ensuring the required accuracy of the relative orientation of images for stereo matching. It also includes masking of large water areas that seriously reduce the quality of the results. Furthermore, a good estimate of the depth range is required, since accurate estimates can seriously reduce the processing time for stereo matching. In this paper an approach is presented that allows performing all these steps fully automated. It includes very robust and precise tie point selection, enabling the accurate calculation of the images' relative orientation via bundle adjustment. It is also shown how water masking and elevation range estimation can be performed automatically on the base of freely available SRTM data. Extensive tests with a large number of different satellite images from QuickBird and WorldView are presented as proof of the robustness and reliability of the proposed method.
NASA Technical Reports Server (NTRS)
Sokalski, W. A.; Shibata, M.; Ornstein, R. L.; Rein, R.
1992-01-01
The quality of several atomic charge models based on different definitions has been analyzed using cumulative atomic multipole moments (CAMM). This formalism can generate higher atomic moments starting from any atomic charges, while preserving the corresponding molecular moments. The atomic charge contribution to the higher molecular moments, as well as to the electrostatic potentials, has been examined for CO and HCN molecules at several different levels of theory. The results clearly show that the electrostatic potential obtained from CAMM expansion is convergent up to R-5 term for all atomic charge models used. This illustrates that higher atomic moments can be used to supplement any atomic charge model to obtain more accurate description of electrostatic properties.
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
Gröning, Flora; Jones, Marc E H; Curtis, Neil; Herrel, Anthony; O'Higgins, Paul; Evans, Susan E; Fagan, Michael J
2013-07-01
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
An accurate and comprehensive model of thin fluid flows with inertia on curved substrates
NASA Astrophysics Data System (ADS)
Roberts, A. J.; Li, Zhenquan
2006-04-01
Consider the three-dimensional flow of a viscous Newtonian fluid upon a curved two-dimensional substrate when the fluid film is thin, as occurs in many draining, coating and biological flows. We derive a comprehensive model of the dynamics of the film, the model being expressed in terms of the film thickness eta and the average lateral velocity bar{bm u}. Centre manifold theory assures us that the model accurately and systematically includes the effects of the curvature of substrate, gravitational body force, fluid inertia and dissipation. The model resolves wavelike phenomena in the dynamics of viscous fluid flows over arbitrarily curved substrates such as cylinders, tubes and spheres. We briefly illustrate its use in simulating drop formation on cylindrical fibres, wave transitions, three-dimensional instabilities, Faraday waves, viscous hydraulic jumps, flow vortices in a compound channel and flow down and up a step. These models are the most complete models for thin-film flow of a Newtonian fluid; many other thin-film models can be obtained by different restrictions and truncations of the model derived here.
NASA Astrophysics Data System (ADS)
Smith, R.; Flynn, C.; Candlish, G. N.; Fellhauer, M.; Gibson, B. K.
2015-04-01
We present accurate models of the gravitational potential produced by a radially exponential disc mass distribution. The models are produced by combining three separate Miyamoto-Nagai discs. Such models have been used previously to model the disc of the Milky Way, but here we extend this framework to allow its application to discs of any mass, scalelength, and a wide range of thickness from infinitely thin to near spherical (ellipticities from 0 to 0.9). The models have the advantage of simplicity of implementation, and we expect faster run speeds over a double exponential disc treatment. The potentials are fully analytical, and differentiable at all points. The mass distribution of our models deviates from the radial mass distribution of a pure exponential disc by <0.4 per cent out to 4 disc scalelengths, and <1.9 per cent out to 10 disc scalelengths. We tabulate fitting parameters which facilitate construction of exponential discs for any scalelength, and a wide range of disc thickness (a user-friendly, web-based interface is also available). Our recipe is well suited for numerical modelling of the tidal effects of a giant disc galaxy on star clusters or dwarf galaxies. We consider three worked examples; the Milky Way thin and thick disc, and a discy dwarf galaxy.
Algal productivity modeling: a step toward accurate assessments of full-scale algal cultivation.
Béchet, Quentin; Chambonnière, Paul; Shilton, Andy; Guizard, Guillaume; Guieysse, Benoit
2015-05-01
A new biomass productivity model was parameterized for Chlorella vulgaris using short-term (<30 min) oxygen productivities from algal microcosms exposed to 6 light intensities (20-420 W/m(2)) and 6 temperatures (5-42 °C). The model was then validated against experimental biomass productivities recorded in bench-scale photobioreactors operated under 4 light intensities (30.6-74.3 W/m(2)) and 4 temperatures (10-30 °C), yielding an accuracy of ± 15% over 163 days of cultivation. This modeling approach addresses major challenges associated with the accurate prediction of algal productivity at full-scale. Firstly, while most prior modeling approaches have only considered the impact of light intensity on algal productivity, the model herein validated also accounts for the critical impact of temperature. Secondly, this study validates a theoretical approach to convert short-term oxygen productivities into long-term biomass productivities. Thirdly, the experimental methodology used has the practical advantage of only requiring one day of experimental work for complete model parameterization. The validation of this new modeling approach is therefore an important step for refining feasibility assessments of algae biotechnologies. PMID:25502920
Accurately modeling Gaussian beam propagation in the context of Monte Carlo techniques
NASA Astrophysics Data System (ADS)
Hokr, Brett H.; Winblad, Aidan; Bixler, Joel N.; Elpers, Gabriel; Zollars, Byron; Scully, Marlan O.; Yakovlev, Vladislav V.; Thomas, Robert J.
2016-03-01
Monte Carlo simulations are widely considered to be the gold standard for studying the propagation of light in turbid media. However, traditional Monte Carlo methods fail to account for diffraction because they treat light as a particle. This results in converging beams focusing to a point instead of a diffraction limited spot, greatly effecting the accuracy of Monte Carlo simulations near the focal plane. Here, we present a technique capable of simulating a focusing beam in accordance to the rules of Gaussian optics, resulting in a diffraction limited focal spot. This technique can be easily implemented into any traditional Monte Carlo simulation allowing existing models to be converted to include accurate focusing geometries with minimal effort. We will present results for a focusing beam in a layered tissue model, demonstrating that for different scenarios the region of highest intensity, thus the greatest heating, can change from the surface to the focus. The ability to simulate accurate focusing geometries will greatly enhance the usefulness of Monte Carlo for countless applications, including studying laser tissue interactions in medical applications and light propagation through turbid media.
Fu, Q.; Sun, W.B.; Yang, P.
1998-09-01
An accurate parameterization is presented for the infrared radiative properties of cirrus clouds. For the single-scattering calculations, a composite scheme is developed for randomly oriented hexagonal ice crystals by comparing results from Mie theory, anomalous diffraction theory (ADT), the geometric optics method (GOM), and the finite-difference time domain technique. This scheme employs a linear combination of single-scattering properties from the Mie theory, ADT, and GOM, which is accurate for a wide range of size parameters. Following the approach of Q. Fu, the extinction coefficient, absorption coefficient, and asymmetry factor are parameterized as functions of the cloud ice water content and generalized effective size (D{sub ge}). The present parameterization of the single-scattering properties of cirrus clouds is validated by examining the bulk radiative properties for a wide range of atmospheric conditions. Compared with reference results, the typical relative error in emissivity due to the parameterization is {approximately}2.2%. The accuracy of this parameterization guarantees its reliability in applications to climate models. The present parameterization complements the scheme for the solar radiative properties of cirrus clouds developed by Q. Fu for use in numerical models.
NASA Technical Reports Server (NTRS)
Kopasakis, George
2014-01-01
The presentation covers a recently developed methodology to model atmospheric turbulence as disturbances for aero vehicle gust loads and for controls development like flutter and inlet shock position. The approach models atmospheric turbulence in their natural fractional order form, which provides for more accuracy compared to traditional methods like the Dryden model, especially for high speed vehicle. The presentation provides a historical background on atmospheric turbulence modeling and the approaches utilized for air vehicles. This is followed by the motivation and the methodology utilized to develop the atmospheric turbulence fractional order modeling approach. Some examples covering the application of this method are also provided, followed by concluding remarks.
Burward-Hoy, J. M.; Geist, W. H.; Krick, M. S.; Mayo, D. R.
2004-01-01
Neutron multiplicity counting is a technique for the rapid, nondestructive measurement of plutonium mass in pure and impure materials. This technique is very powerful because it uses the measured coincidence count rates to determine the sample mass without requiring a set of representative standards for calibration. Interpreting measured singles, doubles, and triples count rates using the three-parameter standard point model accurately determines plutonium mass, neutron multiplication, and the ratio of ({alpha},n) to spontaneous-fission neutrons (alpha) for oxides of moderate mass. However, underlying standard point model assumptions - including constant neutron energy and constant multiplication throughout the sample - cause significant biases for the mass, multiplication, and alpha in measurements of metal and large, dense oxides.
Accurate Cold-Test Model of Helical TWT Slow-Wave Circuits
NASA Technical Reports Server (NTRS)
Kory, Carol L.; Dayton, J. A., Jr.
1998-01-01
Recently, a method has been established to accurately calculate cold-test data for helical slow-wave structures using the three-dimensional (3-D) electromagnetic computer code, MAFIA. Cold-test parameters have been calculated for several helical traveling-wave tube (TWT) slow-wave circuits possessing various support rod configurations, and results are presented here showing excellent agreement with experiment. The helical models include tape thickness, dielectric support shapes and material properties consistent with the actual circuits. The cold-test data from this helical model can be used as input into large-signal helical TWT interaction codes making it possible, for the first time, to design a complete TWT via computer simulation.
Accurate Cold-Test Model of Helical TWT Slow-Wave Circuits
NASA Technical Reports Server (NTRS)
Kory, Carol L.; Dayton, James A., Jr.
1998-01-01
Recently, a method has been established to accurately calculate cold-test data for helical slow-wave structures using the three-dimensional (3-D) electromagnetic computer code, MAxwell's equations by the Finite Integration Algorithm (MAFIA). Cold-test parameters have been calculated for several helical traveLing-wave tube (TWT) slow-wave circuits possessing various support rod configurations, and results are presented here showing excellent agreement with experiment. The helical models include tape thickness, dielectric support shapes and material properties consistent with the actual circuits. The cold-test data from this helical model can be used as input into large-signal helical TWT interaction codes making It possible, for the first time, to design complete TWT via computer simulation.
Accurate Cold-Test Model of Helical TWT Slow-Wave Circuits
NASA Technical Reports Server (NTRS)
Kory, Carol L.; Dayton, James A., Jr.
1997-01-01
Recently, a method has been established to accurately calculate cold-test data for helical slow-wave structures using the three-dimensional electromagnetic computer code, MAFIA. Cold-test parameters have been calculated for several helical traveling-wave tube (TWT) slow-wave circuits possessing various support rod configurations, and results are presented here showing excellent agreement with experiment. The helical models include tape thickness, dielectric support shapes and material properties consistent with the actual circuits. The cold-test data from this helical model can be used as input into large-signal helical TWT interaction codes making it possible, for the first time, to design a complete TWT via computer simulation.
Blackman, Jonathan; Field, Scott E; Galley, Chad R; Szilágyi, Béla; Scheel, Mark A; Tiglio, Manuel; Hemberger, Daniel A
2015-09-18
Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. Using reduced order modeling techniques, we construct an accurate surrogate model, which is evaluated in a millisecond to a second, for numerical relativity (NR) waveforms from nonspinning binary black hole coalescences with mass ratios in [1, 10] and durations corresponding to about 15 orbits before merger. We assess the model's uncertainty and show that our modeling strategy predicts NR waveforms not used for the surrogate's training with errors nearly as small as the numerical error of the NR code. Our model includes all spherical-harmonic _{-2}Y_{ℓm} waveform modes resolved by the NR code up to ℓ=8. We compare our surrogate model to effective one body waveforms from 50M_{⊙} to 300M_{⊙} for advanced LIGO detectors and find that the surrogate is always more faithful (by at least an order of magnitude in most cases). PMID:26430979
NASA Astrophysics Data System (ADS)
Kopparla, P.; Natraj, V.; Spurr, R. J. D.; Shia, R. L.; Yung, Y. L.
2014-12-01
Radiative transfer (RT) computations are an essential component of energy budget calculations in climate models. However, full treatment of RT processes is computationally expensive, prompting usage of 2-stream approximations in operational climate models. This simplification introduces errors of the order of 10% in the top of the atmosphere (TOA) fluxes [Randles et al., 2013]. Natraj et al. [2005, 2010] and Spurr and Natraj [2013] demonstrated the ability of a technique using principal component analysis (PCA) to speed up RT simulations. In the PCA method for RT performance enhancement, empirical orthogonal functions are developed for binned sets of inherent optical properties that possess some redundancy; costly multiple-scattering RT calculations are only done for those (few) optical states corresponding to the most important principal components, and correction factors are applied to approximate radiation fields. Here, we extend the PCA method to a broadband spectral region from the ultraviolet to the shortwave infrared (0.3-3 micron), accounting for major gas absorptions in this region. Comparisons between the new model, called Universal Principal Component Analysis model for Radiative Transfer (UPCART), 2-stream models (such as those used in climate applications) and line-by-line RT models are performed, in order for spectral radiances, spectral fluxes and broadband fluxes. Each of these are calculated at the TOA for several scenarios with varying aerosol types, extinction and scattering optical depth profiles, and solar and viewing geometries. We demonstrate that very accurate radiative forcing estimates can be obtained, with better than 1% accuracy in all spectral regions and better than 0.1% in most cases as compared to an exact line-by-line RT model. The model is comparable in speeds to 2-stream models, potentially rendering UPCART useful for operational General Circulation Models (GCMs). The operational speed and accuracy of UPCART can be further
Wang, Guotai; Zhang, Shaoting; Xie, Hongzhi; Metaxas, Dimitris N; Gu, Lixu
2015-01-01
Shape prior plays an important role in accurate and robust liver segmentation. However, liver shapes have complex variations and accurate modeling of liver shapes is challenging. Using large-scale training data can improve the accuracy but it limits the computational efficiency. In order to obtain accurate liver shape priors without sacrificing the efficiency when dealing with large-scale training data, we investigate effective and scalable shape prior modeling method that is more applicable in clinical liver surgical planning system. We employed the Sparse Shape Composition (SSC) to represent liver shapes by an optimized sparse combination of shapes in the repository, without any assumptions on parametric distributions of liver shapes. To leverage large-scale training data and improve the computational efficiency of SSC, we also introduced a homotopy-based method to quickly solve the L1-norm optimization problem in SSC. This method takes advantage of the sparsity of shape modeling, and solves the original optimization problem in SSC by continuously transforming it into a series of simplified problems whose solution is fast to compute. When new training shapes arrive gradually, the homotopy strategy updates the optimal solution on the fly and avoids re-computing it from scratch. Experiments showed that SSC had a high accuracy and efficiency in dealing with complex liver shape variations, excluding gross errors and preserving local details on the input liver shape. The homotopy-based SSC had a high computational efficiency, and its runtime increased very slowly when repository's capacity and vertex number rose to a large degree. When repository's capacity was 10,000, with 2000 vertices on each shape, homotopy method cost merely about 11.29 s to solve the optimization problem in SSC, nearly 2000 times faster than interior point method. The dice similarity coefficient (DSC), average symmetric surface distance (ASD), and maximum symmetric surface distance measurement
"Computational Modeling of Actinide Complexes"
Balasubramanian, K
2007-03-07
We will present our recent studies on computational actinide chemistry of complexes which are not only interesting from the standpoint of actinide coordination chemistry but also of relevance to environmental management of high-level nuclear wastes. We will be discussing our recent collaborative efforts with Professor Heino Nitsche of LBNL whose research group has been actively carrying out experimental studies on these species. Computations of actinide complexes are also quintessential to our understanding of the complexes found in geochemical, biochemical environments and actinide chemistry relevant to advanced nuclear systems. In particular we have been studying uranyl, plutonyl, and Cm(III) complexes are in aqueous solution. These studies are made with a variety of relativistic methods such as coupled cluster methods, DFT, and complete active space multi-configuration self-consistent-field (CASSCF) followed by large-scale CI computations and relativistic CI (RCI) computations up to 60 million configurations. Our computational studies on actinide complexes were motivated by ongoing EXAFS studies of speciated complexes in geo and biochemical environments carried out by Prof Heino Nitsche's group at Berkeley, Dr. David Clark at Los Alamos and Dr. Gibson's work on small actinide molecules at ORNL. The hydrolysis reactions of urnayl, neputyl and plutonyl complexes have received considerable attention due to their geochemical and biochemical importance but the results of free energies in solution and the mechanism of deprotonation have been topic of considerable uncertainty. We have computed deprotonating and migration of one water molecule from the first solvation shell to the second shell in UO{sub 2}(H{sub 2}O){sub 5}{sup 2+}, UO{sub 2}(H{sub 2}O){sub 5}{sup 2+}NpO{sub 2}(H{sub 2}O){sub 6}{sup +}, and PuO{sub 2}(H{sub 2}O){sub 5}{sup 2+} complexes. Our computed Gibbs free energy(7.27 kcal/m) in solution for the first time agrees with the experiment (7.1 kcal
Multi Sensor Data Integration for AN Accurate 3d Model Generation
NASA Astrophysics Data System (ADS)
Chhatkuli, S.; Satoh, T.; Tachibana, K.
2015-05-01
The aim of this paper is to introduce a novel technique of data integration between two different data sets, i.e. laser scanned RGB point cloud and oblique imageries derived 3D model, to create a 3D model with more details and better accuracy. In general, aerial imageries are used to create a 3D city model. Aerial imageries produce an overall decent 3D city models and generally suit to generate 3D model of building roof and some non-complex terrain. However, the automatically generated 3D model, from aerial imageries, generally suffers from the lack of accuracy in deriving the 3D model of road under the bridges, details under tree canopy, isolated trees, etc. Moreover, the automatically generated 3D model from aerial imageries also suffers from undulated road surfaces, non-conforming building shapes, loss of minute details like street furniture, etc. in many cases. On the other hand, laser scanned data and images taken from mobile vehicle platform can produce more detailed 3D road model, street furniture model, 3D model of details under bridge, etc. However, laser scanned data and images from mobile vehicle are not suitable to acquire detailed 3D model of tall buildings, roof tops, and so forth. Our proposed approach to integrate multi sensor data compensated each other's weakness and helped to create a very detailed 3D model with better accuracy. Moreover, the additional details like isolated trees, street furniture, etc. which were missing in the original 3D model derived from aerial imageries could also be integrated in the final model automatically. During the process, the noise in the laser scanned data for example people, vehicles etc. on the road were also automatically removed. Hence, even though the two dataset were acquired in different time period the integrated data set or the final 3D model was generally noise free and without unnecessary details.
Fitmunk: improving protein structures by accurate, automatic modeling of side-chain conformations.
Porebski, Przemyslaw Jerzy; Cymborowski, Marcin; Pasenkiewicz-Gierula, Marta; Minor, Wladek
2016-02-01
Improvements in crystallographic hardware and software have allowed automated structure-solution pipelines to approach a near-`one-click' experience for the initial determination of macromolecular structures. However, in many cases the resulting initial model requires a laborious, iterative process of refinement and validation. A new method has been developed for the automatic modeling of side-chain conformations that takes advantage of rotamer-prediction methods in a crystallographic context. The algorithm, which is based on deterministic dead-end elimination (DEE) theory, uses new dense conformer libraries and a hybrid energy function derived from experimental data and prior information about rotamer frequencies to find the optimal conformation of each side chain. In contrast to existing methods, which incorporate the electron-density term into protein-modeling frameworks, the proposed algorithm is designed to take advantage of the highly discriminatory nature of electron-density maps. This method has been implemented in the program Fitmunk, which uses extensive conformational sampling. This improves the accuracy of the modeling and makes it a versatile tool for crystallographic model building, refinement and validation. Fitmunk was extensively tested on over 115 new structures, as well as a subset of 1100 structures from the PDB. It is demonstrated that the ability of Fitmunk to model more than 95% of side chains accurately is beneficial for improving the quality of crystallographic protein models, especially at medium and low resolutions. Fitmunk can be used for model validation of existing structures and as a tool to assess whether side chains are modeled optimally or could be better fitted into electron density. Fitmunk is available as a web service at http://kniahini.med.virginia.edu/fitmunk/server/ or at http://fitmunk.bitbucket.org/. PMID:26894674
Are Quasi-Steady-State Approximated Models Suitable for Quantifying Intrinsic Noise Accurately?
Sengupta, Dola; Kar, Sandip
2015-01-01
Large gene regulatory networks (GRN) are often modeled with quasi-steady-state approximation (QSSA) to reduce the huge computational time required for intrinsic noise quantification using Gillespie stochastic simulation algorithm (SSA). However, the question still remains whether the stochastic QSSA model measures the intrinsic noise as accurately as the SSA performed for a detailed mechanistic model or not? To address this issue, we have constructed mechanistic and QSSA models for few frequently observed GRNs exhibiting switching behavior and performed stochastic simulations with them. Our results strongly suggest that the performance of a stochastic QSSA model in comparison to SSA performed for a mechanistic model critically relies on the absolute values of the mRNA and protein half-lives involved in the corresponding GRN. The extent of accuracy level achieved by the stochastic QSSA model calculations will depend on the level of bursting frequency generated due to the absolute value of the half-life of either mRNA or protein or for both the species. For the GRNs considered, the stochastic QSSA quantifies the intrinsic noise at the protein level with greater accuracy and for larger combinations of half-life values of mRNA and protein, whereas in case of mRNA the satisfactory accuracy level can only be reached for limited combinations of absolute values of half-lives. Further, we have clearly demonstrated that the abundance levels of mRNA and protein hardly matter for such comparison between QSSA and mechanistic models. Based on our findings, we conclude that QSSA model can be a good choice for evaluating intrinsic noise for other GRNs as well, provided we make a rational choice based on experimental half-life values available in literature. PMID:26327626
Fitmunk: improving protein structures by accurate, automatic modeling of side-chain conformations
Porebski, Przemyslaw Jerzy; Cymborowski, Marcin; Pasenkiewicz-Gierula, Marta; Minor, Wladek
2016-01-01
Improvements in crystallographic hardware and software have allowed automated structure-solution pipelines to approach a near-‘one-click’ experience for the initial determination of macromolecular structures. However, in many cases the resulting initial model requires a laborious, iterative process of refinement and validation. A new method has been developed for the automatic modeling of side-chain conformations that takes advantage of rotamer-prediction methods in a crystallographic context. The algorithm, which is based on deterministic dead-end elimination (DEE) theory, uses new dense conformer libraries and a hybrid energy function derived from experimental data and prior information about rotamer frequencies to find the optimal conformation of each side chain. In contrast to existing methods, which incorporate the electron-density term into protein-modeling frameworks, the proposed algorithm is designed to take advantage of the highly discriminatory nature of electron-density maps. This method has been implemented in the program Fitmunk, which uses extensive conformational sampling. This improves the accuracy of the modeling and makes it a versatile tool for crystallographic model building, refinement and validation. Fitmunk was extensively tested on over 115 new structures, as well as a subset of 1100 structures from the PDB. It is demonstrated that the ability of Fitmunk to model more than 95% of side chains accurately is beneficial for improving the quality of crystallographic protein models, especially at medium and low resolutions. Fitmunk can be used for model validation of existing structures and as a tool to assess whether side chains are modeled optimally or could be better fitted into electron density. Fitmunk is available as a web service at http://kniahini.med.virginia.edu/fitmunk/server/ or at http://fitmunk.bitbucket.org/. PMID:26894674
Filizola, Marta
2009-01-01
For years conventional drug design at G-protein coupled receptors (GPCRs) has mainly focused on the inhibition of a single receptor at a usually well-defined ligand-binding site. The recent discovery of more and more physiologically relevant GPCR dimers/oligomers suggests that selectively targeting these complexes or designing small molecules that inhibit receptor-receptor interactions might provide new opportunities for novel drug discovery. To uncover the fundamental mechanisms and dynamics governing GPCR dimerization/oligomerization, it is crucial to understand the dynamic process of receptor-receptor association, and to identify regions that are suitable for selective drug binding. This minireview highlights current progress in the development of increasingly accurate dynamic molecular models of GPCR oligomers based on structural, biochemical, and biophysical information that has recently appeared in the literature. In view of this new information, there has never been a more exciting time for computational research into GPCRs than at present. Information-driven modern molecular models of GPCR complexes are expected to efficiently guide the rational design of GPCR oligomer-specific drugs, possibly allowing researchers to reach for the high-hanging fruits in GPCR drug discovery, i.e. more potent and selective drugs for efficient therapeutic interventions. PMID:19465029
Argudo, David; Bethel, Neville P; Marcoline, Frank V; Grabe, Michael
2016-07-01
Biological membranes deform in response to resident proteins leading to a coupling between membrane shape and protein localization. Additionally, the membrane influences the function of membrane proteins. Here we review contributions to this field from continuum elastic membrane models focusing on the class of models that couple the protein to the membrane. While it has been argued that continuum models cannot reproduce the distortions observed in fully-atomistic molecular dynamics simulations, we suggest that this failure can be overcome by using chemically accurate representations of the protein. We outline our recent advances along these lines with our hybrid continuum-atomistic model, and we show the model is in excellent agreement with fully-atomistic simulations of the nhTMEM16 lipid scramblase. We believe that the speed and accuracy of continuum-atomistic methodologies will make it possible to simulate large scale, slow biological processes, such as membrane morphological changes, that are currently beyond the scope of other computational approaches. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov. PMID:26853937
A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina
Maturana, Matias I.; Apollo, Nicholas V.; Hadjinicolaou, Alex E.; Garrett, David J.; Cloherty, Shaun L.; Kameneva, Tatiana; Grayden, David B.; Ibbotson, Michael R.; Meffin, Hamish
2016-01-01
Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron’s electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy. PMID:27035143
Hybridization modeling of oligonucleotide SNP arrays for accurate DNA copy number estimation
Wan, Lin; Sun, Kelian; Ding, Qi; Cui, Yuehua; Li, Ming; Wen, Yalu; Elston, Robert C.; Qian, Minping; Fu, Wenjiang J
2009-01-01
Affymetrix SNP arrays have been widely used for single-nucleotide polymorphism (SNP) genotype calling and DNA copy number variation inference. Although numerous methods have achieved high accuracy in these fields, most studies have paid little attention to the modeling of hybridization of probes to off-target allele sequences, which can affect the accuracy greatly. In this study, we address this issue and demonstrate that hybridization with mismatch nucleotides (HWMMN) occurs in all SNP probe-sets and has a critical effect on the estimation of allelic concentrations (ACs). We study sequence binding through binding free energy and then binding affinity, and develop a probe intensity composite representation (PICR) model. The PICR model allows the estimation of ACs at a given SNP through statistical regression. Furthermore, we demonstrate with cell-line data of known true copy numbers that the PICR model can achieve reasonable accuracy in copy number estimation at a single SNP locus, by using the ratio of the estimated AC of each sample to that of the reference sample, and can reveal subtle genotype structure of SNPs at abnormal loci. We also demonstrate with HapMap data that the PICR model yields accurate SNP genotype calls consistently across samples, laboratories and even across array platforms. PMID:19586935
A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina.
Maturana, Matias I; Apollo, Nicholas V; Hadjinicolaou, Alex E; Garrett, David J; Cloherty, Shaun L; Kameneva, Tatiana; Grayden, David B; Ibbotson, Michael R; Meffin, Hamish
2016-04-01
Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron's electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy. PMID:27035143
Fast and accurate modeling of molecular atomization energies with machine learning.
Rupp, Matthias; Tkatchenko, Alexandre; Müller, Klaus-Robert; von Lilienfeld, O Anatole
2012-02-01
We introduce a machine learning model to predict atomization energies of a diverse set of organic molecules, based on nuclear charges and atomic positions only. The problem of solving the molecular Schrödinger equation is mapped onto a nonlinear statistical regression problem of reduced complexity. Regression models are trained on and compared to atomization energies computed with hybrid density-functional theory. Cross validation over more than seven thousand organic molecules yields a mean absolute error of ∼10 kcal/mol. Applicability is demonstrated for the prediction of molecular atomization potential energy curves. PMID:22400967
Do Ecological Niche Models Accurately Identify Climatic Determinants of Species Ranges?
Searcy, Christopher A; Shaffer, H Bradley
2016-04-01
Defining species' niches is central to understanding their distributions and is thus fundamental to basic ecology and climate change projections. Ecological niche models (ENMs) are a key component of making accurate projections and include descriptions of the niche in terms of both response curves and rankings of variable importance. In this study, we evaluate Maxent's ranking of environmental variables based on their importance in delimiting species' range boundaries by asking whether these same variables also govern annual recruitment based on long-term demographic studies. We found that Maxent-based assessments of variable importance in setting range boundaries in the California tiger salamander (Ambystoma californiense; CTS) correlate very well with how important those variables are in governing ongoing recruitment of CTS at the population level. This strong correlation suggests that Maxent's ranking of variable importance captures biologically realistic assessments of factors governing population persistence. However, this result holds only when Maxent models are built using best-practice procedures and variables are ranked based on permutation importance. Our study highlights the need for building high-quality niche models and provides encouraging evidence that when such models are built, they can reflect important aspects of a species' ecology. PMID:27028071
Linaro, Daniele; Storace, Marco; Giugliano, Michele
2011-01-01
Stochastic channel gating is the major source of intrinsic neuronal noise whose functional consequences at the microcircuit- and network-levels have been only partly explored. A systematic study of this channel noise in large ensembles of biophysically detailed model neurons calls for the availability of fast numerical methods. In fact, exact techniques employ the microscopic simulation of the random opening and closing of individual ion channels, usually based on Markov models, whose computational loads are prohibitive for next generation massive computer models of the brain. In this work, we operatively define a procedure for translating any Markov model describing voltage- or ligand-gated membrane ion-conductances into an effective stochastic version, whose computer simulation is efficient, without compromising accuracy. Our approximation is based on an improved Langevin-like approach, which employs stochastic differential equations and no Montecarlo methods. As opposed to an earlier proposal recently debated in the literature, our approximation reproduces accurately the statistical properties of the exact microscopic simulations, under a variety of conditions, from spontaneous to evoked response features. In addition, our method is not restricted to the Hodgkin-Huxley sodium and potassium currents and is general for a variety of voltage- and ligand-gated ion currents. As a by-product, the analysis of the properties emerging in exact Markov schemes by standard probability calculus enables us for the first time to analytically identify the sources of inaccuracy of the previous proposal, while providing solid ground for its modification and improvement we present here. PMID:21423712
Accurate integral equation theory for the central force model of liquid water and ionic solutions
NASA Astrophysics Data System (ADS)
Ichiye, Toshiko; Haymet, A. D. J.
1988-10-01
The atom-atom pair correlation functions and thermodynamics of the central force model of water, introduced by Lemberg, Stillinger, and Rahman, have been calculated accurately by an integral equation method which incorporates two new developments. First, a rapid new scheme has been used to solve the Ornstein-Zernike equation. This scheme combines the renormalization methods of Allnatt, and Rossky and Friedman with an extension of the trigonometric basis-set solution of Labik and co-workers. Second, by adding approximate ``bridge'' functions to the hypernetted-chain (HNC) integral equation, we have obtained predictions for liquid water in which the hydrogen bond length and number are in good agreement with ``exact'' computer simulations of the same model force laws. In addition, for dilute ionic solutions, the ion-oxygen and ion-hydrogen coordination numbers display both the physically correct stoichiometry and good agreement with earlier simulations. These results represent a measurable improvement over both a previous HNC solution of the central force model and the ex-RISM integral equation solutions for the TIPS and other rigid molecule models of water.
Efficient and Accurate Explicit Integration Algorithms with Application to Viscoplastic Models
NASA Technical Reports Server (NTRS)
Arya, Vinod K.
1994-01-01
Several explicit integration algorithms with self-adative time integration strategies are developed and investigated for efficiency and accuracy. These algorithms involve the Runge-Kutta second order, the lower Runge-Kutta method of orders one and two, and the exponential integration method. The algorithms are applied to viscoplastic models put forth by Freed and Verrilli and Bodner and Partom for thermal/mechanical loadings (including tensile, relaxation, and cyclic loadings). The large amount of computations performed showed that, for comparable accuracy, the efficiency of an integration algorithm depends significantly on the type of application (loading). However, in general, for the aforementioned loadings and viscoplastic models, the exponential integration algorithm with the proposed self-adaptive time integration strategy worked more (or comparably) efficiently and accurately than the other integration algorithms. Using this strategy for integrating viscoplastic models may lead to considerable savings in computer time (better efficiency) without adversely affecting the accuracy of the results. This conclusion should encourage the utilization of viscoplastic models in the stress analysis and design of structural components.
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. PMID:27260782
Capturing Complexity through Maturity Modelling
ERIC Educational Resources Information Center
Underwood, Jean; Dillon, Gayle
2004-01-01
The impact of information and communication technologies (ICT) on the process and products of education is difficult to assess for a number of reasons. In brief, education is a complex system of interrelationships, of checks and balances. This context is not a neutral backdrop on which teaching and learning are played out. Rather, it may help, or…
Santolini, Marc; Mora, Thierry; Hakim, Vincent
2014-01-01
The identification of transcription factor binding sites (TFBSs) on genomic DNA is of crucial importance for understanding and predicting regulatory elements in gene networks. TFBS motifs are commonly described by Position Weight Matrices (PWMs), in which each DNA base pair contributes independently to the transcription factor (TF) binding. However, this description ignores correlations between nucleotides at different positions, and is generally inaccurate: analysing fly and mouse in vivo ChIPseq data, we show that in most cases the PWM model fails to reproduce the observed statistics of TFBSs. To overcome this issue, we introduce the pairwise interaction model (PIM), a generalization of the PWM model. The model is based on the principle of maximum entropy and explicitly describes pairwise correlations between nucleotides at different positions, while being otherwise as unconstrained as possible. It is mathematically equivalent to considering a TF-DNA binding energy that depends additively on each nucleotide identity at all positions in the TFBS, like the PWM model, but also additively on pairs of nucleotides. We find that the PIM significantly improves over the PWM model, and even provides an optimal description of TFBS statistics within statistical noise. The PIM generalizes previous approaches to interdependent positions: it accounts for co-variation of two or more base pairs, and predicts secondary motifs, while outperforming multiple-motif models consisting of mixtures of PWMs. We analyse the structure of pairwise interactions between nucleotides, and find that they are sparse and dominantly located between consecutive base pairs in the flanking region of TFBS. Nonetheless, interactions between pairs of non-consecutive nucleotides are found to play a significant role in the obtained accurate description of TFBS statistics. The PIM is computationally tractable, and provides a general framework that should be useful for describing and predicting TFBSs beyond
Application of thin plate splines for accurate regional ionosphere modeling with multi-GNSS data
NASA Astrophysics Data System (ADS)
Krypiak-Gregorczyk, Anna; Wielgosz, Pawel; Borkowski, Andrzej
2016-04-01
GNSS-derived regional ionosphere models are widely used in both precise positioning, ionosphere and space weather studies. However, their accuracy is often not sufficient to support precise positioning, RTK in particular. In this paper, we presented new approach that uses solely carrier phase multi-GNSS observables and thin plate splines (TPS) for accurate ionospheric TEC modeling. TPS is a closed solution of a variational problem minimizing both the sum of squared second derivatives of a smoothing function and the deviation between data points and this function. This approach is used in UWM-rt1 regional ionosphere model developed at UWM in Olsztyn. The model allows for providing ionospheric TEC maps with high spatial and temporal resolutions - 0.2x0.2 degrees and 2.5 minutes, respectively. For TEC estimation, EPN and EUPOS reference station data is used. The maps are available with delay of 15-60 minutes. In this paper we compare the performance of UWM-rt1 model with IGS global and CODE regional ionosphere maps during ionospheric storm that took place on March 17th, 2015. During this storm, the TEC level over Europe doubled comparing to earlier quiet days. The performance of the UWM-rt1 model was validated by (a) comparison to reference double-differenced ionospheric corrections over selected baselines, and (b) analysis of post-fit residuals to calibrated carrier phase geometry-free observational arcs at selected test stations. The results show a very good performance of UWM-rt1 model. The obtained post-fit residuals in case of UWM maps are lower by one order of magnitude comparing to IGS maps. The accuracy of UWM-rt1 -derived TEC maps is estimated at 0.5 TECU. This may be directly translated to the user positioning domain.
NASA Astrophysics Data System (ADS)
Somerville, W. R. C.; Auguié, B.; Le Ru, E. C.
2016-03-01
SMARTIES calculates the optical properties of oblate and prolate spheroidal particles, with comparable capabilities and ease-of-use as Mie theory for spheres. This suite of MATLAB codes provides a fully documented implementation of an improved T-matrix algorithm for the theoretical modelling of electromagnetic scattering by particles of spheroidal shape. Included are scripts that cover a range of scattering problems relevant to nanophotonics and plasmonics, including calculation of far-field scattering and absorption cross-sections for fixed incidence orientation, orientation-averaged cross-sections and scattering matrix, surface-field calculations as well as near-fields, wavelength-dependent near-field and far-field properties, and access to lower-level functions implementing the T-matrix calculations, including the T-matrix elements which may be calculated more accurately than with competing codes.
A fast and accurate PCA based radiative transfer model: Extension to the broadband shortwave region
NASA Astrophysics Data System (ADS)
Kopparla, Pushkar; Natraj, Vijay; Spurr, Robert; Shia, Run-Lie; Crisp, David; Yung, Yuk L.
2016-04-01
Accurate radiative transfer (RT) calculations are necessary for many earth-atmosphere applications, from remote sensing retrieval to climate modeling. A Principal Component Analysis (PCA)-based spectral binning method has been shown to provide an order of magnitude increase in computational speed while maintaining an overall accuracy of 0.01% (compared to line-by-line calculations) over narrow spectral bands. In this paper, we have extended the PCA method for RT calculations over the entire shortwave region of the spectrum from 0.3 to 3 microns. The region is divided into 33 spectral fields covering all major gas absorption regimes. We find that the RT performance runtimes are shorter by factors between 10 and 100, while root mean square errors are of order 0.01%.
Accurate force fields and methods for modelling organic molecular crystals at finite temperatures.
Nyman, Jonas; Pundyke, Orla Sheehan; Day, Graeme M
2016-06-21
We present an assessment of the performance of several force fields for modelling intermolecular interactions in organic molecular crystals using the X23 benchmark set. The performance of the force fields is compared to several popular dispersion corrected density functional methods. In addition, we present our implementation of lattice vibrational free energy calculations in the quasi-harmonic approximation, using several methods to account for phonon dispersion. This allows us to also benchmark the force fields' reproduction of finite temperature crystal structures. The results demonstrate that anisotropic atom-atom multipole-based force fields can be as accurate as several popular DFT-D methods, but have errors 2-3 times larger than the current best DFT-D methods. The largest error in the examined force fields is a systematic underestimation of the (absolute) lattice energy. PMID:27230942
O’Connor, James PB; Boult, Jessica KR; Jamin, Yann; Babur, Muhammad; Finegan, Katherine G; Williams, Kaye J; Little, Ross A; Jackson, Alan; Parker, Geoff JM; Reynolds, Andrew R; Waterton, John C; Robinson, Simon P
2015-01-01
There is a clinical need for non-invasive biomarkers of tumor hypoxia for prognostic and predictive studies, radiotherapy planning and therapy monitoring. Oxygen enhanced MRI (OE-MRI) is an emerging imaging technique for quantifying the spatial distribution and extent of tumor oxygen delivery in vivo. In OE-MRI, the longitudinal relaxation rate of protons (ΔR1) changes in proportion to the concentration of molecular oxygen dissolved in plasma or interstitial tissue fluid. Therefore, well-oxygenated tissues show positive ΔR1. We hypothesized that the fraction of tumor tissue refractory to oxygen challenge (lack of positive ΔR1, termed “Oxy-R fraction”) would be a robust biomarker of hypoxia in models with varying vascular and hypoxic features. Here we demonstrate that OE-MRI signals are accurate, precise and sensitive to changes in tumor pO2 in highly vascular 786-0 renal cancer xenografts. Furthermore, we show that Oxy-R fraction can quantify the hypoxic fraction in multiple models with differing hypoxic and vascular phenotypes, when used in combination with measurements of tumor perfusion. Finally, Oxy-R fraction can detect dynamic changes in hypoxia induced by the vasomodulator agent hydralazine. In contrast, more conventional biomarkers of hypoxia (derived from blood oxygenation-level dependent MRI and dynamic contrast-enhanced MRI) did not relate to tumor hypoxia consistently. Our results show that the Oxy-R fraction accurately quantifies tumor hypoxia non-invasively and is immediately translatable to the clinic. PMID:26659574
Nielsen, Jens; D’Avezac, Mayeul; Hetherington, James; Stamatakis, Michail
2013-12-14
Ab initio kinetic Monte Carlo (KMC) simulations have been successfully applied for over two decades to elucidate the underlying physico-chemical phenomena on the surfaces of heterogeneous catalysts. These simulations necessitate detailed knowledge of the kinetics of elementary reactions constituting the reaction mechanism, and the energetics of the species participating in the chemistry. The information about the energetics is encoded in the formation energies of gas and surface-bound species, and the lateral interactions between adsorbates on the catalytic surface, which can be modeled at different levels of detail. The majority of previous works accounted for only pairwise-additive first nearest-neighbor interactions. More recently, cluster-expansion Hamiltonians incorporating long-range interactions and many-body terms have been used for detailed estimations of catalytic rate [C. Wu, D. J. Schmidt, C. Wolverton, and W. F. Schneider, J. Catal. 286, 88 (2012)]. In view of the increasing interest in accurate predictions of catalytic performance, there is a need for general-purpose KMC approaches incorporating detailed cluster expansion models for the adlayer energetics. We have addressed this need by building on the previously introduced graph-theoretical KMC framework, and we have developed Zacros, a FORTRAN2003 KMC package for simulating catalytic chemistries. To tackle the high computational cost in the presence of long-range interactions we introduce parallelization with OpenMP. We further benchmark our framework by simulating a KMC analogue of the NO oxidation system established by Schneider and co-workers [J. Catal. 286, 88 (2012)]. We show that taking into account only first nearest-neighbor interactions may lead to large errors in the prediction of the catalytic rate, whereas for accurate estimates thereof, one needs to include long-range terms in the cluster expansion.
The S-model: A highly accurate MOST model for CAD
NASA Astrophysics Data System (ADS)
Satter, J. H.
1986-09-01
A new MOST model which combines simplicity and a logical structure with a high accuracy of only 0.5-4.5% is presented. The model is suited for enhancement and depletion devices with either large or small dimensions. It includes the effects of scattering and carrier-velocity saturation as well as the influence of the intrinsic source and drain series resistance. The decrease of the drain current due to substrate bias is incorporated too. The model is in the first place intended for digital purposes. All necessary quantities are calculated in a straightforward manner without iteration. An almost entirely new way of determining the parameters is described and a new cluster parameter is introduced, which is responsible for the high accuracy of the model. The total number of parameters is 7. A still simpler β expression is derived, which is suitable for only one value of the substrate bias and contains only three parameters, while maintaining the accuracy. The way in which the parameters are determined is readily suited for automatic measurement. A simple linear regression procedure programmed in the computer, which controls the measurements, produces the parameter values.
Does increased hydrochemical model complexity decrease robustness?
NASA Astrophysics Data System (ADS)
Medici, C.; Wade, A. J.; Francés, F.
2012-05-01
SummaryThe aim of this study was, within a sensitivity analysis framework, to determine if additional model complexity gives a better capability to model the hydrology and nitrogen dynamics of a small Mediterranean forested catchment or if the additional parameters cause over-fitting. Three nitrogen-models of varying hydrological complexity were considered. For each model, general sensitivity analysis (GSA) and Generalized Likelihood Uncertainty Estimation (GLUE) were applied, each based on 100,000 Monte Carlo simulations. The results highlighted the most complex structure as the most appropriate, providing the best representation of the non-linear patterns observed in the flow and streamwater nitrate concentrations between 1999 and 2002. Its 5% and 95% GLUE bounds, obtained considering a multi-objective approach, provide the narrowest band for streamwater nitrogen, which suggests increased model robustness, though all models exhibit periods of inconsistent good and poor fits between simulated outcomes and observed data. The results confirm the importance of the riparian zone in controlling the short-term (daily) streamwater nitrogen dynamics in this catchment but not the overall flux of nitrogen from the catchment. It was also shown that as the complexity of a hydrological model increases over-parameterisation occurs, but the converse is true for a water quality model where additional process representation leads to additional acceptable model simulations. Water quality data help constrain the hydrological representation in process-based models. Increased complexity was justifiable for modelling river-system hydrochemistry. Increased complexity was justifiable for modelling river-system hydrochemistry.
Random generalized linear model: a highly accurate and interpretable ensemble predictor
2013-01-01
Background Ensemble predictors such as the random forest are known to have superior accuracy but their black-box predictions are difficult to interpret. In contrast, a generalized linear model (GLM) is very interpretable especially when forward feature selection is used to construct the model. However, forward feature selection tends to overfit the data and leads to low predictive accuracy. Therefore, it remains an important research goal to combine the advantages of ensemble predictors (high accuracy) with the advantages of forward regression modeling (interpretability). To address this goal several articles have explored GLM based ensemble predictors. Since limited evaluations suggested that these ensemble predictors were less accurate than alternative predictors, they have found little attention in the literature. Results Comprehensive evaluations involving hundreds of genomic data sets, the UCI machine learning benchmark data, and simulations are used to give GLM based ensemble predictors a new and careful look. A novel bootstrap aggregated (bagged) GLM predictor that incorporates several elements of randomness and instability (random subspace method, optional interaction terms, forward variable selection) often outperforms a host of alternative prediction methods including random forests and penalized regression models (ridge regression, elastic net, lasso). This random generalized linear model (RGLM) predictor provides variable importance measures that can be used to define a “thinned” ensemble predictor (involving few features) that retains excellent predictive accuracy. Conclusion RGLM is a state of the art predictor that shares the advantages of a random forest (excellent predictive accuracy, feature importance measures, out-of-bag estimates of accuracy) with those of a forward selected generalized linear model (interpretability). These methods are implemented in the freely available R software package randomGLM. PMID:23323760
Accurate Time-Dependent Traveling-Wave Tube Model Developed for Computational Bit-Error-Rate Testing
NASA Technical Reports Server (NTRS)
Kory, Carol L.
2001-01-01
The phenomenal growth of the satellite communications industry has created a large demand for traveling-wave tubes (TWT's) operating with unprecedented specifications requiring the design and production of many novel devices in record time. To achieve this, the TWT industry heavily relies on computational modeling. However, the TWT industry's computational modeling capabilities need to be improved because there are often discrepancies between measured TWT data and that predicted by conventional two-dimensional helical TWT interaction codes. This limits the analysis and design of novel devices or TWT's with parameters differing from what is conventionally manufactured. In addition, the inaccuracy of current computational tools limits achievable TWT performance because optimized designs require highly accurate models. To address these concerns, a fully three-dimensional, time-dependent, helical TWT interaction model was developed using the electromagnetic particle-in-cell code MAFIA (Solution of MAxwell's equations by the Finite-Integration-Algorithm). The model includes a short section of helical slow-wave circuit with excitation fed by radiofrequency input/output couplers, and an electron beam contained by periodic permanent magnet focusing. A cutaway view of several turns of the three-dimensional helical slow-wave circuit with input/output couplers is shown. This has been shown to be more accurate than conventionally used two-dimensional models. The growth of the communications industry has also imposed a demand for increased data rates for the transmission of large volumes of data. To achieve increased data rates, complex modulation and multiple access techniques are employed requiring minimum distortion of the signal as it is passed through the TWT. Thus, intersymbol interference (ISI) becomes a major consideration, as well as suspected causes such as reflections within the TWT. To experimentally investigate effects of the physical TWT on ISI would be
Gay, Guillaume; Courtheoux, Thibault; Reyes, Céline
2012-01-01
In fission yeast, erroneous attachments of spindle microtubules to kinetochores are frequent in early mitosis. Most are corrected before anaphase onset by a mechanism involving the protein kinase Aurora B, which destabilizes kinetochore microtubules (ktMTs) in the absence of tension between sister chromatids. In this paper, we describe a minimal mathematical model of fission yeast chromosome segregation based on the stochastic attachment and detachment of ktMTs. The model accurately reproduces the timing of correct chromosome biorientation and segregation seen in fission yeast. Prevention of attachment defects requires both appropriate kinetochore orientation and an Aurora B–like activity. The model also reproduces abnormal chromosome segregation behavior (caused by, for example, inhibition of Aurora B). It predicts that, in metaphase, merotelic attachment is prevented by a kinetochore orientation effect and corrected by an Aurora B–like activity, whereas in anaphase, it is corrected through unbalanced forces applied to the kinetochore. These unbalanced forces are sufficient to prevent aneuploidy. PMID:22412019
Accurate models for P-gp drug recognition induced from a cancer cell line cytotoxicity screen.
Levatić, Jurica; Ćurak, Jasna; Kralj, Marijeta; Šmuc, Tomislav; Osmak, Maja; Supek, Fran
2013-07-25
P-glycoprotein (P-gp, MDR1) is a promiscuous drug efflux pump of substantial pharmacological importance. Taking advantage of large-scale cytotoxicity screening data involving 60 cancer cell lines, we correlated the differential biological activities of ∼13,000 compounds against cellular P-gp levels. We created a large set of 934 high-confidence P-gp substrates or nonsubstrates by enforcing agreement with an orthogonal criterion involving P-gp overexpressing ADR-RES cells. A support vector machine (SVM) was 86.7% accurate in discriminating P-gp substrates on independent test data, exceeding previous models. Two molecular features had an overarching influence: nearly all P-gp substrates were large (>35 atoms including H) and dense (specific volume of <7.3 Å(3)/atom) molecules. Seven other descriptors and 24 molecular fragments ("effluxophores") were found enriched in the (non)substrates and incorporated into interpretable rule-based models. Biological experiments on an independent P-gp overexpressing cell line, the vincristine-resistant VK2, allowed us to reclassify six compounds previously annotated as substrates, validating our method's predictive ability. Models are freely available at http://pgp.biozyne.com . PMID:23772653
Complexity and Uncertainty in Soil Nitrogen Modeling
NASA Astrophysics Data System (ADS)
Ajami, N. K.; Gu, C.
2009-12-01
Model uncertainty is rarely considered in the field of biogeochemical modeling. The standard biogeochemical modeling approach is to proceed based on one selected model with the “right” complexity level based on data availability. However other plausible models can result in dissimilar answer to the scientific question in hand using the same set of data. Relying on a single model can lead to underestimation of uncertainty associated with the results and therefore lead to unreliable conclusions. Multi-model ensemble strategy is a means to exploit the diversity of skillful predictions from different models with multiple levels of complexity. The aim of this study is two fold, first to explore the impact of a model’s complexity level on the accuracy of the end results and second to introduce a probabilistic multi-model strategy in the context of a process-based biogeochemical model. We developed three different versions of a biogeochemical model, TOUGHREACT-N, with various complexity levels. Each one of these models was calibrated against the observed data from a tomato field in Western Sacramento County, California, and considered two different weighting sets on the objective function. This way we created a set of six ensemble members. The Bayesian Model Averaging (BMA) approach was then used to combine these ensemble members by the likelihood that an individual model is correct given the observations. The results clearly indicate the need to consider a multi-model ensemble strategy over a single model selection in biogeochemical modeling.
NASA Astrophysics Data System (ADS)
West, J. B.; Ehleringer, J. R.; Cerling, T.
2006-12-01
Understanding how the biosphere responds to change it at the heart of biogeochemistry, ecology, and other Earth sciences. The dramatic increase in human population and technological capacity over the past 200 years or so has resulted in numerous, simultaneous changes to biosphere structure and function. This, then, has lead to increased urgency in the scientific community to try to understand how systems have already responded to these changes, and how they might do so in the future. Since all biospheric processes exhibit some patchiness or patterns over space, as well as time, we believe that understanding the dynamic interactions between natural systems and human technological manipulations can be improved if these systems are studied in an explicitly spatial context. We present here results of some of our efforts to model the spatial variation in the stable isotope ratios (δ2H and δ18O) of plants over large spatial extents, and how these spatial model predictions compare to spatially explicit data. Stable isotopes trace and record ecological processes and as such, if modeled correctly over Earth's surface allow us insights into changes in biosphere states and processes across spatial scales. The data-model comparisons show good agreement, in spite of the remaining uncertainties (e.g., plant source water isotopic composition). For example, inter-annual changes in climate are recorded in wine stable isotope ratios. Also, a much simpler model of leaf water enrichment driven with spatially continuous global rasters of precipitation and climate normals largely agrees with complex GCM modeling that includes leaf water δ18O. Our results suggest that modeling plant stable isotope ratios across large spatial extents may be done with reasonable accuracy, including over time. These spatial maps, or isoscapes, can now be utilized to help understand spatially distributed data, as well as to help guide future studies designed to understand ecological change across
Elvira, L; Hernandez, F; Cuesta, P; Cano, S; Gonzalez-Martin, J-V; Astiz, S
2013-06-01
Although the intensive production system of Lacaune dairy sheep is the only profitable method for producers outside of the French Roquefort area, little is known about this type of systems. This study evaluated yield records of 3677 Lacaune sheep under intensive management between 2005 and 2010 in order to describe the lactation curve of this breed and to investigate the suitability of different mathematical functions for modeling this curve. A total of 7873 complete lactations during a 40-week lactation period corresponding to 201 281 pieces of weekly yield data were used. First, five mathematical functions were evaluated on the basis of the residual mean square, determination coefficient, Durbin Watson and Runs Test values. The two better models were found to be Pollott Additive and fractional polynomial (FP). In the second part of the study, the milk yield, peak of milk yield, day of peak and persistency of the lactations were calculated with Pollot Additive and FP models and compared with the real data. The results indicate that both models gave an extremely accurate fit to Lacaune lactation curves in order to predict milk yields (P = 0.871), with the FP model being the best choice to provide a good fit to an extensive amount of real data and applicable on farm without specific statistical software. On the other hand, the interpretation of the parameters of the Pollott Additive function helps to understand the biology of the udder of the Lacaune sheep. The characteristics of the Lacaune lactation curve and milk yield are affected by lactation number and length. The lactation curves obtained in the present study allow the early identification of ewes with low milk yield potential, which will help to optimize farm profitability. PMID:23257242
NASA Astrophysics Data System (ADS)
Kopparla, P.; Natraj, V.; Shia, R. L.; Spurr, R. J. D.; Crisp, D.; Yung, Y. L.
2015-12-01
Radiative transfer (RT) computations form the engine of atmospheric retrieval codes. However, full treatment of RT processes is computationally expensive, prompting usage of two-stream approximations in current exoplanetary atmospheric retrieval codes [Line et al., 2013]. Natraj et al. [2005, 2010] and Spurr and Natraj [2013] demonstrated the ability of a technique using principal component analysis (PCA) to speed up RT computations. In the PCA method for RT performance enhancement, empirical orthogonal functions are developed for binned sets of inherent optical properties that possess some redundancy; costly multiple-scattering RT calculations are only done for those few optical states corresponding to the most important principal components, and correction factors are applied to approximate radiation fields. Kopparla et al. [2015, in preparation] extended the PCA method to a broadband spectral region from the ultraviolet to the shortwave infrared (0.3-3 micron), accounting for major gas absorptions in this region. Here, we apply the PCA method to a some typical (exo-)planetary retrieval problems. Comparisons between the new model, called Universal Principal Component Analysis Radiative Transfer (UPCART) model, two-stream models and line-by-line RT models are performed, for spectral radiances, spectral fluxes and broadband fluxes. Each of these are calculated at the top of the atmosphere for several scenarios with varying aerosol types, extinction and scattering optical depth profiles, and stellar and viewing geometries. We demonstrate that very accurate radiance and flux estimates can be obtained, with better than 1% accuracy in all spectral regions and better than 0.1% in most cases, as compared to a numerically exact line-by-line RT model. The accuracy is enhanced when the results are convolved to typical instrument resolutions. The operational speed and accuracy of UPCART can be further improved by optimizing binning schemes and parallelizing the codes, work
NASA Astrophysics Data System (ADS)
Huang, Guo-Jiao; Bai, Chao-Ying; Greenhalgh, Stewart
2013-09-01
The traditional grid/cell-based wavefront expansion algorithms, such as the shortest path algorithm, can only find the first arrivals or multiply reflected (or mode converted) waves transmitted from subsurface interfaces, but cannot calculate the other later reflections/conversions having a minimax time path. In order to overcome the above limitations, we introduce the concept of a stationary minimax time path of Fermat's Principle into the multistage irregular shortest path method. Here we extend it from Cartesian coordinates for a flat earth model to global ray tracing of multiple phases in a 3-D complex spherical earth model. The ray tracing results for 49 different kinds of crustal, mantle and core phases show that the maximum absolute traveltime error is less than 0.12 s and the average absolute traveltime error is within 0.09 s when compared with the AK135 theoretical traveltime tables for a 1-D reference model. Numerical tests in terms of computational accuracy and CPU time consumption indicate that the new scheme is an accurate, efficient and a practical way to perform 3-D multiphase arrival tracking in regional or global traveltime tomography.
Fock spaces for modeling macromolecular complexes
NASA Astrophysics Data System (ADS)
Kinney, Justin
Large macromolecular complexes play a fundamental role in how cells function. Here I describe a Fock space formalism for mathematically modeling these complexes. Specifically, this formalism allows ensembles of complexes to be defined in terms of elementary molecular ``building blocks'' and ``assembly rules.'' Such definitions avoid the massive redundancy inherent in standard representations, in which all possible complexes are manually enumerated. Methods for systematically computing ensembles of complexes from a list of components and interaction rules are described. I also show how this formalism readily accommodates coarse-graining. Finally, I introduce diagrammatic techniques that greatly facilitate the application of this formalism to both equilibrium and non-equilibrium biochemical systems.
NASA Astrophysics Data System (ADS)
Kees, C. E.; Farthing, M. W.; Terrel, A.; Certik, O.; Seljebotn, D.
2013-12-01
This presentation will focus on two barriers to progress in the hydrological modeling community, and research and development conducted to lessen or eliminate them. The first is a barrier to sharing hydrological models among specialized scientists that is caused by intertwining the implementation of numerical methods with the implementation of abstract numerical modeling information. In the Proteus toolkit for computational methods and simulation, we have decoupled these two important parts of computational model through separate "physics" and "numerics" interfaces. More recently we have begun developing the Strong Form Language for easy and direct representation of the mathematical model formulation in a domain specific language embedded in Python. The second major barrier is sharing ANY scientific software tools that have complex library or module dependencies, as most parallel, multi-physics hydrological models must have. In this setting, users and developer are dependent on an entire distribution, possibly depending on multiple compilers and special instructions depending on the environment of the target machine. To solve these problem we have developed, hashdist, a stateless package management tool and a resulting portable, open source scientific software distribution.
Molecular simulation and modeling of complex I.
Hummer, Gerhard; Wikström, Mårten
2016-07-01
Molecular modeling and molecular dynamics simulations play an important role in the functional characterization of complex I. With its large size and complicated function, linking quinone reduction to proton pumping across a membrane, complex I poses unique modeling challenges. Nonetheless, simulations have already helped in the identification of possible proton transfer pathways. Simulations have also shed light on the coupling between electron and proton transfer, thus pointing the way in the search for the mechanistic principles underlying the proton pump. In addition to reviewing what has already been achieved in complex I modeling, we aim here to identify pressing issues and to provide guidance for future research to harness the power of modeling in the functional characterization of complex I. This article is part of a Special Issue entitled Respiratory complex I, edited by Volker Zickermann and Ulrich Brandt. PMID:26780586
Telfer, Scott; Erdemir, Ahmet; Woodburn, James; Cavanagh, Peter R
2016-01-25
Integration of patient-specific biomechanical measurements into the design of therapeutic footwear has been shown to improve clinical outcomes in patients with diabetic foot disease. The addition of numerical simulations intended to optimise intervention design may help to build on these advances, however at present the time and labour required to generate and run personalised models of foot anatomy restrict their routine clinical utility. In this study we developed second-generation personalised simple finite element (FE) models of the forefoot with varying geometric fidelities. Plantar pressure predictions from barefoot, shod, and shod with insole simulations using simplified models were compared to those obtained from CT-based FE models incorporating more detailed representations of bone and tissue geometry. A simplified model including representations of metatarsals based on simple geometric shapes, embedded within a contoured soft tissue block with outer geometry acquired from a 3D surface scan was found to provide pressure predictions closest to the more complex model, with mean differences of 13.3kPa (SD 13.4), 12.52kPa (SD 11.9) and 9.6kPa (SD 9.3) for barefoot, shod, and insole conditions respectively. The simplified model design could be produced in <1h compared to >3h in the case of the more detailed model, and solved on average 24% faster. FE models of the forefoot based on simplified geometric representations of the metatarsal bones and soft tissue surface geometry from 3D surface scans may potentially provide a simulation approach with improved clinical utility, however further validity testing around a range of therapeutic footwear types is required. PMID:26708965
NASA Astrophysics Data System (ADS)
Guerlet, Sandrine; Spiga, A.; Sylvestre, M.; Fouchet, T.; Millour, E.; Wordsworth, R.; Leconte, J.; Forget, F.
2013-10-01
Recent observations of Saturn’s stratospheric thermal structure and composition revealed new phenomena: an equatorial oscillation in temperature, reminiscent of the Earth's Quasi-Biennal Oscillation ; strong meridional contrasts of hydrocarbons ; a warm “beacon” associated with the powerful 2010 storm. Those signatures cannot be reproduced by 1D photochemical and radiative models and suggest that atmospheric dynamics plays a key role. This motivated us to develop a complete 3D General Circulation Model (GCM) for Saturn, based on the LMDz hydrodynamical core, to explore the circulation, seasonal variability, and wave activity in Saturn's atmosphere. In order to closely reproduce Saturn's radiative forcing, a particular emphasis was put in obtaining fast and accurate radiative transfer calculations. Our radiative model uses correlated-k distributions and spectral discretization tailored for Saturn's atmosphere. We include internal heat flux, ring shadowing and aerosols. We will report on the sensitivity of the model to spectral discretization, spectroscopic databases, and aerosol scenarios (varying particle sizes, opacities and vertical structures). We will also discuss the radiative effect of the ring shadowing on Saturn's atmosphere. We will present a comparison of temperature fields obtained with this new radiative equilibrium model to that inferred from Cassini/CIRS observations. In the troposphere, our model reproduces the observed temperature knee caused by heating at the top of the tropospheric aerosol layer. In the lower stratosphere (20mbar
modeled temperature is 5-10K too low compared to measurements. This suggests that processes other than radiative heating/cooling by trace
NASA Astrophysics Data System (ADS)
Wosnik, M.; Bachant, P.
2014-12-01
Cross-flow turbines, often referred to as vertical-axis turbines, show potential for success in marine hydrokinetic (MHK) and wind energy applications, ranging from small- to utility-scale installations in tidal/ocean currents and offshore wind. As turbine designs mature, the research focus is shifting from individual devices to the optimization of turbine arrays. It would be expensive and time-consuming to conduct physical model studies of large arrays at large model scales (to achieve sufficiently high Reynolds numbers), and hence numerical techniques are generally better suited to explore the array design parameter space. However, since the computing power available today is not sufficient to conduct simulations of the flow in and around large arrays of turbines with fully resolved turbine geometries (e.g., grid resolution into the viscous sublayer on turbine blades), the turbines' interaction with the energy resource (water current or wind) needs to be parameterized, or modeled. Models used today--a common model is the actuator disk concept--are not able to predict the unique wake structure generated by cross-flow turbines. This wake structure has been shown to create "constructive" interference in some cases, improving turbine performance in array configurations, in contrast with axial-flow, or horizontal axis devices. Towards a more accurate parameterization of cross-flow turbines, an extensive experimental study was carried out using a high-resolution turbine test bed with wake measurement capability in a large cross-section tow tank. The experimental results were then "interpolated" using high-fidelity Navier--Stokes simulations, to gain insight into the turbine's near-wake. The study was designed to achieve sufficiently high Reynolds numbers for the results to be Reynolds number independent with respect to turbine performance and wake statistics, such that they can be reliably extrapolated to full scale and used for model validation. The end product of
Selecting model complexity in learning problems
Buescher, K.L.; Kumar, P.R.
1993-10-01
To learn (or generalize) from noisy data, one must resist the temptation to pick a model for the underlying process that overfits the data. Many existing techniques solve this problem at the expense of requiring the evaluation of an absolute, a priori measure of each model`s complexity. We present a method that does not. Instead, it uses a natural, relative measure of each model`s complexity. This method first creates a pool of ``simple`` candidate models using part of the data and then selects from among these by using the rest of the data.
Accurate modeling of cache replacement policies in a Data-Grid.
Otoo, Ekow J.; Shoshani, Arie
2003-01-23
Caching techniques have been used to improve the performance gap of storage hierarchies in computing systems. In data intensive applications that access large data files over wide area network environment, such as a data grid,caching mechanism can significantly improve the data access performance under appropriate workloads. In a data grid, it is envisioned that local disk storage resources retain or cache the data files being used by local application. Under a workload of shared access and high locality of reference, the performance of the caching techniques depends heavily on the replacement policies being used. A replacement policy effectively determines which set of objects must be evicted when space is needed. Unlike cache replacement policies in virtual memory paging or database buffering, developing an optimal replacement policy for data grids is complicated by the fact that the file objects being cached have varying sizes and varying transfer and processing costs that vary with time. We present an accurate model for evaluating various replacement policies and propose a new replacement algorithm referred to as ''Least Cost Beneficial based on K backward references (LCB-K).'' Using this modeling technique, we compare LCB-K with various replacement policies such as Least Frequently Used (LFU), Least Recently Used (LRU), Greedy DualSize (GDS), etc., using synthetic and actual workload of accesses to and from tertiary storage systems. The results obtained show that (LCB-K) and (GDS) are the most cost effective cache replacement policies for storage resource management in data grids.
NASA Astrophysics Data System (ADS)
Walter, Johannes; Thajudeen, Thaseem; Süß, Sebastian; Segets, Doris; Peukert, Wolfgang
2015-04-01
Analytical centrifugation (AC) is a powerful technique for the characterisation of nanoparticles in colloidal systems. As a direct and absolute technique it requires no calibration or measurements of standards. Moreover, it offers simple experimental design and handling, high sample throughput as well as moderate investment costs. However, the full potential of AC for nanoparticle size analysis requires the development of powerful data analysis techniques. In this study we show how the application of direct boundary models to AC data opens up new possibilities in particle characterisation. An accurate analysis method, successfully applied to sedimentation data obtained by analytical ultracentrifugation (AUC) in the past, was used for the first time in analysing AC data. Unlike traditional data evaluation routines for AC using a designated number of radial positions or scans, direct boundary models consider the complete sedimentation boundary, which results in significantly better statistics. We demonstrate that meniscus fitting, as well as the correction of radius and time invariant noise significantly improves the signal-to-noise ratio and prevents the occurrence of false positives due to optical artefacts. Moreover, hydrodynamic non-ideality can be assessed by the residuals obtained from the analysis. The sedimentation coefficient distributions obtained by AC are in excellent agreement with the results from AUC. Brownian dynamics simulations were used to generate numerical sedimentation data to study the influence of diffusion on the obtained distributions. Our approach is further validated using polystyrene and silica nanoparticles. In particular, we demonstrate the strength of AC for analysing multimodal distributions by means of gold nanoparticles.
ACCURATE UNIVERSAL MODELS FOR THE MASS ACCRETION HISTORIES AND CONCENTRATIONS OF DARK MATTER HALOS
Zhao, D. H.; Jing, Y. P.; Mo, H. J.; Boerner, G.
2009-12-10
A large amount of observations have constrained cosmological parameters and the initial density fluctuation spectrum to a very high accuracy. However, cosmological parameters change with time and the power index of the power spectrum dramatically varies with mass scale in the so-called concordance LAMBDACDM cosmology. Thus, any successful model for its structural evolution should work well simultaneously for various cosmological models and different power spectra. We use a large set of high-resolution N-body simulations of a variety of structure formation models (scale-free, standard CDM, open CDM, and LAMBDACDM) to study the mass accretion histories, the mass and redshift dependence of concentrations, and the concentration evolution histories of dark matter halos. We find that there is significant disagreement between the much-used empirical models in the literature and our simulations. Based on our simulation results, we find that the mass accretion rate of a halo is tightly correlated with a simple function of its mass, the redshift, parameters of the cosmology, and of the initial density fluctuation spectrum, which correctly disentangles the effects of all these factors and halo environments. We also find that the concentration of a halo is strongly correlated with the universe age when its progenitor on the mass accretion history first reaches 4% of its current mass. According to these correlations, we develop new empirical models for both the mass accretion histories and the concentration evolution histories of dark matter halos, and the latter can also be used to predict the mass and redshift dependence of halo concentrations. These models are accurate and universal: the same set of model parameters works well for different cosmological models and for halos of different masses at different redshifts, and in the LAMBDACDM case the model predictions match the simulation results very well even though halo mass is traced to about 0.0005 times the final mass
An Accurate In Vitro Model of the E. coli Envelope
Clifton, Luke A.; Holt, Stephen A.; Hughes, Arwel V.; Daulton, Emma L.; Arunmanee, Wanatchaporn; Heinrich, Frank; Khalid, Syma; Jefferies, Damien; Charlton, Timothy R.; Webster, John R. P.; Kinane, Christian J.
2015-01-01
Abstract Gram‐negative bacteria are an increasingly serious source of antibiotic‐resistant infections, partly owing to their characteristic protective envelope. This complex, 20 nm thick barrier includes a highly impermeable, asymmetric bilayer outer membrane (OM), which plays a pivotal role in resisting antibacterial chemotherapy. Nevertheless, the OM molecular structure and its dynamics are poorly understood because the structure is difficult to recreate or study in vitro. The successful formation and characterization of a fully asymmetric model envelope using Langmuir–Blodgett and Langmuir–Schaefer methods is now reported. Neutron reflectivity and isotopic labeling confirmed the expected structure and asymmetry and showed that experiments with antibacterial proteins reproduced published in vivo behavior. By closely recreating natural OM behavior, this model provides a much needed robust system for antibiotic development. PMID:27346898
An accurate in vitro model of the E. coli envelope.
Clifton, Luke A; Holt, Stephen A; Hughes, Arwel V; Daulton, Emma L; Arunmanee, Wanatchaporn; Heinrich, Frank; Khalid, Syma; Jefferies, Damien; Charlton, Timothy R; Webster, John R P; Kinane, Christian J; Lakey, Jeremy H
2015-10-01
Gram-negative bacteria are an increasingly serious source of antibiotic-resistant infections, partly owing to their characteristic protective envelope. This complex, 20 nm thick barrier includes a highly impermeable, asymmetric bilayer outer membrane (OM), which plays a pivotal role in resisting antibacterial chemotherapy. Nevertheless, the OM molecular structure and its dynamics are poorly understood because the structure is difficult to recreate or study in vitro. The successful formation and characterization of a fully asymmetric model envelope using Langmuir-Blodgett and Langmuir-Schaefer methods is now reported. Neutron reflectivity and isotopic labeling confirmed the expected structure and asymmetry and showed that experiments with antibacterial proteins reproduced published in vivo behavior. By closely recreating natural OM behavior, this model provides a much needed robust system for antibiotic development. PMID:26331292
Sandala, Gregory M.; Hopmann, Kathrin H.; Ghosh, Abhik
2011-01-01
Six popular density functionals in conjunction with the conductor-like screening (COSMO) solvation model have been used to obtain linear Mössbauer isomer shift (IS) and quadrupole splitting (QS) parameters for a test set of 20 complexes (with 24 sites) comprised of nonheme nitrosyls (Fe–NO) and non-nitrosyl (Fe–S) complexes. For the first time in an IS analysis, the Fe electron density was calculated both directly at the nucleus, ρ(0)N, which is the typical procedure, and on a small sphere surrounding the nucleus, ρ(0)S, which is the new standard algorithm implemented in the ADF software package. We find that both methods yield (near) identical slopes from each linear regression analysis but are shifted with respect to ρ(0) along the x-axis. Therefore, the calculation of the Fe electron density with either method gives calibration fits with equal predictive value. Calibration parameters obtained from the complete test set for OLYP, OPBE, PW91, and BP86 yield correlation coefficients (r2) of approximately 0.90, indicating that the calibration fit is of good quality. However, fits obtained from B3LYP and B3LYP* with both Slater-type and Gaussian-type orbitals are generally found to be of poorer quality. For several of the complexes examined in this study, we find that B3LYP and B3LYP* give geometries that possess significantly larger deviations from the experimental structures than OLYP, OPBE, PW91 or BP86. This phenomenon is particularly true for the di- and tetranuclear Fe complexes examined in this study. Previous Mössbauer calibration fit studies using these functionals have usually included mononuclear Fe complexes alone, where these discrepancies are less pronounced. An examination of spin expectation values reveals B3LYP and B3LYP* approach the weak-coupling limit more closely than the GGA exchange-correlation functionals. The high degree of variability in our calculated S2 values for the Fe–NO complexes highlights their challenging electronic
Hu, Y.X.; Stamnes, K. )
1993-04-01
A new parameterization of the radiative Properties of water clouds is presented. Cloud optical properties for valent radius throughout the solar and both solar and terrestrial spectra and for cloud equivalent radii in the range 2.5-60 [mu]m are calculated from Mie theory. It is found that cloud optical properties depend mainly on equivalent radius throughout the solar and terrestrial spectrum and are insensitive to the details of the droplet size distribution, such as shape, skewness, width, and modality (single or bimodal). This suggests that in cloud models, aimed at predicting the evolution of cloud microphysics with climate change, it is sufficient to determine the third and the second moments of the size distribution (the ratio of which determines the equivalent radius). It also implies that measurements of the cloud liquid water content and the extinction coefficient are sufficient to determine cloud optical properties experimentally (i.e., measuring the complete droplet size distribution is not required). Based on the detailed calculations, the optical properties are parameterized as a function of cloud liquid water path and equivalent cloud droplet radius by using a nonlinear least-square fitting. The parameterization is performed separately for the range of radii 2.5-12 [mu]m, 12-30,[mu]m, and 30-60 [mu]m. Cloud heating and cooling rates are computed from this parameterization by using a comprehensive radiation model. Comparison with similar results obtained from exact Mie scattering calculations shows that this parameterization yields very accurate results and that it is several thousand times faster. This parameterization separates the dependence of cloud optical properties on droplet size and liquid water content, and is suitable for inclusion into climate models. 22 refs., 7 figs., 6 tabs.
Scaffolding in Complex Modelling Situations
ERIC Educational Resources Information Center
Stender, Peter; Kaiser, Gabriele
2015-01-01
The implementation of teacher-independent realistic modelling processes is an ambitious educational activity with many unsolved problems so far. Amongst others, there hardly exists any empirical knowledge about efficient ways of possible teacher support with students' activities, which should be mainly independent from the teacher. The research…
Modeling of Non-Gravitational Forces for Precise and Accurate Orbit Determination
NASA Astrophysics Data System (ADS)
Hackel, Stefan; Gisinger, Christoph; Steigenberger, Peter; Balss, Ulrich; Montenbruck, Oliver; Eineder, Michael
2014-05-01
Remote sensing satellites support a broad range of scientific and commercial applications. The two radar imaging satellites TerraSAR-X and TanDEM-X provide spaceborne Synthetic Aperture Radar (SAR) and interferometric SAR data with a very high accuracy. The precise reconstruction of the satellite's trajectory is based on the Global Positioning System (GPS) measurements from a geodetic-grade dual-frequency Integrated Geodetic and Occultation Receiver (IGOR) onboard the spacecraft. The increasing demand for precise radar products relies on validation methods, which require precise and accurate orbit products. An analysis of the orbit quality by means of internal and external validation methods on long and short timescales shows systematics, which reflect deficits in the employed force models. Following the proper analysis of this deficits, possible solution strategies are highlighted in the presentation. The employed Reduced Dynamic Orbit Determination (RDOD) approach utilizes models for gravitational and non-gravitational forces. A detailed satellite macro model is introduced to describe the geometry and the optical surface properties of the satellite. Two major non-gravitational forces are the direct and the indirect Solar Radiation Pressure (SRP). The satellite TerraSAR-X flies on a dusk-dawn orbit with an altitude of approximately 510 km above ground. Due to this constellation, the Sun almost constantly illuminates the satellite, which causes strong across-track accelerations on the plane rectangular to the solar rays. The indirect effect of the solar radiation is called Earth Radiation Pressure (ERP). This force depends on the sunlight, which is reflected by the illuminated Earth surface (visible spectra) and the emission of the Earth body in the infrared spectra. Both components of ERP require Earth models to describe the optical properties of the Earth surface. Therefore, the influence of different Earth models on the orbit quality is assessed. The scope of
NASA Astrophysics Data System (ADS)
Reppert, Mike; Naibo, Virginia; Jankowiak, Ryszard
2010-07-01
Accurate lineshape functions for modeling fluorescence line narrowing (FLN) difference spectra (ΔFLN spectra) in the low-fluence limit are derived and examined in terms of the physical interpretation of various contributions, including photoproduct absorption and emission. While in agreement with the earlier results of Jaaniso [Proc. Est. Acad. Sci., Phys., Math. 34, 277 (1985)] and Fünfschilling et al. [J. Lumin. 36, 85 (1986)], the derived formulas differ substantially from functions used recently [e.g., M. Rätsep et al., Chem. Phys. Lett. 479, 140 (2009)] to model ΔFLN spectra. In contrast to traditional FLN spectra, it is demonstrated that for most physically reasonable parameters, the ΔFLN spectrum reduces simply to the single-site fluorescence lineshape function. These results imply that direct measurement of a bulk-averaged single-site fluorescence lineshape function can be accomplished with no complicated extraction process or knowledge of any additional parameters such as site distribution function shape and width. We argue that previous analysis of ΔFLN spectra obtained for many photosynthetic complexes led to strong artificial lowering of apparent electron-phonon coupling strength, especially on the high-energy side of the pigment site distribution function.
Role models for complex networks
NASA Astrophysics Data System (ADS)
Reichardt, J.; White, D. R.
2007-11-01
We present a framework for automatically decomposing (“block-modeling”) the functional classes of agents within a complex network. These classes are represented by the nodes of an image graph (“block model”) depicting the main patterns of connectivity and thus functional roles in the network. Using a first principles approach, we derive a measure for the fit of a network to any given image graph allowing objective hypothesis testing. From the properties of an optimal fit, we derive how to find the best fitting image graph directly from the network and present a criterion to avoid overfitting. The method can handle both two-mode and one-mode data, directed and undirected as well as weighted networks and allows for different types of links to be dealt with simultaneously. It is non-parametric and computationally efficient. The concepts of structural equivalence and modularity are found as special cases of our approach. We apply our method to the world trade network and analyze the roles individual countries play in the global economy.
Modeling of protein binary complexes using structural mass spectrometry data
Kamal, J.K. Amisha; Chance, Mark R.
2008-01-01
In this article, we describe a general approach to modeling the structure of binary protein complexes using structural mass spectrometry data combined with molecular docking. In the first step, hydroxyl radical mediated oxidative protein footprinting is used to identify residues that experience conformational reorganization due to binding or participate in the binding interface. In the second step, a three-dimensional atomic structure of the complex is derived by computational modeling. Homology modeling approaches are used to define the structures of the individual proteins if footprinting detects significant conformational reorganization as a function of complex formation. A three-dimensional model of the complex is constructed from these binary partners using the ClusPro program, which is composed of docking, energy filtering, and clustering steps. Footprinting data are used to incorporate constraints—positive and/or negative—in the docking step and are also used to decide the type of energy filter—electrostatics or desolvation—in the successive energy-filtering step. By using this approach, we examine the structure of a number of binary complexes of monomeric actin and compare the results to crystallographic data. Based on docking alone, a number of competing models with widely varying structures are observed, one of which is likely to agree with crystallographic data. When the docking steps are guided by footprinting data, accurate models emerge as top scoring. We demonstrate this method with the actin/gelsolin segment-1 complex. We also provide a structural model for the actin/cofilin complex using this approach which does not have a crystal or NMR structure. PMID:18042684
Agent-based modeling of complex infrastructures
North, M. J.
2001-06-01
Complex Adaptive Systems (CAS) can be applied to investigate complex infrastructures and infrastructure interdependencies. The CAS model agents within the Spot Market Agent Research Tool (SMART) and Flexible Agent Simulation Toolkit (FAST) allow investigation of the electric power infrastructure, the natural gas infrastructure and their interdependencies.
Abdelnour, Farras; Voss, Henning U.; Raj, Ashish
2014-01-01
The relationship between anatomic connectivity of large-scale brain networks and their functional connectivity is of immense importance and an area of active research. Previous attempts have required complex simulations which model the dynamics of each cortical region, and explore the coupling between regions as derived by anatomic connections. While much insight is gained from these non-linear simulations, they can be computationally taxing tools for predicting functional from anatomic connectivities. Little attention has been paid to linear models. Here we show that a properly designed linear model appears to be superior to previous non-linear approaches in capturing the brain’s long-range second order correlation structure that governs the relationship between anatomic and functional connectivities. We derive a linear network of brain dynamics based on graph diffusion, whereby the diffusing quantity undergoes a random walk on a graph. We test our model using subjects who underwent diffusion MRI and resting state fMRI. The network diffusion model applied to the structural networks largely predicts the correlation structures derived from their fMRI data, to a greater extent than other approaches. The utility of the proposed approach is that it can routinely be used to infer functional correlation from anatomic connectivity. And since it is linear, anatomic connectivity can also be inferred from functional data. The success of our model confirms the linearity of ensemble average signals in the brain, and implies that their long-range correlation structure may percolate within the brain via purely mechanistic processes enacted on its structural connectivity pathways. PMID:24384152
Numerical models of complex diapirs
NASA Astrophysics Data System (ADS)
Podladchikov, Yu.; Talbot, C.; Poliakov, A. N. B.
1993-12-01
Numerically modelled diapirs that rise into overburdens with viscous rheology produce a large variety of shapes. This work uses the finite-element method to study the development of diapirs that rise towards a surface on which a diapir-induced topography creeps flat or disperses ("erodes") at different rates. Slow erosion leads to diapirs with "mushroom" shapes, moderate erosion rate to "wine glass" diapirs and fast erosion to "beer glass"- and "column"-shaped diapirs. The introduction of a low-viscosity layer at the top of the overburden causes diapirs to develop into structures resembling a "Napoleon hat". These spread lateral sheets.
Walter, Johannes; Thajudeen, Thaseem; Süss, Sebastian; Segets, Doris; Peukert, Wolfgang
2015-04-21
Analytical centrifugation (AC) is a powerful technique for the characterisation of nanoparticles in colloidal systems. As a direct and absolute technique it requires no calibration or measurements of standards. Moreover, it offers simple experimental design and handling, high sample throughput as well as moderate investment costs. However, the full potential of AC for nanoparticle size analysis requires the development of powerful data analysis techniques. In this study we show how the application of direct boundary models to AC data opens up new possibilities in particle characterisation. An accurate analysis method, successfully applied to sedimentation data obtained by analytical ultracentrifugation (AUC) in the past, was used for the first time in analysing AC data. Unlike traditional data evaluation routines for AC using a designated number of radial positions or scans, direct boundary models consider the complete sedimentation boundary, which results in significantly better statistics. We demonstrate that meniscus fitting, as well as the correction of radius and time invariant noise significantly improves the signal-to-noise ratio and prevents the occurrence of false positives due to optical artefacts. Moreover, hydrodynamic non-ideality can be assessed by the residuals obtained from the analysis. The sedimentation coefficient distributions obtained by AC are in excellent agreement with the results from AUC. Brownian dynamics simulations were used to generate numerical sedimentation data to study the influence of diffusion on the obtained distributions. Our approach is further validated using polystyrene and silica nanoparticles. In particular, we demonstrate the strength of AC for analysing multimodal distributions by means of gold nanoparticles. PMID:25789666
NASA Astrophysics Data System (ADS)
Lachaume, Regis; Rabus, Markus; Jordan, Andres
2015-08-01
In stellar interferometry, the assumption that the observables can be seen as Gaussian, independent variables is the norm. In particular, neither the optical interferometry FITS (OIFITS) format nor the most popular fitting software in the field, LITpro, offer means to specify a covariance matrix or non-Gaussian uncertainties. Interferometric observables are correlated by construct, though. Also, the calibration by an instrumental transfer function ensures that the resulting observables are not Gaussian, even if uncalibrated ones happened to be so.While analytic frameworks have been published in the past, they are cumbersome and there is no generic implementation available. We propose here a relatively simple way of dealing with correlated errors without the need to extend the OIFITS specification or making some Gaussian assumptions. By repeatedly picking at random which interferograms, which calibrator stars, and which are the errors on their diameters, and performing the data processing on the bootstrapped data, we derive a sampling of p(O), the multivariate probability density function (PDF) of the observables O. The results can be stored in a normal OIFITS file. Then, given a model m with parameters P predicting observables O = m(P), we can estimate the PDF of the model parameters f(P) = p(m(P)) by using a density estimation of the observables' PDF p.With observations repeated over different baselines, on nights several days apart, and with a significant set of calibrators systematic errors are de facto taken into account. We apply the technique to a precise and accurate assessment of stellar diameters obtained at the Very Large Telescope Interferometer with PIONIER.
Stable, accurate and efficient computation of normal modes for horizontal stratified models
NASA Astrophysics Data System (ADS)
Wu, Bo; Chen, Xiaofei
2016-08-01
We propose an adaptive root-determining strategy that is very useful when dealing with trapped modes or Stoneley modes whose energies become very insignificant on the free surface in the presence of low-velocity layers or fluid layers in the model. Loss of modes in these cases or inaccuracy in the calculation of these modes may then be easily avoided. Built upon the generalized reflection/transmission coefficients, the concept of `family of secular functions' that we herein call `adaptive mode observers' is thus naturally introduced to implement this strategy, the underlying idea of which has been distinctly noted for the first time and may be generalized to other applications such as free oscillations or applied to other methods in use when these cases are encountered. Additionally, we have made further improvements upon the generalized reflection/transmission coefficient method; mode observers associated with only the free surface and low-velocity layers (and the fluid/solid interface if the model contains fluid layers) are adequate to guarantee no loss and high precision at the same time of any physically existent modes without excessive calculations. Finally, the conventional definition of the fundamental mode is reconsidered, which is entailed in the cases under study. Some computational aspects are remarked on. With the additional help afforded by our superior root-searching scheme and the possibility of speeding calculation using a less number of layers aided by the concept of `turning point', our algorithm is remarkably efficient as well as stable and accurate and can be used as a powerful tool for widely related applications.
Stable, accurate and efficient computation of normal modes for horizontal stratified models
NASA Astrophysics Data System (ADS)
Wu, Bo; Chen, Xiaofei
2016-06-01
We propose an adaptive root-determining strategy that is very useful when dealing with trapped modes or Stoneley modes whose energies become very insignificant on the free surface in the presence of low-velocity layers or fluid layers in the model. Loss of modes in these cases or inaccuracy in the calculation of these modes may then be easily avoided. Built upon the generalized reflection/transmission coefficients, the concept of "family of secular functions" that we herein call "adaptive mode observers", is thus naturally introduced to implement this strategy, the underlying idea of which has been distinctly noted for the first time and may be generalized to other applications such as free oscillations or applied to other methods in use when these cases are encountered. Additionally, we have made further improvements upon the generalized reflection/transmission coefficient method; mode observers associated with only the free surface and low-velocity layers (and the fluid/solid interface if the model contains fluid layers) are adequate to guarantee no loss and high precision at the same time of any physically existent modes without excessive calculations. Finally, the conventional definition of the fundamental mode is reconsidered, which is entailed in the cases under study. Some computational aspects are remarked on. With the additional help afforded by our superior root-searching scheme and the possibility of speeding calculation using a less number of layers aided by the concept of "turning point", our algorithm is remarkably efficient as well as stable and accurate and can be used as a powerful tool for widely related applications.
Accurate calculation and modeling of the adiabatic connection in density functional theory
NASA Astrophysics Data System (ADS)
Teale, A. M.; Coriani, S.; Helgaker, T.
2010-04-01
AC. When parametrized in terms of the same input data, the AC-CI model offers improved performance over the corresponding AC-D model, which is shown to be the lowest-order contribution to the AC-CI model. The utility of the accurately calculated AC curves for the analysis of standard density functionals is demonstrated for the BLYP exchange-correlation functional and the interaction-strength-interpolation (ISI) model AC integrand. From the results of this analysis, we investigate the performance of our proposed two-parameter AC-D and AC-CI models when a simple density functional for the AC at infinite interaction strength is employed in place of information at the fully interacting point. The resulting two-parameter correlation functionals offer a qualitatively correct behavior of the AC integrand with much improved accuracy over previous attempts. The AC integrands in the present work are recommended as a basis for further work, generating functionals that avoid spurious error cancellations between exchange and correlation energies and give good accuracy for the range of densities and types of correlation contained in the systems studied here.
Towards more accurate wind and solar power prediction by improving NWP model physics
NASA Astrophysics Data System (ADS)
Steiner, Andrea; Köhler, Carmen; von Schumann, Jonas; Ritter, Bodo
2014-05-01
nighttime to well mixed conditions during the day presents a big challenge to NWP models. Fast decrease and successive increase in hub-height wind speed after sunrise, and the formation of nocturnal low level jets will be discussed. For PV, the life cycle of low stratus clouds and fog is crucial. Capturing these processes correctly depends on the accurate simulation of diffusion or vertical momentum transport and the interaction with other atmospheric and soil processes within the numerical weather model. Results from Single Column Model simulations and 3d case studies will be presented. Emphasis is placed on wind forecasts; however, some references to highlights concerning the PV-developments will also be given. *) ORKA: Optimierung von Ensembleprognosen regenerativer Einspeisung für den Kürzestfristbereich am Anwendungsbeispiel der Netzsicherheitsrechnungen **) EWeLiNE: Erstellung innovativer Wetter- und Leistungsprognosemodelle für die Netzintegration wetterabhängiger Energieträger, www.projekt-eweline.de
Mathematical model accurately predicts protein release from an affinity-based delivery system.
Vulic, Katarina; Pakulska, Malgosia M; Sonthalia, Rohit; Ramachandran, Arun; Shoichet, Molly S
2015-01-10
Affinity-based controlled release modulates the delivery of protein or small molecule therapeutics through transient dissociation/association. To understand which parameters can be used to tune release, we used a mathematical model based on simple binding kinetics. A comprehensive asymptotic analysis revealed three characteristic regimes for therapeutic release from affinity-based systems. These regimes can be controlled by diffusion or unbinding kinetics, and can exhibit release over either a single stage or two stages. This analysis fundamentally changes the way we think of controlling release from affinity-based systems and thereby explains some of the discrepancies in the literature on which parameters influence affinity-based release. The rate of protein release from affinity-based systems is determined by the balance of diffusion of the therapeutic agent through the hydrogel and the dissociation kinetics of the affinity pair. Equations for tuning protein release rate by altering the strength (KD) of the affinity interaction, the concentration of binding ligand in the system, the rate of dissociation (koff) of the complex, and the hydrogel size and geometry, are provided. We validated our model by collapsing the model simulations and the experimental data from a recently described affinity release system, to a single master curve. Importantly, this mathematical analysis can be applied to any single species affinity-based system to determine the parameters required for a desired release profile. PMID:25449806
Długosz, Maciej; Antosiewicz, Jan M
2015-07-01
Proper treatment of hydrodynamic interactions is of importance in evaluation of rigid-body mobility tensors of biomolecules in Stokes flow and in simulations of their folding and solution conformation, as well as in simulations of the translational and rotational dynamics of either flexible or rigid molecules in biological systems at low Reynolds numbers. With macromolecules conveniently modeled in calculations or in dynamic simulations as ensembles of spherical frictional elements, various approximations to hydrodynamic interactions, such as the two-body, far-field Rotne-Prager approach, are commonly used, either without concern or as a compromise between the accuracy and the numerical complexity. Strikingly, even though the analytical Rotne-Prager approach fails to describe (both in the qualitative and quantitative sense) mobilities in the simplest system consisting of two spheres, when the distance between their surfaces is of the order of their size, it is commonly applied to model hydrodynamic effects in macromolecular systems. Here, we closely investigate hydrodynamic effects in two and three-body systems, consisting of bead-shell molecular models, using either the analytical Rotne-Prager approach, or an accurate numerical scheme that correctly accounts for the many-body character of hydrodynamic interactions and their short-range behavior. We analyze mobilities, and translational and rotational velocities of bodies resulting from direct forces acting on them. We show, that with the sufficient number of frictional elements in hydrodynamic models of interacting bodies, the far-field approximation is able to provide a description of hydrodynamic effects that is in a reasonable qualitative as well as quantitative agreement with the description resulting from the application of the virtually exact numerical scheme, even for small separations between bodies. PMID:26068580
Toward accurate tooth segmentation from computed tomography images using a hybrid level set model
Gan, Yangzhou; Zhao, Qunfei; Xia, Zeyang E-mail: jing.xiong@siat.ac.cn; Hu, Ying; Xiong, Jing E-mail: jing.xiong@siat.ac.cn; Zhang, Jianwei
2015-01-15
Purpose: A three-dimensional (3D) model of the teeth provides important information for orthodontic diagnosis and treatment planning. Tooth segmentation is an essential step in generating the 3D digital model from computed tomography (CT) images. The aim of this study is to develop an accurate and efficient tooth segmentation method from CT images. Methods: The 3D dental CT volumetric images are segmented slice by slice in a two-dimensional (2D) transverse plane. The 2D segmentation is composed of a manual initialization step and an automatic slice by slice segmentation step. In the manual initialization step, the user manually picks a starting slice and selects a seed point for each tooth in this slice. In the automatic slice segmentation step, a developed hybrid level set model is applied to segment tooth contours from each slice. Tooth contour propagation strategy is employed to initialize the level set function automatically. Cone beam CT (CBCT) images of two subjects were used to tune the parameters. Images of 16 additional subjects were used to validate the performance of the method. Volume overlap metrics and surface distance metrics were adopted to assess the segmentation accuracy quantitatively. The volume overlap metrics were volume difference (VD, mm{sup 3}) and Dice similarity coefficient (DSC, %). The surface distance metrics were average symmetric surface distance (ASSD, mm), RMS (root mean square) symmetric surface distance (RMSSSD, mm), and maximum symmetric surface distance (MSSD, mm). Computation time was recorded to assess the efficiency. The performance of the proposed method has been compared with two state-of-the-art methods. Results: For the tested CBCT images, the VD, DSC, ASSD, RMSSSD, and MSSD for the incisor were 38.16 ± 12.94 mm{sup 3}, 88.82 ± 2.14%, 0.29 ± 0.03 mm, 0.32 ± 0.08 mm, and 1.25 ± 0.58 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the canine were 49.12 ± 9.33 mm{sup 3}, 91.57 ± 0.82%, 0.27 ± 0.02 mm, 0
NASA Astrophysics Data System (ADS)
Chien Chang, Jia-Ren; Tai, Cheng-Chi
2006-07-01
This article reports on the design and development of a complete, programmable electrocardiogram (ECG) generator, which can be used for the testing, calibration and maintenance of electrocardiograph equipment. A modified mathematical model, developed from the three coupled ordinary differential equations of McSharry et al. [IEEE Trans. Biomed. Eng. 50, 289, (2003)], was used to locate precisely the positions of the onset, termination, angle, and duration of individual components in an ECG. Generator facilities are provided so the user can adjust the signal amplitude, heart rate, QRS-complex slopes, and P- and T-wave settings. The heart rate can be adjusted in increments of 1BPM (beats per minute), from 20to176BPM, while the amplitude of the ECG signal can be set from 0.1to400mV with a 0.1mV resolution. Experimental results show that the proposed concept and the resulting system are feasible.
TRIM—3D: a three-dimensional model for accurate simulation of shallow water flow
Casulli, Vincenzo; Bertolazzi, Enrico; Cheng, Ralph T.
1993-01-01
A semi-implicit finite difference formulation for the numerical solution of three-dimensional tidal circulation is discussed. The governing equations are the three-dimensional Reynolds equations in which the pressure is assumed to be hydrostatic. A minimal degree of implicitness has been introduced in the finite difference formula so that the resulting algorithm permits the use of large time steps at a minimal computational cost. This formulation includes the simulation of flooding and drying of tidal flats, and is fully vectorizable for an efficient implementation on modern vector computers. The high computational efficiency of this method has made it possible to provide the fine details of circulation structure in complex regions that previous studies were unable to obtain. For proper interpretation of the model results suitable interactive graphics is also an essential tool.
Towards accurate kinetic modeling of prompt NO formation in hydrocarbon flames via the NCN pathway
Sutton, Jeffrey A.; Fleming, James W.
2008-08-15
A basic kinetic mechanism that can predict the appropriate prompt-NO precursor NCN, as shown by experiment, with relative accuracy while still producing postflame NO results that can be calculated as accurately as or more accurately than through the former HCN pathway is presented for the first time. The basic NCN submechanism should be a starting point for future NCN kinetic and prompt NO formation refinement.
Complex system modelling for veterinary epidemiology.
Lanzas, Cristina; Chen, Shi
2015-02-01
The use of mathematical models has a long tradition in infectious disease epidemiology. The nonlinear dynamics and complexity of pathogen transmission pose challenges in understanding its key determinants, in identifying critical points, and designing effective mitigation strategies. Mathematical modelling provides tools to explicitly represent the variability, interconnectedness, and complexity of systems, and has contributed to numerous insights and theoretical advances in disease transmission, as well as to changes in public policy, health practice, and management. In recent years, our modelling toolbox has considerably expanded due to the advancements in computing power and the need to model novel data generated by technologies such as proximity loggers and global positioning systems. In this review, we discuss the principles, advantages, and challenges associated with the most recent modelling approaches used in systems science, the interdisciplinary study of complex systems, including agent-based, network and compartmental modelling. Agent-based modelling is a powerful simulation technique that considers the individual behaviours of system components by defining a set of rules that govern how individuals ("agents") within given populations interact with one another and the environment. Agent-based models have become a recent popular choice in epidemiology to model hierarchical systems and address complex spatio-temporal dynamics because of their ability to integrate multiple scales and datasets. PMID:25449734
Building phenomenological models of complex biological processes
NASA Astrophysics Data System (ADS)
Daniels, Bryan; Nemenman, Ilya
2009-11-01
A central goal of any modeling effort is to make predictions regarding experimental conditions that have not yet been observed. Overly simple models will not be able to fit the original data well, but overly complex models are likely to overfit the data and thus produce bad predictions. Modern quantitative biology modeling efforts often err on the complexity side of this balance, using myriads of microscopic biochemical reaction processes with a priori unknown kinetic parameters to model relatively simple biological phenomena. In this work, we show how Bayesian model selection (which is mathematically similar to low temperature expansion in statistical physics) can be used to build coarse-grained, phenomenological models of complex dynamical biological processes, which have better predictive powers than microscopically correct, but poorely constrained mechanistic molecular models. We illustrate this on the example of a multiply-modifiable protein molecule, which is a simplified description of multiple biological systems, such as an immune receptors and an RNA polymerase complex. Our approach is similar in spirit to the phenomenological Landau expansion for the free energy in the theory of critical phenomena.
SUMMARY OF COMPLEX TERRAIN MODEL EVALUATION
The Environmental Protection Agency conducted a scientific review of a set of eight complex terrain dispersion models. TRC Environmental Consultants, Inc. calculated and tabulated a uniform set of performance statistics for the models using the Cinder Cone Butte and Westvaco Luke...
Explicit stress integration of complex soil models
NASA Astrophysics Data System (ADS)
Zhao, Jidong; Sheng, Daichao; Rouainia, M.; Sloan, Scott W.
2005-10-01
In this paper, two complex critical-state models are implemented in a displacement finite element code. The two models are used for structured clays and sands, and are characterized by multiple yield surfaces, plastic yielding within the yield surface, and complex kinematic and isotropic hardening laws. The consistent tangent operators - which lead to a quadratic convergence when used in a fully implicit algorithm - are difficult to derive or may even not exist. The stress integration scheme used in this paper is based on the explicit Euler method with automatic substepping and error control. This scheme employs the classical elastoplastic stiffness matrix and requires only the first derivatives of the yield function and plastic potential. This explicit scheme is used to integrate the two complex critical-state models - the sub/super-loading surfaces model (SSLSM) and the kinematic hardening structure model (KHSM). Various boundary-value problems are then analysed. The results for the two models are compared with each other, as well with those from standard Cam-clay models. Accuracy and efficiency of the scheme used for the complex models are also investigated. Copyright
From Complex to Simple: Interdisciplinary Stochastic Models
ERIC Educational Resources Information Center
Mazilu, D. A.; Zamora, G.; Mazilu, I.
2012-01-01
We present two simple, one-dimensional, stochastic models that lead to a qualitative understanding of very complex systems from biology, nanoscience and social sciences. The first model explains the complicated dynamics of microtubules, stochastic cellular highways. Using the theory of random walks in one dimension, we find analytical expressions…
Modeling the chemistry of complex petroleum mixtures.
Quann, R J
1998-01-01
Determining the complete molecular composition of petroleum and its refined products is not feasible with current analytical techniques because of the astronomical number of molecular components. Modeling the composition and behavior of such complex mixtures in refinery processes has accordingly evolved along a simplifying concept called lumping. Lumping reduces the complexity of the problem to a manageable form by grouping the entire set of molecular components into a handful of lumps. This traditional approach does not have a molecular basis and therefore excludes important aspects of process chemistry and molecular property fundamentals from the model's formulation. A new approach called structure-oriented lumping has been developed to model the composition and chemistry of complex mixtures at a molecular level. The central concept is to represent an individual molecular or a set of closely related isomers as a mathematical construct of certain specific and repeating structural groups. A complex mixture such as petroleum can then be represented as thousands of distinct molecular components, each having a mathematical identity. This enables the automated construction of large complex reaction networks with tens of thousands of specific reactions for simulating the chemistry of complex mixtures. Further, the method provides a convenient framework for incorporating molecular physical property correlations, existing group contribution methods, molecular thermodynamic properties, and the structure--activity relationships of chemical kinetics in the development of models. PMID:9860903
Boyce, Christopher M; Holland, Daniel J; Scott, Stuart A; Dennis, John S
2013-12-18
Discrete element modeling is being used increasingly to simulate flow in fluidized beds. These models require complex measurement techniques to provide validation for the approximations inherent in the model. This paper introduces the idea of modeling the experiment to ensure that the validation is accurate. Specifically, a 3D, cylindrical gas-fluidized bed was simulated using a discrete element model (DEM) for particle motion coupled with computational fluid dynamics (CFD) to describe the flow of gas. The results for time-averaged, axial velocity during bubbling fluidization were compared with those from magnetic resonance (MR) experiments made on the bed. The DEM-CFD data were postprocessed with various methods to produce time-averaged velocity maps for comparison with the MR results, including a method which closely matched the pulse sequence and data processing procedure used in the MR experiments. The DEM-CFD results processed with the MR-type time-averaging closely matched experimental MR results, validating the DEM-CFD model. Analysis of different averaging procedures confirmed that MR time-averages of dynamic systems correspond to particle-weighted averaging, rather than frame-weighted averaging, and also demonstrated that the use of Gaussian slices in MR imaging of dynamic systems is valid. PMID:24478537
2013-01-01
Discrete element modeling is being used increasingly to simulate flow in fluidized beds. These models require complex measurement techniques to provide validation for the approximations inherent in the model. This paper introduces the idea of modeling the experiment to ensure that the validation is accurate. Specifically, a 3D, cylindrical gas-fluidized bed was simulated using a discrete element model (DEM) for particle motion coupled with computational fluid dynamics (CFD) to describe the flow of gas. The results for time-averaged, axial velocity during bubbling fluidization were compared with those from magnetic resonance (MR) experiments made on the bed. The DEM-CFD data were postprocessed with various methods to produce time-averaged velocity maps for comparison with the MR results, including a method which closely matched the pulse sequence and data processing procedure used in the MR experiments. The DEM-CFD results processed with the MR-type time-averaging closely matched experimental MR results, validating the DEM-CFD model. Analysis of different averaging procedures confirmed that MR time-averages of dynamic systems correspond to particle-weighted averaging, rather than frame-weighted averaging, and also demonstrated that the use of Gaussian slices in MR imaging of dynamic systems is valid. PMID:24478537
Updating the debate on model complexity
Simmons, Craig T.; Hunt, Randall J.
2012-01-01
As scientists who are trying to understand a complex natural world that cannot be fully characterized in the field, how can we best inform the society in which we live? This founding context was addressed in a special session, “Complexity in Modeling: How Much is Too Much?” convened at the 2011 Geological Society of America Annual Meeting. The session had a variety of thought-provoking presentations—ranging from philosophy to cost-benefit analyses—and provided some areas of broad agreement that were not evident in discussions of the topic in 1998 (Hunt and Zheng, 1999). The session began with a short introduction during which model complexity was framed borrowing from an economic concept, the Law of Diminishing Returns, and an example of enjoyment derived by eating ice cream. Initially, there is increasing satisfaction gained from eating more ice cream, to a point where the gain in satisfaction starts to decrease, ending at a point when the eater sees no value in eating more ice cream. A traditional view of model complexity is similar—understanding gained from modeling can actually decrease if models become unnecessarily complex. However, oversimplified models—those that omit important aspects of the problem needed to make a good prediction—can also limit and confound our understanding. Thus, the goal of all modeling is to find the “sweet spot” of model sophistication—regardless of whether complexity was added sequentially to an overly simple model or collapsed from an initial highly parameterized framework that uses mathematics and statistics to attain an optimum (e.g., Hunt et al., 2007). Thus, holistic parsimony is attained, incorporating “as simple as possible,” as well as the equally important corollary “but no simpler.”
Balancing model complexity and measurements in hydrology
NASA Astrophysics Data System (ADS)
Van De Giesen, N.; Schoups, G.; Weijs, S. V.
2012-12-01
The Data Processing Inequality implies that hydrological modeling can only reduce, and never increase, the amount of information available in the original data used to formulate and calibrate hydrological models: I(X;Z(Y)) ≤ I(X;Y). Still, hydrologists around the world seem quite content building models for "their" watersheds to move our discipline forward. Hydrological models tend to have a hybrid character with respect to underlying physics. Most models make use of some well established physical principles, such as mass and energy balances. One could argue that such principles are based on many observations, and therefore add data. These physical principles, however, are applied to hydrological models that often contain concepts that have no direct counterpart in the observable physical universe, such as "buckets" or "reservoirs" that fill up and empty out over time. These not-so-physical concepts are more like the Artificial Neural Networks and Support Vector Machines of the Artificial Intelligence (AI) community. Within AI, one quickly came to the realization that by increasing model complexity, one could basically fit any dataset but that complexity should be controlled in order to be able to predict unseen events. The more data are available to train or calibrate the model, the more complex it can be. Many complexity control approaches exist in AI, with Solomonoff inductive inference being one of the first formal approaches, the Akaike Information Criterion the most popular, and Statistical Learning Theory arguably being the most comprehensive practical approach. In hydrology, complexity control has hardly been used so far. There are a number of reasons for that lack of interest, the more valid ones of which will be presented during the presentation. For starters, there are no readily available complexity measures for our models. Second, some unrealistic simplifications of the underlying complex physics tend to have a smoothing effect on possible model
Multifaceted Modelling of Complex Business Enterprises.
Chakraborty, Subrata; Mengersen, Kerrie; Fidge, Colin; Ma, Lin; Lassen, David
2015-01-01
We formalise and present a new generic multifaceted complex system approach for modelling complex business enterprises. Our method has a strong focus on integrating the various data types available in an enterprise which represent the diverse perspectives of various stakeholders. We explain the challenges faced and define a novel approach to converting diverse data types into usable Bayesian probability forms. The data types that can be integrated include historic data, survey data, and management planning data, expert knowledge and incomplete data. The structural complexities of the complex system modelling process, based on various decision contexts, are also explained along with a solution. This new application of complex system models as a management tool for decision making is demonstrated using a railway transport case study. The case study demonstrates how the new approach can be utilised to develop a customised decision support model for a specific enterprise. Various decision scenarios are also provided to illustrate the versatility of the decision model at different phases of enterprise operations such as planning and control. PMID:26247591
Multifaceted Modelling of Complex Business Enterprises
2015-01-01
We formalise and present a new generic multifaceted complex system approach for modelling complex business enterprises. Our method has a strong focus on integrating the various data types available in an enterprise which represent the diverse perspectives of various stakeholders. We explain the challenges faced and define a novel approach to converting diverse data types into usable Bayesian probability forms. The data types that can be integrated include historic data, survey data, and management planning data, expert knowledge and incomplete data. The structural complexities of the complex system modelling process, based on various decision contexts, are also explained along with a solution. This new application of complex system models as a management tool for decision making is demonstrated using a railway transport case study. The case study demonstrates how the new approach can be utilised to develop a customised decision support model for a specific enterprise. Various decision scenarios are also provided to illustrate the versatility of the decision model at different phases of enterprise operations such as planning and control. PMID:26247591
A new method based on the subpixel Gaussian model for accurate estimation of asteroid coordinates
NASA Astrophysics Data System (ADS)
Savanevych, V. E.; Briukhovetskyi, O. B.; Sokovikova, N. S.; Bezkrovny, M. M.; Vavilova, I. B.; Ivashchenko, Yu. M.; Elenin, L. V.; Khlamov, S. V.; Movsesian, Ia. S.; Dashkova, A. M.; Pogorelov, A. V.
2015-08-01
We describe a new iteration method to estimate asteroid coordinates, based on a subpixel Gaussian model of the discrete object image. The method operates by continuous parameters (asteroid coordinates) in a discrete observational space (the set of pixel potentials) of the CCD frame. In this model, the kind of coordinate distribution of the photons hitting a pixel of the CCD frame is known a priori, while the associated parameters are determined from a real digital object image. The method that is developed, which is flexible in adapting to any form of object image, has a high measurement accuracy along with a low calculating complexity, due to the maximum-likelihood procedure that is implemented to obtain the best fit instead of a least-squares method and Levenberg-Marquardt algorithm for minimization of the quadratic form. Since 2010, the method has been tested as the basis of our Collection Light Technology (COLITEC) software, which has been installed at several observatories across the world with the aim of the automatic discovery of asteroids and comets in sets of CCD frames. As a result, four comets (C/2010 X1 (Elenin), P/2011 NO1(Elenin), C/2012 S1 (ISON) and P/2013 V3 (Nevski)) as well as more than 1500 small Solar system bodies (including five near-Earth objects (NEOs), 21 Trojan asteroids of Jupiter and one Centaur object) have been discovered. We discuss these results, which allowed us to compare the accuracy parameters of the new method and confirm its efficiency. In 2014, the COLITEC software was recommended to all members of the Gaia-FUN-SSO network for analysing observations as a tool to detect faint moving objects in frames.
Accurate Estimation of Protein Folding and Unfolding Times: Beyond Markov State Models.
Suárez, Ernesto; Adelman, Joshua L; Zuckerman, Daniel M
2016-08-01
Because standard molecular dynamics (MD) simulations are unable to access time scales of interest in complex biomolecular systems, it is common to "stitch together" information from multiple shorter trajectories using approximate Markov state model (MSM) analysis. However, MSMs may require significant tuning and can yield biased results. Here, by analyzing some of the longest protein MD data sets available (>100 μs per protein), we show that estimators constructed based on exact non-Markovian (NM) principles can yield significantly improved mean first-passage times (MFPTs) for protein folding and unfolding. In some cases, MSM bias of more than an order of magnitude can be corrected when identical trajectory data are reanalyzed by non-Markovian approaches. The NM analysis includes "history" information, higher order time correlations compared to MSMs, that is available in every MD trajectory. The NM strategy is insensitive to fine details of the states used and works well when a fine time-discretization (i.e., small "lag time") is used. PMID:27340835
Slip complexity in earthquake fault models.
Rice, J R; Ben-Zion, Y
1996-01-01
We summarize studies of earthquake fault models that give rise to slip complexities like those in natural earthquakes. For models of smooth faults between elastically deformable continua, it is critical that the friction laws involve a characteristic distance for slip weakening or evolution of surface state. That results in a finite nucleation size, or coherent slip patch size, h*. Models of smooth faults, using numerical cell size properly small compared to h*, show periodic response or complex and apparently chaotic histories of large events but have not been found to show small event complexity like the self-similar (power law) Gutenberg-Richter frequency-size statistics. This conclusion is supported in the present paper by fully inertial elastodynamic modeling of earthquake sequences. In contrast, some models of locally heterogeneous faults with quasi-independent fault segments, represented approximately by simulations with cell size larger than h* so that the model becomes "inherently discrete," do show small event complexity of the Gutenberg-Richter type. Models based on classical friction laws without a weakening length scale or for which the numerical procedure imposes an abrupt strength drop at the onset of slip have h* = 0 and hence always fall into the inherently discrete class. We suggest that the small-event complexity that some such models show will not survive regularization of the constitutive description, by inclusion of an appropriate length scale leading to a finite h*, and a corresponding reduction of numerical grid size. Images Fig. 2 Fig. 3 Fig. 4 Fig. 5 PMID:11607669
Minimum-complexity helicopter simulation math model
NASA Technical Reports Server (NTRS)
Heffley, Robert K.; Mnich, Marc A.
1988-01-01
An example of a minimal complexity simulation helicopter math model is presented. Motivating factors are the computational delays, cost, and inflexibility of the very sophisticated math models now in common use. A helicopter model form is given which addresses each of these factors and provides better engineering understanding of the specific handling qualities features which are apparent to the simulator pilot. The technical approach begins with specification of features which are to be modeled, followed by a build up of individual vehicle components and definition of equations. Model matching and estimation procedures are given which enable the modeling of specific helicopters from basic data sources such as flight manuals. Checkout procedures are given which provide for total model validation. A number of possible model extensions and refinement are discussed. Math model computer programs are defined and listed.
Knorr, K L; Hilsenbeck, S G; Wenger, C R; Pounds, G; Oldaker, T; Vendely, P; Pandian, M R; Harrington, D; Clark, G M
1992-01-01
Determining an appropriate level of adjuvant therapy is one of the most difficult facets of treating breast cancer patients. Although the myriad of prognostic factors aid in this decision, often they give conflicting reports of a patient's prognosis. What we need is a survival model which can properly utilize the information contained in these factors and give an accurate, reliable account of the patient's probability of recurrence. We also need a method of evaluating these models' predictive ability instead of simply measuring goodness-of-fit, as is currently done. Often, prognostic factors are broken into two categories such as positive or negative. But this dichotomization may hide valuable prognostic information. We investigated whether continuous representations of factors, including standard transformations--logarithmic, square root, categorical, and smoothers--might more accurately estimate the underlying relationship between each factor and survival. We chose the logistic regression model, a special case of the commonly used Cox model, to test our hypothesis. The model containing continuous transformed factors fit the data more closely than the model containing the traditional dichotomized factors. In order to appropriately evaluate these models, we introduce three predictive validity statistics--the Calibration score, the Overall Calibration score, and the Brier score--designed to assess the model's accuracy and reliability. These standardized scores showed the transformed factors predicted three year survival accurately and reliably. The scores can also be used to assess models or compare across studies. PMID:1391991
Woon, D.E.; Dunning, T.H. Jr.; Peterson, K.A.
1996-04-01
Augmented correlation consistent basis sets of double (aug-cc-pVDZ), triple (aug-cc-pVTZ), and modified quadruple zeta (aug-cc-pVQZ{prime}) quality have been employed to describe the N{sub 2}{endash}HF potential energy surface at the Hartree{endash}Fock level and with single reference correlated wave functions including Mo/ller{endash}Plesset perturbation theory (MP2, MP3, MP4) and coupled cluster methods [CCSD, CCSD(T)]. The most accurate computed equilibrium binding energies {ital D}{sub {ital e}} are (with counterpoise correction) 810 cm{sup {minus}1} (MP4/aug-cc-pVQZ{prime}) and 788 cm{sup {minus}1} [CCSD(T)/aug-cc-pVQZ{prime}]. Estimated complete basis set limits of 814 cm{sup {minus}1} (MP4) and 793 cm{sup {minus}1} [CCSD(T)] indicate that the large basis set results are essentially converged. Harmonic frequencies and zero-point energies were determined through the aug-cc-pVTZ level. Combining the zero point energies computed at the aug-cc-pVTZ level with the equilibrium binding energies computed at the aug-cc-pVQZ{prime} level, we predict {ital D}{sub 0} values of 322 and 296 cm{sup {minus}1}, respectively, at the MP4 and CCSD(T) levels of theory. Using experimental anharmonic frequencies, on the other hand, the CCSD(T) value of {ital D}{sub 0} is increased to 415 cm{sup {minus}1}, in good agreement with the experimental value recently reported by Miller and co-workers, 398{plus_minus}2 cm{sup {minus}1}. {copyright} {ital 1996 American Institute of Physics.}
Augustin, Christoph M.; Neic, Aurel; Liebmann, Manfred; Prassl, Anton J.; Niederer, Steven A.; Haase, Gundolf; Plank, Gernot
2016-01-01
Electromechanical (EM) models of the heart have been used successfully to study fundamental mechanisms underlying a heart beat in health and disease. However, in all modeling studies reported so far numerous simplifications were made in terms of representing biophysical details of cellular function and its heterogeneity, gross anatomy and tissue microstructure, as well as the bidirectional coupling between electrophysiology (EP) and tissue distension. One limiting factor is the employed spatial discretization methods which are not sufficiently flexible to accommodate complex geometries or resolve heterogeneities, but, even more importantly, the limited efficiency of the prevailing solver techniques which are not sufficiently scalable to deal with the incurring increase in degrees of freedom (DOF) when modeling cardiac electromechanics at high spatio-temporal resolution. This study reports on the development of a novel methodology for solving the nonlinear equation of finite elasticity using human whole organ models of cardiac electromechanics, discretized at a high para-cellular resolution. Three patient-specific, anatomically accurate, whole heart EM models were reconstructed from magnetic resonance (MR) scans at resolutions of 220 μm, 440 μm and 880 μm, yielding meshes of approximately 184.6, 24.4 and 3.7 million tetrahedral elements and 95.9, 13.2 and 2.1 million displacement DOF, respectively. The same mesh was used for discretizing the governing equations of both electrophysiology (EP) and nonlinear elasticity. A novel algebraic multigrid (AMG) preconditioner for an iterative Krylov solver was developed to deal with the resulting computational load. The AMG preconditioner was designed under the primary objective of achieving favorable strong scaling characteristics for both setup and solution runtimes, as this is key for exploiting current high performance computing hardware. Benchmark results using the 220 μm, 440 μm and 880 μm meshes demonstrate
NASA Astrophysics Data System (ADS)
Augustin, Christoph M.; Neic, Aurel; Liebmann, Manfred; Prassl, Anton J.; Niederer, Steven A.; Haase, Gundolf; Plank, Gernot
2016-01-01
Electromechanical (EM) models of the heart have been used successfully to study fundamental mechanisms underlying a heart beat in health and disease. However, in all modeling studies reported so far numerous simplifications were made in terms of representing biophysical details of cellular function and its heterogeneity, gross anatomy and tissue microstructure, as well as the bidirectional coupling between electrophysiology (EP) and tissue distension. One limiting factor is the employed spatial discretization methods which are not sufficiently flexible to accommodate complex geometries or resolve heterogeneities, but, even more importantly, the limited efficiency of the prevailing solver techniques which is not sufficiently scalable to deal with the incurring increase in degrees of freedom (DOF) when modeling cardiac electromechanics at high spatio-temporal resolution. This study reports on the development of a novel methodology for solving the nonlinear equation of finite elasticity using human whole organ models of cardiac electromechanics, discretized at a high para-cellular resolution. Three patient-specific, anatomically accurate, whole heart EM models were reconstructed from magnetic resonance (MR) scans at resolutions of 220 μm, 440 μm and 880 μm, yielding meshes of approximately 184.6, 24.4 and 3.7 million tetrahedral elements and 95.9, 13.2 and 2.1 million displacement DOF, respectively. The same mesh was used for discretizing the governing equations of both electrophysiology (EP) and nonlinear elasticity. A novel algebraic multigrid (AMG) preconditioner for an iterative Krylov solver was developed to deal with the resulting computational load. The AMG preconditioner was designed under the primary objective of achieving favorable strong scaling characteristics for both setup and solution runtimes, as this is key for exploiting current high performance computing hardware. Benchmark results using the 220 μm, 440 μm and 880 μm meshes demonstrate
Du, Xiao-Hong; Wang, Qing-Ming; Uchino, Kenji
2004-02-01
In this paper, we present the design of measurements for single crystals by using the general results in Part I of this paper. The selection of impedance measurement or admittance measurement for both bar and plate type resonators is dependent on whether the cutting orientation l is parallel to or perpendicular to the electric field direction n. Two matrices A and B, which are defined in part I of this paper, are major tools used for the measurement design. For different cutting orientations, the elements in matrix A are associated with different elastic and piezoelectric constants. Matrix B reveals what vibration modes can be excited electrically and how to excite them. With the aid of matrices A and B, the design of measurement becomes straightforward. The measurement for a rhombohedral class (3m) LiNbO3 single crystal is used as an example to demonstrate the experiment and calculation procedures. It is found that by using either three thin bars and one plate or three plates and one thin bar we can completely characterize the complex materials constants of a LiNbO3 single crystal. PMID:15055814
The Kuramoto model in complex networks
NASA Astrophysics Data System (ADS)
Rodrigues, Francisco A.; Peron, Thomas K. DM.; Ji, Peng; Kurths, Jürgen
2016-01-01
Synchronization of an ensemble of oscillators is an emergent phenomenon present in several complex systems, ranging from social and physical to biological and technological systems. The most successful approach to describe how coherent behavior emerges in these complex systems is given by the paradigmatic Kuramoto model. This model has been traditionally studied in complete graphs. However, besides being intrinsically dynamical, complex systems present very heterogeneous structure, which can be represented as complex networks. This report is dedicated to review main contributions in the field of synchronization in networks of Kuramoto oscillators. In particular, we provide an overview of the impact of network patterns on the local and global dynamics of coupled phase oscillators. We cover many relevant topics, which encompass a description of the most used analytical approaches and the analysis of several numerical results. Furthermore, we discuss recent developments on variations of the Kuramoto model in networks, including the presence of noise and inertia. The rich potential for applications is discussed for special fields in engineering, neuroscience, physics and Earth science. Finally, we conclude by discussing problems that remain open after the last decade of intensive research on the Kuramoto model and point out some promising directions for future research.
Mathematical modelling of complex contagion on clustered networks
NASA Astrophysics Data System (ADS)
O'sullivan, David J.; O'Keeffe, Gary; Fennell, Peter; Gleeson, James
2015-09-01
The spreading of behavior, such as the adoption of a new innovation, is influenced bythe structure of social networks that interconnect the population. In the experiments of Centola (Science, 2010), adoption of new behavior was shown to spread further and faster across clustered-lattice networks than across corresponding random networks. This implies that the “complex contagion” effects of social reinforcement are important in such diffusion, in contrast to “simple” contagion models of disease-spread which predict that epidemics would grow more efficiently on random networks than on clustered networks. To accurately model complex contagion on clustered networks remains a challenge because the usual assumptions (e.g. of mean-field theory) regarding tree-like networks are invalidated by the presence of triangles in the network; the triangles are, however, crucial to the social reinforcement mechanism, which posits an increased probability of a person adopting behavior that has been adopted by two or more neighbors. In this paper we modify the analytical approach that was introduced by Hebert-Dufresne et al. (Phys. Rev. E, 2010), to study disease-spread on clustered networks. We show how the approximation method can be adapted to a complex contagion model, and confirm the accuracy of the method with numerical simulations. The analytical results of the model enable us to quantify the level of social reinforcement that is required to observe—as in Centola’s experiments—faster diffusion on clustered topologies than on random networks.
Modelling biological complexity: a physical scientist's perspective
Coveney, Peter V; Fowler, Philip W
2005-01-01
We discuss the modern approaches of complexity and self-organization to understanding dynamical systems and how these concepts can inform current interest in systems biology. From the perspective of a physical scientist, it is especially interesting to examine how the differing weights given to philosophies of science in the physical and biological sciences impact the application of the study of complexity. We briefly describe how the dynamics of the heart and circadian rhythms, canonical examples of systems biology, are modelled by sets of nonlinear coupled differential equations, which have to be solved numerically. A major difficulty with this approach is that all the parameters within these equations are not usually known. Coupled models that include biomolecular detail could help solve this problem. Coupling models across large ranges of length- and time-scales is central to describing complex systems and therefore to biology. Such coupling may be performed in at least two different ways, which we refer to as hierarchical and hybrid multiscale modelling. While limited progress has been made in the former case, the latter is only beginning to be addressed systematically. These modelling methods are expected to bring numerous benefits to biology, for example, the properties of a system could be studied over a wider range of length- and time-scales, a key aim of systems biology. Multiscale models couple behaviour at the molecular biological level to that at the cellular level, thereby providing a route for calculating many unknown parameters as well as investigating the effects at, for example, the cellular level, of small changes at the biomolecular level, such as a genetic mutation or the presence of a drug. The modelling and simulation of biomolecular systems is itself very computationally intensive; we describe a recently developed hybrid continuum-molecular model, HybridMD, and its associated molecular insertion algorithm, which point the way towards the
Modelling biological complexity: a physical scientist's perspective.
Coveney, Peter V; Fowler, Philip W
2005-09-22
We discuss the modern approaches of complexity and self-organization to understanding dynamical systems and how these concepts can inform current interest in systems biology. From the perspective of a physical scientist, it is especially interesting to examine how the differing weights given to philosophies of science in the physical and biological sciences impact the application of the study of complexity. We briefly describe how the dynamics of the heart and circadian rhythms, canonical examples of systems biology, are modelled by sets of nonlinear coupled differential equations, which have to be solved numerically. A major difficulty with this approach is that all the parameters within these equations are not usually known. Coupled models that include biomolecular detail could help solve this problem. Coupling models across large ranges of length- and time-scales is central to describing complex systems and therefore to biology. Such coupling may be performed in at least two different ways, which we refer to as hierarchical and hybrid multiscale modelling. While limited progress has been made in the former case, the latter is only beginning to be addressed systematically. These modelling methods are expected to bring numerous benefits to biology, for example, the properties of a system could be studied over a wider range of length- and time-scales, a key aim of systems biology. Multiscale models couple behaviour at the molecular biological level to that at the cellular level, thereby providing a route for calculating many unknown parameters as well as investigating the effects at, for example, the cellular level, of small changes at the biomolecular level, such as a genetic mutation or the presence of a drug. The modelling and simulation of biomolecular systems is itself very computationally intensive; we describe a recently developed hybrid continuum-molecular model, HybridMD, and its associated molecular insertion algorithm, which point the way towards the
How useful are complex flood damage models?
NASA Astrophysics Data System (ADS)
Schröter, Kai; Kreibich, Heidi; Vogel, Kristin; Riggelsen, Carsten; Scherbaum, Frank; Merz, Bruno
2014-04-01
We investigate the usefulness of complex flood damage models for predicting relative damage to residential buildings in a spatial and temporal transfer context. We apply eight different flood damage models to predict relative building damage for five historic flood events in two different regions of Germany. Model complexity is measured in terms of the number of explanatory variables which varies from 1 variable up to 10 variables which are singled out from 28 candidate variables. Model validation is based on empirical damage data, whereas observation uncertainty is taken into consideration. The comparison of model predictive performance shows that additional explanatory variables besides the water depth improve the predictive capability in a spatial and temporal transfer context, i.e., when the models are transferred to different regions and different flood events. Concerning the trade-off between predictive capability and reliability the model structure seem more important than the number of explanatory variables. Among the models considered, the reliability of Bayesian network-based predictions in space-time transfer is larger than for the remaining models, and the uncertainties associated with damage predictions are reflected more completely.
Dunn, Nicholas J. H.; Noid, W. G.
2015-12-28
The present work investigates the capability of bottom-up coarse-graining (CG) methods for accurately modeling both structural and thermodynamic properties of all-atom (AA) models for molecular liquids. In particular, we consider 1, 2, and 3-site CG models for heptane, as well as 1 and 3-site CG models for toluene. For each model, we employ the multiscale coarse-graining method to determine interaction potentials that optimally approximate the configuration dependence of the many-body potential of mean force (PMF). We employ a previously developed “pressure-matching” variational principle to determine a volume-dependent contribution to the potential, U{sub V}(V), that approximates the volume-dependence of the PMF. We demonstrate that the resulting CG models describe AA density fluctuations with qualitative, but not quantitative, accuracy. Accordingly, we develop a self-consistent approach for further optimizing U{sub V}, such that the CG models accurately reproduce the equilibrium density, compressibility, and average pressure of the AA models, although the CG models still significantly underestimate the atomic pressure fluctuations. Additionally, by comparing this array of models that accurately describe the structure and thermodynamic pressure of heptane and toluene at a range of different resolutions, we investigate the impact of bottom-up coarse-graining upon thermodynamic properties. In particular, we demonstrate that U{sub V} accounts for the reduced cohesion in the CG models. Finally, we observe that bottom-up coarse-graining introduces subtle correlations between the resolution, the cohesive energy density, and the “simplicity” of the model.
Assessment of higher order turbulence models for complex two- and three-dimensional flowfields
NASA Technical Reports Server (NTRS)
Menter, Florian R.
1992-01-01
A numerical method is presented to solve the three-dimensional Navier-Stokes equations in combination with a full Reynolds-stress turbulence model. Computations will be shown for three complex flowfields. The results of the Reynolds-stress model will be compared with those predicted by two different versions of the k-omega model. It will be shown that an improved version of the k-omega model gives as accurate results as the Reynolds-stress model.
Modeling Electromagnetic Scattering From Complex Inhomogeneous Objects
NASA Technical Reports Server (NTRS)
Deshpande, Manohar; Reddy, C. J.
2011-01-01
This software innovation is designed to develop a mathematical formulation to estimate the electromagnetic scattering characteristics of complex, inhomogeneous objects using the finite-element-method (FEM) and method-of-moments (MoM) concepts, as well as to develop a FORTRAN code called FEMOM3DS (Finite Element Method and Method of Moments for 3-Dimensional Scattering), which will implement the steps that are described in the mathematical formulation. Very complex objects can be easily modeled, and the operator of the code is not required to know the details of electromagnetic theory to study electromagnetic scattering.
Synthetic seismograms for a complex crustal model
NASA Astrophysics Data System (ADS)
Sandmeier, K.-J.; Wenzel, F.
1986-01-01
The algorithm of the original Reflectivity Method has been vectorized and implemented on a CDC CYBER 205 computer. Calculation times are shortened by a factor of 20 to 30 compared with a general purpose computer with a capacity of several million floating point operations per second (MFLOP). The rapid calculation of synthetic seismograms for complex models, high frequency sources and all offset ranges is a provision for modeling not only particular phases but the whole observed wavefield. As an example we model refraction data of the Black Forest, Southwest Germany and are able to derive rather tight constraints on the physical properties of the lower crust.
Accurate cortical tissue classification on MRI by modeling cortical folding patterns.
Kim, Hosung; Caldairou, Benoit; Hwang, Ji-Wook; Mansi, Tommaso; Hong, Seok-Jun; Bernasconi, Neda; Bernasconi, Andrea
2015-09-01
Accurate tissue classification is a crucial prerequisite to MRI morphometry. Automated methods based on intensity histograms constructed from the entire volume are challenged by regional intensity variations due to local radiofrequency artifacts as well as disparities in tissue composition, laminar architecture and folding patterns. Current work proposes a novel anatomy-driven method in which parcels conforming cortical folding were regionally extracted from the brain. Each parcel is subsequently classified using nonparametric mean shift clustering. Evaluation was carried out on manually labeled images from two datasets acquired at 3.0 Tesla (n = 15) and 1.5 Tesla (n = 20). In both datasets, we observed high tissue classification accuracy of the proposed method (Dice index >97.6% at 3.0 Tesla, and >89.2% at 1.5 Tesla). Moreover, our method consistently outperformed state-of-the-art classification routines available in SPM8 and FSL-FAST, as well as a recently proposed local classifier that partitions the brain into cubes. Contour-based analyses localized more accurate white matter-gray matter (GM) interface classification of the proposed framework compared to the other algorithms, particularly in central and occipital cortices that generally display bright GM due to their highly degree of myelination. Excellent accuracy was maintained, even in the absence of correction for intensity inhomogeneity. The presented anatomy-driven local classification algorithm may significantly improve cortical boundary definition, with possible benefits for morphometric inference and biomarker discovery. PMID:26037453
Ustinov, E A
2014-10-01
Commensurate-incommensurate (C-IC) transition of krypton molecular layer on graphite received much attention in recent decades in theoretical and experimental researches. However, there still exists a possibility of generalization of the phenomenon from thermodynamic viewpoint on the basis of accurate molecular simulation. Recently, a new technique was developed for analysis of two-dimensional (2D) phase transitions in systems involving a crystalline phase, which is based on accounting for the effect of temperature and the chemical potential on the lattice constant of the 2D layer using the Gibbs-Duhem equation [E. A. Ustinov, J. Chem. Phys. 140, 074706 (2014)]. The technique has allowed for determination of phase diagrams of 2D argon layers on the uniform surface and in slit pores. This paper extends the developed methodology on systems accounting for the periodic modulation of the substrate potential. The main advantage of the developed approach is that it provides highly accurate evaluation of the chemical potential of crystalline layers, which allows reliable determination of temperature and other parameters of various 2D phase transitions. Applicability of the methodology is demonstrated on the krypton-graphite system. Analysis of phase diagram of the krypton molecular layer, thermodynamic functions of coexisting phases, and a method of prediction of adsorption isotherms is considered accounting for a compression of the graphite due to the krypton-carbon interaction. The temperature and heat of C-IC transition has been reliably determined for the gas-solid and solid-solid system. PMID:25296827
Ustinov, E. A.
2014-10-07
Commensurate–incommensurate (C-IC) transition of krypton molecular layer on graphite received much attention in recent decades in theoretical and experimental researches. However, there still exists a possibility of generalization of the phenomenon from thermodynamic viewpoint on the basis of accurate molecular simulation. Recently, a new technique was developed for analysis of two-dimensional (2D) phase transitions in systems involving a crystalline phase, which is based on accounting for the effect of temperature and the chemical potential on the lattice constant of the 2D layer using the Gibbs–Duhem equation [E. A. Ustinov, J. Chem. Phys. 140, 074706 (2014)]. The technique has allowed for determination of phase diagrams of 2D argon layers on the uniform surface and in slit pores. This paper extends the developed methodology on systems accounting for the periodic modulation of the substrate potential. The main advantage of the developed approach is that it provides highly accurate evaluation of the chemical potential of crystalline layers, which allows reliable determination of temperature and other parameters of various 2D phase transitions. Applicability of the methodology is demonstrated on the krypton–graphite system. Analysis of phase diagram of the krypton molecular layer, thermodynamic functions of coexisting phases, and a method of prediction of adsorption isotherms is considered accounting for a compression of the graphite due to the krypton–carbon interaction. The temperature and heat of C-IC transition has been reliably determined for the gas–solid and solid–solid system.
Surface electron density models for accurate ab initio molecular dynamics with electronic friction
NASA Astrophysics Data System (ADS)
Novko, D.; Blanco-Rey, M.; Alducin, M.; Juaristi, J. I.
2016-06-01
Ab initio molecular dynamics with electronic friction (AIMDEF) is a valuable methodology to study the interaction of atomic particles with metal surfaces. This method, in which the effect of low-energy electron-hole (e-h) pair excitations is treated within the local density friction approximation (LDFA) [Juaristi et al., Phys. Rev. Lett. 100, 116102 (2008), 10.1103/PhysRevLett.100.116102], can provide an accurate description of both e-h pair and phonon excitations. In practice, its applicability becomes a complicated task in those situations of substantial surface atoms displacements because the LDFA requires the knowledge at each integration step of the bare surface electron density. In this work, we propose three different methods of calculating on-the-fly the electron density of the distorted surface and we discuss their suitability under typical surface distortions. The investigated methods are used in AIMDEF simulations for three illustrative adsorption cases, namely, dissociated H2 on Pd(100), N on Ag(111), and N2 on Fe(110). Our AIMDEF calculations performed with the three approaches highlight the importance of going beyond the frozen surface density to accurately describe the energy released into e-h pair excitations in case of large surface atom displacements.
NASA Astrophysics Data System (ADS)
Zhang, Xiang; Vu-Quoc, Loc
2007-07-01
We present in this paper the displacement-driven version of a tangential force-displacement (TFD) model that accounts for both elastic and plastic deformations together with interfacial friction occurring in collisions of spherical particles. This elasto-plastic frictional TFD model, with its force-driven version presented in [L. Vu-Quoc, L. Lesburg, X. Zhang. An accurate tangential force-displacement model for granular-flow simulations: contacting spheres with plastic deformation, force-driven formulation, Journal of Computational Physics 196(1) (2004) 298-326], is consistent with the elasto-plastic frictional normal force-displacement (NFD) model presented in [L. Vu-Quoc, X. Zhang. An elasto-plastic contact force-displacement model in the normal direction: displacement-driven version, Proceedings of the Royal Society of London, Series A 455 (1991) 4013-4044]. Both the NFD model and the present TFD model are based on the concept of additive decomposition of the radius of contact area into an elastic part and a plastic part. The effect of permanent indentation after impact is represented by a correction to the radius of curvature. The effect of material softening due to plastic flow is represented by a correction to the elastic moduli. The proposed TFD model is accurate, and is validated against nonlinear finite element analyses involving plastic flows in both the loading and unloading conditions. The proposed consistent displacement-driven, elasto-plastic NFD and TFD models are designed for implementation in computer codes using the discrete-element method (DEM) for granular-flow simulations. The model is shown to be accurate and is validated against nonlinear elasto-plastic finite-element analysis.
Human driven transitions in complex model ecosystems
NASA Astrophysics Data System (ADS)
Harfoot, Mike; Newbold, Tim; Tittinsor, Derek; Purves, Drew
2015-04-01
Human activities have been observed to be impacting ecosystems across the globe, leading to reduced ecosystem functioning, altered trophic and biomass structure and ultimately ecosystem collapse. Previous attempts to understand global human impacts on ecosystems have usually relied on statistical models, which do not explicitly model the processes underlying the functioning of ecosystems, represent only a small proportion of organisms and do not adequately capture complex non-linear and dynamic responses of ecosystems to perturbations. We use a mechanistic ecosystem model (1), which simulates the underlying processes structuring ecosystems and can thus capture complex and dynamic interactions, to investigate boundaries of complex ecosystems to human perturbation. We explore several drivers including human appropriation of net primary production and harvesting of animal biomass. We also present an analysis of the key interactions between biotic, societal and abiotic earth system components, considering why and how we might think about these couplings. References: M. B. J. Harfoot et al., Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model., PLoS Biol. 12, e1001841 (2014).
ERIC Educational Resources Information Center
Gong, Yue; Beck, Joseph E.; Heffernan, Neil T.
2011-01-01
Student modeling is a fundamental concept applicable to a variety of intelligent tutoring systems (ITS). However, there is not a lot of practical guidance on how to construct and train such models. This paper compares two approaches for student modeling, Knowledge Tracing (KT) and Performance Factors Analysis (PFA), by evaluating their predictive…
Models in biology: ‘accurate descriptions of our pathetic thinking’
2014-01-01
In this essay I will sketch some ideas for how to think about models in biology. I will begin by trying to dispel the myth that quantitative modeling is somehow foreign to biology. I will then point out the distinction between forward and reverse modeling and focus thereafter on the former. Instead of going into mathematical technicalities about different varieties of models, I will focus on their logical structure, in terms of assumptions and conclusions. A model is a logical machine for deducing the latter from the former. If the model is correct, then, if you believe its assumptions, you must, as a matter of logic, also believe its conclusions. This leads to consideration of the assumptions underlying models. If these are based on fundamental physical laws, then it may be reasonable to treat the model as ‘predictive’, in the sense that it is not subject to falsification and we can rely on its conclusions. However, at the molecular level, models are more often derived from phenomenology and guesswork. In this case, the model is a test of its assumptions and must be falsifiable. I will discuss three models from this perspective, each of which yields biological insights, and this will lead to some guidelines for prospective model builders. PMID:24886484
More accurate predictions with transonic Navier-Stokes methods through improved turbulence modeling
NASA Technical Reports Server (NTRS)
Johnson, Dennis A.
1989-01-01
Significant improvements in predictive accuracies for off-design conditions are achievable through better turbulence modeling; and, without necessarily adding any significant complication to the numerics. One well established fact about turbulence is it is slow to respond to changes in the mean strain field. With the 'equilibrium' algebraic turbulence models no attempt is made to model this characteristic and as a consequence these turbulence models exaggerate the turbulent boundary layer's ability to produce turbulent Reynolds shear stresses in regions of adverse pressure gradient. As a consequence, too little momentum loss within the boundary layer is predicted in the region of the shock wave and along the aft part of the airfoil where the surface pressure undergoes further increases. Recently, a 'nonequilibrium' algebraic turbulence model was formulated which attempts to capture this important characteristic of turbulence. This 'nonequilibrium' algebraic model employs an ordinary differential equation to model the slow response of the turbulence to changes in local flow conditions. In its original form, there was some question as to whether this 'nonequilibrium' model performed as well as the 'equilibrium' models for weak interaction cases. However, this turbulence model has since been further improved wherein it now appears that this turbulence model performs at least as well as the 'equilibrium' models for weak interaction cases and for strong interaction cases represents a very significant improvement. The performance of this turbulence model relative to popular 'equilibrium' models is illustrated for three airfoil test cases of the 1987 AIAA Viscous Transonic Airfoil Workshop, Reno, Nevada. A form of this 'nonequilibrium' turbulence model is currently being applied to wing flows for which similar improvements in predictive accuracy are being realized.
A Practical Philosophy of Complex Climate Modelling
NASA Technical Reports Server (NTRS)
Schmidt, Gavin A.; Sherwood, Steven
2014-01-01
We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project (CMIP).We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naive predictions. The framework we use for making inferences about reality using simulations is naturally Bayesian (in an informal sense), and has many points of contact with more familiar examples of scientific epistemology. While the use of complex simulations in science is a development that changes much in how science is done in practice, we argue that the concepts being applied fit very much into traditional practices of the scientific method, albeit those more often associated with laboratory work.
Johnson, Timothy C.; Wellman, Dawn M.
2015-06-26
Electrical resistivity tomography (ERT) has been widely used in environmental applications to study processes associated with subsurface contaminants and contaminant remediation. Anthropogenic alterations in subsurface electrical conductivity associated with contamination often originate from highly industrialized areas with significant amounts of buried metallic infrastructure. The deleterious influence of such infrastructure on imaging results generally limits the utility of ERT where it might otherwise prove useful for subsurface investigation and monitoring. In this manuscript we present a method of accurately modeling the effects of buried conductive infrastructure within the forward modeling algorithm, thereby removing them from the inversion results. The method is implemented in parallel using immersed interface boundary conditions, whereby the global solution is reconstructed from a series of well-conditioned partial solutions. Forward modeling accuracy is demonstrated by comparison with analytic solutions. Synthetic imaging examples are used to investigate imaging capabilities within a subsurface containing electrically conductive buried tanks, transfer piping, and well casing, using both well casings and vertical electrode arrays as current sources and potential measurement electrodes. Results show that, although accurate infrastructure modeling removes the dominating influence of buried metallic features, the presence of metallic infrastructure degrades imaging resolution compared to standard ERT imaging. However, accurate imaging results may be obtained if electrodes are appropriately located.
Intrinsic Uncertainties in Modeling Complex Systems.
Cooper, Curtis S; Bramson, Aaron L.; Ames, Arlo L.
2014-09-01
Models are built to understand and predict the behaviors of both natural and artificial systems. Because it is always necessary to abstract away aspects of any non-trivial system being modeled, we know models can potentially leave out important, even critical elements. This reality of the modeling enterprise forces us to consider the prospective impacts of those effects completely left out of a model - either intentionally or unconsidered. Insensitivity to new structure is an indication of diminishing returns. In this work, we represent a hypothetical unknown effect on a validated model as a finite perturba- tion whose amplitude is constrained within a control region. We find robustly that without further constraints, no meaningful bounds can be placed on the amplitude of a perturbation outside of the control region. Thus, forecasting into unsampled regions is a very risky proposition. We also present inherent difficulties with proper time discretization of models and representing in- herently discrete quantities. We point out potentially worrisome uncertainties, arising from math- ematical formulation alone, which modelers can inadvertently introduce into models of complex systems. Acknowledgements This work has been funded under early-career LDRD project #170979, entitled "Quantify- ing Confidence in Complex Systems Models Having Structural Uncertainties", which ran from 04/2013 to 09/2014. We wish to express our gratitude to the many researchers at Sandia who con- tributed ideas to this work, as well as feedback on the manuscript. In particular, we would like to mention George Barr, Alexander Outkin, Walt Beyeler, Eric Vugrin, and Laura Swiler for provid- ing invaluable advice and guidance through the course of the project. We would also like to thank Steven Kleban, Amanda Gonzales, Trevor Manzanares, and Sarah Burwell for their assistance in managing project tasks and resources.
Simulating Complex Modulated Phases Through Spin Models
NASA Astrophysics Data System (ADS)
Selinger, Jonathan V.; Lopatina, Lena M.; Geng, Jun; Selinger, Robin L. B.
2009-03-01
We extend the computational approach for studying striped phases on curved surfaces, presented in the previous talk, to two new problems involving complex modulated phases. First, we simulate a smectic liquid crystal on an arbitrary mesh by mapping the director field onto a vector spin and the density wave onto an Ising spin. We can thereby determine how the smectic phase responds to any geometrical constraints, including hybrid boundary conditions, patterned substrates, and disordered substrates. This method may provide a useful tool for designing ferroelectric liquid crystal cells. Second, we explore a model of vector spins on a flat two-dimensional (2D) lattice with long-range antiferromagnetic interactions. This model generates modulated phases with surprisingly complex structures, including 1D stripes and 2D periodic cells, which are independent of the underlying lattice. We speculate on the physical significance of these structures.
NASA Astrophysics Data System (ADS)
Toyokuni, Genti; Takenaka, Hiroshi
2012-06-01
We propose a method for modeling global seismic wave propagation through an attenuative Earth model including the center. This method enables accurate and efficient computations since it is based on the 2.5-D approach, which solves wave equations only on a 2-D cross section of the whole Earth and can correctly model 3-D geometrical spreading. We extend a numerical scheme for the elastic waves in spherical coordinates using the finite-difference method (FDM), to solve the viscoelastodynamic equation. For computation of realistic seismic wave propagation, incorporation of anelastic attenuation is crucial. Since the nature of Earth material is both elastic solid and viscous fluid, we should solve stress-strain relations of viscoelastic material, including attenuative structures. These relations represent the stress as a convolution integral in time, which has had difficulty treating viscoelasticity in time-domain computation such as the FDM. However, we now have a method using so-called memory variables, invented in the 1980s, followed by improvements in Cartesian coordinates. Arbitrary values of the quality factor (Q) can be incorporated into the wave equation via an array of Zener bodies. We also introduce the multi-domain, an FD grid of several layers with different grid spacings, into our FDM scheme. This allows wider lateral grid spacings with depth, so as not to perturb the FD stability criterion around the Earth center. In addition, we propose a technique to avoid the singularity problem of the wave equation in spherical coordinates at the Earth center. We develop a scheme to calculate wavefield variables on this point, based on linear interpolation for the velocity-stress, staggered-grid FDM. This scheme is validated through a comparison of synthetic seismograms with those obtained by the Direct Solution Method for a spherically symmetric Earth model, showing excellent accuracy for our FDM scheme. As a numerical example, we apply the method to simulate seismic
Industrial Source Complex (ISC) dispersion model. Software
Schewe, G.; Sieurin, E.
1980-01-01
The model updates various EPA dispersion model algorithms and combines them in two computer programs that can be used to assess the air quality impact of emissions from the wide variety of source types associated with an industrial source complex. The ISC Model short-term program ISCST, an updated version of the EPA Single Source (CRSTER) Model uses sequential hourly meteorological data to calculate values of average concentration or total dry deposition for time periods of 1, 2, 3, 4, 6, 8, 12 and 24 hours. Additionally, ISCST may be used to calculate 'N' is 366 days. The ISC Model long-term computer program ISCLT, a sector-averaged model that updates and combines basic features of the EPA Air Quality Display Model (AQDM) and the EPA Climatological Dispersion Model (CDM), uses STAR Summaries to calculate seasonal and/or annual average concentration or total deposition values. Both the ISCST and ISCLT programs make the same basic dispersion-model assumptions. Additionally, both the ISCST and ISCLT programs use either a polar or a Cartesian receptor grid...Software Description: The programs are written in the FORTRAN IV programming language for implementation on a UNIVAC 1110 computer and also on medium-to-large IBM or CDC systems. 65,000k words of core storage are required to operate the model.
Noncommutative complex Grosse-Wulkenhaar model
Hounkonnou, Mahouton Norbert; Samary, Dine Ousmane
2008-11-18
This paper stands for an application of the noncommutative (NC) Noether theorem, given in our previous work [AIP Proc 956(2007) 55-60], for the NC complex Grosse-Wulkenhaar model. It provides with an extension of a recent work [Physics Letters B 653(2007) 343-345]. The local conservation of energy-momentum tensors (EMTs) is recovered using improvement procedures based on Moyal algebraic techniques. Broken dilatation symmetry is discussed. NC gauge currents are also explicitly computed.
Pal, Saikat; Lindsey, Derek P.; Besier, Thor F.; Beaupre, Gary S.
2013-01-01
Cartilage material properties provide important insights into joint health, and cartilage material models are used in whole-joint finite element models. Although the biphasic model representing experimental creep indentation tests is commonly used to characterize cartilage, cartilage short-term response to loading is generally not characterized using the biphasic model. The purpose of this study was to determine the short-term and equilibrium material properties of human patella cartilage using a viscoelastic model representation of creep indentation tests. We performed 24 experimental creep indentation tests from 14 human patellar specimens ranging in age from 20 to 90 years (median age 61 years). We used a finite element model to reproduce the experimental tests and determined cartilage material properties from viscoelastic and biphasic representations of cartilage. The viscoelastic model consistently provided excellent representation of the short-term and equilibrium creep displacements. We determined initial elastic modulus, equilibrium elastic modulus, and equilibrium Poisson’s ratio using the viscoelastic model. The viscoelastic model can represent the short-term and equilibrium response of cartilage and may easily be implemented in whole-joint finite element models. PMID:23027200
NASA Astrophysics Data System (ADS)
Zakrzewski, Jakub; Delande, Dominique
2008-11-01
The quantum phase transition point between the insulator and the superfluid phase at unit filling factor of the infinite one-dimensional Bose-Hubbard model is numerically computed with a high accuracy. The method uses the infinite system version of the time evolving block decimation algorithm, here tested in a challenging case. We provide also the accurate estimate of the phase transition point at double occupancy.
The noisy voter model on complex networks
NASA Astrophysics Data System (ADS)
Carro, Adrián; Toral, Raúl; San Miguel, Maxi
2016-04-01
We propose a new analytical method to study stochastic, binary-state models on complex networks. Moving beyond the usual mean-field theories, this alternative approach is based on the introduction of an annealed approximation for uncorrelated networks, allowing to deal with the network structure as parametric heterogeneity. As an illustration, we study the noisy voter model, a modification of the original voter model including random changes of state. The proposed method is able to unfold the dependence of the model not only on the mean degree (the mean-field prediction) but also on more complex averages over the degree distribution. In particular, we find that the degree heterogeneity—variance of the underlying degree distribution—has a strong influence on the location of the critical point of a noise-induced, finite-size transition occurring in the model, on the local ordering of the system, and on the functional form of its temporal correlations. Finally, we show how this latter point opens the possibility of inferring the degree heterogeneity of the underlying network by observing only the aggregate behavior of the system as a whole, an issue of interest for systems where only macroscopic, population level variables can be measured.
The noisy voter model on complex networks
Carro, Adrián; Toral, Raúl; San Miguel, Maxi
2016-01-01
We propose a new analytical method to study stochastic, binary-state models on complex networks. Moving beyond the usual mean-field theories, this alternative approach is based on the introduction of an annealed approximation for uncorrelated networks, allowing to deal with the network structure as parametric heterogeneity. As an illustration, we study the noisy voter model, a modification of the original voter model including random changes of state. The proposed method is able to unfold the dependence of the model not only on the mean degree (the mean-field prediction) but also on more complex averages over the degree distribution. In particular, we find that the degree heterogeneity—variance of the underlying degree distribution—has a strong influence on the location of the critical point of a noise-induced, finite-size transition occurring in the model, on the local ordering of the system, and on the functional form of its temporal correlations. Finally, we show how this latter point opens the possibility of inferring the degree heterogeneity of the underlying network by observing only the aggregate behavior of the system as a whole, an issue of interest for systems where only macroscopic, population level variables can be measured. PMID:27094773
The noisy voter model on complex networks.
Carro, Adrián; Toral, Raúl; San Miguel, Maxi
2016-01-01
We propose a new analytical method to study stochastic, binary-state models on complex networks. Moving beyond the usual mean-field theories, this alternative approach is based on the introduction of an annealed approximation for uncorrelated networks, allowing to deal with the network structure as parametric heterogeneity. As an illustration, we study the noisy voter model, a modification of the original voter model including random changes of state. The proposed method is able to unfold the dependence of the model not only on the mean degree (the mean-field prediction) but also on more complex averages over the degree distribution. In particular, we find that the degree heterogeneity-variance of the underlying degree distribution-has a strong influence on the location of the critical point of a noise-induced, finite-size transition occurring in the model, on the local ordering of the system, and on the functional form of its temporal correlations. Finally, we show how this latter point opens the possibility of inferring the degree heterogeneity of the underlying network by observing only the aggregate behavior of the system as a whole, an issue of interest for systems where only macroscopic, population level variables can be measured. PMID:27094773
Complexity of groundwater models in catchment hydrological models
NASA Astrophysics Data System (ADS)
Attinger, Sabine; Herold, Christian; Kumar, Rohini; Mai, Juliane; Ross, Katharina; Samaniego, Luis; Zink, Matthias
2015-04-01
In catchment hydrological models, groundwater is usually modeled very simple: it is conceptualized as a linear reservoir that gets the water from the upper unsaturated zone reservoir and releases water to the river system as baseflow. The baseflow is only a minor component of the total river flow and groundwater reservoir parameters are therefore difficult to be inversely estimated by means of river flow data only. In addition, the modelled values of the absolute height of the water filling the groundwater reservoir - in other words the groundwater levels - are of limited meaning due to coarse or no spatial resolution of groundwater and due to the fact that only river flow data are used for the calibration. The talk focuses on the question: Which complexity in terms of model complexity and model resolution is necessary to characterize groundwater processes and groundwater responses adequately in distributed catchment hydrological models? Starting from a spatially distributed catchment hydrological model with a groundwater compartment that is conceptualized as a linear reservoir we stepwise increase the groundwater model complexity and its spatial resolution to investigate which resolution, which complexity and which data are needed to reproduce baseflow and groundwater level data adequately.
Accurate analytical method for the extraction of solar cell model parameters
NASA Astrophysics Data System (ADS)
Phang, J. C. H.; Chan, D. S. H.; Phillips, J. R.
1984-05-01
Single diode solar cell model parameters are rapidly extracted from experimental data by means of the presently derived analytical expressions. The parameter values obtained have a less than 5 percent error for most solar cells, in light of the extraction of model parameters for two cells of differing quality which were compared with parameters extracted by means of the iterative method.
Complex Constructivism: A Theoretical Model of Complexity and Cognition
ERIC Educational Resources Information Center
Doolittle, Peter E.
2014-01-01
Education has long been driven by its metaphors for teaching and learning. These metaphors have influenced both educational research and educational practice. Complexity and constructivism are two theories that provide functional and robust metaphors. Complexity provides a metaphor for the structure of myriad phenomena, while constructivism…
Active appearance model and deep learning for more accurate prostate segmentation on MRI
NASA Astrophysics Data System (ADS)
Cheng, Ruida; Roth, Holger R.; Lu, Le; Wang, Shijun; Turkbey, Baris; Gandler, William; McCreedy, Evan S.; Agarwal, Harsh K.; Choyke, Peter; Summers, Ronald M.; McAuliffe, Matthew J.
2016-03-01
Prostate segmentation on 3D MR images is a challenging task due to image artifacts, large inter-patient prostate shape and texture variability, and lack of a clear prostate boundary specifically at apex and base levels. We propose a supervised machine learning model that combines atlas based Active Appearance Model (AAM) with a Deep Learning model to segment the prostate on MR images. The performance of the segmentation method is evaluated on 20 unseen MR image datasets. The proposed method combining AAM and Deep Learning achieves a mean Dice Similarity Coefficient (DSC) of 0.925 for whole 3D MR images of the prostate using axial cross-sections. The proposed model utilizes the adaptive atlas-based AAM model and Deep Learning to achieve significant segmentation accuracy.
Fast and accurate Monte Carlo sampling of first-passage times from Wiener diffusion models
Drugowitsch, Jan
2016-01-01
We present a new, fast approach for drawing boundary crossing samples from Wiener diffusion models. Diffusion models are widely applied to model choices and reaction times in two-choice decisions. Samples from these models can be used to simulate the choices and reaction times they predict. These samples, in turn, can be utilized to adjust the models’ parameters to match observed behavior from humans and other animals. Usually, such samples are drawn by simulating a stochastic differential equation in discrete time steps, which is slow and leads to biases in the reaction time estimates. Our method, instead, facilitates known expressions for first-passage time densities, which results in unbiased, exact samples and a hundred to thousand-fold speed increase in typical situations. In its most basic form it is restricted to diffusion models with symmetric boundaries and non-leaky accumulation, but our approach can be extended to also handle asymmetric boundaries or to approximate leaky accumulation. PMID:26864391
D’Adamo, Giuseppe; Pelissetto, Andrea; Pierleoni, Carlo
2014-12-28
A coarse-graining strategy, previously developed for polymer solutions, is extended here to mixtures of linear polymers and hard-sphere colloids. In this approach, groups of monomers are mapped onto a single pseudoatom (a blob) and the effective blob-blob interactions are obtained by requiring the model to reproduce some large-scale structural properties in the zero-density limit. We show that an accurate parametrization of the polymer-colloid interactions is obtained by simply introducing pair potentials between blobs and colloids. For the coarse-grained (CG) model in which polymers are modelled as four-blob chains (tetramers), the pair potentials are determined by means of the iterative Boltzmann inversion scheme, taking full-monomer (FM) pair correlation functions at zero-density as targets. For a larger number n of blobs, pair potentials are determined by using a simple transferability assumption based on the polymer self-similarity. We validate the model by comparing its predictions with full-monomer results for the interfacial properties of polymer solutions in the presence of a single colloid and for thermodynamic and structural properties in the homogeneous phase at finite polymer and colloid density. The tetramer model is quite accurate for q ≲ 1 (q=R{sup ^}{sub g}/R{sub c}, where R{sup ^}{sub g} is the zero-density polymer radius of gyration and R{sub c} is the colloid radius) and reasonably good also for q = 2. For q = 2, an accurate coarse-grained description is obtained by using the n = 10 blob model. We also compare our results with those obtained by using single-blob models with state-dependent potentials.
Accurate calculation of binding energies for molecular clusters - Assessment of different models
NASA Astrophysics Data System (ADS)
Friedrich, Joachim; Fiedler, Benjamin
2016-06-01
In this work we test different strategies to compute high-level benchmark energies for medium-sized molecular clusters. We use the incremental scheme to obtain CCSD(T)/CBS energies for our test set and carefully validate the accuracy for binding energies by statistical measures. The local errors of the incremental scheme are <1 kJ/mol. Since they are smaller than the basis set errors, we obtain higher total accuracy due to the applicability of larger basis sets. The final CCSD(T)/CBS benchmark values are ΔE = - 278.01 kJ/mol for (H2O)10, ΔE = - 221.64 kJ/mol for (HF)10, ΔE = - 45.63 kJ/mol for (CH4)10, ΔE = - 19.52 kJ/mol for (H2)20 and ΔE = - 7.38 kJ/mol for (H2)10 . Furthermore we test state-of-the-art wave-function-based and DFT methods. Our benchmark data will be very useful for critical validations of new methods. We find focal-point-methods for estimating CCSD(T)/CBS energies to be highly accurate and efficient. For foQ-i3CCSD(T)-MP2/TZ we get a mean error of 0.34 kJ/mol and a standard deviation of 0.39 kJ/mol.
conSSert: Consensus SVM Model for Accurate Prediction of Ordered Secondary Structure.
Kieslich, Chris A; Smadbeck, James; Khoury, George A; Floudas, Christodoulos A
2016-03-28
Accurate prediction of protein secondary structure remains a crucial step in most approaches to the protein-folding problem, yet the prediction of ordered secondary structure, specifically beta-strands, remains a challenge. We developed a consensus secondary structure prediction method, conSSert, which is based on support vector machines (SVM) and provides exceptional accuracy for the prediction of beta-strands with QE accuracy of over 0.82 and a Q2-EH of 0.86. conSSert uses as input probabilities for the three types of secondary structure (helix, strand, and coil) that are predicted by four top performing methods: PSSpred, PSIPRED, SPINE-X, and RAPTOR. conSSert was trained/tested using 4261 protein chains from PDBSelect25, and 8632 chains from PISCES. Further validation was performed using targets from CASP9, CASP10, and CASP11. Our data suggest that poor performance in strand prediction is likely a result of training bias and not solely due to the nonlocal nature of beta-sheet contacts. conSSert is freely available for noncommercial use as a webservice: http://ares.tamu.edu/conSSert/ . PMID:26928531
A new geometric-based model to accurately estimate arm and leg inertial estimates.
Wicke, Jason; Dumas, Geneviève A
2014-06-01
Segment estimates of mass, center of mass and moment of inertia are required input parameters to analyze the forces and moments acting across the joints. The objectives of this study were to propose a new geometric model for limb segments, to evaluate it against criterion values obtained from DXA, and to compare its performance to five other popular models. Twenty five female and 24 male college students participated in the study. For the criterion measures, the participants underwent a whole body DXA scan, and estimates for segment mass, center of mass location, and moment of inertia (frontal plane) were directly computed from the DXA mass units. For the new model, the volume was determined from two standing frontal and sagittal photographs. Each segment was modeled as a stack of slices, the sections of which were ellipses if they are not adjoining another segment and sectioned ellipses if they were adjoining another segment (e.g. upper arm and trunk). Length of axes of the ellipses was obtained from the photographs. In addition, a sex-specific, non-uniform density function was developed for each segment. A series of anthropometric measurements were also taken by directly following the definitions provided of the different body segment models tested, and the same parameters determined for each model. Comparison of models showed that estimates from the new model were consistently closer to the DXA criterion than those from the other models, with an error of less than 5% for mass and moment of inertia and less than about 6% for center of mass location. PMID:24735506
Magnetic modeling of the Bushveld Igneous Complex
NASA Astrophysics Data System (ADS)
Webb, S. J.; Cole, J.; Letts, S. A.; Finn, C.; Torsvik, T. H.; Lee, M. D.
2009-12-01
Magnetic modeling of the 2.06 Ga Bushveld Complex presents special challenges due a variety of magnetic effects. These include strong remanence in the Main Zone and extremely high magnetic susceptibilities in the Upper Zone, which exhibit self-demagnetization. Recent palaeomagnetic results have resolved a long standing discrepancy between age data, which constrain the emplacement to within 1 million years, and older palaeomagnetic data which suggested ~50 million years for emplacement. The new palaeomagnetic results agree with the age data and present a single consistent pole, as opposed to a long polar wander path, for the Bushveld for all of the Zones and all of the limbs. These results also pass a fold test indicating the Bushveld Complex was emplaced horizontally lending support to arguments for connectivity. The magnetic signature of the Bushveld Complex provides an ideal mapping tool as the UZ has high susceptibility values and is well layered showing up as distinct anomalies on new high resolution magnetic data. However, this signature is similar to the highly magnetic BIFs found in the Transvaal and in the Witwatersrand Supergroups. Through careful mapping using new high resolution aeromagnetic data, we have been able to map the Bushveld UZ in complicated geological regions and identify a characteristic signature with well defined layers. The Main Zone, which has a more subdued magnetic signature, does have a strong remanent component and exhibits several magnetic reversals. The magnetic layers of the UZ contain layers of magnetitite with as much as 80-90% pure magnetite with large crystals (1-2 cm). While these layers are not strongly remanent, they have extremely high magnetic susceptibilities, and the self demagnetization effect must be taken into account when modeling these layers. Because the Bushveld Complex is so large, the geometry of the Earth’s magnetic field relative to the layers of the UZ Bushveld Complex changes orientation, creating
Cimpoesu, Dorin Stoleriu, Laurentiu; Stancu, Alexandru
2013-12-14
We propose a generalized Stoner-Wohlfarth (SW) type model to describe various experimentally observed angular dependencies of the switching field in non-single-domain magnetic particles. Because the nonuniform magnetic states are generally characterized by complicated spin configurations with no simple analytical description, we maintain the macrospin hypothesis and we phenomenologically include the effects of nonuniformities only in the anisotropy energy, preserving as much as possible the elegance of SW model, the concept of critical curve and its geometric interpretation. We compare the results obtained with our model with full micromagnetic simulations in order to evaluate the performance and limits of our approach.
NASA Astrophysics Data System (ADS)
Maeda, Chiaki; Tasaki, Satoko; Kirihara, Soshu
2011-05-01
Computer graphic models of bioscaffolds with four-coordinate lattice structures of solid rods in artificial bones were designed by using a computer aided design. The scaffold models composed of acryl resin with hydroxyapatite particles at 45vol. % were fabricated by using stereolithography of a computer aided manufacturing. After dewaxing and sintering heat treatment processes, the ceramics scaffold models with four-coordinate lattices and fine hydroxyapatite microstructures were obtained successfully. By using a computer aided analysis, it was found that bio-fluids could flow extensively inside the sintered scaffolds. This result shows that the lattice structures will realize appropriate bio-fluid circulations and promote regenerations of new bones.
Benchmarking of a New Finite Volume Shallow Water Code for Accurate Tsunami Modelling
NASA Astrophysics Data System (ADS)
Reis, Claudia; Clain, Stephane; Figueiredo, Jorge; Baptista, Maria Ana; Miranda, Jorge Miguel
2015-04-01
Finite volume methods used to solve the shallow-water equation with source terms receive great attention on the two last decades due to its fundamental properties: the built-in conservation property, the capacity to treat correctly discontinuities and the ability to handle complex bathymetry configurations preserving the some steady-state configuration (well-balanced scheme). Nevertheless, it is still a challenge to build an efficient numerical scheme, with very few numerical artifacts (e.g. numerical diffusion) which can be used in an operational environment, and are able to better capture the dynamics of the wet-dry interface and the physical phenomenon that occur in the inundation area. We present here a new finite volume code and benchmark it against analytical and experimental results, and we test the performance of the code in the complex topographic of the Tagus Estuary, close to Lisbon, Portugal. This work is funded by the Portugal-France research agreement, through the research project FCT-ANR/MAT-NAN/0122/2012.
NASA Astrophysics Data System (ADS)
Dale, Andy; Stolpovsky, Konstantin; Wallmann, Klaus
2016-04-01
The recycling and burial of biogenic material in the sea floor plays a key role in the regulation of ocean chemistry. Proper consideration of these processes in ocean biogeochemical models is becoming increasingly recognized as an important step in model validation and prediction. However, the rate of organic matter remineralization in sediments and the benthic flux of redox-sensitive elements are difficult to predict a priori. In this communication, examples of empirical benthic flux models that can be coupled to earth system models to predict sediment-water exchange in the open ocean are presented. Large uncertainties hindering further progress in this field include knowledge of the reactivity of organic carbon reaching the sediment, the importance of episodic variability in bottom water chemistry and particle rain rates (for both the deep-sea and margins) and the role of benthic fauna. How do we meet the challenge?
A model for the accurate computation of the lateral scattering of protons in water.
Bellinzona, E V; Ciocca, M; Embriaco, A; Ferrari, A; Fontana, A; Mairani, A; Parodi, K; Rotondi, A; Sala, P; Tessonnier, T
2016-02-21
A pencil beam model for the calculation of the lateral scattering in water of protons for any therapeutic energy and depth is presented. It is based on the full Molière theory, taking into account the energy loss and the effects of mixtures and compounds. Concerning the electromagnetic part, the model has no free parameters and is in very good agreement with the FLUKA Monte Carlo (MC) code. The effects of the nuclear interactions are parametrized with a two-parameter tail function, adjusted on MC data calculated with FLUKA. The model, after the convolution with the beam and the detector response, is in agreement with recent proton data in water from HIT. The model gives results with the same accuracy of the MC codes based on Molière theory, with a much shorter computing time. PMID:26808380
A model for the accurate computation of the lateral scattering of protons in water
NASA Astrophysics Data System (ADS)
Bellinzona, E. V.; Ciocca, M.; Embriaco, A.; Ferrari, A.; Fontana, A.; Mairani, A.; Parodi, K.; Rotondi, A.; Sala, P.; Tessonnier, T.
2016-02-01
A pencil beam model for the calculation of the lateral scattering in water of protons for any therapeutic energy and depth is presented. It is based on the full Molière theory, taking into account the energy loss and the effects of mixtures and compounds. Concerning the electromagnetic part, the model has no free parameters and is in very good agreement with the FLUKA Monte Carlo (MC) code. The effects of the nuclear interactions are parametrized with a two-parameter tail function, adjusted on MC data calculated with FLUKA. The model, after the convolution with the beam and the detector response, is in agreement with recent proton data in water from HIT. The model gives results with the same accuracy of the MC codes based on Molière theory, with a much shorter computing time.
Xu, Xuemiao; Zhang, Huaidong; Han, Guoqiang; Kwan, Kin Chung; Pang, Wai-Man; Fang, Jiaming; Zhao, Gansen
2016-01-01
Exterior orientation parameters’ (EOP) estimation using space resection plays an important role in topographic reconstruction for push broom scanners. However, existing models of space resection are highly sensitive to errors in data. Unfortunately, for lunar imagery, the altitude data at the ground control points (GCPs) for space resection are error-prone. Thus, existing models fail to produce reliable EOPs. Motivated by a finding that for push broom scanners, angular rotations of EOPs can be estimated independent of the altitude data and only involving the geographic data at the GCPs, which are already provided, hence, we divide the modeling of space resection into two phases. Firstly, we estimate the angular rotations based on the reliable geographic data using our proposed mathematical model. Then, with the accurate angular rotations, the collinear equations for space resection are simplified into a linear problem, and the global optimal solution for the spatial position of EOPs can always be achieved. Moreover, a certainty term is integrated to penalize the unreliable altitude data for increasing the error tolerance. Experimental results evidence that our model can obtain more accurate EOPs and topographic maps not only for the simulated data, but also for the real data from Chang’E-1, compared to the existing space resection model. PMID:27077855
Wang, Mingyu; Han, Lijuan; Liu, Shasha; Zhao, Xuebing; Yang, Jinghua; Loh, Soh Kheang; Sun, Xiaomin; Zhang, Chenxi; Fang, Xu
2015-09-01
Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed. PMID:26121186
Xu, Xuemiao; Zhang, Huaidong; Han, Guoqiang; Kwan, Kin Chung; Pang, Wai-Man; Fang, Jiaming; Zhao, Gansen
2016-01-01
Exterior orientation parameters' (EOP) estimation using space resection plays an important role in topographic reconstruction for push broom scanners. However, existing models of space resection are highly sensitive to errors in data. Unfortunately, for lunar imagery, the altitude data at the ground control points (GCPs) for space resection are error-prone. Thus, existing models fail to produce reliable EOPs. Motivated by a finding that for push broom scanners, angular rotations of EOPs can be estimated independent of the altitude data and only involving the geographic data at the GCPs, which are already provided, hence, we divide the modeling of space resection into two phases. Firstly, we estimate the angular rotations based on the reliable geographic data using our proposed mathematical model. Then, with the accurate angular rotations, the collinear equations for space resection are simplified into a linear problem, and the global optimal solution for the spatial position of EOPs can always be achieved. Moreover, a certainty term is integrated to penalize the unreliable altitude data for increasing the error tolerance. Experimental results evidence that our model can obtain more accurate EOPs and topographic maps not only for the simulated data, but also for the real data from Chang'E-1, compared to the existing space resection model. PMID:27077855
Berger, Perrine; Alouini, Mehdi; Bourderionnet, Jérôme; Bretenaker, Fabien; Dolfi, Daniel
2010-01-18
We developed an improved model in order to predict the RF behavior and the slow light properties of the SOA valid for any experimental conditions. It takes into account the dynamic saturation of the SOA, which can be fully characterized by a simple measurement, and only relies on material fitting parameters, independent of the optical intensity and the injected current. The present model is validated by showing a good agreement with experiments for small and large modulation indices. PMID:20173888
Heuijerjans, Ashley; Matikainen, Marko K.; Julkunen, Petro; Eliasson, Pernilla; Aspenberg, Per; Isaksson, Hanna
2015-01-01
Background Computational models of Achilles tendons can help understanding how healthy tendons are affected by repetitive loading and how the different tissue constituents contribute to the tendon’s biomechanical response. However, available models of Achilles tendon are limited in their description of the hierarchical multi-structural composition of the tissue. This study hypothesised that a poroviscoelastic fibre-reinforced model, previously successful in capturing cartilage biomechanical behaviour, can depict the biomechanical behaviour of the rat Achilles tendon found experimentally. Materials and Methods We developed a new material model of the Achilles tendon, which considers the tendon’s main constituents namely: water, proteoglycan matrix and collagen fibres. A hyperelastic formulation of the proteoglycan matrix enabled computations of large deformations of the tendon, and collagen fibres were modelled as viscoelastic. Specimen-specific finite element models were created of 9 rat Achilles tendons from an animal experiment and simulations were carried out following a repetitive tensile loading protocol. The material model parameters were calibrated against data from the rats by minimising the root mean squared error (RMS) between experimental force data and model output. Results and Conclusions All specimen models were successfully fitted to experimental data with high accuracy (RMS 0.42-1.02). Additional simulations predicted more compliant and soft tendon behaviour at reduced strain-rates compared to higher strain-rates that produce a stiff and brittle tendon response. Stress-relaxation simulations exhibited strain-dependent stress-relaxation behaviour where larger strains produced slower relaxation rates compared to smaller strain levels. Our simulations showed that the collagen fibres in the Achilles tendon are the main load-bearing component during tensile loading, where the orientation of the collagen fibres plays an important role for the tendon
NASA Astrophysics Data System (ADS)
O'Brien, Edward P.; Morrison, Greg; Brooks, Bernard R.; Thirumalai, D.
2009-03-01
Single molecule Förster resonance energy transfer (FRET) experiments are used to infer the properties of the denatured state ensemble (DSE) of proteins. From the measured average FRET efficiency, ⟨E⟩, the distance distribution P(R ) is inferred by assuming that the DSE can be described as a polymer. The single parameter in the appropriate polymer model (Gaussian chain, wormlike chain, or self-avoiding walk) for P(R ) is determined by equating the calculated and measured ⟨E⟩. In order to assess the accuracy of this "standard procedure," we consider the generalized Rouse model (GRM), whose properties [⟨E⟩ and P(R )] can be analytically computed, and the Molecular Transfer Model for protein L for which accurate simulations can be carried out as a function of guanadinium hydrochloride (GdmCl) concentration. Using the precisely computed ⟨E⟩ for the GRM and protein L, we infer P(R ) using the standard procedure. We find that the mean end-to-end distance can be accurately inferred (less than 10% relative error) using ⟨E⟩ and polymer models for P(R ). However, the value extracted for the radius of gyration (Rg) and the persistence length (lp) are less accurate. For protein L, the errors in the inferred properties increase as the GdmCl concentration increases for all polymer models. The relative error in the inferred Rg and lp, with respect to the exact values, can be as large as 25% at the highest GdmCl concentration. We propose a self-consistency test, requiring measurements of ⟨E⟩ by attaching dyes to different residues in the protein, to assess the validity of describing DSE using the Gaussian model. Application of the self-consistency test to the GRM shows that even for this simple model, which exhibits an order→disorder transition, the Gaussian P(R ) is inadequate. Analysis of experimental data of FRET efficiencies with dyes at several locations for the cold shock protein, and simulations results for protein L, for which accurate FRET
NASA Astrophysics Data System (ADS)
Klostermann, U. K.; Mülders, T.; Schmöller, T.; Lorusso, G. F.; Hendrickx, E.
2010-04-01
In this paper, we discuss the performance of EUV resist models in terms of predictive accuracy, and we assess the readiness of the corresponding model calibration methodology. The study is done on an extensive OPC data set collected at IMEC for the ShinEtsu resist SEVR-59 on the ASML EUV Alpha Demo Tool (ADT), with the data set including more than thousand CD values. We address practical aspects such as the speed of calibration and selection of calibration patterns. The model is calibrated on 12 process window data series varying in pattern width (32, 36, 40 nm), orientation (H, V) and pitch (dense, isolated). The minimum measured feature size at nominal process condition is a 32 nm CD at a dense pitch of 64 nm. Mask metrology is applied to verify and eventually correct nominal width of the drawn CD. Cross-sectional SEM information is included in the calibration to tune the simulated resist loss and sidewall angle. The achieved calibration RMS is ~ 1.0 nm. We show what elements are important to obtain a well calibrated model. We discuss the impact of 3D mask effects on the Bossung tilt. We demonstrate that a correct representation of the flare level during the calibration is important to achieve a high predictability at various flare conditions. Although the model calibration is performed on a limited subset of the measurement data (one dimensional structures only), its accuracy is validated based on a large number of OPC patterns (at nominal dose and focus conditions) not included in the calibration; validation RMS results as small as 1 nm can be reached. Furthermore, we study the model's extendibility to two-dimensional end of line (EOL) structures. Finally, we correlate the experimentally observed fingerprint of the CD uniformity to a model, where EUV tool specific signatures are taken into account.
Hewitt, Nicola J; Edwards, Robert J; Fritsche, Ellen; Goebel, Carsten; Aeby, Pierre; Scheel, Julia; Reisinger, Kerstin; Ouédraogo, Gladys; Duche, Daniel; Eilstein, Joan; Latil, Alain; Kenny, Julia; Moore, Claire; Kuehnl, Jochen; Barroso, Joao; Fautz, Rolf; Pfuhler, Stefan
2013-06-01
Several human skin models employing primary cells and immortalized cell lines used as monocultures or combined to produce reconstituted 3D skin constructs have been developed. Furthermore, these models have been included in European genotoxicity and sensitization/irritation assay validation projects. In order to help interpret data, Cosmetics Europe (formerly COLIPA) facilitated research projects that measured a variety of defined phase I and II enzyme activities and created a complete proteomic profile of xenobiotic metabolizing enzymes (XMEs) in native human skin and compared them with data obtained from a number of in vitro models of human skin. Here, we have summarized our findings on the current knowledge of the metabolic capacity of native human skin and in vitro models and made an overall assessment of the metabolic capacity from gene expression, proteomic expression, and substrate metabolism data. The known low expression and function of phase I enzymes in native whole skin were reflected in the in vitro models. Some XMEs in whole skin were not detected in in vitro models and vice versa, and some major hepatic XMEs such as cytochrome P450-monooxygenases were absent or measured only at very low levels in the skin. Conversely, despite varying mRNA and protein levels of phase II enzymes, functional activity of glutathione S-transferases, N-acetyltransferase 1, and UDP-glucuronosyltransferases were all readily measurable in whole skin and in vitro skin models at activity levels similar to those measured in the liver. These projects have enabled a better understanding of the contribution of XMEs to toxicity endpoints. PMID:23539547
Structured analysis and modeling of complex systems
NASA Technical Reports Server (NTRS)
Strome, David R.; Dalrymple, Mathieu A.
1992-01-01
The Aircrew Evaluation Sustained Operations Performance (AESOP) facility at Brooks AFB, Texas, combines the realism of an operational environment with the control of a research laboratory. In recent studies we collected extensive data from the Airborne Warning and Control Systems (AWACS) Weapons Directors subjected to high and low workload Defensive Counter Air Scenarios. A critical and complex task in this environment involves committing a friendly fighter against a hostile fighter. Structured Analysis and Design techniques and computer modeling systems were applied to this task as tools for analyzing subject performance and workload. This technology is being transferred to the Man-Systems Division of NASA Johnson Space Center for application to complex mission related tasks, such as manipulating the Shuttle grappler arm.
Pantuzzo, Fernando L; Silva, Julio César J; Ciminelli, Virginia S T
2009-09-15
A fast and accurate microwave-assisted digestion method for arsenic determination by flame atomic absorption spectrometry (FAAS) in typical, complex residues from gold mining is presented. Three digestion methods were evaluated: an open vessel digestion using a mixture of HCl:HNO(3):HF acids (Method A) and two microwave digestion methods using a mixture of HCl:H(2)O(2):HNO(3) in high (Method B) and medium-pressure (Method C) vessels. The matrix effect was also investigated. Arsenic concentration from external and standard addition calibration curves (at a 95% confidence level) were statistically equal (p-value=0.122) using microwave digestion in high-pressure vessel. The results from the open vessel digestion were statistically different (p-value=0.007) whereas in the microwave digestion in medium-pressure vessel (Method C) the dissolution of the samples was incomplete. PMID:19345010
Toward Accurate Modeling of the Effect of Ion-Pair Formation on Solute Redox Potential.
Qu, Xiaohui; Persson, Kristin A
2016-09-13
A scheme to model the dependence of a solute redox potential on the supporting electrolyte is proposed, and the results are compared to experimental observations and other reported theoretical models. An improved agreement with experiment is exhibited if the effect of the supporting electrolyte on the redox potential is modeled through a concentration change induced via ion pair formation with the salt, rather than by only considering the direct impact on the redox potential of the solute itself. To exemplify the approach, the scheme is applied to the concentration-dependent redox potential of select molecules proposed for nonaqueous flow batteries. However, the methodology is general and enables rational computational electrolyte design through tuning of the operating window of electrochemical systems by shifting the redox potential of its solutes; including potentially both salts as well as redox active molecules. PMID:27500744
The Intermediate Complexity Atmospheric Research Model
NASA Astrophysics Data System (ADS)
Gutmann, Ethan; Clark, Martyn; Rasmussen, Roy; Arnold, Jeffrey; Brekke, Levi
2015-04-01
The high-resolution, non-hydrostatic atmospheric models often used for dynamical downscaling are extremely computationally expensive, and, for a certain class of problems, their complexity hinders our ability to ask key scientific questions, particularly those related to hydrology and climate change. For changes in precipitation in particular, an atmospheric model grid spacing capable of resolving the structure of mountain ranges is of critical importance, yet such simulations can not currently be performed with an advanced regional climate model for long time periods, over large areas, and forced by many climate models. Here we present the newly developed Intermediate Complexity Atmospheric Research model (ICAR) capable of simulating critical atmospheric processes two to three orders of magnitude faster than a state of the art regional climate model. ICAR uses a simplified dynamical formulation based off of linear theory, combined with the circulation field from a low-resolution climate model. The resulting three-dimensional wind field is used to advect heat and moisture within the domain, while sub-grid physics (e.g. microphysics) are processed by standard and simplified physics schemes from the Weather Research and Forecasting (WRF) model. ICAR is tested in comparison to WRF by downscaling a climate change scenario over the Colorado Rockies. Both atmospheric models predict increases in precipitation across the domain with a greater increase on the western half. In contrast, statistically downscaled precipitation using multiple common statistical methods predict decreases in precipitation over the western half of the domain. Finally, we apply ICAR to multiple CMIP5 climate models and scenarios with multiple parameterization options to investigate the importance of uncertainty in sub-grid physics as compared to the uncertainty in the large scale climate scenario. ICAR is a useful tool for climate change and weather forecast downscaling, particularly for orographic
Pino, Francisco; Roé, Nuria; Aguiar, Pablo; Falcon, Carles; Ros, Domènec; Pavía, Javier
2015-02-15
Purpose: Single photon emission computed tomography (SPECT) has become an important noninvasive imaging technique in small-animal research. Due to the high resolution required in small-animal SPECT systems, the spatially variant system response needs to be included in the reconstruction algorithm. Accurate modeling of the system response should result in a major improvement in the quality of reconstructed images. The aim of this study was to quantitatively assess the impact that an accurate modeling of spatially variant collimator/detector response has on image-quality parameters, using a low magnification SPECT system equipped with a pinhole collimator and a small gamma camera. Methods: Three methods were used to model the point spread function (PSF). For the first, only the geometrical pinhole aperture was included in the PSF. For the second, the septal penetration through the pinhole collimator was added. In the third method, the measured intrinsic detector response was incorporated. Tomographic spatial resolution was evaluated and contrast, recovery coefficients, contrast-to-noise ratio, and noise were quantified using a custom-built NEMA NU 4–2008 image-quality phantom. Results: A high correlation was found between the experimental data corresponding to intrinsic detector response and the fitted values obtained by means of an asymmetric Gaussian distribution. For all PSF models, resolution improved as the distance from the point source to the center of the field of view increased and when the acquisition radius diminished. An improvement of resolution was observed after a minimum of five iterations when the PSF modeling included more corrections. Contrast, recovery coefficients, and contrast-to-noise ratio were better for the same level of noise in the image when more accurate models were included. Ring-type artifacts were observed when the number of iterations exceeded 12. Conclusions: Accurate modeling of the PSF improves resolution, contrast, and recovery
ERIC Educational Resources Information Center
Vladescu, Jason C.; Carroll, Regina; Paden, Amber; Kodak, Tiffany M.
2012-01-01
The present study replicates and extends previous research on the use of video modeling (VM) with voiceover instruction to train staff to implement discrete-trial instruction (DTI). After staff trainees reached the mastery criterion when teaching an adult confederate with VM, they taught a child with a developmental disability using DTI. The…
NASA Technical Reports Server (NTRS)
Ellison, Donald; Conway, Bruce; Englander, Jacob
2015-01-01
A significant body of work exists showing that providing a nonlinear programming (NLP) solver with expressions for the problem constraint gradient substantially increases the speed of program execution and can also improve the robustness of convergence, especially for local optimizers. Calculation of these derivatives is often accomplished through the computation of spacecraft's state transition matrix (STM). If the two-body gravitational model is employed as is often done in the context of preliminary design, closed form expressions for these derivatives may be provided. If a high fidelity dynamics model, that might include perturbing forces such as the gravitational effect from multiple third bodies and solar radiation pressure is used then these STM's must be computed numerically. We present a method for the power hardward model and a full ephemeris model. An adaptive-step embedded eight order Dormand-Prince numerical integrator is discussed and a method for the computation of the time of flight derivatives in this framework is presented. The use of these numerically calculated derivatieves offer a substantial improvement over finite differencing in the context of a global optimizer. Specifically the inclusion of these STM's into the low thrust missiondesign tool chain in use at NASA Goddard Spaceflight Center allows for an increased preliminary mission design cadence.
Developing an Accurate CFD Based Gust Model for the Truss Braced Wing Aircraft
NASA Technical Reports Server (NTRS)
Bartels, Robert E.
2013-01-01
The increased flexibility of long endurance aircraft having high aspect ratio wings necessitates attention to gust response and perhaps the incorporation of gust load alleviation. The design of civil transport aircraft with a strut or truss-braced high aspect ratio wing furthermore requires gust response analysis in the transonic cruise range. This requirement motivates the use of high fidelity nonlinear computational fluid dynamics (CFD) for gust response analysis. This paper presents the development of a CFD based gust model for the truss braced wing aircraft. A sharp-edged gust provides the gust system identification. The result of the system identification is several thousand time steps of instantaneous pressure coefficients over the entire vehicle. This data is filtered and downsampled to provide the snapshot data set from which a reduced order model is developed. A stochastic singular value decomposition algorithm is used to obtain a proper orthogonal decomposition (POD). The POD model is combined with a convolution integral to predict the time varying pressure coefficient distribution due to a novel gust profile. Finally the unsteady surface pressure response of the truss braced wing vehicle to a one-minus-cosine gust, simulated using the reduced order model, is compared with the full CFD.
Accurate prediction of the refractive index of polymers using first principles and data modeling
NASA Astrophysics Data System (ADS)
Afzal, Mohammad Atif Faiz; Cheng, Chong; Hachmann, Johannes
Organic polymers with a high refractive index (RI) have recently attracted considerable interest due to their potential application in optical and optoelectronic devices. The ability to tailor the molecular structure of polymers is the key to increasing the accessible RI values. Our work concerns the creation of predictive in silico models for the optical properties of organic polymers, the screening of large-scale candidate libraries, and the mining of the resulting data to extract the underlying design principles that govern their performance. This work was set up to guide our experimentalist partners and allow them to target the most promising candidates. Our model is based on the Lorentz-Lorenz equation and thus includes the polarizability and number density values for each candidate. For the former, we performed a detailed benchmark study of different density functionals, basis sets, and the extrapolation scheme towards the polymer limit. For the number density we devised an exceedingly efficient machine learning approach to correlate the polymer structure and the packing fraction in the bulk material. We validated the proposed RI model against the experimentally known RI values of 112 polymers. We could show that the proposed combination of physical and data modeling is both successful and highly economical to characterize a wide range of organic polymers, which is a prerequisite for virtual high-throughput screening.
Chon, K H; Cohen, R J; Holstein-Rathlou, N H
1997-01-01
A linear and nonlinear autoregressive moving average (ARMA) identification algorithm is developed for modeling time series data. The algorithm uses Laguerre expansion of kernals (LEK) to estimate Volterra-Wiener kernals. However, instead of estimating linear and nonlinear system dynamics via moving average models, as is the case for the Volterra-Wiener analysis, we propose an ARMA model-based approach. The proposed algorithm is essentially the same as LEK, but this algorithm is extended to include past values of the output as well. Thus, all of the advantages associated with using the Laguerre function remain with our algorithm; but, by extending the algorithm to the linear and nonlinear ARMA model, a significant reduction in the number of Laguerre functions can be made, compared with the Volterra-Wiener approach. This translates into a more compact system representation and makes the physiological interpretation of higher order kernels easier. Furthermore, simulation results show better performance of the proposed approach in estimating the system dynamics than LEK in certain cases, and it remains effective in the presence of significant additive measurement noise. PMID:9236985
Sapsis, Themistoklis P; Majda, Andrew J
2013-08-20
A framework for low-order predictive statistical modeling and uncertainty quantification in turbulent dynamical systems is developed here. These reduced-order, modified quasilinear Gaussian (ROMQG) algorithms apply to turbulent dynamical systems in which there is significant linear instability or linear nonnormal dynamics in the unperturbed system and energy-conserving nonlinear interactions that transfer energy from the unstable modes to the stable modes where dissipation occurs, resulting in a statistical steady state; such turbulent dynamical systems are ubiquitous in geophysical and engineering turbulence. The ROMQG method involves constructing a low-order, nonlinear, dynamical system for the mean and covariance statistics in the reduced subspace that has the unperturbed statistics as a stable fixed point and optimally incorporates the indirect effect of non-Gaussian third-order statistics for the unperturbed system in a systematic calibration stage. This calibration procedure is achieved through information involving only the mean and covariance statistics for the unperturbed equilibrium. The performance of the ROMQG algorithm is assessed on two stringent test cases: the 40-mode Lorenz 96 model mimicking midlatitude atmospheric turbulence and two-layer baroclinic models for high-latitude ocean turbulence with over 125,000 degrees of freedom. In the Lorenz 96 model, the ROMQG algorithm with just a single mode captures the transient response to random or deterministic forcing. For the baroclinic ocean turbulence models, the inexpensive ROMQG algorithm with 252 modes, less than 0.2% of the total, captures the nonlinear response of the energy, the heat flux, and even the one-dimensional energy and heat flux spectra. PMID:23918398
Modeling the human prothrombinase complex components
NASA Astrophysics Data System (ADS)
Orban, Tivadar
Thrombin generation is the culminating stage of the blood coagulation process. Thrombin is obtained from prothrombin (the substrate) in a reaction catalyzed by the prothrombinase complex (the enzyme). The prothrombinase complex is composed of factor Xa (the enzyme), factor Va (the cofactor) associated in the presence of calcium ions on a negatively charged cell membrane. Factor Xa, alone, can activate prothrombin to thrombin; however, the rate of conversion is not physiologically relevant for survival. Incorporation of factor Va into prothrombinase accelerates the rate of prothrombinase activity by 300,000-fold, and provides the physiological pathway of thrombin generation. The long-term goal of the current proposal is to provide the necessary support for the advancing of studies to design potential drug candidates that may be used to avoid development of deep venous thrombosis in high-risk patients. The short-term goals of the present proposal are to (1) to propose a model of a mixed asymmetric phospholipid bilayer, (2) expand the incomplete model of human coagulation factor Va and study its interaction with the phospholipid bilayer, (3) to create a homology model of prothrombin (4) to study the dynamics of interaction between prothrombin and the phospholipid bilayer.
Yu, Victoria Y.; Tran, Angelia; Nguyen, Dan; Cao, Minsong; Ruan, Dan; Low, Daniel A.; Sheng, Ke
2015-11-15
Purpose: Significant dosimetric benefits had been previously demonstrated in highly noncoplanar treatment plans. In this study, the authors developed and verified an individualized collision model for the purpose of delivering highly noncoplanar radiotherapy and tested the feasibility of total delivery automation with Varian TrueBeam developer mode. Methods: A hand-held 3D scanner was used to capture the surfaces of an anthropomorphic phantom and a human subject, which were positioned with a computer-aided design model of a TrueBeam machine to create a detailed virtual geometrical collision model. The collision model included gantry, collimator, and couch motion degrees of freedom. The accuracy of the 3D scanner was validated by scanning a rigid cubical phantom with known dimensions. The collision model was then validated by generating 300 linear accelerator orientations corresponding to 300 gantry-to-couch and gantry-to-phantom distances, and comparing the corresponding distance measurements to their corresponding models. The linear accelerator orientations reflected uniformly sampled noncoplanar beam angles to the head, lung, and prostate. The distance discrepancies between measurements on the physical and virtual systems were used to estimate treatment-site-specific safety buffer distances with 0.1%, 0.01%, and 0.001% probability of collision between the gantry and couch or phantom. Plans containing 20 noncoplanar beams to the brain, lung, and prostate optimized via an in-house noncoplanar radiotherapy platform were converted into XML script for automated delivery and the entire delivery was recorded and timed to demonstrate the feasibility of automated delivery. Results: The 3D scanner measured the dimension of the 14 cm cubic phantom within 0.5 mm. The maximal absolute discrepancy between machine and model measurements for gantry-to-couch and gantry-to-phantom was 0.95 and 2.97 cm, respectively. The reduced accuracy of gantry-to-phantom measurements was
Are satellite based rainfall estimates accurate enough for crop modelling under Sahelian climate?
NASA Astrophysics Data System (ADS)
Ramarohetra, J.; Sultan, B.
2012-04-01
Agriculture is considered as the most climate dependant human activity. In West Africa and especially in the sudano-sahelian zone, rain-fed agriculture - that represents 93% of cultivated areas and is the means of support of 70% of the active population - is highly vulnerable to precipitation variability. To better understand and anticipate climate impacts on agriculture, crop models - that estimate crop yield from climate information (e.g rainfall, temperature, insolation, humidity) - have been developed. These crop models are useful (i) in ex ante analysis to quantify the impact of different strategies implementation - crop management (e.g. choice of varieties, sowing date), crop insurance or medium-range weather forecast - on yields, (ii) for early warning systems and to (iii) assess future food security. Yet, the successful application of these models depends on the accuracy of their climatic drivers. In the sudano-sahelian zone , the quality of precipitation estimations is then a key factor to understand and anticipate climate impacts on agriculture via crop modelling and yield estimations. Different kinds of precipitation estimations can be used. Ground measurements have long-time series but an insufficient network density, a large proportion of missing values, delay in reporting time, and they have limited availability. An answer to these shortcomings may lie in the field of remote sensing that provides satellite-based precipitation estimations. However, satellite-based rainfall estimates (SRFE) are not a direct measurement but rather an estimation of precipitation. Used as an input for crop models, it determines the performance of the simulated yield, hence SRFE require validation. The SARRAH crop model is used to model three different varieties of pearl millet (HKP, MTDO, Souna3) in a square degree centred on 13.5°N and 2.5°E, in Niger. Eight satellite-based rainfall daily products (PERSIANN, CMORPH, TRMM 3b42-RT, GSMAP MKV+, GPCP, TRMM 3b42v6, RFEv2 and
NASA Astrophysics Data System (ADS)
Yahja, A.; Kim, C.; Lin, Y.; Bajcsy, P.
2008-12-01
This paper addresses the problem of accurate estimation of geospatial models from a set of groundwater recharge & discharge (R&D) maps and from auxiliary remote sensing and terrestrial raster measurements. The motivation for our work is driven by the cost of field measurements, and by the limitations of currently available physics-based modeling techniques that do not include all relevant variables and allow accurate predictions only at coarse spatial scales. The goal is to improve our understanding of the underlying physical phenomena and increase the accuracy of geospatial models--with a combination of remote sensing, field measurements and physics-based modeling. Our approach is to process a set of R&D maps generated from interpolated sparse field measurements using existing physics-based models, and identify the R&D map that would be the most suitable for extracting a set of rules between the auxiliary variables of interest and the R&D map labels. We implemented this approach by ranking R&D maps using information entropy and mutual information criteria, and then by deriving a set of rules using a machine learning technique, such as the decision tree method. The novelty of our work is in developing a general framework for building geospatial models with the ultimate goal of minimizing cost and maximizing model accuracy. The framework is demonstrated for groundwater R&D rate models but could be applied to other similar studies, for instance, to understanding hypoxia based on physics-based models and remotely sensed variables. Furthermore, our key contribution is in designing a ranking method for R&D maps that allows us to analyze multiple plausible R&D maps with a different number of zones which was not possible in our earlier prototype of the framework called Spatial Pattern to Learn. We will present experimental results using examples R&D and other maps from an area in Wisconsin.
Faster and more accurate graphical model identification of tandem mass spectra using trellises
Wang, Shengjie; Halloran, John T.; Bilmes, Jeff A.; Noble, William S.
2016-01-01
Tandem mass spectrometry (MS/MS) is the dominant high throughput technology for identifying and quantifying proteins in complex biological samples. Analysis of the tens of thousands of fragmentation spectra produced by an MS/MS experiment begins by assigning to each observed spectrum the peptide that is hypothesized to be responsible for generating the spectrum. This assignment is typically done by searching each spectrum against a database of peptides. To our knowledge, all existing MS/MS search engines compute scores individually between a given observed spectrum and each possible candidate peptide from the database. In this work, we use a trellis, a data structure capable of jointly representing a large set of candidate peptides, to avoid redundantly recomputing common sub-computations among different candidates. We show how trellises may be used to significantly speed up existing scoring algorithms, and we theoretically quantify the expected speedup afforded by trellises. Furthermore, we demonstrate that compact trellis representations of whole sets of peptides enables efficient discriminative learning of a dynamic Bayesian network for spectrum identification, leading to greatly improved spectrum identification accuracy. Contact: bilmes@uw.edu or william-noble@uw.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307634
An accurate two-phase approximate solution to the acute viral infection model
Perelson, Alan S
2009-01-01
During an acute viral infection, virus levels rise, reach a peak and then decline. Data and numerical solutions suggest the growth and decay phases are linear on a log scale. While viral dynamic models are typically nonlinear with analytical solutions difficult to obtain, the exponential nature of the solutions suggests approximations can be found. We derive a two-phase approximate solution to the target cell limited influenza model and illustrate the accuracy using data and previously established parameter values of six patients infected with influenza A. For one patient, the subsequent fall in virus concentration was not consistent with our predictions during the decay phase and an alternate approximation is derived. We find expressions for the rate and length of initial viral growth in terms of the parameters, the extent each parameter is involved in viral peaks, and the single parameter responsible for virus decay. We discuss applications of this analysis in antiviral treatments and investigating host and virus heterogeneities.
Features of creation of highly accurate models of triumphal pylons for archaeological reconstruction
NASA Astrophysics Data System (ADS)
Grishkanich, A. S.; Sidorov, I. S.; Redka, D. N.
2015-12-01
Cited a measuring operation for determining the geometric characteristics of objects in space and geodetic survey objects on the ground. In the course of the work, data were obtained on a relative positioning of the pylons in space. There are deviations from verticality. In comparison with traditional surveying this testing method is preferable because it allows you to get in semi-automated mode, the CAD model of the object is high for subsequent analysis that is more economical-ly advantageous.
NASA Astrophysics Data System (ADS)
Naumenko, Mikhail; Guzivaty, Vadim; Sapelko, Tatiana
2016-04-01
Lake morphometry refers to physical factors (shape, size, structure, etc) that determine the lake depression. Morphology has a great influence on lake ecological characteristics especially on water thermal conditions and mixing depth. Depth analyses, including sediment measurement at various depths, volumes of strata and shoreline characteristics are often critical to the investigation of biological, chemical and physical properties of fresh waters as well as theoretical retention time. Management techniques such as loading capacity for effluents and selective removal of undesirable components of the biota are also dependent on detailed knowledge of the morphometry and flow characteristics. During the recent years a lake bathymetric surveys were carried out by using echo sounder with a high bottom depth resolution and GPS coordinate determination. Few digital bathymetric models have been created with 10*10 m spatial grid for some small lakes of Russian Plain which the areas not exceed 1-2 sq. km. The statistical characteristics of the depth and slopes distribution of these lakes calculated on an equidistant grid. It will provide the level-surface-volume variations of small lakes and reservoirs, calculated through combination of various satellite images. We discuss the methodological aspects of creating of morphometric models of depths and slopes of small lakes as well as the advantages of digital models over traditional methods.
Robust and Accurate Modeling Approaches for Migraine Per-Patient Prediction from Ambulatory Data.
Pagán, Josué; De Orbe, M Irene; Gago, Ana; Sobrado, Mónica; Risco-Martín, José L; Mora, J Vivancos; Moya, José M; Ayala, José L
2015-01-01
Migraine is one of the most wide-spread neurological disorders, and its medical treatment represents a high percentage of the costs of health systems. In some patients, characteristic symptoms that precede the headache appear. However, they are nonspecific, and their prediction horizon is unknown and pretty variable; hence, these symptoms are almost useless for prediction, and they are not useful to advance the intake of drugs to be effective and neutralize the pain. To solve this problem, this paper sets up a realistic monitoring scenario where hemodynamic variables from real patients are monitored in ambulatory conditions with a wireless body sensor network (WBSN). The acquired data are used to evaluate the predictive capabilities and robustness against noise and failures in sensors of several modeling approaches. The obtained results encourage the development of per-patient models based on state-space models (N4SID) that are capable of providing average forecast windows of 47 min and a low rate of false positives. PMID:26134103
Towards a More Accurate Solar Power Forecast By Improving NWP Model Physics
NASA Astrophysics Data System (ADS)
Köhler, C.; Lee, D.; Steiner, A.; Ritter, B.
2014-12-01
The growing importance and successive expansion of renewable energies raise new challenges for decision makers, transmission system operators, scientists and many more. In this interdisciplinary field, the role of Numerical Weather Prediction (NWP) is to reduce the uncertainties associated with the large share of weather-dependent power sources. Precise power forecast, well-timed energy trading on the stock market, and electrical grid stability can be maintained. The research project EWeLiNE is a collaboration of the German Weather Service (DWD), the Fraunhofer Institute (IWES) and three German transmission system operators (TSOs). Together, wind and photovoltaic (PV) power forecasts shall be improved by combining optimized NWP and enhanced power forecast models. The conducted work focuses on the identification of critical weather situations and the associated errors in the German regional NWP model COSMO-DE. Not only the representation of the model cloud characteristics, but also special events like Sahara dust over Germany and the solar eclipse in 2015 are treated and their effect on solar power accounted for. An overview of the EWeLiNE project and results of the ongoing research will be presented.
Robust and Accurate Modeling Approaches for Migraine Per-Patient Prediction from Ambulatory Data
Pagán, Josué; Irene De Orbe, M.; Gago, Ana; Sobrado, Mónica; Risco-Martín, José L.; Vivancos Mora, J.; Moya, José M.; Ayala, José L.
2015-01-01
Migraine is one of the most wide-spread neurological disorders, and its medical treatment represents a high percentage of the costs of health systems. In some patients, characteristic symptoms that precede the headache appear. However, they are nonspecific, and their prediction horizon is unknown and pretty variable; hence, these symptoms are almost useless for prediction, and they are not useful to advance the intake of drugs to be effective and neutralize the pain. To solve this problem, this paper sets up a realistic monitoring scenario where hemodynamic variables from real patients are monitored in ambulatory conditions with a wireless body sensor network (WBSN). The acquired data are used to evaluate the predictive capabilities and robustness against noise and failures in sensors of several modeling approaches. The obtained results encourage the development of per-patient models based on state-space models (N4SID) that are capable of providing average forecast windows of 47 min and a low rate of false positives. PMID:26134103
NASA Astrophysics Data System (ADS)
Jiang, Yongfei; Zhang, Jun; Zhao, Wanhua
2015-05-01
Hemodynamics altered by stent implantation is well-known to be closely related to in-stent restenosis. Computational fluid dynamics (CFD) method has been used to investigate the hemodynamics in stented arteries in detail and help to analyze the performances of stents. In this study, blood models with Newtonian or non-Newtonian properties were numerically investigated for the hemodynamics at steady or pulsatile inlet conditions respectively employing CFD based on the finite volume method. The results showed that the blood model with non-Newtonian property decreased the area of low wall shear stress (WSS) compared with the blood model with Newtonian property and the magnitude of WSS varied with the magnitude and waveform of the inlet velocity. The study indicates that the inlet conditions and blood models are all important for accurately predicting the hemodynamics. This will be beneficial to estimate the performances of stents and also help clinicians to select the proper stents for the patients.
Accurate 3d Textured Models of Vessels for the Improvement of the Educational Tools of a Museum
NASA Astrophysics Data System (ADS)
Soile, S.; Adam, K.; Ioannidis, C.; Georgopoulos, A.
2013-02-01
Besides the demonstration of the findings, modern museums organize educational programs which aim to experience and knowledge sharing combined with entertainment rather than to pure learning. Toward that effort, 2D and 3D digital representations are gradually replacing the traditional recording of the findings through photos or drawings. The present paper refers to a project that aims to create 3D textured models of two lekythoi that are exhibited in the National Archaeological Museum of Athens in Greece; on the surfaces of these lekythoi scenes of the adventures of Odysseus are depicted. The project is expected to support the production of an educational movie and some other relevant interactive educational programs for the museum. The creation of accurate developments of the paintings and of accurate 3D models is the basis for the visualization of the adventures of the mythical hero. The data collection was made by using a structured light scanner consisting of two machine vision cameras that are used for the determination of geometry of the object, a high resolution camera for the recording of the texture, and a DLP projector. The creation of the final accurate 3D textured model is a complicated and tiring procedure which includes the collection of geometric data, the creation of the surface, the noise filtering, the merging of individual surfaces, the creation of a c-mesh, the creation of the UV map, the provision of the texture and, finally, the general processing of the 3D textured object. For a better result a combination of commercial and in-house software made for the automation of various steps of the procedure was used. The results derived from the above procedure were especially satisfactory in terms of accuracy and quality of the model. However, the procedure was proved to be time consuming while the use of various software packages presumes the services of a specialist.
Key Issues for an Accurate Modelling of GaSb TPV Converters
NASA Astrophysics Data System (ADS)
Martín, Diego; Algora, Carlos
2003-01-01
GaSb TPV devices are commonly manufactured by Zn diffusion from the vapour phase on a n-type substrate, leading to very high doping concentrations in a narrow emitter. This fact emphasizes the need of a careful modelling that must include high doping effects to simulate the optoelectronic behaviour of devices. In this work the key parameters that have strong influence on the performance of GaSb TPV devices are underlined, more reliable values are suggested and our first results on the study of the absorption coefficient dependence with p-type high doping concentration are presented.
Membrane associated complexes in calcium dynamics modelling
NASA Astrophysics Data System (ADS)
Szopa, Piotr; Dyzma, Michał; Kaźmierczak, Bogdan
2013-06-01
Mitochondria not only govern energy production, but are also involved in crucial cellular signalling processes. They are one of the most important organelles determining the Ca2+ regulatory pathway in the cell. Several mathematical models explaining these mechanisms were constructed, but only few of them describe interplay between calcium concentrations in endoplasmic reticulum (ER), cytoplasm and mitochondria. Experiments measuring calcium concentrations in mitochondria and ER suggested the existence of cytosolic microdomains with locally elevated calcium concentration in the nearest vicinity of the outer mitochondrial membrane. These intermediate physical connections between ER and mitochondria are called MAM (mitochondria-associated ER membrane) complexes. We propose a model with a direct calcium flow from ER to mitochondria, which may be justified by the existence of MAMs, and perform detailed numerical analysis of the effect of this flow on the type and shape of calcium oscillations. The model is partially based on the Marhl et al model. We have numerically found that the stable oscillations exist for a considerable set of parameter values. However, for some parameter sets the oscillations disappear and the trajectories of the model tend to a steady state with very high calcium level in mitochondria. This can be interpreted as an early step in an apoptotic pathway.
Wind modelling over complex terrain using CFD
NASA Astrophysics Data System (ADS)
Avila, Matias; Owen, Herbert; Folch, Arnau; Prieto, Luis; Cosculluela, Luis
2015-04-01
The present work deals with the numerical CFD modelling of onshore wind farms in the context of High Performance Computing (HPC). The CFD model involves the numerical solution of the Reynolds-Averaged Navier-Stokes (RANS) equations together with a κ-É turbulence model and the energy equation, specially designed for Atmospheric Boundary Layer (ABL) flows. The aim is to predict the wind velocity distribution over complex terrain, using a model that includes meteorological data assimilation, thermal coupling, forested canopy and Coriolis effects. The modelling strategy involves automatic mesh generation, terrain data assimilation and generation of boundary conditions for the inflow wind flow distribution up to the geostrophic height. The CFD model has been implemented in Alya, a HPC multi physics parallel solver able to run with thousands of processors with an optimal scalability, developed in Barcelona Supercomputing Center. The implemented thermal stability and canopy physical model was developed by Sogachev in 2012. The k-É equations are of non-linear convection diffusion reaction type. The implemented numerical scheme consists on a stabilized finite element formulation based on the variational multiscale method, that is known to be stable for this kind of turbulence equations. We present a numerical formulation that stresses on the robustness of the solution method, tackling common problems that produce instability. The iterative strategy and linearization scheme is discussed. It intends to avoid the possibility of having negative values of diffusion during the iterative process, which may lead to divergence of the scheme. These problems are addressed by acting on the coefficients of the reaction and diffusion terms and on the turbulent variables themselves. The k-É equations are highly nonlinear. Complex terrain induces transient flow instabilities that may preclude the convergence of computer flow simulations based on steady state formulation of the
Multiconjugate adaptive optics applied to an anatomically accurate human eye model.
Bedggood, P A; Ashman, R; Smith, G; Metha, A B
2006-09-01
Aberrations of both astronomical telescopes and the human eye can be successfully corrected with conventional adaptive optics. This produces diffraction-limited imagery over a limited field of view called the isoplanatic patch. A new technique, known as multiconjugate adaptive optics, has been developed recently in astronomy to increase the size of this patch. The key is to model atmospheric turbulence as several flat, discrete layers. A human eye, however, has several curved, aspheric surfaces and a gradient index lens, complicating the task of correcting aberrations over a wide field of view. Here we utilize a computer model to determine the degree to which this technology may be applied to generate high resolution, wide-field retinal images, and discuss the considerations necessary for optimal use with the eye. The Liou and Brennan schematic eye simulates the aspheric surfaces and gradient index lens of real human eyes. We show that the size of the isoplanatic patch of the human eye is significantly increased through multiconjugate adaptive optics. PMID:19529172
Accurate modeling of SiPM detectors coupled to FE electronics for timing performance analysis
NASA Astrophysics Data System (ADS)
Ciciriello, F.; Corsi, F.; Licciulli, F.; Marzocca, C.; Matarrese, G.; Del Guerra, A.; Bisogni, M. G.
2013-08-01
It has already been shown how the shape of the current pulse produced by a SiPM in response to an incident photon is sensibly affected by the characteristics of the front-end electronics (FEE) used to read out the detector. When the application requires to approach the best theoretical time performance of the detection system, the influence of all the parasitics associated to the coupling SiPM-FEE can play a relevant role and must be adequately modeled. In particular, it has been reported that the shape of the current pulse is affected by the parasitic inductance of the wiring connection between SiPM and FEE. In this contribution, we extend the validity of a previously presented SiPM model to account for the wiring inductance. Various combinations of the main performance parameters of the FEE (input resistance and bandwidth) have been simulated in order to evaluate their influence on the time accuracy of the detection system, when the time pick-off of each single event is extracted by means of a leading edge discriminator (LED) technique.
Considering mask pellicle effect for more accurate OPC model at 45nm technology node
NASA Astrophysics Data System (ADS)
Wang, Ching-Heng; Liu, Qingwei; Zhang, Liguo
2008-11-01
Now it comes to the 45nm technology node, which should be the first generation of the immersion micro-lithography. And the brand-new lithography tool makes many optical effects, which can be ignored at 90nm and 65nm nodes, now have significant impact on the pattern transmission process from design to silicon. Among all the effects, one that needs to be pay attention to is the mask pellicle effect's impact on the critical dimension variation. With the implement of hyper-NA lithography tools, light transmits the mask pellicle vertically is not a good approximation now, and the image blurring induced by the mask pellicle should be taken into account in the computational microlithography. In this works, we investigate how the mask pellicle impacts the accuracy of the OPC model. And we will show that considering the extremely tight critical dimension control spec for 45nm generation node, to take the mask pellicle effect into the OPC model now becomes necessary.
Modeling the relational complexities of symptoms.
Dolin, R H
1994-12-01
Realization of the value of reliable codified medical data is growing at a rapid rate. Symptom data in particular have been shown to be useful in decision analysis and in the determination of patient outcomes. Electronic medical record systems are emerging, and attempts are underway to define the structure and content of these systems to support the storage of all medical data. The underlying models upon which these systems are being built continue to be strengthened by a deeper understanding of the complex information they are to store. This report analyzes symptoms as they might be recorded in free text notes and presents a high-level conceptual data model representation of this domain. PMID:7869941
Inexpensive Complex Hand Model Twenty Years Later.
Frenger, Paul
2015-01-01
Twenty years ago the author unveiled his inexpensive complex hand model, which reproduced every motion of the human hand. A control system programmed in the Forth language operated its actuators and sensors. Follow-on papers for this popular project were next presented in Texas, Canada and Germany. From this hand grew the authors meter-tall robot (nicknamed ANNIE: Android With Neural Networks, Intellect and Emotions). It received machine vision, facial expressiveness, speech synthesis and speech recognition; a simian version also received a dexterous ape foot. New artificial intelligence features included op-amp neurons for OCR and simulated emotions, hormone emulation, endocannabinoid receptors, fear-trust-love mechanisms, a Grandmother Cell recognizer and artificial consciousness. Simulated illnesses included narcotic addiction, autism, PTSD, fibromyalgia and Alzheimers disease. The author gave 13 robotics-AI presentations at NASA in Houston since 2006. A meter-tall simian robot was proposed with gripping hand-feet for use with space vehicles and to explore distant planets and moons. Also proposed were: intelligent motorized exoskeletons for astronaut force multiplication; a cognitive prosthesis to detect and alleviate decreased crew mental performance; and a gynoid robot medic to tend astronauts in deep space missions. What began as a complex hand model evolved into an innovative robot-AI within two decades. PMID:25996742
Complex Educational Design: A Course Design Model Based on Complexity
ERIC Educational Resources Information Center
Freire, Maximina Maria
2013-01-01
Purpose: This article aims at presenting a conceptual framework which, theoretically grounded on complexity, provides the basis to conceive of online language courses that intend to respond to the needs of students and society. Design/methodology/approach: This paper is introduced by reflections on distance education and on the paradigmatic view…
Accurate modeling of light trapping in thin film silicon solar cells
Abouelsaood, A.A.; Ghannam, M.Y.; Poortmans, J.; Mertens, R.P.
1997-12-31
An attempt is made to assess the accuracy of the simplifying assumption of total retransmission of light inside the escape or loss cone which is made in many models of optical confinement in thin-film silicon solar cells. A closed form expression is derived for the absorption enhancement factor as a function of the refractive index in the low-absorption limit for a thin-film cell with a flat front surface and a lambertian back reflector. Numerical calculations are carried out to investigate similar systems with antireflection coatings, and the investigation of cells with a textured front surface is achieved using a modified version of the existing ray-tracing computer simulation program TEXTURE.
A microbial clock provides an accurate estimate of the postmortem interval in a mouse model system
Metcalf, Jessica L; Wegener Parfrey, Laura; Gonzalez, Antonio; Lauber, Christian L; Knights, Dan; Ackermann, Gail; Humphrey, Gregory C; Gebert, Matthew J; Van Treuren, Will; Berg-Lyons, Donna; Keepers, Kyle; Guo, Yan; Bullard, James; Fierer, Noah; Carter, David O; Knight, Rob
2013-01-01
Establishing the time since death is critical in every death investigation, yet existing techniques are susceptible to a range of errors and biases. For example, forensic entomology is widely used to assess the postmortem interval (PMI), but errors can range from days to months. Microbes may provide a novel method for estimating PMI that avoids many of these limitations. Here we show that postmortem microbial community changes are dramatic, measurable, and repeatable in a mouse model system, allowing PMI to be estimated within approximately 3 days over 48 days. Our results provide a detailed understanding of bacterial and microbial eukaryotic ecology within a decomposing corpse system and suggest that microbial community data can be developed into a forensic tool for estimating PMI. DOI: http://dx.doi.org/10.7554/eLife.01104.001 PMID:24137541
Biomechanical modeling provides more accurate data for neuronavigation than rigid registration
Garlapati, Revanth Reddy; Roy, Aditi; Joldes, Grand Roman; Wittek, Adam; Mostayed, Ahmed; Doyle, Barry; Warfield, Simon Keith; Kikinis, Ron; Knuckey, Neville; Bunt, Stuart; Miller, Karol
2015-01-01
It is possible to improve neuronavigation during image-guided surgery by warping the high-quality preoperative brain images so that they correspond with the current intraoperative configuration of the brain. In this work, the accuracy of registration results obtained using comprehensive biomechanical models is compared to the accuracy of rigid registration, the technology currently available to patients. This comparison allows us to investigate whether biomechanical modeling provides good quality image data for neuronavigation for a larger proportion of patients than rigid registration. Preoperative images for 33 cases of neurosurgery were warped onto their respective intraoperative configurations using both biomechanics-based method and rigid registration. We used a Hausdorff distance-based evaluation process that measures the difference between images to quantify the performance of both methods of registration. A statistical test for difference in proportions was conducted to evaluate the null hypothesis that the proportion of patients for whom improved neuronavigation can be achieved, is the same for rigid and biomechanics-based registration. The null hypothesis was confidently rejected (p-value<10−4). Even the modified hypothesis that less than 25% of patients would benefit from the use of biomechanics-based registration was rejected at a significance level of 5% (p-value = 0.02). The biomechanics-based method proved particularly effective for cases experiencing large craniotomy-induced brain deformations. The outcome of this analysis suggests that our nonlinear biomechanics-based methods are beneficial to a large proportion of patients and can be considered for use in the operating theatre as one possible method of improving neuronavigation and surgical outcomes. PMID:24460486
Lupaşcu, Carmen Alina; Tegolo, Domenico; Trucco, Emanuele
2013-12-01
We present an algorithm estimating the width of retinal vessels in fundus camera images. The algorithm uses a novel parametric surface model of the cross-sectional intensities of vessels, and ensembles of bagged decision trees to estimate the local width from the parameters of the best-fit surface. We report comparative tests with REVIEW, currently the public database of reference for retinal width estimation, containing 16 images with 193 annotated vessel segments and 5066 profile points annotated manually by three independent experts. Comparative tests are reported also with our own set of 378 vessel widths selected sparsely in 38 images from the Tayside Scotland diabetic retinopathy screening programme and annotated manually by two clinicians. We obtain considerably better accuracies compared to leading methods in REVIEW tests and in Tayside tests. An important advantage of our method is its stability (success rate, i.e., meaningful measurement returned, of 100% on all REVIEW data sets and on the Tayside data set) compared to a variety of methods from the literature. We also find that results depend crucially on testing data and conditions, and discuss criteria for selecting a training set yielding optimal accuracy. PMID:24001930
Accurate analytical modelling of cosmic ray induced failure rates of power semiconductor devices
NASA Astrophysics Data System (ADS)
Bauer, Friedhelm D.
2009-06-01
A new, simple and efficient approach is presented to conduct estimations of the cosmic ray induced failure rate for high voltage silicon power devices early in the design phase. This allows combining common design issues such as device losses and safe operating area with the constraints imposed by the reliability to result in a better and overall more efficient design methodology. Starting from an experimental and theoretical background brought forth a few yeas ago [Kabza H et al. Cosmic radiation as a cause for power device failure and possible countermeasures. In: Proceedings of the sixth international symposium on power semiconductor devices and IC's, Davos, Switzerland; 1994. p. 9-12, Zeller HR. Cosmic ray induced breakdown in high voltage semiconductor devices, microscopic model and possible countermeasures. In: Proceedings of the sixth international symposium on power semiconductor devices and IC's, Davos, Switzerland; 1994. p. 339-40, and Matsuda H et al. Analysis of GTO failure mode during d.c. blocking. In: Proceedings of the sixth international symposium on power semiconductor devices and IC's, Davos, Switzerland; 1994. p. 221-5], an exact solution of the failure rate integral is derived and presented in a form which lends itself to be combined with the results available from commercial semiconductor simulation tools. Hence, failure rate integrals can be obtained with relative ease for realistic two- and even three-dimensional semiconductor geometries. Two case studies relating to IGBT cell design and planar junction termination layout demonstrate the purpose of the method.
Slodownik, Dan; Grinberg, Igor; Spira, Ram M; Skornik, Yehuda; Goldstein, Ronald S
2009-04-01
The current standard method for predicting contact allergenicity is the murine local lymph node assay (LLNA). Public objection to the use of animals in testing of cosmetics makes the development of a system that does not use sentient animals highly desirable. The chorioallantoic membrane (CAM) of the chick egg has been extensively used for the growth of normal and transformed mammalian tissues. The CAM is not innervated, and embryos are sacrificed before the development of pain perception. The aim of this study was to determine whether the sensitization phase of contact dermatitis to known cosmetic allergens can be quantified using CAM-engrafted human skin and how these results compare with published EC3 data obtained with the LLNA. We studied six common molecules used in allergen testing and quantified migration of epidermal Langerhans cells (LC) as a measure of their allergic potency. All agents with known allergic potential induced statistically significant migration of LC. The data obtained correlated well with published data for these allergens generated using the LLNA test. The human-skin CAM model therefore has great potential as an inexpensive, non-radioactive, in vivo alternative to the LLNA, which does not require the use of sentient animals. In addition, this system has the advantage of testing the allergic response of human, rather than animal skin. PMID:19054059
Wang, Shiyao; Deng, Zhidong; Yin, Gang
2016-01-01
A high-performance differential global positioning system (GPS) receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS–inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car. PMID:26927108
Wang, Shiyao; Deng, Zhidong; Yin, Gang
2016-01-01
A high-performance differential global positioning system (GPS) receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS-inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car. PMID:26927108
NASA Astrophysics Data System (ADS)
Rybynok, V. O.; Kyriacou, P. A.
2007-10-01
Diabetes is one of the biggest health challenges of the 21st century. The obesity epidemic, sedentary lifestyles and an ageing population mean prevalence of the condition is currently doubling every generation. Diabetes is associated with serious chronic ill health, disability and premature mortality. Long-term complications including heart disease, stroke, blindness, kidney disease and amputations, make the greatest contribution to the costs of diabetes care. Many of these long-term effects could be avoided with earlier, more effective monitoring and treatment. Currently, blood glucose can only be monitored through the use of invasive techniques. To date there is no widely accepted and readily available non-invasive monitoring technique to measure blood glucose despite the many attempts. This paper challenges one of the most difficult non-invasive monitoring techniques, that of blood glucose, and proposes a new novel approach that will enable the accurate, and calibration free estimation of glucose concentration in blood. This approach is based on spectroscopic techniques and a new adaptive modelling scheme. The theoretical implementation and the effectiveness of the adaptive modelling scheme for this application has been described and a detailed mathematical evaluation has been employed to prove that such a scheme has the capability of extracting accurately the concentration of glucose from a complex biological media.
Using Perspective to Model Complex Processes
Kelsey, R.L.; Bisset, K.R.
1999-04-04
The notion of perspective, when supported in an object-based knowledge representation, can facilitate better abstractions of reality for modeling and simulation. The object modeling of complex physical and chemical processes is made more difficult in part due to the poor abstractions of state and phase changes available in these models. The notion of perspective can be used to create different views to represent the different states of matter in a process. These techniques can lead to a more understandable model. Additionally, the ability to record the progress of a process from start to finish is problematic. It is desirable to have a historic record of the entire process, not just the end result of the process. A historic record should facilitate backtracking and re-start of a process at different points in time. The same representation structures and techniques can be used to create a sequence of process markers to represent a historic record. By using perspective, the sequence of markers can have multiple and varying views tailored for a particular user's context of interest.
NASA Astrophysics Data System (ADS)
Weber, Tobias K. D.; Riedel, Thomas
2015-04-01
Free water is a prerequesite to chemical reactions and biological activity in earth's upper crust essential to life. The void volume between the solid compounds provides space for water, air, and organisms that thrive on the consumption of minerals and organic matter thereby regulating soil carbon turnover. However, not all water in the pore space in soils and sediments is in its liquid state. This is a result of the adhesive forces which reduce the water activity in small pores and charged mineral surfaces. This water has a lower tendency to react chemically in solution as this additional binding energy lowers its activity. In this work, we estimated the amount of soil pore water that is thermodynamically different from a simple aqueous solution. The quantity of soil pore water with properties different to liquid water was found to systematically increase with increasing clay content. The significance of this is that the grain size and surface area apparently affects the thermodynamic state of water. This implies that current methods to determine the amount of water content, traditionally determined from bulk density or gravimetric water content after drying at 105°C overestimates the amount of free water in a soil especially at higher clay content. Our findings have consequences for biogeochemical processes in soils, e.g. nutrients may be contained in water which is not free which could enhance preservation. From water activity measurements on a set of various soils with 0 to 100 wt-% clay, we can show that 5 to 130 mg H2O per g of soil can generally be considered as unsuitable for microbial respiration. These results may therefore provide a unifying explanation for the grain size dependency of organic matter preservation in sedimentary environments and call for a revised view on the biogeochemical environment in soils and sediments. This could allow a different type of process oriented modelling.
van Wyk, Marnus J; Bingle, Marianne; Meyer, Frans J C
2005-09-01
International bodies such as International Commission on Non-Ionizing Radiation Protection (ICNIRP) and the Institute for Electrical and Electronic Engineering (IEEE) make provision for human exposure assessment based on SAR calculations (or measurements) and basic restrictions. In the case of base station exposure this is mostly applicable to occupational exposure scenarios in the very near field of these antennas where the conservative reference level criteria could be unnecessarily restrictive. This study presents a variety of critical aspects that need to be considered when calculating SAR in a human body close to a mobile phone base station antenna. A hybrid FEM/MoM technique is proposed as a suitable numerical method to obtain accurate results. The verification of the FEM/MoM implementation has been presented in a previous publication; the focus of this study is an investigation into the detail that must be included in a numerical model of the antenna, to accurately represent the real-world scenario. This is accomplished by comparing numerical results to measurements for a generic GSM base station antenna and appropriate, representative canonical and human phantoms. The results show that it is critical to take the disturbance effect of the human phantom (a large conductive body) on the base station antenna into account when the antenna-phantom spacing is less than 300 mm. For these small spacings, the antenna structure must be modeled in detail. The conclusion is that it is feasible to calculate, using the proposed techniques and methodology, accurate occupational compliance zones around base station antennas based on a SAR profile and basic restriction guidelines. PMID:15931680
Complex Geometry Creation and Turbulent Conjugate Heat Transfer Modeling
Bodey, Isaac T; Arimilli, Rao V; Freels, James D
2011-01-01
The multiphysics capabilities of COMSOL provide the necessary tools to simulate the turbulent thermal-fluid aspects of the High Flux Isotope Reactor (HFIR). Version 4.1, and later, of COMSOL provides three different turbulence models: the standard k-{var_epsilon} closure model, the low Reynolds number (LRN) k-{var_epsilon} model, and the Spalart-Allmaras model. The LRN meets the needs of the nominal HFIR thermal-hydraulic requirements for 2D and 3D simulations. COMSOL also has the capability to create complex geometries. The circular involute fuel plates used in the HFIR require the use of algebraic equations to generate an accurate geometrical representation in the simulation environment. The best-estimate simulation results show that the maximum fuel plate clad surface temperatures are lower than those predicted by the legacy thermal safety code used at HFIR by approximately 17 K. The best-estimate temperature distribution determined by COMSOL was then used to determine the necessary increase in the magnitude of the power density profile (PDP) to produce a similar clad surface temperature as compared to the legacy thermal safety code. It was determined and verified that a 19% power increase was sufficient to bring the two temperature profiles to relatively good agreement.
Ants (Formicidae): models for social complexity.
Smith, Chris R; Dolezal, Adam; Eliyahu, Dorit; Holbrook, C Tate; Gadau, Jürgen
2009-07-01
The family Formicidae (ants) is composed of more than 12,000 described species that vary greatly in size, morphology, behavior, life history, ecology, and social organization. Ants occur in most terrestrial habitats and are the dominant animals in many of them. They have been used as models to address fundamental questions in ecology, evolution, behavior, and development. The literature on ants is extensive, and the natural history of many species is known in detail. Phylogenetic relationships for the family, as well as within many subfamilies, are known, enabling comparative studies. Their ease of sampling and ecological variation makes them attractive for studying populations and questions relating to communities. Their sociality and variation in social organization have contributed greatly to an understanding of complex systems, division of labor, and chemical communication. Ants occur in colonies composed of tens to millions of individuals that vary greatly in morphology, physiology, and behavior; this variation has been used to address proximate and ultimate mechanisms generating phenotypic plasticity. Relatedness asymmetries within colonies have been fundamental to the formulation and empirical testing of kin and group selection theories. Genomic resources have been developed for some species, and a whole-genome sequence for several species is likely to follow in the near future; comparative genomics in ants should provide new insights into the evolution of complexity and sociogenomics. Future studies using ants should help establish a more comprehensive understanding of social life, from molecules to colonies. PMID:20147200
Physical modelling of the nuclear pore complex
Fassati, Ariberto; Ford, Ian J.; Hoogenboom, Bart W.
2013-01-01
Physically interesting behaviour can arise when soft matter is confined to nanoscale dimensions. A highly relevant biological example of such a phenomenon is the Nuclear Pore Complex (NPC) found perforating the nuclear envelope of eukaryotic cells. In the central conduit of the NPC, of ∼30–60 nm diameter, a disordered network of proteins regulates all macromolecular transport between the nucleus and the cytoplasm. In spite of a wealth of experimental data, the selectivity barrier of the NPC has yet to be explained fully. Experimental and theoretical approaches are complicated by the disordered and heterogeneous nature of the NPC conduit. Modelling approaches have focused on the behaviour of the partially unfolded protein domains in the confined geometry of the NPC conduit, and have demonstrated that within the range of parameters thought relevant for the NPC, widely varying behaviour can be observed. In this review, we summarise recent efforts to physically model the NPC barrier and function. We illustrate how attempts to understand NPC barrier function have employed many different modelling techniques, each of which have contributed to our understanding of the NPC.
Reducing Spatial Data Complexity for Classification Models
Ruta, Dymitr; Gabrys, Bogdan
2007-11-29
Intelligent data analytics gradually becomes a day-to-day reality of today's businesses. However, despite rapidly increasing storage and computational power current state-of-the-art predictive models still can not handle massive and noisy corporate data warehouses. What is more adaptive and real-time operational environment requires multiple models to be frequently retrained which further hinders their use. Various data reduction techniques ranging from data sampling up to density retention models attempt to address this challenge by capturing a summarised data structure, yet they either do not account for labelled data or degrade the classification performance of the model trained on the condensed dataset. Our response is a proposition of a new general framework for reducing the complexity of labelled data by means of controlled spatial redistribution of class densities in the input space. On the example of Parzen Labelled Data Compressor (PLDC) we demonstrate a simulatory data condensation process directly inspired by the electrostatic field interaction where the data are moved and merged following the attracting and repelling interactions with the other labelled data. The process is controlled by the class density function built on the original data that acts as a class-sensitive potential field ensuring preservation of the original class density distributions, yet allowing data to rearrange and merge joining together their soft class partitions. As a result we achieved a model that reduces the labelled datasets much further than any competitive approaches yet with the maximum retention of the original class densities and hence the classification performance. PLDC leaves the reduced dataset with the soft accumulative class weights allowing for efficient online updates and as shown in a series of experiments if coupled with Parzen Density Classifier (PDC) significantly outperforms competitive data condensation methods in terms of classification performance at the
Reducing Spatial Data Complexity for Classification Models
NASA Astrophysics Data System (ADS)
Ruta, Dymitr; Gabrys, Bogdan
2007-11-01
Intelligent data analytics gradually becomes a day-to-day reality of today's businesses. However, despite rapidly increasing storage and computational power current state-of-the-art predictive models still can not handle massive and noisy corporate data warehouses. What is more adaptive and real-time operational environment requires multiple models to be frequently retrained which further hinders their use. Various data reduction techniques ranging from data sampling up to density retention models attempt to address this challenge by capturing a summarised data structure, yet they either do not account for labelled data or degrade the classification performance of the model trained on the condensed dataset. Our response is a proposition of a new general framework for reducing the complexity of labelled data by means of controlled spatial redistribution of class densities in the input space. On the example of Parzen Labelled Data Compressor (PLDC) we demonstrate a simulatory data condensation process directly inspired by the electrostatic field interaction where the data are moved and merged following the attracting and repelling interactions with the other labelled data. The process is controlled by the class density function built on the original data that acts as a class-sensitive potential field ensuring preservation of the original class density distributions, yet allowing data to rearrange and merge joining together their soft class partitions. As a result we achieved a model that reduces the labelled datasets much further than any competitive approaches yet with the maximum retention of the original class densities and hence the classification performance. PLDC leaves the reduced dataset with the soft accumulative class weights allowing for efficient online updates and as shown in a series of experiments if coupled with Parzen Density Classifier (PDC) significantly outperforms competitive data condensation methods in terms of classification performance at the
40 CFR 80.45 - Complex emissions model.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 40 Protection of Environment 17 2012-07-01 2012-07-01 false Complex emissions model. 80.45 Section...) REGULATION OF FUELS AND FUEL ADDITIVES Reformulated Gasoline § 80.45 Complex emissions model. (a) Definition... fuel which is being evaluated for its emissions performance using the complex model OXY =...
NASA Astrophysics Data System (ADS)
de Natale, Giuseppe; Crippa, Bruno; Troise, Claudia; Pingue, Folco; Audia, Karim; Dalla Via, Giorgio
2010-05-01
The seismic sequence occurred in the Abruzzo Apennines near L'Aquila (Italy) in April 2009 caused extensive damage and a large number of casualties (close to 300). The earthquake struck an area in the Italian Apennines chain where several faults, belonging to adjacent seismotectonic domains, create a complex tectonic regime resulting from the interaction among regional stress build-up, local stress changes caused by individual earthquakes and visco-elastic stress relaxation. Understanding such complex interaction in the Apennines can lead to a large step forward in the seismic risk mitigation in Italy. The Abruzzo earthquake has been exceptionally well recorded by InSAR data, much better than the first Italian earthquake ever recorded by satellites, namely the 1997 Umbria-Marche one. Envisat data for the Abruzzo earthquake are in fact very clear and allow an accurate reconstruction of the faulting mechanism. We present here an accurate inversion of vertical deformation data obtained by ENVISAT images, aimed to give a detailed reconstruction of the fault geometry and slip distribution. The resulting faulting models are then used to compute, by a suitable theoretical model based on elastic dislocation theory, the stress changes induced on the neighbouring faults. The study of the subsequent mainshocks of the Abruzzo sequence clearly evidence the effect of static stress changes consecutively triggering the subsequent mainshocks. Furthermore, this analysis put in evidence the seismotectonic domains that have been more heavily charged by stress released by the Abruzzo mainshocks. The most important faults significantly charged by the Abruzzo sequence include the Sulmona and Avezzano tectonic domains, including also the area, West-Southwest to the Avezzano domain, where a large earthquake occurred in 1394. Taking into account the average regional stress build-up in the area, the positive Coulomb stress changes caused by this earthquake can be seen as anticipating the
NASA Astrophysics Data System (ADS)
Xin, Cui; Di-Yu, Zhang; Gao, Chen; Ji-Gen, Chen; Si-Liang, Zeng; Fu-Ming, Guo; Yu-Jun, Yang
2016-03-01
We demonstrate that the interference minima in the linear molecular harmonic spectra can be accurately predicted by a modified two-center model. Based on systematically investigating the interference minima in the linear molecular harmonic spectra by the strong-field approximation (SFA), it is found that the locations of the harmonic minima are related not only to the nuclear distance between the two main atoms contributing to the harmonic generation, but also to the symmetry of the molecular orbital. Therefore, we modify the initial phase difference between the double wave sources in the two-center model, and predict the harmonic minimum positions consistent with those simulated by SFA. Project supported by the National Basic Research Program of China (Grant No. 2013CB922200) and the National Natural Science Foundation of China (Grant Nos. 11274001, 11274141, 11304116, 11247024, and 11034003), and the Jilin Provincial Research Foundation for Basic Research, China (Grant Nos. 20130101012JC and 20140101168JC).
NASA Astrophysics Data System (ADS)
Rong, Y. M.; Chang, Y.; Huang, Y.; Zhang, G. J.; Shao, X. Y.
2015-12-01
There are few researches that concentrate on the prediction of the bead geometry for laser brazing with crimping butt. This paper addressed the accurate prediction of the bead profile by developing a generalized regression neural network (GRNN) algorithm. Firstly GRNN model was developed and trained to decrease the prediction error that may be influenced by the sample size. Then the prediction accuracy was demonstrated by comparing with other articles and back propagation artificial neural network (BPNN) algorithm. Eventually the reliability and stability of GRNN model were discussed from the points of average relative error (ARE), mean square error (MSE) and root mean square error (RMSE), while the maximum ARE and MSE were 6.94% and 0.0303 that were clearly less than those (14.28% and 0.0832) predicted by BPNN. Obviously, it was proved that the prediction accuracy was improved at least 2 times, and the stability was also increased much more.
Gray, Alan; Harlen, Oliver G.; Harris, Sarah A.; Khalid, Syma; Leung, Yuk Ming; Lonsdale, Richard; Mulholland, Adrian J.; Pearson, Arwen R.; Read, Daniel J.; Richardson, Robin A.
2015-01-01
Despite huge advances in the computational techniques available for simulating biomolecules at the quantum-mechanical, atomistic and coarse-grained levels, there is still a widespread perception amongst the experimental community that these calculations are highly specialist and are not generally applicable by researchers outside the theoretical community. In this article, the successes and limitations of biomolecular simulation and the further developments that are likely in the near future are discussed. A brief overview is also provided of the experimental biophysical methods that are commonly used to probe biomolecular structure and dynamics, and the accuracy of the information that can be obtained from each is compared with that from modelling. It is concluded that progress towards an accurate spatial and temporal model of biomacromolecules requires a combination of all of these biophysical techniques, both experimental and computational. PMID:25615870
NASA Astrophysics Data System (ADS)
Pau, George Shu Heng; Shen, Chaopeng; Riley, William J.; Liu, Yaning
2016-02-01
The topography, and the biotic and abiotic parameters are typically upscaled to make watershed-scale hydrologic-biogeochemical models computationally tractable. However, upscaling procedure can produce biases when nonlinear interactions between different processes are not fully captured at coarse resolutions. Here we applied the Proper Orthogonal Decomposition Mapping Method (PODMM) to downscale the field solutions from a coarse (7 km) resolution grid to a fine (220 m) resolution grid. PODMM trains a reduced-order model (ROM) with coarse-resolution and fine-resolution solutions, here obtained using PAWS+CLM, a quasi-3-D watershed processes model that has been validated for many temperate watersheds. Subsequent fine-resolution solutions were approximated based only on coarse-resolution solutions and the ROM. The approximation errors were efficiently quantified using an error estimator. By jointly estimating correlated variables and temporally varying the ROM parameters, we further reduced the approximation errors by up to 20%. We also improved the method's robustness by constructing multiple ROMs using different set of variables, and selecting the best approximation based on the error estimator. The ROMs produced accurate downscaling of soil moisture, latent heat flux, and net primary production with O(1000) reduction in computational cost. The subgrid distributions were also nearly indistinguishable from the ones obtained using the fine-resolution model. Compared to coarse-resolution solutions, biases in upscaled ROM solutions were reduced by up to 80%. This method has the potential to help address the long-standing spatial scaling problem in hydrology and enable long-time integration, parameter estimation, and stochastic uncertainty analysis while accurately representing the heterogeneities.
Comparison of Two Pasture Growth Models of Differing Complexity
Technology Transfer Automated Retrieval System (TEKTRAN)
Two pasture growth models that share many common features but differ in model complexity have been developed for incorporation into the Integrated Farm System Model (IFSM). Major differences between models include the explicit representation of roots in the more complex model, and their effects on c...
Analytical models for complex swirling flows
NASA Astrophysics Data System (ADS)
Borissov, A.; Hussain, V.
1996-11-01
We develops a new class of analytical solutions of the Navier-Stokes equations for swirling flows, and suggests ways to predict and control such flows occurring in various technological applications. We view momentum accumulation on the axis as a key feature of swirling flows and consider vortex-sink flows on curved axisymmetric surfaces with an axial flow. We show that these solutions model swirling flows in a cylindrical can, whirlpools, tornadoes, and cosmic swirling jets. The singularity of these solutions on the flow axis is removed by matching them with near-axis Schlichting and Long's swirling jets. The matched solutions model flows with very complex patterns, consisting of up to seven separation regions with recirculatory 'bubbles' and vortex rings. We apply the matched solutions for computing flows in the Ranque-Hilsch tube, in the meniscus of electrosprays, in vortex breakdown, and in an industrial vortex burner. The simple analytical solutions allow a clear understanding of how different control parameters affect the flow and guide selection of optimal parameter values for desired flow features. These solutions permit extension to other problems (such as heat transfer and chemical reaction) and have the potential of being significantly useful for further detailed investigation by direct or large-eddy numerical simulations as well as laboratory experimentation.
Discrete Element Modeling of Complex Granular Flows
NASA Astrophysics Data System (ADS)
Movshovitz, N.; Asphaug, E. I.
2010-12-01
Granular materials occur almost everywhere in nature, and are actively studied in many fields of research, from food industry to planetary science. One approach to the study of granular media, the continuum approach, attempts to find a constitutive law that determines the material's flow, or strain, under applied stress. The main difficulty with this approach is that granular systems exhibit different behavior under different conditions, behaving at times as an elastic solid (e.g. pile of sand), at times as a viscous fluid (e.g. when poured), or even as a gas (e.g. when shaken). Even if all these physics are accounted for, numerical implementation is made difficult by the wide and often discontinuous ranges in continuum density and sound speed. A different approach is Discrete Element Modeling (DEM). Here the goal is to directly model every grain in the system as a rigid body subject to various body and surface forces. The advantage of this method is that it treats all of the above regimes in the same way, and can easily deal with a system moving back and forth between regimes. But as a granular system typically contains a multitude of individual grains, the direct integration of the system can be very computationally expensive. For this reason most DEM codes are limited to spherical grains of uniform size. However, spherical grains often cannot replicate the behavior of real world granular systems. A simple pile of spherical grains, for example, relies on static friction alone to keep its shape, while in reality a pile of irregular grains can maintain a much steeper angle by interlocking force chains. In the present study we employ a commercial DEM, nVidia's PhysX Engine, originally designed for the game and animation industry, to simulate complex granular flows with irregular, non-spherical grains. This engine runs as a multi threaded process and can be GPU accelerated. We demonstrate the code's ability to physically model granular materials in the three regimes
Gao, Yaozong; Shao, Yeqin; Lian, Jun; Wang, Andrew Z; Chen, Ronald C; Shen, Dinggang
2016-06-01
Segmenting male pelvic organs from CT images is a prerequisite for prostate cancer radiotherapy. The efficacy of radiation treatment highly depends on segmentation accuracy. However, accurate segmentation of male pelvic organs is challenging due to low tissue contrast of CT images, as well as large variations of shape and appearance of the pelvic organs. Among existing segmentation methods, deformable models are the most popular, as shape prior can be easily incorporated to regularize the segmentation. Nonetheless, the sensitivity to initialization often limits their performance, especially for segmenting organs with large shape variations. In this paper, we propose a novel approach to guide deformable models, thus making them robust against arbitrary initializations. Specifically, we learn a displacement regressor, which predicts 3D displacement from any image voxel to the target organ boundary based on the local patch appearance. This regressor provides a non-local external force for each vertex of deformable model, thus overcoming the initialization problem suffered by the traditional deformable models. To learn a reliable displacement regressor, two strategies are particularly proposed. 1) A multi-task random forest is proposed to learn the displacement regressor jointly with the organ classifier; 2) an auto-context model is used to iteratively enforce structural information during voxel-wise prediction. Extensive experiments on 313 planning CT scans of 313 patients show that our method achieves better results than alternative classification or regression based methods, and also several other existing methods in CT pelvic organ segmentation. PMID:26800531
Sethurajan, Athinthra Krishnaswamy; Krachkovskiy, Sergey A; Halalay, Ion C; Goward, Gillian R; Protas, Bartosz
2015-09-17
We used NMR imaging (MRI) combined with data analysis based on inverse modeling of the mass transport problem to determine ionic diffusion coefficients and transference numbers in electrolyte solutions of interest for Li-ion batteries. Sensitivity analyses have shown that accurate estimates of these parameters (as a function of concentration) are critical to the reliability of the predictions provided by models of porous electrodes. The inverse modeling (IM) solution was generated with an extension of the Planck-Nernst model for the transport of ionic species in electrolyte solutions. Concentration-dependent diffusion coefficients and transference numbers were derived using concentration profiles obtained from in situ (19)F MRI measurements. Material properties were reconstructed under minimal assumptions using methods of variational optimization to minimize the least-squares deviation between experimental and simulated concentration values with uncertainty of the reconstructions quantified using a Monte Carlo analysis. The diffusion coefficients obtained by pulsed field gradient NMR (PFG-NMR) fall within the 95% confidence bounds for the diffusion coefficient values obtained by the MRI+IM method. The MRI+IM method also yields the concentration dependence of the Li(+) transference number in agreement with trends obtained by electrochemical methods for similar systems and with predictions of theoretical models for concentrated electrolyte solutions, in marked contrast to the salt concentration dependence of transport numbers determined from PFG-NMR data. PMID:26247105
Chen, Y; Mo, X; Chen, M; Olivera, G; Parnell, D; Key, S; Lu, W; Reeher, M; Galmarini, D
2014-06-01
Purpose: An accurate leaf fluence model can be used in applications such as patient specific delivery QA and in-vivo dosimetry for TomoTherapy systems. It is known that the total fluence is not a linear combination of individual leaf fluence due to leakage-transmission, tongue-and-groove, and source occlusion effect. Here we propose a method to model the nonlinear effects as linear terms thus making the MLC-detector system a linear system. Methods: A leaf pattern basis (LPB) consisting of no-leaf-open, single-leaf-open, double-leaf-open and triple-leaf-open patterns are chosen to represent linear and major nonlinear effects of leaf fluence as a linear system. An arbitrary leaf pattern can be expressed as (or decomposed to) a linear combination of the LPB either pulse by pulse or weighted by dwelling time. The exit detector responses to the LPB are obtained by processing returned detector signals resulting from the predefined leaf patterns for each jaw setting. Through forward transformation, detector signal can be predicted given a delivery plan. An equivalent leaf open time (LOT) sinogram containing output variation information can also be inversely calculated from the measured detector signals. Twelve patient plans were delivered in air. The equivalent LOT sinograms were compared with their planned sinograms. Results: The whole calibration process was done in 20 minutes. For two randomly generated leaf patterns, 98.5% of the active channels showed differences within 0.5% of the local maximum between the predicted and measured signals. Averaged over the twelve plans, 90% of LOT errors were within +/−10 ms. The LOT systematic error increases and shows an oscillating pattern when LOT is shorter than 50 ms. Conclusion: The LPB method models the MLC-detector response accurately, which improves patient specific delivery QA and in-vivo dosimetry for TomoTherapy systems. It is sensitive enough to detect systematic LOT errors as small as 10 ms.
NASA Astrophysics Data System (ADS)
McCullagh, Nuala; Jeong, Donghui; Szalay, Alexander S.
2016-01-01
Accurate modelling of non-linearities in the galaxy bispectrum, the Fourier transform of the galaxy three-point correlation function, is essential to fully exploit it as a cosmological probe. In this paper, we present numerical and theoretical challenges in modelling the non-linear bispectrum. First, we test the robustness of the matter bispectrum measured from N-body simulations using different initial conditions generators. We run a suite of N-body simulations using the Zel'dovich approximation and second-order Lagrangian perturbation theory (2LPT) at different starting redshifts, and find that transients from initial decaying modes systematically reduce the non-linearities in the matter bispectrum. To achieve 1 per cent accuracy in the matter bispectrum at z ≤ 3 on scales k < 1 h Mpc-1, 2LPT initial conditions generator with initial redshift z ≳ 100 is required. We then compare various analytical formulas and empirical fitting functions for modelling the non-linear matter bispectrum, and discuss the regimes for which each is valid. We find that the next-to-leading order (one-loop) correction from standard perturbation theory matches with N-body results on quasi-linear scales for z ≥ 1. We find that the fitting formula in Gil-Marín et al. accurately predicts the matter bispectrum for z ≤ 1 on a wide range of scales, but at higher redshifts, the fitting formula given in Scoccimarro & Couchman gives the best agreement with measurements from N-body simulations.
Kao, Athit; Chiu, Chi-li; Vellucci, Danielle; Yang, Yingying; Patel, Vishal R.; Guan, Shenheng; Randall, Arlo; Baldi, Pierre; Rychnovsky, Scott D.; Huang, Lan
2011-01-01
Knowledge of elaborate structures of protein complexes is fundamental for understanding their functions and regulations. Although cross-linking coupled with mass spectrometry (MS) has been presented as a feasible strategy for structural elucidation of large multisubunit protein complexes, this method has proven challenging because of technical difficulties in unambiguous identification of cross-linked peptides and determination of cross-linked sites by MS analysis. In this work, we developed a novel cross-linking strategy using a newly designed MS-cleavable cross-linker, disuccinimidyl sulfoxide (DSSO). DSSO contains two symmetric collision-induced dissociation (CID)-cleavable sites that allow effective identification of DSSO-cross-linked peptides based on their distinct fragmentation patterns unique to cross-linking types (i.e. interlink, intralink, and dead end). The CID-induced separation of interlinked peptides in MS/MS permits MS3 analysis of single peptide chain fragment ions with defined modifications (due to DSSO remnants) for easy interpretation and unambiguous identification using existing database searching tools. Integration of data analyses from three generated data sets (MS, MS/MS, and MS3) allows high confidence identification of DSSO cross-linked peptides. The efficacy of the newly developed DSSO-based cross-linking strategy was demonstrated using model peptides and proteins. In addition, this method was successfully used for structural characterization of the yeast 20 S proteasome complex. In total, 13 non-redundant interlinked peptides of the 20 S proteasome were identified, representing the first application of an MS-cleavable cross-linker for the characterization of a multisubunit protein complex. Given its effectiveness and simplicity, this cross-linking strategy can find a broad range of applications in elucidating the structural topology of proteins and protein complexes. PMID:20736410
Bhaskara, Ramachandra M; Padhi, Amrita; Srinivasan, Narayanaswamy
2014-07-01
With the preponderance of multidomain proteins in eukaryotic genomes, it is essential to recognize the constituent domains and their functions. Often function involves communications across the domain interfaces, and the knowledge of the interacting sites is essential to our understanding of the structure-function relationship. Using evolutionary information extracted from homologous domains in at least two diverse domain architectures (single and multidomain), we predict the interface residues corresponding to domains from the two-domain proteins. We also use information from the three-dimensional structures of individual domains of two-domain proteins to train naïve Bayes classifier model to predict the interfacial residues. Our predictions are highly accurate (∼85%) and specific (∼95%) to the domain-domain interfaces. This method is specific to multidomain proteins which contain domains in at least more than one protein architectural context. Using predicted residues to constrain domain-domain interaction, rigid-body docking was able to provide us with accurate full-length protein structures with correct orientation of domains. We believe that these results can be of considerable interest toward rational protein and interaction design, apart from providing us with valuable information on the nature of interactions. PMID:24375512
Modeling competitive substitution in a polyelectrolyte complex
Peng, B.; Muthukumar, M.
2015-12-28
We have simulated the invasion of a polyelectrolyte complex made of a polycation chain and a polyanion chain, by another longer polyanion chain, using the coarse-grained united atom model for the chains and the Langevin dynamics methodology. Our simulations reveal many intricate details of the substitution reaction in terms of conformational changes of the chains and competition between the invading chain and the chain being displaced for the common complementary chain. We show that the invading chain is required to be sufficiently longer than the chain being displaced for effecting the substitution. Yet, having the invading chain to be longer than a certain threshold value does not reduce the substitution time much further. While most of the simulations were carried out in salt-free conditions, we show that presence of salt facilitates the substitution reaction and reduces the substitution time. Analysis of our data shows that the dominant driving force for the substitution process involving polyelectrolytes lies in the release of counterions during the substitution.
NASA Astrophysics Data System (ADS)
Hackel, Stefan; Montenbruck, Oliver; Steigenberger, -Peter; Eineder, Michael; Gisinger, Christoph
Remote sensing satellites support a broad range of scientific and commercial applications. The two radar imaging satellites TerraSAR-X and TanDEM-X provide spaceborne Synthetic Aperture Radar (SAR) and interferometric SAR data with a very high accuracy. The increasing demand for precise radar products relies on sophisticated validation methods, which require precise and accurate orbit products. Basically, the precise reconstruction of the satellite’s trajectory is based on the Global Positioning System (GPS) measurements from a geodetic-grade dual-frequency receiver onboard the spacecraft. The Reduced Dynamic Orbit Determination (RDOD) approach utilizes models for the gravitational and non-gravitational forces. Following a proper analysis of the orbit quality, systematics in the orbit products have been identified, which reflect deficits in the non-gravitational force models. A detailed satellite macro model is introduced to describe the geometry and the optical surface properties of the satellite. Two major non-gravitational forces are the direct and the indirect Solar Radiation Pressure (SRP). Due to the dusk-dawn orbit configuration of TerraSAR-X, the satellite is almost constantly illuminated by the Sun. Therefore, the direct SRP has an effect on the lateral stability of the determined orbit. The indirect effect of the solar radiation principally contributes to the Earth Radiation Pressure (ERP). The resulting force depends on the sunlight, which is reflected by the illuminated Earth surface in the visible, and the emission of the Earth body in the infrared spectra. Both components of ERP require Earth models to describe the optical properties of the Earth surface. Therefore, the influence of different Earth models on the orbit quality is assessed within the presentation. The presentation highlights the influence of non-gravitational force and satellite macro models on the orbit quality of TerraSAR-X.
Dai, Xiaoxu; Hu, Minghua; Tian, Wen; Xie, Daoyi; Hu, Bin
2016-01-01
This paper presents a propagation dynamics model for congestion propagation in complex networks of airspace. It investigates the application of an epidemiology model to complex networks by comparing the similarities and differences between congestion propagation and epidemic transmission. The model developed satisfies the constraints of actual motion in airspace, based on the epidemiology model. Exploiting the constraint that the evolution of congestion cluster in the airspace is always dynamic and heterogeneous, the SIR epidemiology model (one of the classical models in epidemic spreading) with logistic increase is applied to congestion propagation and shown to be more accurate in predicting the evolution of congestion peak than the model based on probability, which is common to predict the congestion propagation. Results from sample data show that the model not only predicts accurately the value and time of congestion peak, but also describes accurately the characteristics of congestion propagation. Then, a numerical study is performed in which it is demonstrated that the structure of the networks have different effects on congestion propagation in airspace. It is shown that in regions with severe congestion, the adjustment of dissipation rate is more significant than propagation rate in controlling the propagation of congestion. PMID:27336405
Application of Epidemiology Model on Complex Networks in Propagation Dynamics of Airspace Congestion
Dai, Xiaoxu; Hu, Minghua; Tian, Wen; Xie, Daoyi; Hu, Bin
2016-01-01
This paper presents a propagation dynamics model for congestion propagation in complex networks of airspace. It investigates the application of an epidemiology model to complex networks by comparing the similarities and differences between congestion propagation and epidemic transmission. The model developed satisfies the constraints of actual motion in airspace, based on the epidemiology model. Exploiting the constraint that the evolution of congestion cluster in the airspace is always dynamic and heterogeneous, the SIR epidemiology model (one of the classical models in epidemic spreading) with logistic increase is applied to congestion propagation and shown to be more accurate in predicting the evolution of congestion peak than the model based on probability, which is common to predict the congestion propagation. Results from sample data show that the model not only predicts accurately the value and time of congestion peak, but also describes accurately the characteristics of congestion propagation. Then, a numerical study is performed in which it is demonstrated that the structure of the networks have different effects on congestion propagation in airspace. It is shown that in regions with severe congestion, the adjustment of dissipation rate is more significant than propagation rate in controlling the propagation of congestion. PMID:27336405
Radoń, Mariusz; Gąssowska, Katarzyna; Szklarzewicz, Janusz; Broclawik, Ewa
2016-04-12
Aqua complexes of transition metals are useful models for understanding the electronic structure of metal-oxide species relevant in photocatalytic water splitting. Moreover, spin-forbidden d-d transitions of aqua complexes provide valuable experimental data of spin-state energetics, which can be used for benchmarking of computational methods. Here, low-energy spin states of Fe(III) and Ru(III) aqua complexes are studied with an array of DFT and high-level wave function methods (CASPT2, RASPT2, NEVPT2, CCSD(T)-F12, and other coupled cluster methods up to full CCSDT). The results from single-reference and multireference methods are cross-checked, and the amount of multireference character for both considered spin states of [Fe(H2O)6](3+) is carefully analyzed. In addition to small [M(H2O)6](3+) clusters (M = Fe, Ru), we also employ larger models [M(H2O)6·(H2O)12](3+), with explicit water molecules in the second coordination sphere, to describe the situation in aqueous solution. By comparing the results for both types of models, our calculations evidence large and systematic solvation effects on the spin-state energetics. It is found that, due to the interaction with hydrogen-bonded water molecules in the second coordination sphere, the first coordination sphere undergoes a noticeable contraction and deformation. In consequence, the presence of solvation shell affects the relative energies of spin states by as much as 3-4 × 10(3) cm(-1) (∼10 kcal/mol). Once this solvation effect is accounted for, the spin-state energetics from CCSD(T) and NEVPT2 calculations turn out to be in an excellent agreement with the experimental estimates, which was not the case for isolated [M(H2O)6](3+) species is gas phase. We thus postulate that significant discrepancies between theory and experimental data for [Fe(H2O)6](3+) that were previously reported in the literature may be plausibly resolved and attributed to the neglect of explicit solvation effects and also, to some extent, to
Chang, Chih-Hao . E-mail: chchang@engineering.ucsb.edu; Liou, Meng-Sing . E-mail: meng-sing.liou@grc.nasa.gov
2007-07-01
In this paper, we propose a new approach to compute compressible multifluid equations. Firstly, a single-pressure compressible multifluid model based on the stratified flow model is proposed. The stratified flow model, which defines different fluids in separated regions, is shown to be amenable to the finite volume method. We can apply the conservation law to each subregion and obtain a set of balance equations. Secondly, the AUSM{sup +} scheme, which is originally designed for the compressible gas flow, is extended to solve compressible liquid flows. By introducing additional dissipation terms into the numerical flux, the new scheme, called AUSM{sup +}-up, can be applied to both liquid and gas flows. Thirdly, the contribution to the numerical flux due to interactions between different phases is taken into account and solved by the exact Riemann solver. We will show that the proposed approach yields an accurate and robust method for computing compressible multiphase flows involving discontinuities, such as shock waves and fluid interfaces. Several one-dimensional test problems are used to demonstrate the capability of our method, including the Ransom's water faucet problem and the air-water shock tube problem. Finally, several two dimensional problems will show the capability to capture enormous details and complicated wave patterns in flows having large disparities in the fluid density and velocities, such as interactions between water shock wave and air bubble, between air shock wave and water column(s), and underwater explosion.
NASA Astrophysics Data System (ADS)
Zhang, Na; Yao, Jun; Huang, Zhaoqin; Wang, Yueying
2013-06-01
Numerical simulation in naturally fractured media is challenging because of the coexistence of porous media and fractures on multiple scales that need to be coupled. We present a new approach to reservoir simulation that gives accurate resolution of both large-scale and fine-scale flow patterns. Multiscale methods are suitable for this type of modeling, because it enables capturing the large scale behavior of the solution without solving all the small features. Dual-porosity models in view of their strength and simplicity can be mainly used for sugar-cube representation of fractured media. In such a representation, the transfer function between the fracture and the matrix block can be readily calculated for water-wet media. For a mixed-wet system, the evaluation of the transfer function becomes complicated due to the effect of gravity. In this work, we use a multiscale finite element method (MsFEM) for two-phase flow in fractured media using the discrete-fracture model. By combining MsFEM with the discrete-fracture model, we aim towards a numerical scheme that facilitates fractured reservoir simulation without upscaling. MsFEM uses a standard Darcy model to approximate the pressure and saturation on a coarse grid, whereas fine scale effects are captured through basis functions constructed by solving local flow problems using the discrete-fracture model. The accuracy and the robustness of MsFEM are shown through several examples. In the first example, we consider several small fractures in a matrix and then compare the results solved by the finite element method. Then, we use the MsFEM in more complex models. The results indicate that the MsFEM is a promising path toward direct simulation of highly resolution geomodels.
NASA Astrophysics Data System (ADS)
Stukel, Michael R.; Landry, Michael R.; Ohman, Mark D.; Goericke, Ralf; Samo, Ty; Benitez-Nelson, Claudia R.
2012-03-01
Despite the increasing use of linear inverse modeling techniques to elucidate fluxes in undersampled marine ecosystems, the accuracy with which they estimate food web flows has not been resolved. New Markov Chain Monte Carlo (MCMC) solution methods have also called into question the biases of the commonly used L2 minimum norm (L 2MN) solution technique. Here, we test the abilities of MCMC and L 2MN methods to recover field-measured ecosystem rates that are sequentially excluded from the model input. For data, we use experimental measurements from process cruises of the California Current Ecosystem (CCE-LTER) Program that include rate estimates of phytoplankton and bacterial production, micro- and mesozooplankton grazing, and carbon export from eight study sites varying from rich coastal upwelling to offshore oligotrophic conditions. Both the MCMC and L 2MN methods predicted well-constrained rates of protozoan and mesozooplankton grazing with reasonable accuracy, but the MCMC method overestimated primary production. The MCMC method more accurately predicted the poorly constrained rate of vertical carbon export than the L 2MN method, which consistently overestimated export. Results involving DOC and bacterial production were equivocal. Overall, when primary production is provided as model input, the MCMC method gives a robust depiction of ecosystem processes. Uncertainty in inverse ecosystem models is large and arises primarily from solution under-determinacy. We thus suggest that experimental programs focusing on food web fluxes expand the range of experimental measurements to include the nature and fate of detrital pools, which play large roles in the model.
Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.; Fournier, Marcia V.
2008-10-20
One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic
NASA Astrophysics Data System (ADS)
Yogurtcu, Osman N.; Johnson, Margaret E.
2015-08-01
The dynamics of association between diffusing and reacting molecular species are routinely quantified using simple rate-equation kinetics that assume both well-mixed concentrations of species and a single rate constant for parameterizing the binding rate. In two-dimensions (2D), however, even when systems are well-mixed, the assumption of a single characteristic rate constant for describing association is not generally accurate, due to the properties of diffusional searching in dimensions d ≤ 2. Establishing rigorous bounds for discriminating between 2D reactive systems that will be accurately described by rate equations with a single rate constant, and those that will not, is critical for both modeling and experimentally parameterizing binding reactions restricted to surfaces such as cellular membranes. We show here that in regimes of intrinsic reaction rate (ka) and diffusion (D) parameters ka/D > 0.05, a single rate constant cannot be fit to the dynamics of concentrations of associating species independently of the initial conditions. Instead, a more sophisticated multi-parametric description than rate-equations is necessary to robustly characterize bimolecular reactions from experiment. Our quantitative bounds derive from our new analysis of 2D rate-behavior predicted from Smoluchowski theory. Using a recently developed single particle reaction-diffusion algorithm we extend here to 2D, we are able to test and validate the predictions of Smoluchowski theory and several other theories of reversible reaction dynamics in 2D for the first time. Finally, our results also mean that simulations of reactive systems in 2D using rate equations must be undertaken with caution when reactions have ka/D > 0.05, regardless of the simulation volume. We introduce here a simple formula for an adaptive concentration dependent rate constant for these chemical kinetics simulations which improves on existing formulas to better capture non-equilibrium reaction dynamics from dilute
NASA Astrophysics Data System (ADS)
Barbour, San-Lian S.; Barbour, Randall L.; Koo, Ping C.; Graber, Harry L.; Chang, Jenghwa
1995-05-01
results reported are the first to demonstrate that high quality images of small added inclusions can be obtained from anatomically accurate models of thick tissues having arbitrary boundaries based on the analysis of diffusely sscattered light.
Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems.
Williams, Richard A; Timmis, Jon; Qwarnstrom, Eva E
2016-01-01
Computational modelling and simulation is increasingly being used to complement traditional wet-lab techniques when investigating the mechanistic behaviours of complex biological systems. In order to ensure computational models are fit for purpose, it is essential that the abstracted view of biology captured in the computational model, is clearly and unambiguously defined within a conceptual model of the biological domain (a domain model), that acts to accurately represent the biological system and to document the functional requirements for the resultant computational model. We present a domain model of the IL-1 stimulated NF-κB signalling pathway, which unambiguously defines the spatial, temporal and stochastic requirements for our future computational model. Through the development of this model, we observe that, in isolation, UML is not sufficient for the purpose of creating a domain model, and that a number of descriptive and multivariate statistical techniques provide complementary perspectives, in particular when modelling the heterogeneity of dynamics at the single-cell level. We believe this approach of using UML to define the structure and interactions within a complex system, along with statistics to define the stochastic and dynamic nature of complex systems, is crucial for ensuring that conceptual models of complex dynamical biosystems, which are developed using UML, are fit for purpose, and unambiguously define the functional requirements for the resultant computational model. PMID:27571414
Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems
Timmis, Jon; Qwarnstrom, Eva E.
2016-01-01
Computational modelling and simulation is increasingly being used to complement traditional wet-lab techniques when investigating the mechanistic behaviours of complex biological systems. In order to ensure computational models are fit for purpose, it is essential that the abstracted view of biology captured in the computational model, is clearly and unambiguously defined within a conceptual model of the biological domain (a domain model), that acts to accurately represent the biological system and to document the functional requirements for the resultant computational model. We present a domain model of the IL-1 stimulated NF-κB signalling pathway, which unambiguously defines the spatial, temporal and stochastic requirements for our future computational model. Through the development of this model, we observe that, in isolation, UML is not sufficient for the purpose of creating a domain model, and that a number of descriptive and multivariate statistical techniques provide complementary perspectives, in particular when modelling the heterogeneity of dynamics at the single-cell level. We believe this approach of using UML to define the structure and interactions within a complex system, along with statistics to define the stochastic and dynamic nature of complex systems, is crucial for ensuring that conceptual models of complex dynamical biosystems, which are developed using UML, are fit for purpose, and unambiguously define the functional requirements for the resultant computational model. PMID:27571414
Clinical complexity in medicine: A measurement model of task and patient complexity
Islam, R.; Weir, C.; Fiol, G. Del
2016-01-01
Summary Background Complexity in medicine needs to be reduced to simple components in a way that is comprehensible to researchers and clinicians. Few studies in the current literature propose a measurement model that addresses both task and patient complexity in medicine. Objective The objective of this paper is to develop an integrated approach to understand and measure clinical complexity by incorporating both task and patient complexity components focusing on infectious disease domain. The measurement model was adapted and modified to healthcare domain. Methods Three clinical Infectious Disease teams were observed, audio-recorded and transcribed. Each team included an Infectious Diseases expert, one Infectious Diseases fellow, one physician assistant and one pharmacy resident fellow. The transcripts were parsed and the authors independently coded complexity attributes. This baseline measurement model of clinical complexity was modified in an initial set of coding process and further validated in a consensus-based iterative process that included several meetings and email discussions by three clinical experts from diverse backgrounds from the Department of Biomedical Informatics at the University of Utah. Inter-rater reliability was calculated using Cohen’s kappa. Results The proposed clinical complexity model consists of two separate components. The first is a clinical task complexity model with 13 clinical complexity-contributing factors and 7 dimensions. The second is the patient complexity model with 11 complexity-contributing factors and 5 dimensions. Conclusion The measurement model for complexity encompassing both task and patient complexity will be a valuable resource for future researchers and industry to measure and understand complexity in healthcare. PMID:26404626
Gray, Alan; Harlen, Oliver G.; Harris, Sarah A.; Khalid, Syma; Leung, Yuk Ming; Lonsdale, Richard; Mulholland, Adrian J.; Pearson, Arwen R.; Read, Daniel J.; Richardson, Robin A.
2015-01-01
The current computational techniques available for biomolecular simulation are described, and the successes and limitations of each with reference to the experimental biophysical methods that they complement are presented. Despite huge advances in the computational techniques available for simulating biomolecules at the quantum-mechanical, atomistic and coarse-grained levels, there is still a widespread perception amongst the experimental community that these calculations are highly specialist and are not generally applicable by researchers outside the theoretical community. In this article, the successes and limitations of biomolecular simulation and the further developments that are likely in the near future are discussed. A brief overview is also provided of the experimental biophysical methods that are commonly used to probe biomolecular structure and dynamics, and the accuracy of the information that can be obtained from each is compared with that from modelling. It is concluded that progress towards an accurate spatial and temporal model of biomacromolecules requires a combination of all of these biophysical techniques, both experimental and computational.
NASA Astrophysics Data System (ADS)
Stecca, Guglielmo; Siviglia, Annunziato; Blom, Astrid
2016-07-01
We present an accurate numerical approximation to the Saint-Venant-Hirano model for mixed-sediment morphodynamics in one space dimension. Our solution procedure originates from the fully-unsteady matrix-vector formulation developed in [54]. The principal part of the problem is solved by an explicit Finite Volume upwind method of the path-conservative type, by which all the variables are updated simultaneously in a coupled fashion. The solution to the principal part is embedded into a splitting procedure for the treatment of frictional source terms. The numerical scheme is extended to second-order accuracy and includes a bookkeeping procedure for handling the evolution of size stratification in the substrate. We develop a concept of balancedness for the vertical mass flux between the substrate and active layer under bed degradation, which prevents the occurrence of non-physical oscillations in the grainsize distribution of the substrate. We suitably modify the numerical scheme to respect this principle. We finally verify the accuracy in our solution to the equations, and its ability to reproduce one-dimensional morphodynamics due to streamwise and vertical sorting, using three test cases. In detail, (i) we empirically assess the balancedness of vertical mass fluxes under degradation; (ii) we study the convergence to the analytical linearised solution for the propagation of infinitesimal-amplitude waves [54], which is here employed for the first time to assess a mixed-sediment model; (iii) we reproduce Ribberink's E8-E9 flume experiment [46].
An accurate locally active memristor model for S-type negative differential resistance in NbOx
NASA Astrophysics Data System (ADS)
Gibson, Gary A.; Musunuru, Srinitya; Zhang, Jiaming; Vandenberghe, Ken; Lee, James; Hsieh, Cheng-Chih; Jackson, Warren; Jeon, Yoocharn; Henze, Dick; Li, Zhiyong; Stanley Williams, R.
2016-01-01
A number of important commercial applications would benefit from the introduction of easily manufactured devices that exhibit current-controlled, or "S-type," negative differential resistance (NDR). A leading example is emerging non-volatile memory based on crossbar array architectures. Due to the inherently linear current vs. voltage characteristics of candidate non-volatile memristor memory elements, individual memory cells in these crossbar arrays can be addressed only if a highly non-linear circuit element, termed a "selector," is incorporated in the cell. Selectors based on a layer of niobium oxide sandwiched between two electrodes have been investigated by a number of groups because the NDR they exhibit provides a promisingly large non-linearity. We have developed a highly accurate compact dynamical model for their electrical conduction that shows that the NDR in these devices results from a thermal feedback mechanism. A series of electrothermal measurements and numerical simulations corroborate this model. These results reveal that the leakage currents can be minimized by thermally isolating the selector or by incorporating materials with larger activation energies for electron motion.
NASA Astrophysics Data System (ADS)
Gritsyk, P. A.; Somov, B. V.
2016-08-01
The M7.7 solar flare of July 19, 2012, at 05:58 UT was observed with high spatial, temporal, and spectral resolutions in the hard X-ray and optical ranges. The flare occurred at the solar limb, which allowed us to see the relative positions of the coronal and chromospheric X-ray sources and to determine their spectra. To explain the observations of the coronal source and the chromospheric one unocculted by the solar limb, we apply an accurate analytical model for the kinetic behavior of accelerated electrons in a flare. We interpret the chromospheric hard X-ray source in the thick-target approximation with a reverse current and the coronal one in the thin-target approximation. Our estimates of the slopes of the hard X-ray spectra for both sources are consistent with the observations. However, the calculated intensity of the coronal source is lower than the observed one by several times. Allowance for the acceleration of fast electrons in a collapsing magnetic trap has enabled us to remove this contradiction. As a result of our modeling, we have estimated the flux density of the energy transferred by electrons with energies above 15 keV to be ˜5 × 1010 erg cm-2 s-1, which exceeds the values typical of the thick-target model without a reverse current by a factor of ˜5. To independently test the model, we have calculated the microwave spectrum in the range 1-50 GHz that corresponds to the available radio observations.
Power Curve Modeling in Complex Terrain Using Statistical Models
NASA Astrophysics Data System (ADS)
Bulaevskaya, V.; Wharton, S.; Clifton, A.; Qualley, G.; Miller, W.
2014-12-01
Traditional power output curves typically model power only as a function of the wind speed at the turbine hub height. While the latter is an essential predictor of power output, wind speed information in other parts of the vertical profile, as well as additional atmospheric variables, are also important determinants of power. The goal of this work was to determine the gain in predictive ability afforded by adding wind speed information at other heights, as well as other atmospheric variables, to the power prediction model. Using data from a wind farm with a moderately complex terrain in the Altamont Pass region in California, we trained three statistical models, a neural network, a random forest and a Gaussian process model, to predict power output from various sets of aforementioned predictors. The comparison of these predictions to the observed power data revealed that considerable improvements in prediction accuracy can be achieved both through the addition of predictors other than the hub-height wind speed and the use of statistical models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344 and was funded by Wind Uncertainty Quantification Laboratory Directed Research and Development Project at LLNL under project tracking code 12-ERD-069.
Sundaramurthy, Aravind; Alai, Aaron; Ganpule, Shailesh; Holmberg, Aaron; Plougonven, Erwan; Chandra, Namas
2012-09-01
Blast waves generated by improvised explosive devices (IEDs) cause traumatic brain injury (TBI) in soldiers and civilians. In vivo animal models that use shock tubes are extensively used in laboratories to simulate field conditions, to identify mechanisms of injury, and to develop injury thresholds. In this article, we place rats in different locations along the length of the shock tube (i.e., inside, outside, and near the exit), to examine the role of animal placement location (APL) in the biomechanical load experienced by the animal. We found that the biomechanical load on the brain and internal organs in the thoracic cavity (lungs and heart) varied significantly depending on the APL. When the specimen is positioned outside, organs in the thoracic cavity experience a higher pressure for a longer duration, in contrast to APL inside the shock tube. This in turn will possibly alter the injury type, severity, and lethality. We found that the optimal APL is where the Friedlander waveform is first formed inside the shock tube. Once the optimal APL was determined, the effect of the incident blast intensity on the surface and intracranial pressure was measured and analyzed. Noticeably, surface and intracranial pressure increases linearly with the incident peak overpressures, though surface pressures are significantly higher than the other two. Further, we developed and validated an anatomically accurate finite element model of the rat head. With this model, we determined that the main pathway of pressure transmission to the brain was through the skull and not through the snout; however, the snout plays a secondary role in diffracting the incoming blast wave towards the skull. PMID:22620716
Guo, En-Yu; Chawla, Nikhilesh; Jing, Tao; Torquato, Salvatore; Jiao, Yang
2014-03-01
Heterogeneous materials are ubiquitous in nature and synthetic situations and have a wide range of important engineering applications. Accurate modeling and reconstructing three-dimensional (3D) microstructure of topologically complex materials from limited morphological information such as a two-dimensional (2D) micrograph is crucial to the assessment and prediction of effective material properties and performance under extreme conditions. Here, we extend a recently developed dilation–erosion method and employ the Yeong–Torquato stochastic reconstruction procedure to model and generate 3D austenitic–ferritic cast duplex stainless steel microstructure containing percolating filamentary ferrite phase from 2D optical micrographs of the material sample. Specifically, the ferrite phase is dilated to produce a modified target 2D microstructure and the resulting 3D reconstruction is eroded to recover the percolating ferrite filaments. The dilation–erosion reconstruction is compared with the actual 3D microstructure, obtained from serial sectioning (polishing), as well as the standard stochastic reconstructions incorporating topological connectedness information. The fact that the former can achieve the same level of accuracy as the latter suggests that the dilation–erosion procedure is tantamount to incorporating appreciably more topological and geometrical information into the reconstruction while being much more computationally efficient. - Highlights: • Spatial correlation functions used to characterize filamentary ferrite phase • Clustering information assessed from 3D experimental structure via serial sectioning • Stochastic reconstruction used to generate 3D virtual structure 2D micrograph • Dilation–erosion method to improve accuracy of 3D reconstruction.
NASA Astrophysics Data System (ADS)
de Boer, H. J.; Dekker, S. C.; Wassen, M. J.
2009-04-01
Earth System Models of Intermediate Complexity (EMICs) are popular tools for palaeo climate simulations. Recent studies applied these models in comparison to terrestrial proxy records and aimed to reconstruct changes in seasonal climate forced by altered ocean circulation patterns. To strengthen this powerful methodology, we argue that the magnitude of the simulated atmospheric changes should be considered in relation to the internal variability of both the climate system and the intermediate complexity model. To attribute a shift in modelled climate to reality, this ‘signal' should be detectable above the ‘noise' related to the internal variability of the climate system and the internal variability of the model. Both noise and climate signals vary over the globe and change with the seasons. We therefore argue that spatial explicit fields of noise should be considered in relation to the strengths of the simulated signals at a seasonal timescale. We approximated total noise on terrestrial temperature and precipitation from a 29 member simulation with the EMIC PUMA-2 and global temperature and precipitation datasets. To illustrate this approach, we calculate Signal-to-Noise-Ratios (SNRs) in terrestrial temperature and precipitation on simulations of an El Niño warm event, a phase change in Atlantic Meridional Oscillation (AMO) and a Heinrich cooling event. The results of the El Niño and AMO simulations indicate that the chance to accurately detect a climate signal increases with increasing SNRs. Considering the regions and seasons with highest SNRs, the simulated El Niño anomalies show good agreement with observations (r² = 0.8 and 0.6 for temperature and precipitation at SNRs > 4). The AMO signals rarely surpass the noise levels and remain mostly undetected. The simulation of a Heinrich event predicts highest SNRs for temperature (up to 10) over Arabia and Russia during Boreal winter and spring. Highest SNRs for precipitation (up to 12) are predicted over
NASA Astrophysics Data System (ADS)
Jolivet, L.; Cohen, M.; Ruas, A.
2015-08-01
Landscape influences fauna movement at different levels, from habitat selection to choices of movements' direction. Our goal is to provide a development frame in order to test simulation functions for animal's movement. We describe our approach for such simulations and we compare two types of functions to calculate trajectories. To do so, we first modelled the role of landscape elements to differentiate between elements that facilitate movements and the ones being hindrances. Different influences are identified depending on landscape elements and on animal species. Knowledge were gathered from ecologists, literature and observation datasets. Second, we analysed the description of animal movement recorded with GPS at fine scale, corresponding to high temporal frequency and good location accuracy. Analysing this type of data provides information on the relation between landscape features and movements. We implemented an agent-based simulation approach to calculate potential trajectories constrained by the spatial environment and individual's behaviour. We tested two functions that consider space differently: one function takes into account the geometry and the types of landscape elements and one cost function sums up the spatial surroundings of an individual. Results highlight the fact that the cost function exaggerates the distances travelled by an individual and simplifies movement patterns. The geometry accurate function represents a good bottom-up approach for discovering interesting areas or obstacles for movements.
Webb-Robertson, Bobbie-Jo M.; Cannon, William R.; Oehmen, Christopher S.; Shah, Anuj R.; Gurumoorthi, Vidhya; Lipton, Mary S.; Waters, Katrina M.
2008-07-01
Motivation: The standard approach to identifying peptides based on accurate mass and elution time (AMT) compares these profiles obtained from a high resolution mass spectrometer to a database of peptides previously identified from tandem mass spectrometry (MS/MS) studies. It would be advantageous, with respect to both accuracy and cost, to only search for those peptides that are detectable by MS (proteotypic). Results: We present a Support Vector Machine (SVM) model that uses a simple descriptor space based on 35 properties of amino acid content, charge, hydrophilicity, and polarity for the quantitative prediction of proteotypic peptides. Using three independently derived AMT databases (Shewanella oneidensis, Salmonella typhimurium, Yersinia pestis) for training and validation within and across species, the SVM resulted in an average accuracy measure of ~0.8 with a standard deviation of less than 0.025. Furthermore, we demonstrate that these results are achievable with a small set of 12 variables and can achieve high proteome coverage. Availability: http://omics.pnl.gov/software/STEPP.php
Turabelidze, Anna; Guo, Shujuan; DiPietro, Luisa A
2010-01-01
Studies in the field of wound healing have utilized a variety of different housekeeping genes for reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis. However, nearly all of these studies assume that the selected normalization gene is stably expressed throughout the course of the repair process. The purpose of our current investigation was to identify the most stable housekeeping genes for studying gene expression in mouse wound healing using RT-qPCR. To identify which housekeeping genes are optimal for studying gene expression in wound healing, we examined all articles published in Wound Repair and Regeneration that cited RT-qPCR during the period of January/February 2008 until July/August 2009. We determined that ACTβ, GAPDH, 18S, and β2M were the most frequently used housekeeping genes in human, mouse, and pig studies. We also investigated nine commonly used housekeeping genes that are not generally used in wound healing models: GUS, TBP, RPLP2, ATP5B, SDHA, UBC, CANX, CYC1, and YWHAZ. We observed that wounded and unwounded tissues have contrasting housekeeping gene expression stability. The results demonstrate that commonly used housekeeping genes must be validated as accurate normalizing genes for each individual experimental condition. PMID:20731795
Mui, K W; Wong, L T; Chung, L Y
2009-11-01
Atmospheric visibility impairment has gained increasing concern as it is associated with the existence of a number of aerosols as well as common air pollutants and produces unfavorable conditions for observation, dispersion, and transportation. This study analyzed the atmospheric visibility data measured in urban and suburban Hong Kong (two selected stations) with respect to time-matched mass concentrations of common air pollutants including nitrogen dioxide (NO(2)), nitrogen monoxide (NO), respirable suspended particulates (PM(10)), sulfur dioxide (SO(2)), carbon monoxide (CO), and meteorological parameters including air temperature, relative humidity, and wind speed. No significant difference in atmospheric visibility was reported between the two measurement locations (p > or = 0.6, t test); and good atmospheric visibility was observed more frequently in summer and autumn than in winter and spring (p < 0.01, t test). It was also found that atmospheric visibility increased with temperature but decreased with the concentrations of SO(2), CO, PM(10), NO, and NO(2). The results showed that atmospheric visibility was season dependent and would have significant correlations with temperature, the mass concentrations of PM(10) and NO(2), and the air pollution index API (correlation coefficients mid R: R mid R: > or = 0.7, p < or = 0.0001, t test). Mathematical expressions catering to the seasonal variations of atmospheric visibility were thus proposed. By comparison, the proposed visibility prediction models were more accurate than some existing regional models. In addition to improving visibility prediction accuracy, this study would be useful for understanding the context of low atmospheric visibility, exploring possible remedial measures, and evaluating the impact of air pollution and atmospheric visibility impairment in this region. PMID:18951139
NASA Astrophysics Data System (ADS)
Infantino, Angelo; Marengo, Mario; Baschetti, Serafina; Cicoria, Gianfranco; Longo Vaschetto, Vittorio; Lucconi, Giulia; Massucci, Piera; Vichi, Sara; Zagni, Federico; Mostacci, Domiziano
2015-11-01
Biomedical cyclotrons for production of Positron Emission Tomography (PET) radionuclides and radiotherapy with hadrons or ions are widely diffused and established in hospitals as well as in industrial facilities and research sites. Guidelines for site planning and installation, as well as for radiation protection assessment, are given in a number of international documents; however, these well-established guides typically offer analytic methods of calculation of both shielding and materials activation, in approximate or idealized geometry set up. The availability of Monte Carlo codes with accurate and up-to-date libraries for transport and interactions of neutrons and charged particles at energies below 250 MeV, together with the continuously increasing power of nowadays computers, makes systematic use of simulations with realistic geometries possible, yielding equipment and site specific evaluation of the source terms, shielding requirements and all quantities relevant to radiation protection. In this work, the well-known Monte Carlo code FLUKA was used to simulate two representative models of cyclotron for PET radionuclides production, including their targetry; and one type of proton therapy cyclotron including the energy selection system. Simulations yield estimates of various quantities of radiological interest, including the effective dose distribution around the equipment, the effective number of neutron produced per incident proton and the activation of target materials, the structure of the cyclotron, the energy degrader, the vault walls and the soil. The model was validated against experimental measurements and comparison with well-established reference data. Neutron ambient dose equivalent H*(10) was measured around a GE PETtrace cyclotron: an average ratio between experimental measurement and simulations of 0.99±0.07 was found. Saturation yield of 18F, produced by the well-known 18O(p,n)18F reaction, was calculated and compared with the IAEA recommended
NASA Astrophysics Data System (ADS)
Finger, David; Vis, Marc; Huss, Matthias; Seibert, Jan
2015-04-01
The assessment of snow, glacier, and rainfall runoff contribution to discharge in mountain streams is of major importance for an adequate water resource management. Such contributions can be estimated via hydrological models, provided that the modeling adequately accounts for snow and glacier melt, as well as rainfall runoff. We present a multiple data set calibration approach to estimate runoff composition using hydrological models with three levels of complexity. For this purpose, the code of the conceptual runoff model HBV-light was enhanced to allow calibration and validation of simulations against glacier mass balances, satellite-derived snow cover area and measured discharge. Three levels of complexity of the model were applied to glacierized catchments in Switzerland, ranging from 39 to 103 km2. The results indicate that all three observational data sets are reproduced adequately by the model, allowing an accurate estimation of the runoff composition in the three mountain streams. However, calibration against only runoff leads to unrealistic snow and glacier melt rates. Based on these results, we recommend using all three observational data sets in order to constrain model parameters and compute snow, glacier, and rain contributions. Finally, based on the comparison of model performance of different complexities, we postulate that the availability and use of different data sets to calibrate hydrological models might be more important than model complexity to achieve realistic estimations of runoff composition.
Thermophysical Model of S-complex NEAs: 1627 Ivar
NASA Astrophysics Data System (ADS)
Crowell, Jenna L.; Howell, Ellen S.; Magri, Christopher; Fernandez, Yan R.; Marshall, Sean E.; Warner, Brian D.; Vervack, Ronald J.
2015-11-01
We present updates to the thermophysical model of asteroid 1627 Ivar. Ivar is an Amor class near Earth asteroid (NEA) with a taxonomic type of Sqw [1] and a rotation rate of 4.795162 ± 5.4 * 10-6 hours [2]. In 2013, our group observed Ivar in radar, in CCD lightcurves, and in the near-IR’s reflected and thermal regimes (0.8 - 4.1 µm) using the Arecibo Observatory’s 2380 MHz radar, the Palmer Divide Station’s 0.35m telescope, and the SpeX instrument at the NASA IRTF respectively. Using these radar and lightcurve data, we generated a detailed shape model of Ivar using the software SHAPE [3,4]. Our shape model reveals more surface detail compared to earlier models [5] and we found Ivar to be an elongated asteroid with the maximum extended length along the three body-fixed coordinates being 12 x 11.76 x 6 km. For our thermophysical modeling, we have used SHERMAN [6,7] with input parameters such as the asteroid’s IR emissivity, optical scattering law and thermal inertia, in order to complete thermal computations based on our shape model and the known spin state. We then create synthetic near-IR spectra that can be compared to our observed spectra, which cover a wide range of Ivar’s rotational longitudes and viewing geometries. As has been noted [6,8], the use of an accurate shape model is often crucial for correctly interpreting multi-epoch thermal emission observations. We will present what SHERMAN has let us determine about the reflective, thermal, and surface properties for Ivar that best reproduce our spectra. From our derived best-fit thermal parameters, we will learn more about the regolith, surface properties, and heterogeneity of Ivar and how those properties compare to those of other S-complex asteroids. References: [1] DeMeo et al. 2009, Icarus 202, 160-180 [2] Crowell, J. et al. 2015, LPSC 46 [3] Magri C. et al. 2007, Icarus 186, 152-177 [4] Crowell, J. et al. 2014, AAS/DPS 46 [5] Kaasalainen, M. et al. 2004, Icarus 167, 178-196 [6] Crowell, J. et
Modeling Complex Workflow in Molecular Diagnostics
Gomah, Mohamed E.; Turley, James P.; Lu, Huimin; Jones, Dan
2010-01-01
One of the hurdles to achieving personalized medicine has been implementing the laboratory processes for performing and reporting complex molecular tests. The rapidly changing test rosters and complex analysis platforms in molecular diagnostics have meant that many clinical laboratories still use labor-intensive manual processing and testing without the level of automation seen in high-volume chemistry and hematology testing. We provide here a discussion of design requirements and the results of implementation of a suite of lab management tools that incorporate the many elements required for use of molecular diagnostics in personalized medicine, particularly in cancer. These applications provide the functionality required for sample accessioning and tracking, material generation, and testing that are particular to the evolving needs of individualized molecular diagnostics. On implementation, the applications described here resulted in improvements in the turn-around time for reporting of more complex molecular test sets, and significant changes in the workflow. Therefore, careful mapping of workflow can permit design of software applications that simplify even the complex demands of specialized molecular testing. By incorporating design features for order review, software tools can permit a more personalized approach to sample handling and test selection without compromising efficiency. PMID:20007844
APPLICATION OF SURFACE COMPLEXATION MODELS TO SOIL SYSTEMS
Technology Transfer Automated Retrieval System (TEKTRAN)
Chemical surface complexation models were developed to describe potentiometric titration and ion adsorption data on oxide minerals. These models provide molecular descriptions of adsorption using an equilibrium approach that defines surface species, chemical reactions, mass and charge balances and ...
Koesters, Thomas; Friedman, Kent P.; Fenchel, Matthias; Zhan, Yiqiang; Hermosillo, Gerardo; Babb, James; Jelescu, Ileana O.; Faul, David; Boada, Fernando E.; Shepherd, Timothy M.
2016-01-01
Simultaneous PET/MR of the brain is a promising new technology for characterizing patients with suspected cognitive impairment or epilepsy. Unlike CT though, MR signal intensities do not provide a direct correlate to PET photon attenuation correction (AC) and inaccurate radiotracer standard uptake value (SUV) estimation could limit future PET/MR clinical applications. We tested a novel AC method that supplements standard Dixon-based tissue segmentation with a superimposed model-based bone compartment. Methods We directly compared SUV estimation for MR-based AC methods to reference CT AC in 16 patients undergoing same-day, single 18FDG dose PET/CT and PET/MR for suspected neurodegeneration. Three Dixon-based MR AC methods were compared to CT – standard Dixon 4-compartment segmentation alone, Dixon with a superimposed model-based bone compartment, and Dixon with a superimposed bone compartment and linear attenuation correction optimized specifically for brain tissue. The brain was segmented using a 3D T1-weighted volumetric MR sequence and SUV estimations compared to CT AC for whole-image, whole-brain and 91 FreeSurfer-based regions-of-interest. Results Modifying the linear AC value specifically for brain and superimposing a model-based bone compartment reduced whole-brain SUV estimation bias of Dixon-based PET/MR AC by 95% compared to reference CT AC (P < 0.05) – this resulted in a residual −0.3% whole-brain mean SUV bias. Further, brain regional analysis demonstrated only 3 frontal lobe regions with SUV estimation bias of 5% or greater (P < 0.05). These biases appeared to correlate with high individual variability in the frontal bone thickness and pneumatization. Conclusion Bone compartment and linear AC modifications result in a highly accurate MR AC method in subjects with suspected neurodegeneration. This prototype MR AC solution appears equivalent than other recently proposed solutions, and does not require additional MR sequences and scan time. These
Hostaš, Jiří; Jakubec, Dávid; Laskowski, Roman A; Gnanasekaran, Ramachandran; Řezáč, Jan; Vondrášek, Jiří; Hobza, Pavel
2015-09-01
Representative pairs of amino acid side chains and nucleic acid bases extracted from available high-quality structures of protein-DNA complexes were analyzed using a range of computational methods. CCSD(T)/CBS interaction energies were calculated for the chosen 272 pairs. These reference interaction energies were used to test the MP2.5/CBS, MP2.X/CBS, MP2-F12, DFT-D3, PM6, and Amber force field methods. Method MP2.5 provided excellent agreement with reference data (root-mean-square error (RMSE) of 0.11 kcal/mol), which is more than 1 order of magnitude faster than the CCSD(T) method. When MP2-F12 and MP2.5 were combined, the results were within reasonable accuracy (0.20 kcal/mol), with a computational savings of almost 2 orders of magnitude. Therefore, this method is a promising tool for accurate calculations of interaction energies in protein-DNA motifs of up to ∼100 atoms, for which CCSD(T)/CBS benchmark calculations are not feasible. B3-LYP-D3 calculated with def2-TZVPP and def2-QZVP basis sets yielded sufficiently good results with a reasonably small RMSE. This method provided better results for neutral systems, whereas positively charged species exhibited the worst agreement with the benchmark data. The Amber force field yielded unbalanced results-performing well for systems containing nonpolar amino acids but severely underestimating interaction energies for charged complexes. The semiempirical PM6 method with corrections for hydrogen bonding and dispersion energy (PM6-D3H4) exhibited considerably smaller error than the Amber force field, which makes it an effective tool for modeling extended protein-ligand complexes (of up to 10,000 atoms). PMID:26575904
Dispersion Modeling in Complex Urban Systems
Models are used to represent real systems in an understandable way. They take many forms. A conceptual model explains the way a system works. In environmental studies, for example, a conceptual model may delineate all the factors and parameters for determining how a particle move...
Specifying and Refining a Complex Measurement Model.
ERIC Educational Resources Information Center
Levy, Roy; Mislevy, Robert J.
This paper aims to describe a Bayesian approach to modeling and estimating cognitive models both in terms of statistical machinery and actual instrument development. Such a method taps the knowledge of experts to provide initial estimates for the probabilistic relationships among the variables in a multivariate latent variable model and refines…
Turbulence modeling for complex hypersonic flows
NASA Technical Reports Server (NTRS)
Huang, P. G.; Coakley, T. J.
1993-01-01
The paper presents results of calculations for a range of 2D turbulent hypersonic flows using two-equation models. The baseline models and the model corrections required for good hypersonic-flow predictions will be illustrated. Three experimental data sets were chosen for comparison. They are: (1) the hypersonic flare flows of Kussoy and Horstman, (2) a 2D hypersonic compression corner flow of Coleman and Stollery, and (3) the ogive-cylinder impinging shock-expansion flows of Kussoy and Horstman. Comparisons with the experimental data have shown that baseline models under-predict the extent of flow separation but over-predict the heat transfer rate near flow reattachment. Modifications to the models are described which remove the above-mentioned deficiencies. Although we have restricted the discussion only to the selected baseline models in this paper, the modifications proposed are universal and can in principle be transferred to any existing two-equation model formulation.
Baspinar, Alper; Cukuroglu, Engin; Nussinov, Ruth; Keskin, Ozlem; Gursoy, Attila
2014-07-01
The PRISM web server enables fast and accurate prediction of protein-protein interactions (PPIs). The prediction algorithm is knowledge-based. It combines structural similarity and accounts for evolutionary conservation in the template interfaces. The predicted models are stored in its repository. Given two protein structures, PRISM will provide a structural model of their complex if a matching template interface is available. Users can download the complex structure, retrieve the interface residues and visualize the complex model. The PRISM web server is user friendly, free and open to all users at http://cosbi.ku.edu.tr/prism. PMID:24829450
Green, Christopher T.; Zhang, Yong; Jurgens, Bryant C.; Starn, J. Jeffrey; Landon, Matthew K.
2014-01-01
Analytical models of the travel time distribution (TTD) from a source area to a sample location are often used to estimate groundwater ages and solute concentration trends. The accuracies of these models are not well known for geologically complex aquifers. In this study, synthetic datasets were used to quantify the accuracy of four analytical TTD models as affected by TTD complexity, observation errors, model selection, and tracer selection. Synthetic TTDs and tracer data were generated from existing numerical models with complex hydrofacies distributions for one public-supply well and 14 monitoring wells in the Central Valley, California. Analytical TTD models were calibrated to synthetic tracer data, and prediction errors were determined for estimates of TTDs and conservative tracer (NO3−) concentrations. Analytical models included a new, scale-dependent dispersivity model (SDM) for two-dimensional transport from the watertable to a well, and three other established analytical models. The relative influence of the error sources (TTD complexity, observation error, model selection, and tracer selection) depended on the type of prediction. Geological complexity gave rise to complex TTDs in monitoring wells that strongly affected errors of the estimated TTDs. However, prediction errors for NO3− and median age depended more on tracer concentration errors. The SDM tended to give the most accurate estimates of the vertical velocity and other predictions, although TTD model selection had minor effects overall. Adding tracers improved predictions if the new tracers had different input histories. Studies using TTD models should focus on the factors that most strongly affect the desired predictions.
Studying complex chemistries using PLASIMO's global model
NASA Astrophysics Data System (ADS)
Koelman, PMJ; Tadayon Mousavi, S.; Perillo, R.; Graef, WAAD; Mihailova, DB; van Dijk, J.
2016-02-01
The Plasimo simulation software is used to construct a Global Model of a CO2 plasma. A DBD plasma between two coaxial cylinders is considered, which is driven by a triangular input power pulse. The plasma chemistry is studied during this power pulse and in the afterglow. The model consists of 71 species that interact in 3500 reactions. Preliminary results from the model are presented. The model has been validated by comparing its results with those presented in Kozák et al. (Plasma Sources Science and Technology 23(4) p. 045004, 2014). A good qualitative agreement has been reached; potential sources of remaining discrepancies are extensively discussed.
A 3D modeling approach to complex faults with multi-source data
NASA Astrophysics Data System (ADS)
Wu, Qiang; Xu, Hua; Zou, Xukai; Lei, Hongzhuan
2015-04-01
Fault modeling is a very important step in making an accurate and reliable 3D geological model. Typical existing methods demand enough fault data to be able to construct complex fault models, however, it is well known that the available fault data are generally sparse and undersampled. In this paper, we propose a workflow of fault modeling, which can integrate multi-source data to construct fault models. For the faults that are not modeled with these data, especially small-scale or approximately parallel with the sections, we propose the fault deduction method to infer the hanging wall and footwall lines after displacement calculation. Moreover, using the fault cutting algorithm can supplement the available fault points on the location where faults cut each other. Increasing fault points in poor sample areas can not only efficiently construct fault models, but also reduce manual intervention. By using a fault-based interpolation and remeshing the horizons, an accurate 3D geological model can be constructed. The method can naturally simulate geological structures no matter whether the available geological data are sufficient or not. A concrete example of using the method in Tangshan, China, shows that the method can be applied to broad and complex geological areas.
Multiscale Computational Models of Complex Biological Systems
Walpole, Joseph; Papin, Jason A.; Peirce, Shayn M.
2014-01-01
Integration of data across spatial, temporal, and functional scales is a primary focus of biomedical engineering efforts. The advent of powerful computing platforms, coupled with quantitative data from high-throughput experimental platforms, has allowed multiscale modeling to expand as a means to more comprehensively investigate biological phenomena in experimentally relevant ways. This review aims to highlight recently published multiscale models of biological systems while using their successes to propose the best practices for future model development. We demonstrate that coupling continuous and discrete systems best captures biological information across spatial scales by selecting modeling techniques that are suited to the task. Further, we suggest how to best leverage these multiscale models to gain insight into biological systems using quantitative, biomedical engineering methods to analyze data in non-intuitive ways. These topics are discussed with a focus on the future of the field, the current challenges encountered, and opportunities yet to be realized. PMID:23642247
NASA Astrophysics Data System (ADS)
Zhang, Jianying; Yan, Guangwu
2015-12-01
A spatiotemporal lattice Boltzmann model for solving the three-dimensional cubic-quintic complex Ginzburg-Landau equation (CQCGLE) is proposed. Different from the classic lattice Boltzmann models, this lattice Boltzmann model is based on uniformly distributed lattice points in a three-dimensional spatiotemporal space, and the evolution of the model is about a spatial axis rather than time. The algorithm possesses advantages similar to the lattice Boltzmann method in that it is easily adapted to complex Ginzburg-Landau equations. Examples show that the model reproduces the phenomena in the CQCGLE accurately.
Information, complexity and efficiency: The automobile model
Allenby, B. |
1996-08-08
The new, rapidly evolving field of industrial ecology - the objective, multidisciplinary study of industrial and economic systems and their linkages with fundamental natural systems - provides strong ground for believing that a more environmentally and economically efficient economy will be more information intensive and complex. Information and intellectual capital will be substituted for the more traditional inputs of materials and energy in producing a desirable, yet sustainable, quality of life. While at this point this remains a strong hypothesis, the evolution of the automobile industry can be used to illustrate how such substitution may, in fact, already be occurring in an environmentally and economically critical sector.
NASA Astrophysics Data System (ADS)
Valentine, A. P.; Kaeufl, P.; De Wit, R. W. L.; Trampert, J.
2014-12-01
Obtaining knowledge about source parameters in (near) real-time during or shortly after an earthquake is essential for mitigating damage and directing resources in the aftermath of the event. Therefore, a variety of real-time source-inversion algorithms have been developed over recent decades. This has been driven by the ever-growing availability of dense seismograph networks in many seismogenic areas of the world and the significant advances in real-time telemetry. By definition, these algorithms rely on short time-windows of sparse, local and regional observations, resulting in source estimates that are highly sensitive to observational errors, noise and missing data. In order to obtain estimates more rapidly, many algorithms are either entirely based on empirical scaling relations or make simplifying assumptions about the Earth's structure, which can in turn lead to biased results. It is therefore essential that realistic uncertainty bounds are estimated along with the parameters. A natural means of propagating probabilistic information on source parameters through the entire processing chain from first observations to potential end users and decision makers is provided by the Bayesian formalism.We present a novel method based on pattern recognition allowing us to incorporate highly accurate physical modelling into an uncertainty-aware real-time inversion algorithm. The algorithm is based on a pre-computed Green's functions database, containing a large set of source-receiver paths in a highly heterogeneous crustal model. Unlike similar methods, which often employ a grid search, we use a supervised learning algorithm to relate synthetic waveforms to point source parameters. This training procedure has to be performed only once and leads to a representation of the posterior probability density function p(m|d) --- the distribution of source parameters m given observations d --- which can be evaluated quickly for new data.Owing to the flexibility of the pattern
Sensitivity Analysis in Complex Plasma Chemistry Models
NASA Astrophysics Data System (ADS)
Turner, Miles
2015-09-01
The purpose of a plasma chemistry model is prediction of chemical species densities, including understanding the mechanisms by which such species are formed. These aims are compromised by an uncertain knowledge of the rate constants included in the model, which directly causes uncertainty in the model predictions. We recently showed that this predictive uncertainty can be large--a factor of ten or more in some cases. There is probably no context in which a plasma chemistry model might be used where the existence of uncertainty on this scale could not be a matter of concern. A question that at once follows is: Which rate constants cause such uncertainty? In the present paper we show how this question can be answered by applying a systematic screening procedure--the so-called Morris method--to identify sensitive rate constants. We investigate the topical example of the helium-oxygen chemistry. Beginning with a model with almost four hundred reactions, we show that only about fifty rate constants materially affect the model results, and as few as ten cause most of the uncertainty. This means that the model can be improved, and the uncertainty substantially reduced, by focussing attention on this tractably small set of rate constants. Work supported by Science Foundation Ireland under grant08/SRC/I1411, and by COST Action MP1101 ``Biomedical Applications of Atmospheric Pressure Plasmas.''
Modeling Power Systems as Complex Adaptive Systems
Chassin, David P.; Malard, Joel M.; Posse, Christian; Gangopadhyaya, Asim; Lu, Ning; Katipamula, Srinivas; Mallow, J V.
2004-12-30
Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.
Uniform surface complexation approaches to radionuclide sorption modeling
Turner, D.R.; Pabalan, R.T.; Muller, P.; Bertetti, F.P.
1995-12-01
Simplified surface complexation models, based on a uniform set of model parameters have been developed to address complex radionuclide sorption behavior. Existing data have been examined, and interpreted using numerical nonlinear least-squares optimization techniques to determine the necessary binding constants. Simplified modeling approaches have generally proven successful at simulating and predicting radionuclide sorption on (hydr)oxides and aluminosilicates over a wide range of physical and chemical conditions.
NASA Astrophysics Data System (ADS)
Kim, Jibeom; Jeon, Joonhyeon
2015-01-01
Recently, related studies on Equation Of State (EOS) have reported that generalized van der Waals (GvdW) shows poor representations in the near critical region for non-polar and non-sphere molecules. Hence, there are still remains a problem of GvdW parameters to minimize loss in describing saturated vapor densities and vice versa. This paper describes a recursive model GvdW (rGvdW) for an accurate representation of pure fluid materials in the near critical region. For the performance evaluation of rGvdW in the near critical region, other EOS models are also applied together with two pure molecule group: alkane and amine. The comparison results show rGvdW provides much more accurate and reliable predictions of pressure than the others. The calculating model of EOS through this approach gives an additional insight into the physical significance of accurate prediction of pressure in the nearcritical region.
NASA Astrophysics Data System (ADS)
Olmsted, Peter
2004-03-01
"Shear banding", i.e. flow-induced macroscopic "phase coexistence" or apparent "phase transitions", has been observed in many complex fluids, including wormlike micelles, lamellar systems, associating polymers, and liquid crystals. In this talk I will review this behavior, and discuss a general phenomenology for understanding shear banding and flow-induced phase separation in complex fluids, at a "thermodynamic" level (as opposed to a "statistical mechanics" level). An accurate theory must include the relevant microstructural order parameters, and construct the fully coupled spatially-dependent hydrodynamic equations of motion. Although this has been successfully done for very few model fluids, we can nonetheless obtain general rules for the "phase behavior". Perhaps surprisingly, the interface between coexisting phases plays a crucial role in determining the steady state behavior, and is much more important than its equilibrium counterpart. I will discuss recent work addressed at the kinetics and morphology of wormlike micellar solutions, and touch on models for more complex oscillatory and possibly chaotic systems.
Integrated Modeling of Complex Optomechanical Systems
NASA Astrophysics Data System (ADS)
Andersen, Torben; Enmark, Anita
2011-09-01
Mathematical modeling and performance simulation are playing an increasing role in large, high-technology projects. There are two reasons; first, projects are now larger than they were before, and the high cost calls for detailed performance prediction before construction. Second, in particular for space-related designs, it is often difficult to test systems under realistic conditions beforehand, and mathematical modeling is then needed to verify in advance that a system will work as planned. Computers have become much more powerful, permitting calculations that were not possible before. At the same time mathematical tools have been further developed and found acceptance in the community. Particular progress has been made in the fields of structural mechanics, optics and control engineering, where new methods have gained importance over the last few decades. Also, methods for combining optical, structural and control system models into global models have found widespread use. Such combined models are usually called integrated models and were the subject of this symposium. The objective was to bring together people working in the fields of groundbased optical telescopes, ground-based radio telescopes, and space telescopes. We succeeded in doing so and had 39 interesting presentations and many fruitful discussions during coffee and lunch breaks and social arrangements. We are grateful that so many top ranked specialists found their way to Kiruna and we believe that these proceedings will prove valuable during much future work.
The Creation of Surrogate Models for Fast Estimation of Complex Model Outcomes
Pruett, W. Andrew; Hester, Robert L.
2016-01-01
A surrogate model is a black box model that reproduces the output of another more complex model at a single time point. This is to be distinguished from the method of surrogate data, used in time series. The purpose of a surrogate is to reduce the time necessary for a computation at the cost of rigor and generality. We describe a method of constructing surrogates in the form of support vector machine (SVM) regressions for the purpose of exploring the parameter space of physiological models. Our focus is on the methodology of surrogate creation and accuracy assessment in comparison to the original model. This is done in the context of a simulation of hemorrhage in one model, “Small”, and renal denervation in another, HumMod. In both cases, the surrogate predicts the drop in mean arterial pressure following the intervention. We asked three questions concerning surrogate models: (1) how many training examples are necessary to obtain an accurate surrogate, (2) is surrogate accuracy homogeneous, and (3) how much can computation time be reduced when using a surrogate. We found the minimum training set size that would guarantee maximal accuracy was widely variable, but could be algorithmically generated. The average error for the pressure response to the protocols was -0.05±2.47 in Small, and -0.3 +/- 3.94 mmHg in HumMod. In the Small model, error grew with actual pressure drop, and in HumMod, larger pressure drops were overestimated by the surrogates. Surrogate use resulted in a 6 order of magnitude decrease in computation time. These results suggest surrogate modeling is a valuable tool for generating predictions of an integrative model’s behavior on densely sampled subsets of its parameter space. PMID:27258010
A statistical model of ChIA-PET data for accurate detection of chromatin 3D interactions
Paulsen, Jonas; Rødland, Einar A.; Holden, Lars; Holden, Marit; Hovig, Eivind
2014-01-01
Identification of three-dimensional (3D) interactions between regulatory elements across the genome is crucial to unravel the complex regulatory machinery that orchestrates proliferation and differentiation of cells. ChIA-PET is a novel method to identify such interactions, where physical contacts between regions bound by a specific protein are quantified using next-generation sequencing. However, determining the significance of the observed interaction frequencies in such datasets is challenging, and few methods have been proposed. Despite the fact that regions that are close in linear genomic distance have a much higher tendency to interact by chance, no methods to date are capable of taking such dependency into account. Here, we propose a statistical model taking into account the genomic distance relationship, as well as the general propensity of anchors to be involved in contacts overall. Using both real and simulated data, we show that the previously proposed statistical test, based on Fisher's exact test, leads to invalid results when data are dependent on genomic distance. We also evaluate our method on previously validated cell-line specific and constitutive 3D interactions, and show that relevant interactions are significant, while avoiding over-estimating the significance of short nearby interactions. PMID:25114054
The sigma model on complex projective superspaces
NASA Astrophysics Data System (ADS)
Candu, Constantin; Mitev, Vladimir; Quella, Thomas; Saleur, Hubert; Schomerus, Volker
2010-02-01
The sigma model on projective superspaces mathbb{C}{mathbb{P}^{S - 1left| S right.}} gives rise to a continuous family of interacting 2D conformal field theories which are parametrized by the curvature radius R and the theta angle θ. Our main goal is to determine the spectrum of the model, non-perturbatively as a function of both parameters. We succeed to do so for all open boundary conditions preserving the full global symmetry of the model. In string theory parlor, these correspond to volume filling branes that are equipped with a monopole line bundle and connection. The paper consists of two parts. In the first part, we approach the problem within the continuum formulation. Combining combinatorial arguments with perturbative studies and some simple free field calculations, we determine a closed formula for the partition function of the theory. This is then tested numerically in the second part. There we extend the proposal of [
A simple model clarifies the complicated relationships of complex networks
NASA Astrophysics Data System (ADS)
Zheng, Bojin; Wu, Hongrun; Kuang, Li; Qin, Jun; Du, Wenhua; Wang, Jianmin; Li, Deyi
2014-08-01
Real-world networks such as the Internet and WWW have many common traits. Until now, hundreds of models were proposed to characterize these traits for understanding the networks. Because different models used very different mechanisms, it is widely believed that these traits origin from different causes. However, we find that a simple model based on optimisation can produce many traits, including scale-free, small-world, ultra small-world, Delta-distribution, compact, fractal, regular and random networks. Moreover, by revising the proposed model, the community-structure networks are generated. By this model and the revised versions, the complicated relationships of complex networks are illustrated. The model brings a new universal perspective to the understanding of complex networks and provide a universal method to model complex networks from the viewpoint of optimisation.
A simple model clarifies the complicated relationships of complex networks
Zheng, Bojin; Wu, Hongrun; Kuang, Li; Qin, Jun; Du, Wenhua; Wang, Jianmin; Li, Deyi
2014-01-01
Real-world networks such as the Internet and WWW have many common traits. Until now, hundreds of models were proposed to characterize these traits for understanding the networks. Because different models used very different mechanisms, it is widely believed that these traits origin from different causes. However, we find that a simple model based on optimisation can produce many traits, including scale-free, small-world, ultra small-world, Delta-distribution, compact, fractal, regular and random networks. Moreover, by revising the proposed model, the community-structure networks are generated. By this model and the revised versions, the complicated relationships of complex networks are illustrated. The model brings a new universal perspective to the understanding of complex networks and provide a universal method to model complex networks from the viewpoint of optimisation. PMID:25160506
Improving phylogenetic regression under complex evolutionary models.
Mazel, Florent; Davies, T Jonathan; Georges, Damien; Lavergne, Sébastien; Thuiller, Wilfried; Peres-NetoO, Pedro R
2016-02-01
Phylogenetic Generalized Least Square (PGLS) is the tool of choice among phylogenetic comparative methods to measure the correlation between species features such as morphological and life-history traits or niche characteristics. In its usual form, it assumes that the residual variation follows a homogenous model of evolution across the branches of the phylogenetic tree. Since a homogenous model of evolution is unlikely to be realistic in nature, we explored the robustness of the phylogenetic regression when this assumption is violated. We did so by simulating a set of traits under various heterogeneous models of evolution, and evaluating the statistical performance (type I error [the percentage of tests based on samples that incorrectly rejected a true null hypothesis] and power [the percentage of tests that correctly rejected a false null hypothesis]) of classical phylogenetic regression. We found that PGLS has good power but unacceptable type I error rates. This finding is important since this method has been increasingly used in comparative analyses over the last decade. To address this issue, we propose a simple solution based on transforming the underlying variance-covariance matrix to adjust for model heterogeneity within PGLS. We suggest that heterogeneous rates of evolution might be particularly prevalent in large phylogenetic trees, while most current approaches assume a homogenous rate of evolution. Our analysis demonstrates that overlooking rate heterogeneity can result in inflated type I errors, thus misleading comparative analyses. We show that it is possible to correct for this bias even when the underlying model of evolution is not known a priori. PMID:27145604
A musculoskeletal model of the elbow joint complex
NASA Technical Reports Server (NTRS)
Gonzalez, Roger V.; Barr, Ronald E.; Abraham, Lawrence D.
1993-01-01
This paper describes a musculoskeletal model that represents human elbow flexion-extension and forearm pronation-supination. Musculotendon parameters and the skeletal geometry were determined for the musculoskeletal model in the analysis of ballistic elbow joint complex movements. The key objective was to develop a computational model, guided by optimal control, to investigate the relationship among patterns of muscle excitation, individual muscle forces, and movement kinematics. The model was verified using experimental kinematic, torque, and electromyographic data from volunteer subjects performing both isometric and ballistic elbow joint complex movements. In general, the model predicted kinematic and muscle excitation patterns similar to what was experimentally measured.
Blueprints for Complex Learning: The 4C/ID-Model.
ERIC Educational Resources Information Center
van Merrienboer, Jeroen J. G.; Clark, Richard E.; de Croock, Marcel B. M.
2002-01-01
Describes the four-component instructional design system (4C/ID-model) developed for the design of training programs for complex skills. Discusses the structure of training blueprints for complex learning and associated instructional methods, focusing on learning tasks, supportive information, just-in-time information, and part-task practice.…
Classrooms as Complex Adaptive Systems: A Relational Model
ERIC Educational Resources Information Center
Burns, Anne; Knox, John S.
2011-01-01
In this article, we describe and model the language classroom as a complex adaptive system (see Logan & Schumann, 2005). We argue that linear, categorical descriptions of classroom processes and interactions do not sufficiently explain the complex nature of classrooms, and cannot account for how classroom change occurs (or does not occur), over…
Lee, Mi Kyung; Coker, David F
2016-08-18
An accurate approach for computing intermolecular and intrachromophore contributions to spectral densities to describe the electronic-nuclear interactions relevant for modeling excitation energy transfer processes in light harvesting systems is presented. The approach is based on molecular dynamics (MD) calculations of classical correlation functions of long-range contributions to excitation energy fluctuations and a separate harmonic analysis and single-point gradient quantum calculations for electron-intrachromophore vibrational couplings. A simple model is also presented that enables detailed analysis of the shortcomings of standard MD-based excitation energy fluctuation correlation function approaches. The method introduced here avoids these problems, and its reliability is demonstrated in accurate predictions for bacteriochlorophyll molecules in the Fenna-Matthews-Olson pigment-protein complex, where excellent agreement with experimental spectral densities is found. This efficient approach can provide instantaneous spectral densities for treating the influence of fluctuations in environmental dissipation on fast electronic relaxation. PMID:27472379
Kairn, T.; Kenny, J.; Crowe, S. B.; Fielding, A. L.; Franich, R. D.; Johnston, P. N.; Knight, R. T.; Langton, C. M.; Schlect, D.; Trapp, J. V.
2010-04-15
Purpose: The component modules in the standard BEAMnrc distribution may appear to be insufficient to model micro-multileaf collimators that have trifaceted leaf ends and complex leaf profiles. This note indicates, however, that accurate Monte Carlo simulations of radiotherapy beams defined by a complex collimation device can be completed using BEAMnrc's standard VARMLC component module. Methods: That this simple collimator model can produce spatially and dosimetrically accurate microcollimated fields is illustrated using comparisons with ion chamber and film measurements of the dose deposited by square and irregular fields incident on planar, homogeneous water phantoms. Results: Monte Carlo dose calculations for on-axis and off-axis fields are shown to produce good agreement with experimental values, even on close examination of the penumbrae. Conclusions: The use of a VARMLC model of the micro-multileaf collimator, along with a commissioned model of the associated linear accelerator, is therefore recommended as an alternative to the development or use of in-house or third-party component modules for simulating stereotactic radiotherapy and radiosurgery treatments. Simulation parameters for the VARMLC model are provided which should allow other researchers to adapt and use this model to study clinical stereotactic radiotherapy treatments.
Impact of data quality and model complexity on prediction of pesticide leaching.
Dann, R L; Close, M E; Lee, R; Pang, L
2006-01-01
Accurate input data for leaching models are expensive and difficult to obtain which may lead to the use of "general" non-site-specific input data. This study investigated the effect of using different quality data on model outputs. Three models of varying complexity, GLEAMS, LEACHM, and HYDRUS-2D, were used to simulate pesticide leaching at a field trial near Hamilton, New Zealand, on an allophanic silt loam using input data of varying quality. Each model was run for four different pesticides (hexazinone, procymidone, picloram and triclopyr); three different sets of pesticide sorption and degradation parameters (i.e., site optimized, laboratory derived, and sourced from the USDA Pesticide Properties Database); and three different sets of soil physical data of varying quality (i.e., site specific, regional database, and particle size distribution data). We found that the selection of site-optimized pesticide sorption (Koc) and degradation parameters (half-life), compared to the use of more general database derived values, had significantly more impact than the quality of the soil input data used, but interestingly also more impact than the choice of the models. Models run with pesticide sorption and degradation parameters derived from observed solute concentrations data provided simulation outputs with goodness-of-fit values closest to optimum, followed by laboratory-derived parameters, with the USDA parameters providing the least accurate simulations. In general, when using pesticide sorption and degradation parameters optimized from site solute concentrations, the more complex models (LEACHM and HYDRUS-2D) were more accurate. However, when using USDA database derived parameters, all models performed about equally. PMID:16510708
Felmy, Andrew R.; Mason, Marvin J.; Qafoku, Odeta; Dixon, David A.
2005-04-19
This symposium manuscript describes the development of an accurate aqueous thermodynamic model for predicting the speciation of Sr in the waste tanks at the Hanford site. A systematic approach is described that details the studies performed to define the most important inorganic and organic complexation reactions as well as the effects of other important metal ions that compete with Sr for complexation reactions with the chelates. By using this approach we were able to define a reduced set of inorganic complexation, organic complexation, and competing metal reactions that best represent the much more complex waste tank chemical system. A summary is presented of the final thermodynamic model for the system Na-Ca-Sr-OH-CO3-NO3-EDTA-HEDTA-H2O from 25 to 75 ºC that was previously published in a variety of sources. Previously unpublished experimental data are also given for the competing metal Ni as well for certain chemical systems, Na-Sr-CO3-PO4-H2O, and for the solubility of amorphous iron hydroxide in the presence of several organic chelating agents. These data were not used in model development but were key to the final selection of the specific chemical systems prioritized for detailed study.
NASA Astrophysics Data System (ADS)
Huang, X.; Bandilla, K.; Celia, M. A.; Bachu, S.
2013-12-01
Geological carbon sequestration can significantly contribute to climate-change mitigation only if it is deployed at a very large scale. This means that injection scenarios must occur, and be analyzed, at the basin scale. Various mathematical models of different complexity may be used to assess the fate of injected CO2 and/or resident brine. These models span the range from multi-dimensional, multi-phase numerical simulators to simple single-phase analytical solutions. In this study, we consider a range of models, all based on vertically-integrated governing equations, to predict the basin-scale pressure response to specific injection scenarios. The Canadian section of the Basal Aquifer is used as a test site to compare the different modeling approaches. The model domain covers an area of approximately 811,000 km2, and the total injection rate is 63 Mt/yr, corresponding to 9 locations where large point sources have been identified. Predicted areas of critical pressure exceedance are used as a comparison metric among the different modeling approaches. Comparison of the results shows that single-phase numerical models may be good enough to predict the pressure response over a large aquifer; however, a simple superposition of semi-analytical or analytical solutions is not sufficiently accurate because spatial variability of formation properties plays an important role in the problem, and these variations are not captured properly with simple superposition. We consider two different injection scenarios: injection at the source locations and injection at locations with more suitable aquifer properties. Results indicate that in formations with significant spatial variability of properties, strong variations in injectivity among the different source locations can be expected, leading to the need to transport the captured CO2 to suitable injection locations, thereby necessitating development of a pipeline network. We also consider the sensitivity of porosity and
Prequential Analysis of Complex Data with Adaptive Model Reselection†
Clarke, Jennifer; Clarke, Bertrand
2010-01-01
In Prequential analysis, an inference method is viewed as a forecasting system, and the quality of the inference method is based on the quality of its predictions. This is an alternative approach to more traditional statistical methods that focus on the inference of parameters of the data generating distribution. In this paper, we introduce adaptive combined average predictors (ACAPs) for the Prequential analysis of complex data. That is, we use convex combinations of two different model averages to form a predictor at each time step in a sequence. A novel feature of our strategy is that the models in each average are re-chosen adaptively at each time step. To assess the complexity of a given data set, we introduce measures of data complexity for continuous response data. We validate our measures in several simulated contexts prior to using them in real data examples. The performance of ACAPs is compared with the performances of predictors based on stacking or likelihood weighted averaging in several model classes and in both simulated and real data sets. Our results suggest that ACAPs achieve a better trade off between model list bias and model list variability in cases where the data is very complex. This implies that the choices of model class and averaging method should be guided by a concept of complexity matching, i.e. the analysis of a complex data set may require a more complex model class and averaging strategy than the analysis of a simpler data set. We propose that complexity matching is akin to a bias–variance tradeoff in statistical modeling. PMID:20617104
Felmy, Andrew R.; Qafoku, Odeta
2004-09-01
An aqueous thermodynamic model is developed which accurately describes the effects of high base concentration on the complexation of Ni2+ by ethylenedinitrilotetraacetic acid (EDTA). The model is primarily developed from an extensive data on the solubility of Ni(OH)2(c) in the presence of EDTA and in the presence and absence of Ca2+ as the competing metal ion. The solubility data for Ni(OH)2(c) were obtained in solutions ranging in NaOH concentration from 0.01 to 11.6m, and in Ca 2+ concentrations extending to saturation with respect to portlandite, Ca(OH)2. Owing to the inert nature of the Ni-EDTA complexation reactions, solubility experiments were approached from both the oversaturation and undersaturation direction and over time frames extending to 413 days. The final aqueous thermodynamic model is based upon the equations of Pitzer, accurately predicts the observed solubilities to concentrations as high as 11.6m NaOH, and is consistent with UV-Vis spectroscopic studies of the complexes in solution.
Hettinger, Lawrence J.; Kirlik, Alex; Goh, Yang Miang; Buckle, Peter
2015-01-01
Accurate comprehension and analysis of complex sociotechnical systems is a daunting task. Empirically examining, or simply envisioning the structure and behaviour of such systems challenges traditional analytic and experimental approaches as well as our everyday cognitive capabilities. Computer-based models and simulations afford potentially useful means of accomplishing sociotechnical system design and analysis objectives. From a design perspective, they can provide a basis for a common mental model among stakeholders, thereby facilitating accurate comprehension of factors impacting system performance and potential effects of system modifications. From a research perspective, models and simulations afford the means to study aspects of sociotechnical system design and operation, including the potential impact of modifications to structural and dynamic system properties, in ways not feasible with traditional experimental approaches. This paper describes issues involved in the design and use of such models and simulations and describes a proposed path forward to their development and implementation. Practitioner Summary: The size and complexity of real-world sociotechnical systems can present significant barriers to their design, comprehension and empirical analysis. This article describes the potential advantages of computer-based models and simulations for understanding factors that impact sociotechnical system design and operation, particularly with respect to process and occupational safety. PMID:25761227
Size and complexity in model financial systems.
Arinaminpathy, Nimalan; Kapadia, Sujit; May, Robert M
2012-11-01
The global financial crisis has precipitated an increasing appreciation of the need for a systemic perspective toward financial stability. For example: What role do large banks play in systemic risk? How should capital adequacy standards recognize this role? How is stability shaped by concentration and diversification in the financial system? We explore these questions using a deliberately simplified, dynamic model of a banking system that combines three different channels for direct transmission of contagion from one bank to another: liquidity hoarding, asset price contagion, and the propagation of defaults via counterparty credit risk. Importantly, we also introduce a mechanism for capturing how swings in "confidence" in the system may contribute to instability. Our results highlight that the importance of relatively large, well-connected banks in system stability scales more than proportionately with their size: the impact of their collapse arises not only from their connectivity, but also from their effect on confidence in the system. Imposing tougher capital requirements on larger banks than smaller ones can thus enhance the resilience of the system. Moreover, these effects are more pronounced in more concentrated systems, and continue to apply, even when allowing for potential diversification benefits that may be realized by larger banks. We discuss some tentative implications for policy, as well as conceptual analogies in ecosystem stability and in the control of infectious diseases. PMID:23091020
Size and complexity in model financial systems
Arinaminpathy, Nimalan; Kapadia, Sujit; May, Robert M.
2012-01-01
The global financial crisis has precipitated an increasing appreciation of the need for a systemic perspective toward financial stability. For example: What role do large banks play in systemic risk? How should capital adequacy standards recognize this role? How is stability shaped by concentration and diversification in the financial system? We explore these questions using a deliberately simplified, dynamic model of a banking system that combines three different channels for direct transmission of contagion from one bank to another: liquidity hoarding, asset price contagion, and the propagation of defaults via counterparty credit risk. Importantly, we also introduce a mechanism for capturing how swings in “confidence” in the system may contribute to instability. Our results highlight that the importance of relatively large, well-connected banks in system stability scales more than proportionately with their size: the impact of their collapse arises not only from their connectivity, but also from their effect on confidence in the system. Imposing tougher capital requirements on larger banks than smaller ones can thus enhance the resilience of the system. Moreover, these effects are more pronounced in more concentrated systems, and continue to apply, even when allowing for potential diversification benefits that may be realized by larger banks. We discuss some tentative implications for policy, as well as conceptual analogies in ecosystem stability and in the control of infectious diseases. PMID:23091020
Probabilistic Multi-Factor Interaction Model for Complex Material Behavior
NASA Technical Reports Server (NTRS)
Abumeri, Galib H.; Chamis, Christos C.
2010-01-01
Complex material behavior is represented by a single equation of product form to account for interaction among the various factors. The factors are selected by the physics of the problem and the environment that the model is to represent. For example, different factors will be required for each to represent temperature, moisture, erosion, corrosion, etc. It is important that the equation represent the physics of the behavior in its entirety accurately. The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the external launch tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points - the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used were obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated. The problem lies in how to represent the divot weight with a single equation. A unique solution to this problem is a multi-factor equation of product form. Each factor is of the following form (1 xi/xf)ei, where xi is the initial value, usually at ambient conditions, xf the final value, and ei the exponent that makes the curve represented unimodal that meets the initial and final values. The exponents are either evaluated by test data or by technical judgment. A minor disadvantage may be the selection of exponents in the absence of any empirical data. This form has been used successfully in describing the foam ejected in simulated space environmental conditions. Seven factors were required
Is there hope for multi-site complexation modeling?
Bickmore, Barry R.; Rosso, Kevin M.; Mitchell, S. C.
2006-06-06
It has been shown here that the standard formulation of the MUSIC model does not deliver the molecular-scale insight into oxide surface reactions that it promises. The model does not properly divide long-range electrostatic and short-range contributions to acid-base reaction energies, and it does not treat solvation in a physically realistic manner. However, even if the current MUSIC model does not succeed in its ambitions, its ambitions are still reasonable. It was a pioneering attempt in that Hiemstra and coworkers recognized that intrinsic equilibrium constants, where the effects of long-range electrostatic effects have been removed, must be theoretically constrained prior to model fitting if there is to be any hope of obtaining molecular-scale insights from SCMs. We have also shown, on the other hand, that it may be premature to dismiss all valence-based models of acidity. Not only can some such models accurately predict intrinsic acidity constants, but they can also now be linked to the results of molecular dynamics simulations of solvated systems. Significant challenges remain for those interested in creating SCMs that are accurate at the molecular scale. It will only be after all model parameters can be predicted from theory, and the models validated against titration data that we will be able to begin to have some confidence that we really are adequately describing the chemical systems in question.
NNLOPS accurate associated HW production
NASA Astrophysics Data System (ADS)
Astill, William; Bizon, Wojciech; Re, Emanuele; Zanderighi, Giulia
2016-06-01
We present a next-to-next-to-leading order accurate description of associated HW production consistently matched to a parton shower. The method is based on reweighting events obtained with the HW plus one jet NLO accurate calculation implemented in POWHEG, extended with the MiNLO procedure, to reproduce NNLO accurate Born distributions. Since the Born kinematics is more complex than the cases treated before, we use a parametrization of the Collins-Soper angles to reduce the number of variables required for the reweighting. We present phenomenological results at 13 TeV, with cuts suggested by the Higgs Cross section Working Group.
NASA Astrophysics Data System (ADS)
McBride, D.; Cross, M.; Croft, N.; Bennett, C.; Gebhardt, J.
2006-03-01
A computational procedure is presented for solving complex variably saturated flows in porous media, that may easily be implemented into existing conventional finite-volume-based computational fluid dynamics codes, so that their functionality might be geared upon to readily enable the modelling of a complex suite of interacting fluid, thermal and chemical reaction process physics. This procedure has been integrated within a multi-physics finite volume unstructured mesh framework, allowing arbitrarily complex three-dimensional geometries to be modelled. The model is particularly targeted at ore heap-leaching processes, which encounter complex flow problems, such as infiltration into dry soil, drainage, perched water tables and flow through heterogeneous materials, but is equally applicable to any process involving flow through porous media, such as in environmental recovery processes. The computational procedure is based on the mixed form of the classical Richards equation, employing an adaptive transformed mixed algorithm that is numerically robust and significantly reduces compute (or CPU) time. The computational procedure is accurate (compares well with other methods and analytical data), comprehensive (representing any kind of porous flow model), and is computationally efficient. As such, this procedure provides a suitable basis for the implementation of large-scale industrial heap-leach models.
Kellogg, R M
1982-01-01
In terms of the reporting of accomplished chemistry this review can do no more than give an indication of the rapid progress in the branch of bioorganic modelling based on the use of macrocyclic compounds that (usually) act as complexing agents. What remains to be done, however, is to point out problems that have not been satisfactorily solved and to suggest other profitable areas of investigation. From the material accumulated in this review one can draw the conclusion that especially crown (or cryptate) systems offer special advantages in bioorganic modelling because such compounds can - enzyme like - complex a potential substrate. On the basis of quite simple binding considerations, coupled with an analysis of steric interactions, accurate predictions of the stereochemistry of the complex can be made. The inclusion of catalytic groups in the crown (or cryptate) system and reactive functional groups in the substrate is then done in such a fashion that the stereoelectronic arrangement is compatible with the predicted geometry of the complex. However, the good complexing ability of the ligand is paradoxically often its greatest failing in terms of developing a system in which the functionalized ligand acts truly as a catalyst. As seen from much of the chemistry discussed in this review the ligand is incapable of the double task of complexing substrate but releasing product in an enzymic fashion, i.e. that turnover occurs. How is this problem to be solved? Induced conformational changes are an obvious approach although the design of proper systems remains a challenge for which few suggestions outside of unlimited ingenuity can be given. Much of the solution to such problems will lie also in a much better understanding than we now have of non-covalent interactions and the stereochemistry of such interactions. The assembly and disassembly of large molecular aggregates by the making and dissolution of non-covalent bonds is an art at which chemists are still relative
Reassessing Geophysical Models of the Bushveld Complex in 3D
NASA Astrophysics Data System (ADS)
Cole, J.; Webb, S. J.; Finn, C.
2012-12-01
Conceptual geophysical models of the Bushveld Igneous Complex show three possible geometries for its mafic component: 1) Separate intrusions with vertical feeders for the eastern and western lobes (Cousins, 1959) 2) Separate dipping sheets for the two lobes (Du Plessis and Kleywegt, 1987) 3) A single saucer-shaped unit connected at depth in the central part between the two lobes (Cawthorn et al, 1998) Model three incorporates isostatic adjustment of the crust in response to the weight of the dense mafic material. The model was corroborated by results of a broadband seismic array over southern Africa, known as the Southern African Seismic Experiment (SASE) (Nguuri, et al, 2001; Webb et al, 2004). This new information about the crustal thickness only became available in the last decade and could not be considered in the earlier models. Nevertheless, there is still on-going debate as to which model is correct. All of the models published up to now have been done in 2 or 2.5 dimensions. This is not well suited to modelling the complex geometry of the Bushveld intrusion. 3D modelling takes into account effects of variations in geometry and geophysical properties of lithologies in a full three dimensional sense and therefore affects the shape and amplitude of calculated fields. The main question is how the new knowledge of the increased crustal thickness, as well as the complexity of the Bushveld Complex, will impact on the gravity fields calculated for the existing conceptual models, when modelling in 3D. The three published geophysical models were remodelled using full 3Dl potential field modelling software, and including crustal thickness obtained from the SASE. The aim was not to construct very detailed models, but to test the existing conceptual models in an equally conceptual way. Firstly a specific 2D model was recreated in 3D, without crustal thickening, to establish the difference between 2D and 3D results. Then the thicker crust was added. Including the less
A mechanistic model of the cysteine synthase complex.
Feldman-Salit, Anna; Wirtz, Markus; Hell, Ruediger; Wade, Rebecca C
2009-02-13
Plants and bacteria assimilate and incorporate inorganic sulfur into organic compounds such as the amino acid cysteine. Cysteine biosynthesis involves a bienzyme complex, the cysteine synthase (CS) complex. The CS complex is composed of the enzymes serine acetyl transferase (SAT) and O-acetyl-serine-(thiol)-lyase (OAS-TL). Although it is experimentally known that formation of the CS complex influences cysteine production, the exact biological function of the CS complex, the mechanism of reciprocal regulation of the constituent enzymes and the structure of the complex are still poorly understood. Here, we used docking techniques to construct a model of the CS complex from mitochondrial Arabidopsis thaliana. The three-dimensional structures of the enzymes were modeled by comparative techniques. The C-termini of SAT, missing in the template structures but crucial for CS formation, were modeled de novo. Diffusional encounter complexes of SAT and OAS-TL were generated by rigid-body Brownian dynamics simulation. By incorporating experimental constraints during Brownian dynamics simulation, we identified complexes consistent with experiments. Selected encounter complexes were refined by molecular dynamics simulation to generate structures of bound complexes. We found that although a stoichiometric ratio of six OAS-TL dimers to one SAT hexamer in the CS complex is geometrically possible, binding energy calculations suggest that, consistent with experiments, a ratio of only two OAS-TL dimers to one SAT hexamer is more likely. Computational mutagenesis of residues in OAS-TL that are experimentally significant for CS formation hindered the association of the enzymes due to a less-favorable electrostatic binding free energy. Since the enzymes from A. thaliana were expressed in Escherichia coli, the cross-species binding of SAT and OAS-TL from E. coli and A. thaliana was explored. The results showed that reduced cysteine production might be due to a cross-binding of A. thaliana
The Use of Behavior Models for Predicting Complex Operations
NASA Technical Reports Server (NTRS)
Gore, Brian F.
2010-01-01
Modeling and simulation (M&S) plays an important role when complex human-system notions are being proposed, developed and tested within the system design process. National Aeronautics and Space Administration (NASA) as an agency uses many different types of M&S approaches for predicting human-system interactions, especially when it is early in the development phase of a conceptual design. NASA Ames Research Center possesses a number of M&S capabilities ranging from airflow, flight path models, aircraft models, scheduling models, human performance models (HPMs), and bioinformatics models among a host of other kinds of M&S capabilities that are used for predicting whether the proposed designs will benefit the specific mission criteria. The Man-Machine Integration Design and Analysis System (MIDAS) is a NASA ARC HPM software tool that integrates many models of human behavior with environment models, equipment models, and procedural / task models. The challenge to model comprehensibility is heightened as the number of models that are integrated and the requisite fidelity of the procedural sets are increased. Model transparency is needed for some of the more complex HPMs to maintain comprehensibility of the integrated model performance. This will be exemplified in a recent MIDAS v5 application model and plans for future model refinements will be presented.
NASA Astrophysics Data System (ADS)
Feldgus, Steven; Shields, George C.
2001-10-01
The Bergman cyclization of large polycyclic enediyne systems that mimic the cores of the enediyne anticancer antibiotics was studied using the ONIOM hybrid method. Tests on small enediynes show that ONIOM can accurately match experimental data. The effect of the triggering reaction in the natural products is investigated, and we support the argument that it is strain effects that lower the cyclization barrier. The barrier for the triggered molecule is very low, leading to a reasonable half-life at biological temperatures. No evidence is found that would suggest a concerted cyclization/H-atom abstraction mechanism is necessary for DNA cleavage.
First results from the International Urban Energy Balance Model Comparison: Model Complexity
NASA Astrophysics Data System (ADS)
Blackett, M.; Grimmond, S.; Best, M.
2009-04-01
A great variety of urban energy balance models has been developed. These vary in complexity from simple schemes that represent the city as a slab, through those which model various facets (i.e. road, walls and roof) to more complex urban forms (including street canyons with intersections) and features (such as vegetation cover and anthropogenic heat fluxes). Some schemes also incorporate detailed representations of momentum and energy fluxes distributed throughout various layers of the urban canopy layer. The models each differ in the parameters they require to describe the site and the in demands they make on computational processing power. Many of these models have been evaluated using observational datasets but to date, no controlled comparisons have been conducted. Urban surface energy balance models provide a means to predict the energy exchange processes which influence factors such as urban temperature, humidity, atmospheric stability and winds. These all need to be modelled accurately to capture features such as the urban heat island effect and to provide key information for dispersion and air quality modelling. A comparison of the various models available will assist in improving current and future models and will assist in formulating research priorities for future observational campaigns within urban areas. In this presentation we will summarise the initial results of this international urban energy balance model comparison. In particular, the relative performance of the models involved will be compared based on their degree of complexity. These results will inform us on ways in which we can improve the modelling of air quality within, and climate impacts of, global megacities. The methodology employed in conducting this comparison followed that used in PILPS (the Project for Intercomparison of Land-Surface Parameterization Schemes) which is also endorsed by the GEWEX Global Land Atmosphere System Study (GLASS) panel. In all cases, models were run
White, E.; Woolley, M.; Bienemann, A.; Johnson, D.E.; Wyatt, M.; Murray, G.; Taylor, H.; Gill, S.S.
2011-01-01
Achieving accurate intracranial electrode or catheter placement is critical in clinical practice in order to maximise the efficacy of deep brain stimulation and drug delivery respectively as well as to minimise side-effects. We have developed a highly accurate and robust method for MRI-guided, stereotactic delivery of catheters and electrodes to deep target structures in the brain of pigs. This study outlines the development of this equipment and animal model. Specifically this system enables reliable head immobilisation, acquisition of high-resolution MR images, precise co-registration of MRI and stereotactic spaces and overall rigidity to facilitate accurate burr hole-generation and catheter implantation. To demonstrate the utility of this system, in this study a total of twelve catheters were implanted into the putamen of six Large White Landrace pigs. All implants were accurately placed into the putamen. Target accuracy had a mean Euclidean distance of 0.623 mm (standard deviation of 0.33 mm). This method has allowed us to accurately insert fine cannulae, suitable for the administration of therapeutic agents by convection-enhanced delivery (CED), into the brain of pigs. This study provides summary evidence of a robust system for catheter implantation into the brain of a large animal model. We are currently using this stereotactic system, implantation procedure and animal model to develop catheter-based drug delivery systems that will be translated into human clinical trials, as well as to model the distribution of therapeutic agents administered by CED over large volumes of brain. PMID:21074564
Geometric modeling of subcellular structures, organelles, and multiprotein complexes
Feng, Xin; Xia, Kelin; Tong, Yiying; Wei, Guo-Wei
2013-01-01
SUMMARY Recently, the structure, function, stability, and dynamics of subcellular structures, organelles, and multi-protein complexes have emerged as a leading interest in structural biology. Geometric modeling not only provides visualizations of shapes for large biomolecular complexes but also fills the gap between structural information and theoretical modeling, and enables the understanding of function, stability, and dynamics. This paper introduces a suite of computational tools for volumetric data processing, information extraction, surface mesh rendering, geometric measurement, and curvature estimation of biomolecular complexes. Particular emphasis is given to the modeling of cryo-electron microscopy data. Lagrangian-triangle meshes are employed for the surface presentation. On the basis of this representation, algorithms are developed for surface area and surface-enclosed volume calculation, and curvature estimation. Methods for volumetric meshing have also been presented. Because the technological development in computer science and mathematics has led to multiple choices at each stage of the geometric modeling, we discuss the rationales in the design and selection of various algorithms. Analytical models are designed to test the computational accuracy and convergence of proposed algorithms. Finally, we select a set of six cryo-electron microscopy data representing typical subcellular complexes to demonstrate the efficacy of the proposed algorithms in handling biomolecular surfaces and explore their capability of geometric characterization of binding targets. This paper offers a comprehensive protocol for the geometric modeling of subcellular structures, organelles, and multiprotein complexes. PMID:23212797
A radio-frequency sheath model for complex waveforms
Turner, M. M.; Chabert, P.
2014-04-21
Plasma sheaths driven by radio-frequency voltages occur in contexts ranging from plasma processing to magnetically confined fusion experiments. An analytical understanding of such sheaths is therefore important, both intrinsically and as an element in more elaborate theoretical structures. Radio-frequency sheaths are commonly excited by highly anharmonic waveforms, but no analytical model exists for this general case. We present a mathematically simple sheath model that is in good agreement with earlier models for single frequency excitation, yet can be solved for arbitrary excitation waveforms. As examples, we discuss dual-frequency and pulse-like waveforms. The model employs the ansatz that the time-averaged electron density is a constant fraction of the ion density. In the cases we discuss, the error introduced by this approximation is small, and in general it can be quantified through an internal consistency condition of the model. This simple and accurate model is likely to have wide application.
Between complexity of modelling and modelling of complexity: An essay on econophysics
NASA Astrophysics Data System (ADS)
Schinckus, C.
2013-09-01
Econophysics is an emerging field dealing with complex systems and emergent properties. A deeper analysis of themes studied by econophysicists shows that research conducted in this field can be decomposed into two different computational approaches: “statistical econophysics” and “agent-based econophysics”. This methodological scission complicates the definition of the complexity used in econophysics. Therefore, this article aims to clarify what kind of emergences and complexities we can find in econophysics in order to better understand, on one hand, the current scientific modes of reasoning this new field provides; and on the other hand, the future methodological evolution of the field.
Using fMRI to Test Models of Complex Cognition
ERIC Educational Resources Information Center
Anderson, John R.; Carter, Cameron S.; Fincham, Jon M.; Qin, Yulin; Ravizza, Susan M.; Rosenberg-Lee, Miriam
2008-01-01
This article investigates the potential of fMRI to test assumptions about different components in models of complex cognitive tasks. If the components of a model can be associated with specific brain regions, one can make predictions for the temporal course of the BOLD response in these regions. An event-locked procedure is described for dealing…
Tips on Creating Complex Geometry Using Solid Modeling Software
ERIC Educational Resources Information Center
Gow, George
2008-01-01
Three-dimensional computer-aided drafting (CAD) software, sometimes referred to as "solid modeling" software, is easy to learn, fun to use, and becoming the standard in industry. However, many users have difficulty creating complex geometry with the solid modeling software. And the problem is not entirely a student problem. Even some teachers and…
Network model of bilateral power markets based on complex networks
NASA Astrophysics Data System (ADS)
Wu, Yang; Liu, Junyong; Li, Furong; Yan, Zhanxin; Zhang, Li
2014-06-01
The bilateral power transaction (BPT) mode becomes a typical market organization with the restructuring of electric power industry, the proper model which could capture its characteristics is in urgent need. However, the model is lacking because of this market organization's complexity. As a promising approach to modeling complex systems, complex networks could provide a sound theoretical framework for developing proper simulation model. In this paper, a complex network model of the BPT market is proposed. In this model, price advantage mechanism is a precondition. Unlike other general commodity transactions, both of the financial layer and the physical layer are considered in the model. Through simulation analysis, the feasibility and validity of the model are verified. At same time, some typical statistical features of BPT network are identified. Namely, the degree distribution follows the power law, the clustering coefficient is low and the average path length is a bit long. Moreover, the topological stability of the BPT network is tested. The results show that the network displays a topological robustness to random market member's failures while it is fragile against deliberate attacks, and the network could resist cascading failure to some extent. These features are helpful for making decisions and risk management in BPT markets.
Evapotranspiration model of different complexity for multiple land cover types
Technology Transfer Automated Retrieval System (TEKTRAN)
A comparison between half-hourly and daily measured and computed evapotranspiration (ET) using three models of different complexity, namely the Priestley-Taylor (P-T), reference Penman-Monteith (P-M), and Common Land Model (CLM) was conducted using three AmeriFlux sites under different land cover an...
Surface complexation model for strontium sorption to amorphous silica and goethite
Carroll, Susan A; Roberts, Sarah K; Criscenti, Louise J; O'Day, Peggy A
2008-01-01
Strontium sorption to amorphous silica and goethite was measured as a function of pH and dissolved strontium and carbonate concentrations at 25°C. Strontium sorption gradually increases from 0 to 100% from pH 6 to 10 for both phases and requires multiple outer-sphere surface complexes to fit the data. All data are modeled using the triple layer model and the site-occupancy standard state; unless stated otherwise all strontium complexes are mononuclear. Strontium sorption to amorphous silica in the presence and absence of dissolved carbonate can be fit with tetradentate Sr2+ and SrOH+ complexes on the β-plane and a monodentate Sr2+complex on the diffuse plane to account for strontium sorption at low ionic strength. Strontium sorption to goethite in the absence of dissolved carbonate can be fit with monodentate and tetradentate SrOH+ complexes and a tetradentate binuclear Sr2+ species on the β-plane. The binuclear complex is needed to account for enhanced sorption at hgh strontium surface loadings. In the presence of dissolved carbonate additional monodentate Sr2+ and SrOH+ carbonate surface complexes on the β-plane are needed to fit strontium sorption to goethite. Modeling strontium sorption as outer-sphere complexes is consistent with quantitative analysis of extended X-ray absorption fine structure (EXAFS) on selected sorption samples that show a single first shell of oxygen atoms around strontium indicating hydrated surface complexes at the amorphous silica and goethite surfaces. Strontium surface complexation equilibrium constants determined in this study combined with other alkaline earth surface complexation constants are used to recalibrate a predictive model based on Born solvation and crystal-chemistry theory. The model is accurate to about 0.7 log K units. More studies are needed to determine the dependence of alkaline earth sorption on ionic strength and dissolved carbonate and sulfate concentrations for the development of a robust surface
Surface Complexation Model for Strontium Sorption to Amorphous Silica and Goethite
Carroll, S; Robers, S; Criscenti, L; O'Day, P
2007-11-30
Strontium sorption to amorphous silica and goethite was measured as a function of pH and dissolved strontium and carbonate concentrations at 25 C. Strontium sorption gradually increases from 0 to 100% from pH 6 to 10 for both phases and requires multiple outer-sphere surface complexes to fit the data. All data are modeled using the triple layer model and the site-occupancy standard state; unless stated otherwise all strontium complexes are mononuclear. Strontium sorption to amorphous silica in the presence and absence of dissolved carbonate can be fit with tetradentate Sr{sup 2+} and SrOH{sup +} complexes on the {beta}-plane and a monodentate Sr{sup 2+} complex on the diffuse plane to account for strontium sorption at low ionic strength. Strontium sorption to goethite in the absence of dissolved carbonate can be fit with monodentate and tetradentate SrOH{sup +} complexes and a tetradentate binuclear Sr{sup 2+} species on the {beta}-plane. The binuclear complex is needed to account for enhanced sorption at high strontium surface loadings. In the presence of dissolved carbonate additional monodentate Sr{sup 2+} and SrOH{sup +} carbonate surface complexes on the {beta}-plane are needed to fit strontium sorption to goethite. Modeling strontium sorption as outer-sphere complexes is consistent with quantitative analysis of extended X-ray absorption fine structure (EXAFS) on selected sorption samples that show a single first shell of oxygen atoms around strontium indicating hydrated surface complexes at the amorphous silica and goethite surfaces. Strontium surface complexation equilibrium constants determined in this study combined with other alkaline earth surface complexation constants are used to recalibrate a predictive model based on Born solvation and crystal-chemistry theory. The model is accurate to about 0.7 log K units. More studies are needed to determine the dependence of alkaline earth sorption on ionic strength and dissolved carbonate and sulfate
Zebrafish as an emerging model for studying complex brain disorders
Kalueff, Allan V.; Stewart, Adam Michael; Gerlai, Robert
2014-01-01
The zebrafish (Danio rerio) is rapidly becoming a popular model organism in pharmacogenetics and neuropharmacology. Both larval and adult zebrafish are currently used to increase our understanding of brain function, dysfunction, and their genetic and pharmacological modulation. Here we review the developing utility of zebrafish in the analysis of complex brain disorders (including, for example, depression, autism, psychoses, drug abuse and cognitive disorders), also covering zebrafish applications towards the goal of modeling major human neuropsychiatric and drug-induced syndromes. We argue that zebrafish models of complex brain disorders and drug-induced conditions have become a rapidly emerging critical field in translational neuropharmacology research. PMID:24412421
Simulating complex intracellular processes using object-oriented computational modelling.
Johnson, Colin G; Goldman, Jacki P; Gullick, William J
2004-11-01
The aim of this paper is to give an overview of computer modelling and simulation in cellular biology, in particular as applied to complex biochemical processes within the cell. This is illustrated by the use of the techniques of object-oriented modelling, where the computer is used to construct abstractions of objects in the domain being modelled, and these objects then interact within the computer to simulate the system and allow emergent properties to be observed. The paper also discusses the role of computer simulation in understanding complexity in biological systems, and the kinds of information which can be obtained about biology via simulation. PMID:15302205
NASA Astrophysics Data System (ADS)
Shen, Yanfeng; Cesnik, Carlos E. S.
2016-09-01
This paper presents a new hybrid modeling technique for the efficient simulation of guided wave generation, propagation, and interaction with damage in complex composite structures. A local finite element model is deployed to capture the piezoelectric effects and actuation dynamics of the transmitter, while the global domain wave propagation and interaction with structural complexity (structure features and damage) are solved utilizing a local interaction simulation approach (LISA). This hybrid approach allows the accurate modeling of the local dynamics of the transducers and keeping the LISA formulation in an explicit format, which facilitates its readiness for parallel computing. The global LISA framework was extended through the 3D Kelvin–Voigt viscoelasticity theory to include anisotropic damping effects for composite structures, as an improvement over the existing LISA formulation. The global LISA framework was implemented using the compute unified device architecture running on graphic processing units. A commercial preprocessor is integrated seamlessly with the computational framework for grid generation and material property allocation to handle complex structures. The excitability and damping effects are successfully captured by this hybrid model, with experimental validation using the scanning laser doppler vibrometry. To demonstrate the capability of our hybrid approach for complex structures, guided wave propagation and interaction with a delamination in a composite panel with stiffeners is presented.
Complexation and molecular modeling studies of europium(III)-gallic acid-amino acid complexes.
Taha, Mohamed; Khan, Imran; Coutinho, João A P
2016-04-01
With many metal-based drugs extensively used today in the treatment of cancer, attention has focused on the development of new coordination compounds with antitumor activity with europium(III) complexes recently introduced as novel anticancer drugs. The aim of this work is to design new Eu(III) complexes with gallic acid, an antioxida'nt phenolic compound. Gallic acid was chosen because it shows anticancer activity without harming health cells. As antioxidant, it helps to protect human cells against oxidative damage that implicated in DNA damage, cancer, and accelerated cell aging. In this work, the formation of binary and ternary complexes of Eu(III) with gallic acid, primary ligand, and amino acids alanine, leucine, isoleucine, and tryptophan was studied by glass electrode potentiometry in aqueous solution containing 0.1M NaNO3 at (298.2±0.1) K. Their overall stability constants were evaluated and the concentration distributions of the complex species in solution were calculated. The protonation constants of gallic acid and amino acids were also determined at our experimental conditions and compared with those predicted by using conductor-like screening model for realistic solvation (COSMO-RS) model. The geometries of Eu(III)-gallic acid complexes were characterized by the density functional theory (DFT). The spectroscopic UV-visible and photoluminescence measurements are carried out to confirm the formation of Eu(III)-gallic acid complexes in aqueous solutions. PMID:26827296
Multiscale Model for the Assembly Kinetics of Protein Complexes.
Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao
2016-02-01
The assembly of proteins into high-order complexes is a general mechanism for these biomolecules to implement their versatile functions in cells. Natural evolution has developed various assembling pathways for specific protein complexes to maintain their stability and proper activities. Previous studies have provided numerous examples of the misassembly of protein complexes leading to severe biological consequences. Although the research focusing on protein complexes has started to move beyond the static representation of quaternary structures to the dynamic aspect of their assembly, the current understanding of the assembly mechanism of protein complexes is still largely limited. To tackle this problem, we developed a new multiscale modeling framework. This framework combines a lower-resolution rigid-body-based simulation with a higher-resolution Cα-based simulation method so that protein complexes can be assembled with both structural details and computational efficiency. We applied this model to a homotrimer and a heterotetramer as simple test systems. Consistent with experimental observations, our simulations indicated very different kinetics between protein oligomerization and dimerization. The formation of protein oligomers is a multistep process that is much slower than dimerization but thermodynamically more stable. Moreover, we showed that even the same protein quaternary structure can have very diverse assembly pathways under different binding constants between subunits, which is important for regulating the functions of protein complexes. Finally, we revealed that the binding between subunits in a complex can be synergistically strengthened during assembly without considering allosteric regulation or conformational changes. Therefore, our model provides a useful tool to understand the general principles of protein complex assembly. PMID:26738810
Pedigree models for complex human traits involving the mitochondrial genome.
Schork, N J; Guo, S W
1993-01-01
Recent biochemical and molecular-genetic discoveries concerning variations in human mtDNA have suggested a role for mtDNA mutations in a number of human traits and disorders. Although the importance of these discoveries cannot be emphasized enough, the complex natures of mitochondrial biogenesis, mutant mtDNA phenotype expression, and the maternal inheritance pattern exhibited by mtDNA transmission make it difficult to develop models that can be used routinely in pedigree analyses to quantify and test hypotheses about the role of mtDNA in the expression of a trait. In the present pape