Alignment-independent technique for 3D QSAR analysis

NASA Astrophysics Data System (ADS)

Wilkes, Jon G.; Stoyanova-Slavova, Iva B.; Buzatu, Dan A.

2016-04-01

Molecular biochemistry is controlled by 3D phenomena but structure-activity models based on 3D descriptors are infrequently used for large data sets because of the computational overhead for determining molecular conformations. A diverse dataset of 146 androgen receptor binders was used to investigate how different methods for defining molecular conformations affect the performance of 3D-quantitative spectral data activity relationship models. Molecular conformations tested: (1) global minimum of molecules' potential energy surface; (2) alignment-to-templates using equal electronic and steric force field contributions; (3) alignment using contributions "Best-for-Each" template; (4) non-energy optimized, non-aligned (2D > 3D). Aggregate predictions from models were compared. Highest average coefficients of determination ranged from R Test 2 = 0.56 to 0.61. The best model using 2D > 3D (imported directly from ChemSpider) produced R Test 2 = 0.61. It was superior to energy-minimized and conformation-aligned models and was achieved in only 3-7 % of the time required using the other conformation strategies. Predictions averaged from models built on different conformations achieved a consensus R Test 2 = 0.65. The best 2D > 3D model was analyzed for underlying structure-activity relationships. For the compound strongest binding to the androgen receptor, 10 substructural features contributing to binding were flagged. Utility of 2D > 3D was compared for two other activity endpoints, each modeling a medium sized data set. Results suggested that large scale, accurate predictions using 2D > 3D SDAR descriptors may be produced for interactions involving endocrine system nuclear receptors and other data sets in which strongest activities are produced by fairly inflexible substrates.

3D printing based on cardiac CT assists anatomic visualization prior to transcatheter aortic valve replacement.

PubMed

Ripley, Beth; Kelil, Tatiana; Cheezum, Michael K; Goncalves, Alexandra; Di Carli, Marcelo F; Rybicki, Frank J; Steigner, Mike; Mitsouras, Dimitrios; Blankstein, Ron

2016-01-01

3D printing is a promising technique that may have applications in medicine, and there is expanding interest in the use of patient-specific 3D models to guide surgical interventions. To determine the feasibility of using cardiac CT to print individual models of the aortic root complex for transcatheter aortic valve replacement (TAVR) planning as well as to determine the ability to predict paravalvular aortic regurgitation (PAR). This retrospective study included 16 patients (9 with PAR identified on blinded interpretation of post-procedure trans-thoracic echocardiography and 7 age, sex, and valve size-matched controls with no PAR). 3D printed models of the aortic root were created from pre-TAVR cardiac computed tomography data. These models were fitted with printed valves and predictions regarding post-implant PAR were made using a light transmission test. Aortic root 3D models were highly accurate, with excellent agreement between annulus measurements made on 3D models and those made on corresponding 2D data (mean difference of -0.34 mm, 95% limits of agreement: ± 1.3 mm). The 3D printed valve models were within 0.1 mm of their designed dimensions. Examination of the fit of valves within patient-specific aortic root models correctly predicted PAR in 6 of 9 patients (6 true positive, 3 false negative) and absence of PAR in 5 of 7 patients (5 true negative, 2 false positive). Pre-TAVR 3D-printing based on cardiac CT provides a unique patient-specific method to assess the physical interplay of the aortic root and implanted valves. With additional optimization, 3D models may complement traditional techniques used for predicting which patients are more likely to develop PAR. Copyright © 2016 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Human and Server Docking Prediction for CAPRI Round 30–35 Using LZerD with Combined Scoring Functions

PubMed Central

Peterson, Lenna X.; Kim, Hyungrae; Esquivel-Rodriguez, Juan; Roy, Amitava; Han, Xusi; Shin, Woong-Hee; Zhang, Jian; Terashi, Genki; Lee, Matt; Kihara, Daisuke

2016-01-01

We report the performance of protein-protein docking predictions by our group for recent rounds of the Critical Assessment of Prediction of Interactions (CAPRI), a community-wide assessment of state-of-the-art docking methods. Our prediction procedure uses a protein-protein docking program named LZerD developed in our group. LZerD represents a protein surface with 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. The appropriate soft representation of protein surface with 3DZD makes the method more tolerant to conformational change of proteins upon docking, which adds an advantage for unbound docking. Docking was guided by interface residue prediction performed with BindML and cons-PPISP as well as literature information when available. The generated docking models were ranked by a combination of scoring functions, including PRESCO, which evaluates the native-likeness of residues’ spatial environments in structure models. First, we discuss the overall performance of our group in the CAPRI prediction rounds and investigate the reasons for unsuccessful cases. Then, we examine the performance of several knowledge-based scoring functions and their combinations for ranking docking models. It was found that the quality of a pool of docking models generated by LZerD, i.e. whether or not the pool includes near-native models, can be predicted by the correlation of multiple scores. Although the current analysis used docking models generated by LZerD, findings on scoring functions are expected to be universally applicable to other docking methods. PMID:27654025

Prediction of fat globule particle size in homogenized milk using Fourier transform mid-infrared spectra.

PubMed

Di Marzo, Larissa; Cree, Patrick; Barbano, David M

2016-11-01

Our objective was to develop partial least square models using data from Fourier transform mid-infrared (MIR) spectra to predict the particle size distributions d(0.5) and d(0.9), surface volume mean diameter D[3,2], and volume moment mean diameter D[4,3] of milk fat globules and validate the models. The goal of the study was to produce a method built into the MIR milk analyzer that could be used to warn the instrument operator that the homogenizer is near failure and needs to be replaced to ensure quality of results. Five homogenizers with different homogenization efficiency were used to homogenize pasteurized modified unhomogenized milks and farm raw bulk milks. Homogenized milks were collected from the homogenizer outlet and then run through an MIR milk analyzer without an in-line homogenizer to collect a MIR spectrum. A separate portion of each homogenized milk was analyzed with a laser light-scattering particle size analyzer to obtain reference values. The study was replicated 3 times with 3 independent sets of modified milks and bulk tank farm milks. Validation of the models was done with a set of 34 milks that were not used in the model development. Partial least square regression models were developed and validated for predicting the following milk fat globule particle size distribution parameters from MIR spectra: d(0.5) and d(0.9), surface volume mean diameter D[3,2], and volume moment mean diameter D[4,3]. The basis for the ability to model particle size distribution of milk fat emulsions was hypothesized to be the result of the partial least square modeling detecting absorbance shifts in MIR spectra of milk fat due to the Christiansen effect. The independent sample validation of particle size prediction methods found more variation in d(0.9) and D[4,3] predictions than the d(0.5) and D[3,2] predictions relative to laser light-scattering reference values, and this may be due to variation in particle size among different pump strokes. The accuracy of the d(0.9) prediction for routine quality assurance, to determine if a homogenizer within an MIR milk analyzer was near the failure level [i.e., d(0.9) >1.7µm] and needed to be replaced, is fit-for-purpose. The daily average particle size performance [i.e., d(0.9)] of a homogenizer based on the mean for the day could be used for monitoring homogenizer performance. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Seismic and Infrasound Location

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

Arrowsmith, Stephen J.; Begnaud, Michael L.

2014-03-19

This presentation includes slides on Signal Propagation Through the Earth/Atmosphere Varies at Different Scales; 3D Seismic Models: RSTT; Ray Coverage (Pn); Source-Specific Station Corrections (SSSCs); RSTT Conclusions; SALSA3D (SAndia LoS Alamos) Global 3D Earth Model for Travel Time; Comparison of IDC SSSCs to RSTT Predictions; SALSA3D; Validation and Model Comparison; DSS Lines in the Siberian Platform; DSS Line CRA-4 Comparison; Travel Time Δak135; Travel Time Prediction Uncertainty; SALSA3D Conclusions; Infrasound Data Processing: An example event; Infrasound Data Processing: An example event; Infrasound Location; How does BISL work?; BISL: Application to the 2013 DPRK Test; and BISL: Ongoing Research.

CFL3D, FUN3d, and NSU3D Contributions to the Fifth Drag Prediction Workshop

NASA Technical Reports Server (NTRS)

Park, Michael A.; Laflin, Kelly R.; Chaffin, Mark S.; Powell, Nicholas; Levy, David W.

2013-01-01

Results presented at the Fifth Drag Prediction Workshop using CFL3D, FUN3D, and NSU3D are described. These are calculations on the workshop provided grids and drag adapted grids. The NSU3D results have been updated to reflect an improvement to skin friction calculation on skewed grids. FUN3D results generated after the workshop are included for custom participant generated grids and a grid from a previous workshop. Uniform grid refinement at the design condition shows a tight grouping in calculated drag, where the variation in the pressure component of drag is larger than the skin friction component. At this design condition, A fine-grid drag value was predicted with a smaller drag adjoint adapted grid via tetrahedral adaption to a metric and mixed-element subdivision. The buffet study produced larger variation than the design case, which is attributed to large differences in the predicted side-of-body separation extent. Various modeling and discretization approaches had a strong impact on predicted side-of-body separation. This large wing root separation bubble was not observed in wind tunnel tests indicating that more work is necessary in modeling wing root juncture flows to predict experiments.

Development and application of a 3-D geometry/mass model for LDEF satellite ionizing radiation assessments

NASA Technical Reports Server (NTRS)

Colborn, B. L.; Armstrong, T. W.

1992-01-01

A computer model of the three dimensional geometry and material distributions for the LDEF spacecraft, experiment trays, and, for selected trays, the components of experiments within a tray was developed for use in ionizing radiation assessments. The model is being applied to provide 3-D shielding distributions around radiation dosimeters to aid in data interpretation, particularly in assessing the directional properties of the radiation exposure. Also, the model has been interfaced with radiation transport codes for 3-D dosimetry response predictions and for calculations related to determining the accuracy of trapped proton and cosmic ray environment models. The methodology is described used in developing the 3-D LDEF model and the level of detail incorporated. Currently, the trays modeled in detail are F2, F8, and H12 and H3. Applications of the model which are discussed include the 3-D shielding distributions around various dosimeters, the influence of shielding on dosimetry responses, and comparisons of dose predictions based on the present 3-D model vs those from 1-D geometry model approximations used in initial estimates.

Predicting the mixed-mode I/II spatial damage propagation along 3D-printed soft interfacial layer via a hyperelastic softening model

NASA Astrophysics Data System (ADS)

Liu, Lei; Li, Yaning

2018-07-01

A methodology was developed to use a hyperelastic softening model to predict the constitutive behavior and the spatial damage propagation of nonlinear materials with damage-induced softening under mixed-mode loading. A user subroutine (ABAQUS/VUMAT) was developed for numerical implementation of the model. 3D-printed wavy soft rubbery interfacial layer was used as a material system to verify and validate the methodology. The Arruda - Boyce hyperelastic model is incorporated with the softening model to capture the nonlinear pre-and post- damage behavior of the interfacial layer under mixed Mode I/II loads. To characterize model parameters of the 3D-printed rubbery interfacial layer, a series of scarf-joint specimens were designed, which enabled systematic variation of stress triaxiality via a single geometric parameter, the slant angle. It was found that the important model parameter m is exponentially related to the stress triaxiality. Compact tension specimens of the sinusoidal wavy interfacial layer with different waviness were designed and fabricated via multi-material 3D printing. Finite element (FE) simulations were conducted to predict the spatial damage propagation of the material within the wavy interfacial layer. Compact tension experiments were performed to verify the model prediction. The results show that the model developed is able to accurately predict the damage propagation of the 3D-printed rubbery interfacial layer under complicated stress-state without pre-defined failure criteria.

Human and server docking prediction for CAPRI round 30-35 using LZerD with combined scoring functions.

PubMed

Peterson, Lenna X; Kim, Hyungrae; Esquivel-Rodriguez, Juan; Roy, Amitava; Han, Xusi; Shin, Woong-Hee; Zhang, Jian; Terashi, Genki; Lee, Matt; Kihara, Daisuke

2017-03-01

We report the performance of protein-protein docking predictions by our group for recent rounds of the Critical Assessment of Prediction of Interactions (CAPRI), a community-wide assessment of state-of-the-art docking methods. Our prediction procedure uses a protein-protein docking program named LZerD developed in our group. LZerD represents a protein surface with 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. The appropriate soft representation of protein surface with 3DZD makes the method more tolerant to conformational change of proteins upon docking, which adds an advantage for unbound docking. Docking was guided by interface residue prediction performed with BindML and cons-PPISP as well as literature information when available. The generated docking models were ranked by a combination of scoring functions, including PRESCO, which evaluates the native-likeness of residues' spatial environments in structure models. First, we discuss the overall performance of our group in the CAPRI prediction rounds and investigate the reasons for unsuccessful cases. Then, we examine the performance of several knowledge-based scoring functions and their combinations for ranking docking models. It was found that the quality of a pool of docking models generated by LZerD, that is whether or not the pool includes near-native models, can be predicted by the correlation of multiple scores. Although the current analysis used docking models generated by LZerD, findings on scoring functions are expected to be universally applicable to other docking methods. Proteins 2017; 85:513-527. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Global and Regional 3D Tomography for Improved Seismic Event Location and Uncertainty in Explosion Monitoring

NASA Astrophysics Data System (ADS)

Downey, N.; Begnaud, M. L.; Hipp, J. R.; Ballard, S.; Young, C. S.; Encarnacao, A. V.

2017-12-01

The SALSA3D global 3D velocity model of the Earth was developed to improve the accuracy and precision of seismic travel time predictions for a wide suite of regional and teleseismic phases. Recently, the global SALSA3D model was updated to include additional body wave phases including mantle phases, core phases, reflections off the core-mantle boundary and underside reflections off the surface of the Earth. We show that this update improves travel time predictions and leads directly to significant improvements in the accuracy and precision of seismic event locations as compared to locations computed using standard 1D velocity models like ak135, or 2½D models like RSTT. A key feature of our inversions is that path-specific model uncertainty of travel time predictions are calculated using the full 3D model covariance matrix computed during tomography, which results in more realistic uncertainty ellipses that directly reflect tomographic data coverage. Application of this method can also be done at a regional scale: we present a velocity model with uncertainty obtained using data obtained from the University of Utah Seismograph Stations. These results show a reduction in travel-time residuals for re-located events compared with those obtained using previously published models.

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

PubMed

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

2016-11-01

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

3D MI-DRAGON: new model for the reconstruction of US FDA drug- target network and theoretical-experimental studies of inhibitors of rasagiline derivatives for AChE.

PubMed

Prado-Prado, Francisco; García-Mera, Xerardo; Escobar, Manuel; Alonso, Nerea; Caamaño, Olga; Yañez, Matilde; González-Díaz, Humberto

2012-01-01

The number of neurodegenerative diseases has been increasing in recent years. Many of the drug candidates to be used in the treatment of neurodegenerative diseases present specific 3D structural features. An important protein in this sense is the acetylcholinesterase (AChE), which is the target of many Alzheimer's dementia drugs. Consequently, the prediction of Drug-Protein Interactions (DPIs/nDPIs) between new drug candidates and specific 3D structure and targets is of major importance. To this end, we can use Quantitative Structure-Activity Relationships (QSAR) models to carry out a rational DPIs prediction. Unfortunately, many previous QSAR models developed to predict DPIs take into consideration only 2D structural information and codify the activity against only one target. To solve this problem we can develop some 3D multi-target QSAR (3D mt-QSAR) models. In this study, using the 3D MI-DRAGON technique, we have introduced a new predictor for DPIs based on two different well-known software. We have used the MARCH-INSIDE (MI) and DRAGON software to calculate 3D structural parameters for drugs and targets respectively. Both classes of 3D parameters were used as input to train Artificial Neuronal Network (ANN) algorithms using as benchmark dataset the complex network (CN) made up of all DPIs between US FDA approved drugs and their targets. The entire dataset was downloaded from the DrugBank database. The best 3D mt-QSAR predictor found was an ANN of Multi-Layer Perceptron-type (MLP) with profile MLP 37:37-24-1:1. This MLP classifies correctly 274 out of 321 DPIs (Sensitivity = 85.35%) and 1041 out of 1190 nDPIs (Specificity = 87.48%), corresponding to training Accuracy = 87.03%. We have validated the model with external predicting series with Sensitivity = 84.16% (542/644 DPIs; Specificity = 87.51% (2039/2330 nDPIs) and Accuracy = 86.78%. The new CNs of DPIs reconstructed from US FDA can be used to explore large DPI databases in order to discover both new drugs and/or targets. We have carried out some theoretical-experimental studies to illustrate the practical use of 3D MI-DRAGON. First, we have reported the prediction and pharmacological assay of 22 different rasagiline derivatives with possible AChE inhibitory activity. In this work, we have reviewed different computational studies on Drug- Protein models. First, we have reviewed 10 studies on DP computational models. Next, we have reviewed 2D QSAR, 3D QSAR, CoMFA, CoMSIA and Docking with different compounds to find Drug-Protein QSAR models. Last, we have developped a 3D multi-target QSAR (3D mt-QSAR) models for the prediction of the activity of new compounds against different targets or the discovery of new targets.

The influence of computational strategy on prediction of mechanical stress in carotid atherosclerotic plaques: comparison of 2D structure-only, 3D structure-only, one-way and fully coupled fluid-structure interaction analyses.

PubMed

Huang, Yuan; Teng, Zhongzhao; Sadat, Umar; Graves, Martin J; Bennett, Martin R; Gillard, Jonathan H

2014-04-11

Compositional and morphological features of carotid atherosclerotic plaques provide complementary information to luminal stenosis in predicting clinical presentations. However, they alone cannot predict cerebrovascular risk. Mechanical stress within the plaque induced by cyclical changes in blood pressure has potential to assess plaque vulnerability. Various modeling strategies have been employed to predict stress, including 2D and 3D structure-only, 3D one-way and fully coupled fluid-structure interaction (FSI) simulations. However, differences in stress predictions using different strategies have not been assessed. Maximum principal stress (Stress-P1) within 8 human carotid atherosclerotic plaques was calculated based on geometry reconstructed from in vivo computerized tomography and high resolution, multi-sequence magnetic resonance images. Stress-P1 within the diseased region predicted by 2D and 3D structure-only, and 3D one-way FSI simulations were compared to 3D fully coupled FSI analysis. Compared to 3D fully coupled FSI, 2D structure-only simulation significantly overestimated stress level (94.1 kPa [65.2, 117.3] vs. 85.5 kPa [64.4, 113.6]; median [inter-quartile range], p=0.0004). However, when slices around the bifurcation region were excluded, stresses predicted by 2D structure-only simulations showed a good correlation (R(2)=0.69) with values obtained from 3D fully coupled FSI analysis. 3D structure-only model produced a small yet statistically significant stress overestimation compared to 3D fully coupled FSI (86.8 kPa [66.3, 115.8] vs. 85.5 kPa [64.4, 113.6]; p<0.0001). In contrast, one-way FSI underestimated stress compared to 3D fully coupled FSI (78.8 kPa [61.1, 100.4] vs. 85.5 kPa [64.4, 113.7]; p<0.0001). A 3D structure-only model seems to be a computationally inexpensive yet reasonably accurate approximation for stress within carotid atherosclerotic plaques with mild to moderate luminal stenosis as compared to fully coupled FSI analysis. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Multi-scale modeling of tsunami flows and tsunami-induced forces

NASA Astrophysics Data System (ADS)

Qin, X.; Motley, M. R.; LeVeque, R. J.; Gonzalez, F. I.

2016-12-01

The modeling of tsunami flows and tsunami-induced forces in coastal communities with the incorporation of the constructed environment is challenging for many numerical modelers because of the scale and complexity of the physical problem. A two-dimensional (2D) depth-averaged model can be efficient for modeling of waves offshore but may not be accurate enough to predict the complex flow with transient variance in vertical direction around constructed environments on land. On the other hand, using a more complex three-dimensional model is much more computational expensive and can become impractical due to the size of the problem and the meshing requirements near the built environment. In this study, a 2D depth-integrated model and a 3D Reynolds Averaged Navier-Stokes (RANS) model are built to model a 1:50 model-scale, idealized community, representative of Seaside, OR, USA, for which existing experimental data is available for comparison. Numerical results from the two numerical models are compared with each other as well as experimental measurement. Both models predict the flow parameters (water level, velocity, and momentum flux in the vicinity of the buildings) accurately, in general, except for time period near the initial impact, where the depth-averaged models can fail to capture the complexities in the flow. Forces predicted using direct integration of predicted pressure on structural surfaces from the 3D model and using momentum flux from the 2D model with constructed environment are compared, which indicates that force prediction from the 2D model is not always reliable in such a complicated case. Force predictions from integration of the pressure are also compared with forces predicted from bare earth momentum flux calculations to reveal the importance of incorporating the constructed environment in force prediction models.

Predicting Subtype Selectivity for Adenosine Receptor Ligands with Three-Dimensional Biologically Relevant Spectrum (BRS-3D)

NASA Astrophysics Data System (ADS)

He, Song-Bing; Ben Hu; Kuang, Zheng-Kun; Wang, Dong; Kong, De-Xin

2016-11-01

Adenosine receptors (ARs) are potential therapeutic targets for Parkinson’s disease, diabetes, pain, stroke and cancers. Prediction of subtype selectivity is therefore important from both therapeutic and mechanistic perspectives. In this paper, we introduced a shape similarity profile as molecular descriptor, namely three-dimensional biologically relevant spectrum (BRS-3D), for AR selectivity prediction. Pairwise regression and discrimination models were built with the support vector machine methods. The average determination coefficient (r2) of the regression models was 0.664 (for test sets). The 2B-3 (A2B vs A3) model performed best with q2 = 0.769 for training sets (10-fold cross-validation), and r2 = 0.766, RMSE = 0.828 for test sets. The models’ robustness and stability were validated with 100 times resampling and 500 times Y-randomization. We compared the performance of BRS-3D with 3D descriptors calculated by MOE. BRS-3D performed as good as, or better than, MOE 3D descriptors. The performances of the discrimination models were also encouraging, with average accuracy (ACC) 0.912 and MCC 0.792 (test set). The 2A-3 (A2A vs A3) selectivity discrimination model (ACC = 0.882 and MCC = 0.715 for test set) outperformed an earlier reported one (ACC = 0.784). These results demonstrated that, through multiple conformation encoding, BRS-3D can be used as an effective molecular descriptor for AR subtype selectivity prediction.

FUN3D and CFL3D Computations for the First High Lift Prediction Workshop

NASA Technical Reports Server (NTRS)

Park, Michael A.; Lee-Rausch, Elizabeth M.; Rumsey, Christopher L.

2011-01-01

Two Reynolds-averaged Navier-Stokes codes were used to compute flow over the NASA Trapezoidal Wing at high lift conditions for the 1st AIAA CFD High Lift Prediction Workshop, held in Chicago in June 2010. The unstructured-grid code FUN3D and the structured-grid code CFL3D were applied to several different grid systems. The effects of code, grid system, turbulence model, viscous term treatment, and brackets were studied. The SST model on this configuration predicted lower lift than the Spalart-Allmaras model at high angles of attack; the Spalart-Allmaras model agreed better with experiment. Neglecting viscous cross-derivative terms caused poorer prediction in the wing tip vortex region. Output-based grid adaptation was applied to the unstructured-grid solutions. The adapted grids better resolved wake structures and reduced flap flow separation, which was also observed in uniform grid refinement studies. Limitations of the adaptation method as well as areas for future improvement were identified.

2D-QSAR and 3D-QSAR Analyses for EGFR Inhibitors

PubMed Central

Zhao, Manman; Zheng, Linfeng; Qiu, Chun

2017-01-01

Epidermal growth factor receptor (EGFR) is an important target for cancer therapy. In this study, EGFR inhibitors were investigated to build a two-dimensional quantitative structure-activity relationship (2D-QSAR) model and a three-dimensional quantitative structure-activity relationship (3D-QSAR) model. In the 2D-QSAR model, the support vector machine (SVM) classifier combined with the feature selection method was applied to predict whether a compound was an EGFR inhibitor. As a result, the prediction accuracy of the 2D-QSAR model was 98.99% by using tenfold cross-validation test and 97.67% by using independent set test. Then, in the 3D-QSAR model, the model with q2 = 0.565 (cross-validated correlation coefficient) and r2 = 0.888 (non-cross-validated correlation coefficient) was built to predict the activity of EGFR inhibitors. The mean absolute error (MAE) of the training set and test set was 0.308 log units and 0.526 log units, respectively. In addition, molecular docking was also employed to investigate the interaction between EGFR inhibitors and EGFR. PMID:28630865

Differences in 3D vs. 2D analysis in lumbar spinal fusion simulations.

PubMed

Hsu, Hung-Wei; Bashkuev, Maxim; Pumberger, Matthias; Schmidt, Hendrik

2018-04-27

Lumbar interbody fusion is currently the gold standard in treating patients with disc degeneration or segmental instability. Despite it having been used for several decades, the non-union rate remains high. A failed fusion is frequently attributed to an inadequate mechanical environment after instrumentation. Finite element (FE) models can provide insights into the mechanics of the fusion process. Previous fusion simulations using FE models showed that the geometries and material of the cage can greatly influence the fusion outcome. However, these studies used axisymmetric models which lacked realistic spinal geometries. Therefore, different modeling approaches were evaluated to understand the bone-formation process. Three FE models of the lumbar motion segment (L4-L5) were developed: 2D, Sym-3D and Nonsym-3D. The fusion process based on existing mechano-regulation algorithms using the FE simulations to evaluate the mechanical environment was then integrated into these models. In addition, the influence of different lordotic angles (5, 10 and 15°) was investigated. The volume of newly formed bone, the axial stiffness of the whole segment and bone distribution inside and surrounding the cage were evaluated. In contrast to the Nonsym-3D, the 2D and Sym-3D models predicted excessive bone formation prior to bridging (peak values with 36 and 9% higher than in equilibrium, respectively). The 3D models predicted a more uniform bone distribution compared to the 2D model. The current results demonstrate the crucial role of the realistic 3D geometry of the lumbar motion segment in predicting bone formation after lumbar spinal fusion. Copyright © 2018 Elsevier Ltd. All rights reserved.

Three-dimensional effects for radio frequency antenna modeling

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

Carter, M.D.; Batchelor, D.B.; Stallings, D.C.

1994-10-15

Electromagnetic field calculations for radio frequency (rf) antennas in two dimensions (2-D) neglect finite antenna length effects as well as the feeders leading to the main current strap. The 2-D calculations predict that the return currents in the sidewalls of the antenna structure depend strongly on the plasma parameters, but this prediction is suspect because of experimental evidence. To study the validity of the 2-D approximation, the Multiple Antenna Implementation System (MAntIS) has been used to perform three-dimensional (3-D) modeling of the power spectrum, plasma loading, and inductance for a relevant loop antenna design. Effects on antenna performance caused bymore » feeders to the main current strap and conducting sidewalls are considered. The modeling shows that the feeders affect the launched power spectrum in an indirect way by forcing the driven rf current to return in the antenna structure rather than the plasma, as in the 2-D model. It has also been found that poloidal dependencies in the plasma impedance matrix can reduce the loading predicted from that predicted in the 2-D model. For some plasma parameters, the combined 3-D effects can lead to a reduction in the predicted loading by as much as a factor of 2 from that given by the 2-D model, even with end-effect corrections for the 2-D model.« less

Three-dimensional effects for radio frequency antenna modeling

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

Carter, M.D.; Batchelor, D.B.; Stallings, D.C.

1993-12-31

Electromagnetic field calculations for radio frequency (rf) antennas in two dimensions (2-D) neglect finite antenna length effects as well as the feeders leading to the main current strap. The 2-D calculations predict that the return currents in the sidewalls of the antenna structure depend strongly on the plasma parameters, but this prediction is suspect because of experimental evidence. To study the validity of the 2-D approximation, the Multiple Antenna Implementation System (MAntIS) has been used to perform three-dimensional (3-D) modeling of the power spectrum, plasma loading, and inductance for a relevant loop antenna design. Effects on antenna performance caused bymore » feeders to the main current strap and conducting sidewalls are considered. The modeling shows that the feeders affect the launched power spectrum in an indirect way by forcing the driven rf current to return in the antenna structure rather than the plasma, as in the 2-D model. It has also been found that poloidal dependencies in the plasma impedance matrix can reduce the loading predicted from that predicted in the 2-D model. For some plasma parameters, the combined 3-D effects can lead to a reduction in the predicted loading by as much as a factor of 2 from that given by the 2-D model, even with end-effect corrections for the 2-D model.« less

Limb darkening laws for two exoplanet host stars derived from 3D stellar model atmospheres. Comparison with 1D models and HST light curve observations

NASA Astrophysics Data System (ADS)

Hayek, W.; Sing, D.; Pont, F.; Asplund, M.

2012-03-01

We compare limb darkening laws derived from 3D hydrodynamical model atmospheres and 1D hydrostatic MARCS models for the host stars of two well-studied transiting exoplanet systems, the late-type dwarfs HD 209458 and HD 189733. The surface brightness distribution of the stellar disks is calculated for a wide spectral range using 3D LTE spectrum formation and opacity sampling⋆. We test our theoretical predictions using least-squares fits of model light curves to wavelength-integrated primary eclipses that were observed with the Hubble Space Telescope (HST). The limb darkening law derived from the 3D model of HD 209458 in the spectral region between 2900 Å and 5700 Å produces significantly better fits to the HST data, removing systematic residuals that were previously observed for model light curves based on 1D limb darkening predictions. This difference arises mainly from the shallower mean temperature structure of the 3D model, which is a consequence of the explicit simulation of stellar surface granulation where 1D models need to rely on simplified recipes. In the case of HD 189733, the model atmospheres produce practically equivalent limb darkening curves between 2900 Å and 5700 Å, partly due to obstruction by spectral lines, and the data are not sufficient to distinguish between the light curves. We also analyze HST observations between 5350 Å and 10 500 Å for this star; the 3D model leads to a better fit compared to 1D limb darkening predictions. The significant improvement of fit quality for the HD 209458 system demonstrates the higher degree of realism of 3D hydrodynamical models and the importance of surface granulation for the formation of the atmospheric radiation field of late-type stars. This result agrees well with recent investigations of limb darkening in the solar continuum and other observational tests of the 3D models. The case of HD 189733 is no contradiction as the model light curves are less sensitive to the temperature stratification of the stellar atmosphere and the observed data in the 2900-5700 Å region are not sufficient to distinguish more clearly between the 3D and 1D limb darkening predictions. Full theoretical spectra for both stars are available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/539/A102, as well as at www.astro.ex.ac.uk/people/sing.

Regression models for predicting peak and continuous three-dimensional spinal loads during symmetric and asymmetric lifting tasks.

PubMed

Fathallah, F A; Marras, W S; Parnianpour, M

1999-09-01

Most biomechanical assessments of spinal loading during industrial work have focused on estimating peak spinal compressive forces under static and sagittally symmetric conditions. The main objective of this study was to explore the potential of feasibly predicting three-dimensional (3D) spinal loading in industry from various combinations of trunk kinematics, kinetics, and subject-load characteristics. The study used spinal loading, predicted by a validated electromyography-assisted model, from 11 male participants who performed a series of symmetric and asymmetric lifts. Three classes of models were developed: (a) models using workplace, subject, and trunk motion parameters as independent variables (kinematic models); (b) models using workplace, subject, and measured moments variables (kinetic models); and (c) models incorporating workplace, subject, trunk motion, and measured moments variables (combined models). The results showed that peak 3D spinal loading during symmetric and asymmetric lifting were predicted equally well using all three types of regression models. Continuous 3D loading was predicted best using the combined models. When the use of such models is infeasible, the kinematic models can provide adequate predictions. Finally, lateral shear forces (peak and continuous) were consistently underestimated using all three types of models. The study demonstrated the feasibility of predicting 3D loads on the spine under specific symmetric and asymmetric lifting tasks without the need for collecting EMG information. However, further validation and development of the models should be conducted to assess and extend their applicability to lifting conditions other than those presented in this study. Actual or potential applications of this research include exposure assessment in epidemiological studies, ergonomic intervention, and laboratory task assessment.

Prediction of p38 map kinase inhibitory activity of 3, 4-dihydropyrido [3, 2-d] pyrimidone derivatives using an expert system based on principal component analysis and least square support vector machine

PubMed Central

Shahlaei, M.; Saghaie, L.

2014-01-01

A quantitative structure–activity relationship (QSAR) study is suggested for the prediction of biological activity (pIC50) of 3, 4-dihydropyrido [3,2-d] pyrimidone derivatives as p38 inhibitors. Modeling of the biological activities of compounds of interest as a function of molecular structures was established by means of principal component analysis (PCA) and least square support vector machine (LS-SVM) methods. The results showed that the pIC50 values calculated by LS-SVM are in good agreement with the experimental data, and the performance of the LS-SVM regression model is superior to the PCA-based model. The developed LS-SVM model was applied for the prediction of the biological activities of pyrimidone derivatives, which were not in the modeling procedure. The resulted model showed high prediction ability with root mean square error of prediction of 0.460 for LS-SVM. The study provided a novel and effective approach for predicting biological activities of 3, 4-dihydropyrido [3,2-d] pyrimidone derivatives as p38 inhibitors and disclosed that LS-SVM can be used as a powerful chemometrics tool for QSAR studies. PMID:26339262

The Value of 3D Printing Models of Left Atrial Appendage Using Real-Time 3D Transesophageal Echocardiographic Data in Left Atrial Appendage Occlusion: Applications toward an Era of Truly Personalized Medicine.

PubMed

Liu, Peng; Liu, Rijing; Zhang, Yan; Liu, Yingfeng; Tang, Xiaoming; Cheng, Yanzhen

The objective of this study was to assess the clinical feasibility of generating 3D printing models of left atrial appendage (LAA) using real-time 3D transesophageal echocardiogram (TEE) data for preoperative reference of LAA occlusion. Percutaneous LAA occlusion can effectively prevent patients with atrial fibrillation from stroke. However, the anatomical structure of LAA is so complicated that adequate information of its structure is essential for successful LAA occlusion. Emerging 3D printing technology has the demonstrated potential to structure more accurately than conventional imaging modalities by creating tangible patient-specific models. Typically, 3D printing data sets are acquired from CT and MRI, which may involve intravenous contrast, sedation, and ionizing radiation. It has been reported that 3D models of LAA were successfully created by the data acquired from CT. However, 3D printing of the LAA using real-time 3D TEE data has not yet been explored. Acquisition of 3D transesophageal echocardiographic data from 8 patients with atrial fibrillation was performed using the Philips EPIQ7 ultrasound system. Raw echocardiographic image data were opened in Philips QLAB and converted to 'Cartesian DICOM' format and imported into Mimics® software to create 3D models of LAA, which were printed using a rubber-like material. The printed 3D models were then used for preoperative reference and procedural simulation in LAA occlusion. We successfully printed LAAs of 8 patients. Each LAA costs approximately CNY 800-1,000 and the total process takes 16-17 h. Seven of the 8 Watchman devices predicted by preprocedural 2D TEE images were of the same sizes as those placed in the real operation. Interestingly, 3D printing models were highly reflective of the shape and size of LAAs, and all device sizes predicted by the 3D printing model were fully consistent with those placed in the real operation. Also, the 3D printed model could predict operating difficulty and the presence of a peridevice leak. 3D printing of the LAA using real-time 3D transesophageal echocardiographic data has a perfect and rapid application in LAA occlusion to assist with physician planning and decision making. © 2016 S. Karger AG, Basel.

CPHmodels-3.0--remote homology modeling using structure-guided sequence profiles.

PubMed

Nielsen, Morten; Lundegaard, Claus; Lund, Ole; Petersen, Thomas Nordahl

2010-07-01

CPHmodels-3.0 is a web server predicting protein 3D structure by use of single template homology modeling. The server employs a hybrid of the scoring functions of CPHmodels-2.0 and a novel remote homology-modeling algorithm. A query sequence is first attempted modeled using the fast CPHmodels-2.0 profile-profile scoring function suitable for close homology modeling. The new computational costly remote homology-modeling algorithm is only engaged provided that no suitable PDB template is identified in the initial search. CPHmodels-3.0 was benchmarked in the CASP8 competition and produced models for 94% of the targets (117 out of 128), 74% were predicted as high reliability models (87 out of 117). These achieved an average RMSD of 4.6 A when superimposed to the 3D structure. The remaining 26% low reliably models (30 out of 117) could superimpose to the true 3D structure with an average RMSD of 9.3 A. These performance values place the CPHmodels-3.0 method in the group of high performing 3D prediction tools. Beside its accuracy, one of the important features of the method is its speed. For most queries, the response time of the server is <20 min. The web server is available at http://www.cbs.dtu.dk/services/CPHmodels/.

Improving 3D Genome Reconstructions Using Orthologous and Functional Constraints

PubMed Central

Diament, Alon; Tuller, Tamir

2015-01-01

The study of the 3D architecture of chromosomes has been advancing rapidly in recent years. While a number of methods for 3D reconstruction of genomic models based on Hi-C data were proposed, most of the analyses in the field have been performed on different 3D representation forms (such as graphs). Here, we reproduce most of the previous results on the 3D genomic organization of the eukaryote Saccharomyces cerevisiae using analysis of 3D reconstructions. We show that many of these results can be reproduced in sparse reconstructions, generated from a small fraction of the experimental data (5% of the data), and study the properties of such models. Finally, we propose for the first time a novel approach for improving the accuracy of 3D reconstructions by introducing additional predicted physical interactions to the model, based on orthologous interactions in an evolutionary-related organism and based on predicted functional interactions between genes. We demonstrate that this approach indeed leads to the reconstruction of improved models. PMID:26000633

A Unit-Cell Model for Predicting the Elastic Constants of 3D Four Directional Cylindrical Braided Composite Shafts

NASA Astrophysics Data System (ADS)

Hao, Wenfeng; Liu, Ye; Huang, Xinrong; Liu, Yinghua; Zhu, Jianguo

2018-06-01

In this work, the elastic constants of 3D four directional cylindrical braided composite shafts were predicted using analytical and numerical methods. First, the motion rule of yarn carrier of 3D four directional cylindrical braided composite shafts was analyzed, and the horizontal projection of yarn motion trajectory was obtained. Then, the geometry models of unit-cells with different braiding angles and fiber volume contents were built up, and the meso-scale models of 3D cylindrical braided composite shafts were obtained. Finally, the effects of braiding angles and fiber volume contents on the elastic constants of 3D braided composite shafts were analyzed theoretically and numerically. These results play a crucial role in investigating the mechanical properties of 3D 4-directional braided composites shafts.

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

Shiraishi, Satomi; Moore, Kevin L., E-mail: kevinmoore@ucsd.edu

Purpose: To demonstrate knowledge-based 3D dose prediction for external beam radiotherapy. Methods: Using previously treated plans as training data, an artificial neural network (ANN) was trained to predict a dose matrix based on patient-specific geometric and planning parameters, such as the closest distance (r) to planning target volume (PTV) and organ-at-risks (OARs). Twenty-three prostate and 43 stereotactic radiosurgery/radiotherapy (SRS/SRT) cases with at least one nearby OAR were studied. All were planned with volumetric-modulated arc therapy to prescription doses of 81 Gy for prostate and 12–30 Gy for SRS. Using these clinically approved plans, ANNs were trained to predict dose matrixmore » and the predictive accuracy was evaluated using the dose difference between the clinical plan and prediction, δD = D{sub clin} − D{sub pred}. The mean (〈δD{sub r}〉), standard deviation (σ{sub δD{sub r}}), and their interquartile range (IQR) for the training plans were evaluated at a 2–3 mm interval from the PTV boundary (r{sub PTV}) to assess prediction bias and precision. Initially, unfiltered models which were trained using all plans in the cohorts were created for each treatment site. The models predict approximately the average quality of OAR sparing. Emphasizing a subset of plans that exhibited superior to the average OAR sparing during training, refined models were created to predict high-quality rectum sparing for prostate and brainstem sparing for SRS. Using the refined model, potentially suboptimal plans were identified where the model predicted further sparing of the OARs was achievable. Replans were performed to test if the OAR sparing could be improved as predicted by the model. Results: The refined models demonstrated highly accurate dose distribution prediction. For prostate cases, the average prediction bias for all voxels irrespective of organ delineation ranged from −1% to 0% with maximum IQR of 3% over r{sub PTV} ∈ [ − 6, 30] mm. The average prediction error was less than 10% for the same r{sub PTV} range. For SRS cases, the average prediction bias ranged from −0.7% to 1.5% with maximum IQR of 5% over r{sub PTV} ∈ [ − 4, 32] mm. The average prediction error was less than 8%. Four potentially suboptimal plans were identified for each site and subsequent replanning demonstrated improved sparing of rectum and brainstem. Conclusions: The study demonstrates highly accurate knowledge-based 3D dose predictions for radiotherapy plans.« less

Icing Analysis of a Swept NACA 0012 Wing Using LEWICE3D Version 3.48

NASA Technical Reports Server (NTRS)

Bidwell, Colin S.

2014-01-01

Icing calculations were performed for a NACA 0012 swept wing tip using LEWICE3D Version 3.48 coupled with the ANSYS CFX flow solver. The calculated ice shapes were compared to experimental data generated in the NASA Glenn Icing Research Tunnel (IRT). The IRT tests were designed to test the performance of the LEWICE3D ice void density model which was developed to improve the prediction of swept wing ice shapes. Icing tests were performed for a range of temperatures at two different droplet inertia parameters and two different sweep angles. The predicted mass agreed well with the experiment with an average difference of 12%. The LEWICE3D ice void density model under-predicted void density by an average of 30% for the large inertia parameter cases and by 63% for the small inertia parameter cases. This under-prediction in void density resulted in an over-prediction of ice area by an average of 115%. The LEWICE3D ice void density model produced a larger average area difference with experiment than the standard LEWICE density model, which doesn't account for the voids in the swept wing ice shape, (115% and 75% respectively) but it produced ice shapes which were deemed more appropriate because they were conservative (larger than experiment). Major contributors to the overly conservative ice shape predictions were deficiencies in the leading edge heat transfer and the sensitivity of the void ice density model to the particle inertia parameter. The scallop features present on the ice shapes were thought to generate interstitial flow and horse shoe vortices which enhance the leading edge heat transfer. A set of changes to improve the leading edge heat transfer and the void density model were tested. The changes improved the ice shape predictions considerably. More work needs to be done to evaluate the performance of these modifications for a wider range of geometries and icing conditions.

Icing Analysis of a Swept NACA 0012 Wing Using LEWICE3D Version 3.48

NASA Technical Reports Server (NTRS)

Bidwell, Colin S.

2014-01-01

Icing calculations were performed for a NACA 0012 swept wing tip using LEWICE3D Version 3.48 coupled with the ANSYS CFX flow solver. The calculated ice shapes were compared to experimental data generated in the NASA Glenn Icing Research Tunnel (IRT). The IRT tests were designed to test the performance of the LEWICE3D ice void density model which was developed to improve the prediction of swept wing ice shapes. Icing tests were performed for a range of temperatures at two different droplet inertia parameters and two different sweep angles. The predicted mass agreed well with the experiment with an average difference of 12%. The LEWICE3D ice void density model under-predicted void density by an average of 30% for the large inertia parameter cases and by 63% for the small inertia parameter cases. This under-prediction in void density resulted in an over-prediction of ice area by an average of 115%. The LEWICE3D ice void density model produced a larger average area difference with experiment than the standard LEWICE density model, which doesn't account for the voids in the swept wing ice shape, (115% and 75% respectively) but it produced ice shapes which were deemed more appropriate because they were conservative (larger than experiment). Major contributors to the overly conservative ice shape predictions were deficiencies in the leading edge heat transfer and the sensitivity of the void ice density model to the particle inertia parameter. The scallop features present on the ice shapes were thought to generate interstitial flow and horse shoe vortices which enhance the leading edge heat transfer. A set of changes to improve the leading edge heat transfer and the void density model were tested. The changes improved the ice shape predictions considerably. More work needs to be done to evaluate the performance of these modifications for a wider range of geometries and icing conditions

The Acoustic Analogy: A Powerful Tool in Aeroacoustics with Emphasis on Jet Noise Prediction

NASA Technical Reports Server (NTRS)

Farassat, F.; Doty, Michael J.; Hunter, Craig A.

2004-01-01

The acoustic analogy introduced by Lighthill to study jet noise is now over 50 years old. In the present paper, Lighthill s Acoustic Analogy is revisited together with a brief evaluation of the state-of-the-art of the subject and an exploration of the possibility of further improvements in jet noise prediction from analytical methods, computational fluid dynamics (CFD) predictions, and measurement techniques. Experimental Particle Image Velocimetry (PIV) data is used both to evaluate turbulent statistics from Reynolds-averaged Navier-Stokes (RANS) CFD and to propose correlation models for the Lighthill stress tensor. The NASA Langley Jet3D code is used to study the effect of these models on jet noise prediction. From the analytical investigation, a retarded time correction is shown that improves, by approximately 8 dB, the over-prediction of aft-arc jet noise by Jet3D. In experimental investigation, the PIV data agree well with the CFD mean flow predictions, with room for improvement in Reynolds stress predictions. Initial modifications, suggested by the PIV data, to the form of the Jet3D correlation model showed no noticeable improvements in jet noise prediction.

4D-CT motion estimation using deformable image registration and 5D respiratory motion modeling.

PubMed

Yang, Deshan; Lu, Wei; Low, Daniel A; Deasy, Joseph O; Hope, Andrew J; El Naqa, Issam

2008-10-01

Four-dimensional computed tomography (4D-CT) imaging technology has been developed for radiation therapy to provide tumor and organ images at the different breathing phases. In this work, a procedure is proposed for estimating and modeling the respiratory motion field from acquired 4D-CT imaging data and predicting tissue motion at the different breathing phases. The 4D-CT image data consist of series of multislice CT volume segments acquired in ciné mode. A modified optical flow deformable image registration algorithm is used to compute the image motion from the CT segments to a common full volume 3D-CT reference. This reference volume is reconstructed using the acquired 4D-CT data at the end-of-exhalation phase. The segments are optimally aligned to the reference volume according to a proposed a priori alignment procedure. The registration is applied using a multigrid approach and a feature-preserving image downsampling maxfilter to achieve better computational speed and higher registration accuracy. The registration accuracy is about 1.1 +/- 0.8 mm for the lung region according to our verification using manually selected landmarks and artificially deformed CT volumes. The estimated motion fields are fitted to two 5D (spatial 3D+tidal volume+airflow rate) motion models: forward model and inverse model. The forward model predicts tissue movements and the inverse model predicts CT density changes as a function of tidal volume and airflow rate. A leave-one-out procedure is used to validate these motion models. The estimated modeling prediction errors are about 0.3 mm for the forward model and 0.4 mm for the inverse model.

Comparison of regional air dispersion simulation and ambient air monitoring data for the soil fumigant 1,3-dichloropropene.

PubMed

van Wesenbeeck, I J; Cryer, S A; de Cirugeda Helle, O; Li, C; Driver, J H

2016-11-01

SOFEA v2.0 is an air dispersion modeling tool used to predict acute and chronic pesticide concentrations in air for large air sheds resulting from agronomic practices. A 1,3-dichloropropene (1,3-D) air monitoring study in high use townships in Merced County, CA, logged 3-day average air concentrations at nine locations over a 14.5month period. SOFEA, using weather data measured at the site, and using a historical CDPR regulatory assumption of a constant 320m mixing height, predicted the general pattern and correct order of magnitude for 1,3-D air concentrations as a function of time, but failed to estimate the highest observed 1,3-D concentrations of the monitoring study. A time series and statistical comparison of the measured and modeled data indicated that the model underestimated 1,3-D concentrations during calm periods (wind speed <1m/s), such that the annual average concentration was under predicted by approximately 4.7-fold, and the variability was not representative of the measured data. Calm periods are associated with low mixing heights (MHs) and are more prevalent in the Central Valley of CA during the winter months, and thus the assumption of a constant 320m mixing height is not appropriate. An algorithm was developed to calculate the MH using the air temperature in the weather file when the wind speed was <1m/s. When the model was run using the revised MHs, the average of the modeled 1,3-D concentration Probability Distribution Function (PDF) was within 5% of the measured PDF, and the variability in modeled concentrations more closely matched the measured dataset. Use of the PCRAMMET processed weather data from the site (including PCRAMMET MH) resulted in the global annual average concentration within 2-fold of measured data. Receptor density was also found to have an effect on the modeled 1,3-D concentration PDF, and a 50×50 receptor grid in the nine township domain captured the measured 1,3-D concentration distribution much better than a 3×3 receptor grid (i.e., simulated receptors at the nine monitoring locations). Comparison of the monitored and simulated PDF for 72-h 1,3-D concentrations indicated that SOFEA slightly over predicts the 1,3-D concentration distribution at all percentiles below the 99th with slight under prediction of the 99-100th percentile values. This suggests that without further refinement, the SOFEA2 model, based upon field validation observations, will result in representative but conservative estimates of lifetime exposure to 1,3-D for bystanders in 1,3-D use areas. Copyright © 2016. Published by Elsevier B.V.

Biomimetic three-dimensional tissue models for advanced high-throughput drug screening

PubMed Central

Nam, Ki-Hwan; Smith, Alec S.T.; Lone, Saifullah; Kwon, Sunghoon; Kim, Deok-Ho

2015-01-01

Most current drug screening assays used to identify new drug candidates are 2D cell-based systems, even though such in vitro assays do not adequately recreate the in vivo complexity of 3D tissues. Inadequate representation of the human tissue environment during a preclinical test can result in inaccurate predictions of compound effects on overall tissue functionality. Screening for compound efficacy by focusing on a single pathway or protein target, coupled with difficulties in maintaining long-term 2D monolayers, can serve to exacerbate these issues when utilizing such simplistic model systems for physiological drug screening applications. Numerous studies have shown that cell responses to drugs in 3D culture are improved from those in 2D, with respect to modeling in vivo tissue functionality, which highlights the advantages of using 3D-based models for preclinical drug screens. In this review, we discuss the development of microengineered 3D tissue models which accurately mimic the physiological properties of native tissue samples, and highlight the advantages of using such 3D micro-tissue models over conventional cell-based assays for future drug screening applications. We also discuss biomimetic 3D environments, based-on engineered tissues as potential preclinical models for the development of more predictive drug screening assays for specific disease models. PMID:25385716

5D Modelling: An Efficient Approach for Creating Spatiotemporal Predictive 3D Maps of Large-Scale Cultural Resources

NASA Astrophysics Data System (ADS)

Doulamis, A.; Doulamis, N.; Ioannidis, C.; Chrysouli, C.; Grammalidis, N.; Dimitropoulos, K.; Potsiou, C.; Stathopoulou, E.-K.; Ioannides, M.

2015-08-01

Outdoor large-scale cultural sites are mostly sensitive to environmental, natural and human made factors, implying an imminent need for a spatio-temporal assessment to identify regions of potential cultural interest (material degradation, structuring, conservation). On the other hand, in Cultural Heritage research quite different actors are involved (archaeologists, curators, conservators, simple users) each of diverse needs. All these statements advocate that a 5D modelling (3D geometry plus time plus levels of details) is ideally required for preservation and assessment of outdoor large scale cultural sites, which is currently implemented as a simple aggregation of 3D digital models at different time and levels of details. The main bottleneck of such an approach is its complexity, making 5D modelling impossible to be validated in real life conditions. In this paper, a cost effective and affordable framework for 5D modelling is proposed based on a spatial-temporal dependent aggregation of 3D digital models, by incorporating a predictive assessment procedure to indicate which regions (surfaces) of an object should be reconstructed at higher levels of details at next time instances and which at lower ones. In this way, dynamic change history maps are created, indicating spatial probabilities of regions needed further 3D modelling at forthcoming instances. Using these maps, predictive assessment can be made, that is, to localize surfaces within the objects where a high accuracy reconstruction process needs to be activated at the forthcoming time instances. The proposed 5D Digital Cultural Heritage Model (5D-DCHM) is implemented using open interoperable standards based on the CityGML framework, which also allows the description of additional semantic metadata information. Visualization aspects are also supported to allow easy manipulation, interaction and representation of the 5D-DCHM geometry and the respective semantic information. The open source 3DCityDB incorporating a PostgreSQL geo-database is used to manage and manipulate 3D data and their semantics.

3D QSAR studies on protein tyrosine phosphatase 1B inhibitors: comparison of the quality and predictivity among 3D QSAR models obtained from different conformer-based alignments.

PubMed

Pandey, Gyanendra; Saxena, Anil K

2006-01-01

A set of 65 flexible peptidomimetic competitive inhibitors (52 in the training set and 13 in the test set) of protein tyrosine phosphatase 1B (PTP1B) has been used to compare the quality and predictive power of 3D quantitative structure-activity relationship (QSAR) comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models for the three most commonly used conformer-based alignments, namely, cocrystallized conformer-based alignment (CCBA), docked conformer-based alignment (DCBA), and global minima energy conformer-based alignment (GMCBA). These three conformers of 5-[(2S)-2-({(2S)-2-[(tert-butoxycarbonyl)amino]-3-phenylpropanoyl}amino)3-oxo-3-pentylamino)propyl]-2-(carboxymethoxy)benzoic acid (compound number 66) were obtained from the X-ray structure of its cocrystallized complex with PTP1B (PDB ID: 1JF7), its docking studies, and its global minima by simulated annealing. Among the 3D QSAR models developed using the above three alignments, the CCBA provided the optimal predictive CoMFA model for the training set with cross-validated r2 (q2)=0.708, non-cross-validated r2=0.902, standard error of estimate (s)=0.165, and F=202.553 and the optimal CoMSIA model with q2=0.440, r2=0.799, s=0.192, and F=117.782. These models also showed the best test set prediction for the 13 compounds with predictive r2 values of 0.706 and 0.683, respectively. Though the QSAR models derived using the other two alignments also produced statistically acceptable models in the order DCBA>GMCBA in terms of the values of q2, r2, and predictive r2, they were inferior to the corresponding models derived using CCBA. Thus, the order of preference for the alignment selection for 3D QSAR model development may be CCBA>DCBA>GMCBA, and the information obtained from the CoMFA and CoMSIA contour maps may be useful in designing specific PTP1B inhibitors.

Grid-Adapted FUN3D Computations for the Second High Lift Prediction Workshop

NASA Technical Reports Server (NTRS)

Lee-Rausch, E. M.; Rumsey, C. L.; Park, M. A.

2014-01-01

Contributions of the unstructured Reynolds-averaged Navier-Stokes code FUN3D to the 2nd AIAA CFD High Lift Prediction Workshop are described, and detailed comparisons are made with experimental data. Using workshop-supplied grids, results for the clean wing configuration are compared with results from the structured code CFL3D Using the same turbulence model, both codes compare reasonably well in terms of total forces and moments, and the maximum lift is similarly over-predicted for both codes compared to experiment. By including more representative geometry features such as slat and flap brackets and slat pressure tube bundles, FUN3D captures the general effects of the Reynolds number variation, but under-predicts maximum lift on workshop-supplied grids in comparison with the experimental data, due to excessive separation. However, when output-based, off-body grid adaptation in FUN3D is employed, results improve considerably. In particular, when the geometry includes both brackets and the pressure tube bundles, grid adaptation results in a more accurate prediction of lift near stall in comparison with the wind-tunnel data. Furthermore, a rotation-corrected turbulence model shows improved pressure predictions on the outboard span when using adapted grids.

NASA Trapezoidal Wing Simulation Using Stress-w and One- and Two-Equation Turbulence Models

NASA Technical Reports Server (NTRS)

Rodio, J. J.; Xiao, X; Hassan, H. A.; Rumsey, C. L.

2014-01-01

The Wilcox 2006 stress-omega model (also referred to as WilcoxRSM-w2006) has been implemented in the NASA Langley code CFL3D and used to study a variety of 2-D and 3-D configurations. It predicted a variety of basic cases reasonably well, including secondary flow in a supersonic rectangular duct. One- and two-equation turbulence models that employ the Boussinesq constitutive relation were unable to predict this secondary flow accurately because it is driven by normal turbulent stress differences. For the NASA trapezoidal wing at high angles of attack, the WilcoxRSM-w2006 model predicted lower maximum lift than experiment, similar to results of a two-equation model.

Comprehending 3D Diagrams: Sketching to Support Spatial Reasoning.

PubMed

Gagnier, Kristin M; Atit, Kinnari; Ormand, Carol J; Shipley, Thomas F

2017-10-01

Science, technology, engineering, and mathematics (STEM) disciplines commonly illustrate 3D relationships in diagrams, yet these are often challenging for students. Failing to understand diagrams can hinder success in STEM because scientific practice requires understanding and creating diagrammatic representations. We explore a new approach to improving student understanding of diagrams that convey 3D relations that is based on students generating their own predictive diagrams. Participants' comprehension of 3D spatial diagrams was measured in a pre- and post-design where students selected the correct 2D slice through 3D geologic block diagrams. Generating sketches that predicated the internal structure of a model led to greater improvement in diagram understanding than visualizing the interior of the model without sketching, or sketching the model without attempting to predict unseen spatial relations. In addition, we found a positive correlation between sketched diagram accuracy and improvement on the diagram comprehension measure. Results suggest that generating a predictive diagram facilitates students' abilities to make inferences about spatial relationships in diagrams. Implications for use of sketching in supporting STEM learning are discussed. Copyright © 2016 Cognitive Science Society, Inc.

Strain memory of 2D and 3D rigid inclusion populations in viscous flows - What is clast SPO telling us?

NASA Astrophysics Data System (ADS)

Stahr, Donald W.; Law, Richard D.

2014-11-01

We model the development of shape preferred orientation (SPO) of a large population of two- and three-dimensional (2D and 3D) rigid clasts suspended in a linear viscous matrix deformed by superposed steady and continuously non-steady plane strain flows to investigate the sensitivity of clasts to changing boundary conditions during a single or superposed deformation events. Resultant clast SPOs are compared to one developed by an identical initial population that experienced a steady flow history of constant kinematic vorticity and reached an identical finite strain state, allowing examination of SPO sensitivity to deformation path. Rotation paths of individual triaxial inclusions are complex, even for steady plane strain flow histories. It has been suggested that the 3D nature of the system renders predictions based on 2D models inadequate for applied clast-based kinematic vorticity gauges. We demonstrate that for a large population of clasts, simplification to a 2D model does provide a good approximation to the SPO predicted by full 3D analysis for steady and non-steady plane strain deformation paths. Predictions of shape fabric development from 2D models are not only qualitatively similar to the more complex 3D analysis, but they display the same limitations of techniques based on clast SPO commonly used as a quantitative kinematic vorticity gauge. Our model results from steady, superposed, and non-steady flow histories with a significant pure shearing component at a wide range of finite strain resemble predictions for an identical initial population that experienced a single steady simple shearing deformation. We conclude that individual 2D and 3D clasts respond instantaneously to changes in boundary conditions, however, in aggregate, the SPO of a population of rigid inclusions does not reflect the late-stage kinematics of deformation, nor is it an indicator of the unique 'mean' kinematic vorticity experienced by a deformed rock volume.

Saliency Detection of Stereoscopic 3D Images with Application to Visual Discomfort Prediction

NASA Astrophysics Data System (ADS)

Li, Hong; Luo, Ting; Xu, Haiyong

2017-06-01

Visual saliency detection is potentially useful for a wide range of applications in image processing and computer vision fields. This paper proposes a novel bottom-up saliency detection approach for stereoscopic 3D (S3D) images based on regional covariance matrix. As for S3D saliency detection, besides the traditional 2D low-level visual features, additional 3D depth features should also be considered. However, only limited efforts have been made to investigate how different features (e.g. 2D and 3D features) contribute to the overall saliency of S3D images. The main contribution of this paper is that we introduce a nonlinear feature integration descriptor, i.e., regional covariance matrix, to fuse both 2D and 3D features for S3D saliency detection. The regional covariance matrix is shown to be effective for nonlinear feature integration by modelling the inter-correlation of different feature dimensions. Experimental results demonstrate that the proposed approach outperforms several existing relevant models including 2D extended and pure 3D saliency models. In addition, we also experimentally verified that the proposed S3D saliency map can significantly improve the prediction accuracy of experienced visual discomfort when viewing S3D images.

3D-quantitative structure-activity relationship studies on benzothiadiazepine hydroxamates as inhibitors of tumor necrosis factor-alpha converting enzyme.

PubMed

Murumkar, Prashant R; Giridhar, Rajani; Yadav, Mange Ram

2008-04-01

A set of 29 benzothiadiazepine hydroxamates having selective tumor necrosis factor-alpha converting enzyme inhibitory activity were used to compare the quality and predictive power of 3D-quantitative structure-activity relationship, comparative molecular field analysis, and comparative molecular similarity indices models for the atom-based, centroid/atom-based, data-based, and docked conformer-based alignment. Removal of two outliers from the initial training set of molecules improved the predictivity of models. Among the 3D-quantitative structure-activity relationship models developed using the above four alignments, the database alignment provided the optimal predictive comparative molecular field analysis model for the training set with cross-validated r(2) (q(2)) = 0.510, non-cross-validated r(2) = 0.972, standard error of estimates (s) = 0.098, and F = 215.44 and the optimal comparative molecular similarity indices model with cross-validated r(2) (q(2)) = 0.556, non-cross-validated r(2) = 0.946, standard error of estimates (s) = 0.163, and F = 99.785. These models also showed the best test set prediction for six compounds with predictive r(2) values of 0.460 and 0.535, respectively. The contour maps obtained from 3D-quantitative structure-activity relationship studies were appraised for activity trends for the molecules analyzed. The comparative molecular similarity indices models exhibited good external predictivity as compared with that of comparative molecular field analysis models. The data generated from the present study helped us to further design and report some novel and potent tumor necrosis factor-alpha converting enzyme inhibitors.

Cardiovascular risk prediction in HIV-infected patients: comparing the Framingham, atherosclerotic cardiovascular disease risk score (ASCVD), Systematic Coronary Risk Evaluation for the Netherlands (SCORE-NL) and Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) risk prediction models.

PubMed

Krikke, M; Hoogeveen, R C; Hoepelman, A I M; Visseren, F L J; Arends, J E

2016-04-01

The aim of the study was to compare the predictions of five popular cardiovascular disease (CVD) risk prediction models, namely the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) model, the Framingham Heart Study (FHS) coronary heart disease (FHS-CHD) and general CVD (FHS-CVD) models, the American Heart Association (AHA) atherosclerotic cardiovascular disease risk score (ASCVD) model and the Systematic Coronary Risk Evaluation for the Netherlands (SCORE-NL) model. A cross-sectional design was used to compare the cumulative CVD risk predictions of the models. Furthermore, the predictions of the general CVD models were compared with those of the HIV-specific D:A:D model using three categories (< 10%, 10-20% and > 20%) to categorize the risk and to determine the degree to which patients were categorized similarly or in a higher/lower category. A total of 997 HIV-infected patients were included in the study: 81% were male and they had a median age of 46 [interquartile range (IQR) 40-52] years, a known duration of HIV infection of 6.8 (IQR 3.7-10.9) years, and a median time on ART of 6.4 (IQR 3.0-11.5) years. The D:A:D, ASCVD and SCORE-NL models gave a lower cumulative CVD risk, compared with that of the FHS-CVD and FHS-CHD models. Comparing the general CVD models with the D:A:D model, the FHS-CVD and FHS-CHD models only classified 65% and 79% of patients, respectively, in the same category as did the D:A:D model. However, for the ASCVD and SCORE-NL models, this percentage was 89% and 87%, respectively. Furthermore, FHS-CVD and FHS-CHD attributed a higher CVD risk to 33% and 16% of patients, respectively, while this percentage was < 6% for ASCVD and SCORE-NL. When using FHS-CVD and FHS-CHD, a higher overall CVD risk was attributed to the HIV-infected patients than when using the D:A:D, ASCVD and SCORE-NL models. This could have consequences regarding overtreatment, drug-related adverse events and drug-drug interactions. © 2015 British HIV Association.

A multiphysics 3D model of tissue growth under interstitial perfusion in a tissue-engineering bioreactor.

PubMed

Nava, Michele M; Raimondi, Manuela T; Pietrabissa, Riccardo

2013-11-01

The main challenge in engineered cartilage consists in understanding and controlling the growth process towards a functional tissue. Mathematical and computational modelling can help in the optimal design of the bioreactor configuration and in a quantitative understanding of important culture parameters. In this work, we present a multiphysics computational model for the prediction of cartilage tissue growth in an interstitial perfusion bioreactor. The model consists of two separate sub-models, one two-dimensional (2D) sub-model and one three-dimensional (3D) sub-model, which are coupled between each other. These sub-models account both for the hydrodynamic microenvironment imposed by the bioreactor, using a model based on the Navier-Stokes equation, the mass transport equation and the biomass growth. The biomass, assumed as a phase comprising cells and the synthesised extracellular matrix, has been modelled by using a moving boundary approach. In particular, the boundary at the fluid-biomass interface is moving with a velocity depending from the local oxygen concentration and viscous stress. In this work, we show that all parameters predicted, such as oxygen concentration and wall shear stress, by the 2D sub-model with respect to the ones predicted by the 3D sub-model are systematically overestimated and thus the tissue growth, which directly depends on these parameters. This implies that further predictive models for tissue growth should take into account of the three dimensionality of the problem for any scaffold microarchitecture.

Three-dimensional (3D) structure prediction of the American and African oil-palms β-ketoacyl-[ACP] synthase-II protein by comparative modelling

PubMed Central

Wang, Edina; Chinni, Suresh; Bhore, Subhash Janardhan

2014-01-01

Background: The fatty-acid profile of the vegetable oils determines its properties and nutritional value. Palm-oil obtained from the African oil-palm [Elaeis guineensis Jacq. (Tenera)] contains 44% palmitic acid (C16:0), but, palm-oil obtained from the American oilpalm [Elaeis oleifera] contains only 25% C16:0. In part, the b-ketoacyl-[ACP] synthase II (KASII) [EC: 2.3.1.179] protein is responsible for the high level of C16:0 in palm-oil derived from the African oil-palm. To understand more about E. guineensis KASII (EgKASII) and E. oleifera KASII (EoKASII) proteins, it is essential to know its structures. Hence, this study was undertaken. Objective: The objective of this study was to predict three-dimensional (3D) structure of EgKASII and EoKASII proteins using molecular modelling tools. Materials and Methods: The amino-acid sequences for KASII proteins were retrieved from the protein database of National Center for Biotechnology Information (NCBI), USA. The 3D structures were predicted for both proteins using homology modelling and ab-initio technique approach of protein structure prediction. The molecular dynamics (MD) simulation was performed to refine the predicted structures. The predicted structure models were evaluated and root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values were calculated. Results: The homology modelling showed that EgKASII and EoKASII proteins are 78% and 74% similar with Streptococcus pneumonia KASII and Brucella melitensis KASII, respectively. The EgKASII and EoKASII structures predicted by using ab-initio technique approach shows 6% and 9% deviation to its structures predicted by homology modelling, respectively. The structure refinement and validation confirmed that the predicted structures are accurate. Conclusion: The 3D structures for EgKASII and EoKASII proteins were predicted. However, further research is essential to understand the interaction of EgKASII and EoKASII proteins with its substrates. PMID:24748752

Three-dimensional (3D) structure prediction of the American and African oil-palms β-ketoacyl-[ACP] synthase-II protein by comparative modelling.

PubMed

Wang, Edina; Chinni, Suresh; Bhore, Subhash Janardhan

2014-01-01

The fatty-acid profile of the vegetable oils determines its properties and nutritional value. Palm-oil obtained from the African oil-palm [Elaeis guineensis Jacq. (Tenera)] contains 44% palmitic acid (C16:0), but, palm-oil obtained from the American oilpalm [Elaeis oleifera] contains only 25% C16:0. In part, the b-ketoacyl-[ACP] synthase II (KASII) [EC: 2.3.1.179] protein is responsible for the high level of C16:0 in palm-oil derived from the African oil-palm. To understand more about E. guineensis KASII (EgKASII) and E. oleifera KASII (EoKASII) proteins, it is essential to know its structures. Hence, this study was undertaken. The objective of this study was to predict three-dimensional (3D) structure of EgKASII and EoKASII proteins using molecular modelling tools. The amino-acid sequences for KASII proteins were retrieved from the protein database of National Center for Biotechnology Information (NCBI), USA. The 3D structures were predicted for both proteins using homology modelling and ab-initio technique approach of protein structure prediction. The molecular dynamics (MD) simulation was performed to refine the predicted structures. The predicted structure models were evaluated and root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values were calculated. The homology modelling showed that EgKASII and EoKASII proteins are 78% and 74% similar with Streptococcus pneumonia KASII and Brucella melitensis KASII, respectively. The EgKASII and EoKASII structures predicted by using ab-initio technique approach shows 6% and 9% deviation to its structures predicted by homology modelling, respectively. The structure refinement and validation confirmed that the predicted structures are accurate. The 3D structures for EgKASII and EoKASII proteins were predicted. However, further research is essential to understand the interaction of EgKASII and EoKASII proteins with its substrates.

Automated body weight prediction of dairy cows using 3-dimensional vision.

PubMed

Song, X; Bokkers, E A M; van der Tol, P P J; Groot Koerkamp, P W G; van Mourik, S

2018-05-01

The objectives of this study were to quantify the error of body weight prediction using automatically measured morphological traits in a 3-dimensional (3-D) vision system and to assess the influence of various sources of uncertainty on body weight prediction. In this case study, an image acquisition setup was created in a cow selection box equipped with a top-view 3-D camera. Morphological traits of hip height, hip width, and rump length were automatically extracted from the raw 3-D images taken of the rump area of dairy cows (n = 30). These traits combined with days in milk, age, and parity were used in multiple linear regression models to predict body weight. To find the best prediction model, an exhaustive feature selection algorithm was used to build intermediate models (n = 63). Each model was validated by leave-one-out cross-validation, giving the root mean square error and mean absolute percentage error. The model consisting of hip width (measurement variability of 0.006 m), days in milk, and parity was the best model, with the lowest errors of 41.2 kg of root mean square error and 5.2% mean absolute percentage error. Our integrated system, including the image acquisition setup, image analysis, and the best prediction model, predicted the body weights with a performance similar to that achieved using semi-automated or manual methods. Moreover, the variability of our simplified morphological trait measurement showed a negligible contribution to the uncertainty of body weight prediction. We suggest that dairy cow body weight prediction can be improved by incorporating more predictive morphological traits and by improving the prediction model structure. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Molecular Phylogeny and Predicted 3D Structure of Plant beta-D-N-Acetylhexosaminidase

PubMed Central

Hossain, Md. Anowar

2014-01-01

beta-D-N-Acetylhexosaminidase, a family 20 glycosyl hydrolase, catalyzes the removal of β-1,4-linked N-acetylhexosamine residues from oligosaccharides and their conjugates. We constructed phylogenetic tree of β-hexosaminidases to analyze the evolutionary history and predicted functions of plant hexosaminidases. Phylogenetic analysis reveals the complex history of evolution of plant β-hexosaminidase that can be described by gene duplication events. The 3D structure of tomato β-hexosaminidase (β-Hex-Sl) was predicted by homology modeling using 1now as a template. Structural conformity studies of the best fit model showed that more than 98% of the residues lie inside the favoured and allowed regions where only 0.9% lie in the unfavourable region. Predicted 3D structure contains 531 amino acids residues with glycosyl hydrolase20b domain-I and glycosyl hydrolase20 superfamily domain-II including the (β/α)8 barrel in the central part. The α and β contents of the modeled structure were found to be 33.3% and 12.2%, respectively. Eleven amino acids were found to be involved in ligand-binding site; Asp(330) and Glu(331) could play important roles in enzyme-catalyzed reactions. The predicted model provides a structural framework that can act as a guide to develop a hypothesis for β-Hex-Sl mutagenesis experiments for exploring the functions of this class of enzymes in plant kingdom. PMID:25165734

Prediction of global and local model quality in CASP8 using the ModFOLD server.

PubMed

McGuffin, Liam J

2009-01-01

The development of effective methods for predicting the quality of three-dimensional (3D) models is fundamentally important for the success of tertiary structure (TS) prediction strategies. Since CASP7, the Quality Assessment (QA) category has existed to gauge the ability of various model quality assessment programs (MQAPs) at predicting the relative quality of individual 3D models. For the CASP8 experiment, automated predictions were submitted in the QA category using two methods from the ModFOLD server-ModFOLD version 1.1 and ModFOLDclust. ModFOLD version 1.1 is a single-model machine learning based method, which was used for automated predictions of global model quality (QMODE1). ModFOLDclust is a simple clustering based method, which was used for automated predictions of both global and local quality (QMODE2). In addition, manual predictions of model quality were made using ModFOLD version 2.0--an experimental method that combines the scores from ModFOLDclust and ModFOLD v1.1. Predictions from the ModFOLDclust method were the most successful of the three in terms of the global model quality, whilst the ModFOLD v1.1 method was comparable in performance to other single-model based methods. In addition, the ModFOLDclust method performed well at predicting the per-residue, or local, model quality scores. Predictions of the per-residue errors in our own 3D models, selected using the ModFOLD v2.0 method, were also the most accurate compared with those from other methods. All of the MQAPs described are publicly accessible via the ModFOLD server at: http://www.reading.ac.uk/bioinf/ModFOLD/. The methods are also freely available to download from: http://www.reading.ac.uk/bioinf/downloads/. Copyright 2009 Wiley-Liss, Inc.

Finding Furfural Hydrogenation Catalysts via Predictive Modelling

PubMed Central

Strassberger, Zea; Mooijman, Maurice; Ruijter, Eelco; Alberts, Albert H; Maldonado, Ana G; Orru, Romano V A; Rothenberg, Gadi

2010-01-01

Abstract We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes gave varied yields, from 62% up to >99.9%, with no obvious structure/activity correlations. Control experiments proved that the carbene ligand remains coordinated to the ruthenium centre throughout the reaction. Deuterium-labelling studies showed a secondary isotope effect (kH:kD=1.5). Further mechanistic studies showed that this transfer hydrogenation follows the so-called monohydride pathway. Using these data, we built a predictive model for 13 of the catalysts, based on 2D and 3D molecular descriptors. We tested and validated the model using the remaining five catalysts (cross-validation, R2=0.913). Then, with this model, the conversion and selectivity were predicted for four completely new ruthenium-carbene complexes. These four catalysts were then synthesized and tested. The results were within 3% of the model’s predictions, demonstrating the validity and value of predictive modelling in catalyst optimization. PMID:23193388

Evaluation of Fish Passage at Whitewater Parks Using 2D and 3D Hydraulic Modeling

NASA Astrophysics Data System (ADS)

Hardee, T.; Nelson, P. A.; Kondratieff, M.; Bledsoe, B. P.

2016-12-01

In-stream whitewater parks (WWPs) are increasingly popular recreational amenities that typically create waves by constricting flow through a chute to increase velocities and form a hydraulic jump. However, the hydraulic conditions these structures create can limit longitudinal habitat connectivity and potentially inhibit upstream fish migration, especially of native fishes. An improved understanding of the fundamental hydraulic processes and potential environmental effects of whitewater parks is needed to inform management decisions about Recreational In-Channel Diversions (RICDs). Here, we use hydraulic models to compute a continuous and spatially explicit description of velocity and depth along potential fish swimming paths in the flow field, and the ensemble of potential paths are compared to fish swimming performance data to predict fish passage via logistic regression analysis. While 3d models have been shown to accurately predict trout movement through WWP structures, 2d methods can provide a more cost-effective and manager-friendly approach to assessing the effects of similar hydraulic structures on fish passage when 3d analysis in not feasible. Here, we use 2d models to examine the hydraulics in several WWP structures on the North Fork of the St. Vrain River at Lyons, Colorado, and we compare these model results to fish passage predictions from a 3d model. Our analysis establishes a foundation for a practical, transferable and physically-rigorous 2d modeling approach for mechanistically evaluating the effects of hydraulic structures on fish passage.

Modeling Statistics of Fish Patchiness and Predicting Associated Influence on Statistics of Acoustic Echoes

DTIC Science & Technology

2013-09-30

published 3-D multi-beam data. The Niwa and Anderson models were compared with 3-D multi-beam data collected by Paramo and Gerlotto. The data were...submitted, refereed] Bhatia, S., T.K. Stanton, J. Paramo , and F. Gerlotto (under revision), “Modeling statistics of fish school dimensions using 3-D

Time Dependent Predictive Modeling of DIII-D ITER Baseline Scenario using Predictive TRANSP

NASA Astrophysics Data System (ADS)

Grierson, B. A.; Andre, R. G.; Budny, R. V.; Solomon, W. M.; Yuan, X.; Candy, J.; Pinsker, R. I.; Staebler, G. M.; Holland, C.; Rafiq, T.

2015-11-01

ITER baseline scenario discharges on DIII-D are modeled with TGLF and MMM transitioning from combined ECH (3.3MW) +NBI(2.8MW) heating to NBI only (3.0 MW) heating maintaining βN = 2.0 on DIII-D predicting temperature, density and rotation for comparison to experimental measurements. These models capture the reduction of confinement associated with direct electron heating H98y2 = 0.89 vs. 1.0) consistent with stiff electron transport. Reasonable agreement between experimental and modeled temperature profiles is achieved for both heating methods, whereas density and momentum predictions differ significantly. Transport fluxes from TGLF indicate that on DIII-D the electron energy flux has reached a transition from low-k to high-k turbulence with more stiff high-k transport that inhibits an increase in core electron stored energy with additional electron heating. Projections to ITER also indicate high electron stiffness. Supported by US DOE DE-AC02-09CH11466, DE-FC02-04ER54698, DE-FG02-07ER54917, DE-FG02-92-ER54141.

Design, synthesis, pharmacological evaluation and in silico ADMET prediction of novel substituted benzimidazole derivatives as angiotensin II-AT1 receptor antagonists based on predictive 3D QSAR models.

PubMed

Vyas, V K; Gupta, N; Ghate, M; Patel, S

2014-01-01

In this study we designed novel substituted benzimidazole derivatives and predicted their absorption, distribution, metabolism, excretion and toxicity (ADMET) properties, based on a predictive 3D QSAR study on 132 substituted benzimidazoles as AngII-AT1 receptor antagonists. The two best predicted compounds were synthesized and evaluated for AngII-AT1 receptor antagonism. Three different alignment tools for comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used. The best 3D QSAR models were obtained using the rigid body (Distill) alignment method. CoMFA and CoMSIA models were found to be statistically significant with leave-one-out correlation coefficients (q(2)) of 0.630 and 0.623, respectively, cross-validated coefficients (r(2)cv) of 0.651 and 0.630, respectively, and conventional coefficients of determination (r(2)) of 0.848 and 0.843, respectively. 3D QSAR models were validated using a test set of 24 compounds, giving satisfactory predicted results (r(2)pred) of 0.727 and 0.689 for the CoMFA and CoMSIA models, respectively. We have identified some key features in substituted benzimidazole derivatives, such as lipophilicity and H-bonding at the 2- and 5-positions of the benzimidazole nucleus, respectively, for AT1 receptor antagonistic activity. We designed 20 novel substituted benzimidazole derivatives and predicted their activity. In silico ADMET properties were also predicted for these designed molecules. Finally, the compounds with best predicted activity were synthesized and evaluated for in vitro angiotensin II-AT1 receptor antagonism.

Three-dimensional Dendritic Needle Network model with application to Al-Cu directional solidification experiments

NASA Astrophysics Data System (ADS)

Tourret, D.; Karma, A.; Clarke, A. J.; Gibbs, P. J.; Imhoff, S. D.

2015-06-01

We present a three-dimensional (3D) extension of a previously proposed multi-scale Dendritic Needle Network (DNN) approach for the growth of complex dendritic microstructures. Using a new formulation of the DNN dynamics equations for dendritic paraboloid-branches of a given thickness, one can directly extend the DNN approach to 3D modeling. We validate this new formulation against known scaling laws and analytical solutions that describe the early transient and steady-state growth regimes, respectively. Finally, we compare the predictions of the model to in situ X-ray imaging of Al-Cu alloy solidification experiments. The comparison shows a very good quantitative agreement between 3D simulations and thin sample experiments. It also highlights the importance of full 3D modeling to accurately predict the primary dendrite arm spacing that is significantly over-estimated by 2D simulations.

Three-dimensional Dendritic Needle Network model with application to Al-Cu directional solidification experiments

DOE PAGES

Tourret, D.; Karma, A.; Clarke, A. J.; ...

2015-06-11

We present a three-dimensional (3D) extension of a previously proposed multi-scale Dendritic Needle Network (DNN) approach for the growth of complex dendritic microstructures. Using a new formulation of the DNN dynamics equations for dendritic paraboloid-branches of a given thickness, one can directly extend the DNN approach to 3D modeling. We validate this new formulation against known scaling laws and analytical solutions that describe the early transient and steady-state growth regimes, respectively. Finally, we compare the predictions of the model to in situ X-ray imaging of Al-Cu alloy solidification experiments. The comparison shows a very good quantitative agreement between 3D simulationsmore » and thin sample experiments. It also highlights the importance of full 3D modeling to accurately predict the primary dendrite arm spacing that is significantly over-estimated by 2D simulations.« less

Predicting 3D structure and stability of RNA pseudoknots in monovalent and divalent ion solutions.

PubMed

Shi, Ya-Zhou; Jin, Lei; Feng, Chen-Jie; Tan, Ya-Lan; Tan, Zhi-Jie

2018-06-01

RNA pseudoknots are a kind of minimal RNA tertiary structural motifs, and their three-dimensional (3D) structures and stability play essential roles in a variety of biological functions. Therefore, to predict 3D structures and stability of RNA pseudoknots is essential for understanding their functions. In the work, we employed our previously developed coarse-grained model with implicit salt to make extensive predictions and comprehensive analyses on the 3D structures and stability for RNA pseudoknots in monovalent/divalent ion solutions. The comparisons with available experimental data show that our model can successfully predict the 3D structures of RNA pseudoknots from their sequences, and can also make reliable predictions for the stability of RNA pseudoknots with different lengths and sequences over a wide range of monovalent/divalent ion concentrations. Furthermore, we made comprehensive analyses on the unfolding pathway for various RNA pseudoknots in ion solutions. Our analyses for extensive pseudokonts and the wide range of monovalent/divalent ion concentrations verify that the unfolding pathway of RNA pseudoknots is mainly dependent on the relative stability of unfolded intermediate states, and show that the unfolding pathway of RNA pseudoknots can be significantly modulated by their sequences and solution ion conditions.

Seismic-geodynamic constraints on three-dimensional structure, vertical flow, and heat transfer in the mantle

USGS Publications Warehouse

Forte, A.M.; Woodward, R.L.

1997-01-01

Joint inversions of seismic and geodynamic data are carried out in which we simultaneously constrain global-scale seismic heterogeneity in the mantle as well as the amplitude of vertical mantle flow across the 670 km seismic discontinuity. These inversions reveal the existence of a family of three-dimensional (3-D) mantle models that satisfy the data while at the same time yielding predictions of layered mantle flow. The new 3-D mantle models we obtain demonstrate that the buoyancy forces due to the undulations of the 670 km phase-change boundary strongly inhibit the vertical flow between the upper and lower mantle. The strong stabilizing effect of the 670 km topography also has an important impact on the predicted dynamic topography of the Earth's solid surface and on the surface gravity anomalies. The new 3-D models that predict strongly or partially layered mantle flow provide essentially identical fits to the global seismic data as previous models that have, until now, predicted only whole-mantle flow. The convective vertical transport of heat across the mantle predicted on the basis of the new 3-D models shows that the heat flow is a minimum at 1000 km depth. This suggests the presence at this depth of a globally defined horizon across which the pattern of lateral heterogeneity changes rapidly. Copyright 1997 by the American Geophysical Union.

Drug screening in 3D in vitro tumor models: overcoming current pitfalls of efficacy read-outs.

PubMed

Santo, Vítor E; Rebelo, Sofia P; Estrada, Marta F; Alves, Paula M; Boghaert, Erwin; Brito, Catarina

2017-01-01

There is cumulating evidence that in vitro 3D tumor models with increased physiological relevance can improve the predictive value of pre-clinical research and ultimately contribute to achieve decisions earlier during the development of cancer-targeted therapies. Due to the role of tumor microenvironment in the response of tumor cells to therapeutics, the incorporation of different elements of the tumor niche on cell model design is expected to contribute to the establishment of more predictive in vitro tumor models. This review is focused on the several challenges and adjustments that the field of oncology research is facing to translate these advanced tumor cells models to drug discovery, taking advantage of the progress on culture technologies, imaging platforms, high throughput and automated systems. The choice of 3D cell model, the experimental design, choice of read-outs and interpretation of data obtained from 3D cell models are critical aspects when considering their implementation in drug discovery. In this review, we foresee some of these aspects and depict the potential directions of pre-clinical oncology drug discovery towards improved prediction of drug efficacy. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High Cycle Fatigue Prediction for Mistuned Bladed Disks with Fully Coupled Fluid-Structural Interaction

DTIC Science & Technology

2006-06-01

response (time domain) structural vibration model for mistuned rotor bladed disk based on the efficient SNM model has been developed. The vi- bration...airfoil and 3D wing, unsteady vortex shedding of a stationary cylinder, induced vibration of a cylinder, forced vibration of a pitching airfoil, induced... vibration and flutter boundary of 2D NACA 64A010 transonic airfoil, 3D plate wing structural response. The predicted results agree well with benchmark

Pumping Optimization Model for Pump and Treat Systems - 15091

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

Baker, S.; Ivarson, Kristine A.; Karanovic, M.

2015-01-15

Pump and Treat systems are being utilized to remediate contaminated groundwater in the Hanford 100 Areas adjacent to the Columbia River in Eastern Washington. Design of the systems was supported by a three-dimensional (3D) fate and transport model. This model provided sophisticated simulation capabilities but requires many hours to calculate results for each simulation considered. Many simulations are required to optimize system performance, so a two-dimensional (2D) model was created to reduce run time. The 2D model was developed as a equivalent-property version of the 3D model that derives boundary conditions and aquifer properties from the 3D model. It producesmore » predictions that are very close to the 3D model predictions, allowing it to be used for comparative remedy analyses. Any potential system modifications identified by using the 2D version are verified for use by running the 3D model to confirm performance. The 2D model was incorporated into a comprehensive analysis system (the Pumping Optimization Model, POM) to simplify analysis of multiple simulations. It allows rapid turnaround by utilizing a graphical user interface that: 1 allows operators to create hypothetical scenarios for system operation, 2 feeds the input to the 2D fate and transport model, and 3 displays the scenario results to evaluate performance improvement. All of the above is accomplished within the user interface. Complex analyses can be completed within a few hours and multiple simulations can be compared side-by-side. The POM utilizes standard office computing equipment and established groundwater modeling software.« less

Performance of a reduced-order FSI model for flow-induced vocal fold vibration

NASA Astrophysics Data System (ADS)

Luo, Haoxiang; Chang, Siyuan; Chen, Ye; Rousseau, Bernard; PhonoSim Team

2017-11-01

Vocal fold vibration during speech production involves a three-dimensional unsteady glottal jet flow and three-dimensional nonlinear tissue mechanics. A full 3D fluid-structure interaction (FSI) model is computationally expensive even though it provides most accurate information about the system. On the other hand, an efficient reduced-order FSI model is useful for fast simulation and analysis of the vocal fold dynamics, which can be applied in procedures such as optimization and parameter estimation. In this work, we study performance of a reduced-order model as compared with the corresponding full 3D model in terms of its accuracy in predicting the vibration frequency and deformation mode. In the reduced-order model, we use a 1D flow model coupled with a 3D tissue model that is the same as in the full 3D model. Two different hyperelastic tissue behaviors are assumed. In addition, the vocal fold thickness and subglottal pressure are varied for systematic comparison. The result shows that the reduced-order model provides consistent predictions as the full 3D model across different tissue material assumptions and subglottal pressures. However, the vocal fold thickness has most effect on the model accuracy, especially when the vocal fold is thin.

Accuracy of three-dimensional soft tissue prediction for Le Fort I osteotomy using Dolphin 3D software: a pilot study.

PubMed

Resnick, C M; Dang, R R; Glick, S J; Padwa, B L

2017-03-01

Three-dimensional (3D) soft tissue prediction is replacing two-dimensional analysis in planning for orthognathic surgery. The accuracy of different computational models to predict soft tissue changes in 3D, however, is unclear. A retrospective pilot study was implemented to assess the accuracy of Dolphin 3D software in making these predictions. Seven patients who had a single-segment Le Fort I osteotomy and had preoperative (T 0 ) and >6-month postoperative (T 1 ) cone beam computed tomography (CBCT) scans and 3D photographs were included. The actual skeletal change was determined by subtracting the T 0 from the T 1 CBCT. 3D photographs were overlaid onto the T 0 CBCT and virtual skeletal movements equivalent to the achieved repositioning were applied using Dolphin 3D planner. A 3D soft tissue prediction (T P ) was generated and differences between the T P and T 1 images (error) were measured at 14 points and at the nasolabial angle. A mean linear prediction error of 2.91±2.16mm was found. The mean error at the nasolabial angle was 8.1±5.6°. In conclusion, the ability to accurately predict 3D soft tissue changes after Le Fort I osteotomy using Dolphin 3D software is limited. Copyright © 2016 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

An Evaluation of Two Internal Surrogates for Determining the Three-Dimensional Position of Peripheral Lung Tumors

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

Spoelstra, Femke; Soernsen de Koste, John R. van; Vincent, Andrew

2009-06-01

Purpose: Both carina and diaphragm positions have been used as surrogates during respiratory-gated radiotherapy. We studied the correlation of both surrogates with three-dimensional (3D) tumor position. Methods and Materials: A total of 59 repeat artifact-free four-dimensional (4D) computed tomography (CT) scans, acquired during uncoached breathing, were identified in 23 patients with Stage I lung cancer. Repeat scans were co-registered to the initial 4D CT scan, and tumor, carina, and ipsilateral diaphragm were manually contoured in all phases of each 4D CT data set. Correlation between positions of carina and diaphragm with 3D tumor position was studied by use of log-likelihoodmore » ratio statistics. Models to predict 3D tumor position from internal surrogates at end inspiration (EI) and end expiration (EE) were developed, and model accuracy was tested by calculating SDs of differences between predicted and actual tumor positions. Results: Motion of both the carina and diaphragm significantly correlated with tumor motion, but log-likelihood ratios indicated that the carina was more predictive for tumor position. When craniocaudal tumor position was predicted by use of craniocaudal carina positions, the SDs of the differences between the predicted and observed positions were 2.2 mm and 2.4 mm at EI and EE, respectively. The corresponding SDs derived with the diaphragm positions were 3.7 mm and 3.9 mm at EI and EE, respectively. Prediction errors in the other directions were comparable. Prediction accuracy was similar at EI and EE. Conclusions: The carina is a better surrogate of 3D tumor position than diaphragm position. Because residual prediction errors were observed in this analysis, additional studies will be performed using audio-coached scans.« less

Docking and 3-D QSAR studies on indolyl aryl sulfones. Binding mode exploration at the HIV-1 reverse transcriptase non-nucleoside binding site and design of highly active N-(2-hydroxyethyl)carboxamide and N-(2-hydroxyethyl)carbohydrazide derivatives.

PubMed

Ragno, Rino; Artico, Marino; De Martino, Gabriella; La Regina, Giuseppe; Coluccia, Antonio; Di Pasquali, Alessandra; Silvestri, Romano

2005-01-13

Three-dimensional quantitative structure-activity relationship (3-D QSAR) studies and docking simulations were developed on indolyl aryl sulfones (IASs), a class of novel HIV-1 non-nucleoside reverse transcriptase (RT) inhibitors (Silvestri, et al. J. Med. Chem. 2003, 46, 2482-2493) highly active against wild type and some clinically relevant resistant strains (Y181C, the double mutant K103N-Y181C, and the K103R-V179D-P225H strain, highly resistant to efavirenz). Predictive 3-D QSAR models using the combination of GRID and GOLPE programs were obtained using a receptor-based alignment by means of docking IASs into the non-nucleoside binding site (NNBS) of RT. The derived 3-D QSAR models showed conventional correlation (r(2)) and cross-validated (q(2)) coefficients values ranging from 0.79 to 0.93 and from 0.59 to 0.84, respectively. All described models were validated by an external test set compiled from previously reported pyrryl aryl sulfones (Artico, et al. J. Med. Chem. 1996, 39, 522-530). The most predictive 3-D QSAR model was then used to predict the activity of novel untested IASs. The synthesis of six designed derivatives (prediction set) allowed disclosure of new IASs endowed with high anti-HIV-1 activities.

Muscle function may depend on model selection in forward simulation of normal walking

PubMed Central

Xiao, Ming; Higginson, Jill S.

2008-01-01

The purpose of this study was to quantify how the predicted muscle function would change in a muscle-driven forward simulation of normal walking when changing the number of degrees of freedom in the model. Muscle function was described by individual muscle contributions to the vertical acceleration of the center of mass (COM). We built a two-dimensional (2D) sagittal plane model and a three-dimensional (3D) model in OpenSim and used both models to reproduce the same normal walking data. Perturbation analysis was applied to deduce muscle function in each model. Muscle excitations and contributions to COM support were compared between the 2D and 3D models. We found that the 2D model was able to reproduce similar joint kinematics and kinetics patterns as the 3D model. Individual muscle excitations were different for most of the hip muscles but ankle and knee muscles were able to attain similar excitations. Total induced vertical COM acceleration by muscles and gravity was the same for both models. However, individual muscle contributions to COM support varied, especially for hip muscles. Although there is currently no standard way to validate muscle function predictions, a 3D model seems to be more appropriate for estimating individual hip muscle function. PMID:18804767

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

PubMed

Chan, H W; Unsworth, J

1989-01-01

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

Validity of Treadmill-Derived Critical Speed on Predicting 5000-Meter Track-Running Performance.

PubMed

Nimmerichter, Alfred; Novak, Nina; Triska, Christoph; Prinz, Bernhard; Breese, Brynmor C

2017-03-01

Nimmerichter, A, Novak, N, Triska, C, Prinz, B, and Breese, BC. Validity of treadmill-derived critical speed on predicting 5,000-meter track-running performance. J Strength Cond Res 31(3): 706-714, 2017-To evaluate 3 models of critical speed (CS) for the prediction of 5,000-m running performance, 16 trained athletes completed an incremental test on a treadmill to determine maximal aerobic speed (MAS) and 3 randomly ordered runs to exhaustion at the [INCREMENT]70% intensity, at 110% and 98% of MAS. Critical speed and the distance covered above CS (D') were calculated using the hyperbolic speed-time (HYP), the linear distance-time (LIN), and the linear speed inverse-time model (INV). Five thousand meter performance was determined on a 400-m running track. Individual predictions of 5,000-m running time (t = [5,000-D']/CS) and speed (s = D'/t + CS) were calculated across the 3 models in addition to multiple regression analyses. Prediction accuracy was assessed with the standard error of estimate (SEE) from linear regression analysis and the mean difference expressed in units of measurement and coefficient of variation (%). Five thousand meter running performance (speed: 4.29 ± 0.39 m·s; time: 1,176 ± 117 seconds) was significantly better than the predictions from all 3 models (p < 0.0001). The mean difference was 65-105 seconds (5.7-9.4%) for time and -0.22 to -0.34 m·s (-5.0 to -7.5%) for speed. Predictions from multiple regression analyses with CS and D' as predictor variables were not significantly different from actual running performance (-1.0 to 1.1%). The SEE across all models and predictions was approximately 65 seconds or 0.20 m·s and is therefore considered as moderate. The results of this study have shown the importance of aerobic and anaerobic energy system contribution to predict 5,000-m running performance. Using estimates of CS and D' is valuable for predicting performance over race distances of 5,000 m.

Longitudinal predictive ability of mapping models: examining post-intervention EQ-5D utilities derived from baseline MHAQ data in rheumatoid arthritis patients.

PubMed

Kontodimopoulos, Nick; Bozios, Panagiotis; Yfantopoulos, John; Niakas, Dimitris

2013-04-01

The purpose of this methodological study was to to provide insight into the under-addressed issue of the longitudinal predictive ability of mapping models. Post-intervention predicted and reported utilities were compared, and the effect of disease severity on the observed differences was examined. A cohort of 120 rheumatoid arthritis (RA) patients (60.0% female, mean age 59.0) embarking on therapy with biological agents completed the Modified Health Assessment Questionnaire (MHAQ) and the EQ-5D at baseline, and at 3, 6 and 12 months post-intervention. OLS regression produced a mapping equation to estimate post-intervention EQ-5D utilities from baseline MHAQ data. Predicted and reported utilities were compared with t test, and the prediction error was modeled, using fixed effects, in terms of covariates such as age, gender, time, disease duration, treatment, RF, DAS28 score, predicted and reported EQ-5D. The OLS model (RMSE = 0.207, R(2) = 45.2%) consistently underestimated future utilities, with a mean prediction error of 6.5%. Mean absolute differences between reported and predicted EQ-5D utilities at 3, 6 and 12 months exceeded the typically reported MID of the EQ-5D (0.03). According to the fixed-effects model, time, lower predicted EQ-5D and higher DAS28 scores had a significant impact on prediction errors, which appeared increasingly negative for lower reported EQ-5D scores, i.e., predicted utilities tended to be lower than reported ones in more severe health states. This study builds upon existing research having demonstrated the potential usefulness of mapping disease-specific instruments onto utility measures. The specific issue of longitudinal validity is addressed, as mapping models derived from baseline patients need to be validated on post-therapy samples. The underestimation of post-treatment utilities in the present study, at least in more severe patients, warrants further research before it is prudent to conduct cost-utility analyses in the context of RA by means of the MHAQ alone.

Unchained Melody: Revisiting the Estimation of SF-6D Values

PubMed Central

Craig, Benjamin M.

2015-01-01

Purpose In the original SF-6D valuation study, the analytical design inherited conventions that detrimentally affected its ability to predict values on a quality-adjusted life year (QALY) scale. Our objective is to estimate UK values for SF-6D states using the original data and multi-attribute utility (MAU) regression after addressing its limitations and to compare the revised SF-6D and EQ-5D value predictions. Methods Using the unaltered data (611 respondents, 3503 SG responses), the parameters of the original MAU model were re-estimated under 3 alternative error specifications, known as the instant, episodic, and angular random utility models. Value predictions on a QALY scale were compared to EQ-5D3L predictions using the 1996 Health Survey for England. Results Contrary to the original results, the revised SF-6D value predictions range below 0 QALYs (i.e., worse than death) and agree largely with EQ-5D predictions after adjusting for scale. Although a QALY is defined as a year in optimal health, the SF-6D sets a higher standard for optimal health than the EQ-5D-3L; therefore, it has larger units on a QALY scale by construction (20.9% more). Conclusions Much of the debate in health valuation has focused on differences between preference elicitation tasks, sampling, and instruments. After correcting errant econometric practices and adjusting for differences in QALY scale between the EQ-5D and SF-6D values, the revised predictions demonstrate convergent validity, making them more suitable for UK economic evaluations compared to original estimates. PMID:26359242

Three-dimensional transvaginal sonographic assessment of uterine volume as preoperative predictor of need to morcellate in women undergoing laparoscopic hysterectomy.

PubMed

Gerges, B; Mongelli, M; Casikar, I; Bignardi, T; Condous, G

2017-08-01

In light of recent statements from the United States Food and Drug Administration warning against the use of power morcellation of uterine leiomyomas during laparoscopy, we sought to evaluate the use of preoperative two- (2D) and three- (3D) dimensional transvaginal ultrasound (US) assessment of uterine volume to predict the need for morcellation in women undergoing laparoscopic hysterectomy (LH). This was a prospective observational study performed between October 2008 and November 2011 in a tertiary referral laparoscopic unit. All women scheduled to undergo LH were included and underwent detailed preoperative transvaginal US. Uterine volumes were calculated using 2D-US measurements (ellipsoid formula), and using Virtual Organ Computer-aided AnaLysis (VOCAL™) having acquired 3D-US volumes of the uterus. Age, parity, need to morcellate and final uterine dry weight at histology were recorded. The estimated uterine volumes were then incorporated into a previously published logistic regression model to predict the need to morcellate for both nulliparous and parous women. The probability threshold cut-off of 0.14 (95% sensitivity) was evaluated in terms of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and likelihood ratios (LRs). The performance of the models incorporating 2D- and 3D-US calculations were compared with 2D- and 3D-US-generated volumes alone, using receiver-operating characteristics (ROC) curves. Of 76 women who underwent LH during the study period, 79% (n = 60) had complete background and 3D-US data. Their mean age was 43.7 years, 91.7% were parous and 35% underwent morcellation. The greatest uterine volume that did not require morcellation was 404 mL estimated using 3D-US, which corresponded to a uterine volume of 688.8 mL using 2D-US. The smallest uterine volume that required morcellation was 118.9 mL using 3D-US, which corresponded to a uterine volume of 123.4 mL using 2D-US. The 3D-US uterine volume for parous women with a sensitivity of 95% based on ROC-curve analysis was approximately 120 mL, which equated to a predicted probability of morcellation cut-off of 0.14. For this cut-off, specificity was 55.00%, PPV was 51.35%, NPV was 95.65%, LR+ was 2.11 and LR- was 0.09. Areas under the ROC curves for the morcellation logistic regression model were 0.769 (95% CI, 0.653-0.886) and 0.586 (95% CI, 0.419-0.753) using uterine volumes obtained by 3D-US and by 2D-US, respectively, and they were 0.938 (95% CI, 0.879-0.996) and 0.815 (95% CI, 0.681-0.948) using 3D-US and 2D-US volumes alone. The need to morcellate can be predicted preoperatively using 3D-US uterine volumes obtained by transvaginal US with a fair degree of accuracy. Uteri with volumes smaller than 120 mL at 3D-US are very unlikely to require morcellation. The incorporation of 3D-US-estimated uterine volume into the previously published logistic regression model does not seem to confer any significant improvement when compared with 3D-US uterine volume alone to predict the need to morcellate in women undergoing total LH. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.

PIV Validation of 3D Multicomponent Model for Cold Spray Within Nitrogen and Helium Supersonic Flow Field

NASA Astrophysics Data System (ADS)

Faizan-Ur-Rab, M.; Zahiri, S. H.; Masood, S. H.; Jahedi, M.; Nagarajah, R.

2017-06-01

This study presents the validation of a developed three-dimensional multicomponent model for cold spray process using two particle image velocimetry (PIV) experiments. The k- ɛ type 3D model developed for spherical titanium particles was validated with the measured titanium particle velocity within a nitrogen and helium supersonic jet. The 3D model predicted lower values of particle velocity than the PIV experimental study that used irregularly shaped titanium particles. The results of the 3D model were consistent with the PIV experiment that used spherical titanium powder. The 3D model simulation of particle velocity within the helium and nitrogen jet was coupled with an estimation of titanium particle temperature. This was achieved with the consideration of the fact that cold spray particle temperature is difficult and expensive to measure due to considerably lower temperature of particles than thermal spray. The model predicted an interesting pattern of particle size distribution with respect to the location of impact with a concentration of finer particles close to the jet center. It is believed that the 3D model outcomes for particle velocity, temperature and location could be a useful tool to optimize system design, deposition process and mechanical properties of the additively manufactured cold spray structures.

Response of corrugated fiberboard to moisture flow : a 3-D finite element transient nonlinear analysis

Treesearch

Adeeb A. Rahman; Thomas J. Urbanik; Mustafa Mahamid

2003-01-01

Collapse of fiberboard packaging boxes, in the shipping industry, due to rise in humidity conditions is common and very costly. A 3D FE nonlinear model is developed to predict the moisture flow throughout a corrugated packaging fiberboard sandwich structure. The model predicts how the moisture diffusion will permeate through the layers of a fiberboard (medium and...

Effect of Turbulence Models on Two Massively-Separated Benchmark Flow Cases

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.

2003-01-01

Two massively-separated flow cases (the 2-D hill and the 3-D Ahmed body) were computed with several different turbulence models in the Reynolds-averaged Navier-Stokes code CFL3D as part of participation in a turbulence modeling workshop held in Poitiers, France in October, 2002. Overall, results were disappointing, but were consistent with results from other RANS codes and other turbulence models at the workshop. For the 2-D hill case, those turbulence models that predicted separation location accurately ended up yielding a too-long separation extent downstream. The one model that predicted a shorter separation extent in better agreement with LES data did so only by coincidence: its prediction of earlier reattachment was due to a too-late prediction of the separation location. For the Ahmed body, two slant angles were computed, and CFD performed fairly well for one of the cases (the larger slant angle). Both turbulence models tested in this case were very similar to each other. For the smaller slant angle, CFD predicted massive separation, whereas the experiment showed reattachment about half-way down the center of the face. These test cases serve as reminders that state- of-the-art CFD is currently not a reliable predictor of massively-separated flow physics, and that further validation studies in this area would be beneficial.

3D Printed Organ Models with Physical Properties of Tissue and Integrated Sensors.

PubMed

Qiu, Kaiyan; Zhao, Zichen; Haghiashtiani, Ghazaleh; Guo, Shuang-Zhuang; He, Mingyu; Su, Ruitao; Zhu, Zhijie; Bhuiyan, Didarul B; Murugan, Paari; Meng, Fanben; Park, Sung Hyun; Chu, Chih-Chang; Ogle, Brenda M; Saltzman, Daniel A; Konety, Badrinath R; Sweet, Robert M; McAlpine, Michael C

2018-03-01

The design and development of novel methodologies and customized materials to fabricate patient-specific 3D printed organ models with integrated sensing capabilities could yield advances in smart surgical aids for preoperative planning and rehearsal. Here, we demonstrate 3D printed prostate models with physical properties of tissue and integrated soft electronic sensors using custom-formulated polymeric inks. The models show high quantitative fidelity in static and dynamic mechanical properties, optical characteristics, and anatomical geometries to patient tissues and organs. The models offer tissue-mimicking tactile sensation and behavior and thus can be used for the prediction of organ physical behavior under deformation. The prediction results show good agreement with values obtained from simulations. The models also allow the application of surgical and diagnostic tools to their surface and inner channels. Finally, via the conformal integration of 3D printed soft electronic sensors, pressure applied to the models with surgical tools can be quantitatively measured.

3D Printed Organ Models with Physical Properties of Tissue and Integrated Sensors

PubMed Central

Qiu, Kaiyan; Zhao, Zichen; Haghiashtiani, Ghazaleh; Guo, Shuang-Zhuang; He, Mingyu; Su, Ruitao; Zhu, Zhijie; Bhuiyan, Didarul B.; Murugan, Paari; Meng, Fanben; Park, Sung Hyun; Chu, Chih-Chang; Ogle, Brenda M.; Saltzman, Daniel A.; Konety, Badrinath R.

2017-01-01

The design and development of novel methodologies and customized materials to fabricate patient-specific 3D printed organ models with integrated sensing capabilities could yield advances in smart surgical aids for preoperative planning and rehearsal. Here, we demonstrate 3D printed prostate models with physical properties of tissue and integrated soft electronic sensors using custom-formulated polymeric inks. The models show high quantitative fidelity in static and dynamic mechanical properties, optical characteristics, and anatomical geometries to patient tissues and organs. The models offer tissue-mimicking tactile sensation and behavior and thus can be used for the prediction of organ physical behavior under deformation. The prediction results show good agreement with values obtained from simulations. The models also allow the application of surgical and diagnostic tools to their surface and inner channels. Finally, via the conformal integration of 3D printed soft electronic sensors, pressure applied to the models with surgical tools can be quantitatively measured. PMID:29608202

Calculating Path-Dependent Travel Time Prediction Variance and Covariance fro a Global Tomographic P-Velocity Model

NASA Astrophysics Data System (ADS)

Ballard, S.; Hipp, J. R.; Encarnacao, A.; Young, C. J.; Begnaud, M. L.; Phillips, W. S.

2012-12-01

Seismic event locations can be made more accurate and precise by computing predictions of seismic travel time through high fidelity 3D models of the wave speed in the Earth's interior. Given the variable data quality and uneven data sampling associated with this type of model, it is essential that there be a means to calculate high-quality estimates of the path-dependent variance and covariance associated with the predicted travel times of ray paths through the model. In this paper, we describe a methodology for accomplishing this by exploiting the full model covariance matrix and show examples of path-dependent travel time prediction uncertainty computed from SALSA3D, our global, seamless 3D tomographic P-velocity model. Typical global 3D models have on the order of 1/2 million nodes, so the challenge in calculating the covariance matrix is formidable: 0.9 TB storage for 1/2 of a symmetric matrix, necessitating an Out-Of-Core (OOC) blocked matrix solution technique. With our approach the tomography matrix (G which includes Tikhonov regularization terms) is multiplied by its transpose (GTG) and written in a blocked sub-matrix fashion. We employ a distributed parallel solution paradigm that solves for (GTG)-1 by assigning blocks to individual processing nodes for matrix decomposition update and scaling operations. We first find the Cholesky decomposition of GTG which is subsequently inverted. Next, we employ OOC matrix multiplication methods to calculate the model covariance matrix from (GTG)-1 and an assumed data covariance matrix. Given the model covariance matrix, we solve for the travel-time covariance associated with arbitrary ray-paths by summing the model covariance along both ray paths. Setting the paths equal and taking the square root yields the travel prediction uncertainty for the single path.

Modelling Behaviour of a Carbon Epoxy Composite Exposed to Fire: Part II—Comparison with Experimental Results

PubMed Central

Tranchard, Pauline; Samyn, Fabienne; Duquesne, Sophie; Estèbe, Bruno; Bourbigot, Serge

2017-01-01

Based on a phenomenological methodology, a three dimensional (3D) thermochemical model was developed to predict the temperature profile, the mass loss and the decomposition front of a carbon-reinforced epoxy composite laminate (T700/M21 composite) exposed to fire conditions. This 3D model takes into account the energy accumulation by the solid material, the anisotropic heat conduction, the thermal decomposition of the material, the gas mass flow into the composite, and the internal pressure. Thermophysical properties defined as temperature dependant properties were characterised using existing as well as innovative methodologies in order to use them as inputs into our physical model. The 3D thermochemical model accurately predicts the measured mass loss and observed decomposition front when the carbon fibre/epoxy composite is directly impacted by a propane flame. In short, the model shows its capability to predict the fire behaviour of a carbon fibre reinforced composite for fire safety engineering. PMID:28772836

Modelling Behaviour of a Carbon Epoxy Composite Exposed to Fire: Part II-Comparison with Experimental Results.

PubMed

Tranchard, Pauline; Samyn, Fabienne; Duquesne, Sophie; Estèbe, Bruno; Bourbigot, Serge

2017-04-28

Based on a phenomenological methodology, a three dimensional (3D) thermochemical model was developed to predict the temperature profile, the mass loss and the decomposition front of a carbon-reinforced epoxy composite laminate (T700/M21 composite) exposed to fire conditions. This 3D model takes into account the energy accumulation by the solid material, the anisotropic heat conduction, the thermal decomposition of the material, the gas mass flow into the composite, and the internal pressure. Thermophysical properties defined as temperature dependant properties were characterised using existing as well as innovative methodologies in order to use them as inputs into our physical model. The 3D thermochemical model accurately predicts the measured mass loss and observed decomposition front when the carbon fibre/epoxy composite is directly impacted by a propane flame. In short, the model shows its capability to predict the fire behaviour of a carbon fibre reinforced composite for fire safety engineering.

Sustained immunogenicity of the HPV-16/18 AS04-adjuvanted vaccine administered as a two-dose schedule in adolescent girls: Five-year clinical data and modeling predictions from a randomized study

PubMed Central

Romanowski, Barbara; Schwarz, Tino F; Ferguson, Linda; Peters, Klaus; Dionne, Marc; Behre, Ulrich; Schulze, Karin; Hillemanns, Peter; Suryakiran, Pemmaraju; Thomas, Florence; Struyf, Frank

2016-01-01

In this randomized, partially-blind study (clinicaltrials.gov; NCT00541970), the licensed formulation of the human papillomavirus (HPV)-16/18 AS04-adjuvanted vaccine (20 μg each of HPV-16/18 antigens) was found highly immunogenic up to 4 y after first vaccination, whether administered as a 2-dose (2D) schedule in girls 9–14 y or 3-dose (3D) schedule in women 15–25 y. This end-of-study analysis extends immunogenicity and safety data until Month (M) 60, and presents antibody persistence predictions estimated by piecewise and modified power law models. Healthy females (age stratified: 9–14, 15–19, 20–25 y) were randomized to receive 2D at M0,6 (N = 240 ) or 3D at M0,1,6 (N = 239). Here, results are reported for girls 9–14 y (2D) and women 15–25 y (3D). Seropositivity rates, geometric mean titers (by enzyme-linked immunosorbent assay) and geometric mean titer ratios (GMRs; 3D/2D; post-hoc exploratory analysis) were calculated. All subjects seronegative pre-vaccination in the according-to-protocol immunogenicity cohort were seropositive for anti-HPV-16 and −18 at M60. Antibody responses elicited by the 2D and 3D schedules were comparable at M60, with GMRs close to 1 (anti-HPV-16: 1.13 [95% confidence interval: 0.82–1.54]; anti-HPV-18: 1.06 [0.74–1.51]). Statistical modeling predicted that in 95% of subjects, antibodies induced by 2D and 3D schedules could persist above natural infection levels for ≥ 21 y post-vaccination. The vaccine had a clinically acceptable safety profile in both groups. In conclusion, a 2D M0,6 schedule of the HPV-16/18 AS04-adjuvanted vaccine was immunogenic for up to 5 y in 9–14 y-old girls. Statistical modeling predicted that 2D-induced antibodies could persist for longer than 20 y. PMID:26176261

Performance of a reduced-order FSI model for flow-induced vocal fold vibration

NASA Astrophysics Data System (ADS)

Chang, Siyuan; Luo, Haoxiang; Luo's lab Team

2016-11-01

Vocal fold vibration during speech production involves a three-dimensional unsteady glottal jet flow and three-dimensional nonlinear tissue mechanics. A full 3D fluid-structure interaction (FSI) model is computationally expensive even though it provides most accurate information about the system. On the other hand, an efficient reduced-order FSI model is useful for fast simulation and analysis of the vocal fold dynamics, which is often needed in procedures such as optimization and parameter estimation. In this work, we study the performance of a reduced-order model as compared with the corresponding full 3D model in terms of its accuracy in predicting the vibration frequency and deformation mode. In the reduced-order model, we use a 1D flow model coupled with a 3D tissue model. Two different hyperelastic tissue behaviors are assumed. In addition, the vocal fold thickness and subglottal pressure are varied for systematic comparison. The result shows that the reduced-order model provides consistent predictions as the full 3D model across different tissue material assumptions and subglottal pressures. However, the vocal fold thickness has most effect on the model accuracy, especially when the vocal fold is thin. Supported by the NSF.

Reversal of Glaucoma Hemifield Test Results and Visual Field Features in Glaucoma.

PubMed

Wang, Mengyu; Pasquale, Louis R; Shen, Lucy Q; Boland, Michael V; Wellik, Sarah R; De Moraes, Carlos Gustavo; Myers, Jonathan S; Wang, Hui; Baniasadi, Neda; Li, Dian; Silva, Rafaella Nascimento E; Bex, Peter J; Elze, Tobias

2018-03-01

To develop a visual field (VF) feature model to predict the reversal of glaucoma hemifield test (GHT) results to within normal limits (WNL) after 2 consecutive outside normal limits (ONL) results. Retrospective cohort study. Visual fields of 44 503 eyes from 26 130 participants. Eyes with 3 or more consecutive reliable VFs measured with the Humphrey Field Analyzer (Swedish interactive threshold algorithm standard 24-2) were included. Eyes with ONL GHT results for the 2 baseline VFs were selected. We extracted 3 categories of VF features from the baseline tests: (1) VF global indices (mean deviation [MD] and pattern standard deviation), (2) mismatch between baseline VFs, and (3) VF loss patterns (archetypes). Logistic regression was applied to predict the GHT results reversal. Cross-validation was applied to evaluate the model on testing data by the area under the receiver operating characteristic curve (AUC). We ascertained clinical glaucoma status on a patient subset (n = 97) to determine the usefulness of our model. Predictive models for GHT results reversal using VF features. For the 16 604 eyes with 2 initial ONL results, the prevalence of a subsequent WNL result increased from 0.1% for MD < -12 dB to 13.8% for MD ≥-3 dB. Compared with models with VF global indices, the AUC of predictive models increased from 0.669 (MD ≥-3 dB) and 0.697 (-6 dB ≤ MD < -3 dB) to 0.770 and 0.820, respectively, by adding VF mismatch features and computationally derived VF archetypes (P < 0.001 for both). The GHT results reversal was associated with a large mismatch between baseline VFs. Moreover, the GHT results reversal was associated more with VF archetypes of nonglaucomatous loss, severe widespread loss, and lens rim artifacts. For a subset of 97 eyes, using our model to predict absence of glaucoma based on clinical evidence after 2 ONL results yielded significantly better prediction accuracy (87.7%; P < 0.001) than predicting GHT results reversal (68.8%) with a prescribed specificity 67.7%. Using VF features may predict the GHT results reversal to WNL after 2 consecutive ONL results. Copyright © 2017 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Sensitivity Analysis and Parameter Estimation for a Reactive Transport Model of Uranium Bioremediation

NASA Astrophysics Data System (ADS)

Meyer, P. D.; Yabusaki, S.; Curtis, G. P.; Ye, M.; Fang, Y.

2011-12-01

A three-dimensional, variably-saturated flow and multicomponent biogeochemical reactive transport model of uranium bioremediation was used to generate synthetic data . The 3-D model was based on a field experiment at the U.S. Dept. of Energy Rifle Integrated Field Research Challenge site that used acetate biostimulation of indigenous metal reducing bacteria to catalyze the conversion of aqueous uranium in the +6 oxidation state to immobile solid-associated uranium in the +4 oxidation state. A key assumption in past modeling studies at this site was that a comprehensive reaction network could be developed largely through one-dimensional modeling. Sensitivity analyses and parameter estimation were completed for a 1-D reactive transport model abstracted from the 3-D model to test this assumption, to identify parameters with the greatest potential to contribute to model predictive uncertainty, and to evaluate model structure and data limitations. Results showed that sensitivities of key biogeochemical concentrations varied in space and time, that model nonlinearities and/or parameter interactions have a significant impact on calculated sensitivities, and that the complexity of the model's representation of processes affecting Fe(II) in the system may make it difficult to correctly attribute observed Fe(II) behavior to modeled processes. Non-uniformity of the 3-D simulated groundwater flux and averaging of the 3-D synthetic data for use as calibration targets in the 1-D modeling resulted in systematic errors in the 1-D model parameter estimates and outputs. This occurred despite using the same reaction network for 1-D modeling as used in the data-generating 3-D model. Predictive uncertainty of the 1-D model appeared to be significantly underestimated by linear parameter uncertainty estimates.

Survival curves of Listeria monocytogenes in chorizos modeled with artificial neural networks.

PubMed

Hajmeer, M; Basheer, I; Cliver, D O

2006-09-01

Using artificial neural networks (ANNs), a highly accurate model was developed to simulate survival curves of Listeria monocytogenes in chorizos as affected by the initial water activity (a(w0)) of the sausage formulation, temperature (T), and air inflow velocity (F) where the sausages are stored. The ANN-based survival model (R(2)=0.970) outperformed the regression-based cubic model (R(2)=0.851), and as such was used to derive other models (using regression) that allow prediction of the times needed to drop count by 1, 2, 3, and 4 logs (i.e., nD-values, n=1, 2, 3, 4). The nD-value regression models almost perfectly predicted the various times derived from a number of simulated survival curves exhibiting a wide variety of the operating conditions (R(2)=0.990-0.995). The nD-values were found to decrease with decreasing a(w0), and increasing T and F. The influence of a(w0) on nD-values seems to become more significant at some critical value of a(w0), below which the variation is negligible (0.93 for 1D-value, 0.90 for 2D-value, and <0.85 for 3D- and 4D-values). There is greater influence of storage T and F on 3D- and 4D-values than on 1D- and 2D-values.

NASA Langley developments in response calculations needed for failure and life prediction

NASA Technical Reports Server (NTRS)

Housner, Jerrold M.

1993-01-01

NASA Langley developments in response calculations needed for failure and life predictions are discussed. Topics covered include: structural failure analysis in concurrent engineering; accuracy of independent regional modeling demonstrated on classical example; functional interface method accurately joins incompatible finite element models; interface method for insertion of local detail modeling extended to curve pressurized fuselage window panel; interface concept for joining structural regions; motivation for coupled 2D-3D analysis; compression panel with discontinuous stiffener coupled 2D-3D model and axial surface strains at the middle of the hat stiffener; use of adaptive refinement with multiple methods; adaptive mesh refinement; and studies on quantity effect of bow-type initial imperfections on reliability of stiffened panels.

Engineering 3D Models of Tumors and Bone to Understand Tumor-Induced Bone Disease and Improve Treatments.

PubMed

Kwakwa, Kristin A; Vanderburgh, Joseph P; Guelcher, Scott A; Sterling, Julie A

2017-08-01

Bone is a structurally unique microenvironment that presents many challenges for the development of 3D models for studying bone physiology and diseases, including cancer. As researchers continue to investigate the interactions within the bone microenvironment, the development of 3D models of bone has become critical. 3D models have been developed that replicate some properties of bone, but have not fully reproduced the complex structural and cellular composition of the bone microenvironment. This review will discuss 3D models including polyurethane, silk, and collagen scaffolds that have been developed to study tumor-induced bone disease. In addition, we discuss 3D printing techniques used to better replicate the structure of bone. 3D models that better replicate the bone microenvironment will help researchers better understand the dynamic interactions between tumors and the bone microenvironment, ultimately leading to better models for testing therapeutics and predicting patient outcomes.

Accuracy of three-dimensional facial soft tissue simulation in post-traumatic zygoma reconstruction.

PubMed

Li, P; Zhou, Z W; Ren, J Y; Zhang, Y; Tian, W D; Tang, W

2016-12-01

The aim of this study was to evaluate the accuracy of novel software-CMF-preCADS-for the prediction of soft tissue changes following repositioning surgery for zygomatic fractures. Twenty patients who had sustained an isolated zygomatic fracture accompanied by facial deformity and who were treated with repositioning surgery participated in this study. Cone beam computed tomography (CBCT) scans and three-dimensional (3D) stereophotographs were acquired preoperatively and postoperatively. The 3D skeletal model from the preoperative CBCT data was matched with the postoperative one, and the fractured zygomatic fragments were segmented and aligned to the postoperative position for prediction. Then, the predicted model was matched with the postoperative 3D stereophotograph for quantification of the simulation error. The mean absolute error in the zygomatic soft tissue region between the predicted model and the real one was 1.42±1.56mm for all cases. The accuracy of the prediction (mean absolute error ≤2mm) was 87%. In the subjective assessment it was found that the majority of evaluators considered the predicted model and the postoperative model to be 'very similar'. CMF-preCADS software can provide a realistic, accurate prediction of the facial soft tissue appearance after repositioning surgery for zygomatic fractures. The reliability of this software for other types of repositioning surgery for maxillofacial fractures should be validated in the future. Copyright © 2016. Published by Elsevier Ltd.

Heritabilities of measured and mid-infrared predicted milk fat globule size, milk fat and protein percentages, and their genetic correlations.

PubMed

Fleming, A; Schenkel, F S; Koeck, A; Malchiodi, F; Ali, R A; Corredig, M; Mallard, B; Sargolzaei, M; Miglior, F

2017-05-01

The objective of this study was to estimate the heritability of milk fat globule (MFG) size and mid-infrared (MIR) predicted MFG size in Holstein cattle. The genetic correlations between measured and predicted MFG size with milk fat and protein percentage were also investigated. Average MFG size was measured in 1,583 milk samples taken from 254 Holstein cows from 29 herds across Canada. Size was expressed as volume moment mean (D[4,3]) and surface moment mean (D[3,2]). Analyzed milk samples also had average MFG size predicted from their MIR spectral records. Fat and protein percentages were obtained for all test-day milk samples in the cow's lactation. Univariate and bivariate repeatability animal models were used to estimate heritability and genetic correlations. Moderate heritabilities of 0.364 and 0.466 were found for D[4,3] and D[3,2], respectively, and a strong genetic correlation was found between the 2 traits (0.98). The heritabilities for the MIR-predicted MFG size were lower than those estimated for the measured MFG size at 0.300 for predicted D[4,3] and 0.239 for predicted D[3,2]. The genetic correlation between measured and predicted D[4,3] was 0.685; the correlation was slightly higher between measured and predicted D[3,2] at 0.764, likely due to the better prediction accuracy of D[3,2]. Milk fat percentage had moderate genetic correlations with both D[4,3] and D[3,2] (0.538 and 0.681, respectively). The genetic correlation between predicted MFG size and fat percentage was much stronger (greater than 0.97 for both predicted D[4,3] and D[3,2]). The stronger correlation suggests a limitation for the use of the predicted values of MFG size as indicator traits for true average MFG size in milk in selection programs. Larger samples sizes are required to provide better evidence of the estimated genetic parameters. A genetic component appears to exist for the average MFG size in bovine milk, and the variation could be exploited in selection programs. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

[The third dimension tomography versus cranial X-ray cephalometry to predict maxilla advance by distraction in hypoplastic maxilla].

PubMed

Rosas-Muñoz, Arturo; Soriano-Padilla, Fernando; Rendón-Macías, Mario Enrique

2010-01-01

the osteogenic distraction is the treatment for the correction of the hypoplastic maxilla secondary to the repair of a cleft lip-palate. Its planning is based on articulated models. Our objective was to describe the accuracy of three-dimensional Cephalometry (CT3D) for projecting jaw displacement. three patients with hypoplastic maxilla. Interventions estimation of the advance required of lateral maxilla through Cephalometry of skull (CLC), CT3D and an articulated model (gold standard). Two months after distraction finalized the advance predicted was compared. the error of the advance projection in each patient was smaller with the CT3D versus CLC (+1, +1 and +1 mm versus -10, -14 and -9mm). Corrections post-distraction were of +25 %, +26 % and +38.4 % on the programmed one. CT3D predicted better the correction (+19 %, +10.8 %, +33.4 % versus CLC: -50 %; -60.8 % and -34.6 %). Chewing alterations were not seen in any patient. the planning of the necessary advance for distraction in patients with hypoplastic maxilla by CT3D can shorten the time of studies and should be consider as next to the projection of articulated model.

Understanding differences between DELFT3D and empirical predictions of alongshore sediment transport gradients

USGS Publications Warehouse

List, Jeffrey; Benedet, Lindino; Hanes, Daniel M.; Ruggiero, Peter

2009-01-01

Predictions of alongshore transport gradients are critical for forecasting shoreline change. At the previous ICCE conference, it was demonstrated that alongshore transport gradients predicted by the empirical CERC equation can differ substantially from predictions made by the hydrodynamics-based model Delft3D in the case of a simulated borrow pit on the shoreface. Here we use the Delft3D momentum balance to examine the reason for this difference. Alongshore advective flow accelerations in our Delft3D simulation are mainly driven by pressure gradients resulting from alongshore variations in wave height and setup, and Delft3D transport gradients are controlled by these flow accelerations. The CERC equation does not take this process into account, and for this reason a second empirical transport term is sometimes added when alongshore gradients in wave height are thought to be significant. However, our test case indicates that this second term does not properly predict alongshore transport gradients.

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

PubMed

DeShaw, Jonathan; Rahmatalla, Salam

2014-08-01

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

SALSA3D: A Tomographic Model of Compressional Wave Slowness in the Earth’s Mantle for Improved Travel-Time Prediction and Travel-Time Prediction Uncertainty

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

Ballard, Sanford; Hipp, James R.; Begnaud, Michael L.

The task of monitoring the Earth for nuclear explosions relies heavily on seismic data to detect, locate, and characterize suspected nuclear tests. In this study, motivated by the need to locate suspected explosions as accurately and precisely as possible, we developed a tomographic model of the compressional wave slowness in the Earth’s mantle with primary focus on the accuracy and precision of travel-time predictions for P and Pn ray paths through the model. Path-dependent travel-time prediction uncertainties are obtained by computing the full 3D model covariance matrix and then integrating slowness variance and covariance along ray paths from source tomore » receiver. Path-dependent travel-time prediction uncertainties reflect the amount of seismic data that was used in tomography with very low values for paths represented by abundant data in the tomographic data set and very high values for paths through portions of the model that were poorly sampled by the tomography data set. The pattern of travel-time prediction uncertainty is a direct result of the off-diagonal terms of the model covariance matrix and underscores the importance of incorporating the full model covariance matrix in the determination of travel-time prediction uncertainty. In addition, the computed pattern of uncertainty differs significantly from that of 1D distance-dependent travel-time uncertainties computed using traditional methods, which are only appropriate for use with travel times computed through 1D velocity models.« less

SALSA3D: A Tomographic Model of Compressional Wave Slowness in the Earth’s Mantle for Improved Travel-Time Prediction and Travel-Time Prediction Uncertainty

DOE PAGES

Ballard, Sanford; Hipp, James R.; Begnaud, Michael L.; ...

2016-10-11

The task of monitoring the Earth for nuclear explosions relies heavily on seismic data to detect, locate, and characterize suspected nuclear tests. In this study, motivated by the need to locate suspected explosions as accurately and precisely as possible, we developed a tomographic model of the compressional wave slowness in the Earth’s mantle with primary focus on the accuracy and precision of travel-time predictions for P and Pn ray paths through the model. Path-dependent travel-time prediction uncertainties are obtained by computing the full 3D model covariance matrix and then integrating slowness variance and covariance along ray paths from source tomore » receiver. Path-dependent travel-time prediction uncertainties reflect the amount of seismic data that was used in tomography with very low values for paths represented by abundant data in the tomographic data set and very high values for paths through portions of the model that were poorly sampled by the tomography data set. The pattern of travel-time prediction uncertainty is a direct result of the off-diagonal terms of the model covariance matrix and underscores the importance of incorporating the full model covariance matrix in the determination of travel-time prediction uncertainty. In addition, the computed pattern of uncertainty differs significantly from that of 1D distance-dependent travel-time uncertainties computed using traditional methods, which are only appropriate for use with travel times computed through 1D velocity models.« less

Assessing the external validity of algorithms to estimate EQ-5D-3L from the WOMAC.

PubMed

Kiadaliri, Aliasghar A; Englund, Martin

2016-10-04

The use of mapping algorithms have been suggested as a solution to predict health utilities when no preference-based measure is included in the study. However, validity and predictive performance of these algorithms are highly variable and hence assessing the accuracy and validity of algorithms before use them in a new setting is of importance. The aim of the current study was to assess the predictive accuracy of three mapping algorithms to estimate the EQ-5D-3L from the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) among Swedish people with knee disorders. Two of these algorithms developed using ordinary least squares (OLS) models and one developed using mixture model. The data from 1078 subjects mean (SD) age 69.4 (7.2) years with frequent knee pain and/or knee osteoarthritis from the Malmö Osteoarthritis study in Sweden were used. The algorithms' performance was assessed using mean error, mean absolute error, and root mean squared error. Two types of prediction were estimated for mixture model: weighted average (WA), and conditional on estimated component (CEC). The overall mean was overpredicted by an OLS model and underpredicted by two other algorithms (P < 0.001). All predictions but the CEC predictions of mixture model had a narrower range than the observed scores (22 to 90 %). All algorithms suffered from overprediction for severe health states and underprediction for mild health states with lesser extent for mixture model. While the mixture model outperformed OLS models at the extremes of the EQ-5D-3D distribution, it underperformed around the center of the distribution. While algorithm based on mixture model reflected the distribution of EQ-5D-3L data more accurately compared with OLS models, all algorithms suffered from systematic bias. This calls for caution in applying these mapping algorithms in a new setting particularly in samples with milder knee problems than original sample. Assessing the impact of the choice of these algorithms on cost-effectiveness studies through sensitivity analysis is recommended.

Learning-based saliency model with depth information.

PubMed

Ma, Chih-Yao; Hang, Hsueh-Ming

2015-01-01

Most previous studies on visual saliency focused on two-dimensional (2D) scenes. Due to the rapidly growing three-dimensional (3D) video applications, it is very desirable to know how depth information affects human visual attention. In this study, we first conducted eye-fixation experiments on 3D images. Our fixation data set comprises 475 3D images and 16 subjects. We used a Tobii TX300 eye tracker (Tobii, Stockholm, Sweden) to track the eye movement of each subject. In addition, this database contains 475 computed depth maps. Due to the scarcity of public-domain 3D fixation data, this data set should be useful to the 3D visual attention research community. Then, a learning-based visual attention model was designed to predict human attention. In addition to the popular 2D features, we included the depth map and its derived features. The results indicate that the extra depth information can enhance the saliency estimation accuracy specifically for close-up objects hidden in a complex-texture background. In addition, we examined the effectiveness of various low-, mid-, and high-level features on saliency prediction. Compared with both 2D and 3D state-of-the-art saliency estimation models, our methods show better performance on the 3D test images. The eye-tracking database and the MATLAB source codes for the proposed saliency model and evaluation methods are available on our website.

Predicting longshore gradients in longshore transport: the CERC formula compared to Delft3D

USGS Publications Warehouse

List, Jeffrey H.; Hanes, Daniel M.; Ruggiero, Peter

2007-01-01

The prediction of longshore transport gradients is critical for forecasting shoreline change. We employ simple test cases consisting of shoreface pits at varying distances from the shoreline to compare the longshore transport gradients predicted by the CERC formula against results derived from the process-based model Delft3D. Results show that while in some cases the two approaches give very similar results, in many cases the results diverge greatly. Although neither approach is validated with field data here, the Delft3D-based transport gradients provide much more consistent predictions of erosional and accretionary zones as the pit location varies across the shoreface.

Three-dimensional mapping of soil chemical characteristics at micrometric scale: Statistical prediction by combining 2D SEM-EDX data and 3D X-ray computed micro-tomographic images

NASA Astrophysics Data System (ADS)

Hapca, Simona

2015-04-01

Many soil properties and functions emerge from interactions of physical, chemical and biological processes at microscopic scales, which can be understood only by integrating techniques that traditionally are developed within separate disciplines. While recent advances in imaging techniques, such as X-ray computed tomography (X-ray CT), offer the possibility to reconstruct the 3D physical structure at fine resolutions, for the distribution of chemicals in soil, existing methods, based on scanning electron microscope (SEM) and energy dispersive X-ray detection (EDX), allow for characterization of the chemical composition only on 2D surfaces. At present, direct 3D measurement techniques are still lacking, sequential sectioning of soils, followed by 2D mapping of chemical elements and interpolation to 3D, being an alternative which is explored in this study. Specifically, we develop an integrated experimental and theoretical framework which combines 3D X-ray CT imaging technique with 2D SEM-EDX and use spatial statistics methods to map the chemical composition of soil in 3D. The procedure involves three stages 1) scanning a resin impregnated soil cube by X-ray CT, followed by precision cutting to produce parallel thin slices, the surfaces of which are scanned by SEM-EDX, 2) alignment of the 2D chemical maps within the internal 3D structure of the soil cube, and 3) development, of spatial statistics methods to predict the chemical composition of 3D soil based on the observed 2D chemical and 3D physical data. Specifically, three statistical models consisting of a regression tree, a regression tree kriging and cokriging model were used to predict the 3D spatial distribution of carbon, silicon, iron and oxygen in soil, these chemical elements showing a good spatial agreement between the X-ray grayscale intensities and the corresponding 2D SEM-EDX data. Due to the spatial correlation between the physical and chemical data, the regression-tree model showed a great potential in predicting chemical composition in particular for iron, which is generally sparsely distributed in soil. For carbon, silicon and oxygen, which are more densely distributed, the additional kriging of the regression tree residuals improved significantly the prediction, whereas prediction based on co-kriging was less consistent across replicates, underperforming regression-tree kriging. The present study shows a great potential in integrating geo-statistical methods with imaging techniques to unveil the 3D chemical structure of soil at very fine scales, the framework being suitable to be further applied to other types of imaging data such as images of biological thin sections for characterization of microbial distribution. Key words: X-ray CT, SEM-EDX, segmentation techniques, spatial correlation, 3D soil images, 2D chemical maps.

Numerical simulation of a 100-ton ANFO detonation

NASA Astrophysics Data System (ADS)

Weber, P. W.; Millage, K. K.; Crepeau, J. E.; Happ, H. J.; Gitterman, Y.; Needham, C. E.

2015-03-01

This work describes the results from a US government-owned hydrocode (SHAMRC, Second-Order Hydrodynamic Automatic Mesh Refinement Code) that simulated an explosive detonation experiment with 100,000 kg of Ammonium Nitrate-Fuel Oil (ANFO) and 2,080 kg of Composition B (CompB). The explosive surface charge was nearly hemispherical and detonated in desert terrain. Two-dimensional axisymmetric (2D) and three-dimensional (3D) simulations were conducted, with the 3D model providing a more accurate representation of the experimental setup geometry. Both 2D and 3D simulations yielded overpressure and impulse waveforms that agreed qualitatively with experiment, including the capture of the secondary shock observed in the experiment. The 2D simulation predicted the primary shock arrival time correctly but secondary shock arrival time was early. The 2D-predicted impulse waveforms agreed very well with the experiment, especially at later calculation times, and prediction of the early part of the impulse waveform (associated with the initial peak) was better quantitatively for 2D compared to 3D. The 3D simulation also predicted the primary shock arrival time correctly, and secondary shock arrival times in 3D were closer to the experiment than in the 2D results. The 3D-predicted impulse waveform had better quantitative agreement than 2D for the later part of the impulse waveform. The results of this numerical study show that SHAMRC may be used reliably to predict phenomena associated with the 100-ton detonation. The ultimate fidelity of the simulations was limited by both computer time and memory. The results obtained provide good accuracy and indicate that the code is well suited to predicting the outcomes of explosive detonations.

Modeling late rectal toxicities based on a parameterized representation of the 3D dose distribution

NASA Astrophysics Data System (ADS)

Buettner, Florian; Gulliford, Sarah L.; Webb, Steve; Partridge, Mike

2011-04-01

Many models exist for predicting toxicities based on dose-volume histograms (DVHs) or dose-surface histograms (DSHs). This approach has several drawbacks as firstly the reduction of the dose distribution to a histogram results in the loss of spatial information and secondly the bins of the histograms are highly correlated with each other. Furthermore, some of the complex nonlinear models proposed in the past lack a direct physical interpretation and the ability to predict probabilities rather than binary outcomes. We propose a parameterized representation of the 3D distribution of the dose to the rectal wall which explicitly includes geometrical information in the form of the eccentricity of the dose distribution as well as its lateral and longitudinal extent. We use a nonlinear kernel-based probabilistic model to predict late rectal toxicity based on the parameterized dose distribution and assessed its predictive power using data from the MRC RT01 trial (ISCTRN 47772397). The endpoints under consideration were rectal bleeding, loose stools, and a global toxicity score. We extract simple rules identifying 3D dose patterns related to a specifically low risk of complication. Normal tissue complication probability (NTCP) models based on parameterized representations of geometrical and volumetric measures resulted in areas under the curve (AUCs) of 0.66, 0.63 and 0.67 for predicting rectal bleeding, loose stools and global toxicity, respectively. In comparison, NTCP models based on standard DVHs performed worse and resulted in AUCs of 0.59 for all three endpoints. In conclusion, we have presented low-dimensional, interpretable and nonlinear NTCP models based on the parameterized representation of the dose to the rectal wall. These models had a higher predictive power than models based on standard DVHs and their low dimensionality allowed for the identification of 3D dose patterns related to a low risk of complication.

A computational approach for coupled 1D and 2D/3D CFD modelling of pulse Tube cryocoolers

NASA Astrophysics Data System (ADS)

Fang, T.; Spoor, P. S.; Ghiaasiaan, S. M.

2017-12-01

The physics behind Stirling-type cryocoolers are complicated. One dimensional (1D) simulation tools offer limited details and accuracy, in particular for cryocoolers that have non-linear configurations. Multi-dimensional Computational Fluid Dynamic (CFD) methods are useful but are computationally expensive in simulating cyrocooler systems in their entirety. In view of the fact that some components of a cryocooler, e.g., inertance tubes and compliance tanks, can be modelled as 1D components with little loss of critical information, a 1D-2D/3D coupled model was developed. Accordingly, one-dimensional - like components are represented by specifically developed routines. These routines can be coupled to CFD codes and provide boundary conditions for 2D/3D CFD simulations. The developed coupled model, while preserving sufficient flow field details, is two orders of magnitude faster than equivalent 2D/3D CFD models. The predictions show good agreement with experimental data and 2D/3D CFD model.

Assessment of critical path analyses of the relationship between permeability and electrical conductivity of pore networks

NASA Astrophysics Data System (ADS)

Skaggs, Todd H.

2011-10-01

Critical path analysis (CPA) is a method for estimating macroscopic transport coefficients of heterogeneous materials that are highly disordered at the micro-scale. Developed originally to model conduction in semiconductors, numerous researchers have noted that CPA might also have relevance to flow and transport processes in porous media. However, the results of several numerical investigations of critical path analysis on pore network models raise questions about the applicability of CPA to porous media. Among other things, these studies found that (i) in well-connected 3D networks, CPA predictions were inaccurate and became worse when heterogeneity was increased; and (ii) CPA could not fully explain the transport properties of 2D networks. To better understand the applicability of CPA to porous media, we made numerical computations of permeability and electrical conductivity on 2D and 3D networks with differing pore-size distributions and geometries. A new CPA model for the relationship between the permeability and electrical conductivity was found to be in good agreement with numerical data, and to be a significant improvement over a classical CPA model. In sufficiently disordered 3D networks, the new CPA prediction was within ±20% of the true value, and was nearly optimal in terms of minimizing the squared prediction errors across differing network configurations. The agreement of CPA predictions with 2D network computations was similarly good, although 2D networks are in general not well-suited for evaluating CPA. Numerical transport coefficients derived for regular 3D networks of slit-shaped pores were found to be in better agreement with experimental data from rock samples than were coefficients derived for networks of cylindrical pores.

The impact of lateral variations in lithospheric thickness on glacial isostatic adjustment in West Antarctica

NASA Astrophysics Data System (ADS)

Nield, Grace A.; Whitehouse, Pippa L.; van der Wal, Wouter; Blank, Bas; O'Donnell, John Paul; Stuart, Graham W.

2018-04-01

Differences in predictions of Glacial Isostatic Adjustment (GIA) for Antarctica persist due to uncertainties in deglacial history and Earth rheology. The Earth models adopted in many GIA studies are defined by parameters that vary in the radial direction only and represent a global average Earth structure (referred to as 1D Earth models). Over-simplifying actual Earth structure leads to bias in model predictions in regions where Earth parameters differ significantly from the global average, such as West Antarctica. We investigate the impact of lateral variations in lithospheric thickness on GIA in Antarctica by carrying out two experiments that use different rheological approaches to define 3D Earth models that include spatial variations in lithospheric thickness. The first experiment defines an elastic lithosphere with spatial variations in thickness inferred from seismic studies. We compare the results from this 3D model with results derived from a 1D Earth model that has a uniform lithospheric thickness defined as the average of the 3D lithospheric thickness. Irrespective of deglacial history and sub-lithospheric mantle viscosity, we find higher gradients of present-day uplift rates (i.e. higher amplitude and shorter wavelength) in West Antarctica when using the 3D models, due to the thinner-than-1D-average lithosphere prevalent in this region. The second experiment uses seismically-inferred temperature as input to a power-law rheology thereby allowing the lithosphere to have a viscosity structure. Modelling the lithosphere with a power-law rheology results in behaviour that is equivalent to a thinner-lithosphere model, and it leads to higher amplitude and shorter wavelength deformation compared with the first experiment. We conclude that neglecting spatial variations in lithospheric thickness in GIA models will result in predictions of peak uplift and subsidence that are biased low in West Antarctica. This has important implications for ice-sheet modelling studies as the steeper gradients of uplift predicted from the more realistic 3D model may promote stability in marine-grounded regions of West Antarctica. Including lateral variations in lithospheric thickness, at least to the level of considering West and East Antarctica separately, is important for capturing short wavelength deformation and it has the potential to provide a better fit to GPS observations as well as an improved GIA correction for GRACE data.

Experimental validation of boundary element methods for noise prediction

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Oswald, Fred B.

1992-01-01

Experimental validation of methods to predict radiated noise is presented. A combined finite element and boundary element model was used to predict the vibration and noise of a rectangular box excited by a mechanical shaker. The predicted noise was compared to sound power measured by the acoustic intensity method. Inaccuracies in the finite element model shifted the resonance frequencies by about 5 percent. The predicted and measured sound power levels agree within about 2.5 dB. In a second experiment, measured vibration data was used with a boundary element model to predict noise radiation from the top of an operating gearbox. The predicted and measured sound power for the gearbox agree within about 3 dB.

Development of a 3D log sawing optimization system for small sawmills in central Appalachia, US

Treesearch

Wenshu Lin; Jingxin Wang; Edward Thomas

2011-01-01

A 3D log sawing optimization system was developed to perform log generation, opening face determination, sawing simulation, and lumber grading using 3D modeling techniques. Heuristic and dynamic programming algorithms were used to determine opening face and grade sawing optimization. Positions and shapes of internal log defects were predicted using a model developed by...

A Novel Quasi-3D Method for Cascade Flow Considering Axial Velocity Density Ratio

NASA Astrophysics Data System (ADS)

Chen, Zhiqiang; Zhou, Ming; Xu, Quanyong; Huang, Xudong

2018-03-01

A novel quasi-3D Computational Fluid Dynamics (CFD) method of mid-span flow simulation for compressor cascades is proposed. Two dimension (2D) Reynolds-Averaged Navier-Stokes (RANS) method is shown facing challenge in predicting mid-span flow with a unity Axial Velocity Density Ratio (AVDR). Three dimension (3D) RANS solution also shows distinct discrepancies if the AVDR is not predicted correctly. In this paper, 2D and 3D CFD results discrepancies are analyzed and a novel quasi-3D CFD method is proposed. The new quasi-3D model is derived by reducing 3D RANS Finite Volume Method (FVM) discretization over a one-spanwise-layer structured mesh cell. The sidewall effect is considered by two parts. The first part is explicit interface fluxes of mass, momentum and energy as well as turbulence. The second part is a cell boundary scaling factor representing sidewall boundary layer contraction. The performance of the novel quasi-3D method is validated on mid-span pressure distribution, pressure loss and shock prediction of two typical cascades. The results show good agreement with the experiment data on cascade SJ301-20 and cascade AC6-10 at all test condition. The proposed quasi-3D method shows superior accuracy over traditional 2D RANS method and 3D RANS method in performance prediction of compressor cascade.

Modeling and simulation studies of human β3 adrenergic receptor and its interactions with agonists.

PubMed

Sahi, Shakti; Tewatia, Parul; Malik, Balwant K

2012-12-01

β3 adrenergic receptor (β3AR) is known to mediate various pharmacological and physiological effects such as thermogenesis in brown adipocytes, lipolysis in white adipocytes, glucose homeostasis and intestinal smooth muscle relaxation. Several efforts have been made in this field to understand their function and regulation in different human tissues and they have emerged as potential attractive targets in drug discovery for the treatment of diabetes, depression, obesity etc. Although the crystal structures of Bovine Rhodopsin and β2 adrenergic receptor have been resolved, to date there is no three dimensional structural information on β3AR. Our aim in this study was to model 3D structure of β3AR by various molecular modeling and simulation techniques. In this paper, we describe a refined predicted model of β3AR using different algorithms for structure prediction. The structural refinement and minimization of the generated 3D model of β3AR were done by Schrodinger suite 9.1. Docking studies of β3AR model with the known agonists enabled us to identify specific residues, viz, Asp 117, Ser 208, Ser 209, Ser 212, Arg 315, Asn 332, within the β3AR binding pocket, which might play an important role in ligand binding. Receptor ligand interaction studies clearly indicated that these five residues showed strong hydrogen bonding interactions with the ligands. The results have been correlated with the experimental data available. The predicted ligand binding interactions and the simulation studies validate the methods used to predict the 3D-structure.

Selective 4D modelling framework for spatial-temporal land information management system

NASA Astrophysics Data System (ADS)

Doulamis, Anastasios; Soile, Sofia; Doulamis, Nikolaos; Chrisouli, Christina; Grammalidis, Nikos; Dimitropoulos, Kosmas; Manesis, Charalambos; Potsiou, Chryssy; Ioannidis, Charalabos

2015-06-01

This paper introduces a predictive (selective) 4D modelling framework where only the spatial 3D differences are modelled at the forthcoming time instances, while regions of no significant spatial-temporal alterations remain intact. To accomplish this, initially spatial-temporal analysis is applied between 3D digital models captured at different time instances. So, the creation of dynamic change history maps is made. Change history maps indicate spatial probabilities of regions needed further 3D modelling at forthcoming instances. Thus, change history maps are good examples for a predictive assessment, that is, to localize surfaces within the objects where a high accuracy reconstruction process needs to be activated at the forthcoming time instances. The proposed 4D Land Information Management System (LIMS) is implemented using open interoperable standards based on the CityGML framework. CityGML allows the description of the semantic metadata information and the rights of the land resources. Visualization aspects are also supported to allow easy manipulation, interaction and representation of the 4D LIMS digital parcels and the respective semantic information. The open source 3DCityDB incorporating a PostgreSQL geo-database is used to manage and manipulate 3D data and their semantics. An application is made to detect the change through time of a 3D block of plots in an urban area of Athens, Greece. Starting with an accurate 3D model of the buildings in 1983, a change history map is created using automated dense image matching on aerial photos of 2010. For both time instances meshes are created and through their comparison the changes are detected.

US EPA 2012 Air Quality Fused Surface for the Conterminous U.S. Map Service

EPA Pesticide Factsheets

This web service contains a polygon layer that depicts fused air quality predictions for 2012 for census tracts in the conterminous United States. Fused air quality predictions (for ozone and PM2.5) are modeled using a Bayesian space-time downscaling fusion model approach described in a series of three published journal papers: 1) (Berrocal, V., Gelfand, A. E. and Holland, D. M. (2012). Space-time fusion under error in computer model output: an application to modeling air quality. Biometrics 68, 837-848; 2) Berrocal, V., Gelfand, A. E. and Holland, D. M. (2010). A bivariate space-time downscaler under space and time misalignment. The Annals of Applied Statistics 4, 1942-1975; and 3) Berrocal, V., Gelfand, A. E., and Holland, D. M. (2010). A spatio-temporal downscaler for output from numerical models. J. of Agricultural, Biological,and Environmental Statistics 15, 176-197) is used to provide daily, predictive PM2.5 (daily average) and O3 (daily 8-hr maximum) surfaces for 2012. Summer (O3) and annual (PM2.5) means calculated and published. The downscaling fusion model uses both air quality monitoring data from the National Air Monitoring Stations/State and Local Air Monitoring Stations (NAMS/SLAMS) and numerical output from the Models-3/Community Multiscale Air Quality (CMAQ). Currently, predictions at the US census tract centroid locations within the 12 km CMAQ domain are archived. Predictions at the CMAQ grid cell centroids, or any desired set of locations co

3-D Modeling of a Nearshore Dye Release

NASA Astrophysics Data System (ADS)

Maxwell, A. R.; Hibler, L. F.; Miller, L. M.

2006-12-01

The usage of computer modeling software in predicting the behavior of a plume discharged into deep water is well established. Nearfield plume spreading in coastal areas with complex bathymetry is less commonly studied; in addition to geometry, some of the difficulties of this environment include: tidal exchange, temperature, and salinity gradients. Although some researchers have applied complex hydrodynamic models to this problem, nearfield regions are typically modeled by calibration of an empirical or expert system model. In the present study, the 3D hydrodynamic model Delft3D-FLOW was used to predict the advective transport from a point release in Sequim Bay, Washington. A nested model approach was used, wherein a coarse model using a mesh extending to nearby tide gages (cell sizes up to 1 km) was run over several tidal cycles in order to provide boundary conditions to a smaller area. The nested mesh (cell sizes up to 30 m) was forced on two open boundaries using the water surface elevation derived from the coarse model. Initial experiments with the uncalibrated model were conducted in order to predict plume propagation based on the best available field data. Field experiments were subsequently carried out by releasing rhodamine dye into the bay at near-peak flood tidal current and near high slack tidal conditions. Surface and submerged releases were carried out from an anchored vessel. Concurrently collected data from the experiment include temperature, salinity, dye concentration, and hyperspectral imagery, collected from boats and aircraft. A REMUS autonomous underwater vehicle was used to measure current velocity and dye concentration at varying depths, as well as to acquire additional bathymetric information. Preliminary results indicate that the 3D hydrodynamic model offers a reasonable prediction of plume propagation speed and shape. A sensitivity analysis is underway to determine the significant factors in effectively using the model as a predictive tool for plume tracking in data-limited environments. The Delft-PART stochastic particle transport model is also being examined to determine its utility for the present study.

Application of a High-Fidelity Icing Analysis Method to a Model-Scale Rotor in Forward Flight

NASA Technical Reports Server (NTRS)

Narducci, Robert; Orr, Stanley; Kreeger, Richard E.

2012-01-01

An icing analysis process involving the loose coupling of OVERFLOW-RCAS for rotor performance prediction and with LEWICE3D for thermal analysis and ice accretion is applied to a model-scale rotor for validation. The process offers high-fidelity rotor analysis for the noniced and iced rotor performance evaluation that accounts for the interaction of nonlinear aerodynamics with blade elastic deformations. Ice accumulation prediction also involves loosely coupled data exchanges between OVERFLOW and LEWICE3D to produce accurate ice shapes. Validation of the process uses data collected in the 1993 icing test involving Sikorsky's Powered Force Model. Non-iced and iced rotor performance predictions are compared to experimental measurements as are predicted ice shapes.

Deformation behaviors of three-dimensional graphene honeycombs under out-of-plane compression: Atomistic simulations and predictive modeling

NASA Astrophysics Data System (ADS)

Meng, Fanchao; Chen, Cheng; Hu, Dianyin; Song, Jun

2017-12-01

Combining atomistic simulations and continuum modeling, a comprehensive study of the out-of-plane compressive deformation behaviors of equilateral three-dimensional (3D) graphene honeycombs was performed. It was demonstrated that under out-of-plane compression, the honeycomb exhibits two critical deformation events, i.e., elastic mechanical instability (including elastic buckling and structural transformation) and inelastic structural collapse. The above events were shown to be strongly dependent on the honeycomb cell size and affected by the local atomic bonding at the cell junction. By treating the 3D graphene honeycomb as a continuum cellular solid, and accounting for the structural heterogeneity and constraint at the junction, a set of analytical models were developed to accurately predict the threshold stresses corresponding to the onset of those deformation events. The present study elucidates key structure-property relationships of 3D graphene honeycombs under out-of-plane compression, and provides a comprehensive theoretical framework to predictively analyze their deformation responses, and more generally, offers critical new knowledge for the rational bottom-up design of 3D networks of two-dimensional nanomaterials.

Extended evaluation on the ES-D3 cell differentiation assay combined with the BeWo transport model, to predict relative developmental toxicity of triazole compounds.

PubMed

Li, Hequn; Flick, Burkhard; Rietjens, Ivonne M C M; Louisse, Jochem; Schneider, Steffen; van Ravenzwaay, Bennard

2016-05-01

The mouse embryonic stem D3 (ES-D3) cell differentiation assay is based on the morphometric measurement of cardiomyocyte differentiation and is a promising tool to detect developmental toxicity of compounds. The BeWo transport model, consisting of BeWo b30 cells grown on transwell inserts and mimicking the placental barrier, is useful to determine relative placental transport velocities of compounds. We have previously demonstrated the usefulness of the ES-D3 cell differentiation assay in combination with the in vitro BeWo transport model to predict the relative in vivo developmental toxicity potencies of a set of reference azole compounds. To further evaluate this combined in vitro toxicokinetic and toxicodynamic approach, we combined ES-D3 cell differentiation data of six novel triazoles with relative transport rates obtained from the BeWo model and compared the obtained ranking to the developmental toxicity ranking as derived from in vivo data. The data show that the combined in vitro approach provided a correct prediction for in vivo developmental toxicity, whereas the ES-D3 cell differentiation assay as stand-alone did not. In conclusion, we have validated the combined in vitro approach for developmental toxicity, which we have previously developed with a set of reference azoles, for a set of six novel triazoles. We suggest that this combined model, which takes both toxicodynamic and toxicokinetic aspects into account, should be further validated for other chemical classes of developmental toxicants.

A model-based 3D patient-specific pre-treatment QA method for VMAT using the EPID

NASA Astrophysics Data System (ADS)

McCowan, P. M.; Asuni, G.; van Beek, T.; van Uytven, E.; Kujanpaa, K.; McCurdy, B. M. C.

2017-02-01

This study reports the development and validation of a model-based, 3D patient dose reconstruction method for pre-treatment quality assurance using EPID images. The method is also investigated for sensitivity to potential MLC delivery errors. Each cine-mode EPID image acquired during plan delivery was processed using a previously developed back-projection dose reconstruction model providing a 3D dose estimate on the CT simulation data. Validation was carried out using 24 SBRT-VMAT patient plans by comparing: (1) ion chamber point dose measurements in a solid water phantom, (2) the treatment planning system (TPS) predicted 3D dose to the EPID reconstructed 3D dose in a solid water phantom, and (3) the TPS predicted 3D dose to the EPID and our forward predicted reconstructed 3D dose in the patient (CT data). AAA and AcurosXB were used for TPS predictions. Dose distributions were compared using 3%/3 mm (95% tolerance) and 2%/2 mm (90% tolerance) γ-tests in the planning target volume (PTV) and 20% dose volumes. The average percentage point dose differences between the ion chamber and the EPID, AcurosXB, and AAA were 0.73  ±  1.25%, 0.38  ±  0.96% and 1.06  ±  1.34% respectively. For the patient (CT) dose comparisons, seven (3%/3 mm) and nine (2%/2 mm) plans failed the EPID versus AAA. All plans passed the EPID versus Acuros XB and the EPID versus forward model γ-comparisons. Four types of MLC sensitive errors (opening, shifting, stuck, and retracting), of varying magnitude (0.2, 0.5, 1.0, 2.0 mm), were introduced into six different SBRT-VMAT plans. γ-comparisons of the erroneous EPID dose and original predicted dose were carried out using the same criteria as above. For all plans, the sensitivity testing using a 3%/3 mm γ-test in the PTV successfully determined MLC errors on the order of 1.0 mm, except for the single leaf retraction-type error. A 2%/2 mm criteria produced similar results with two more additional detected errors.

Transverse Tensile Properties of 3 Dimension-4 Directional Braided Cf/SiC Composite Based on Double-Scale Model

NASA Astrophysics Data System (ADS)

Niu, Xuming; Sun, Zhigang; Song, Yingdong

2017-11-01

In this thesis, a double-scale model for 3 Dimension-4 directional(3D-4d) braided C/SiC composites(CMCs) has been proposed to investigate mechanical properties of it. The double-scale model involves micro-scale which takes fiber/matrix/porosity in fibers tows into consideration and the unit cell scale which considers the 3D-4d braiding structure. Basing on the Micro-optical photographs of composite, we can build a parameterized finite element model that reflects structure of 3D-4d braided composites. The mechanical properties of fiber tows in transverse direction are studied by combining the crack band theory for matrix cracking and cohesive zone model for interface debonding. Transverse tensile process of 3D-4d CMCs can be simulated by introducing mechanical properties of fiber tows into finite element of 3D-4d braided CMCs. Quasi-static tensile tests of 3D-4d braided CMCs have been performed with PWS-100 test system. The predicted tensile stress-strain curve by the double scale model finds good agreement with the experimental results.

Predicting CH4 adsorption capacity of microporous carbon using N2 isotherm and a new analytical model

USGS Publications Warehouse

Sun, Jielun; Chen, S.; Rostam-Abadi, M.; Rood, M.J.

1998-01-01

A new analytical pore size distribution (PSD) model was developed to predict CH4 adsorption (storage) capacity of microporous adsorbent carbon. The model is based on a 3-D adsorption isotherm equation, derived from statistical mechanical principles. Least squares error minimization is used to solve the PSD without any pre-assumed distribution function. In comparison with several well-accepted analytical methods from the literature, this 3-D model offers relatively realistic PSD description for select reference materials, including activated carbon fibers. N2 and CH4 adsorption data were correlated using the 3-D model for commercial carbons BPL and AX-21. Predicted CH4 adsorption isotherms, based on N2 adsorption at 77 K, were in reasonable agreement with the experimental CH4 isotherms. Modeling results indicate that not all the pores contribute the same percentage Vm/Vs for CH4 storage due to different adsorbed CH4 densities. Pores near 8-9 A?? shows higher Vm/Vs on the equivalent volume basis than does larger pores.

Three-dimensional effects for radio frequency antenna modeling

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

Carter, M.D.; Batchelor, D.B.; Stallings, D.C.

1993-09-01

Electromagnetic field calculations for radio frequency (rf) antennas in two dimensions (2-D) neglect finite antenna length effects as well as the feeders leading to the main current strap. Comparisons with experiments indicate that these 2-D calculations can overestimate the loading of the antenna and fail to give the correct reactive behavior. To study the validity of the 2-D approximation, the Multiple Antenna Implementation System (MAntIS) has been used to perform 3-D modeling of the power spectrum, plasma loading, and inductance for a relevant loop antenna design. Effects on antenna performance caused by feeders to the main current strap, conducting sidewalls,more » and finite phase velocity are considered. The plasma impedance matrix for the loading calculation is generated by use of the ORION-1D code. The 3-D model is benchmarked with the 2-D model in the 2-D limit. For finite-length antennas, inductance calculations are found to be in much more reasonable agreement with experiments for 3-D modeling than for the 2-D estimates. The modeling shows that the feeders affect the launched power spectrum in an indirect way by forcing the driven rf current to return in the antenna sidewalls rather than in the plasma as in the 2-D model. Thus, the feeders have much more influence than the plasma on the currents that return in the sidewall. It has also been found that poloidal dependencies in the plasma impedance matrix can reduce the loading from that predicted in the 2-D model. For some plasma parameters, the combined 3-D effects can lead to a reduction in the predicted loading by as much as a factor of 2 from that given by the 2-D model.« less

3D analysis of eddy current loss in the permanent magnet coupling.

PubMed

Zhu, Zina; Meng, Zhuo

2016-07-01

This paper first presents a 3D analytical model for analyzing the radial air-gap magnetic field between the inner and outer magnetic rotors of the permanent magnet couplings by using the Amperian current model. Based on the air-gap field analysis, the eddy current loss in the isolation cover is predicted according to the Maxwell's equations. A 3D finite element analysis model is constructed to analyze the magnetic field spatial distributions and vector eddy currents, and then the simulation results obtained are analyzed and compared with the analytical method. Finally, the current losses of two types of practical magnet couplings are measured in the experiment to compare with the theoretical results. It is concluded that the 3D analytical method of eddy current loss in the magnet coupling is viable and could be used for the eddy current loss prediction of magnet couplings.

Geological modelling of mineral deposits for prediction in mining

NASA Astrophysics Data System (ADS)

Sides, E. J.

Accurate prediction of the shape, location, size and properties of the solid rock materials to be extracted during mining is essential for reliable technical and financial planning. This is achieved through geological modelling of the three-dimensional (3D) shape and properties of the materials present in mineral deposits, and the presentation of results in a form which is accessible to mine planning engineers. In recent years the application of interactive graphics software, offering 3D database handling, modelling and visualisation, has greatly enhanced the options available for predicting the subsurface limits and characteristics of mineral deposits. A review of conventional 3D geological interpretation methods, and the model struc- tures and modelling methods used in reserve estimation and mine planning software packages, illustrates the importance of such approaches in the modern mining industry. Despite the widespread introduction and acceptance of computer hardware and software in mining applications, in recent years, there has been little fundamental change in the way in which geology is used in orebody modelling for predictive purposes. Selected areas of current research, aimed at tackling issues such as the use of orientation data, quantification of morphological differences, incorporation of geological age relationships, multi-resolution models and the application of virtual reality hardware and software, are discussed.

Comparative Protein Structure Modeling Using MODELLER.

PubMed

Webb, Benjamin; Sali, Andrej

2014-09-08

Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. Copyright © 2014 John Wiley & Sons, Inc.

Application of a coupled smoothed particle hydrodynamics (SPH) and coarse-grained (CG) numerical modelling approach to study three-dimensional (3-D) deformations of single cells of different food-plant materials during drying.

PubMed

Rathnayaka, C M; Karunasena, H C P; Senadeera, W; Gu, Y T

2018-03-14

Numerical modelling has gained popularity in many science and engineering streams due to the economic feasibility and advanced analytical features compared to conventional experimental and theoretical models. Food drying is one of the areas where numerical modelling is increasingly applied to improve drying process performance and product quality. This investigation applies a three dimensional (3-D) Smoothed Particle Hydrodynamics (SPH) and Coarse-Grained (CG) numerical approach to predict the morphological changes of different categories of food-plant cells such as apple, grape, potato and carrot during drying. To validate the model predictions, experimental findings from in-house experimental procedures (for apple) and sources of literature (for grape, potato and carrot) have been utilised. The subsequent comaprison indicate that the model predictions demonstrate a reasonable agreement with the experimental findings, both qualitatively and quantitatively. In this numerical model, a higher computational accuracy has been maintained by limiting the consistency error below 1% for all four cell types. The proposed meshfree-based approach is well-equipped to predict the morphological changes of plant cellular structure over a wide range of moisture contents (10% to 100% dry basis). Compared to the previous 2-D meshfree-based models developed for plant cell drying, the proposed model can draw more useful insights on the morphological behaviour due to the 3-D nature of the model. In addition, the proposed computational modelling approach has a high potential to be used as a comprehensive tool in many other tissue morphology related investigations.

Multifidelity-CMA: a multifidelity approach for efficient personalisation of 3D cardiac electromechanical models.

PubMed

Molléro, Roch; Pennec, Xavier; Delingette, Hervé; Garny, Alan; Ayache, Nicholas; Sermesant, Maxime

2018-02-01

Personalised computational models of the heart are of increasing interest for clinical applications due to their discriminative and predictive abilities. However, the simulation of a single heartbeat with a 3D cardiac electromechanical model can be long and computationally expensive, which makes some practical applications, such as the estimation of model parameters from clinical data (the personalisation), very slow. Here we introduce an original multifidelity approach between a 3D cardiac model and a simplified "0D" version of this model, which enables to get reliable (and extremely fast) approximations of the global behaviour of the 3D model using 0D simulations. We then use this multifidelity approximation to speed-up an efficient parameter estimation algorithm, leading to a fast and computationally efficient personalisation method of the 3D model. In particular, we show results on a cohort of 121 different heart geometries and measurements. Finally, an exploitable code of the 0D model with scripts to perform parameter estimation will be released to the community.

Comparison of updates to the Molly cow model to predict methane production from dairy cows fed pasture.

PubMed

Gregorini, P; Beukes, P C; Hanigan, M D; Waghorn, G; Muetzel, S; McNamara, J P

2013-08-01

Molly is a deterministic, mechanistic, dynamic model representing the digestion, metabolism, and production of a dairy cow. This study compared the predictions of enteric methane production from the original version of Molly (MollyOrigin) and 2 new versions of Molly. Updated versions included new ruminal fiber digestive parameters and animal hormonal parameters (Molly84) and a revised version of digestive and ruminal parameters (Molly85), using 3 different ruminal volatile fatty acid (VFA) stoichiometry constructs to describe the VFA pattern and methane (CH4) production (g of CH4/d). The VFA stoichiometry constructs were the original forage and mixed-diet VFA constructs and a new VFA stoichiometry based on a more recent and larger set of data that includes lactate and valerate production, amylolytic and cellulolytic bacteria, as well as protozoal pools. The models' outputs were challenged using data from 16 dairy cattle 26 mo old [standard error of the mean (SEM)=1.7], 82 (SEM=8.7) d in milk, producing 17 (SEM=0.2) kg of milk/d, and fed fresh-cut ryegrass [dry matter intake=12.3 (SEM=0.3) kg of DM/d] in respiration chambers. Mean observed CH4 production was 266±5.6 SEM (g/d). Mean predicted values for CH4 production were 287 and 258 g/d for MollyOrigin without and with the new VFA construct. Model Molly84 predicted 295 and 288 g of CH4/d with and without the new VFA settings. Model Molly85 predicted the same CH4 production (276 g/d) with or without the new VFA construct. The incorporation of the new VFA construct did not consistently reduce the low prediction error across the versions of Molly evaluated in the present study. The improvements in the Molly versions from MollyOrigin to Molly84 to Molly85 resulted in a decrease in mean square prediction error from 8.6 to 8.3 to 4.3% using the forage diet setting. The majority of the mean square prediction error was apportioned to random bias (e.g., 43, 65, and 70% in MollyOrigin, Molly84, and Molly85, respectively, on the forage setting, showing that with the updated versions a greater proportion of error was random). The slope bias was less than 2% in all cases. We concluded that, of the versions of Molly used for pastoral systems, Molly85 has the capability to predict CH4 production from grass-fed dairy cows with the highest accuracy. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Path-Dependent Travel Time Prediction Variance and Covariance for a Global Tomographic P- and S-Velocity Model

NASA Astrophysics Data System (ADS)

Hipp, J. R.; Ballard, S.; Begnaud, M. L.; Encarnacao, A. V.; Young, C. J.; Phillips, W. S.

2015-12-01

Recently our combined SNL-LANL research team has succeeded in developing a global, seamless 3D tomographic P- and S-velocity model (SALSA3D) that provides superior first P and first S travel time predictions at both regional and teleseismic distances. However, given the variable data quality and uneven data sampling associated with this type of model, it is essential that there be a means to calculate high-quality estimates of the path-dependent variance and covariance associated with the predicted travel times of ray paths through the model. In this paper, we describe a methodology for accomplishing this by exploiting the full model covariance matrix and show examples of path-dependent travel time prediction uncertainty computed from our latest tomographic model. Typical global 3D SALSA3D models have on the order of 1/2 million nodes, so the challenge in calculating the covariance matrix is formidable: 0.9 TB storage for 1/2 of a symmetric matrix, necessitating an Out-Of-Core (OOC) blocked matrix solution technique. With our approach the tomography matrix (G which includes a prior model covariance constraint) is multiplied by its transpose (GTG) and written in a blocked sub-matrix fashion. We employ a distributed parallel solution paradigm that solves for (GTG)-1 by assigning blocks to individual processing nodes for matrix decomposition update and scaling operations. We first find the Cholesky decomposition of GTG which is subsequently inverted. Next, we employ OOC matrix multiplication methods to calculate the model covariance matrix from (GTG)-1 and an assumed data covariance matrix. Given the model covariance matrix, we solve for the travel-time covariance associated with arbitrary ray-paths by summing the model covariance along both ray paths. Setting the paths equal and taking the square root yields the travel prediction uncertainty for the single path.

Determination of rice syrup adulterant concentration in honey using three-dimensional fluorescence spectra and multivariate calibrations

NASA Astrophysics Data System (ADS)

Chen, Quansheng; Qi, Shuai; Li, Huanhuan; Han, Xiaoyan; Ouyang, Qin; Zhao, Jiewen

2014-10-01

To rapidly and efficiently detect the presence of adulterants in honey, three-dimensional fluorescence spectroscopy (3DFS) technique was employed with the help of multivariate calibration. The data of 3D fluorescence spectra were compressed using characteristic extraction and the principal component analysis (PCA). Then, partial least squares (PLS) and back propagation neural network (BP-ANN) algorithms were used for modeling. The model was optimized by cross validation, and its performance was evaluated according to root mean square error of prediction (RMSEP) and correlation coefficient (R) in prediction set. The results showed that BP-ANN model was superior to PLS models, and the optimum prediction results of the mixed group (sunflower ± longan ± buckwheat ± rape) model were achieved as follow: RMSEP = 0.0235 and R = 0.9787 in the prediction set. The study demonstrated that the 3D fluorescence spectroscopy technique combined with multivariate calibration has high potential in rapid, nondestructive, and accurate quantitative analysis of honey adulteration.

The Effects of 3D Computer Modelling on Conceptual Change about Seasons and Phases of the Moon

ERIC Educational Resources Information Center

Kucukozer, Huseyin

2008-01-01

In this study, prospective science teachers' misconceptions about the seasons and the phases of the Moon were determined, and then the effects of 3D computer modelling on their conceptual changes were investigated. The topics were covered in two classes with a total of 76 students using a predict-observe-explain strategy supported by 3D computer…

Computational identification of a phospholipidosis toxicophore using (13)C and (15)N NMR-distance based fingerprints.

PubMed

Slavov, Svetoslav H; Wilkes, Jon G; Buzatu, Dan A; Kruhlak, Naomi L; Willard, James M; Hanig, Joseph P; Beger, Richard D

2014-12-01

Modified 3D-SDAR fingerprints combining (13)C and (15)N NMR chemical shifts augmented with inter-atomic distances were used to model the potential of chemicals to induce phospholipidosis (PLD). A curated dataset of 328 compounds (some of which were cationic amphiphilic drugs) was used to generate 3D-QSDAR models based on tessellations of the 3D-SDAR space with grids of different density. Composite PLS models averaging the aggregated predictions from 100 fully randomized individual models were generated. On each of the 100 runs, the activities of an external blind test set comprised of 294 proprietary chemicals were predicted and averaged to provide composite estimates of their PLD-inducing potentials (PLD+ if PLD is observed, otherwise PLD-). The best performing 3D-QSDAR model utilized a grid with a density of 8ppm×8ppm in the C-C region, 8ppm×20ppm in the C-N region and 20ppm×20ppm in the N-N region. The classification predictive performance parameters of this model evaluated on the basis of the external test set were as follows: accuracy=0.70, sensitivity=0.73 and specificity=0.66. A projection of the most frequently occurring bins on the standard coordinate space suggested a toxicophore composed of an aromatic ring with a centroid 3.5-7.5Å distant from an amino-group. The presence of a second aromatic ring separated by a 4-5Å spacer from the first ring and at a distance of between 5.5Å and 7Å from the amino-group was also associated with a PLD+ effect. These models provide comparable predictive performance to previously reported models for PLD with the added benefit of being based entirely on non-confidential, publicly available training data and with good predictive performance when tested in a rigorous, external validation exercise. Published by Elsevier Ltd.

Categorical QSAR models for skin sensitization based on local lymph node assay measures and both ground and excited state 4D-fingerprint descriptors

NASA Astrophysics Data System (ADS)

Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Santos-Filho, Osvaldo A.; Esposito, Emilio X.; Hopfinger, Anton J.; Tseng, Yufeng J.

2008-06-01

In previous studies we have developed categorical QSAR models for predicting skin-sensitization potency based on 4D-fingerprint (4D-FP) descriptors and in vivo murine local lymph node assay (LLNA) measures. Only 4D-FP derived from the ground state (GMAX) structures of the molecules were used to build the QSAR models. In this study we have generated 4D-FP descriptors from the first excited state (EMAX) structures of the molecules. The GMAX, EMAX and the combined ground and excited state 4D-FP descriptors (GEMAX) were employed in building categorical QSAR models. Logistic regression (LR) and partial least square coupled logistic regression (PLS-CLR), found to be effective model building for the LLNA skin-sensitization measures in our previous studies, were used again in this study. This also permitted comparison of the prior ground state models to those involving first excited state 4D-FP descriptors. Three types of categorical QSAR models were constructed for each of the GMAX, EMAX and GEMAX datasets: a binary model (2-state), an ordinal model (3-state) and a binary-binary model (two-2-state). No significant differences exist among the LR 2-state model constructed for each of the three datasets. However, the PLS-CLR 3-state and 2-state models based on the EMAX and GEMAX datasets have higher predictivity than those constructed using only the GMAX dataset. These EMAX and GMAX categorical models are also more significant and predictive than corresponding models built in our previous QSAR studies of LLNA skin-sensitization measures.

Vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitors: development and validation of predictive 3-D QSAR models through extensive ligand- and structure-based approaches

NASA Astrophysics Data System (ADS)

Ragno, Rino; Ballante, Flavio; Pirolli, Adele; Wickersham, Richard B.; Patsilinakos, Alexandros; Hesse, Stéphanie; Perspicace, Enrico; Kirsch, Gilbert

2015-08-01

Vascular endothelial growth factor receptor-2, (VEGFR-2), is a key element in angiogenesis, the process by which new blood vessels are formed, and is thus an important pharmaceutical target. Here, 3-D quantitative structure-activity relationship (3-D QSAR) were used to build a quantitative screening and pharmacophore model of the VEGFR-2 receptors for design of inhibitors with improved activities. Most of available experimental data information has been used as training set to derive optimized and fully cross-validated eight mono-probe and a multi-probe quantitative models. Notable is the use of 262 molecules, aligned following both structure-based and ligand-based protocols, as external test set confirming the 3-D QSAR models' predictive capability and their usefulness in design new VEGFR-2 inhibitors. From a survey on literature, this is the first generation of a wide-ranging computational medicinal chemistry application on VEGFR2 inhibitors.

Improved performance in CAPRI round 37 using LZerD docking and template-based modeling with combined scoring functions.

PubMed

Peterson, Lenna X; Shin, Woong-Hee; Kim, Hyungrae; Kihara, Daisuke

2018-03-01

We report our group's performance for protein-protein complex structure prediction and scoring in Round 37 of the Critical Assessment of PRediction of Interactions (CAPRI), an objective assessment of protein-protein complex modeling. We demonstrated noticeable improvement in both prediction and scoring compared to previous rounds of CAPRI, with our human predictor group near the top of the rankings and our server scorer group at the top. This is the first time in CAPRI that a server has been the top scorer group. To predict protein-protein complex structures, we used both multi-chain template-based modeling (TBM) and our protein-protein docking program, LZerD. LZerD represents protein surfaces using 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. Because 3DZD are a soft representation of the protein surface, LZerD is tolerant to small conformational changes, making it well suited to docking unbound and TBM structures. The key to our improved performance in CAPRI Round 37 was to combine multi-chain TBM and docking. As opposed to our previous strategy of performing docking for all target complexes, we used TBM when multi-chain templates were available and docking otherwise. We also describe the combination of multiple scoring functions used by our server scorer group, which achieved the top rank for the scorer phase. © 2017 Wiley Periodicals, Inc.

Engineering 3D Models of Tumors and Bone to Understand Tumor-Induced Bone Disease and Improve Treatments

PubMed Central

Kwakwa, Kristin A.; Vanderburgh, Joseph P.; Guelcher, Scott A.

2018-01-01

Purpose of Review Bone is a structurally unique microenvironment that presents many challenges for the development of 3D models for studying bone physiology and diseases, including cancer. As researchers continue to investigate the interactions within the bone microenvironment, the development of 3D models of bone has become critical. Recent Findings 3D models have been developed that replicate some properties of bone, but have not fully reproduced the complex structural and cellular composition of the bone microenvironment. This review will discuss 3D models including polyurethane, silk, and collagen scaffolds that have been developed to study tumor-induced bone disease. In addition, we discuss 3D printing techniques used to better replicate the structure of bone. Summary 3D models that better replicate the bone microenvironment will help researchers better understand the dynamic interactions between tumors and the bone microenvironment, ultimately leading to better models for testing therapeutics and predicting patient outcomes. PMID:28646444

Multiphase flow predictions from carbonate pore space images using extracted network models

NASA Astrophysics Data System (ADS)

Al-Kharusi, Anwar S.; Blunt, Martin J.

2008-06-01

A methodology to extract networks from pore space images is used to make predictions of multiphase transport properties for subsurface carbonate samples. The extraction of the network model is based on the computation of the location and sizes of pores and throats to create a topological representation of the void space of three-dimensional (3-D) rock images, using the concept of maximal balls. In this work, we follow a multistaged workflow. We start with a 2-D thin-section image; convert it statistically into a 3-D representation of the pore space; extract a network model from this image; and finally, simulate primary drainage, waterflooding, and secondary drainage flow processes using a pore-scale simulator. We test this workflow for a reservoir carbonate rock. The network-predicted absolute permeability is similar to the core plug measured value and the value computed on the 3-D void space image using the lattice Boltzmann method. The predicted capillary pressure during primary drainage agrees well with a mercury-air experiment on a core sample, indicating that we have an adequate representation of the rock's pore structure. We adjust the contact angles in the network to match the measured waterflood and secondary drainage capillary pressures. We infer a significant degree of contact angle hysteresis. We then predict relative permeabilities for primary drainage, waterflooding, and secondary drainage that agree well with laboratory measured values. This approach can be used to predict multiphase transport properties when wettability and pore structure vary in a reservoir, where experimental data is scant or missing. There are shortfalls to this approach, however. We compare results from three networks, one of which was derived from a section of the rock containing vugs. Our method fails to predict properties reliably when an unrepresentative image is processed to construct the 3-D network model. This occurs when the image volume is not sufficient to represent the geological variations observed in a core plug sample.

CAD-Based Modeling of Advanced Rotary Wing Structures for Integrated 3-D Aeromechanics Analysis

NASA Astrophysics Data System (ADS)

Staruk, William

This dissertation describes the first comprehensive use of integrated 3-D aeromechanics modeling, defined as the coupling of 3-D solid finite element method (FEM) structural dynamics with 3-D computational fluid dynamics (CFD), for the analysis of a real helicopter rotor. The development of this new methodology (a departure from how rotor aeroelastic analysis has been performed for 40 years), its execution on a real rotor, and the fundamental understanding of aeromechanics gained from it, are the key contributions of this dissertation. This work also presents the first CFD/CSD analysis of a tiltrotor in edgewise flight, revealing many of its unique loading mechanisms. The use of 3-D FEM, integrated with a trim solver and aerodynamics modeling, has the potential to enhance the design of advanced rotors by overcoming fundamental limitations of current generation beam-based analysis tools and offering integrated internal dynamic stress and strain predictions for design. Two primary goals drove this research effort: 1) developing a methodology to create 3-D CAD-based brick finite element models of rotors including multibody joints, controls, and aerodynamic interfaces, and 2) refining X3D, the US Army's next generation rotor structural dynamics solver featuring 3-D FEM within a multibody formulation with integrated aerodynamics, to model a tiltrotor in the edgewise conversion flight regime, which drives critical proprotor structural loads. Prior tiltrotor analysis has primarily focused on hover aerodynamics with rigid blades or forward flight whirl-flutter stability with simplified aerodynamics. The first goal was met with the development of a detailed methodology for generating multibody 3-D structural models, starting from CAD geometry, continuing to higher-order hexahedral finite element meshing, to final assembly of the multibody model by creating joints, assigning material properties, and defining the aerodynamic interface. Several levels of verification and validation were carried out systematically, covering formulation, model accuracy, and accuracy of the physics of the problem and the many complex coupled aeromechanical phenomena that characterize the behavior of a tiltrotor in the conversion corridor. Compatibility of the new structural analysis models with X3D is demonstrated using analytical test cases, including 90° twisted beams and thick composite plates, and a notional bearingless rotor. Prediction of deformations and stresses in composite beams and plates is validated and verified against experimental measurements, theory, and state-of-the-art beam models. The second goal was met through integrated analysis of the Tilt Rotor Aeroacoustic Model (TRAM) proprotor using X3D coupled to Helios--the US Army's next generation CFD framework featuring a high fidelity Reynolds-average Navier-Stokes (RANS) structured/unstructured overset solver--as well as low order aerodynamic models. Although development of CFD was not part of this work, coupling X3D with Helios was, including establishing consistent interface definitions for blade deformations (for CFD mesh motion), aerodynamic interfaces (for loads transfer), and rotor control angles (for trim). It is expected that this method and solver will henceforth be an integral part of the Helios framework, providing an equal fidelity of representation for fluids and structures in the development of future advanced rotor systems. Structural dynamics analysis of the TRAM model show accurate prediction of the lower natural frequencies, demonstrating the ability to model advanced rotors from first principles using 3-D structural dynamics, and a study of how joint properties affect these frequencies reveals how X3D can be used as a detailed design tool. The CFD/CSD analysis reveals accurate prediction of rotor performance and airloads in edgewise flight when compared to wind tunnel test data. Structural blade loads trends are well predicted at low thrust, but a 3/rev component of flap and lag bending moment appearing in test data at high thrust remains a mystery. Efficiently simulating a gimbaled rotor is not trivial; a time-domain method with only a single blade model is proposed and tested. The internal stress in the blade, particularly at its root where the gimbal action has major influence, is carefully examined, revealing complex localized loading patterns.

Computer-Assisted Decision Support for Student Admissions Based on Their Predicted Academic Performance.

PubMed

Muratov, Eugene; Lewis, Margaret; Fourches, Denis; Tropsha, Alexander; Cox, Wendy C

2017-04-01

Objective. To develop predictive computational models forecasting the academic performance of students in the didactic-rich portion of a doctor of pharmacy (PharmD) curriculum as admission-assisting tools. Methods. All PharmD candidates over three admission cycles were divided into two groups: those who completed the PharmD program with a GPA ≥ 3; and the remaining candidates. Random Forest machine learning technique was used to develop a binary classification model based on 11 pre-admission parameters. Results. Robust and externally predictive models were developed that had particularly high overall accuracy of 77% for candidates with high or low academic performance. These multivariate models were highly accurate in predicting these groups to those obtained using undergraduate GPA and composite PCAT scores only. Conclusion. The models developed in this study can be used to improve the admission process as preliminary filters and thus quickly identify candidates who are likely to be successful in the PharmD curriculum.

3-D numerical simulations of earthquake ground motion in sedimentary basins: testing accuracy through stringent models

NASA Astrophysics Data System (ADS)

Chaljub, Emmanuel; Maufroy, Emeline; Moczo, Peter; Kristek, Jozef; Hollender, Fabrice; Bard, Pierre-Yves; Priolo, Enrico; Klin, Peter; de Martin, Florent; Zhang, Zhenguo; Zhang, Wei; Chen, Xiaofei

2015-04-01

Differences between 3-D numerical predictions of earthquake ground motion in the Mygdonian basin near Thessaloniki, Greece, led us to define four canonical stringent models derived from the complex realistic 3-D model of the Mygdonian basin. Sediments atop an elastic bedrock are modelled in the 1D-sharp and 1D-smooth models using three homogeneous layers and smooth velocity distribution, respectively. The 2D-sharp and 2D-smooth models are extensions of the 1-D models to an asymmetric sedimentary valley. In all cases, 3-D wavefields include strongly dispersive surface waves in the sediments. We compared simulations by the Fourier pseudo-spectral method (FPSM), the Legendre spectral-element method (SEM) and two formulations of the finite-difference method (FDM-S and FDM-C) up to 4 Hz. The accuracy of individual solutions and level of agreement between solutions vary with type of seismic waves and depend on the smoothness of the velocity model. The level of accuracy is high for the body waves in all solutions. However, it strongly depends on the discrete representation of the material interfaces (at which material parameters change discontinuously) for the surface waves in the sharp models. An improper discrete representation of the interfaces can cause inaccurate numerical modelling of surface waves. For all the numerical methods considered, except SEM with mesh of elements following the interfaces, a proper implementation of interfaces requires definition of an effective medium consistent with the interface boundary conditions. An orthorhombic effective medium is shown to significantly improve accuracy and preserve the computational efficiency of modelling. The conclusions drawn from the analysis of the results of the canonical cases greatly help to explain differences between numerical predictions of ground motion in realistic models of the Mygdonian basin. We recommend that any numerical method and code that is intended for numerical prediction of earthquake ground motion should be verified through stringent models that would make it possible to test the most important aspects of accuracy.

Predictive Model for Particle Residence Time Distributions in Riser Reactors. Part 1: Model Development and Validation

DOE PAGES

Foust, Thomas D.; Ziegler, Jack L.; Pannala, Sreekanth; ...

2017-02-28

Here in this computational study, we model the mixing of biomass pyrolysis vapor with solid catalyst in circulating riser reactors with a focus on the determination of solid catalyst residence time distributions (RTDs). A comprehensive set of 2D and 3D simulations were conducted for a pilot-scale riser using the Eulerian-Eulerian two-fluid modeling framework with and without sub-grid-scale models for the gas-solids interaction. A validation test case was also simulated and compared to experiments, showing agreement in the pressure gradient and RTD mean and spread. For simulation cases, it was found that for accurate RTD prediction, the Johnson and Jackson partialmore » slip solids boundary condition was required for all models and a sub-grid model is useful so that ultra high resolutions grids that are very computationally intensive are not required. Finally, we discovered a 2/3 scaling relation for the RTD mean and spread when comparing resolved 2D simulations to validated unresolved 3D sub-grid-scale model simulations.« less

Template CoMFA Generates Single 3D-QSAR Models that, for Twelve of Twelve Biological Targets, Predict All ChEMBL-Tabulated Affinities

PubMed Central

Cramer, Richard D.

2015-01-01

The possible applicability of the new template CoMFA methodology to the prediction of unknown biological affinities was explored. For twelve selected targets, all ChEMBL binding affinities were used as training and/or prediction sets, making these 3D-QSAR models the most structurally diverse and among the largest ever. For six of the targets, X-ray crystallographic structures provided the aligned templates required as input (BACE, cdk1, chk2, carbonic anhydrase-II, factor Xa, PTP1B). For all targets including the other six (hERG, cyp3A4 binding, endocrine receptor, COX2, D2, and GABAa), six modeling protocols applied to only three familiar ligands provided six alternate sets of aligned templates. The statistical qualities of the six or seven models thus resulting for each individual target were remarkably similar. Also, perhaps unexpectedly, the standard deviations of the errors of cross-validation predictions accompanying model derivations were indistinguishable from the standard deviations of the errors of truly prospective predictions. These standard deviations of prediction ranged from 0.70 to 1.14 log units and averaged 0.89 (8x in concentration units) over the twelve targets, representing an average reduction of almost 50% in uncertainty, compared to the null hypothesis of “predicting” an unknown affinity to be the average of known affinities. These errors of prediction are similar to those from Tanimoto coefficients of fragment occurrence frequencies, the predominant approach to side effect prediction, which template CoMFA can augment by identifying additional active structural classes, by improving Tanimoto-only predictions, by yielding quantitative predictions of potency, and by providing interpretable guidance for avoiding or enhancing any specific target response. PMID:26065424

Storm Surge Modeling of Typhoon Haiyan at the Naval Oceanographic Office Using Delft3D

NASA Astrophysics Data System (ADS)

Gilligan, M. J.; Lovering, J. L.

2016-02-01

The Naval Oceanographic Office provides estimates of the rise in sea level along the coast due to storm surge associated with tropical cyclones, typhoons, and hurricanes. Storm surge modeling and prediction helps the US Navy by providing a threat assessment tool to help protect Navy assets and provide support for humanitarian assistance/disaster relief efforts. Recent advancements in our modeling capabilities include the use of the Delft3D modeling suite as part of a Naval Research Laboratory (NRL) developed Coastal Surge Inundation Prediction System (CSIPS). Model simulations were performed on Typhoon Haiyan, which made landfall in the Philippines in November 2013. Comparisons of model simulations using forecast and hindcast track data highlight the importance of accurate storm track information for storm surge predictions. Model runs using the forecast track prediction and hindcast track information give maximum storm surge elevations of 4 meters and 6.1 meters, respectively. Model results for the hindcast simulation were compared with data published by the JSCE-PICE Joint survey for locations in San Pedro Bay (SPB) and on the Eastern Samar Peninsula (ESP). In SPB, where wind-induced set-up predominates, the model run using the forecast track predicted surge within 2 meters in 38% of survey locations and within 3 meters in 59% of the locations. When the hindcast track was used, the model predicted within 2 meters in 77% of the locations and within 3 meters in 95% of the locations. The model was unable to predict the high surge reported along the ESP produced by infragravity wave-induced set-up, which is not simulated in the model. Additional modeling capabilities incorporating infragravity waves are required to predict storm surge accurately along open coasts with steep bathymetric slopes, such as those seen in island arcs.

Extreme possible variations of the deuterium abundance within the Galaxy

NASA Astrophysics Data System (ADS)

Delbourgo-Salvador, P.; Audouze, J.; Vidal-Madjar, A.

1987-03-01

In order to reconcile the present baryonic densities deduced respectively from the primordial abundances of D and 4He, some recent chemical evolution models imply that D could have been destroyed more thoroughly during the Galaxy evolution than what was previously predicted. Under the conditions outlined by these models, the present abundance of D may vary by factors as large as 50 in different parts of the Galaxy. If such variations are not observed, this implies that the ratio X(D)prim/X(D)present is not large (2 - 3): the simplest Big Bang models may then be unable to reconcile the baryonic densities predicted by D and 4He respectively.

Voxel inversion of airborne electromagnetic data for improved groundwater model construction and prediction accuracy

NASA Astrophysics Data System (ADS)

Kruse Christensen, Nikolaj; Ferre, Ty Paul A.; Fiandaca, Gianluca; Christensen, Steen

2017-03-01

We present a workflow for efficient construction and calibration of large-scale groundwater models that includes the integration of airborne electromagnetic (AEM) data and hydrological data. In the first step, the AEM data are inverted to form a 3-D geophysical model. In the second step, the 3-D geophysical model is translated, using a spatially dependent petrophysical relationship, to form a 3-D hydraulic conductivity distribution. The geophysical models and the hydrological data are used to estimate spatially distributed petrophysical shape factors. The shape factors primarily work as translators between resistivity and hydraulic conductivity, but they can also compensate for structural defects in the geophysical model. The method is demonstrated for a synthetic case study with sharp transitions among various types of deposits. Besides demonstrating the methodology, we demonstrate the importance of using geophysical regularization constraints that conform well to the depositional environment. This is done by inverting the AEM data using either smoothness (smooth) constraints or minimum gradient support (sharp) constraints, where the use of sharp constraints conforms best to the environment. The dependency on AEM data quality is also tested by inverting the geophysical model using data corrupted with four different levels of background noise. Subsequently, the geophysical models are used to construct competing groundwater models for which the shape factors are calibrated. The performance of each groundwater model is tested with respect to four types of prediction that are beyond the calibration base: a pumping well's recharge area and groundwater age, respectively, are predicted by applying the same stress as for the hydrologic model calibration; and head and stream discharge are predicted for a different stress situation. As expected, in this case the predictive capability of a groundwater model is better when it is based on a sharp geophysical model instead of a smoothness constraint. This is true for predictions of recharge area, head change, and stream discharge, while we find no improvement for prediction of groundwater age. Furthermore, we show that the model prediction accuracy improves with AEM data quality for predictions of recharge area, head change, and stream discharge, while there appears to be no accuracy improvement for the prediction of groundwater age.

Cube search, revisited.

PubMed

Zhang, Xuetao; Huang, Jie; Yigit-Elliott, Serap; Rosenholtz, Ruth

2015-03-16

Observers can quickly search among shaded cubes for one lit from a unique direction. However, replace the cubes with similar 2-D patterns that do not appear to have a 3-D shape, and search difficulty increases. These results have challenged models of visual search and attention. We demonstrate that cube search displays differ from those with "equivalent" 2-D search items in terms of the informativeness of fairly low-level image statistics. This informativeness predicts peripheral discriminability of target-present from target-absent patches, which in turn predicts visual search performance, across a wide range of conditions. Comparing model performance on a number of classic search tasks, cube search does not appear unexpectedly easy. Easy cube search, per se, does not provide evidence for preattentive computation of 3-D scene properties. However, search asymmetries derived from rotating and/or flipping the cube search displays cannot be explained by the information in our current set of image statistics. This may merely suggest a need to modify the model's set of 2-D image statistics. Alternatively, it may be difficult cube search that provides evidence for preattentive computation of 3-D scene properties. By attributing 2-D luminance variations to a shaded 3-D shape, 3-D scene understanding may slow search for 2-D features of the target. © 2015 ARVO.

Cube search, revisited

PubMed Central

Zhang, Xuetao; Huang, Jie; Yigit-Elliott, Serap; Rosenholtz, Ruth

2015-01-01

Observers can quickly search among shaded cubes for one lit from a unique direction. However, replace the cubes with similar 2-D patterns that do not appear to have a 3-D shape, and search difficulty increases. These results have challenged models of visual search and attention. We demonstrate that cube search displays differ from those with “equivalent” 2-D search items in terms of the informativeness of fairly low-level image statistics. This informativeness predicts peripheral discriminability of target-present from target-absent patches, which in turn predicts visual search performance, across a wide range of conditions. Comparing model performance on a number of classic search tasks, cube search does not appear unexpectedly easy. Easy cube search, per se, does not provide evidence for preattentive computation of 3-D scene properties. However, search asymmetries derived from rotating and/or flipping the cube search displays cannot be explained by the information in our current set of image statistics. This may merely suggest a need to modify the model's set of 2-D image statistics. Alternatively, it may be difficult cube search that provides evidence for preattentive computation of 3-D scene properties. By attributing 2-D luminance variations to a shaded 3-D shape, 3-D scene understanding may slow search for 2-D features of the target. PMID:25780063

The Physics of Boundary-Layer Aero-Optic Effects

DTIC Science & Technology

2012-09-01

various models to predict aero-optical effects for both subsonic and supersonic Mach numbers, laser beam sizes and non- adiabatic walls. The developed...models to predict aero-optical effects for both subsonic and supersonic Mach numbers, laser beam sizes and non- adiabatic walls. The developed models were... Supersonic Facilities .................................................................................................... 8 3.3 2-D Wavefront Data

Product development: using a 3D computer model to optimize the stability of the Rocket powered wheelchair.

PubMed

Pinkney, S; Fernie, G

2001-01-01

A three-dimensional (3D) lumped-parameter model of a powered wheelchair was created to aid the development of the Rocket prototype wheelchair and to help explore the effect of innovative design features on its stability. The model was developed using simulation software, specifically Working Model 3D. The accuracy of the model was determined by comparing both its static stability angles and dynamic behavior as it passed down a 4.8-cm (1.9") road curb at a heading of 45 degrees with the performance of the actual wheelchair. The model's predictions of the static stability angles in the forward, rearward, and lateral directions were within 9.3, 7.1, and 3.8% of the measured values, respectively. The average absolute error in the predicted position of the wheelchair as it moved down the curb was 2.2 cm/m (0.9" per 3'3") traveled. The accuracy was limited by the inability to model soft bodies, the inherent difficulties in modeling a statically indeterminate system, and the computing time. Nevertheless, it was found to be useful in investigating the effect of eight design alterations on the lateral stability of the wheelchair. Stability was quantified by determining the static lateral stability angles and the maximum height of a road curb over which the wheelchair could successfully drive on a diagonal heading. The model predicted that the stability was more dependent on the configuration of the suspension system than on the dimensions and weight distribution of the wheelchair. Furthermore, for the situations and design alterations studied, predicted improvements in static stability were not correlated with improvements in dynamic stability.

Learning the spherical harmonic features for 3-D face recognition.

PubMed

Liu, Peijiang; Wang, Yunhong; Huang, Di; Zhang, Zhaoxiang; Chen, Liming

2013-03-01

In this paper, a competitive method for 3-D face recognition (FR) using spherical harmonic features (SHF) is proposed. With this solution, 3-D face models are characterized by the energies contained in spherical harmonics with different frequencies, thereby enabling the capture of both gross shape and fine surface details of a 3-D facial surface. This is in clear contrast to most 3-D FR techniques which are either holistic or feature based, using local features extracted from distinctive points. First, 3-D face models are represented in a canonical representation, namely, spherical depth map, by which SHF can be calculated. Then, considering the predictive contribution of each SHF feature, especially in the presence of facial expression and occlusion, feature selection methods are used to improve the predictive performance and provide faster and more cost-effective predictors. Experiments have been carried out on three public 3-D face datasets, SHREC2007, FRGC v2.0, and Bosphorus, with increasing difficulties in terms of facial expression, pose, and occlusion, and which demonstrate the effectiveness of the proposed method.

Comparing a quasi-3D to a full 3D nearshore circulation model: SHORECIRC and ROMS

USGS Publications Warehouse

Haas, Kevin A.; Warner, John C.

2009-01-01

Predictions of nearshore and surf zone processes are important for determining coastal circulation, impacts of storms, navigation, and recreational safety. Numerical modeling of these systems facilitates advancements in our understanding of coastal changes and can provide predictive capabilities for resource managers. There exists many nearshore coastal circulation models, however they are mostly limited or typically only applied as depth integrated models. SHORECIRC is an established surf zone circulation model that is quasi-3D to allow the effect of the variability in the vertical structure of the currents while maintaining the computational advantage of a 2DH model. Here we compare SHORECIRC to ROMS, a fully 3D ocean circulation model which now includes a three dimensional formulation for the wave-driven flows. We compare the models with three different test applications for: (i) spectral waves approaching a plane beach with an oblique angle of incidence; (ii) monochromatic waves driving longshore currents in a laboratory basin; and (iii) monochromatic waves on a barred beach with rip channels in a laboratory basin. Results identify that the models are very similar for the depth integrated flows and qualitatively consistent for the vertically varying components. The differences are primarily the result of the vertically varying radiation stress utilized by ROMS and the utilization of long wave theory for the radiation stress formulation in vertical varying momentum balance by SHORECIRC. The quasi-3D model is faster, however the applicability of the fully 3D model allows it to extend over a broader range of processes, temporal, and spatial scales.

Comparing a quasi-3D to a full 3D nearshore circulation model: SHORECIRC and ROMS

USGS Publications Warehouse

Haas, K.A.; Warner, J.C.

2009-01-01

Predictions of nearshore and surf zone processes are important for determining coastal circulation, impacts of storms, navigation, and recreational safety. Numerical modeling of these systems facilitates advancements in our understanding of coastal changes and can provide predictive capabilities for resource managers. There exists many nearshore coastal circulation models, however they are mostly limited or typically only applied as depth integrated models. SHORECIRC is an established surf zone circulation model that is quasi-3D to allow the effect of the variability in the vertical structure of the currents while maintaining the computational advantage of a 2DH model. Here we compare SHORECIRC to ROMS, a fully 3D ocean circulation model which now includes a three dimensional formulation for the wave-driven flows. We compare the models with three different test applications for: (i) spectral waves approaching a plane beach with an oblique angle of incidence; (ii) monochromatic waves driving longshore currents in a laboratory basin; and (iii) monochromatic waves on a barred beach with rip channels in a laboratory basin. Results identify that the models are very similar for the depth integrated flows and qualitatively consistent for the vertically varying components. The differences are primarily the result of the vertically varying radiation stress utilized by ROMS and the utilization of long wave theory for the radiation stress formulation in vertical varying momentum balance by SHORECIRC. The quasi-3D model is faster, however the applicability of the fully 3D model allows it to extend over a broader range of processes, temporal, and spatial scales. ?? 2008 Elsevier Ltd.

In vitro-in vivo extrapolation of CYP2D6 inactivation by paroxetine: prediction of nonstationary pharmacokinetics and drug interaction magnitude.

PubMed

Venkatakrishnan, Karthik; Obach, R Scott

2005-06-01

Attempts at predicting drug-drug interactions perpetrated by paroxetine from in vitro data have utilized reversible enzyme inhibition models and have been unsuccessful to date, grossly underpredicting interaction magnitude. Recent data have provided evidence for mechanism-based inactivation of CYP2D6 by paroxetine. We have predicted the pharmacokinetic consequences of CYP2D6 inactivation by paroxetine from in vitro inactivation kinetics (kinact 0.17 min(-1), unbound KI 0.315 microM), in vivo inhibitor concentrations, and an estimated CYP2D6 degradation half-life of 51 h, using a mathematical model of mechanism-based inhibition. The model-predicted accumulation ratio of paroxetine was 5 times that expected from single-dose kinetics and in excellent agreement with the observed 5- to 6-fold greater accumulation. Magnitudes of interactions produced by paroxetine (20-30 mg/day) with desipramine, risperidone, perphenazine, atomoxetine, (S)-metoprolol, and (R)-metoprolol were predicted, considering the contribution of CYP2D6 to their oral clearance. Predicted fold-increases in victim drug AUC were 5-, 6-, 5-, 6-, 4-, and 6-fold, respectively, and are in reasonable agreement with observed values of 5-, 6-, >7-, 7-, 5-, and 8-fold, respectively. Failure to consider microsomal binding in vitro adversely affected predictive accuracy. Simulation of the sensitivities of these predictions to model inputs suggests a 2-fold underprediction of interaction magnitude when a CYP2D6 degradation half-life of 14 h (reported for rat CYP3A) is used. In summary, the scaling model for mechanism-based inactivation successfully predicted the pharmacokinetic consequences of CYP2D6 inactivation by paroxetine from in vitro data.

The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction.

PubMed

Roche, Daniel B; Buenavista, Maria T; Tetchner, Stuart J; McGuffin, Liam J

2011-07-01

The IntFOLD server is a novel independent server that integrates several cutting edge methods for the prediction of structure and function from sequence. Our guiding principles behind the server development were as follows: (i) to provide a simple unified resource that makes our prediction software accessible to all and (ii) to produce integrated output for predictions that can be easily interpreted. The output for predictions is presented as a simple table that summarizes all results graphically via plots and annotated 3D models. The raw machine readable data files for each set of predictions are also provided for developers, which comply with the Critical Assessment of Methods for Protein Structure Prediction (CASP) data standards. The server comprises an integrated suite of five novel methods: nFOLD4, for tertiary structure prediction; ModFOLD 3.0, for model quality assessment; DISOclust 2.0, for disorder prediction; DomFOLD 2.0 for domain prediction; and FunFOLD 1.0, for ligand binding site prediction. Predictions from the IntFOLD server were found to be competitive in several categories in the recent CASP9 experiment. The IntFOLD server is available at the following web site: http://www.reading.ac.uk/bioinf/IntFOLD/.

3D gain modeling of LMJ and NIF amplifiers

NASA Astrophysics Data System (ADS)

LeTouze, Geoffroy; Cabourdin, Olivier; Mengue, J. F.; Guenet, Mireille; Grebot, Eric; Seznec, Stephane E.; Jancaitis, Kenneth S.; Marshall, Christopher D.; Zapata, Luis E.; Erlandson, A. E.

1999-07-01

A 3D ray-trace model has been developed to predict the performance of flashlamp pumped laser amplifiers. The computer program, written in C++, includes a graphical display option using the Open Inventor library, as well as a parser and a loader allowing the user to easily model complex multi-segment amplifier systems. It runs both on a workstation cluster at LLNL, and on the T3E Cray at CEA. We will discuss how we have reduce the required computation time without changing precision by optimizing the parameters which set the discretization level of the calculation. As an example, the sample of calculation points is chosen to fit the pumping profile through the thickness of amplifier slabs. We will show the difference in pump rates with our latest model as opposed to those produced by our earlier 2.5D code AmpModel. We will also present the results of calculations which model surfaces and other 3D effects such as top and bottom refelcotr positions and reflectivity which could not be included in the 2.5D model. This new computer model also includes a full 3D calculation of the amplified spontaneous emission rate in the laser slab, as opposed to the 2.5D model which tracked only the variation in the gain across the transverse dimensions of the slab. We will present the impact of this evolution of the model on the predicted stimulated decay rate and the resulting gain distribution. Comparison with most recent AmpLab experimental result will be presented, in the different typical NIF and LMJ configurations.

The Impacts of 3-D Earth Structure on GIA-Induced Crustal Deformation and Future Sea-Level Change in the Antarctic

NASA Astrophysics Data System (ADS)

Powell, E. M.; Hay, C.; Latychev, K.; Gomez, N. A.; Mitrovica, J. X.

2016-12-01

Glacial Isostatic Adjustment (GIA) models used to constrain the extent of past ice sheets and viscoelastic Earth structure, or to correct geodetic and geological observables for ice age effects, generally only consider depth-dependent variations in Earth viscosity and lithospheric structure. A et al. [2013] argued that 3-D Earth structure could impact GIA observables in Antarctica, but concluded that the presence of such structure contributes less to GIA uncertainty than do differences in Antarctic deglaciation histories. New seismic and geological evidence, however, indicates the Antarctic is underlain by complex, high amplitude variability in viscoelastic structure, including a low viscosity zone (LVZ) under West Antarctica. Hay et al. [2016] showed that sea-level fingerprints of modern melting calculated using such Earth models differ from those based on elastic or 1-D viscoelastic Earth models within decades of melting. Our investigation is motivated by two questions: (1) How does 3-D Earth structure, especially this LVZ, impact observations of GIA-induced crustal deformation associated with the last deglaciation? (2) How will 3-D Earth structure affect predictions of future sea-level rise in Antarctica? We compute the gravitationally self-consistent sea level, uplift, and gravity changes using the finite volume treatment of Latychev et al. [2005]. We consider four viscoelastic Earth models: a global 1-D model; a regional, West Antarctic-like 1-D model; a 3-D model where the lithospheric thickness varies laterally; and a 3-D model where both viscosity and lithospheric thickness vary laterally. For our Last Glacial Maximum to present investigations we employ ICE6g [Peltier et al., 2015]. For our present-future investigations we consider a melt scenario consistent with GRACE satellite gravity derived solutions [Harig et al., 2015]. Our calculations indicate that predictions of crustal deformations due to both GIA and ongoing melting are strongly influenced by 3-D lithospheric thickness and viscosity structure. Future sea level change due to ongoing melting is primarily influenced by 3-D viscosity structure. We show that 1-D Earth models built using regional inferences of viscosity and lithospheric thickness do not accurately capture the variability introduced by 3-D Earth structure.

The Impacts of 3-D Earth Structure on GIA-Induced Crustal Deformation and Future Sea-Level Change in the Antarctic

NASA Astrophysics Data System (ADS)

Powell, E. M.; Hay, C.; Latychev, K.; Gomez, N. A.; Mitrovica, J. X.

2017-12-01

Glacial Isostatic Adjustment (GIA) models used to constrain the extent of past ice sheets and viscoelastic Earth structure, or to correct geodetic and geological observables for ice age effects, generally only consider depth-dependent variations in Earth viscosity and lithospheric structure. A et al. [2013] argued that 3-D Earth structure could impact GIA observables in Antarctica, but concluded that the presence of such structure contributes less to GIA uncertainty than do differences in Antarctic deglaciation histories. New seismic and geological evidence, however, indicates the Antarctic is underlain by complex, high amplitude variability in viscoelastic structure, including a low viscosity zone (LVZ) under West Antarctica. Hay et al. [2016] showed that sea-level fingerprints of modern melting calculated using such Earth models differ from those based on elastic or 1-D viscoelastic Earth models within decades of melting. Our investigation is motivated by two questions: (1) How does 3-D Earth structure, especially this LVZ, impact observations of GIA-induced crustal deformation associated with the last deglaciation? (2) How will 3-D Earth structure affect predictions of future sea-level rise in Antarctica? We compute the gravitationally self-consistent sea level, uplift, and gravity changes using the finite volume treatment of Latychev et al. [2005]. We consider four viscoelastic Earth models: a global 1-D model; a regional, West Antarctic-like 1-D model; a 3-D model where the lithospheric thickness varies laterally; and a 3-D model where both viscosity and lithospheric thickness vary laterally. For our Last Glacial Maximum to present investigations we employ ICE6g [Peltier et al., 2015]. For our present-future investigations we consider a melt scenario consistent with GRACE satellite gravity derived solutions [Harig et al., 2015]. Our calculations indicate that predictions of crustal deformations due to both GIA and ongoing melting are strongly influenced by 3-D lithospheric thickness and viscosity structure. Future sea level change due to ongoing melting is primarily influenced by 3-D viscosity structure. We show that 1-D Earth models built using regional inferences of viscosity and lithospheric thickness do not accurately capture the variability introduced by 3-D Earth structure.

Effective equations for matter-wave gap solitons in higher-order transversal states.

PubMed

Mateo, A Muñoz; Delgado, V

2013-10-01

We demonstrate that an important class of nonlinear stationary solutions of the three-dimensional (3D) Gross-Pitaevskii equation (GPE) exhibiting nontrivial transversal configurations can be found and characterized in terms of an effective one-dimensional (1D) model. Using a variational approach we derive effective equations of lower dimensionality for BECs in (m,n(r)) transversal states (states featuring a central vortex of charge m as well as n(r) concentric zero-density rings at every z plane) which provides us with a good approximate solution of the original 3D problem. Since the specifics of the transversal dynamics can be absorbed in the renormalization of a couple of parameters, the functional form of the equations obtained is universal. The model proposed finds its principal application in the study of the existence and classification of 3D gap solitons supported by 1D optical lattices, where in addition to providing a good estimate for the 3D wave functions it is able to make very good predictions for the μ(N) curves characterizing the different fundamental families. We have corroborated the validity of our model by comparing its predictions with those from the exact numerical solution of the full 3D GPE.

Daily hydro- and morphodynamic simulations at Duck, NC, USA using Delft3D

NASA Astrophysics Data System (ADS)

Penko, Allison; Veeramony, Jay; Palmsten, Margaret; Bak, Spicer; Brodie, Katherine; Hesser, Tyler

2017-04-01

Operational forecasting of the coastal nearshore has wide ranging societal and humanitarian benefits, specifically for the prediction of natural hazards due to extreme storm events. However, understanding the model limitations and uncertainty is as equally important as the predictions themselves. By comparing and contrasting the predictions of multiple high-resolution models in a location with near real-time collection of observations, we are able to perform a vigorous analysis of the model results in order to achieve more robust and certain predictions. In collaboration with the U.S. Army Corps of Engineers Field Research Facility (USACE FRF) as part of the Coastal Model Test Bed (CMTB) project, we have set up Delft3D at Duck, NC, USA to run in near-real time, driven by measured wave data at the boundary. The CMTB at the USACE FRF allows for the unique integration of operational wave, circulation, and morphology models with real-time observations. The FRF has an extensive array of in-situ and remotely sensed oceanographic, bathymetric, and meteorological data that is broadcast in near-real time onto a publically accessible server. Wave, current, and bed elevation instruments are permanently installed across the model domain including 2 waverider buoys in 17-m and 26-m water depths at 3.5-km and 17-km offshore, respectively, that record directional wave data every 30-min. Here, we present the workflow and output of the Delft3D hydro- and morphodynamic simulations at Duck, and show the tactical benefits and operational potential of such a system. A nested Delft3D simulation runs a parent grid that extends 12-km in the along-shore and 3.5-km in the cross-shore with 50-m resolution and a maximum depth of approximately 17-m. The bathymetry for the parent grid was obtained from a regional digital elevation model (DEM) generated by the Federal Emergency Management Agency (FEMA). The inner nested grid extends 1.8-km in the along-shore and 1-km in the cross-shore with 5-m resolution and a maximum depth of approximately 8-m. The inner nested grid initial model bathymetry is set to either the predicted bathymetry from the previous day's simulation or a survey, whichever is more recent. Delft3D-WAVE runs in the parent grid and is driven with the real-time spectral wave measurements from the waverider buoy in 17-m depth. The spectral output from Delft3D-WAVE in the parent grid is then used as the boundary condition for the inner nested high-resolution grid, in which the coupled Delft3D wave-flow-morphology model is run. The model results are then compared to the wave, current, and bathymetry observations collected at the FRF as well as other models that are run in the CMTB.

Modeling Statistics of Fish Patchiness and Predicting Associated Influence on Statistics of Acoustic Echoes

DTIC Science & Technology

2013-09-30

data. The Niwa and Anderson models were compared with 3-D multi-beam data collected by Paramo and Gerlotto. The data were consistent with the...Bhatia, S., T.K. Stanton, J. Paramo , and F. Gerlotto (under revision), “Modeling statistics of fish school dimensions using 3-D data from a

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Distribution of aerosolized particles in healthy and emphysematous rat lungs: comparison between experimental and numerical studies.

PubMed

Oakes, Jessica M; Marsden, Alison L; Grandmont, Céline; Darquenne, Chantal; Vignon-Clementel, Irene E

2015-04-13

In silico models of airflow and particle deposition in the lungs are increasingly used to determine the therapeutic or toxic effects of inhaled aerosols. While computational methods have advanced significantly, relatively few studies have directly compared model predictions to experimental data. Furthermore, few prior studies have examined the influence of emphysema on particle deposition. In this work we performed airflow and particle simulations to compare numerical predictions to data from our previous aerosol exposure experiments. Employing an image-based 3D rat airway geometry, we first compared steady flow simulations to coupled 3D-0D unsteady simulations in the healthy rat lung. Then, in 3D-0D simulations, the influence of emphysema was investigated by matching disease location to the experimental study. In both the healthy unsteady and steady simulations, good agreement was found between numerical predictions of aerosol delivery and experimental deposition data. However, deposition patterns in the 3D geometry differed between the unsteady and steady cases. On the contrary, satisfactory agreement was not found between the numerical predictions and experimental data for the emphysematous lungs. This indicates that the deposition rate downstream of the 3D geometry is likely proportional to airflow delivery in the healthy lungs, but not in the emphysematous lungs. Including small airway collapse, variations in downstream airway size and tissue properties, and tracking particles throughout expiration may result in a more favorable agreement in future studies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Second-Moment RANS Model Verification and Validation Using the Turbulence Modeling Resource Website (Invited)

NASA Technical Reports Server (NTRS)

Eisfeld, Bernhard; Rumsey, Chris; Togiti, Vamshi

2015-01-01

The implementation of the SSG/LRR-omega differential Reynolds stress model into the NASA flow solvers CFL3D and FUN3D and the DLR flow solver TAU is verified by studying the grid convergence of the solution of three different test cases from the Turbulence Modeling Resource Website. The model's predictive capabilities are assessed based on four basic and four extended validation cases also provided on this website, involving attached and separated boundary layer flows, effects of streamline curvature and secondary flow. Simulation results are compared against experimental data and predictions by the eddy-viscosity models of Spalart-Allmaras (SA) and Menter's Shear Stress Transport (SST).

A predictive nondestructive model for the covariation of tree height, diameter, and stem volume scaling relationships.

PubMed

Zhang, Zhongrui; Zhong, Quanlin; Niklas, Karl J; Cai, Liang; Yang, Yusheng; Cheng, Dongliang

2016-08-24

Metabolic scaling theory (MST) posits that the scaling exponents among plant height H, diameter D, and biomass M will covary across phyletically diverse species. However, the relationships between scaling exponents and normalization constants remain unclear. Therefore, we developed a predictive model for the covariation of H, D, and stem volume V scaling relationships and used data from Chinese fir (Cunninghamia lanceolata) in Jiangxi province, China to test it. As predicted by the model and supported by the data, normalization constants are positively correlated with their associated scaling exponents for D vs. V and H vs. V, whereas normalization constants are negatively correlated with the scaling exponents of H vs. D. The prediction model also yielded reliable estimations of V (mean absolute percentage error = 10.5 ± 0.32 SE across 12 model calibrated sites). These results (1) support a totally new covariation scaling model, (2) indicate that differences in stem volume scaling relationships at the intra-specific level are driven by anatomical or ecophysiological responses to site quality and/or management practices, and (3) provide an accurate non-destructive method for predicting Chinese fir stem volume.

Concentrations and fate of decamethylcyclopentasiloxane (D(5)) in the atmosphere.

PubMed

McLachlan, Michael S; Kierkegaard, Amelie; Hansen, Kaj M; van Egmond, Roger; Christensen, Jesper H; Skjøth, Carsten A

2010-07-15

Decamethylcyclopentasiloxane (D(5)) is a volatile compound used in personal care products that is released to the atmosphere in large quantities. Although D(5) is currently under consideration for regulation, there have been no field investigations of its atmospheric fate. We employed a recently developed, quality assured method to measure D(5) concentration in ambient air at a rural site in Sweden. The samples were collected with daily resolution between January and June 2009. The D(5) concentration ranged from 0.3 to 9 ng m(-3), which is 1-3 orders of magnitude lower than previous reports. The measured data were compared with D(5) concentrations predicted using an atmospheric circulation model that included both OH radical and D(5) chemistry. The model was parametrized using emissions estimates and physical chemical properties determined in laboratory experiments. There was good agreement between the measured and modeled D(5) concentrations. The results show that D(5) is clearly subject to long-range atmospheric transport, but that it is also effectively removed from the atmosphere via phototransformation. Atmospheric deposition has little influence on the atmospheric fate. The good agreement between the model predictions and the field observations indicates that there is a good understanding of the major factors governing D(5) concentrations in the atmosphere.

Object detection in natural backgrounds predicted by discrimination performance and models

NASA Technical Reports Server (NTRS)

Rohaly, A. M.; Ahumada, A. J. Jr; Watson, A. B.

1997-01-01

Many models of visual performance predict image discriminability, the visibility of the difference between a pair of images. We compared the ability of three image discrimination models to predict the detectability of objects embedded in natural backgrounds. The three models were: a multiple channel Cortex transform model with within-channel masking; a single channel contrast sensitivity filter model; and a digital image difference metric. Each model used a Minkowski distance metric (generalized vector magnitude) to summate absolute differences between the background and object plus background images. For each model, this summation was implemented with three different exponents: 2, 4 and infinity. In addition, each combination of model and summation exponent was implemented with and without a simple contrast gain factor. The model outputs were compared to measures of object detectability obtained from 19 observers. Among the models without the contrast gain factor, the multiple channel model with a summation exponent of 4 performed best, predicting the pattern of observer d's with an RMS error of 2.3 dB. The contrast gain factor improved the predictions of all three models for all three exponents. With the factor, the best exponent was 4 for all three models, and their prediction errors were near 1 dB. These results demonstrate that image discrimination models can predict the relative detectability of objects in natural scenes.

3D RNA and functional interactions from evolutionary couplings

PubMed Central

Weinreb, Caleb; Riesselman, Adam; Ingraham, John B.; Gross, Torsten; Sander, Chris; Marks, Debora S.

2016-01-01

Summary Non-coding RNAs are ubiquitous, but the discovery of new RNA gene sequences far outpaces research on their structure and functional interactions. We mine the evolutionary sequence record to derive precise information about function and structure of RNAs and RNA-protein complexes. As in protein structure prediction, we use maximum entropy global probability models of sequence co-variation to infer evolutionarily constrained nucleotide-nucleotide interactions within RNA molecules, and nucleotide-amino acid interactions in RNA-protein complexes. The predicted contacts allow all-atom blinded 3D structure prediction at good accuracy for several known RNA structures and RNA-protein complexes. For unknown structures, we predict contacts in 160 non-coding RNA families. Beyond 3D structure prediction, evolutionary couplings help identify important functional interactions, e.g., at switch points in riboswitches and at a complex nucleation site in HIV. Aided by accelerating sequence accumulation, evolutionary coupling analysis can accelerate the discovery of functional interactions and 3D structures involving RNA. PMID:27087444

Dynamic effects of root system architecture improve root water uptake in 1-D process-based soil-root hydrodynamics

NASA Astrophysics Data System (ADS)

Bouda, Martin; Saiers, James E.

2017-12-01

Root system architecture (RSA) can significantly affect plant access to water, total transpiration, as well as its partitioning by soil depth, with implications for surface heat, water, and carbon budgets. Despite recent advances in land surface model (LSM) descriptions of plant hydraulics, descriptions of RSA have not been included because of their three-dimensional complexity, which makes them generally too computationally costly. Here we demonstrate a new, process-based 1D layered model that captures the dynamic shifts in water potential gradients of 3D RSA under different soil moisture conditions: the RSA stencil. Using root systems calibrated to the rooting profiles of four plant functional types (PFT) of the Community Land Model, we show that the RSA stencil predicts plant water potentials within 2% to the outputs of a full 3D model, under the same assumptions on soil moisture heterogeneity, despite its trivial computational cost, resulting in improved predictions of water uptake and soil moisture compared to a model without RSA in a transient simulation. Our results suggest that LSM predictions of soil moisture dynamics and dependent variables can be improved by the implementation of this model, calibrated for individual PFTs using field observations.

Application of a time-magnitude prediction model for earthquakes

NASA Astrophysics Data System (ADS)

An, Weiping; Jin, Xueshen; Yang, Jialiang; Dong, Peng; Zhao, Jun; Zhang, He

2007-06-01

In this paper we discuss the physical meaning of the magnitude-time model parameters for earthquake prediction. The gestation process for strong earthquake in all eleven seismic zones in China can be described by the magnitude-time prediction model using the computations of the parameters of the model. The average model parameter values for China are: b = 0.383, c=0.154, d = 0.035, B = 0.844, C = -0.209, and D = 0.188. The robustness of the model parameters is estimated from the variation in the minimum magnitude of the transformed data, the spatial extent, and the temporal period. Analysis of the spatial and temporal suitability of the model indicates that the computation unit size should be at least 4° × 4° for seismic zones in North China, at least 3° × 3° in Southwest and Northwest China, and the time period should be as long as possible.

RNA 3D Structure Modeling by Combination of Template-Based Method ModeRNA, Template-Free Folding with SimRNA, and Refinement with QRNAS.

PubMed

Piatkowski, Pawel; Kasprzak, Joanna M; Kumar, Deepak; Magnus, Marcin; Chojnowski, Grzegorz; Bujnicki, Janusz M

2016-01-01

RNA encompasses an essential part of all known forms of life. The functions of many RNA molecules are dependent on their ability to form complex three-dimensional (3D) structures. However, experimental determination of RNA 3D structures is laborious and challenging, and therefore, the majority of known RNAs remain structurally uncharacterized. To address this problem, computational structure prediction methods were developed that either utilize information derived from known structures of other RNA molecules (by way of template-based modeling) or attempt to simulate the physical process of RNA structure formation (by way of template-free modeling). All computational methods suffer from various limitations that make theoretical models less reliable than high-resolution experimentally determined structures. This chapter provides a protocol for computational modeling of RNA 3D structure that overcomes major limitations by combining two complementary approaches: template-based modeling that is capable of predicting global architectures based on similarity to other molecules but often fails to predict local unique features, and template-free modeling that can predict the local folding, but is limited to modeling the structure of relatively small molecules. Here, we combine the use of a template-based method ModeRNA with a template-free method SimRNA. ModeRNA requires a sequence alignment of the target RNA sequence to be modeled with a template of the known structure; it generates a model that predicts the structure of a conserved core and provides a starting point for modeling of variable regions. SimRNA can be used to fold small RNAs (<80 nt) without any additional structural information, and to refold parts of models for larger RNAs that have a correctly modeled core. ModeRNA can be either downloaded, compiled and run locally or run through a web interface at http://genesilico.pl/modernaserver/ . SimRNA is currently available to download for local use as a precompiled software package at http://genesilico.pl/software/stand-alone/simrna and as a web server at http://genesilico.pl/SimRNAweb . For model optimization we use QRNAS, available at http://genesilico.pl/qrnas .

Regional Climate Simulations with COSMO-CLM for West Africa using three different soil-vegetation-atmosphere-transfer (SVAT) module

NASA Astrophysics Data System (ADS)

Breil, Marcus; Panitz, Hans-Jürgen

2014-05-01

Climate predictions on decadal timescales constitute a new field of research, closing the gap between short-term and seasonal weather predictions and long-term climate projections. Therefore, the Federal Ministry of Education and Research in Germany (BMBF) has recently funded the research program MiKlip (Mittelfristige Klimaprognosen), which aims to create a model system that can provide reliable decadal climate forecasts. Recent studies have suggested that one region with high potential decadal predictability is West Africa. Therefore, the project DEPARTURE (DEcadal Prediction of African Rainfall and ATlantic HURricanE Activity) was established within the MiKlip program to assess the feasibility and the potential added value of regional decadal climate predictions for West Africa. To quantify the potential decadal climate predictability, a multi-model approach with the three different regional climate models REMO, WRF and COSMO-CLM (CCLM) will be realized. The presented research will contribute to DEPARTURE by performing hindcast ensemble simulations with CCLM, driven by global decadal MPI-ESM-LR simulations. Thereby, one focus is on the dynamic soil-vegetation-climate interaction on decadal timescales. Recent studies indicate that there are significant feedbacks between the land-surface and the atmosphere, which might influence the decadal climate variability substantially. To investigate this connection, two different SVATs (Community Land Model (CLM), and VEG3D) will be coupled with the CCLM, replacing TERRA_ML, the standard SVAT implemented in CCLM. Thus, sensitive model parameters shall be identified, whereby the understanding of important processes might be improved. As a first step, TERRA_ML is substituted by VEG3D, a SVAT developed at the IMK-TRO, Karlsruhe, Germany. Compared to TERRA_ML, VEG3D includes an explicit vegetation layer by using a big leaf approach, inducing higher correlations with observations as it has been shown in previous studies. The coupling of VEG3D with CCLM is performed by using the OASIS3-MCT coupling software, developed by CERFACS, Toulouse, France. Results of CCLM simulations using both SVATs are analysed and compared for the DEPARTURE model domain. Thereby ERA-Interim driven CCLM simulations with VEG3D showed better agreement with observational data than simulations with TERRA_ML, especially for dense vegetaded areas. This will be demonstrated exemplarily. Additionally, results for MPI-ESM-LR driven decadal hindcast simulations (1966 - 1975) are analysed and presented.

Light distribution in plant canopies: A comparison between 1-D multi-layer modeling approach and 3-D ray tracing

NASA Astrophysics Data System (ADS)

Srinivasan, V.; Yiwen, X.; Ellis, A.; Christensen, A.; Borkiewic, K.; Cox, D.; Hart, J.; Long, S.; Marshall-Colon, A.

2016-12-01

The distribution of absorbed solar radiation in the photosynthetically active region wavelength (PAR) within plant canopies plays a critical role in determining photosynthetic carbon uptake and its associated transpiration. The vertical distribution of leaf area, leaf angles, leaf absorptivity and reflectivity within the canopy, affect the distribution of PAR absorbed throughout the canopy. While the upper canopy sunlit leaves absorb most of the incoming PAR and hence contribute most towards total canopy carbon uptake, the lower canopy shaded leaves which receive mostly lower intensity diffuse PAR make significant contributions towards plant carbon uptake. Most detailed vegetation models use a 1-D vertical multi-layer approach to model the sunlight and shaded canopy leaf fractions, and quantify the direct and diffuse radiation absorbed by the respective leaf fractions. However, this approach is only applicable under canopy closure conditions, and furthermore it fails to accurately capture the effects of diurnally varying leaf angle distributions in some plant canopies. Here, we show by using a 3-D ray tracing model which uses an explicit 3-D canopy structure that enforces no conditions about canopy closure, that the effects of diurnal variation of canopy leaf angle distributions better match with observed data. Our comparative analysis performed on soybean crop canopies between 3-D ray tracing model and the multi-layer model shows that the distribution of absorbed direct PAR is not exponential while, the distribution of absorbed diffuse PAR radiation within plant canopies is exponential. These results show the multi-layer model to significantly over-predict canopy PAR absorbed, and in turn significantly overestimate photosynthetic carbon uptake by up to 13% and canopy transpiration by 7% under mid-day sun conditions as verified through our canopy chamber experiments. Our results indicate that current detailed 1-D multi-layer canopy radiation attenuation models significantly over predict canopy radiation absorption and its associated canopy photosynthetic and transpiration fluxes, and use of a 3-D ray tracing model provides more realistic predictions of leaf canopy integrated fluxes of carbon and water.

Assessing deep-seated landslide susceptibility using 3-D groundwater and slope-stability analyses, southwestern Seattle, Washington

USGS Publications Warehouse

Brien, Dianne L.; Reid, Mark E.

2008-01-01

In Seattle, Washington, deep-seated landslides on bluffs along Puget Sound have historically caused extensive damage to land and structures. These large failures are controlled by three-dimensional (3-D) variations in strength and pore-water pressures. We assess the slope stability of part of southwestern Seattle using a 3-D limit-equilibrium analysis coupled with a 3-D groundwater flow model. Our analyses use a high-resolution digital elevation model (DEM) combined with assignment of strength and hydraulic properties based on geologic units. The hydrogeology of the Seattle area consists of a layer of permeable glacial outwash sand that overlies less permeable glacial lacustrine silty clay. Using a 3-D groundwater model, MODFLOW-2000, we simulate a water table above the less permeable units and calibrate the model to observed conditions. The simulated pore-pressure distribution is then used in a 3-D slope-stability analysis, SCOOPS, to quantify the stability of the coastal bluffs. For wet winter conditions, our analyses predict that the least stable areas are steep hillslopes above Puget Sound, where pore pressures are elevated in the outwash sand. Groundwater flow converges in coastal reentrants, resulting in elevated pore pressures and destabilization of slopes. Regions predicted to be least stable include the areas in or adjacent to three mapped historically active deep-seated landslides. The results of our 3-D analyses differ significantly from a slope map or results from one-dimensional (1-D) analyses.

Evaluation and development of satellite inferences of convective storm intensity using combined case study and thunderstorm model simulations

NASA Technical Reports Server (NTRS)

Cotton, W. R.; Tripoli, G. J.

1982-01-01

Observational requirements for predicting convective storm development and intensity as suggested by recent numerical experiments are examined. Recent 3D numerical experiments are interpreted with regard to the relationship between overshooting tops and surface wind gusts. The development of software for emulating satellite inferred cloud properties using 3D cloud model predicted data and the simulation of Heymsfield (1981) Northern Illinois storm are described as well as the development of a conceptual/semi-quantitative model of eastward propagating, mesoscale convective complexes forming to the lee of the Rocky Mountains.

LECTINPred: web Server that Uses Complex Networks of Protein Structure for Prediction of Lectins with Potential Use as Cancer Biomarkers or in Parasite Vaccine Design.

PubMed

Munteanu, Cristian R; Pedreira, Nieves; Dorado, Julián; Pazos, Alejandro; Pérez-Montoto, Lázaro G; Ubeira, Florencio M; González-Díaz, Humberto

2014-04-01

Lectins (Ls) play an important role in many diseases such as different types of cancer, parasitic infections and other diseases. Interestingly, the Protein Data Bank (PDB) contains +3000 protein 3D structures with unknown function. Thus, we can in principle, discover new Ls mining non-annotated structures from PDB or other sources. However, there are no general models to predict new biologically relevant Ls based on 3D chemical structures. We used the MARCH-INSIDE software to calculate the Markov-Shannon 3D electrostatic entropy parameters for the complex networks of protein structure of 2200 different protein 3D structures, including 1200 Ls. We have performed a Linear Discriminant Analysis (LDA) using these parameters as inputs in order to seek a new Quantitative Structure-Activity Relationship (QSAR) model, which is able to discriminate 3D structure of Ls from other proteins. We implemented this predictor in the web server named LECTINPred, freely available at http://bio-aims.udc.es/LECTINPred.php. This web server showed the following goodness-of-fit statistics: Sensitivity=96.7 % (for Ls), Specificity=87.6 % (non-active proteins), and Accuracy=92.5 % (for all proteins), considering altogether both the training and external prediction series. In mode 2, users can carry out an automatic retrieval of protein structures from PDB. We illustrated the use of this server, in operation mode 1, performing a data mining of PDB. We predicted Ls scores for +2000 proteins with unknown function and selected the top-scored ones as possible lectins. In operation mode 2, LECTINPred can also upload 3D structural models generated with structure-prediction tools like LOMETS or PHYRE2. The new Ls are expected to be of relevance as cancer biomarkers or useful in parasite vaccine design. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

USM3D Predictions of Supersonic Nozzle Flow

NASA Technical Reports Server (NTRS)

Carter, Melissa B.; Elmiligui, Alaa A.; Campbell, Richard L.; Nayani, Sudheer N.

2014-01-01

This study focused on the NASA Tetrahedral Unstructured Software System CFD code (USM3D) capability to predict supersonic plume flow. Previous studies, published in 2004 and 2009, investigated USM3D's results versus historical experimental data. This current study continued that comparison however focusing on the use of the volume souring to capture the shear layers and internal shock structure of the plume. This study was conducted using two benchmark axisymmetric supersonic jet experimental data sets. The study showed that with the use of volume sourcing, USM3D was able to capture and model a jet plume's shear layer and internal shock structure.

Dyamical Systems Theory and Lagrangian Data Assimilation in 4D Geophysical Fluid Dynamics

DTIC Science & Technology

The long-term goal of our project (known as OCEAN 3D +1) was to better understand and predict ocean circulation features that are fundamentally three...dimensional in space and that vary in time. In particular, we sought to quantify the dynamical processes that govern the formation , evolution, and...predictability of 3D +1 transport pathways in the ocean. Our approach was to develop algorithms to thoroughly analyze a hierarchy of model and

Using Flux Site Observations to Calibrate Root System Architecture Stencils for Water Uptake of Plant Functional Types in Land Surface Models.

NASA Astrophysics Data System (ADS)

Bouda, M.

2017-12-01

Root system architecture (RSA) can significantly affect plant access to water, total transpiration, as well as its partitioning by soil depth, with implications for surface heat, water, and carbon budgets. Despite recent advances in land surface model (LSM) descriptions of plant hydraulics, RSA has not been included because of its three-dimensional complexity, which makes RSA modelling generally too computationally costly. This work builds upon the recently introduced "RSA stencil," a process-based 1D layered model that captures the dynamic shifts in water potential gradients of 3D RSA in response to heterogeneous soil moisture profiles. In validations using root systems calibrated to the rooting profiles of four plant functional types (PFT) of the Community Land Model, the RSA stencil predicts plant water potentials within 2% of the outputs of full 3D models, despite its trivial computational cost. In transient simulations, the RSA stencil yields improved predictions of water uptake and soil moisture profiles compared to a 1D model based on root fraction alone. Here I show how the RSA stencil can be calibrated to time-series observations of soil moisture and transpiration to yield a water uptake PFT definition for use in terrestrial models. This model-data integration exercise aims to improve LSM predictions of soil moisture dynamics and, under water-limiting conditions, surface fluxes. These improvements can be expected to significantly impact predictions of downstream variables, including surface fluxes, climate-vegetation feedbacks and soil nutrient cycling.

A degree-day model initiated by pheromone trap captures for managing pecan nut casebearer (Lepidoptera: Pyralidae) in pecans.

PubMed

Knutson, Allen E; Muegge, Mark A

2010-06-01

Field observations from pecan, Carya illinoinensis (Wangenh.) Koch, orchards in Texas were used to develop and validate a degree-day model of cumulative proportional adult flight and oviposition and date of first observed nut entry by larvae of the first summer generation of the pecan nut casebearer, Acrobasis nuxvorella Nuenzig (Lepidoptera: Pyralidae). The model was initiated on the date of first sustained capture of adults in pheromone traps. Mean daily maximum and minimum temperatures were used to determine the sum of degree-days from onset to 99% moth flight and oviposition and the date on which first summer generation larvae were first observed penetrating pecan nuts. Cumulative proportional oviposition (y) was described by a modified Gompertz equation, y = 106.05 x exp(-(exp(3.11 - 0.00669 x (x - 1), with x = cumulative degree-days at a base temperature of 3.33 degrees C. Cumulative proportional moth flight (y) was modeled as y = 102.62 x exp(- (exp(1.49 - 0.00571 x (x - 1). Model prediction error for dates of 10, 25, 50, 75, and 90% cumulative oviposition was 1.3 d and 83% of the predicted dates were within +/- 2 d of the observed event. Prediction error for date of first observed nut entry was 2.2 d and 77% of model predictions were within +/- 2 d of the observed event. The model provides ample lead time for producers to implement orchard scouting to assess pecan nut casebearer infestations and to apply an insecticide if needed to prevent economic loss.

Implementation of algebraic stress models in a general 3-D Navier-Stokes method (PAB3D)

NASA Technical Reports Server (NTRS)

Abdol-Hamid, Khaled S.

1995-01-01

A three-dimensional multiblock Navier-Stokes code, PAB3D, which was developed for propulsion integration and general aerodynamic analysis, has been used extensively by NASA Langley and other organizations to perform both internal (exhaust) and external flow analysis of complex aircraft configurations. This code was designed to solve the simplified Reynolds Averaged Navier-Stokes equations. A two-equation k-epsilon turbulence model has been used with considerable success, especially for attached flows. Accurate predicting of transonic shock wave location and pressure recovery in separated flow regions has been more difficult. Two algebraic Reynolds stress models (ASM) have been recently implemented in the code that greatly improved the code's ability to predict these difficult flow conditions. Good agreement with Direct Numerical Simulation (DNS) for a subsonic flat plate was achieved with ASM's developed by Shih, Zhu, and Lumley and Gatski and Speziale. Good predictions were also achieved at subsonic and transonic Mach numbers for shock location and trailing edge boattail pressure recovery on a single-engine afterbody/nozzle model.

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

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

Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.

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 datasetsmore » 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 value for both ER-positive and ER-negative breast cancer. The signature was selected using a novel biological approach and hence holds promise to represent the key biological processes of breast cancer.« less

Modelling Time and Length Scales of Scour Around a Pipeline

NASA Astrophysics Data System (ADS)

Smith, H. D.; Foster, D. L.

2002-12-01

The scour and burial of submarine objects is an area of interest for engineers, oceanographers and military personnel. Given the limited availability of field observations, there exists a need to accurately describe the hydrodynamics and sediment response around an obstacle using numerical models. In this presentation, we will compare observations of submarine pipeline scour with model predictions. The research presented here uses the computational fluid dynamics (CFD) model FLOW-3D. FLOW-3D, developed by Flow Science in Santa Fe, NM, is a 3-dimensional finite-difference model that solves the Navier-Stokes and continuity equations. Using the Volume of Fluid (VOF) technique, FLOW-3D is able to resolve fluid-fluid and fluid-air interfaces. The FAVOR technique allows for complex geometry to be resolved with rectangular grids. FLOW-3D uses a bulk transport method to describe sediment transport and feedback to the hydrodynamic solver is accomplished by morphology evolution and fluid viscosity due to sediment suspension. Previous investigations by the authors have shown FLOW-3D to well-predict the hydrodynamics around five static scoured bed profiles and a stationary pipeline (``Modelling of Flow Around a Cylinder Over a Scoured Bed,'' submit to Journal of Waterway, Port, Coastal, and Ocean Engineering). Following experiments performed by Mao (1986, Dissertation, Technical University of Denmark), we will be performing model-data comparisons of length and time scales for scour around a pipeline. Preliminary investigations with LES and k-ɛ closure schemes have shown that the model predicts shorter time scales in scour hole development than that observed by Mao. Predicted time and length scales of scour hole development are shown to be a function of turbulence closure scheme, grain size, and hydrodynamic forcing. Subsequent investigations consider variable wave-current flow regimes and object burial. This investigation will allow us to identify different regimes for the scour process based on dimensionless parameters such as the Reynolds number, the Keulegan-Carpenter number, and the sediment mobility number. This research is sponsored by the Office of Naval Research - Mine Burial Program.

Computational analysis on plug-in hybrid electric motorcycle chassis

NASA Astrophysics Data System (ADS)

Teoh, S. J.; Bakar, R. A.; Gan, L. M.

2013-12-01

Plug-in hybrid electric motorcycle (PHEM) is an alternative to promote sustainability lower emissions. However, the PHEM overall system packaging is constrained by limited space in a motorcycle chassis. In this paper, a chassis applying the concept of a Chopper is analysed to apply in PHEM. The chassis 3dimensional (3D) modelling is built with CAD software. The PHEM power-train components and drive-train mechanisms are intergraded into the 3D modelling to ensure the chassis provides sufficient space. Besides that, a human dummy model is built into the 3D modelling to ensure the rider?s ergonomics and comfort. The chassis 3D model then undergoes stress-strain simulation. The simulation predicts the stress distribution, displacement and factor of safety (FOS). The data are used to identify the critical point, thus suggesting the chassis design is applicable or need to redesign/ modify to meet the require strength. Critical points mean highest stress which might cause the chassis to fail. This point occurs at the joints at triple tree and bracket rear absorber for a motorcycle chassis. As a conclusion, computational analysis predicts the stress distribution and guideline to develop a safe prototype chassis.

Predictive equations for lung volumes from computed tomography for size matching in pulmonary transplantation.

PubMed

Konheim, Jeremy A; Kon, Zachary N; Pasrija, Chetan; Luo, Qingyang; Sanchez, Pablo G; Garcia, Jose P; Griffith, Bartley P; Jeudy, Jean

2016-04-01

Size matching for lung transplantation is widely accomplished using height comparisons between donors and recipients. This gross approximation allows for wide variation in lung size and, potentially, size mismatch. Three-dimensional computed tomography (3D-CT) volumetry comparisons could offer more accurate size matching. Although recipient CT scans are universally available, donor CT scans are rarely performed. Therefore, predicted donor lung volumes could be used for comparison to measured recipient lung volumes, but no such predictive equations exist. We aimed to use 3D-CT volumetry measurements from a normal patient population to generate equations for predicted total lung volume (pTLV), predicted right lung volume (pRLV), and predicted left lung volume (pLLV), for size-matching purposes. Chest CT scans of 400 normal patients were retrospectively evaluated. 3D-CT volumetry was performed to measure total lung volume, right lung volume, and left lung volume of each patient, and predictive equations were generated. The fitted model was tested in a separate group of 100 patients. The model was externally validated by comparison of total lung volume with total lung capacity from pulmonary function tests in a subset of those patients. Age, gender, height, and race were independent predictors of lung volume. In the test group, there were strong linear correlations between predicted and actual lung volumes measured by 3D-CT volumetry for pTLV (r = 0.72), pRLV (r = 0.72), and pLLV (r = 0.69). A strong linear correlation was also observed when comparing pTLV and total lung capacity (r = 0.82). We successfully created a predictive model for pTLV, pRLV, and pLLV. These may serve as reference standards and predict donor lung volume for size matching in lung transplantation. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

USM3D Analysis of Low Boom Configuration

NASA Technical Reports Server (NTRS)

Carter, Melissa B.; Campbell, Richard L.; Nayani, Sudheer N.

2011-01-01

In the past few years considerable improvement was made in NASA's in house boom prediction capability. As part of this improved capability, the USM3D Navier-Stokes flow solver, when combined with a suitable unstructured grid, went from accurately predicting boom signatures at 1 body length to 10 body lengths. Since that time, the research emphasis has shifted from analysis to the design of supersonic configurations with boom signature mitigation In order to design an aircraft, the techniques for accurately predicting boom and drag need to be determined. This paper compares CFD results with the wind tunnel experimental results conducted on a Gulfstream reduced boom and drag configuration. Two different wind-tunnel models were designed and tested for drag and boom data. The goal of this study was to assess USM3D capability for predicting both boom and drag characteristics. Overall, USM3D coupled with a grid that was sheared and stretched was able to reasonably predict boom signature. The computational drag polar matched the experimental results for a lift coefficient above 0.1 despite some mismatch in the predicted lift-curve slope.

Biomechanical Model for Computing Deformations for Whole-Body Image Registration: A Meshless Approach

PubMed Central

Li, Mao; Miller, Karol; Joldes, Grand Roman; Kikinis, Ron; Wittek, Adam

2016-01-01

Patient-specific biomechanical models have been advocated as a tool for predicting deformations of soft body organs/tissue for medical image registration (aligning two sets of images) when differences between the images are large. However, complex and irregular geometry of the body organs makes generation of patient-specific biomechanical models very time consuming. Meshless discretisation has been proposed to solve this challenge. However, applications so far have been limited to 2-D models and computing single organ deformations. In this study, 3-D comprehensive patient-specific non-linear biomechanical models implemented using Meshless Total Lagrangian Explicit Dynamics (MTLED) algorithms are applied to predict a 3-D deformation field for whole-body image registration. Unlike a conventional approach which requires dividing (segmenting) the image into non-overlapping constituents representing different organs/tissues, the mechanical properties are assigned using the Fuzzy C-Means (FCM) algorithm without the image segmentation. Verification indicates that the deformations predicted using the proposed meshless approach are for practical purposes the same as those obtained using the previously validated finite element models. To quantitatively evaluate the accuracy of the predicted deformations, we determined the spatial misalignment between the registered (i.e. source images warped using the predicted deformations) and target images by computing the edge-based Hausdorff distance. The Hausdorff distance-based evaluation determines that our meshless models led to successful registration of the vast majority of the image features. PMID:26791945

Modeling The Shock Initiation of PBX-9501 in ALE3D

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

Leininger, L; Springer, H K; Mace, J

The SMIS (Specific Munitions Impact Scenario) experimental series performed at Los Alamos National Laboratory has determined the 3-dimensional shock initiation behavior of the HMX-based heterogeneous high explosive, PBX 9501. A series of finite element impact calculations have been performed in the ALE3D [1] hydrodynamic code and compared to the SMIS results to validate the code predictions. The SMIS tests use a powder gun to shoot scaled NATO standard fragments at a cylinder of PBX 9501, which has a PMMA case and a steel impact cover. The SMIS real-world shot scenario creates a unique test-bed because many of the fragments arrivemore » at the impact plate off-center and at an angle of impact. The goal of this model validation experiments is to demonstrate the predictive capability of the Tarver-Lee Ignition and Growth (I&G) reactive flow model [2] in this fully 3-dimensional regime of Shock to Detonation Transition (SDT). The 3-dimensional Arbitrary Lagrange Eulerian hydrodynamic model in ALE3D applies the Ignition and Growth (I&G) reactive flow model with PBX 9501 parameters derived from historical 1-dimensional experimental data. The model includes the off-center and angle of impact variations seen in the experiments. Qualitatively, the ALE3D I&G calculations accurately reproduce the 'Go/No-Go' threshold of the Shock to Detonation Transition (SDT) reaction in the explosive, as well as the case expansion recorded by a high-speed optical camera. Quantitatively, the calculations show good agreement with the shock time of arrival at internal and external diagnostic pins. This exercise demonstrates the utility of the Ignition and Growth model applied in a predictive fashion for the response of heterogeneous high explosives in the SDT regime.« less

CLUMP-3D: Testing ΛCDM with Galaxy Cluster Shapes

NASA Astrophysics Data System (ADS)

Sereno, Mauro; Umetsu, Keiichi; Ettori, Stefano; Sayers, Jack; Chiu, I.-Non; Meneghetti, Massimo; Vega-Ferrero, Jesús; Zitrin, Adi

2018-06-01

The ΛCDM model of structure formation makes strong predictions on the concentration and shape of dark matter (DM) halos, which are determined by mass accretion processes. Comparison between predicted shapes and observations provides a geometric test of the ΛCDM model. Accurate and precise measurements needs a full three-dimensional (3D) analysis of the cluster mass distribution. We accomplish this with a multi-probe 3D analysis of the X-ray regular Cluster Lensing and Supernova survey with Hubble (CLASH) clusters combining strong and weak lensing, X-ray photometry and spectroscopy, and the Sunyaev–Zel’dovich effect (SZe). The cluster shapes and concentrations are consistent with ΛCDM predictions. The CLASH clusters are randomly oriented, as expected given the sample selection criteria. Shapes agree with numerical results for DM-only halos, which hints at baryonic physics being less effective in making halos rounder.

Computational Simulation of Thermal and Spattering Phenomena and Microstructure in Selective Laser Melting of Inconel 625

NASA Astrophysics Data System (ADS)

Özel, Tuğrul; Arısoy, Yiğit M.; Criales, Luis E.

Computational modelling of Laser Powder Bed Fusion (L-PBF) processes such as Selective laser Melting (SLM) can reveal information that is hard to obtain or unobtainable by in-situ experimental measurements. A 3D thermal field that is not visible by the thermal camera can be obtained by solving the 3D heat transfer problem. Furthermore, microstructural modelling can be used to predict the quality and mechanical properties of the product. In this paper, a nonlinear 3D Finite Element Method based computational code is developed to simulate the SLM process with different process parameters such as laser power and scan velocity. The code is further improved by utilizing an in-situ thermal camera recording to predict spattering which is in turn included as a stochastic heat loss. Then, thermal gradients extracted from the simulations applied to predict growth directions in the resulting microstructure.

The 3-D CFD modeling of gas turbine combustor-integral bleed flow interaction

NASA Technical Reports Server (NTRS)

Chen, D. Y.; Reynolds, R. S.

1993-01-01

An advanced 3-D Computational Fluid Dynamics (CFD) model was developed to analyze the flow interaction between a gas turbine combustor and an integral bleed plenum. In this model, the elliptic governing equations of continuity, momentum and the k-e turbulence model were solved on a boundary-fitted, curvilinear, orthogonal grid system. The model was first validated against test data from public literature and then applied to a gas turbine combustor with integral bleed. The model predictions agreed well with data from combustor rig testing. The model predictions also indicated strong flow interaction between the combustor and the integral bleed. Integral bleed flow distribution was found to have a great effect on the pressure distribution around the gas turbine combustor.

Computer-aided design, synthesis and biological assay of p-methylsulfonamido phenylethylamine analogues.

PubMed

Liu, H; Ji, M; Jiang, H; Liu, L; Hua, W; Chen, K; Ji, R

2000-10-02

Class III antiarrhythmic agents selectively delay the effective refractory period (ERP) and increase the transmembrance action potential duration (APD). Based on our previous studies, a set of 17 methylsulfonamido phenylethylamine analogues were investigated by 3D-QSAR techniques of CoMFA and CoMSIA. The 3D-QSAR models proved a good predictive ability, and could describe the steric, electrostatic and hydrophobic requirements for recognition forces of the receptor site. According to the clues provided by this 3D-QSAR analysis, we designed and synthesized a series of new analogues of methanesulfonamido phenylethylamine (VIa-i). Pharmacological assay indicated that the effective concentrations of delaying the functional refractory period (FRP) 10ms of these new compounds have a good correlation with the 3D-QSAR predicted values. It is remarkable that the maximal percent change of delaying FRP in microM of compound VIc is much higher than that of dofetilide. The results showed that the 3D-QSAR models are reliable.

Analysis of the Impact of Realistic Wind Size Parameter on the Delft3D Model

NASA Astrophysics Data System (ADS)

Washington, M. H.; Kumar, S.

2017-12-01

The wind size parameter, which is the distance from the center of the storm to the location of the maximum winds, is currently a constant in the Delft3D model. As a result, the Delft3D model's output prediction of the water levels during a storm surge are inaccurate compared to the observed data. To address these issues, an algorithm to calculate a realistic wind size parameter for a given hurricane was designed and implemented using the observed water-level data for Hurricane Matthew. A performance evaluation experiment was conducted to demonstrate the accuracy of the model's prediction of water levels using the realistic wind size input parameter compared to the default constant wind size parameter for Hurricane Matthew, with the water level data observed from October 4th, 2016 to October 9th, 2016 from National Oceanic and Atmospheric Administration (NOAA) as a baseline. The experimental results demonstrate that the Delft3D water level output for the realistic wind size parameter, compared to the default constant size parameter, matches more accurately with the NOAA reference water level data.

Simulations of Quantum Dot Growth on Semiconductor Surfaces: Morphological Design of Sensor Concepts

DTIC Science & Technology

2008-12-01

size equalization can be clearly illustrated during the growth process. In this work we develop a fast multiscale 3D kinetic Monte Carlo ( KMC ) QD...model will provide an attractive means for producing predictably ordered nanostructures. MODEL DESCRIPTION The 3D layer-by-layer KMC growth model...Voter, 2001) and KMC simulation experience (Pan et al., 2004; Pan et al., 2006; Meixner et al, 2003) in 2D, we therefore propose the following simple

A neural network model of three-dimensional dynamic electron density in the inner magnetosphere

NASA Astrophysics Data System (ADS)

Chu, X.; Bortnik, J.; Li, W.; Ma, Q.; Denton, R.; Yue, C.; Angelopoulos, V.; Thorne, R. M.; Darrouzet, F.; Ozhogin, P.; Kletzing, C. A.; Wang, Y.; Menietti, J.

2017-09-01

A plasma density model of the inner magnetosphere is important for a variety of applications including the study of wave-particle interactions, and wave excitation and propagation. Previous empirical models have been developed under many limiting assumptions and do not resolve short-term variations, which are especially important during storms. We present a three-dimensional dynamic electron density (DEN3D) model developed using a feedforward neural network with electron densities obtained from four satellite missions. The DEN3D model takes spacecraft location and time series of solar and geomagnetic indices (F10.7, SYM-H, and AL) as inputs. It can reproduce the observed density with a correlation coefficient of 0.95 and predict test data set with error less than a factor of 2. Its predictive ability on out-of-sample data is tested on field-aligned density profiles from the IMAGE satellite. DEN3D's predictive ability provides unprecedented opportunities to gain insight into the 3-D behavior of the inner magnetospheric plasma density at any time and location. As an example, we apply DEN3D to a storm that occurred on 1 June 2013. It successfully reproduces various well-known dynamic features in three dimensions, such as plasmaspheric erosion and recovery, as well as plume formation. Storm time long-term density variations are consistent with expectations; short-term variations appear to be modulated by substorm activity or enhanced convection, an effect that requires further study together with multispacecraft in situ or imaging measurements. Investigating plasmaspheric refilling with the model, we find that it is not monotonic in time and is more complex than expected from previous studies, deserving further attention.

Receptor-based 3D-QSAR in Drug Design: Methods and Applications in Kinase Studies.

PubMed

Fang, Cheng; Xiao, Zhiyan

2016-01-01

Receptor-based 3D-QSAR strategy represents a superior integration of structure-based drug design (SBDD) and three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis. It combines the accurate prediction of ligand poses by the SBDD approach with the good predictability and interpretability of statistical models derived from the 3D-QSAR approach. Extensive efforts have been devoted to the development of receptor-based 3D-QSAR methods and two alternative approaches have been exploited. One associates with computing the binding interactions between a receptor and a ligand to generate structure-based descriptors for QSAR analyses. The other concerns the application of various docking protocols to generate optimal ligand poses so as to provide reliable molecular alignments for the conventional 3D-QSAR operations. This review highlights new concepts and methodologies recently developed in the field of receptorbased 3D-QSAR, and in particular, covers its application in kinase studies.

QSAR models for thiophene and imidazopyridine derivatives inhibitors of the Polo-Like Kinase 1.

PubMed

Comelli, Nieves C; Duchowicz, Pablo R; Castro, Eduardo A

2014-10-01

The inhibitory activity of 103 thiophene and 33 imidazopyridine derivatives against Polo-Like Kinase 1 (PLK1) expressed as pIC50 (-logIC50) was predicted by QSAR modeling. Multivariate linear regression (MLR) was employed to model the relationship between 0D and 3D molecular descriptors and biological activities of molecules using the replacement method (MR) as variable selection tool. The 136 compounds were separated into several training and test sets. Two splitting approaches, distribution of biological data and structural diversity, and the statistical experimental design procedure D-optimal distance were applied to the dataset. The significance of the training set models was confirmed by statistically higher values of the internal leave one out cross-validated coefficient of determination (Q2) and external predictive coefficient of determination for the test set (Rtest2). The model developed from a training set, obtained with the D-optimal distance protocol and using 3D descriptor space along with activity values, separated chemical features that allowed to distinguish high and low pIC50 values reasonably well. Then, we verified that such model was sufficient to reliably and accurately predict the activity of external diverse structures. The model robustness was properly characterized by means of standard procedures and their applicability domain (AD) was analyzed by leverage method. Copyright © 2014 Elsevier B.V. All rights reserved.

A theoretical and computational study of lithium-ion battery thermal management for electric vehicles using heat pipes

NASA Astrophysics Data System (ADS)

Greco, Angelo; Cao, Dongpu; Jiang, Xi; Yang, Hong

2014-07-01

A simplified one-dimensional transient computational model of a prismatic lithium-ion battery cell is developed using thermal circuit approach in conjunction with the thermal model of the heat pipe. The proposed model is compared to an analytical solution based on variable separation as well as three-dimensional (3D) computational fluid dynamics (CFD) simulations. The three approaches, i.e. the 1D computational model, analytical solution, and 3D CFD simulations, yielded nearly identical results for the thermal behaviours. Therefore the 1D model is considered to be sufficient to predict the temperature distribution of lithium-ion battery thermal management using heat pipes. Moreover, a maximum temperature of 27.6 °C was predicted for the design of the heat pipe setup in a distributed configuration, while a maximum temperature of 51.5 °C was predicted when forced convection was applied to the same configuration. The higher surface contact of the heat pipes allows a better cooling management compared to forced convection cooling. Accordingly, heat pipes can be used to achieve effective thermal management of a battery pack with confined surface areas.

Evaluation and development of satellite inferences of convective storm intensity using combined case study analysis and thunderstorm model simulations

NASA Technical Reports Server (NTRS)

Cotton, W. R.; Tripoli, G. J.

1980-01-01

Major research accomplishments which were achieved during the first year of the grant are summarized. The research concentrated in the following areas: (1) an examination of observational requirements for predicting convective storm development and intensity as suggested by recent numerical experiments; (2) interpretation of recent 3D numerical experiments with regard to the relationship between overshooting tops and surface wind gusts; (3) the development of software for emulating satellite-inferred cloud properties using 3D cloud model predicted data; and (4) the development of a conceptual/semi-quantitative model of eastward propagating, mesoscale convective complexes forming to the lee of the Rocky Mountains.

Receptor-based 3D QSAR analysis of estrogen receptor ligands - merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods

NASA Astrophysics Data System (ADS)

Sippl, Wolfgang

2000-08-01

One of the major challenges in computational approaches to drug design is the accurate prediction of binding affinity of biomolecules. In the present study several prediction methods for a published set of estrogen receptor ligands are investigated and compared. The binding modes of 30 ligands were determined using the docking program AutoDock and were compared with available X-ray structures of estrogen receptor-ligand complexes. On the basis of the docking results an interaction energy-based model, which uses the information of the whole ligand-receptor complex, was generated. Several parameters were modified in order to analyze their influence onto the correlation between binding affinities and calculated ligand-receptor interaction energies. The highest correlation coefficient ( r 2 = 0.617, q 2 LOO = 0.570) was obtained considering protein flexibility during the interaction energy evaluation. The second prediction method uses a combination of receptor-based and 3D quantitative structure-activity relationships (3D QSAR) methods. The ligand alignment obtained from the docking simulations was taken as basis for a comparative field analysis applying the GRID/GOLPE program. Using the interaction field derived with a water probe and applying the smart region definition (SRD) variable selection, a significant and robust model was obtained ( r 2 = 0.991, q 2 LOO = 0.921). The predictive ability of the established model was further evaluated by using a test set of six additional compounds. The comparison with the generated interaction energy-based model and with a traditional CoMFA model obtained using a ligand-based alignment ( r 2 = 0.951, q 2 LOO = 0.796) indicates that the combination of receptor-based and 3D QSAR methods is able to improve the quality of the underlying model.

Coupled 2D-3D finite element method for analysis of a skin panel with a discontinuous stiffener

NASA Technical Reports Server (NTRS)

Wang, J. T.; Lotts, C. G.; Davis, D. D., Jr.; Krishnamurthy, T.

1992-01-01

This paper describes a computationally efficient analysis method which was used to predict detailed stress states in a typical composite compression panel with a discontinuous hat stiffener. A global-local approach was used. The global model incorporated both 2D shell and 3D brick elements connected by newly developed transition elements. Most of the panel was modeled with 2D elements, while 3D elements were employed to model the stiffener flange and the adjacent skin. Both linear and geometrically nonlinear analyses were performed on the global model. The effect of geometric nonlinearity induced by the eccentric load path due to the discontinuous hat stiffener was significant. The local model used a fine mesh of 3D brick elements to model the region at the end of the stiffener. Boundary conditions of the local 3D model were obtained by spline interpolation of the nodal displacements from the global analysis. Detailed in-plane and through-the-thickness stresses were calculated in the flange-skin interface near the end of the stiffener.

De novo prediction of human chromosome structures: Epigenetic marking patterns encode genome architecture.

PubMed

Di Pierro, Michele; Cheng, Ryan R; Lieberman Aiden, Erez; Wolynes, Peter G; Onuchic, José N

2017-11-14

Inside the cell nucleus, genomes fold into organized structures that are characteristic of cell type. Here, we show that this chromatin architecture can be predicted de novo using epigenetic data derived from chromatin immunoprecipitation-sequencing (ChIP-Seq). We exploit the idea that chromosomes encode a 1D sequence of chromatin structural types. Interactions between these chromatin types determine the 3D structural ensemble of chromosomes through a process similar to phase separation. First, a neural network is used to infer the relation between the epigenetic marks present at a locus, as assayed by ChIP-Seq, and the genomic compartment in which those loci reside, as measured by DNA-DNA proximity ligation (Hi-C). Next, types inferred from this neural network are used as an input to an energy landscape model for chromatin organization [Minimal Chromatin Model (MiChroM)] to generate an ensemble of 3D chromosome conformations at a resolution of 50 kilobases (kb). After training the model, dubbed Maximum Entropy Genomic Annotation from Biomarkers Associated to Structural Ensembles (MEGABASE), on odd-numbered chromosomes, we predict the sequences of chromatin types and the subsequent 3D conformational ensembles for the even chromosomes. We validate these structural ensembles by using ChIP-Seq tracks alone to predict Hi-C maps, as well as distances measured using 3D fluorescence in situ hybridization (FISH) experiments. Both sets of experiments support the hypothesis of phase separation being the driving process behind compartmentalization. These findings strongly suggest that epigenetic marking patterns encode sufficient information to determine the global architecture of chromosomes and that de novo structure prediction for whole genomes may be increasingly possible. Copyright © 2017 the Author(s). Published by PNAS.

Modification of polychlorinated phenols and evaluation of their toxicity, biodegradation and bioconcentration using three-dimensional quantitative structure-activity relationship models.

PubMed

Tong, Lidan; Guo, Lixin; Lv, Xiaojun; Li, Yu

2017-01-01

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were established by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Experimental toxicity data in Poecilia reticulata (pLC 50 ) and physico-chemical properties for 12 polychlorinated phenols were used as dependent and as independent variables, respectively. Among the 12 polychlorinated phenols, nine were randomly selected and used as a training set to construct the 3D-QSAR models through the SYBYL-X software to predict the pLC 50 values of the remaining 8 polychlorinated phenols congeners, and the other three polychlorinated phenols were used as a test set to evaluate the 3D-QSAR models (the training set and test set were arranged randomly, shuffled 60 times). Pentachlorophenol (PCP), which is the most toxic among the 20 polychlorinated phenols used in this experiment, was selected as an example for modification using contour maps produced using the established 3D-QSAR models. The aim was to decrease its toxicity and bioconcentration, increase its biodegradation, and maintain or better its effectiveness as a pesticide. The 3D-QSAR models were robust and had good predictive abilities with cross-validation correlation coefficients (q 2 ) of 0.858-0.992 (>0.5), correlation coefficients (r 2 ) of 0.966-1.000 (>0.9), and standard errors of prediction (SEP) of 0.004-0.159. CoMFA showed that the toxicity of the polychlorinated phenols arose mainly from electrostatic (42.7-66.7%) and steric (33.3-7.3%) contributions. By comparison, CoMSIA showed that the toxicity of polychlorinated phenols was dominated by electrostatic (57.5-76.9%) and hydrophobic (19.8-25.7%) contributions, with lesser contributions from the steric (0.7-1.0%) hydrogen bond donor (0.1-20.3%), and hydrogen bond acceptor (0-0.9%). 3D-QSAR electrostatic contour maps were used to modify PCP and design 11 new compounds with lower toxicity. The effectiveness of each of these molecules as a pesticide was verified using a 3D-QSAR model for polychlorinated phenol toxicity against Tetrahymena pyriformis. Four of these compounds, with -Br, -I, -OH and -NH 2 groups in place of chlorine at the 3-position on PCP, were all at least as effective as PCP against T. Pyriformis. The first-order rate constants (K b ) of these four compounds were predicted using a 3D-QSAR model for polychlorinated phenol degradation, which showed they were more biodegradable than PCP. Furthermore, a 3D-QSAR model for polychlorinated phenols bioconcentration in fish (containing Poecilia reticulata, Oncorhynchus mykiss, Pimephales promelas and Oryzias latipes) showed that there was no significant difference between the bioconcentration factors of the four new compounds and that of PCP. The results obtained are hoped to provide a new route for lowering the POPs characteristics of those polychlorinated phenol homologues and derivatives in use. Copyright © 2016 Elsevier Inc. All rights reserved.

D Visualization of Volcanic Ash Dispersion Prediction with Spatial Information Open Platform in Korea

NASA Astrophysics Data System (ADS)

Youn, J.; Kim, T.

2016-06-01

Visualization of disaster dispersion prediction enables decision makers and civilian to prepare disaster and to reduce the damage by showing the realistic simulation results. With advances of GIS technology and the theory of volcanic disaster prediction algorithm, the predicted disaster dispersions are displayed in spatial information. However, most of volcanic ash dispersion predictions are displayed in 2D. 2D visualization has a limitation to understand the realistic dispersion prediction since its height could be presented only by colour. Especially for volcanic ash, 3D visualization of dispersion prediction is essential since it could bring out big aircraft accident. In this paper, we deals with 3D visualization techniques of volcanic ash dispersion prediction with spatial information open platform in Korea. First, time-series volcanic ash 3D position and concentrations are calculated with WRF (Weather Research and Forecasting) model and Modified Fall3D algorithm. For 3D visualization, we propose three techniques; those are 'Cube in the air', 'Cube in the cube', and 'Semi-transparent plane in the air' methods. In the 'Cube in the Air', which locates the semitransparent cubes having different color depends on its particle concentration. Big cube is not realistic when it is zoomed. Therefore, cube is divided into small cube with Octree algorithm. That is 'Cube in the Cube' algorithm. For more realistic visualization, we apply 'Semi-transparent Volcanic Ash Plane' which shows the ash as fog. The results are displayed in the 'V-world' which is a spatial information open platform implemented by Korean government. Proposed techniques were adopted in Volcanic Disaster Response System implemented by Korean Ministry of Public Safety and Security.

Docking Based 3D-QSAR Study of Tricyclic Guanidine Analogues of Batzelladine K as anti-malarial agents

NASA Astrophysics Data System (ADS)

Ahmed, Nafees; Anwar, Sirajudheen; Thet Htar, Thet

2017-06-01

The Plasmodium falciparum Lactate Dehydrogenase enzyme (PfLDH) catalyzes inter-conversion of pyruvate to lactate during glycolysis producing the energy required for parasitic growth. The PfLDH has been studied as a potential molecular target for development of anti-malarial agents. In an attempt to find the potent inhibitor of PfLDH, we have used Discovery studio to perform molecular docking in the active binding pocket of PfLDH by CDOCKER, followed by three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of tricyclic guanidine batzelladine compounds, which were previously synthesized in our laboratory. Docking studies showed that there is a very strong correlation between in silico and in vitro results. Based on docking results, a highly predictive 3D-QSAR model was developed with q2 of 0.516. The model has predicted r2 of 0.91 showing that predicted IC50 values are in good agreement with experimental IC50 values. The results obtained from this study revealed the developed model can be used to design new anti-malarial compounds based on tricyclic guanidine derivatives and to predict activities of new inhibitors.

Docking Based 3D-QSAR Study of Tricyclic Guanidine Analogues of Batzelladine K As Anti-Malarial Agents.

PubMed

Ahmed, Nafees; Anwar, Sirajudheen; Thet Htar, Thet

2017-01-01

The Plasmodium falciparum Lactate Dehydrogenase enzyme ( Pf LDH) catalyzes inter-conversion of pyruvate to lactate during glycolysis producing the energy required for parasitic growth. The Pf LDH has been studied as a potential molecular target for development of anti-malarial agents. In an attempt to find the potent inhibitor of Pf LDH, we have used Discovery studio to perform molecular docking in the active binding pocket of Pf LDH by CDOCKER, followed by three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of tricyclic guanidine batzelladine compounds, which were previously synthesized in our laboratory. Docking studies showed that there is a very strong correlation between in silico and in vitro results. Based on docking results, a highly predictive 3D-QSAR model was developed with q 2 of 0.516. The model has predicted r 2 of 0.91 showing that predicted IC 50 values are in good agreement with experimental IC 50 values. The results obtained from this study revealed the developed model can be used to design new anti-malarial compounds based on tricyclic guanidine derivatives and to predict activities of new inhibitors.

Docking Based 3D-QSAR Study of Tricyclic Guanidine Analogues of Batzelladine K As Anti-Malarial Agents

PubMed Central

Ahmed, Nafees; Anwar, Sirajudheen; Thet Htar, Thet

2017-01-01

The Plasmodium falciparum Lactate Dehydrogenase enzyme (PfLDH) catalyzes inter-conversion of pyruvate to lactate during glycolysis producing the energy required for parasitic growth. The PfLDH has been studied as a potential molecular target for development of anti-malarial agents. In an attempt to find the potent inhibitor of PfLDH, we have used Discovery studio to perform molecular docking in the active binding pocket of PfLDH by CDOCKER, followed by three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of tricyclic guanidine batzelladine compounds, which were previously synthesized in our laboratory. Docking studies showed that there is a very strong correlation between in silico and in vitro results. Based on docking results, a highly predictive 3D-QSAR model was developed with q2 of 0.516. The model has predicted r2 of 0.91 showing that predicted IC50 values are in good agreement with experimental IC50 values. The results obtained from this study revealed the developed model can be used to design new anti-malarial compounds based on tricyclic guanidine derivatives and to predict activities of new inhibitors. PMID:28664157

VP-Nets : Efficient automatic localization of key brain structures in 3D fetal neurosonography.

PubMed

Huang, Ruobing; Xie, Weidi; Alison Noble, J

2018-04-23

Three-dimensional (3D) fetal neurosonography is used clinically to detect cerebral abnormalities and to assess growth in the developing brain. However, manual identification of key brain structures in 3D ultrasound images requires expertise to perform and even then is tedious. Inspired by how sonographers view and interact with volumes during real-time clinical scanning, we propose an efficient automatic method to simultaneously localize multiple brain structures in 3D fetal neurosonography. The proposed View-based Projection Networks (VP-Nets), uses three view-based Convolutional Neural Networks (CNNs), to simplify 3D localizations by directly predicting 2D projections of the key structures onto three anatomical views. While designed for efficient use of data and GPU memory, the proposed VP-Nets allows for full-resolution 3D prediction. We investigated parameters that influence the performance of VP-Nets, e.g. depth and number of feature channels. Moreover, we demonstrate that the model can pinpoint the structure in 3D space by visualizing the trained VP-Nets, despite only 2D supervision being provided for a single stream during training. For comparison, we implemented two other baseline solutions based on Random Forest and 3D U-Nets. In the reported experiments, VP-Nets consistently outperformed other methods on localization. To test the importance of loss function, two identical models are trained with binary corss-entropy and dice coefficient loss respectively. Our best VP-Net model achieved prediction center deviation: 1.8 ± 1.4 mm, size difference: 1.9 ± 1.5 mm, and 3D Intersection Over Union (IOU): 63.2 ± 14.7% when compared to the ground truth. To make the whole pipeline intervention free, we also implement a skull-stripping tool using 3D CNN, which achieves high segmentation accuracy. As a result, the proposed processing pipeline takes a raw ultrasound brain image as input, and output a skull-stripped image with five detected key brain structures. Copyright © 2018 Elsevier B.V. All rights reserved.

Specification and Prediction of the Radiation Environment Using Data Assimilative VERB code

NASA Astrophysics Data System (ADS)

Shprits, Yuri; Kellerman, Adam

2016-07-01

We discuss how data assimilation can be used for the reconstruction of long-term evolution, bench-marking of the physics based codes and used to improve the now-casting and focusing of the radiation belts and ring current. We also discuss advanced data assimilation methods such as parameter estimation and smoothing. We present a number of data assimilation applications using the VERB 3D code. The 3D data assimilative VERB allows us to blend together data from GOES, RBSP A and RBSP B. 1) Model with data assimilation allows us to propagate data to different pitch angles, energies, and L-shells and blends them together with the physics-based VERB code in an optimal way. We illustrate how to use this capability for the analysis of the previous events and for obtaining a global and statistical view of the system. 2) The model predictions strongly depend on initial conditions that are set up for the model. Therefore, the model is as good as the initial conditions that it uses. To produce the best possible initial conditions, data from different sources (GOES, RBSP A, B, our empirical model predictions based on ACE) are all blended together in an optimal way by means of data assimilation, as described above. The resulting initial conditions do not have gaps. This allows us to make more accurate predictions. Real-time prediction framework operating on our website, based on GOES, RBSP A, B and ACE data, and 3D VERB, is presented and discussed.

Accuracy of 1D microvascular flow models in the limit of low Reynolds numbers.

PubMed

Pindera, Maciej Z; Ding, Hui; Athavale, Mahesh M; Chen, Zhijian

2009-05-01

We describe results of numerical simulations of steady flows in tubes with branch bifurcations using fully 3D and reduced 1D geometries. The intent is to delineate the range of validity of reduced models used for simulations of flows in microcapillary networks, as a function of the flow Reynolds number Re. Results from model problems indicate that for Re less than 1 and possibly as high as 10, vasculatures may be represented by strictly 1D Poiseuille flow geometries with flow variation in the axial dimensions only. In that range flow rate predictions in the different branches generated by 1D and 3D models differ by a constant factor, independent of Re. When the cross-sectional areas of the branches are constant these differences are generally small and appear to stem from an uncertainty of how the individual branch lengths are defined. This uncertainty can be accounted for by a simple geometrical correction. For non-constant cross-sections the differences can be much more significant. If additional corrections for the presence of branch junctions and flow area variations are not taken into account in 1D models of complex vasculatures, the resultant flow predictions should be interpreted with caution.

Comparison of mid-Pliocene climate predictions produced by the HadAM3 and GCMAM3 General Circulation Models

USGS Publications Warehouse

Haywood, A.M.; Chandler, M.A.; Valdes, P.J.; Salzmann, U.; Lunt, D.J.; Dowsett, H.J.

2009-01-01

The mid-Pliocene warm period (ca. 3 to 3.3??million years ago) has become an important interval of time for palaeoclimate modelling exercises, with a large number of studies published during the last decade. However, there has been no attempt to assess the degree of model dependency of the results obtained. Here we present an initial comparison of mid-Pliocene climatologies produced by the Goddard Institute for Space Studies and Hadley Centre for Climate Prediction and Research atmosphere-only General Circulation Models (GCMAM3 and HadAM3). Whilst both models are consistent in the simulation of broad-scale differences in mid-Pliocene surface air temperature and total precipitation rates, significant variation is noted on regional and local scales. There are also significant differences in the model predictions of total cloud cover. A terrestrial data/model comparison, facilitated by the BIOME 4 model and a new data set of Piacenzian Stage land cover [Salzmann, U., Haywood, A.M., Lunt, D.J., Valdes, P.J., Hill, D.J., (2008). A new global biome reconstruction and data model comparison for the Middle Pliocene. Global Ecology and Biogeography 17, 432-447, doi:10.1111/j.1466-8238.2007.00381.x] and combined with the use of Kappa statistics, indicates that HadAM3-based biome predictions provide a closer fit to proxy data in the mid to high-latitudes. However, GCMAM3-based biomes in the tropics provide the closest fit to proxy data. ?? 2008 Elsevier B.V.

UT simulation using a fully automated 3D hybrid model: Application to planar backwall breaking defects inspection

NASA Astrophysics Data System (ADS)

Imperiale, Alexandre; Chatillon, Sylvain; Darmon, Michel; Leymarie, Nicolas; Demaldent, Edouard

2018-04-01

The high frequency models gathered in the CIVA software allow fast computations and provide satisfactory quantitative predictions in a wide range of situations. However, the domain of validity of these models is limited since they do not accurately predict the ultrasound response in configurations involving subwavelength complex phenomena. In addition, when modelling backwall breaking defects inspection, an important challenge remains to capture the propagation of the creeping waves that are generated at the critical angle. Hybrid models combining numerical and asymptotic methods have already been shown to be an effective strategy to overcome these limitations in 2D [1]. However, 3D simulations remain a crucial issue for industrial applications because of the computational cost of the numerical solver. A dedicated three dimensional high order finite element model combined with a domain decomposition method has been recently proposed to tackle 3D limitations [2]. In this communication, we will focus on the specific case of planar backwall breaking defects, with an adapted coupling strategy in order to efficiently model the propagation of creeping waves. Numerical and experimental validations will be proposed on various configurations.

Incorporating drug delivery into an imaging-driven, mechanics-coupled reaction diffusion model for predicting the response of breast cancer to neoadjuvant chemotherapy: theory and preliminary clinical results

NASA Astrophysics Data System (ADS)

Jarrett, Angela M.; Hormuth, David A.; Barnes, Stephanie L.; Feng, Xinzeng; Huang, Wei; Yankeelov, Thomas E.

2018-05-01

Clinical methods for assessing tumor response to therapy are largely rudimentary, monitoring only temporal changes in tumor size. Our goal is to predict the response of breast tumors to therapy using a mathematical model that utilizes magnetic resonance imaging (MRI) data obtained non-invasively from individual patients. We extended a previously established, mechanically coupled, reaction-diffusion model for predicting tumor response initialized with patient-specific diffusion weighted MRI (DW-MRI) data by including the effects of chemotherapy drug delivery, which is estimated using dynamic contrast-enhanced (DCE-) MRI data. The extended, drug incorporated, model is initialized using patient-specific DW-MRI and DCE-MRI data. Data sets from five breast cancer patients were used—obtained before, after one cycle, and at mid-point of neoadjuvant chemotherapy. The DCE-MRI data was used to estimate spatiotemporal variations in tumor perfusion with the extended Kety–Tofts model. The physiological parameters derived from DCE-MRI were used to model changes in delivery of therapy drugs within the tumor for incorporation in the extended model. We simulated the original model and the extended model in both 2D and 3D and compare the results for this five-patient cohort. Preliminary results show reductions in the error of model predicted tumor cellularity and size compared to the experimentally-measured results for the third MRI scan when therapy was incorporated. Comparing the two models for agreement between the predicted total cellularity and the calculated total cellularity (from the DW-MRI data) reveals an increased concordance correlation coefficient from 0.81 to 0.98 for the 2D analysis and 0.85 to 0.99 for the 3D analysis (p  <  0.01 for each) when the extended model was used in place of the original model. This study demonstrates the plausibility of using DCE-MRI data as a means to estimate drug delivery on a patient-specific basis in predictive models and represents a step toward the goal of achieving individualized prediction of tumor response to therapy.

Optimizing D'Amico risk groups in radical prostatectomy through the addition of magnetic resonance imaging data.

PubMed

Algarra, R; Zudaire, B; Tienza, A; Velis, J M; Rincón, A; Pascual, I; Zudaire, J

2014-11-01

To improve the predictive efficacy of the D'Amico risk classification system with magnetic resonance imaging (MRI) of the pelvis. We studied 729 patients from a series of 1310 radical prostatectomies for T1-T2 prostate cancer who underwent staging pelvic MRI. Each patient was classified with T2, T3a or T3b MRI, and N (+) patients were excluded. We identified the therapeutic factors that affected the biochemical progression-free survival (BPFS) time (prostate specific antigen [PSA] levels>0.4ng/mL) using a univariate and multivariate study with Cox models. We attempted to improve the predictive power of the D'Amico model (low risk: T1; Gleason 2-6; PSA levels<10ng/mL; intermediate risk: T2 or Gleason 7 or PSA levels 10-20ng/mL; high risk: T3 or Gleason 8-10 or PSA levels>20ng/mL). In the univariate study, the clinical factors that influenced BPFS were the following: Gleason 7 (HR: 1.7); Gleason 8-10 (HR: 2.9); T2 (HR: 1.6); PSA levels 10-20 (HR: 2); PSA levels>20 (HR: 4.3); D'Amico intermediate (HR: 2.1) and high (HR: 4.8) risk; T3a MRI (HR: 2.3) and T3b MRI (HR: 4.5). In the multivariate study, the only variables that affected BPFS were the following: D'Amico intermediate risk (HR: 2; 95% CI 1.2-3.3); D'Amico high risk (HR: 4.1; 95% CI 2.4-6.8); T3a MRI (HR: 1.9; 95% CI 1.2-2.9) and T3b MRI (HR: 3.9; 95% CI 2.5-6.1). Predictive model: Using the multivariate Cox models, we assessed the weight of each variable. A value of 1 was given to D'Amico low risk and T2 MRI; a value of 2 was given to D'Amico intermediate risk and T3a MRI and a value 3 was given to D'Amico high risk and T3b MRI. Each patient had a marker that varied between 2 and 6. The best model included 3 groups, as follows: 494 (67.7%) patients in group 1, with a score of 2-3 points (HR, 1), a BPFS of 86%±2% and 79%±2% at 5 and 10 years, respectively; 179 (24.6%) patients in group 2, with a score of 4 points (HR, 3), a BPFS of 60%±4% and 54%±5% at 5 and 10 years, respectively; and 56 (7.7%) patients in group 3, with a score of 5-6 points (HR, 9.3), a BPFS of 29%±8% and 19%±7% at 5 and 10 years, respectively. The median BPFS time was 1.5 years. MRI data significantly improves the predictive capacity of BPFS when using the D'Amico model data. Copyright © 2013 AEU. Published by Elsevier Espana. All rights reserved.

SRB-3D Solid Rocket Booster performance prediction program. Volume 1: Engineering description/users information manual

NASA Technical Reports Server (NTRS)

Winkler, J. C.

1976-01-01

The modified Solid Rocket Booster Performance Evaluation Model (SRB-3D) was developed as an extension to the internal ballistics module of the SRB-2 performance program. This manual contains the engineering description of SRB-3D which describes the approach used to develop the 3D concept and an explanation of the modifications which were necessary to implement these concepts.

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

Reedlunn, Benjamin

Room D was an in-situ, isothermal, underground experiment conducted at the Waste Isolation Pilot Plant between 1984 and 1991. The room was carefully instrumented to measure the horizontal and vertical closure immediately upon excavation and for several years thereafter. Early finite element simulations of salt creep around Room D under-predicted the vertical closure by 4.5×, causing investigators to explore a series of changes to the way Room D was modeled. Discrepancies between simulations and measurements were resolved through a series of adjustments to model parameters, which were openly acknowledged in published reports. Interest in Room D has been rekindled recentlymore » by the U.S./German Joint Project III and Project WEIMOS, which seek to improve the predictions of rock salt constitutive models. Joint Project participants calibrate their models solely against laboratory tests, and benchmark the models against underground experiments, such as room D. This report describes updating legacy Room D simulations to today’s computational standards by rectifying several numerical issues. Subsequently, the constitutive model used in previous modeling is recalibrated two different ways against a suite of new laboratory creep experiments on salt extracted from the repository horizon of the Waste Isolation Pilot Plant. Simulations with the new, laboratory-based, calibrations under-predict Room D vertical closure by 3.1×. A list of potential improvements is discussed.« less

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

Reedlunn, Benjamin

Room D was an in-situ, isothermal, underground experiment conducted at theWaste Isolation Pilot Plant between 1984 and 1991. The room was carefully instrumented to measure the horizontal and vertical closure immediately upon excavation and for several years thereafter. Early finite element simulations of salt creep around Room D under predicted the vertical closure by 4.5×, causing investigators to explore a series of changes to the way Room D was modeled. Discrepancies between simulations and measurements were resolved through a series of adjustments to model parameters, which were openly acknowledged in published reports. Interest in Room D has been rekindled recentlymore » by the U.S./German Joint Project III and Project WEIMOS, which seek to improve the predictions of rock salt constitutive models. Joint Project participants calibrate their models solely against laboratory tests, and benchmark the models against underground experiments, such as room D. This report describes updating legacy Room D simulations to today’s computational standards by rectifying several numerical issues. Subsequently, the constitutive model used in previous modeling is recalibrated two different ways against a suite of new laboratory creep experiments on salt extracted from the repository horizon of the Waste Isolation Pilot Plant. Simulations with the new, laboratory-based, calibrations under predict Room D vertical closure by 3.1×. A list of potential improvements is discussed.« less

Identification of potential influenza virus endonuclease inhibitors through virtual screening based on the 3D-QSAR model.

PubMed

Kim, J; Lee, C; Chong, Y

2009-01-01

Influenza endonucleases have appeared as an attractive target of antiviral therapy for influenza infection. With the purpose of designing a novel antiviral agent with enhanced biological activities against influenza endonuclease, a three-dimensional quantitative structure-activity relationships (3D-QSAR) model was generated based on 34 influenza endonuclease inhibitors. The comparative molecular similarity index analysis (CoMSIA) with a steric, electrostatic and hydrophobic (SEH) model showed the best correlative and predictive capability (q(2) = 0.763, r(2) = 0.969 and F = 174.785), which provided a pharmacophore composed of the electronegative moiety as well as the bulky hydrophobic group. The CoMSIA model was used as a pharmacophore query in the UNITY search of the ChemDiv compound library to give virtual active compounds. The 3D-QSAR model was then used to predict the activity of the selected compounds, which identified three compounds as the most likely inhibitor candidates.

Ligand Biological Activity Predictions Using Fingerprint-Based Artificial Neural Networks (FANN-QSAR)

PubMed Central

Myint, Kyaw Z.; Xie, Xiang-Qun

2015-01-01

This chapter focuses on the fingerprint-based artificial neural networks QSAR (FANN-QSAR) approach to predict biological activities of structurally diverse compounds. Three types of fingerprints, namely ECFP6, FP2, and MACCS, were used as inputs to train the FANN-QSAR models. The results were benchmarked against known 2D and 3D QSAR methods, and the derived models were used to predict cannabinoid (CB) ligand binding activities as a case study. In addition, the FANN-QSAR model was used as a virtual screening tool to search a large NCI compound database for lead cannabinoid compounds. We discovered several compounds with good CB2 binding affinities ranging from 6.70 nM to 3.75 μM. The studies proved that the FANN-QSAR method is a useful approach to predict bioactivities or properties of ligands and to find novel lead compounds for drug discovery research. PMID:25502380

A combined pharmacophore modeling, 3D-QSAR and molecular docking study of substituted bicyclo-[3.3.0]oct-2-enes as liver receptor homolog-1 (LRH-1) agonists

NASA Astrophysics Data System (ADS)

Lalit, Manisha; Gangwal, Rahul P.; Dhoke, Gaurao V.; Damre, Mangesh V.; Khandelwal, Kanchan; Sangamwar, Abhay T.

2013-10-01

A combined pharmacophore modelling, 3D-QSAR and molecular docking approach was employed to reveal structural and chemical features essential for the development of small molecules as LRH-1 agonists. The best HypoGen pharmacophore hypothesis (Hypo1) consists of one hydrogen-bond donor (HBD), two general hydrophobic (H), one hydrophobic aromatic (HYAr) and one hydrophobic aliphatic (HYA) feature. It has exhibited high correlation coefficient of 0.927, cost difference of 85.178 bit and low RMS value of 1.411. This pharmacophore hypothesis was cross-validated using test set, decoy set and Cat-Scramble methodology. Subsequently, validated pharmacophore hypothesis was used in the screening of small chemical databases. Further, 3D-QSAR models were developed based on the alignment obtained using substructure alignment. The best CoMFA and CoMSIA model has exhibited excellent rncv2 values of 0.991 and 0.987, and rcv2 values of 0.767 and 0.703, respectively. CoMFA predicted rpred2 of 0.87 and CoMSIA predicted rpred2 of 0.78 showed that the predicted values were in good agreement with the experimental values. Molecular docking analysis reveals that π-π interaction with His390 and hydrogen bond interaction with His390/Arg393 is essential for LRH-1 agonistic activity. The results from pharmacophore modelling, 3D-QSAR and molecular docking are complementary to each other and could serve as a powerful tool for the discovery of potent small molecules as LRH-1 agonists.

SPE-5 Ground-Motion Prediction at Far-Field Geophone and Accelerometer Array Sites and SPE-5 Moment and Corner-Frequency Prediction

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

Yang, Xiaoning; Patton, Howard John; Chen, Ting

2016-03-25

This report offers predictions for the SPE-5 ground-motion and accelerometer array sites. These predictions pertain to the waveform and spectral amplitude at certain geophone sites using Denny&Johnson source model and a source model derived from SPE data; waveform, peak velocity and peak acceleration at accelerometer sites using the SPE source model and the finite-difference simulation with LLNL 3D velocity model; and the SPE-5 moment and corner frequency.

Shape: A 3D Modeling Tool for Astrophysics.

PubMed

Steffen, Wolfgang; Koning, Nicholas; Wenger, Stephan; Morisset, Christophe; Magnor, Marcus

2011-04-01

We present a flexible interactive 3D morpho-kinematical modeling application for astrophysics. Compared to other systems, our application reduces the restrictions on the physical assumptions, data type, and amount that is required for a reconstruction of an object's morphology. It is one of the first publicly available tools to apply interactive graphics to astrophysical modeling. The tool allows astrophysicists to provide a priori knowledge about the object by interactively defining 3D structural elements. By direct comparison of model prediction with observational data, model parameters can then be automatically optimized to fit the observation. The tool has already been successfully used in a number of astrophysical research projects.

Vehicle Surveillance with a Generic, Adaptive, 3D Vehicle Model.

PubMed

Leotta, Matthew J; Mundy, Joseph L

2011-07-01

In automated surveillance, one is often interested in tracking road vehicles, measuring their shape in 3D world space, and determining vehicle classification. To address these tasks simultaneously, an effective approach is the constrained alignment of a prior model of 3D vehicle shape to images. Previous 3D vehicle models are either generic but overly simple or rigid and overly complex. Rigid models represent exactly one vehicle design, so a large collection is needed. A single generic model can deform to a wide variety of shapes, but those shapes have been far too primitive. This paper uses a generic 3D vehicle model that deforms to match a wide variety of passenger vehicles. It is adjustable in complexity between the two extremes. The model is aligned to images by predicting and matching image intensity edges. Novel algorithms are presented for fitting models to multiple still images and simultaneous tracking while estimating shape in video. Experiments compare the proposed model to simple generic models in accuracy and reliability of 3D shape recovery from images and tracking in video. Standard techniques for classification are also used to compare the models. The proposed model outperforms the existing simple models at each task.

Generation of 3D templates of active sites of proteins with rigid prosthetic groups.

PubMed

Nebel, Jean-Christophe

2006-05-15

With the increasing availability of protein structures, the generation of biologically meaningful 3D patterns from the simultaneous alignment of several protein structures is an exciting prospect: active sites could be better understood, protein functions and protein 3D structures could be predicted more accurately. Although patterns can already be generated at the fold and topological levels, no system produces high-resolution 3D patterns including atom and cavity positions. To address this challenge, our research focuses on generating patterns from proteins with rigid prosthetic groups. Since these groups are key elements of protein active sites, the generated 3D patterns are expected to be biologically meaningful. In this paper, we present a new approach which allows the generation of 3D patterns from proteins with rigid prosthetic groups. Using 237 protein chains representing proteins containing porphyrin rings, our method was validated by comparing 3D templates generated from homologues with the 3D structure of the proteins they model. Atom positions were predicted reliably: 93% of them had an accuracy of 1.00 A or less. Moreover, similar results were obtained regarding chemical group and cavity positions. Results also suggested our system could contribute to the validation of 3D protein models. Finally, a 3D template was generated for the active site of human cytochrome P450 CYP17, the 3D structure of which is unknown. Its analysis showed that it is biologically meaningful: our method detected the main patterns of the cytochrome P450 superfamily and the motifs linked to catalytic reactions. The 3D template also suggested the position of a residue, which could be involved in a hydrogen bond with CYP17 substrates and the shape and location of a cavity. Comparisons with independently generated 3D models comforted these hypotheses. Alignment software (Nestor3D) is available at http://www.kingston.ac.uk/~ku33185/Nestor3D.html

Validation of a Three-Dimensional Ablation and Thermal Response Simulation Code

NASA Technical Reports Server (NTRS)

Chen, Yih-Kanq; Milos, Frank S.; Gokcen, Tahir

2010-01-01

The 3dFIAT code simulates pyrolysis, ablation, and shape change of thermal protection materials and systems in three dimensions. The governing equations, which include energy conservation, a three-component decomposition model, and a surface energy balance, are solved with a moving grid system to simulate the shape change due to surface recession. This work is the first part of a code validation study for new capabilities that were added to 3dFIAT. These expanded capabilities include a multi-block moving grid system and an orthotropic thermal conductivity model. This paper focuses on conditions with minimal shape change in which the fluid/solid coupling is not necessary. Two groups of test cases of 3dFIAT analyses of Phenolic Impregnated Carbon Ablator in an arc-jet are presented. In the first group, axisymmetric iso-q shaped models are studied to check the accuracy of three-dimensional multi-block grid system. In the second group, similar models with various through-the-thickness conductivity directions are examined. In this group, the material thermal response is three-dimensional, because of the carbon fiber orientation. Predictions from 3dFIAT are presented and compared with arcjet test data. The 3dFIAT predictions agree very well with thermocouple data for both groups of test cases.

Consequences of Fluid Lag in Three-Dimensional Hydraulic Fractures

NASA Astrophysics Data System (ADS)

Advani (Deceased), S. H.; Lee, T. S.; Dean, R. H.; Pak, C. K.; Avasthi, J. M.

1997-04-01

Research investigations on three-dimensional (3-D) rectangular hydraulic fracture configurations with varying degrees of fluid lag are reported. This paper demonstrates that a 3-D fracture model coupled with fluid lag (a small region of reduced pressure) at the fracture tip can predict very large excess pressure measurements for hydraulic fracture processes. Predictions of fracture propagation based on critical stress intensity factors are extremely sensitive to the pressure profile at the tip of a propagating fracture. This strong sensitivity to the pressure profile at the tip of a hydraulic fracture is more strongly pronounced in 3-D models versus 2-D models because 3-D fractures are clamped at the top and bottom, and pressures in the 3-D fractures that are far removed from the fracture tip have little effect on the stress intensity factor at the fracture tip. This rationale for the excess pressure mechanism is in marked contrast to the crack tip process damage zone assumptions and attendant high rock fracture toughness value hypotheses advanced in the literature. A comparison with field data is presented to illustrate the proposed fracture fluid pressure sensitivity phenomenon. This paper does not attempt to calculate the length of the fluid lag region in a propagating fracture but instead attempts to show that the pressure profile at the tip of the propagating fracture plays a major role in fracture propagation, and this role is magnified in 3-D models. Int. J. Numer. Anal. Meth. Geomech., vol. 21, 229-240 (1997).

F-RAG: Generating Atomic Coordinates from RNA Graphs by Fragment Assembly.

PubMed

Jain, Swati; Schlick, Tamar

2017-11-24

Coarse-grained models represent attractive approaches to analyze and simulate ribonucleic acid (RNA) molecules, for example, for structure prediction and design, as they simplify the RNA structure to reduce the conformational search space. Our structure prediction protocol RAGTOP (RNA-As-Graphs Topology Prediction) represents RNA structures as tree graphs and samples graph topologies to produce candidate graphs. However, for a more detailed study and analysis, construction of atomic from coarse-grained models is required. Here we present our graph-based fragment assembly algorithm (F-RAG) to convert candidate three-dimensional (3D) tree graph models, produced by RAGTOP into atomic structures. We use our related RAG-3D utilities to partition graphs into subgraphs and search for structurally similar atomic fragments in a data set of RNA 3D structures. The fragments are edited and superimposed using common residues, full atomic models are scored using RAGTOP's knowledge-based potential, and geometries of top scoring models is optimized. To evaluate our models, we assess all-atom RMSDs and Interaction Network Fidelity (a measure of residue interactions) with respect to experimentally solved structures and compare our results to other fragment assembly programs. For a set of 50 RNA structures, we obtain atomic models with reasonable geometries and interactions, particularly good for RNAs containing junctions. Additional improvements to our protocol and databases are outlined. These results provide a good foundation for further work on RNA structure prediction and design applications. Copyright © 2017 Elsevier Ltd. All rights reserved.

Bayesian Estimation of Thermonuclear Reaction Rates for Deuterium+Deuterium Reactions

NASA Astrophysics Data System (ADS)

Gómez Iñesta, Á.; Iliadis, C.; Coc, A.

2017-11-01

The study of d+d reactions is of major interest since their reaction rates affect the predicted abundances of D, 3He, and 7Li. In particular, recent measurements of primordial D/H ratios call for reduced uncertainties in the theoretical abundances predicted by Big Bang nucleosynthesis (BBN). Different authors have studied reactions involved in BBN by incorporating new experimental data and a careful treatment of systematic and probabilistic uncertainties. To analyze the experimental data, Coc et al. used results of ab initio models for the theoretical calculation of the energy dependence of S-factors in conjunction with traditional statistical methods based on χ 2 minimization. Bayesian methods have now spread to many scientific fields and provide numerous advantages in data analysis. Astrophysical S-factors and reaction rates using Bayesian statistics were calculated by Iliadis et al. Here we present a similar analysis for two d+d reactions, d(d, n)3He and d(d, p)3H, that has been translated into a total decrease of the predicted D/H value by 0.16%.

Structural protein descriptors in 1-dimension and their sequence-based predictions.

PubMed

Kurgan, Lukasz; Disfani, Fatemeh Miri

2011-09-01

The last few decades observed an increasing interest in development and application of 1-dimensional (1D) descriptors of protein structure. These descriptors project 3D structural features onto 1D strings of residue-wise structural assignments. They cover a wide-range of structural aspects including conformation of the backbone, burying depth/solvent exposure and flexibility of residues, and inter-chain residue-residue contacts. We perform first-of-its-kind comprehensive comparative review of the existing 1D structural descriptors. We define, review and categorize ten structural descriptors and we also describe, summarize and contrast over eighty computational models that are used to predict these descriptors from the protein sequences. We show that the majority of the recent sequence-based predictors utilize machine learning models, with the most popular being neural networks, support vector machines, hidden Markov models, and support vector and linear regressions. These methods provide high-throughput predictions and most of them are accessible to a non-expert user via web servers and/or stand-alone software packages. We empirically evaluate several recent sequence-based predictors of secondary structure, disorder, and solvent accessibility descriptors using a benchmark set based on CASP8 targets. Our analysis shows that the secondary structure can be predicted with over 80% accuracy and segment overlap (SOV), disorder with over 0.9 AUC, 0.6 Matthews Correlation Coefficient (MCC), and 75% SOV, and relative solvent accessibility with PCC of 0.7 and MCC of 0.6 (0.86 when homology is used). We demonstrate that the secondary structure predicted from sequence without the use of homology modeling is as good as the structure extracted from the 3D folds predicted by top-performing template-based methods.

QSAR and 3D QSAR of inhibitors of the epidermal growth factor receptor

NASA Astrophysics Data System (ADS)

Pinto-Bazurco, Mariano; Tsakovska, Ivanka; Pajeva, Ilza

This article reports quantitative structure-activity relationships (QSAR) and 3D QSAR models of 134 structurally diverse inhibitors of the epidermal growth factor receptor (EGFR) tyrosine kinase. Free-Wilson analysis was used to derive the QSAR model. It identified the substituents in aniline, the polycyclic system, and the substituents at the 6- and 7-positions of the polycyclic system as the most important structural features. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used in the 3D QSAR modeling. The steric and electrostatic interactions proved the most important for the inhibitory effect. Both QSAR and 3D QSAR models led to consistent results. On the basis of the statistically significant models, new structures were proposed and their inhibitory activities were predicted.

Numerical prediction of 3-D ejector flows

NASA Technical Reports Server (NTRS)

Roberts, D. W.; Paynter, G. C.

1979-01-01

The use of parametric flow analysis, rather than parametric scale testing, to support the design of an ejector system offers a number of potential advantages. The application of available 3-D flow analyses to the design ejectors can be subdivided into several key elements. These are numerics, turbulence modeling, data handling and display, and testing in support of analysis development. Experimental and predicted jet exhaust for the Boeing 727 aircraft are examined.

Ab initio RNA folding by discrete molecular dynamics: From structure prediction to folding mechanisms

PubMed Central

Ding, Feng; Sharma, Shantanu; Chalasani, Poornima; Demidov, Vadim V.; Broude, Natalia E.; Dokholyan, Nikolay V.

2008-01-01

RNA molecules with novel functions have revived interest in the accurate prediction of RNA three-dimensional (3D) structure and folding dynamics. However, existing methods are inefficient in automated 3D structure prediction. Here, we report a robust computational approach for rapid folding of RNA molecules. We develop a simplified RNA model for discrete molecular dynamics (DMD) simulations, incorporating base-pairing and base-stacking interactions. We demonstrate correct folding of 150 structurally diverse RNA sequences. The majority of DMD-predicted 3D structures have <4 Å deviations from experimental structures. The secondary structures corresponding to the predicted 3D structures consist of 94% native base-pair interactions. Folding thermodynamics and kinetics of tRNAPhe, pseudoknots, and mRNA fragments in DMD simulations are in agreement with previous experimental findings. Folding of RNA molecules features transient, non-native conformations, suggesting non-hierarchical RNA folding. Our method allows rapid conformational sampling of RNA folding, with computational time increasing linearly with RNA length. We envision this approach as a promising tool for RNA structural and functional analyses. PMID:18456842

Data assimialation for real-time prediction and reanalysis

NASA Astrophysics Data System (ADS)

Shprits, Y.; Kellerman, A. C.; Podladchikova, T.; Kondrashov, D. A.; Ghil, M.

2015-12-01

We discuss the how data assimilation can be used for the analysis of individual satellite anomalies, development of long-term evolution reconstruction that can be used for the specification models, and use of data assimilation to improve the now-casting and focusing of the radiation belts. We also discuss advanced data assimilation methods such as parameter estimation and smoothing.The 3D data assimilative VERB allows us to blend together data from GOES, RBSP A and RBSP B. Real-time prediction framework operating on our web site based on GOES, RBSP A, B and ACE data and 3D VERB is presented and discussed. In this paper we present a number of application of the data assimilation with the VERB 3D code. 1) Model with data assimilation allows to propagate data to different pitch angles, energies, and L-shells and blends them together with the physics based VERB code in an optimal way. We illustrate how we use this capability for the analysis of the previous events and for obtaining a global and statistical view of the system. 2) The model predictions strongly depend on initial conditions that are set up for the model. Therefore the model is as good as the initial conditions that it uses. To produce the best possible initial condition data from different sources ( GOES, RBSP A, B, our empirical model predictions based on ACE) are all blended together in an optimal way by means of data assimilation as described above. The resulting initial condition does not have gaps. That allows us to make a more accurate predictions.

CFD code calibration and inlet-fairing effects on a 3D hypersonic powered-simulation model

NASA Technical Reports Server (NTRS)

Huebner, Lawrence D.; Tatum, Kenneth E.

1993-01-01

A three-dimensional (3D) computational study has been performed addressing issues related to the wind tunnel testing of a hypersonic powered-simulation model. The study consisted of three objectives. The first objective was to calibrate a state-of-the-art computational fluid dynamics (CFD) code in its ability to predict hypersonic powered-simulation flows by comparing CFD solutions with experimental surface pressure dam. Aftbody lower surface pressures were well predicted, but lower surface wing pressures were less accurately predicted. The second objective was to determine the 3D effects on the aftbody created by fairing over the inlet; this was accomplished by comparing the CFD solutions of two closed-inlet powered configurations with a flowing-inlet powered configuration. Although results at four freestream Mach numbers indicate that the exhaust plume tends to isolate the aftbody surface from most forebody flowfield differences, a smooth inlet fairing provides the least aftbody force and moment variation compared to a flowing inlet. The final objective was to predict and understand the 3D characteristics of exhaust plume development at selected points on a representative flight path. Results showed a dramatic effect of plume expansion onto the wings as the freestream Mach number and corresponding nozzle pressure ratio are increased.

CFD Code Calibration and Inlet-Fairing Effects On a 3D Hypersonic Powered-Simulation Model

NASA Technical Reports Server (NTRS)

Huebner, Lawrence D.; Tatum, Kenneth E.

1993-01-01

A three-dimensional (3D) computational study has been performed addressing issues related to the wind tunnel testing of a hypersonic powered-simulation model. The study consisted of three objectives. The first objective was to calibrate a state-of-the-art computational fluid dynamics (CFD) code in its ability to predict hypersonic powered-simulation flows by comparing CFD solutions with experimental surface pressure data. Aftbody lower surface pressures were well predicted, but lower surface wing pressures were less accurately predicted. The second objective was to determine the 3D effects on the aftbody created by fairing over the inlet; this was accomplished by comparing the CFD solutions of two closed-inlet powered configurations with a flowing- inlet powered configuration. Although results at four freestream Mach numbers indicate that the exhaust plume tends to isolate the aftbody surface from most forebody flow- field differences, a smooth inlet fairing provides the least aftbody force and moment variation compared to a flowing inlet. The final objective was to predict and understand the 3D characteristics of exhaust plume development at selected points on a representative flight path. Results showed a dramatic effect of plume expansion onto the wings as the freestream Mach number and corresponding nozzle pressure ratio are increased.

3D-QSAR modeling and molecular docking studies on a series of 2,5 disubstituted 1,3,4-oxadiazoles

NASA Astrophysics Data System (ADS)

Ghaleb, Adib; Aouidate, Adnane; Ghamali, Mounir; Sbai, Abdelouahid; Bouachrine, Mohammed; Lakhlifi, Tahar

2017-10-01

3D-QSAR (comparative molecular field analysis (CoMFA)) and comparative molecular similarity indices analysis (CoMSIA) were performed on novel 2,5 disubstituted 1,3,4-oxadiazoles analogues as anti-fungal agents. The CoMFA and CoMSIA models using 13 compounds in the training set gives Q2 values of 0.52 and 0.51 respectively, while R2 values of 0.92. The adapted alignment method with the suitable parameters resulted in reliable models. The contour maps produced by the CoMFA and CoMSIA models were employed to determine a three-dimensional quantitative structure-activity relationship. Based on this study a set of new molecules with high predicted activities were designed. Surflex-docking confirmed the stability of predicted molecules in the receptor.

Modeling Three-Dimensional Shock Initiation of PBX 9501 in ALE3D

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

Leininger, L; Springer, H K; Mace, J

A recent SMIS (Specific Munitions Impact Scenario) experimental series performed at Los Alamos National Laboratory has provided 3-dimensional shock initiation behavior of the HMX-based heterogeneous high explosive, PBX 9501. A series of finite element impact calculations have been performed in the ALE3D [1] hydrodynamic code and compared to the SMIS results to validate and study code predictions. These SMIS tests used a powder gun to shoot scaled NATO standard fragments into a cylinder of PBX 9501, which has a PMMA case and a steel impact cover. This SMIS real-world shot scenario creates a unique test-bed because (1) SMIS tests facilitatemore » the investigation of 3D Shock to Detonation Transition (SDT) within the context of a considerable suite of diagnostics, and (2) many of the fragments arrive at the impact plate off-center and at an angle of impact. A particular goal of these model validation experiments is to demonstrate the predictive capability of the ALE3D implementation of the Tarver-Lee Ignition and Growth reactive flow model [2] within a fully 3-dimensional regime of SDT. The 3-dimensional Arbitrary Lagrange Eulerian (ALE) hydrodynamic model in ALE3D applies the Ignition and Growth (I&G) reactive flow model with PBX 9501 parameters derived from historical 1-dimensional experimental data. The model includes the off-center and angle of impact variations seen in the experiments. Qualitatively, the ALE3D I&G calculations reproduce observed 'Go/No-Go' 3D Shock to Detonation Transition (SDT) reaction in the explosive, as well as the case expansion recorded by a high-speed optical camera. Quantitatively, the calculations show good agreement with the shock time of arrival at internal and external diagnostic pins. This exercise demonstrates the utility of the Ignition and Growth model applied for the response of heterogeneous high explosives in the SDT regime.« less

Recognizing 3 D Objects from 2D Images Using Structural Knowledge Base of Genetic Views

DTIC Science & Technology

1988-08-31

technical report. [BIE85] I. Biederman , "Human image understanding: Recent research and a theory", Computer Vision, Graphics, and Image Processing, vol...model bases", Technical Report 87-85, COINS Dept, University of Massachusetts, Amherst, MA 01003, August 1987 . [BUR87b) Burns, J. B. and L. J. Kitchen...34Recognition in 2D images of 3D objects from large model bases using prediction hierarchies", Proc. IJCAI-10, 1987 . [BUR891 J. B. Burns, forthcoming

Investigation of Fully Three-Dimensional Helical RF Field Effects on TWT Beam/Circuit Interaction

NASA Technical Reports Server (NTRS)

Kory, Carol L.

2000-01-01

A fully three-dimensional (3D), time-dependent, helical traveling wave-tube (TWT) interaction model has been developed using the electromagnetic particle-in-cell (PIC) code MAFIA. The model includes a short section of helical slow-wave circuit with excitation fed by RF input/output couplers, and electron beam contained by periodic permanent magnet (PPM) focusing. All components of the model are simulated in three dimensions allowing the effects of the fully 3D helical fields on RF circuit/beam interaction to be investigated for the first time. The development of the interaction model is presented, and predicted TWT performance using 2.5D and 3D models is compared to investigate the effect of conventional approximations used in TWT analyses.

3D Printing in Surgical Management of Double Outlet Right Ventricle.

PubMed

Yoo, Shi-Joon; van Arsdell, Glen S

2017-01-01

Double outlet right ventricle (DORV) is a heterogeneous group of congenital heart diseases that require individualized surgical approach based on precise understanding of the complex cardiovascular anatomy. Physical 3-dimensional (3D) print models not only allow fast and unequivocal perception of the complex anatomy but also eliminate misunderstanding or miscommunication among imagers and surgeons. Except for those cases showing well-recognized classic surgical anatomy of DORV such as in cases with a typical subaortic or subpulmonary ventricular septal defect, 3D print models are of enormous value in surgical decision and planning. Furthermore, 3D print models can also be used for rehearsal of the intended procedure before the actual surgery on the patient so that the outcome of the procedure is precisely predicted and the procedure can be optimally tailored for the patient's specific anatomy. 3D print models are invaluable resource for hands-on surgical training of congenital heart surgeons.

Predicting Failure of Glyburide Therapy in Gestational Diabetes

PubMed Central

Harper, Lorie M.; Glover, Angelica V.; Biggio, Joseph R.; Tita, Alan

2016-01-01

Objective We sought to develop a prediction model to identify women with gestational diabetes (GDM) who require insulin to achieve glycemic control. Study Design Retrospective cohort of all singletons with GDM treated with glyburide 2007–2013. Glyburide failure was defined as reaching glyburide 20 mg/day and receiving insulin. Glyburide success was defined as any glyburide dose without insulin and >70% of visits with glycemic control. Multivariable logistic regression analysis was performed to create a prediction model. Results Of 360 women, 63 (17.5%) qualified as glyburide failure and 157 (43.6%) glyburide success. The final prediction model for glyburide failure included prior GDM, GDM diagnosis ≤26 weeks, 1-hour GCT ≥228 mg/dL, 3-hour GTT 1-hour value ≥221 mg/dL, ≥7 post-prandial blood sugars >120 mg/dL in the week glyburide started, and ≥1 blood sugar >200 mg/dL. The model accurately classified 81% of subjects. Conclusions Women with GDM who will require insulin can be identified at initiation of pharmacologic therapy. PMID:26796130

Testing a 1-D Analytical Salt Intrusion Model and the Predictive Equation in Malaysian Estuaries

NASA Astrophysics Data System (ADS)

Gisen, Jacqueline Isabella; Savenije, Hubert H. G.

2013-04-01

Little is known about the salt intrusion behaviour in Malaysian estuaries. Study on this topic sometimes requires large amounts of data especially if a 2-D or 3-D numerical models are used for analysis. In poor data environments, 1-D analytical models are more appropriate. For this reason, a fully analytical 1-D salt intrusion model, based on the theory of Savenije in 2005, was tested in three Malaysian estuaries (Bernam, Selangor and Muar) because it is simple and requires minimal data. In order to achieve that, site surveys were conducted in these estuaries during the dry season (June-August) at spring tide by moving boat technique. Data of cross-sections, water levels and salinity were collected, and then analysed with the salt intrusion model. This paper demonstrates a good fit between the simulated and observed salinity distribution for all three estuaries. Additionally, the calibrated Van der Burgh's coefficient K, Dispersion coefficient D0, and salt intrusion length L, for the estuaries also displayed a reasonable correlations with those calculated from the predictive equations. This indicates that not only is the salt intrusion model valid for the case studies in Malaysia but also the predictive model. Furthermore, the results from this study describe the current state of the estuaries with which the Malaysian water authority in Malaysia can make decisions on limiting water abstraction or dredging. Keywords: salt intrusion, Malaysian estuaries, discharge, predictive model, dispersion

LARGE-SCALE PREDICTIONS OF MOBILE SOURCE CONTRIBUTIONS TO CONCENTRATIONS OF TOXIC AIR POLLUTANTS

EPA Science Inventory

This presentation shows concentrations and deposition of toxic air pollutants predicted by a 3-D air quality model, the Community Multi Scale Air Quality (CMAQ) modeling system. Contributions from both on-road and non-road mobile sources are analyzed.

Separation of antibody drug conjugate species by RPLC: A generic method development approach.

PubMed

Fekete, Szabolcs; Molnár, Imre; Guillarme, Davy

2017-04-15

This study reports the use of modelling software for the successful method development of IgG1 cysteine conjugated antibody drug conjugate (ADC) in RPLC. The goal of such a method is to be able to calculate the average drug to antibody ratio (DAR) of and ADC product. A generic method development strategy was proposed including the optimization of mobile phase temperature, gradient profile and mobile phase ternary composition. For the first time, a 3D retention modelling was presented for large therapeutic protein. Based on a limited number of preliminary experiments, a fast and efficient separation of the DAR species of a commercial ADC sample, namely brentuximab vedotin, was achieved. The prediction offered by the retention model was found to be highly reliable, with an average error of retention time prediction always lower than 0.5% using a 2D or 3D retention models. For routine purpose, four to six initial experiments were required to build the 2D retention models, while 12 experiments were recommended to create the 3D model. At the end, RPLC can therefore be considered as a good method for estimating the average DAR of an ADC, based on the observed peak area ratios of RPLC chromatogram of the reduced ADC sample. Copyright © 2017 Elsevier B.V. All rights reserved.

Testing of transition-region models: Test cases and data

NASA Technical Reports Server (NTRS)

Singer, Bart A.; Dinavahi, Surya; Iyer, Venkit

1991-01-01

Mean flow quantities in the laminar turbulent transition region and in the fully turbulent region are predicted with different models incorporated into a 3-D boundary layer code. The predicted quantities are compared with experimental data for a large number of different flows and the suitability of the models for each flow is evaluated.

Data Assimilation and Propagation of Uncertainty in Multiscale Cardiovascular Simulation

NASA Astrophysics Data System (ADS)

Schiavazzi, Daniele; Marsden, Alison

2015-11-01

Cardiovascular modeling is the application of computational tools to predict hemodynamics. State-of-the-art techniques couple a 3D incompressible Navier-Stokes solver with a boundary circulation model and can predict local and peripheral hemodynamics, analyze the post-operative performance of surgical designs and complement clinical data collection minimizing invasive and risky measurement practices. The ability of these tools to make useful predictions is directly related to their accuracy in representing measured physiologies. Tuning of model parameters is therefore a topic of paramount importance and should include clinical data uncertainty, revealing how this uncertainty will affect the predictions. We propose a fully Bayesian, multi-level approach to data assimilation of uncertain clinical data in multiscale circulation models. To reduce the computational cost, we use a stable, condensed approximation of the 3D model build by linear sparse regression of the pressure/flow rate relationship at the outlets. Finally, we consider the problem of non-invasively propagating the uncertainty in model parameters to the resulting hemodynamics and compare Monte Carlo simulation with Stochastic Collocation approaches based on Polynomial or Multi-resolution Chaos expansions.

Biomechanical model for computing deformations for whole-body image registration: A meshless approach.

PubMed

Li, Mao; Miller, Karol; Joldes, Grand Roman; Kikinis, Ron; Wittek, Adam

2016-12-01

Patient-specific biomechanical models have been advocated as a tool for predicting deformations of soft body organs/tissue for medical image registration (aligning two sets of images) when differences between the images are large. However, complex and irregular geometry of the body organs makes generation of patient-specific biomechanical models very time-consuming. Meshless discretisation has been proposed to solve this challenge. However, applications so far have been limited to 2D models and computing single organ deformations. In this study, 3D comprehensive patient-specific nonlinear biomechanical models implemented using meshless Total Lagrangian explicit dynamics algorithms are applied to predict a 3D deformation field for whole-body image registration. Unlike a conventional approach that requires dividing (segmenting) the image into non-overlapping constituents representing different organs/tissues, the mechanical properties are assigned using the fuzzy c-means algorithm without the image segmentation. Verification indicates that the deformations predicted using the proposed meshless approach are for practical purposes the same as those obtained using the previously validated finite element models. To quantitatively evaluate the accuracy of the predicted deformations, we determined the spatial misalignment between the registered (i.e. source images warped using the predicted deformations) and target images by computing the edge-based Hausdorff distance. The Hausdorff distance-based evaluation determines that our meshless models led to successful registration of the vast majority of the image features. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Binocular fusion and invariant category learning due to predictive remapping during scanning of a depthful scene with eye movements

PubMed Central

Grossberg, Stephen; Srinivasan, Karthik; Yazdanbakhsh, Arash

2015-01-01

How does the brain maintain stable fusion of 3D scenes when the eyes move? Every eye movement causes each retinal position to process a different set of scenic features, and thus the brain needs to binocularly fuse new combinations of features at each position after an eye movement. Despite these breaks in retinotopic fusion due to each movement, previously fused representations of a scene in depth often appear stable. The 3D ARTSCAN neural model proposes how the brain does this by unifying concepts about how multiple cortical areas in the What and Where cortical streams interact to coordinate processes of 3D boundary and surface perception, spatial attention, invariant object category learning, predictive remapping, eye movement control, and learned coordinate transformations. The model explains data from single neuron and psychophysical studies of covert visual attention shifts prior to eye movements. The model further clarifies how perceptual, attentional, and cognitive interactions among multiple brain regions (LGN, V1, V2, V3A, V4, MT, MST, PPC, LIP, ITp, ITa, SC) may accomplish predictive remapping as part of the process whereby view-invariant object categories are learned. These results build upon earlier neural models of 3D vision and figure-ground separation and the learning of invariant object categories as the eyes freely scan a scene. A key process concerns how an object's surface representation generates a form-fitting distribution of spatial attention, or attentional shroud, in parietal cortex that helps maintain the stability of multiple perceptual and cognitive processes. Predictive eye movement signals maintain the stability of the shroud, as well as of binocularly fused perceptual boundaries and surface representations. PMID:25642198

Binocular fusion and invariant category learning due to predictive remapping during scanning of a depthful scene with eye movements.

PubMed

Grossberg, Stephen; Srinivasan, Karthik; Yazdanbakhsh, Arash

2014-01-01

How does the brain maintain stable fusion of 3D scenes when the eyes move? Every eye movement causes each retinal position to process a different set of scenic features, and thus the brain needs to binocularly fuse new combinations of features at each position after an eye movement. Despite these breaks in retinotopic fusion due to each movement, previously fused representations of a scene in depth often appear stable. The 3D ARTSCAN neural model proposes how the brain does this by unifying concepts about how multiple cortical areas in the What and Where cortical streams interact to coordinate processes of 3D boundary and surface perception, spatial attention, invariant object category learning, predictive remapping, eye movement control, and learned coordinate transformations. The model explains data from single neuron and psychophysical studies of covert visual attention shifts prior to eye movements. The model further clarifies how perceptual, attentional, and cognitive interactions among multiple brain regions (LGN, V1, V2, V3A, V4, MT, MST, PPC, LIP, ITp, ITa, SC) may accomplish predictive remapping as part of the process whereby view-invariant object categories are learned. These results build upon earlier neural models of 3D vision and figure-ground separation and the learning of invariant object categories as the eyes freely scan a scene. A key process concerns how an object's surface representation generates a form-fitting distribution of spatial attention, or attentional shroud, in parietal cortex that helps maintain the stability of multiple perceptual and cognitive processes. Predictive eye movement signals maintain the stability of the shroud, as well as of binocularly fused perceptual boundaries and surface representations.

Sensitivity of Above-Ground Biomass Estimates to Height-Diameter Modelling in Mixed-Species West African Woodlands

PubMed Central

Aynekulu, Ermias; Pitkänen, Sari; Packalen, Petteri

2016-01-01

It has been suggested that above-ground biomass (AGB) inventories should include tree height (H), in addition to diameter (D). As H is a difficult variable to measure, H-D models are commonly used to predict H. We tested a number of approaches for H-D modelling, including additive terms which increased the complexity of the model, and observed how differences in tree-level predictions of H propagated to plot-level AGB estimations. We were especially interested in detecting whether the choice of method can lead to bias. The compared approaches listed in the order of increasing complexity were: (B0) AGB estimations from D-only; (B1) involving also H obtained from a fixed-effects H-D model; (B2) involving also species; (B3) including also between-plot variability as random effects; and (B4) involving multilevel nested random effects for grouping plots in clusters. In light of the results, the modelling approach affected the AGB estimation significantly in some cases, although differences were negligible for some of the alternatives. The most important differences were found between including H or not in the AGB estimation. We observed that AGB predictions without H information were very sensitive to the environmental stress parameter (E), which can induce a critical bias. Regarding the H-D modelling, the most relevant effect was found when species was included as an additive term. We presented a two-step methodology, which succeeded in identifying the species for which the general H-D relation was relevant to modify. Based on the results, our final choice was the single-level mixed-effects model (B3), which accounts for the species but also for the plot random effects reflecting site-specific factors such as soil properties and degree of disturbance. PMID:27367857

MINEMOTION3D: A new set of Programs for Predicting Ground Motion From Explosions in Complex 3D Media

NASA Astrophysics Data System (ADS)

Tibuleac, I. M.; Bonner, J. L.; Orrey, J. L.; Yang, X.

2004-12-01

Predicting ground motion from complicated mining explosions is important for mines developing new blasting programs in regions where vibrations must be kept below certain levels. Additionally, predicting ground motion from mining explosions in complex 3D media is important for moment estimation for nuclear test treaty monitoring. Both problems have been addressed under the development of a new series of numerical prediction programs called MINEMOTION3D including 1) Generalized Fourier Methods to generate Green's functions in 3D media for a moment tensor source implementation and 2) MineSeis3D, a program that simulates seismograms for delay-fired mining explosions with a linear relationship between signals from small size individual shots. To test the programs, local recordings (5 - 23 km) of three production shots at a mine in northern Minnesota were compared to synthetic waveforms in 3D media. A non-zero value of the moment tensor component M12 was considered, to introduce a horizontal spall component into the waveform synthesis when the Green's functions were generated for each model. Methods using seismic noise crosscorrelation for improved inter-element subsurface structure estimation were also evaluated. Comparison of the observed and synthetic waveforms shows promising results. The shape and arrival times of the normalized synthetic and observed waveforms are similar for most of the stations. The synthetic and observed waveform amplitude fit is best for the vertical components in the mean 3D model and worst for the transversal components. The observed effect of spall on the waveform spectra was weak in the case of fragmentation delay fired commercial explosions. Commercial applications of the code could provide data needed for designing explosions which do not exceed ground vibration requirements posed by the U.S. Department of the Interior, Office of Surface Mining.

Fast Geometric Consensus Approach for Protein Model Quality Assessment

PubMed Central

Adamczak, Rafal; Pillardy, Jaroslaw; Vallat, Brinda K.

2011-01-01

Abstract Model quality assessment (MQA) is an integral part of protein structure prediction methods that typically generate multiple candidate models. The challenge lies in ranking and selecting the best models using a variety of physical, knowledge-based, and geometric consensus (GC)-based scoring functions. In particular, 3D-Jury and related GC methods assume that well-predicted (sub-)structures are more likely to occur frequently in a population of candidate models, compared to incorrectly folded fragments. While this approach is very successful in the context of diversified sets of models, identifying similar substructures is computationally expensive since all pairs of models need to be superimposed using MaxSub or related heuristics for structure-to-structure alignment. Here, we consider a fast alternative, in which structural similarity is assessed using 1D profiles, e.g., consisting of relative solvent accessibilities and secondary structures of equivalent amino acid residues in the respective models. We show that the new approach, dubbed 1D-Jury, allows to implicitly compare and rank N models in O(N) time, as opposed to quadratic complexity of 3D-Jury and related clustering-based methods. In addition, 1D-Jury avoids computationally expensive 3D superposition of pairs of models. At the same time, structural similarity scores based on 1D profiles are shown to correlate strongly with those obtained using MaxSub. In terms of the ability to select the best models as top candidates 1D-Jury performs on par with other GC methods. Other potential applications of the new approach, including fast clustering of large numbers of intermediate structures generated by folding simulations, are discussed as well. PMID:21244273

New reaction rates for improved primordial D /H calculation and the cosmic evolution of deuterium

NASA Astrophysics Data System (ADS)

Coc, Alain; Petitjean, Patrick; Uzan, Jean-Philippe; Vangioni, Elisabeth; Descouvemont, Pierre; Iliadis, Christian; Longland, Richard

2015-12-01

Primordial or big bang nucleosynthesis (BBN) is one of the three historically strong evidences for the big bang model. Standard BBN is now a parameter-free theory, since the baryonic density of the Universe has been deduced with an unprecedented precision from observations of the anisotropies of the cosmic microwave background radiation. There is a good agreement between the primordial abundances of 4He, D, 3He, and 7Li deduced from observations and from primordial nucleosynthesis calculations. However, the 7Li calculated abundance is significantly higher than the one deduced from spectroscopic observations and remains an open problem. In addition, recent deuterium observations have drastically reduced the uncertainty on D /H , to reach a value of 1.6%. It needs to be matched by BBN predictions whose precision is now limited by thermonuclear reaction rate uncertainties. This is especially important as many attempts to reconcile Li observations with models lead to an increased D prediction. Here, we reevaluate the d (p ,γ )3He, d (d ,n ) 3H3, and d (d ,p ) 3H reaction rates that govern deuterium destruction, incorporating new experimental data and carefully accounting for systematic uncertainties. Contrary to previous evaluations, we use theoretical ab initio models for the energy dependence of the S factors. As a result, these rates increase at BBN temperatures, leading to a reduced value of D /H =(2.45 ±0.10 )×10-5 (2 σ ), in agreement with observations.

Numerical Analysis of the Elastic Properties of 3D Needled Carbon/Carbon Composites

NASA Astrophysics Data System (ADS)

Tan, Y.; Yan, Y.; Li, X.; Guo, F.

2017-09-01

Based on the observation of microstructures of 3D needled carbon/carbon (C/C) composites, a model of their representative volume element (RVE) considering the true distribution of fibers is established. Using the theories of mesoscopic mechanics and introducing periodic boundary conditions for displacements, their elastic properties, with account of porosity, are determined by finite-element methods. Quasi-static tensile tests were carried out, and the numerical predictions were found to be in good agreement with test results. This means that the RVE model of 3D needled C/C composites can predict their elastic properties efficiently. The effects of needling density, radius of needled fibers, and thickness ratio of a short-cut fiber web and a weftless ply on the elastic constants of the composites are analyzed.

A predictive model of serum 25-hydroxyvitamin D in UK white as well as black and Asian minority ethnic population groups for application in food fortification strategy development towards vitamin D deficiency prevention.

PubMed

O'Neill, Colette M; Kazantzidis, Andreas; Kiely, Mairead; Cox, Lorna; Meadows, Sarah; Goldberg, Gail; Prentice, Ann; Kift, Richard; Webb, Ann R; Cashman, Kevin D

2017-10-01

Within Europe, dark-skinned ethnic groups have been shown to be at much increased risk of vitamin D deficiency compared to their white counterparts. Increasing the dietary supply of vitamin D is potentially the only modifiable environmental component that can be used to prevent vitamin D deficiency among dark-skinned ethnic groups living at high latitude. Empirical data to support development of such strategies is largely lacking. This paper presents the development and validation of an integrated model that may be adapted within the UK population to design fortification strategies for vitamin D, for application in both white and black and Asian minority ethnic (BAME) population groups. Using a step-wise approach, models based on available ultraviolet B (UVB) data, hours of sunlight and two key components (the dose-response of serum 25-hydroxyvitamin D [25(OH)D] to UVB in white and BAME persons and the dose-response of 25(OH)D to vitamin D) were used to predict changes population serum 25(OH)D concentrations throughout the year, stratified by ethnicity, 'via increases' in dietary intake arising from food fortification simulations. The integrated model successfully predicted measured average wintertime 25(OH)D concentrations in addition to the prevalence of serum 25(OH)D <30nmol/L in adult white and BAME individuals (18-70y) in the UK-based National Diet and Nutrition Survey both separately (21.7% and 49.3% predicted versus 20.2% and 50.5% measured, for white and BAME, respectively) and when combined at UK population-relevant proportions of 97% white and 7% BAME (23.2% predicted versus 23.1% measured). Thus this integrated model presents a viable approach to estimating changes in the population concentrations of 25(OH)D that may arise from various dietary fortification approaches. Copyright © 2016 Elsevier Ltd. All rights reserved.

3D CFD Modeling of the LMF System: Desulfurization Kinetics

NASA Astrophysics Data System (ADS)

Cao, Qing; Pitts, April; Zhang, Daojie; Nastac, Laurentiu; Williams, Robert

A fully transient 3D CFD modeling approach capable of predicting the three phase (gas, slag and steel) fluid flow characteristics and behavior of the slag/steel interface in the argon gas bottom stirred ladle with two off-centered porous plugs (Ladle Metallurgical Furnace or LMF) has been recently developed. The model predicts reasonably well the fluid flow characteristics in the LMF system and the observed size of the slag eyes for both the high-stirring and low-stirring conditions. A desulfurization reaction kinetics model considering metal/slag interface characteristics is developed in conjunction with the CFD modeling approach. The model is applied in this study to determine the effects of processing time, and gas flow rate on the efficiency of desulfurization in the studied LMF system.

Statistical modeling of 4D respiratory lung motion using diffeomorphic image registration.

PubMed

Ehrhardt, Jan; Werner, René; Schmidt-Richberg, Alexander; Handels, Heinz

2011-02-01

Modeling of respiratory motion has become increasingly important in various applications of medical imaging (e.g., radiation therapy of lung cancer). Current modeling approaches are usually confined to intra-patient registration of 3D image data representing the individual patient's anatomy at different breathing phases. We propose an approach to generate a mean motion model of the lung based on thoracic 4D computed tomography (CT) data of different patients to extend the motion modeling capabilities. Our modeling process consists of three steps: an intra-subject registration to generate subject-specific motion models, the generation of an average shape and intensity atlas of the lung as anatomical reference frame, and the registration of the subject-specific motion models to the atlas in order to build a statistical 4D mean motion model (4D-MMM). Furthermore, we present methods to adapt the 4D mean motion model to a patient-specific lung geometry. In all steps, a symmetric diffeomorphic nonlinear intensity-based registration method was employed. The Log-Euclidean framework was used to compute statistics on the diffeomorphic transformations. The presented methods are then used to build a mean motion model of respiratory lung motion using thoracic 4D CT data sets of 17 patients. We evaluate the model by applying it for estimating respiratory motion of ten lung cancer patients. The prediction is evaluated with respect to landmark and tumor motion, and the quantitative analysis results in a mean target registration error (TRE) of 3.3 ±1.6 mm if lung dynamics are not impaired by large lung tumors or other lung disorders (e.g., emphysema). With regard to lung tumor motion, we show that prediction accuracy is independent of tumor size and tumor motion amplitude in the considered data set. However, tumors adhering to non-lung structures degrade local lung dynamics significantly and the model-based prediction accuracy is lower in these cases. The statistical respiratory motion model is capable of providing valuable prior knowledge in many fields of applications. We present two examples of possible applications in radiation therapy and image guided diagnosis.

Sirolimus and everolimus clearance in maintenance kidney and liver transplant recipients: Diagnostic efficiency of the concentration/dose ratio for the prediction of trough steady-state concentrations

PubMed Central

Bouzas, Lorena; Hermida, Jesús

2010-01-01

Objectives Therapeutic monitoring of sirolimus and everolimus is necessary in order to minimize adverse side-effects and to ensure effective immunosuppression. A sirolimus-dosing model using the concentration/dose ratio has been previously proposed for kidney transplant patients, and the aim of our study was the evaluation of this single model for the prediction of trough sirolimus and everolimus concentrations. Methods Trough steady-state sirolimus concentrations were determined in several blood samples from each of 7 kidney and 9 liver maintenance transplant recipients, and everolimus concentrations from 20 kidney, 17 liver, and 3 kidney/liver maintenance transplant recipients. Predicted sirolimus and everolimus concentrations (Css), corresponding to the doses (D), were calculated using the measured concentrations (Css0) and corresponding doses (D0) on starting the study: Css = (Css0)(D)/D0. Results The diagnostic efficiency of the predicting model for the correct classification as subtherapeutic, therapeutic, and supratherapeutic values with respect to the experimentally obtained concentrations was 91.3% for sirolimus and 81.4% for everolimus in the kidney transplant patients. In the liver transplant patients the efficiency was 69.2% for sirolimus and 72.6% for everolimus, and in the kidney/liver transplant recipients the efficiency for everolimus was 67.9%. Conclusions The model has an acceptable diagnostic efficiency (>80%) for the prediction of sirolimus and everolimus concentrations in kidney transplant recipients, but not in liver transplant recipients. However, considering the wide ranges found for the prediction error of sirolimus and everolimus concentrations, the clinical relevance of this dosing model is weak. PMID:19943816

Subject-specific finite element modelling of the human foot complex during walking: sensitivity analysis of material properties, boundary and loading conditions.

PubMed

Akrami, Mohammad; Qian, Zhihui; Zou, Zhemin; Howard, David; Nester, Chris J; Ren, Lei

2018-04-01

The objective of this study was to develop and validate a subject-specific framework for modelling the human foot. This was achieved by integrating medical image-based finite element modelling, individualised multi-body musculoskeletal modelling and 3D gait measurements. A 3D ankle-foot finite element model comprising all major foot structures was constructed based on MRI of one individual. A multi-body musculoskeletal model and 3D gait measurements for the same subject were used to define loading and boundary conditions. Sensitivity analyses were used to investigate the effects of key modelling parameters on model predictions. Prediction errors of average and peak plantar pressures were below 10% in all ten plantar regions at five key gait events with only one exception (lateral heel, in early stance, error of 14.44%). The sensitivity analyses results suggest that predictions of peak plantar pressures are moderately sensitive to material properties, ground reaction forces and muscle forces, and significantly sensitive to foot orientation. The maximum region-specific percentage change ratios (peak stress percentage change over parameter percentage change) were 1.935-2.258 for ground reaction forces, 1.528-2.727 for plantar flexor muscles and 4.84-11.37 for foot orientations. This strongly suggests that loading and boundary conditions need to be very carefully defined based on personalised measurement data.

3D numerical simulation of free surface shape during the crystal growth of floating zone (FZ) silicon

NASA Astrophysics Data System (ADS)

Han, Xue-Feng; Liu, Xin; Nakano, Satoshi; Harada, Hirofumi; Miyamura, Yoshiji; Kakimoto, Koichi

2018-02-01

In FZ growth processes, the stability of the free surface is important in the production of single crystal silicon with high quality. To investigate the shape of the free surface in the FZ silicon crystal growth, a 3D numerical model that included gas and liquid phases was developed. In this present study, 3D Young-Laplacian equations have been solved using the Volume of Fluid (VOF) Model. Using this new model, we predicted the 3D shape of the free surface in FZ silicon crystal growth. The effect of magnetic pressure on shape of free surface has been considered. In particular, the free surface of the eccentric growth model, which could not be previously solved using the 2D Young-Laplacian equations, was solved using the VOF model. The calculation results are validated by the experimental results.

USM3D Unstructured Grid Solutions for CAWAPI at NASA LaRC

NASA Technical Reports Server (NTRS)

Lamar, John E.; Abdol-Hamid, Khaled S.

2007-01-01

In support the Cranked Arrow Wing Aerodynamic Project International (CAWAPI) to improve the Technology Readiness Level of flow solvers by comparing results with measured F-16XL-1 flight data, NASA Langley employed the TetrUSS unstructured grid solver, USM3D, to obtain solutions for all seven flight conditions of interest. A newly available solver version that incorporates a number of turbulence models, including the two-equation linear and non-linear k-epsilon, was used in this study. As a first test, a choice was made to utilize only a single grid resolution with the solver for the simulation of the different flight conditions. Comparisons are presented with three turbulence models in USM3D, flight data for surface pressure, boundary-layer profiles, and skin-friction results, as well as limited predictions from other solvers. A result of these comparisons is that the USM3D solver can be used in an engineering environment to predict flow physics on a complex configuration at flight Reynolds numbers with a two-equation linear k-epsilon turbulence model.

A prediction of 3-D viscous flow and performance of the NASA low-speed centrifugal compressor

NASA Technical Reports Server (NTRS)

Moore, John; Moore, Joan G.

1989-01-01

A prediction of the 3-D turbulent flow in the NASA Low-Speed Centrifugal Compressor Impeller has been made. The calculation was made for the compressor design conditions with the specified uniform tip clearance gap. The predicted performance is significantly worse than that predicted in the NASA design study. This is explained by the high tip leakage flow in the present calculation and by the different model adopted for tip leakage flow mixing. The calculation gives an accumulation for high losses in the shroud/pressure-side quadrant near the exit of the impeller. It also predicts a region of meridional backflow near the shroud wall. Both of these flow features should be extensive enough in the NASA impeller to allow detailed flow measurements, leading to improved flow modelling. Recommendations are made for future flow studies in the NASA impeller.

Increasing Range and Lethality of Extended-Range Munitions (ERMS) using Numerical Weather Prediction (NWP) and the AUV Workbench to Compute a Ballistic Correction (BALCOR)

DTIC Science & Technology

2006-12-01

2 D . APPROACH TAKEN......................................................................................3 E...7 d . FORCEnet.................................................................................8 D . HISTORY OF LONG-RANGE PROJECTILES (LRPS...46 D . NUMERICAL WEATHER MODELING CENTERS...............................47 1. Fleet Numerical Meteorological

Modeling Intrajunction Dispersion at a Well-Mixed Tidal River Junction

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

Wolfram, Phillip J.; Fringer, Oliver B.; Monsen, Nancy E.

In this paper, the relative importance of small-scale, intrajunction flow features such as shear layers, separation zones, and secondary flows on dispersion in a well-mixed tidal river junction is explored. A fully nonlinear, nonhydrostatic, and unstructured three-dimensional (3D) model is used to resolve supertidal dispersion via scalar transport at a well-mixed tidal river junction. Mass transport simulated in the junction is compared against predictions using a simple node-channel model to quantify the effects of small-scale, 3D intrajunction flow features on mixing and dispersion. The effects of three-dimensionality are demonstrated by quantifying the difference between two-dimensional (2D) and 3D model results.more » An intermediate 3D model that does not resolve the secondary circulation or the recirculating flow at the junction is also compared to the 3D model to quantify the relative sensitivity of mixing on intrajunction flow features. Resolution of complex flow features simulated by the full 3D model is not always necessary because mixing is primarily governed by bulk flow splitting due to the confluence–diffluence cycle. Finally, results in 3D are comparable to the 2D case for many flow pathways simulated, suggesting that 2D modeling may be reasonable for nonstratified and predominantly hydrostatic flows through relatively straight junctions, but not necessarily for the full junction network.« less

Modeling Intrajunction Dispersion at a Well-Mixed Tidal River Junction

DOE PAGES

Wolfram, Phillip J.; Fringer, Oliver B.; Monsen, Nancy E.; ...

2016-08-01

In this paper, the relative importance of small-scale, intrajunction flow features such as shear layers, separation zones, and secondary flows on dispersion in a well-mixed tidal river junction is explored. A fully nonlinear, nonhydrostatic, and unstructured three-dimensional (3D) model is used to resolve supertidal dispersion via scalar transport at a well-mixed tidal river junction. Mass transport simulated in the junction is compared against predictions using a simple node-channel model to quantify the effects of small-scale, 3D intrajunction flow features on mixing and dispersion. The effects of three-dimensionality are demonstrated by quantifying the difference between two-dimensional (2D) and 3D model results.more » An intermediate 3D model that does not resolve the secondary circulation or the recirculating flow at the junction is also compared to the 3D model to quantify the relative sensitivity of mixing on intrajunction flow features. Resolution of complex flow features simulated by the full 3D model is not always necessary because mixing is primarily governed by bulk flow splitting due to the confluence–diffluence cycle. Finally, results in 3D are comparable to the 2D case for many flow pathways simulated, suggesting that 2D modeling may be reasonable for nonstratified and predominantly hydrostatic flows through relatively straight junctions, but not necessarily for the full junction network.« less

The Sensitivity of Glacial Isostatic Adjustment in West Antarctica to Lateral Variations in Earth Structure

NASA Astrophysics Data System (ADS)

Nield, G.; Whitehouse, P. L.; Blank, B.; van der Wal, W.; O'Donnell, J. P.; Stuart, G. W.; Lloyd, A. J.; Wiens, D.

2017-12-01

Accurate models of Glacial Isostatic Adjustment (GIA) are required for correcting satellite measurements of ice-mass change and for interpretation of geodetic data at the location of present and former ice sheets. Global models of GIA tend to adopt a 1-D representation of Earth structure, varying in the radial direction only. In some regions rheological parameters may differ significantly from this global average leading to bias in model predictions of present-day deformation, geoid change rates and sea-level change. The advancement of 3-D GIA modelling techniques in recent years has led to improvements in the representation of the Earth via the incorporation of laterally varying structure. This study investigates the influence of 3-D Earth structure on deformation rates in West Antarctica using a finite element GIA model with power-law rheology. We utilise datasets of seismic velocity and temperature for the crust and upper mantle with the aim of determining a data-driven Earth model, and consider the differences when compared to deformation predicted from an equivalent 1-D Earth structure.

Use of integrated analogue and numerical modelling to predict tridimensional fracture intensity in fault-related-folds.

NASA Astrophysics Data System (ADS)

Pizzati, Mattia; Cavozzi, Cristian; Magistroni, Corrado; Storti, Fabrizio

2016-04-01

Fracture density pattern predictions with low uncertainty is a fundamental issue for constraining fluid flow pathways in thrust-related anticlines in the frontal parts of thrust-and-fold belts and accretionary prisms, which can also provide plays for hydrocarbon exploration and development. Among the drivers that concur to determine the distribution of fractures in fold-and-thrust-belts, the complex kinematic pathways of folded structures play a key role. In areas with scarce and not reliable underground information, analogue modelling can provide effective support for developing and validating reliable hypotheses on structural architectures and their evolution. In this contribution, we propose a working method that combines analogue and numerical modelling. We deformed a sand-silicone multilayer to eventually produce a non-cylindrical thrust-related anticline at the wedge toe, which was our test geological structure at the reservoir scale. We cut 60 serial cross-sections through the central part of the deformed model to analyze faults and folds geometry using dedicated software (3D Move). The cross-sections were also used to reconstruct the 3D geometry of reference surfaces that compose the mechanical stratigraphy thanks to the use of the software GoCad. From the 3D model of the experimental anticline, by using 3D Move it was possible to calculate the cumulative stress and strain underwent by the deformed reference layers at the end of the deformation and also in incremental steps of fold growth. Based on these model outputs it was also possible to predict the orientation of three main fractures sets (joints and conjugate shear fractures) and their occurrence and density on model surfaces. The next step was the upscaling of the fracture network to the entire digital model volume, to create DFNs.

Three-Dimensional Modeling of Fracture Clusters in Geothermal Reservoirs

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

Ghassemi, Ahmad

The objective of this is to develop a 3-D numerical model for simulating mode I, II, and III (tensile, shear, and out-of-plane) propagation of multiple fractures and fracture clusters to accurately predict geothermal reservoir stimulation using the virtual multi-dimensional internal bond (VMIB). Effective development of enhanced geothermal systems can significantly benefit from improved modeling of hydraulic fracturing. In geothermal reservoirs, where the temperature can reach or exceed 350oC, thermal and poro-mechanical processes play an important role in fracture initiation and propagation. In this project hydraulic fracturing of hot subsurface rock mass will be numerically modeled by extending the virtual multiplemore » internal bond theory and implementing it in a finite element code, WARP3D, a three-dimensional finite element code for solid mechanics. The new constitutive model along with the poro-thermoelastic computational algorithms will allow modeling the initiation and propagation of clusters of fractures, and extension of pre-existing fractures. The work will enable the industry to realistically model stimulation of geothermal reservoirs. The project addresses the Geothermal Technologies Office objective of accurately predicting geothermal reservoir stimulation (GTO technology priority item). The project goal will be attained by: (i) development of the VMIB method for application to 3D analysis of fracture clusters; (ii) development of poro- and thermoelastic material sub-routines for use in 3D finite element code WARP3D; (iii) implementation of VMIB and the new material routines in WARP3D to enable simulation of clusters of fractures while accounting for the effects of the pore pressure, thermal stress and inelastic deformation; (iv) simulation of 3D fracture propagation and coalescence and formation of clusters, and comparison with laboratory compression tests; and (v) application of the model to interpretation of injection experiments (planned by our industrial partner) with reference to the impact of the variations in injection rate and temperature, rock properties, and in-situ stress.« less

Relative binding affinity prediction of farnesoid X receptor in the D3R Grand Challenge 2 using FEP.

PubMed

Schindler, Christina; Rippmann, Friedrich; Kuhn, Daniel

2018-01-01

Physics-based free energy simulations have increasingly become an important tool for predicting binding affinity and the recent introduction of automated protocols has also paved the way towards a more widespread use in the pharmaceutical industry. The D3R 2016 Grand Challenge 2 provided an opportunity to blindly test the commercial free energy calculation protocol FEP+ and assess its performance relative to other affinity prediction methods. The present D3R free energy prediction challenge was built around two experimental data sets involving inhibitors of farnesoid X receptor (FXR) which is a promising anticancer drug target. The FXR binding site is predominantly hydrophobic with few conserved interaction motifs and strong induced fit effects making it a challenging target for molecular modeling and drug design. For both data sets, we achieved reasonable prediction accuracy (RMSD ≈ 1.4 kcal/mol, rank 3-4 according to RMSD out of 20 submissions) comparable to that of state-of-the-art methods in the field. Our D3R results boosted our confidence in the method and strengthen our desire to expand its applications in future in-house drug design projects.

Relative binding affinity prediction of farnesoid X receptor in the D3R Grand Challenge 2 using FEP+

NASA Astrophysics Data System (ADS)

Schindler, Christina; Rippmann, Friedrich; Kuhn, Daniel

2018-01-01

Physics-based free energy simulations have increasingly become an important tool for predicting binding affinity and the recent introduction of automated protocols has also paved the way towards a more widespread use in the pharmaceutical industry. The D3R 2016 Grand Challenge 2 provided an opportunity to blindly test the commercial free energy calculation protocol FEP+ and assess its performance relative to other affinity prediction methods. The present D3R free energy prediction challenge was built around two experimental data sets involving inhibitors of farnesoid X receptor (FXR) which is a promising anticancer drug target. The FXR binding site is predominantly hydrophobic with few conserved interaction motifs and strong induced fit effects making it a challenging target for molecular modeling and drug design. For both data sets, we achieved reasonable prediction accuracy (RMSD ≈ 1.4 kcal/mol, rank 3-4 according to RMSD out of 20 submissions) comparable to that of state-of-the-art methods in the field. Our D3R results boosted our confidence in the method and strengthen our desire to expand its applications in future in-house drug design projects.

Microfluidic on-chip biomimicry for 3D cell culture: a fit-for-purpose investigation from the end user standpoint

PubMed Central

Liu, Ye; Gill, Elisabeth; Shery Huang, Yan Yan

2017-01-01

A plethora of 3D and microfluidics-based culture models have been demonstrated in the recent years with the ultimate aim to facilitate predictive in vitro models for pharmaceutical development. This article summarizes to date the progress in the microfluidics-based tissue culture models, including organ-on-a-chip and vasculature-on-a-chip. Specific focus is placed on addressing the question of what kinds of 3D culture and system complexities are deemed desirable by the biological and biomedical community. This question is addressed through analysis of a research survey to evaluate the potential use of microfluidic cell culture models among the end users. Our results showed a willingness to adopt 3D culture technology among biomedical researchers, although a significant gap still exists between the desired systems and existing 3D culture options. With these results, key challenges and future directions are highlighted. PMID:28670465

Microfluidic on-chip biomimicry for 3D cell culture: a fit-for-purpose investigation from the end user standpoint.

PubMed

Liu, Ye; Gill, Elisabeth; Shery Huang, Yan Yan

2017-06-01

A plethora of 3D and microfluidics-based culture models have been demonstrated in the recent years with the ultimate aim to facilitate predictive in vitro models for pharmaceutical development. This article summarizes to date the progress in the microfluidics-based tissue culture models, including organ-on-a-chip and vasculature-on-a-chip. Specific focus is placed on addressing the question of what kinds of 3D culture and system complexities are deemed desirable by the biological and biomedical community. This question is addressed through analysis of a research survey to evaluate the potential use of microfluidic cell culture models among the end users. Our results showed a willingness to adopt 3D culture technology among biomedical researchers, although a significant gap still exists between the desired systems and existing 3D culture options. With these results, key challenges and future directions are highlighted.

IASI Radiance Data Assimilation in Local Ensemble Transform Kalman Filter

NASA Astrophysics Data System (ADS)

Cho, K.; Hyoung-Wook, C.; Jo, Y.

2016-12-01

Korea institute of Atmospheric Prediction Systems (KIAPS) is developing NWP model with data assimilation systems. Local Ensemble Transform Kalman Filter (LETKF) system, one of the data assimilation systems, has been developed for KIAPS Integrated Model (KIM) based on cubed-sphere grid and has successfully assimilated real data. LETKF data assimilation system has been extended to 4D- LETKF which considers time-evolving error covariance within assimilation window and IASI radiance data assimilation using KPOP (KIAPS package for observation processing) with RTTOV (Radiative Transfer for TOVS). The LETKF system is implementing semi operational prediction including conventional (sonde, aircraft) observation and AMSU-A (Advanced Microwave Sounding Unit-A) radiance data from April. Recently, the semi operational prediction system updated radiance observations including GPS-RO, AMV, IASI (Infrared Atmospheric Sounding Interferometer) data at July. A set of simulation of KIM with ne30np4 and 50 vertical levels (of top 0.3hPa) were carried out for short range forecast (10days) within semi operation prediction LETKF system with ensemble forecast 50 members. In order to only IASI impact, our experiments used only conventional and IAIS radiance data to same semi operational prediction set. We carried out sensitivity test for IAIS thinning method (3D and 4D). IASI observation number was increased by temporal (4D) thinning and the improvement of IASI radiance data impact on the forecast skill of model will expect.

3D Bioprinting of Tissue/Organ Models.

PubMed

Pati, Falguni; Gantelius, Jesper; Svahn, Helene Andersson

2016-04-04

In vitro tissue/organ models are useful platforms that can facilitate systematic, repetitive, and quantitative investigations of drugs/chemicals. The primary objective when developing tissue/organ models is to reproduce physiologically relevant functions that typically require complex culture systems. Bioprinting offers exciting prospects for constructing 3D tissue/organ models, as it enables the reproducible, automated production of complex living tissues. Bioprinted tissues/organs may prove useful for screening novel compounds or predicting toxicity, as the spatial and chemical complexity inherent to native tissues/organs can be recreated. In this Review, we highlight the importance of developing 3D in vitro tissue/organ models by 3D bioprinting techniques, characterization of these models for evaluating their resemblance to native tissue, and their application in the prioritization of lead candidates, toxicity testing, and as disease/tumor models. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Building and validating a prediction model for paediatric type 1 diabetes risk using next generation targeted sequencing of class II HLA genes.

PubMed

Zhao, Lue Ping; Carlsson, Annelie; Larsson, Helena Elding; Forsander, Gun; Ivarsson, Sten A; Kockum, Ingrid; Ludvigsson, Johnny; Marcus, Claude; Persson, Martina; Samuelsson, Ulf; Örtqvist, Eva; Pyo, Chul-Woo; Bolouri, Hamid; Zhao, Michael; Nelson, Wyatt C; Geraghty, Daniel E; Lernmark, Åke

2017-11-01

It is of interest to predict possible lifetime risk of type 1 diabetes (T1D) in young children for recruiting high-risk subjects into longitudinal studies of effective prevention strategies. Utilizing a case-control study in Sweden, we applied a recently developed next generation targeted sequencing technology to genotype class II genes and applied an object-oriented regression to build and validate a prediction model for T1D. In the training set, estimated risk scores were significantly different between patients and controls (P = 8.12 × 10 -92 ), and the area under the curve (AUC) from the receiver operating characteristic (ROC) analysis was 0.917. Using the validation data set, we validated the result with AUC of 0.886. Combining both training and validation data resulted in a predictive model with AUC of 0.903. Further, we performed a "biological validation" by correlating risk scores with 6 islet autoantibodies, and found that the risk score was significantly correlated with IA-2A (Z-score = 3.628, P < 0.001). When applying this prediction model to the Swedish population, where the lifetime T1D risk ranges from 0.5% to 2%, we anticipate identifying approximately 20 000 high-risk subjects after testing all newborns, and this calculation would identify approximately 80% of all patients expected to develop T1D in their lifetime. Through both empirical and biological validation, we have established a prediction model for estimating lifetime T1D risk, using class II HLA. This prediction model should prove useful for future investigations to identify high-risk subjects for prevention research in high-risk populations. Copyright © 2017 John Wiley & Sons, Ltd.

Dynamic mineral clouds on HD 189733b. II. Monte Carlo radiative transfer for 3D cloudy exoplanet atmospheres: combining scattering and emission spectra

NASA Astrophysics Data System (ADS)

Lee, G. K. H.; Wood, K.; Dobbs-Dixon, I.; Rice, A.; Helling, Ch.

2017-05-01

Context. As the 3D spatial properties of exoplanet atmospheres are being observed in increasing detail by current and new generations of telescopes, the modelling of the 3D scattering effects of cloud forming atmospheres with inhomogeneous opacity structures becomes increasingly important to interpret observational data. Aims: We model the scattering and emission properties of a simulated cloud forming, inhomogeneous opacity, hot Jupiter atmosphere of HD 189733b. We compare our results to available Hubble Space Telescope (HST) and Spitzer data and quantify the effects of 3D multiple scattering on observable properties of the atmosphere. We discuss potential observational properties of HD 189733b for the upcoming Transiting Exoplanet Survey Satellite (TESS) and CHaracterising ExOPlanet Satellite (CHEOPS) missions. Methods: We developed a Monte Carlo radiative transfer code and applied it to post-process output of our 3D radiative-hydrodynamic, cloud formation simulation of HD 189733b. We employed three variance reduction techniques, I.e. next event estimation, survival biasing, and composite emission biasing, to improve signal to noise of the output. For cloud particle scattering events, we constructed a log-normal area distribution from the 3D cloud formation radiative-hydrodynamic results, which is stochastically sampled in order to model the Rayleigh and Mie scattering behaviour of a mixture of grain sizes. Results: Stellar photon packets incident on the eastern dayside hemisphere show predominantly Rayleigh, single-scattering behaviour, while multiple scattering occurs on the western hemisphere. Combined scattered and thermal emitted light predictions are consistent with published HST and Spitzer secondary transit observations. Our model predictions are also consistent with geometric albedo constraints from optical wavelength ground-based polarimetry and HST B band measurements. We predict an apparent geometric albedo for HD 189733b of 0.205 and 0.229, in the TESS and CHEOPS photometric bands respectively. Conclusions: Modelling the 3D geometric scattering effects of clouds on observables of exoplanet atmospheres provides an important contribution to the attempt to determine the cloud properties of these objects. Comparisons between TESS and CHEOPS photometry may provide qualitative information on the cloud properties of nearby hot Jupiter exoplanets.

Clinical anthropometrics and body composition from 3D whole-body surface scans.

PubMed

Ng, B K; Hinton, B J; Fan, B; Kanaya, A M; Shepherd, J A

2016-11-01

Obesity is a significant worldwide epidemic that necessitates accessible tools for robust body composition analysis. We investigated whether widely available 3D body surface scanners can provide clinically relevant direct anthropometrics (circumferences, areas and volumes) and body composition estimates (regional fat/lean masses). Thirty-nine healthy adults stratified by age, sex and body mass index (BMI) underwent whole-body 3D scans, dual energy X-ray absorptiometry (DXA), air displacement plethysmography and tape measurements. Linear regressions were performed to assess agreement between 3D measurements and criterion methods. Linear models were derived to predict DXA body composition from 3D scan measurements. Thirty-seven external fitness center users underwent 3D scans and bioelectrical impedance analysis for model validation. 3D body scan measurements correlated strongly to criterion methods: waist circumference R 2 =0.95, hip circumference R 2 =0.92, surface area R 2 =0.97 and volume R 2 =0.99. However, systematic differences were observed for each measure due to discrepancies in landmark positioning. Predictive body composition equations showed strong agreement for whole body (fat mass R 2 =0.95, root mean square error (RMSE)=2.4 kg; fat-free mass R 2 =0.96, RMSE=2.2 kg) and arms, legs and trunk (R 2 =0.79-0.94, RMSE=0.5-1.7 kg). Visceral fat prediction showed moderate agreement (R 2 =0.75, RMSE=0.11 kg). 3D surface scanners offer precise and stable automated measurements of body shape and composition. Software updates may be needed to resolve measurement biases resulting from landmark positioning discrepancies. Further studies are justified to elucidate relationships between body shape, composition and metabolic health across sex, age, BMI and ethnicity groups, as well as in those with metabolic disorders.

Error discrimination of an operational hydrological forecasting system at a national scale

NASA Astrophysics Data System (ADS)

Jordan, F.; Brauchli, T.

2010-09-01

The use of operational hydrological forecasting systems is recommended for hydropower production as well as flood management. However, the forecast uncertainties can be important and lead to bad decisions such as false alarms and inappropriate reservoir management of hydropower plants. In order to improve the forecasting systems, it is important to discriminate the different sources of uncertainties. To achieve this task, reanalysis of past predictions can be realized and provide information about the structure of the global uncertainty. In order to discriminate between uncertainty due to the weather numerical model and uncertainty due to the rainfall-runoff model, simulations assuming perfect weather forecast must be realized. This contribution presents the spatial analysis of the weather uncertainties and their influence on the river discharge prediction of a few different river basins where an operational forecasting system exists. The forecast is based on the RS 3.0 system [1], [2], which is also running the open Internet platform www.swissrivers.ch [3]. The uncertainty related to the hydrological model is compared to the uncertainty related to the weather prediction. A comparison between numerous weather prediction models [4] at different lead times is also presented. The results highlight an important improving potential of both forecasting components: the hydrological rainfall-runoff model and the numerical weather prediction models. The hydrological processes must be accurately represented during the model calibration procedure, while weather prediction models suffer from a systematic spatial bias. REFERENCES [1] Garcia, J., Jordan, F., Dubois, J. & Boillat, J.-L. 2007. "Routing System II, Modélisation d'écoulements dans des systèmes hydrauliques", Communication LCH n° 32, Ed. Prof. A. Schleiss, Lausanne [2] Jordan, F. 2007. Modèle de prévision et de gestion des crues - optimisation des opérations des aménagements hydroélectriques à accumulation pour la réduction des débits de crue, thèse de doctorat n° 3711, Ecole Polytechnique Fédérale, Lausanne [3] Keller, R. 2009. "Le débit des rivières au peigne fin", Revue Technique Suisse, N°7/8 2009, Swiss engineering RTS, UTS SA, Lausanne, p. 11 [4] Kaufmann, P., Schubiger, F. & Binder, P. 2003. Precipitation forecasting by a mesoscale numerical weather prediction (NWP) model : eight years of experience, Hydrology and Earth System

Results of the eruptive column model inter-comparison study

USGS Publications Warehouse

Costa, Antonio; Suzuki, Yujiro; Cerminara, M.; Devenish, Ben J.; Esposti Ongaro, T.; Herzog, Michael; Van Eaton, Alexa; Denby, L.C.; Bursik, Marcus; de' Michieli Vitturi, Mattia; Engwell, S.; Neri, Augusto; Barsotti, Sara; Folch, Arnau; Macedonio, Giovanni; Girault, F.; Carazzo, G.; Tait, S.; Kaminski, E.; Mastin, Larry G.; Woodhouse, Mark J.; Phillips, Jeremy C.; Hogg, Andrew J.; Degruyter, Wim; Bonadonna, Costanza

2016-01-01

This study compares and evaluates one-dimensional (1D) and three-dimensional (3D) numerical models of volcanic eruption columns in a set of different inter-comparison exercises. The exercises were designed as a blind test in which a set of common input parameters was given for two reference eruptions, representing a strong and a weak eruption column under different meteorological conditions. Comparing the results of the different models allows us to evaluate their capabilities and target areas for future improvement. Despite their different formulations, the 1D and 3D models provide reasonably consistent predictions of some of the key global descriptors of the volcanic plumes. Variability in plume height, estimated from the standard deviation of model predictions, is within ~ 20% for the weak plume and ~ 10% for the strong plume. Predictions of neutral buoyancy level are also in reasonably good agreement among the different models, with a standard deviation ranging from 9 to 19% (the latter for the weak plume in a windy atmosphere). Overall, these discrepancies are in the range of observational uncertainty of column height. However, there are important differences amongst models in terms of local properties along the plume axis, particularly for the strong plume. Our analysis suggests that the simplified treatment of entrainment in 1D models is adequate to resolve the general behaviour of the weak plume. However, it is inadequate to capture complex features of the strong plume, such as large vortices, partial column collapse, or gravitational fountaining that strongly enhance entrainment in the lower atmosphere. We conclude that there is a need to more accurately quantify entrainment rates, improve the representation of plume radius, and incorporate the effects of column instability in future versions of 1D volcanic plume models.

Computation of Sound Generated by Flow Over a Circular Cylinder: An Acoustic Analogy Approach

NASA Technical Reports Server (NTRS)

Brentner, Kenneth S.; Cox, Jared S.; Rumsey, Christopher L.; Younis, Bassam A.

1997-01-01

The sound generated by viscous flow past a circular cylinder is predicted via the Lighthill acoustic analogy approach. The two dimensional flow field is predicted using two unsteady Reynolds-averaged Navier-Stokes solvers. Flow field computations are made for laminar flow at three Reynolds numbers (Re = 1000, Re = 10,000, and Re = 90,000) and two different turbulent models at Re = 90,000. The unsteady surface pressures are utilized by an acoustics code that implements Farassat's formulation 1A to predict the acoustic field. The acoustic code is a 3-D code - 2-D results are found by using a long cylinder length. The 2-D predictions overpredict the acoustic amplitude; however, if correlation lengths in the range of 3 to 10 cylinder diameters are used, the predicted acoustic amplitude agrees well with experiment.

How the venetian blind percept emerges from the laminar cortical dynamics of 3D vision

PubMed Central

Cao, Yongqiang; Grossberg, Stephen

2014-01-01

The 3D LAMINART model of 3D vision and figure-ground perception is used to explain and simulate a key example of the Venetian blind effect and to show how it is related to other well-known perceptual phenomena such as Panum's limiting case. The model proposes how lateral geniculate nucleus (LGN) and hierarchically organized laminar circuits in cortical areas V1, V2, and V4 interact to control processes of 3D boundary formation and surface filling-in that simulate many properties of 3D vision percepts, notably consciously seen surface percepts, which are predicted to arise when filled-in surface representations are integrated into surface-shroud resonances between visual and parietal cortex. Interactions between layers 4, 3B, and 2/3 in V1 and V2 carry out stereopsis and 3D boundary formation. Both binocular and monocular information combine to form 3D boundary and surface representations. Surface contour surface-to-boundary feedback from V2 thin stripes to V2 pale stripes combines computationally complementary boundary and surface formation properties, leading to a single consistent percept, while also eliminating redundant 3D boundaries, and triggering figure-ground perception. False binocular boundary matches are eliminated by Gestalt grouping properties during boundary formation. In particular, a disparity filter, which helps to solve the Correspondence Problem by eliminating false matches, is predicted to be realized as part of the boundary grouping process in layer 2/3 of cortical area V2. The model has been used to simulate the consciously seen 3D surface percepts in 18 psychophysical experiments. These percepts include the Venetian blind effect, Panum's limiting case, contrast variations of dichoptic masking and the correspondence problem, the effect of interocular contrast differences on stereoacuity, stereopsis with polarity-reversed stereograms, da Vinci stereopsis, and perceptual closure. These model mechanisms have also simulated properties of 3D neon color spreading, binocular rivalry, 3D Necker cube, and many examples of 3D figure-ground separation. PMID:25309467

How the venetian blind percept emerges from the laminar cortical dynamics of 3D vision.

PubMed

Cao, Yongqiang; Grossberg, Stephen

2014-01-01

The 3D LAMINART model of 3D vision and figure-ground perception is used to explain and simulate a key example of the Venetian blind effect and to show how it is related to other well-known perceptual phenomena such as Panum's limiting case. The model proposes how lateral geniculate nucleus (LGN) and hierarchically organized laminar circuits in cortical areas V1, V2, and V4 interact to control processes of 3D boundary formation and surface filling-in that simulate many properties of 3D vision percepts, notably consciously seen surface percepts, which are predicted to arise when filled-in surface representations are integrated into surface-shroud resonances between visual and parietal cortex. Interactions between layers 4, 3B, and 2/3 in V1 and V2 carry out stereopsis and 3D boundary formation. Both binocular and monocular information combine to form 3D boundary and surface representations. Surface contour surface-to-boundary feedback from V2 thin stripes to V2 pale stripes combines computationally complementary boundary and surface formation properties, leading to a single consistent percept, while also eliminating redundant 3D boundaries, and triggering figure-ground perception. False binocular boundary matches are eliminated by Gestalt grouping properties during boundary formation. In particular, a disparity filter, which helps to solve the Correspondence Problem by eliminating false matches, is predicted to be realized as part of the boundary grouping process in layer 2/3 of cortical area V2. The model has been used to simulate the consciously seen 3D surface percepts in 18 psychophysical experiments. These percepts include the Venetian blind effect, Panum's limiting case, contrast variations of dichoptic masking and the correspondence problem, the effect of interocular contrast differences on stereoacuity, stereopsis with polarity-reversed stereograms, da Vinci stereopsis, and perceptual closure. These model mechanisms have also simulated properties of 3D neon color spreading, binocular rivalry, 3D Necker cube, and many examples of 3D figure-ground separation.

Modeling the Hot Tensile Flow Behaviors at Ultra-High-Strength Steel and Construction of Three-Dimensional Continuous Interaction Space for Forming Parameters

NASA Astrophysics Data System (ADS)

Quan, Guo-zheng; Zhan, Zong-yang; Wang, Tong; Xia, Yu-feng

2017-01-01

The response of true stress to strain rate, temperature and strain is a complex three-dimensional (3D) issue, and the accurate description of such constitutive relationships significantly contributes to the optimum process design. To obtain the true stress-strain data of ultra-high-strength steel, BR1500HS, a series of isothermal hot tensile tests were conducted in a wide temperature range of 973-1,123 K and a strain rate range of 0.01-10 s-1 on a Gleeble 3800 testing machine. Then the constitutive relationships were modeled by an optimally constructed and well-trained backpropagation artificial neural network (BP-ANN). The evaluation of BP-ANN model revealed that it has admirable performance in characterizing and predicting the flow behaviors of BR1500HS. A comparison on improved Arrhenius-type constitutive equation and BP-ANN model shows that the latter has higher accuracy. Consequently, the developed BP-ANN model was used to predict abundant stress-strain data beyond the limited experimental conditions. Then a 3D continuous interaction space for temperature, strain rate, strain and stress was constructed based on these predicted data. The developed 3D continuous interaction space for hot working parameters contributes to fully revealing the intrinsic relationships of BR1500HS steel.

Azolium analogues as CDK4 inhibitors: Pharmacophore modeling, 3D QSAR study and new lead drug discovery

NASA Astrophysics Data System (ADS)

Rondla, Rohini; Padma Rao, Lavanya Souda; Ramatenki, Vishwanath; Vadija, Rajender; Mukkera, Thirupathi; Potlapally, Sarita Rajender; Vuruputuri, Uma

2017-04-01

The cyclin-dependent kinase 4 (CDK4) enzyme is a key regulator in cell cycle G1 phase progression. It is often overexpressed in variety of cancer cells, which makes it an attractive therapeutic target for cancer treatment. A number of chemical scaffolds have been reported as CDK4 inhibitors in the literature, and in particular azolium scaffolds as potential inhibitors. Here, a ligand based pharmacophore modeling and an atom based 3D-QSAR analyses for a series of azolium based CDK4 inhibitors are presented. A five point pharmacophore hypothesis, i.e. APRRR with one H-bond acceptor (A), one positive cationic feature (P) and three ring aromatic sites (R) is developed, which yielded an atom based 3D-QSAR model that shows an excellent correlation coefficient value- R2 = 0.93, fisher ratio- F = 207, along with good predictive ability- Q2 = 0.79, and Pearson R value = 0.89. The visual inspection of the 3D-QSAR model, with the most active and the least active ligands, demonstrates the favorable and unfavorable structural regions for the activity towards CDK4. The roles of positively charged nitrogen, the steric effect, ligand flexibility, and the substituents on the activity are in good agreement with the previously reported experimental results. The generated 3D QSAR model is further applied as query for a 3D database screening, which identifies 23 lead drug candidates with good predicted activities and diverse scaffolds. The ADME analysis reveals that, the pharmacokinetic parameters of all the identified new leads are within the acceptable range.

Mathematical modeling of serum 13C-retinol in captive rhesus monkeys provides new insights on hypervitaminosis A.

PubMed

Escaron, Anne L; Green, Michael H; Howe, Julie A; Tanumihardjo, Sherry A

2009-10-01

Hypervitaminosis A is increasingly a public health concern, and thus noninvasive quantitative methods merit exploration. In this study, we applied the (13)C-retinol isotope dilution test to a nonhuman primate model with excessive liver stores. After baseline serum chemistries, rhesus macaques (Macaca mulatta; n = 16) were administered 3.5 mumol (13)C(2)-retinyl acetate. Blood was drawn at baseline, 5 h, and 2, 4, 7, 14, 21, and 28 d following the dose. Liver biopsies were collected 7 d before and 2 d after dosing (n = 4) and at 7, 14, and 28 d (n = 4/time) after dosing. Serum and liver were analyzed by HPLC and GC-combustion-isotope ratio MS for retinol and its enrichment, respectively. Model-based compartmental analysis was applied to serum data. Lactate dehydrogenase was elevated in 50% of the monkeys. Total body reserves (TBR) of vitamin A (VA) were calculated at 28 d. Predicted TBR (3.52 +/- 2.01 mmol VA) represented measured liver stores (4.56 +/- 1.38 mmol VA; P = 0.124). Predicted liver VA concentrations (13.3 +/- 9.7 micromol/g) were similar to measured liver VA concentrations (16.4 +/- 5.3 micromol/g). The kinetic models predict that 27-52% of extravascular VA is exchanging with serum in hypervitaminotic A monkeys. The test correctly diagnosed hypervitaminosis A in all monkeys, i.e. 100% sensitivity. Stable isotope techniques have important public health potential for the classification of VA status, including hypervitaminosis, because no other technique besides invasive liver biopsies, correctly identifies excessive liver VA stores.

Comparison of FDNS liquid rocket engine plume computations with SPF/2

NASA Technical Reports Server (NTRS)

Kumar, G. N.; Griffith, D. O., II; Warsi, S. A.; Seaford, C. M.

1993-01-01

Prediction of a plume's shape and structure is essential to the evaluation of base region environments. The JANNAF standard plume flowfield analysis code SPF/2 predicts plumes well, but cannot analyze base regions. Full Navier-Stokes CFD codes can calculate both zones; however, before they can be used, they must be validated. The CFD code FDNS3D (Finite Difference Navier-Stokes Solver) was used to analyze the single plume of a Space Transportation Main Engine (STME) and comparisons were made with SPF/2 computations. Both frozen and finite rate chemistry models were employed as well as two turbulence models in SPF/2. The results indicate that FDNS3D plume computations agree well with SPF/2 predictions for liquid rocket engine plumes.

Predicting vapor liquid equilibria using density functional theory: A case study of argon

NASA Astrophysics Data System (ADS)

Goel, Himanshu; Ling, Sanliang; Ellis, Breanna Nicole; Taconi, Anna; Slater, Ben; Rai, Neeraj

2018-06-01

Predicting vapor liquid equilibria (VLE) of molecules governed by weak van der Waals (vdW) interactions using the first principles approach is a significant challenge. Due to the poor scaling of the post Hartree-Fock wave function theory with system size/basis functions, the Kohn-Sham density functional theory (DFT) is preferred for systems with a large number of molecules. However, traditional DFT cannot adequately account for medium to long range correlations which are necessary for modeling vdW interactions. Recent developments in DFT such as dispersion corrected models and nonlocal van der Waals functionals have attempted to address this weakness with a varying degree of success. In this work, we predict the VLE of argon and assess the performance of several density functionals and the second order Møller-Plesset perturbation theory (MP2) by determining critical and structural properties via first principles Monte Carlo simulations. PBE-D3, BLYP-D3, and rVV10 functionals were used to compute vapor liquid coexistence curves, while PBE0-D3, M06-2X-D3, and MP2 were used for computing liquid density at a single state point. The performance of the PBE-D3 functional for VLE is superior to other functionals (BLYP-D3 and rVV10). At T = 85 K and P = 1 bar, MP2 performs well for the density and structural features of the first solvation shell in the liquid phase.

Development of a 3D finite element acoustic model to predict the sound reduction index of stud based double-leaf walls

NASA Astrophysics Data System (ADS)

Arjunan, A.; Wang, C. J.; Yahiaoui, K.; Mynors, D. J.; Morgan, T.; Nguyen, V. B.; English, M.

2014-11-01

Building standards incorporating quantitative acoustical criteria to ensure adequate sound insulation are now being implemented. Engineers are making great efforts to design acoustically efficient double-wall structures. Accordingly, efficient simulation models to predict the acoustic insulation of double-leaf wall structures are needed. This paper presents the development of a numerical tool that can predict the frequency dependent sound reduction index R of stud based double-leaf walls at one-third-octave band frequency range. A fully vibro-acoustic 3D model consisting of two rooms partitioned using a double-leaf wall, considering the structure and acoustic fluid coupling incorporating the existing fluid and structural solvers are presented. The validity of the finite element (FE) model is assessed by comparison with experimental test results carried out in a certified laboratory. Accurate representation of the structural damping matrix to effectively predict the R values are studied. The possibilities of minimising the simulation time using a frequency dependent mesh model was also investigated. The FEA model presented in this work is capable of predicting the weighted sound reduction index Rw along with A-weighted pink noise C and A-weighted urban noise Ctr within an error of 1 dB. The model developed can also be used to analyse the acoustically induced frequency dependent geometrical behaviour of the double-leaf wall components to optimise them for best acoustic performance. The FE modelling procedure reported in this paper can be extended to other building components undergoing fluid-structure interaction (FSI) to evaluate their acoustic insulation.

Characterization of 3d Contact Kinematics and Prediction of Resonant Response of Structures Having 3d Frictional Constraint

NASA Astrophysics Data System (ADS)

Yang, B. D.; Menq, C. H.

1998-11-01

A 3D friction contact model has been developed for the prediction of the resonant response of structures having 3D frictional constraint. In the proposed model, a contact plane is defined and its orientation is assumed invariant. Consequently, the relative motion of the two contacting surfaces can be resolved into two components: the in-plane tangential motion on the contact plane and the normal component perpendicular to the plane. The in-plane tangential relative motion is often two-dimensional, and it can induce stick-slip friction. On the other hand, the normal relative motion can cause variation of the contact normal load and, in extreme circumstances, separation of the two contacting surfaces. In this study, the joined effect of the 2D tangential relative motion and the normal relative motion on the contact kinematics of a friction contact is examined and analytical criteria are developed to determine the transitions among stick, slip, and separation, when experiencing variable normal load. With these transition criteria, the induced friction force on the contact plane and the variable normal load perpendicular to the plane can be predicted for any given cyclic relative motions at the contact interface and hysteresis loops can be produced so as to characterize the equivalent damping and stiffness of the friction contact. These non-linear damping and stiffness along with the harmonic balance method are then used to predict the resonance of a frictionally constrained 3-DOF oscillator. The predicted results are compared with those of the time integration method and the damping effect, the resonant frequency shift, and the jump phenomenon are examined.

Non-LTE line formation of Fe in late-type stars - III. 3D non-LTE analysis of metal-poor stars

NASA Astrophysics Data System (ADS)

Amarsi, A. M.; Lind, K.; Asplund, M.; Barklem, P. S.; Collet, R.

2016-12-01

As one of the most important elements in astronomy, iron abundance determinations need to be as accurate as possible. We investigate the accuracy of spectroscopic iron abundance analyses using archetypal metal-poor stars. We perform detailed 3D non-LTE radiative transfer calculations based on 3D hydrodynamic STAGGER model atmospheres, and employ a new model atom that includes new quantum-mechanical neutral hydrogen collisional rate coefficients. With the exception of the red giant HD122563, we find that the 3D non-LTE models achieve Fe I/Fe II excitation and ionization balance as well as not having any trends with equivalent width to within modelling uncertainties of 0.05 dex, all without having to invoke any microturbulent broadening; for HD122563 we predict that the current best parallax-based surface gravity is overestimated by 0.5 dex. Using a 3D non-LTE analysis, we infer iron abundances from the 3D model atmospheres that are roughly 0.1 dex higher than corresponding abundances from 1D MARCS model atmospheres; these differences go in the same direction as the non-LTE effects themselves. We make available grids of departure coefficients, equivalent widths and abundance corrections, calculated on 1D MARCS model atmospheres and horizontally and temporally averaged 3D STAGGER model atmospheres.

Use of visible and near-infrared spectroscopy to predict pork longissimus lean color stability.

PubMed

King, D A; Shackelford, S D; Wheeler, T L

2011-12-01

This study evaluated the use of visible and near-infrared (VISNIR) spectroscopy to predict lean color stability in pork loin chops. Spectra were collected immediately after and approximately 1 h after rib removal on 1,208 loins. Loins were aged for 14 d before a 2.54-cm chop was placed in simulated retail display. Spectra were collected on aged loins immediately after removal from the vacuum package and on chops 10 min after cutting. Instrumental color measurements [L*, a*, b*, hue angle, chroma, and E (overall color change)] were determined on d 0, 1, 7, 11, and 14 of display. Principal components analysis of display d 0 and 14 values of these traits identified a factor (first principal component; PC1) explaining 67% of the variance that was related to color change. Partial least squares regression was used to develop 3 models to predict PC1 values by using VISNIR spectra collected in the plant, on aged loins, and on chops. Loins with predicted PC1 values less than 0 were classified as having a stable color, whereas values greater than 0 were classified as having a labile lean color. Loins classified as stable by the in-plant model had smaller (P < 0.05) L* values than those classified as labile. Hue angle and ΔE values were less (P < 0.05) and a* and chroma values were greater (P < 0.05) after d 7 of display in loins predicted to have a stable color than in loins predicted to have a labile lean color. Similarly, chops from loins classified as stable using the aged loin model had smaller (P < 0.05) L* values than those from loins classified as labile. Furthermore, loins predicted to be stable had smaller (P < 0.05) hue angle and ΔE values and greater (P < 0.05) a* and chroma values after d 7 of display than did loins predicted to be labile. Results for the chop model were similar to those from the 2 loin models. Chops predicted to have a stable lean color had smaller (P < 0.05) L* values than did those predicted to have a labile lean color. Chops classified as stable had smaller (P < 0.05) hue angle and ΔE values and greater (P < 0.05) a* and chroma values after d 7 of display compared with chops classified as labile. All 3 models effectively segregated chops based on color stability, particularly with regard to redness. Regardless of the model being used, d 14 display values for a*, hue angle, and ΔE in loins classified as stable were similar to the d 7 values of loins classified as labile. Thus, these results suggest that VISNIR spectroscopy would be an effective technology for sorting pork loins with regard to lean color stability.

Site-specific strong ground motion prediction using 2.5-D modelling

NASA Astrophysics Data System (ADS)

Narayan, J. P.

2001-08-01

An algorithm was developed using the 2.5-D elastodynamic wave equation, based on the displacement-stress relation. One of the most significant advantages of the 2.5-D simulation is that the 3-D radiation pattern can be generated using double-couple point shear-dislocation sources in the 2-D numerical grid. A parsimonious staggered grid scheme was adopted instead of the standard staggered grid scheme, since this is the only scheme suitable for computing the dislocation. This new 2.5-D numerical modelling avoids the extensive computational cost of 3-D modelling. The significance of this exercise is that it makes it possible to simulate the strong ground motion (SGM), taking into account the energy released, 3-D radiation pattern, path effects and local site conditions at any location around the epicentre. The slowness vector (py) was used in the supersonic region for each layer, so that all the components of the inertia coefficient are positive. The double-couple point shear-dislocation source was implemented in the numerical grid using the moment tensor components as the body-force couples. The moment per unit volume was used in both the 3-D and 2.5-D modelling. A good agreement in the 3-D and 2.5-D responses for different grid sizes was obtained when the moment per unit volume was further reduced by a factor equal to the finite-difference grid size in the case of the 2.5-D modelling. The components of the radiation pattern were computed in the xz-plane using 3-D and 2.5-D algorithms for various focal mechanisms, and the results were in good agreement. A comparative study of the amplitude behaviour of the 3-D and 2.5-D wavefronts in a layered medium reveals the spatial and temporal damped nature of the 2.5-D elastodynamic wave equation. 3-D and 2.5-D simulated responses at a site using a different strike direction reveal that strong ground motion (SGM) can be predicted just by rotating the strike of the fault counter-clockwise by the same amount as the azimuth of the site with respect to the epicentre. This adjustment is necessary since the response is computed keeping the epicentre, focus and the desired site in the same xz-plane, with the x-axis pointing in the north direction.

Mathematical Modeling of Serum 13C-Retinol in Captive Rhesus Monkeys Provides New Insights on Hypervitaminosis A1–3

PubMed Central

Escaron, Anne L.; Green, Michael H.; Howe, Julie A.; Tanumihardjo, Sherry A.

2009-01-01

Hypervitaminosis A is increasingly a public health concern, and thus noninvasive quantitative methods merit exploration. In this study, we applied the 13C-retinol isotope dilution test to a nonhuman primate model with excessive liver stores. After baseline serum chemistries, rhesus macaques (Macaca mulatta; n = 16) were administered 3.5 μmol 13C2-retinyl acetate. Blood was drawn at baseline, 5 h, and 2, 4, 7, 14, 21, and 28 d following the dose. Liver biopsies were collected 7 d before and 2 d after dosing (n = 4) and at 7, 14, and 28 d (n = 4/time) after dosing. Serum and liver were analyzed by HPLC and GC-combustion-isotope ratio MS for retinol and its enrichment, respectively. Model-based compartmental analysis was applied to serum data. Lactate dehydrogenase was elevated in 50% of the monkeys. Total body reserves (TBR) of vitamin A (VA) were calculated at 28 d. Predicted TBR (3.52 ± 2.01 mmol VA) represented measured liver stores (4.56 ± 1.38 mmol VA; P = 0.124). Predicted liver VA concentrations (13.3 ± 9.7 μmol/g) were similar to measured liver VA concentrations (16.4 ± 5.3 μmol/g). The kinetic models predict that 27–52% of extravascular VA is exchanging with serum in hypervitaminotic A monkeys. The test correctly diagnosed hypervitaminosis A in all monkeys, i.e. 100% sensitivity. Stable isotope techniques have important public health potential for the classification of VA status, including hypervitaminosis, because no other technique besides invasive liver biopsies, correctly identifies excessive liver VA stores. PMID:19710158

Predictors of High-Grade Esophagitis after Definitive 3D Conformal Therapy, Intensity Modulated Radiation Therapy, or Proton Beam Therapy for Non-Small Cell Lung Cancer

PubMed Central

Gomez, Daniel R.; Tucker, Susan L.; Martel, Mary K.; Mohan, Radhe; Balter, Peter A.; Guerra, Jose Luis Lopez; Liu, Hongmei; Komaki, Ritsuko; Cox, James D.; Liao, Zhongxing

2014-01-01

Introduction We analyzed the ability of various patient- and treatment-related factors to predict radiation-induced esophagitis (RE) in patients with non-small cell lung cancer (NSCLC) treated with three-dimensional (3D) conformal radiation therapy (3D-CRT), intensity-modulated radiation therapy (IMRT), or proton beam therapy (PBT). Methods and Materials Patients were treated for NSCLC with 3D-CRT, IMRT, or PBT at MD Anderson from 2000 to 2008 and had full dose-volume histogram (DVH) data available. The endpoint was severe (grade ≥3) RE. The Lyman-Kutcher-Burman (LKB) model was used to analyze RE as a function of the fractional esophageal DVH, with clinical variables included as dose-modifying factors. Results Overall, 652 patients were included: 405 treated with 3D-CRT, 139 with IMRT, and 108 with PBT; corresponding rates of grade ≥3 RE were 8%, 28%, and 6%, with a median time to onset of 42 days (range 11–93 days). A fit of the fractional-DVH LKB model demonstrated that the volume parameter n was significantly different (p=0.046) than 1, indicating that high doses to small volumes are more predictive than mean esophageal dose. The model fit was better for 3D-CRT and PBT than for IMRT. Including receipt of concurrent chemotherapy as a dose-modifying factor significantly improved the LKB model (p=0.005), and the model was further improved by including a variable representing treatment with >30 fractions. Examining individual types of chemotherapy agents revealed a trend toward receipt of concurrent taxanes and increased risk of RE (p=0.105). Conclusions The fractional dose (dose rate) and number of fractions (total dose) distinctly affect the risk of severe RE estimated using the LKB model, and concurrent chemotherapy improves the model fit. This risk of severe RE is underestimated by this model in patients receiving IMRT. PMID:22920974

Tests of Predictions of the Algebraic Cluster Model: the Triangular D 3h Symmetry of 12C

NASA Astrophysics Data System (ADS)

Gai, Moshe

2016-07-01

A new theoretical approach to clustering in the frame of the Algebraic Cluster Model (ACM) has been developed. It predicts rotation-vibration structure with rotational band of an oblate equilateral triangular symmetric spinning top with a D 3h symmetry characterized by the sequence of states: 0+, 2+, 3-, 4±, 5- with a degenerate 4+ and 4- (parity doublet) states. Our measured new 2+ 2 in 12C allows the first study of rotation-vibration structure in 12C. The newly measured 5- state and 4- states fit very well the predicted ground state rotational band structure with the predicted sequence of states: 0+, 2+, 3-, 4±, 5- with almost degenerate 4+ and 4- (parity doublet) states. Such a D 3h symmetry is characteristic of triatomic molecules, but it is observed in the ground state rotational band of 12C for the first time in a nucleus. We discuss predictions of the ACM of other rotation-vibration bands in 12 C such as the (0+) Hoyle band and the (1-) bending mode with prediction of (“missing 3- and 4-”) states that may shed new light on clustering in 12C and light nuclei. In particular, the observation (or non observation) of the predicted (“missing”) states in the Hoyle band will allow us to conclude the geometrical arrangement of the three alpha particles composing the Hoyle state at 7.6542 MeV in 12C. We discuss proposed research programs at the Darmstadt S-DALINAC and at the newly constructed ELI-NP facility near Bucharest to test the predictions of the ACM in isotopes of carbon.

Can Mapping Algorithms Based on Raw Scores Overestimate QALYs Gained by Treatment? A Comparison of Mappings Between the Roland-Morris Disability Questionnaire and the EQ-5D-3L Based on Raw and Differenced Score Data.

PubMed

Madan, Jason; Khan, Kamran A; Petrou, Stavros; Lamb, Sarah E

2017-05-01

Mapping algorithms are increasingly being used to predict health-utility values based on responses or scores from non-preference-based measures, thereby informing economic evaluations. We explored whether predictions in the EuroQol 5-dimension 3-level instrument (EQ-5D-3L) health-utility gains from mapping algorithms might differ if estimated using differenced versus raw scores, using the Roland-Morris Disability Questionnaire (RMQ), a widely used health status measure for low back pain, as an example. We estimated algorithms mapping within-person changes in RMQ scores to changes in EQ-5D-3L health utilities using data from two clinical trials with repeated observations. We also used logistic regression models to estimate response mapping algorithms from these data to predict within-person changes in responses to each EQ-5D-3L dimension from changes in RMQ scores. Predicted health-utility gains from these mappings were compared with predictions based on raw RMQ data. Using differenced scores reduced the predicted health-utility gain from a unit decrease in RMQ score from 0.037 (standard error [SE] 0.001) to 0.020 (SE 0.002). Analysis of response mapping data suggests that the use of differenced data reduces the predicted impact of reducing RMQ scores across EQ-5D-3L dimensions and that patients can experience health-utility gains on the EQ-5D-3L 'usual activity' dimension independent from improvements captured by the RMQ. Mappings based on raw RMQ data overestimate the EQ-5D-3L health utility gains from interventions that reduce RMQ scores. Where possible, mapping algorithms should reflect within-person changes in health outcome and be estimated from datasets containing repeated observations if they are to be used to estimate incremental health-utility gains.

Improved Prediction of Blood-Brain Barrier Permeability Through Machine Learning with Combined Use of Molecular Property-Based Descriptors and Fingerprints.

PubMed

Yuan, Yaxia; Zheng, Fang; Zhan, Chang-Guo

2018-03-21

Blood-brain barrier (BBB) permeability of a compound determines whether the compound can effectively enter the brain. It is an essential property which must be accounted for in drug discovery with a target in the brain. Several computational methods have been used to predict the BBB permeability. In particular, support vector machine (SVM), which is a kernel-based machine learning method, has been used popularly in this field. For SVM training and prediction, the compounds are characterized by molecular descriptors. Some SVM models were based on the use of molecular property-based descriptors (including 1D, 2D, and 3D descriptors) or fragment-based descriptors (known as the fingerprints of a molecule). The selection of descriptors is critical for the performance of a SVM model. In this study, we aimed to develop a generally applicable new SVM model by combining all of the features of the molecular property-based descriptors and fingerprints to improve the accuracy for the BBB permeability prediction. The results indicate that our SVM model has improved accuracy compared to the currently available models of the BBB permeability prediction.

Protein structure modeling and refinement by global optimization in CASP12.

PubMed

Hong, Seung Hwan; Joung, InSuk; Flores-Canales, Jose C; Manavalan, Balachandran; Cheng, Qianyi; Heo, Seungryong; Kim, Jong Yun; Lee, Sun Young; Nam, Mikyung; Joo, Keehyoung; Lee, In-Ho; Lee, Sung Jong; Lee, Jooyoung

2018-03-01

For protein structure modeling in the CASP12 experiment, we have developed a new protocol based on our previous CASP11 approach. The global optimization method of conformational space annealing (CSA) was applied to 3 stages of modeling: multiple sequence-structure alignment, three-dimensional (3D) chain building, and side-chain re-modeling. For better template selection and model selection, we updated our model quality assessment (QA) method with the newly developed SVMQA (support vector machine for quality assessment). For 3D chain building, we updated our energy function by including restraints generated from predicted residue-residue contacts. New energy terms for the predicted secondary structure and predicted solvent accessible surface area were also introduced. For difficult targets, we proposed a new method, LEEab, where the template term played a less significant role than it did in LEE, complemented by increased contributions from other terms such as the predicted contact term. For TBM (template-based modeling) targets, LEE performed better than LEEab, but for FM targets, LEEab was better. For model refinement, we modified our CASP11 molecular dynamics (MD) based protocol by using explicit solvents and tuning down restraint weights. Refinement results from MD simulations that used a new augmented statistical energy term in the force field were quite promising. Finally, when using inaccurate information (such as the predicted contacts), it was important to use the Lorentzian function for which the maximal penalty arising from wrong information is always bounded. © 2017 Wiley Periodicals, Inc.

Filtered sub-grid constitutive models for fluidized gas-particle flows constructed from 3-D simulations

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

Sarkar, Avik; Milioli, Fernando E.; Ozarkar, Shailesh

2016-10-01

The accuracy of fluidized-bed CFD predictions using the two-fluid model can be improved significantly, even when using coarse grids, by replacing the microscopic kinetic-theory-based closures with coarse-grained constitutive models. These coarse-grained constitutive relationships, called filtered models, account for the unresolved gas-particle structures (clusters and bubbles) via sub-grid corrections. Following the previous 2-D approaches of Igci et al. [AIChE J., 54(6), 1431-1448, 2008] and Milioli et al. [AIChE J., 59(9), 3265-3275, 2013], new filtered models are constructed from highly-resolved 3-D simulations of gas-particle flows. Although qualitatively similar to the older 2-D models, the new 3-D relationships exhibit noticeable quantitative and functionalmore » differences. In particular, the filtered stresses are strongly dependent on the gas-particle slip velocity. Closures for the filtered inter-phase drag, gas- and solids-phase pressures and viscosities are reported. A new model for solids stress anisotropy is also presented. These new filtered 3-D constitutive relationships are better suited to practical coarse-grid 3-D simulations of large, commercial-scale devices.« less

Polymer physics predicts the effects of structural variants on chromatin architecture.

PubMed

Bianco, Simona; Lupiáñez, Darío G; Chiariello, Andrea M; Annunziatella, Carlo; Kraft, Katerina; Schöpflin, Robert; Wittler, Lars; Andrey, Guillaume; Vingron, Martin; Pombo, Ana; Mundlos, Stefan; Nicodemi, Mario

2018-05-01

Structural variants (SVs) can result in changes in gene expression due to abnormal chromatin folding and cause disease. However, the prediction of such effects remains a challenge. Here we present a polymer-physics-based approach (PRISMR) to model 3D chromatin folding and to predict enhancer-promoter contacts. PRISMR predicts higher-order chromatin structure from genome-wide chromosome conformation capture (Hi-C) data. Using the EPHA4 locus as a model, the effects of pathogenic SVs are predicted in silico and compared to Hi-C data generated from mouse limb buds and patient-derived fibroblasts. PRISMR deconvolves the folding complexity of the EPHA4 locus and identifies SV-induced ectopic contacts and alterations of 3D genome organization in homozygous or heterozygous states. We show that SVs can reconfigure topologically associating domains, thereby producing extensive rewiring of regulatory interactions and causing disease by gene misexpression. PRISMR can be used to predict interactions in silico, thereby providing a tool for analyzing the disease-causing potential of SVs.

An integrated geophysical study of the lithospheric structure beneath Libya

NASA Astrophysics Data System (ADS)

Brown, Wesley A.

This doctoral dissertation constitutes an integrated geophysical investigation of the lithospheric structure in the region of Libya. It is separated into three sections, each of which will be submitted to different scientific journals for publication. In the first part of the study, I utilized a seamless mosaicking approach based on the commercial Environment for Visualizing Images (ENVI) software package to create mosaics of two geologically interesting portions of Libya. In this study I present a step by step method of mosaicking Landsat 4 satellite images. Firstly, I performed histogram matching to give images the same color scale, then I used a cutline feathering technique to blend suture areas and finally I overlaid the images to form the two mosaics. The resulting mosaics were then combined with structural features and the seismicity map of the area. The resulting mosaics were proven to be useful in identifying recently active faults and shows great potential for verification of other faults and in natural hazard assessment. For the second portion of my research, I made use of over 6,000 free air corrected gravity data in conjunction with other geological and geophysical data to develop a 3D density model for northern Libya. I used a gravity modeling program (SURFGRAV) to develop the 3D density model by manipulating it to accurately predict large areas of Free Air anomaly shown in the data. The residual gravity anomaly values were calculated by subtracting predicted Free Air anomaly from the observed Free Air anomaly. The results were satisfactory for uplifted areas of Libya while there were significant mismatches in basin areas. The density model was iterated and used as a starting model for the final portion of the study. In the last part of this research, I used the Nafe-Drake relationship along with other geological data to convert the 3D density model to a 3D velocity model (LIBYA3D) for the region. Two earthquakes having source receiver paths sampling much of the modeled area were used to perform 1D and 1.5D validation tests, and the results were compared to those from previous studies. The results showed that the new 3D velocity model is valid and superior to the global model. However, until there is sufficient earthquake data acquired, and we are able to perform 2D and 3D modeling we may not be able to see the true improvement of LIBYA3D as compared to the other regional models.

Comparative modeling of biological nutrient removal from landfill leachate using a circulating fluidized bed bioreactor (CFBBR).

PubMed

Eldyasti, Ahmed; Andalib, Mehran; Hafez, Hisham; Nakhla, George; Zhu, Jesse

2011-03-15

Steady state operational data from a pilot scale circulating fluidized bed bioreactor (CFBBR) during biological treatment of landfill leachate, at empty bed contact times (EBCTs) of 0.49, and 0.41 d and volumetric nutrients loading rates of 2.2-2.6 kg COD/(m(3)d), 0.7-0.8 kg N/(m(3)d), and 0.014-0.016 kg P/(m(3)d), was used to calibrate and compare developed process models in BioWin(®) and AQUIFAS(®). BioWin(®) and AQUIFAS(®) were both capable of predicting most of the performance parameters such as effluent TKN, NH(4)-N, NO(3)-N, TP, PO(4)-P, TSS, and VSS with an average percentage error (APE) of 0-20%. BioWin(®) underpredicted the effluent BOD and SBOD values for various runs by 80% while AQUIFAS(®) predicted effluent BOD and SBOD with an APE of 50%. Although both calibrated models, confirmed the advantages of the CFBBR technology in treating the leachate of high volumetric loading and low biomass yields due to the long solid retention time (SRT), both BioWin(®) and AQUIFAS(®) predicted the total biomass and SRT of CFBBR based on active biomass only, whereas in the CFBBR runs both active as well as inactive biomass accumulated. Copyright © 2011 Elsevier B.V. All rights reserved.

3-D residual eddy current field characterisation: applied to diffusion weighted magnetic resonance imaging.

PubMed

O'Brien, Kieran; Daducci, Alessandro; Kickler, Nils; Lazeyras, Francois; Gruetter, Rolf; Feiweier, Thorsten; Krueger, Gunnar

2013-08-01

Clinical use of the Stejskal-Tanner diffusion weighted images is hampered by the geometric distortions that result from the large residual 3-D eddy current field induced. In this work, we aimed to predict, using linear response theory, the residual 3-D eddy current field required for geometric distortion correction based on phantom eddy current field measurements. The predicted 3-D eddy current field induced by the diffusion-weighting gradients was able to reduce the root mean square error of the residual eddy current field to ~1 Hz. The model's performance was tested on diffusion weighted images of four normal volunteers, following distortion correction, the quality of the Stejskal-Tanner diffusion-weighted images was found to have comparable quality to image registration based corrections (FSL) at low b-values. Unlike registration techniques the correction was not hindered by low SNR at high b-values, and results in improved image quality relative to FSL. Characterization of the 3-D eddy current field with linear response theory enables the prediction of the 3-D eddy current field required to correct eddy current induced geometric distortions for a wide range of clinical and high b-value protocols.

Numerical investigations on cavitation intensity for 3D homogeneous unsteady viscous flows

NASA Astrophysics Data System (ADS)

Leclercq, C.; Archer, A.; Fortes-Patella, R.

2016-11-01

The cavitation erosion remains an industrial issue. In this paper, we deal with the cavitation intensity which can be described as the aggressiveness - or erosive capacity - of a cavitating flow. The estimation of this intensity is a challenging problem both in terms of modelling the cavitating flow and predicting the erosion due to cavitation. For this purpose, a model was proposed to estimate cavitation intensity from 3D unsteady cavitating flow simulations. An intensity model based on pressure and void fraction derivatives was developped and applied to a NACA 65012 hydrofoil tested at LMH-EPFL (École Polytechnique Fédérale de Lausanne) [1]. 2D and 3D unsteady cavitating simulations were performed using a homogeneous model with void fraction transport equation included in Code_Saturne with cavitating module [2]. The article presents a description of the numerical code and the physical approach considered. Comparisons between 2D and 3D simulations, as well as between numerical and experimental results obtained by pitting tests, are analyzed in the paper.

Data-driven high-throughput prediction of the 3-D structure of small molecules: review and progress. A response to the letter by the Cambridge Crystallographic Data Centre.

PubMed

Baldi, Pierre

2011-12-27

A response is presented to sentiments expressed in "Data-Driven High-Throughput Prediction of the 3-D Structure of Small Molecules: Review and Progress. A Response from The Cambridge Crystallographic Data Centre", recently published in the Journal of Chemical Information and Modeling, (1) which may give readers a misleading impression regarding significant impediments to scientific research posed by the CCDC.

RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures

PubMed Central

Miao, Zhichao; Adamiak, Ryszard W.; Blanchet, Marc-Frédérick; Boniecki, Michal; Bujnicki, Janusz M.; Chen, Shi-Jie; Cheng, Clarence; Chojnowski, Grzegorz; Chou, Fang-Chieh; Cordero, Pablo; Cruz, José Almeida; Ferré-D'Amaré, Adrian R.; Das, Rhiju; Ding, Feng; Dokholyan, Nikolay V.; Dunin-Horkawicz, Stanislaw; Kladwang, Wipapat; Krokhotin, Andrey; Lach, Grzegorz; Magnus, Marcin; Major, François; Mann, Thomas H.; Masquida, Benoît; Matelska, Dorota; Meyer, Mélanie; Peselis, Alla; Popenda, Mariusz; Purzycka, Katarzyna J.; Serganov, Alexander; Stasiewicz, Juliusz; Szachniuk, Marta; Tandon, Arpit; Tian, Siqi; Wang, Jian; Xiao, Yi; Xu, Xiaojun; Zhang, Jinwei; Zhao, Peinan; Zok, Tomasz; Westhof, Eric

2015-01-01

This paper is a report of a second round of RNA-Puzzles, a collective and blind experiment in three-dimensional (3D) RNA structure prediction. Three puzzles, Puzzles 5, 6, and 10, represented sequences of three large RNA structures with limited or no homology with previously solved RNA molecules. A lariat-capping ribozyme, as well as riboswitches complexed to adenosylcobalamin and tRNA, were predicted by seven groups using RNAComposer, ModeRNA/SimRNA, Vfold, Rosetta, DMD, MC-Fold, 3dRNA, and AMBER refinement. Some groups derived models using data from state-of-the-art chemical-mapping methods (SHAPE, DMS, CMCT, and mutate-and-map). The comparisons between the predictions and the three subsequently released crystallographic structures, solved at diffraction resolutions of 2.5–3.2 Å, were carried out automatically using various sets of quality indicators. The comparisons clearly demonstrate the state of present-day de novo prediction abilities as well as the limitations of these state-of-the-art methods. All of the best prediction models have similar topologies to the native structures, which suggests that computational methods for RNA structure prediction can already provide useful structural information for biological problems. However, the prediction accuracy for non-Watson–Crick interactions, key to proper folding of RNAs, is low and some predicted models had high Clash Scores. These two difficulties point to some of the continuing bottlenecks in RNA structure prediction. All submitted models are available for download at http://ahsoka.u-strasbg.fr/rnapuzzles/. PMID:25883046

Comparison of in situ microstructure measurements to different turbulence closure schemes in a 3-D numerical ocean circulation model

NASA Astrophysics Data System (ADS)

Costa, Andrea; Doglioli, Andrea M.; Marsaleix, Patrick; Petrenko, Anne A.

2017-12-01

In situ measurements of kinetic energy dissipation rate ε and estimates of eddy viscosity KZ from the Gulf of Lion (NW Mediterranean Sea) are used to assess the ability of k - ɛ and k - ℓ closure schemes to predict microscale turbulence in a 3-D numerical ocean circulation model. Two different surface boundary conditions are considered in order to investigate their influence on each closure schemes' performance. The effect of two types of stability functions and optical schemes on the k - ɛ scheme is also explored. Overall, the 3-D model predictions are much closer to the in situ data in the surface mixed layer as opposed to below it. Above the mixed layer depth, we identify one model's configuration that outperforms all the other ones. Such a configuration employs a k - ɛ scheme with Canuto A stability functions, surface boundary conditions parameterizing wave breaking and an appropriate photosynthetically available radiation attenuation length. Below the mixed layer depth, reliability is limited by the model's resolution and the specification of a hard threshold on the minimum turbulent kinetic energy.

Handbook of Analytical Methods for Textile Composites

NASA Technical Reports Server (NTRS)

Cox, Brian N.; Flanagan, Gerry

1997-01-01

The purpose of this handbook is to introduce models and computer codes for predicting the properties of textile composites. The handbook includes several models for predicting the stress-strain response all the way to ultimate failure; methods for assessing work of fracture and notch sensitivity; and design rules for avoiding certain critical mechanisms of failure, such as delamination, by proper textile design. The following textiles received some treatment: 2D woven, braided, and knitted/stitched laminates and 3D interlock weaves, and braids.

The Effect of 3D Computer Modeling and Observation-Based Instruction on the Conceptual Change regarding Basic Concepts of Astronomy in Elementary School Students

ERIC Educational Resources Information Center

Kucukozer, Huseyin; Korkusuz, M. Emin; Kucukozer, H. Asuman; Yurumezoglu, Kemal

2009-01-01

This study has examined the impact of teaching certain basic concepts of astronomy through a predict-observe-explain strategy, which includes three-dimensional (3D) computer modeling and observations on conceptual changes seen in sixth-grade elementary school children (aged 11-13; number of students: 131). A pre- and postastronomy instruction…

Validation and pharmacological characterisation of MK-801-induced locomotor hyperactivity in BALB/C mice as an assay for detection of novel antipsychotics.

PubMed

Bradford, Andrea M; Savage, Kevin M; Jones, Declan N C; Kalinichev, Mikhail

2010-10-01

We evaluated locomotor hyperactivity induced in BALB/C mice by an N-methyl-D-aspartate receptor antagonist MK-801 as an assay for the detection of antipsychotic drugs. We assessed the effects of antipsychotic drugs to validate the assay (study 1), selective dopamine and serotonin ligands for pharmacological characterisation of the model (study 2) and a number of compounds with efficacy in models of schizophrenia to understand the predictive validity of the model (study 3). Adult males (n  = 9/group) were pretreated with a test compound, habituated to locomotor activity cages before receiving MK-801 (0.32 mg/kg) and activity recorded for a further 75 or 120 min. In study 1, we tested haloperidol, clozapine, olanzapine, risperidone, ziprasidone, aripiprazole, sertindole and quetiapine. In study 2, we tested SCH23390 (D(1) antagonist), sulpiride (D(2)/D(3) antagonist), raclopride (D(2)/D(3) antagonist), SB-277011 (D(3) antagonist), L-745,870 (D(4) antagonist), WAY100635 (5-HT(1A) antagonist), 8-OH-DPAT (5-HT(1A) agonist), ketanserin (5-HT(2A)/5-HT(2C) antagonist) and SB-242084 (5-HT(2C) antagonist). In study 3, we tested xanomeline (M(1)/M(4) receptor agonist), LY379268 (mGluR2/3 receptor agonist), diazepam (GABA(A) modulator) and thioperamide (H(3) receptor antagonist). All antipsychotics suppressed MK-801-induced hyperactivity in a dose-dependent and specific manner. The effects of antipsychotics appear to be mediated via dopamine D(1), D(2) and 5-HT(2) receptors. Xanomeline, LY379268 and diazepam were active in this assay while thioperamide was not. MK-801-induced hyperactivity in BALB/C mice model of positive symptoms has shown predictive validity with novel compounds acing at M(1)/M(4), mGluR2/3 and GABA(A) receptors and can be used as a screening assay for detection of novel pharmacotherapies targeting those receptors.

Modeling the influence of coupled mass transfer processes on mass flux downgradient of heterogeneous DNAPL source zones

NASA Astrophysics Data System (ADS)

Yang, Lurong; Wang, Xinyu; Mendoza-Sanchez, Itza; Abriola, Linda M.

2018-04-01

Sequestered mass in low permeability zones has been increasingly recognized as an important source of organic chemical contamination that acts to sustain downgradient plume concentrations above regulated levels. However, few modeling studies have investigated the influence of this sequestered mass and associated (coupled) mass transfer processes on plume persistence in complex dense nonaqueous phase liquid (DNAPL) source zones. This paper employs a multiphase flow and transport simulator (a modified version of the modular transport simulator MT3DMS) to explore the two- and three-dimensional evolution of source zone mass distribution and near-source plume persistence for two ensembles of highly heterogeneous DNAPL source zone realizations. Simulations reveal the strong influence of subsurface heterogeneity on the complexity of DNAPL and sequestered (immobile/sorbed) mass distribution. Small zones of entrapped DNAPL are shown to serve as a persistent source of low concentration plumes, difficult to distinguish from other (sorbed and immobile dissolved) sequestered mass sources. Results suggest that the presence of DNAPL tends to control plume longevity in the near-source area; for the examined scenarios, a substantial fraction (43.3-99.2%) of plume life was sustained by DNAPL dissolution processes. The presence of sorptive media and the extent of sorption non-ideality are shown to greatly affect predictions of near-source plume persistence following DNAPL depletion, with plume persistence varying one to two orders of magnitude with the selected sorption model. Results demonstrate the importance of sorption-controlled back diffusion from low permeability zones and reveal the importance of selecting the appropriate sorption model for accurate prediction of plume longevity. Large discrepancies for both DNAPL depletion time and plume longevity were observed between 2-D and 3-D model simulations. Differences between 2- and 3-D predictions increased in the presence of sorption, especially for the case of non-ideal sorption, demonstrating the limitations of employing 2-D predictions for field-scale modeling.

Numerical Calculations of 3-D High-Lift Flows and Comparison with Experiment

NASA Technical Reports Server (NTRS)

Compton, William B, III

2015-01-01

Solutions were obtained with the Navier-Stokes CFD code TLNS3D to predict the flow about the NASA Trapezoidal Wing, a high-lift wing composed of three elements: the main-wing element, a deployed leading-edge slat, and a deployed trailing-edge flap. Turbulence was modeled by the Spalart-Allmaras one-equation turbulence model. One case with massive separation was repeated using Menter's two-equation SST (Menter's Shear Stress Transport) k-omega turbulence model in an attempt to improve the agreement with experiment. The investigation was conducted at a free stream Mach number of 0.2, and at angles of attack ranging from 10.004 degrees to 34.858 degrees. The Reynolds number based on the mean aerodynamic chord of the wing was 4.3 x 10 (sup 6). Compared to experiment, the numerical procedure predicted the surface pressures very well at angles of attack in the linear range of the lift. However, computed maximum lift was 5% low. Drag was mainly under predicted. The procedure correctly predicted several well-known trends and features of high-lift flows, such as off-body separation. The two turbulence models yielded significantly different solutions for the repeated case.

Prediction of internal dosimetry and toxicity of volatile chemicals in rats using physiologically based pharmacokinetic modeling: carbon tetrachloride as a model compound

EPA Science Inventory

Prediction of internal dosimetry and toxicity of volatile chemicals in rats using physiologically based pharmacokinetic modeling: carbon tetrachloride as a model compound D.N. Williams1, J.E. Simmons2, J.V. Bruckner3, and M.V. Evans2 1ORISE, Oak Ridge, TN 37831-0117; 2US EPA/ORD/...

Identifying novel sequence variants of RNA 3D motifs

PubMed Central

Zirbel, Craig L.; Roll, James; Sweeney, Blake A.; Petrov, Anton I.; Pirrung, Meg; Leontis, Neocles B.

2015-01-01

Predicting RNA 3D structure from sequence is a major challenge in biophysics. An important sub-goal is accurately identifying recurrent 3D motifs from RNA internal and hairpin loop sequences extracted from secondary structure (2D) diagrams. We have developed and validated new probabilistic models for 3D motif sequences based on hybrid Stochastic Context-Free Grammars and Markov Random Fields (SCFG/MRF). The SCFG/MRF models are constructed using atomic-resolution RNA 3D structures. To parameterize each model, we use all instances of each motif found in the RNA 3D Motif Atlas and annotations of pairwise nucleotide interactions generated by the FR3D software. Isostericity relations between non-Watson–Crick basepairs are used in scoring sequence variants. SCFG techniques model nested pairs and insertions, while MRF ideas handle crossing interactions and base triples. We use test sets of randomly-generated sequences to set acceptance and rejection thresholds for each motif group and thus control the false positive rate. Validation was carried out by comparing results for four motif groups to RMDetect. The software developed for sequence scoring (JAR3D) is structured to automatically incorporate new motifs as they accumulate in the RNA 3D Motif Atlas when new structures are solved and is available free for download. PMID:26130723

Three-Dimensional Mapping of Soil Chemical Characteristics at Micrometric Scale by Combining 2D SEM-EDX Data and 3D X-Ray CT Images.

PubMed

Hapca, Simona; Baveye, Philippe C; Wilson, Clare; Lark, Richard Murray; Otten, Wilfred

2015-01-01

There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R2 value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented in this study can be easily adapted and applied to other types of data such as bacterial or fungal population densities for the 3D characterization of microbial distribution.

Three-Dimensional Mapping of Soil Chemical Characteristics at Micrometric Scale by Combining 2D SEM-EDX Data and 3D X-Ray CT Images

PubMed Central

Hapca, Simona; Baveye, Philippe C.; Wilson, Clare; Lark, Richard Murray; Otten, Wilfred

2015-01-01

There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R2 value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented in this study can be easily adapted and applied to other types of data such as bacterial or fungal population densities for the 3D characterization of microbial distribution. PMID:26372473

3D-QSAR studies on 1,2,4-triazolyl 5-azaspiro [2.4]-heptanes as D3R antagonists

NASA Astrophysics Data System (ADS)

Zhang, Xin; Zhang, Hui

2018-07-01

Dopamine D3 receptor has become an attractive target in the treatment of abused drugs. 3D-QSAR studies were performed on a novel series of D3 receptor antagonists, 1,2,4-triazolyl 5-azaspiro [2.4]-heptanes, using CoMFA and CoMSIA methods. Two predictive 3D-QSAR models have been generated for the modified design of D3R antagonists. Based on the steric, electrostatic, hydrophobic and hydrogen-bond acceptor information of contour maps, key structural factors affecting the bioactivity were explored. This work gives helpful suggestions on the design of novel D3R antagonists with increased activities.

Mechanistic model to predict colostrum intake based on deuterium oxide dilution technique data and impact of gestation and prefarrowing diets on piglet intake and sow yield of colostrum.

PubMed

Theil, P K; Flummer, C; Hurley, W L; Kristensen, N B; Labouriau, R L; Sørensen, M T

2014-12-01

The aims of the present study were to quantify colostrum intake (CI) of piglets using the D2O dilution technique, to develop a mechanistic model to predict CI, to compare these data with CI predicted by a previous empirical predictive model developed for bottle-fed piglets, and to study how composition of diets fed to gestating sows affected piglet CI, sow colostrum yield (CY), and colostrum composition. In total, 240 piglets from 40 litters were enriched with D2O. The CI measured by D2O from birth until 24 h after the birth of first-born piglet was on average 443 g (SD 151). Based on measured CI, a mechanistic model to predict CI was developed using piglet characteristics (24-h weight gain [WG; g], BW at birth [BWB; kg], and duration of CI [D; min]: CI, g=-106+2.26 WG+200 BWB+0.111 D-1,414 WG/D+0.0182 WG/BWB (R2=0.944). This model was used to predict the CI for all colostrum suckling piglets within the 40 litters (n=500, mean=437 g, SD=153 g) and was compared with the CI predicted by a previous empirical predictive model (mean=305 g, SD=140 g). The previous empirical model underestimated the CI by 30% compared with that obtained by the new mechanistic model. The sows were fed 1 of 4 gestation diets (n=10 per diet) based on different fiber sources (low fiber [17%] or potato pulp, pectin residue, or sugarbeet pulp [32 to 40%]) from mating until d 108 of gestation. From d 108 of gestation until parturition, sows were fed 1 of 5 prefarrowing diets (n=8 per diet) varying in supplemented fat (3% animal fat, 8% coconut oil, 8% sunflower oil, 8% fish oil, or 4% fish oil+4% octanoic acid). Sows fed diets with pectin residue or sugarbeet pulp during gestation produced colostrum with lower protein, fat, DM, and energy concentrations and higher lactose concentrations, and their piglets had greater CI as compared with sows fed potato pulp or the low-fiber diet (P<0.05), and sows fed pectin residue had a greater CY than potato pulp-fed sows (P<0.05). Prefarrowing diets affected neither CI nor CY, but the prefarrowing diet with coconut oil decreased lactose and increased DM concentrations of colostrum compared with other prefarrowing diets (P<0.05). In conclusion, the new mechanistic predictive model for CI suggests that the previous empirical predictive model underestimates CI of sow-reared piglets by 30%. It was also concluded that nutrition of sows during gestation affected CY and colostrum composition.

Application and comparison of the FADES, MADIT, and SHFM-D risk models for risk stratification of prophylactic implantable cardioverter-defibrillator treatment

PubMed Central

van der Heijden, Aafke C.; van Rees, Johannes B.; Levy, Wayne C.; van der Bom, Johanna G.; Cannegieter, Suzanne C.; de Bie, Mihàly K.; van Erven, Lieselot; Schalij, Martin J.; Borleffs, C. Jan  Willem

2017-01-01

Aims Implantable cardioverter-defibrillator (ICD) treatment is beneficial in selected patients. However, it remains difficult to accurately predict which patients benefit most from ICD implantation. For this purpose, different risk models have been developed. The aim was to validate and compare the FADES, MADIT, and SHFM-D models. Methods and results All patients receiving a prophylactic ICD at the Leiden University Medical Center were evaluated. Individual model performance was evaluated by C-statistics. Model performances were compared using net reclassification improvement (NRI) and integrated differentiation improvement (IDI). The primary endpoint was non-benefit of ICD treatment, defined as mortality without prior ventricular arrhythmias requiring ICD intervention. A total of 1969 patients were included (age 63 ± 11 years; 79% male). During a median follow-up of 4.5 ± 3.9 years, 318 (16%) patients died without prior ICD intervention. All three risk models were predictive for event-free mortality (all: P < 0.001). The C-statistics were 0.66, 0.69, and 0.75, respectively, for FADES, MADIT, and SHFM-D (all: P < 0.001). Application of the SHFM-D resulted in an improved IDI of 4% and NRI of 26% compared with MADIT; IDI improved 11% with the use of SHFM-D instead of FADES (all: P < 0.001), but NRI remained unchanged (P = 0.71). Patients in the highest-risk category of the MADIT and SHFM-D models had 1.7 times higher risk to experience ICD non-benefit than receive appropriate ICD interventions [MADIT: mean difference (MD) 20% (95% CI: 7–33%), P = 0.001; SHFM-D: MD 16% (95% CI: 5–27%), P = 0.005]. Patients in the highest-risk category of FADES were as likely to experience ICD intervention as ICD non-benefit [MD 3% (95% CI: –8 to 14%), P = 0.60]. Conclusion The predictive and discriminatory value of SHFM-D to predict non-benefit of ICD treatment is superior to FADES and MADIT in patients receiving prophylactic ICD treatment. PMID:28130376

4D-Fingerprint Categorical QSAR Models for Skin Sensitization Based on Classification Local Lymph Node Assay Measures

PubMed Central

Li, Yi; Tseng, Yufeng J.; Pan, Dahua; Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Hopfinger, Anton J.

2008-01-01

Currently, the only validated methods to identify skin sensitization effects are in vivo models, such as the Local Lymph Node Assay (LLNA) and guinea pig studies. There is a tremendous need, in particular due to novel legislation, to develop animal alternatives, eg. Quantitative Structure-Activity Relationship (QSAR) models. Here, QSAR models for skin sensitization using LLNA data have been constructed. The descriptors used to generate these models are derived from the 4D-molecular similarity paradigm and are referred to as universal 4D-fingerprints. A training set of 132 structurally diverse compounds and a test set of 15 structurally diverse compounds were used in this study. The statistical methodologies used to build the models are logistic regression (LR), and partial least square coupled logistic regression (PLS-LR), which prove to be effective tools for studying skin sensitization measures expressed in the two categorical terms of sensitizer and non-sensitizer. QSAR models with low values of the Hosmer-Lemeshow goodness-of-fit statistic, χHL2, are significant and predictive. For the training set, the cross-validated prediction accuracy of the logistic regression models ranges from 77.3% to 78.0%, while that of PLS-logistic regression models ranges from 87.1% to 89.4%. For the test set, the prediction accuracy of logistic regression models ranges from 80.0%-86.7%, while that of PLS-logistic regression models ranges from 73.3%-80.0%. The QSAR models are made up of 4D-fingerprints related to aromatic atoms, hydrogen bond acceptors and negatively partially charged atoms. PMID:17226934

Constructing and Validating 3D-pharmacophore Models to a Set of MMP-9 Inhibitors for Designing Novel Anti-melanoma Agents.

PubMed

Medeiros Turra, Kely; Pineda Rivelli, Diogo; Berlanga de Moraes Barros, Silvia; Mesquita Pasqualoto, Kerly Fernanda

2016-07-01

A receptor-independent (RI) four-dimensional structure-activity relationship (4D-QSAR) formalism was applied to a set of sixty-four β-N-biaryl ether sulfonamide hydroxamate derivatives, previously reported as potent inhibitors against matrix metalloproteinase subtype 9 (MMP-9). MMP-9 belongs to a group of enzymes related to the cleavage of several extracellular matrix components and has been associated to cancer invasiveness/metastasis. The best RI 4D-QSAR model was statistically significant (N=47; r(2) =0.91; q(2) =0.83; LSE=0.09; LOF=0.35; outliers=0). Leave-N-out (LNO) and y-randomization approaches indicated the QSAR model was robust and presented no chance correlation, respectively. Furthermore, it also had good external predictability (82 %) regarding the test set (N=17). In addition, the grid cell occupancy descriptors (GCOD) of the predicted bioactive conformation for the most potent inhibitor were successfully interpreted when docked into the MMP-9 active site. The 3D-pharmacophore findings were used to predict novel ligands and exploit the MMP-9 calculated binding affinity through molecular docking procedure. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Homology modeling a fast tool for drug discovery: current perspectives.

PubMed

Vyas, V K; Ukawala, R D; Ghate, M; Chintha, C

2012-01-01

Major goal of structural biology involve formation of protein-ligand complexes; in which the protein molecules act energetically in the course of binding. Therefore, perceptive of protein-ligand interaction will be very important for structure based drug design. Lack of knowledge of 3D structures has hindered efforts to understand the binding specificities of ligands with protein. With increasing in modeling software and the growing number of known protein structures, homology modeling is rapidly becoming the method of choice for obtaining 3D coordinates of proteins. Homology modeling is a representation of the similarity of environmental residues at topologically corresponding positions in the reference proteins. In the absence of experimental data, model building on the basis of a known 3D structure of a homologous protein is at present the only reliable method to obtain the structural information. Knowledge of the 3D structures of proteins provides invaluable insights into the molecular basis of their functions. The recent advances in homology modeling, particularly in detecting and aligning sequences with template structures, distant homologues, modeling of loops and side chains as well as detecting errors in a model contributed to consistent prediction of protein structure, which was not possible even several years ago. This review focused on the features and a role of homology modeling in predicting protein structure and described current developments in this field with victorious applications at the different stages of the drug design and discovery.

Homology Modeling a Fast Tool for Drug Discovery: Current Perspectives

PubMed Central

Vyas, V. K.; Ukawala, R. D.; Ghate, M.; Chintha, C.

2012-01-01

Major goal of structural biology involve formation of protein-ligand complexes; in which the protein molecules act energetically in the course of binding. Therefore, perceptive of protein-ligand interaction will be very important for structure based drug design. Lack of knowledge of 3D structures has hindered efforts to understand the binding specificities of ligands with protein. With increasing in modeling software and the growing number of known protein structures, homology modeling is rapidly becoming the method of choice for obtaining 3D coordinates of proteins. Homology modeling is a representation of the similarity of environmental residues at topologically corresponding positions in the reference proteins. In the absence of experimental data, model building on the basis of a known 3D structure of a homologous protein is at present the only reliable method to obtain the structural information. Knowledge of the 3D structures of proteins provides invaluable insights into the molecular basis of their functions. The recent advances in homology modeling, particularly in detecting and aligning sequences with template structures, distant homologues, modeling of loops and side chains as well as detecting errors in a model contributed to consistent prediction of protein structure, which was not possible even several years ago. This review focused on the features and a role of homology modeling in predicting protein structure and described current developments in this field with victorious applications at the different stages of the drug design and discovery. PMID:23204616

Method for evaluation of predictive models of microwave ablation via post-procedural clinical imaging

NASA Astrophysics Data System (ADS)

Collins, Jarrod A.; Brown, Daniel; Kingham, T. Peter; Jarnagin, William R.; Miga, Michael I.; Clements, Logan W.

2015-03-01

Development of a clinically accurate predictive model of microwave ablation (MWA) procedures would represent a significant advancement and facilitate an implementation of patient-specific treatment planning to achieve optimal probe placement and ablation outcomes. While studies have been performed to evaluate predictive models of MWA, the ability to quantify the performance of predictive models via clinical data has been limited to comparing geometric measurements of the predicted and actual ablation zones. The accuracy of placement, as determined by the degree of spatial overlap between ablation zones, has not been achieved. In order to overcome this limitation, a method of evaluation is proposed where the actual location of the MWA antenna is tracked and recorded during the procedure via a surgical navigation system. Predictive models of the MWA are then computed using the known position of the antenna within the preoperative image space. Two different predictive MWA models were used for the preliminary evaluation of the proposed method: (1) a geometric model based on the labeling associated with the ablation antenna and (2) a 3-D finite element method based computational model of MWA using COMSOL. Given the follow-up tomographic images that are acquired at approximately 30 days after the procedure, a 3-D surface model of the necrotic zone was generated to represent the true ablation zone. A quantification of the overlap between the predicted ablation zones and the true ablation zone was performed after a rigid registration was computed between the pre- and post-procedural tomograms. While both model show significant overlap with the true ablation zone, these preliminary results suggest a slightly higher degree of overlap with the geometric model.

Prediction of car cabin environment by means of 1D and 3D cabin model

NASA Astrophysics Data System (ADS)

Fišer, J.; Pokorný, J.; Jícha, M.

2012-04-01

Thermal comfort and also reduction of energy requirements of air-conditioning system in vehicle cabins are currently very intensively investigated and up-to-date issues. The article deals with two approaches of modelling of car cabin environment; the first model was created in simulation language Modelica (typical 1D approach without cabin geometry) and the second one was created in specialized software Theseus-FE (3D approach with cabin geometry). Performance and capabilities of this tools are demonstrated on the example of the car cabin and the results from simulations are compared with the results from the real car cabin climate chamber measurements.

Advances in ultrasonic testing of austenitic stainless steel welds. Towards a 3D description of the material including attenuation and optimisation by inversion

NASA Astrophysics Data System (ADS)

Moysan, J.; Gueudré, C.; Ploix, M.-A.; Corneloup, G.; Guy, Ph.; Guerjouma, R. El; Chassignole, B.

In the case of multi-pass welds, the material is very difficult to describe due to its anisotropic and heterogeneous properties. Anisotropy results from the metal solidification and is correlated with the grain orientation. A precise description of the material is one of the key points to obtain reliable results with wave propagation codes. A first advance is the model MINA which predicts the grain orientations in multi-pass 316-L steel welds. For flat position welding, good predictions of the grains orientations were obtained using 2D modelling. In case of welding in position the resulting grain structure may be 3D oriented. We indicate how the MINA model can be improved for 3D description. A second advance is a good quantification of the attenuation. Precise measurements are obtained using plane waves angular spectrum method together with the computation of the transmission coefficients for triclinic material. With these two first advances, the third one is now possible: developing an inverse method to obtain the material description through ultrasonic measurements at different positions.

Quantitative Understanding of SHAPE Mechanism from RNA Structure and Dynamics Analysis.

PubMed

Hurst, Travis; Xu, Xiaojun; Zhao, Peinan; Chen, Shi-Jie

2018-05-10

The selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) method probes RNA local structural and dynamic information at single nucleotide resolution. To gain quantitative insights into the relationship between nucleotide flexibility, RNA 3D structure, and SHAPE reactivity, we develop a 3D Structure-SHAPE Relationship model (3DSSR) to rebuild SHAPE profiles from 3D structures. The model starts from RNA structures and combines nucleotide interaction strength and conformational propensity, ligand (SHAPE reagent) accessibility, and base-pairing pattern through a composite function to quantify the correlation between SHAPE reactivity and nucleotide conformational stability. The 3DSSR model shows the relationship between SHAPE reactivity and RNA structure and energetics. Comparisons between the 3DSSR-predicted SHAPE profile and the experimental SHAPE data show correlation, suggesting that the extracted analytical function may have captured the key factors that determine the SHAPE reactivity profile. Furthermore, the theory offers an effective method to sieve RNA 3D models and exclude models that are incompatible with experimental SHAPE data.

The Use of Twitter to Predict the Level of Influenza Activity in the United States

DTIC Science & Technology

2014-09-01

Positive for Influenza Type A or B .......................................................................15 3. Influenza Associated Hospitalizations ...D. MODEL FOR PREDICTING NUMBER OF INFLUENZA- ASSOCIATED HOSPITALIZATIONS ......................................................60 VI. CONCLUSIONS...4. Predicted vs. Actual Rate of Influenza-Associated Hospitalizations per 100,000 Population..........................................85 APPENDIX B

MISS-Prot: web server for self/non-self discrimination of protein residue networks in parasites; theory and experiments in Fasciola peptides and Anisakis allergens.

PubMed

González-Díaz, Humberto; Muíño, Laura; Anadón, Ana M; Romaris, Fernanda; Prado-Prado, Francisco J; Munteanu, Cristian R; Dorado, Julián; Sierra, Alejandro Pazos; Mezo, Mercedes; González-Warleta, Marta; Gárate, Teresa; Ubeira, Florencio M

2011-06-01

Infections caused by human parasites (HPs) affect the poorest 500 million people worldwide but chemotherapy has become expensive, toxic, and/or less effective due to drug resistance. On the other hand, many 3D structures in Protein Data Bank (PDB) remain without function annotation. We need theoretical models to quickly predict biologically relevant Parasite Self Proteins (PSP), which are expressed differentially in a given parasite and are dissimilar to proteins expressed in other parasites and have a high probability to become new vaccines (unique sequence) or drug targets (unique 3D structure). We present herein a model for PSPs in eight different HPs (Ascaris, Entamoeba, Fasciola, Giardia, Leishmania, Plasmodium, Trypanosoma, and Toxoplasma) with 90% accuracy for 15 341 training and validation cases. The model combines protein residue networks, Markov Chain Models (MCM) and Artificial Neural Networks (ANN). The input parameters are the spectral moments of the Markov transition matrix for electrostatic interactions associated with the protein residue complex network calculated with the MARCH-INSIDE software. We implemented this model in a new web-server called MISS-Prot (MARCH-INSIDE Scores for Self-Proteins). MISS-Prot was programmed using PHP/HTML/Python and MARCH-INSIDE routines and is freely available at: . This server is easy to use by non-experts in Bioinformatics who can carry out automatic online upload and prediction with 3D structures deposited at PDB (mode 1). We can also study outcomes of Peptide Mass Fingerprinting (PMFs) and MS/MS for query proteins with unknown 3D structures (mode 2). We illustrated the use of MISS-Prot in experimental and/or theoretical studies of peptides from Fasciola hepatica cathepsin proteases or present on 10 Anisakis simplex allergens (Ani s 1 to Ani s 10). In doing so, we combined electrophoresis (1DE), MALDI-TOF Mass Spectroscopy, and MASCOT to seek sequences, Molecular Mechanics + Molecular Dynamics (MM/MD) to generate 3D structures and MISS-Prot to predict PSP scores. MISS-Prot also allows the prediction of PSP proteins in 16 additional species including parasite hosts, fungi pathogens, disease transmission vectors, and biotechnologically relevant organisms.

In Vivo Validation of Numerical Prediction for Turbulence Intensity in an Aortic Coarctation

PubMed Central

Arzani, Amirhossein; Dyverfeldt, Petter; Ebbers, Tino; Shadden, Shawn C.

2013-01-01

This paper compares numerical predictions of turbulence intensity with in vivo measurement. Magnetic resonance imaging (MRI) was carried out on a 60-year-old female with a restenosed aortic coarctation. Time-resolved three-directional phase-contrast (PC) MRI data was acquired to enable turbulence intensity estimation. A contrast-enhanced MR angiography (MRA) and a time-resolved 2D PCMRI measurement were also performed to acquire data needed to perform subsequent image-based computational fluid dynamics (CFD) modeling. A 3D model of the aortic coarctation and surrounding vasculature was constructed from the MRA data, and physiologic boundary conditions were modeled to match 2D PCMRI and pressure pulse measurements. Blood flow velocity data was subsequently obtained by numerical simulation. Turbulent kinetic energy (TKE) was computed from the resulting CFD data. Results indicate relative agreement (error ≈10%) between the in vivo measurements and the CFD predictions of TKE. The discrepancies in modeled vs. measured TKE values were within expectations due to modeling and measurement errors. PMID:22016327

Predicting enteric methane emission of dairy cows with milk Fourier-transform infrared spectra and gas chromatography-based milk fatty acid profiles.

PubMed

van Gastelen, S; Mollenhorst, H; Antunes-Fernandes, E C; Hettinga, K A; van Burgsteden, G G; Dijkstra, J; Rademaker, J L W

2018-06-01

The objective of the present study was to compare the prediction potential of milk Fourier-transform infrared spectroscopy (FTIR) for CH 4 emissions of dairy cows with that of gas chromatography (GC)-based milk fatty acids (MFA). Data from 9 experiments with lactating Holstein-Friesian cows, with a total of 30 dietary treatments and 218 observations, were used. Methane emissions were measured for 3 consecutive days in climate respiration chambers and expressed as production (g/d), yield (g/kg of dry matter intake; DMI), and intensity (g/kg of fat- and protein-corrected milk; FPCM). Dry matter intake was 16.3 ± 2.18 kg/d (mean ± standard deviation), FPCM yield was 25.9 ± 5.06 kg/d, CH 4 production was 366 ± 53.9 g/d, CH 4 yield was 22.5 ± 2.10 g/kg of DMI, and CH 4 intensity was 14.4 ± 2.58 g/kg of FPCM. Milk was sampled during the same days and analyzed by GC and by FTIR. Multivariate GC-determined MFA-based and FTIR-based CH 4 prediction models were developed, and subsequently, the final CH 4 prediction models were evaluated with root mean squared error of prediction and concordance correlation coefficient analysis. Further, we performed a random 10-fold cross validation to calculate the performance parameters of the models (e.g., the coefficient of determination of cross validation). The final GC-determined MFA-based CH 4 prediction models estimate CH 4 production, yield, and intensity with a root mean squared error of prediction of 35.7 g/d, 1.6 g/kg of DMI, and 1.6 g/kg of FPCM and with a concordance correlation coefficient of 0.72, 0.59, and 0.77, respectively. The final FTIR-based CH 4 prediction models estimate CH 4 production, yield, and intensity with a root mean squared error of prediction of 43.2 g/d, 1.9 g/kg of DMI, and 1.7 g/kg of FPCM and with a concordance correlation coefficient of 0.52, 0.40, and 0.72, respectively. The GC-determined MFA-based prediction models described a greater part of the observed variation in CH 4 emission than did the FTIR-based models. The cross validation results indicate that all CH 4 prediction models (both GC-determined MFA-based and FTIR-based models) are robust; the difference between the coefficient of determination and the coefficient of determination of cross validation ranged from 0.01 to 0.07. The results indicate that GC-determined MFA have a greater potential than FTIR spectra to estimate CH 4 production, yield, and intensity. Both techniques hold potential but may not yet be ready to predict CH 4 emission of dairy cows in practice. Additional CH 4 measurements are needed to improve the accuracy and robustness of GC-determined MFA and FTIR spectra for CH 4 prediction. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Analysis of a High-Lift Multi-Element Airfoil using a Navier-Stokes Code

NASA Technical Reports Server (NTRS)

Whitlock, Mark E.

1995-01-01

A thin-layer Navier-Stokes code, CFL3D, was utilized to compute the flow over a high-lift multi-element airfoil. This study was conducted to improve the prediction of high-lift flowfields using various turbulence models and improved glidding techniques. An overset Chimera grid system is used to model the three element airfoil geometry. The effects of wind tunnel wall modeling, changes to the grid density and distribution, and embedded grids are discussed. Computed pressure and lift coefficients using Spalart-Allmaras, Baldwin-Barth, and Menter's kappa-omega - Shear Stress Transport (SST) turbulence models are compared with experimental data. The ability of CFL3D to predict the effects on lift coefficient due to changes in Reynolds number changes is also discussed.

3D-QSAR and docking studies of 3-Pyridine heterocyclic derivatives as potent PI3K/mTOR inhibitors

NASA Astrophysics Data System (ADS)

Yang, Wenjuan; Shu, Mao; Wang, Yuanqiang; Wang, Rui; Hu, Yong; Meng, Lingxin; Lin, Zhihua

2013-12-01

Phosphoinosmde-3-kinase/ mammalian target of rapamycin (PI3K/mTOR) dual inhibitors have attracted a great deal of interest as antitumor drugs research. In order to design and optimize these dual inhibitors, two types of 3D-quantitative structure-activity relationship (3D-QSAR) studies based on the ligand alignment and receptor alignment were applied using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). In the study based on ligands alignment, models of PI3K (CoMFA with r2, 0.770; q2, 0.622; CoMSIA with r2, 0.945; q2, 0.748) and mTOR (CoMFA with r2, 0.850; q2, 0.654; CoMSIA with r2, 0.983; q2, 0.676) have good predictability. And in the study based on receptor alignment, models of PI3K (CoMFA with r2, 0.745; q2, 0.538; CoMSIA with r2, 0.938; q2, 0.630) and mTOR (CoMFA with r2, 0.977; q2, 0.825; CoMSIA with r2, 0.985; q2, 0.728) also have good predictability. 3D contour maps and docking results suggested different groups on the core parts of the compounds could enhance the biological activities. Finally, ten derivatives as potential candidates of PI3K/mTOR inhibitors with good predicted activities were designed.

Three dimensional quantitative structure-toxicity relationship modeling and prediction of acute toxicity for organic contaminants to algae.

PubMed

Jin, Xiangqin; Jin, Minghao; Sheng, Lianxi

2014-08-01

Although numerous chemicals have been identified to have significant toxicological effect on aquatic organisms, there is still lack of a reliable, high-throughput approach to evaluate, screen and monitor the presence of organic contaminants in aquatic system. In the current study, we proposed a synthetic pipeline to automatically model and predict the acute toxicity of chemicals to algae. In the procedure, a new alignment-free three dimensional (3D) structure characterization method was described and, with this method, several 3D-quantitative structure-toxicity relationship (3D-QSTR) models were developed, from which two were found to exhibit strong internal fitting ability and high external predictive power. The best model was established by Gaussian process (GP), which was further employed to perform extrapolation on a random compound library consisting of 1014 virtually generated substituted benzenes. It was found that (i) substitution number can only exert slight influence on chemical׳s toxicity, but low-substituted benzenes seem to have higher toxicity than those of high-substituted entities, and (ii) benzenes substituted by nitro group and halogens exhibit high acute toxicity as compared to other substituents such as methyl and carboxyl groups. Subsequently, several promising candidates suggested by computational prediction were assayed by using a standard algal growth inhibition test. Consequently, four substituted benzenes, namely 2,3-dinitrophenol, 2-chloro-4-nitroaniline, 1,2,3-trinitrobenzene and 3-bromophenol, were determined to have high acute toxicity to Scenedesmus obliquus, with their EC50 values of 2.5±0.8, 10.5±2.1, 1.4±0.2 and 42.7±5.4μmol/L, respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

The prediction of type 1 diabetes by multiple autoantibody levels and their incorporation into an autoantibody risk score in relatives of type 1 diabetic patients.

PubMed

Sosenko, Jay M; Skyler, Jay S; Palmer, Jerry P; Krischer, Jeffrey P; Yu, Liping; Mahon, Jeffrey; Beam, Craig A; Boulware, David C; Rafkin, Lisa; Schatz, Desmond; Eisenbarth, George

2013-09-01

We assessed whether a risk score that incorporates levels of multiple islet autoantibodies could enhance the prediction of type 1 diabetes (T1D). TrialNet Natural History Study participants (n = 784) were tested for three autoantibodies (GADA, IA-2A, and mIAA) at their initial screening. Samples from those positive for at least one autoantibody were subsequently tested for ICA and ZnT8A. An autoantibody risk score (ABRS) was developed from a proportional hazards model that combined autoantibody levels from each autoantibody along with their designations of positivity and negativity. The ABRS was strongly predictive of T1D (hazard ratio [with 95% CI] 2.72 [2.23-3.31], P < 0.001). Receiver operating characteristic curve areas (with 95% CI) for the ABRS revealed good predictability (0.84 [0.78-0.90] at 2 years, 0.81 [0.74-0.89] at 3 years, P < 0.001 for both). The composite of levels from the five autoantibodies was predictive of T1D before and after an adjustment for the positivity or negativity of autoantibodies (P < 0.001). The findings were almost identical when ICA was excluded from the risk score model. The combination of the ABRS and the previously validated Diabetes Prevention Trial-Type 1 Risk Score (DPTRS) predicted T1D more accurately (0.93 [0.88-0.98] at 2 years, 0.91 [0.83-0.99] at 3 years) than either the DPTRS or the ABRS alone (P ≤ 0.01 for all comparisons). These findings show the importance of considering autoantibody levels in assessing the risk of T1D. Moreover, levels of multiple autoantibodies can be incorporated into an ABRS that accurately predicts T1D.

The Prediction of Type 1 Diabetes by Multiple Autoantibody Levels and Their Incorporation Into an Autoantibody Risk Score in Relatives of Type 1 Diabetic Patients

PubMed Central

Sosenko, Jay M.; Skyler, Jay S.; Palmer, Jerry P.; Krischer, Jeffrey P.; Yu, Liping; Mahon, Jeffrey; Beam, Craig A.; Boulware, David C.; Rafkin, Lisa; Schatz, Desmond; Eisenbarth, George

2013-01-01

OBJECTIVE We assessed whether a risk score that incorporates levels of multiple islet autoantibodies could enhance the prediction of type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS TrialNet Natural History Study participants (n = 784) were tested for three autoantibodies (GADA, IA-2A, and mIAA) at their initial screening. Samples from those positive for at least one autoantibody were subsequently tested for ICA and ZnT8A. An autoantibody risk score (ABRS) was developed from a proportional hazards model that combined autoantibody levels from each autoantibody along with their designations of positivity and negativity. RESULTS The ABRS was strongly predictive of T1D (hazard ratio [with 95% CI] 2.72 [2.23–3.31], P < 0.001). Receiver operating characteristic curve areas (with 95% CI) for the ABRS revealed good predictability (0.84 [0.78–0.90] at 2 years, 0.81 [0.74–0.89] at 3 years, P < 0.001 for both). The composite of levels from the five autoantibodies was predictive of T1D before and after an adjustment for the positivity or negativity of autoantibodies (P < 0.001). The findings were almost identical when ICA was excluded from the risk score model. The combination of the ABRS and the previously validated Diabetes Prevention Trial–Type 1 Risk Score (DPTRS) predicted T1D more accurately (0.93 [0.88–0.98] at 2 years, 0.91 [0.83–0.99] at 3 years) than either the DPTRS or the ABRS alone (P ≤ 0.01 for all comparisons). CONCLUSIONS These findings show the importance of considering autoantibody levels in assessing the risk of T1D. Moreover, levels of multiple autoantibodies can be incorporated into an ABRS that accurately predicts T1D. PMID:23818528

3D-QSAR and docking studies on 4-anilinoquinazoline and 4-anilinoquinoline epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors

NASA Astrophysics Data System (ADS)

Assefa, Haregewein; Kamath, Shantaram; Buolamwini, John K.

2003-08-01

The overexpression and/or mutation of the epidermal growth factor receptor (EGFR) tyrosine kinase has been observed in many human solid tumors, and is under intense investigation as a novel anticancer molecular target. Comparative 3D-QSAR analyses using different alignments were undertaken employing comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) for 122 anilinoquinazoline and 50 anilinoquinoline inhibitors of EGFR kinase. The SYBYL multifit alignment rule was applied to three different conformational templates, two obtained from a MacroModel Monte Carlo conformational search, and one from the bound conformation of erlotinib in complex with EGFR in the X-ray crystal structure. In addition, a flexible ligand docking alignment obtained with the GOLD docking program, and a novel flexible receptor-guided consensus dynamics alignment obtained with the DISCOVER program in the INSIGHTII modeling package were also investigated. 3D-QSAR models with q2 values up to 0.70 and r2 values up to 0.97 were obtained. Among the 4-anilinoquinazoline set, the q2 values were similar, but the ability of the different conformational models to predict the activities of an external test set varied considerably. In this regard, the model derived using the X-ray crystallographically determined bioactive conformation of erlotinib afforded the best predictive model. Electrostatic, hydrophobic and H-bond donor descriptors contributed the most to the QSAR models of the 4-anilinoquinazolines, whereas electrostatic, hydrophobic and H-bond acceptor descriptors contributed the most to the 4-anilinoquinoline QSAR, particularly the H-bond acceptor descriptor. A novel receptor-guided consensus dynamics alignment has also been introduced for 3D-QSAR studies. This new alignment method may incorporate to some extent ligand-receptor induced fit effects into 3D-QSAR models.

A comparison of selected parametric and imputation methods for estimating snag density and snag quality attributes

USGS Publications Warehouse

Eskelson, Bianca N.I.; Hagar, Joan; Temesgen, Hailemariam

2012-01-01

Snags (standing dead trees) are an essential structural component of forests. Because wildlife use of snags depends on size and decay stage, snag density estimation without any information about snag quality attributes is of little value for wildlife management decision makers. Little work has been done to develop models that allow multivariate estimation of snag density by snag quality class. Using climate, topography, Landsat TM data, stand age and forest type collected for 2356 forested Forest Inventory and Analysis plots in western Washington and western Oregon, we evaluated two multivariate techniques for their abilities to estimate density of snags by three decay classes. The density of live trees and snags in three decay classes (D1: recently dead, little decay; D2: decay, without top, some branches and bark missing; D3: extensive decay, missing bark and most branches) with diameter at breast height (DBH) ≥ 12.7 cm was estimated using a nonparametric random forest nearest neighbor imputation technique (RF) and a parametric two-stage model (QPORD), for which the number of trees per hectare was estimated with a Quasipoisson model in the first stage and the probability of belonging to a tree status class (live, D1, D2, D3) was estimated with an ordinal regression model in the second stage. The presence of large snags with DBH ≥ 50 cm was predicted using a logistic regression and RF imputation. Because of the more homogenous conditions on private forest lands, snag density by decay class was predicted with higher accuracies on private forest lands than on public lands, while presence of large snags was more accurately predicted on public lands, owing to the higher prevalence of large snags on public lands. RF outperformed the QPORD model in terms of percent accurate predictions, while QPORD provided smaller root mean square errors in predicting snag density by decay class. The logistic regression model achieved more accurate presence/absence classification of large snags than the RF imputation approach. Adjusting the decision threshold to account for unequal size for presence and absence classes is more straightforward for the logistic regression than for the RF imputation approach. Overall, model accuracies were poor in this study, which can be attributed to the poor predictive quality of the explanatory variables and the large range of forest types and geographic conditions observed in the data.

Dynamic CFD Simulations of the Supersonic Inflatable Aerodynamic Decelerator (SIAD) Ballistic Range Tests

NASA Technical Reports Server (NTRS)

Brock, Joseph M; Stern, Eric

2016-01-01

Dynamic CFD simulations of the SIAD ballistic test model were performed using US3D flow solver. Motivation for performing these simulations is for the purpose of validation and verification of the US3D flow solver as a viable computational tool for predicting dynamic coefficients.

Comparison of different models for non-invasive FFR estimation

NASA Astrophysics Data System (ADS)

Mirramezani, Mehran; Shadden, Shawn

2017-11-01

Coronary artery disease is a leading cause of death worldwide. Fractional flow reserve (FFR), derived from invasively measuring the pressure drop across a stenosis, is considered the gold standard to diagnose disease severity and need for treatment. Non-invasive estimation of FFR has gained recent attention for its potential to reduce patient risk and procedural cost versus invasive FFR measurement. Non-invasive FFR can be obtained by using image-based computational fluid dynamics to simulate blood flow and pressure in a patient-specific coronary model. However, 3D simulations require extensive effort for model construction and numerical computation, which limits their routine use. In this study we compare (ordered by increasing computational cost/complexity): reduced-order algebraic models of pressure drop across a stenosis; 1D, 2D (multiring) and 3D CFD models; as well as 3D FSI for the computation of FFR in idealized and patient-specific stenosis geometries. We demonstrate the ability of an appropriate reduced order algebraic model to closely predict FFR when compared to FFR from a full 3D simulation. This work was supported by the NIH, Grant No. R01-HL103419.

The application of molecular modelling in the safety assessment of chemicals: A case study on ligand-dependent PPARγ dysregulation.

PubMed

Al Sharif, Merilin; Tsakovska, Ivanka; Pajeva, Ilza; Alov, Petko; Fioravanzo, Elena; Bassan, Arianna; Kovarich, Simona; Yang, Chihae; Mostrag-Szlichtyng, Aleksandra; Vitcheva, Vessela; Worth, Andrew P; Richarz, Andrea-N; Cronin, Mark T D

2017-12-01

The aim of this paper was to provide a proof of concept demonstrating that molecular modelling methodologies can be employed as a part of an integrated strategy to support toxicity prediction consistent with the mode of action/adverse outcome pathway (MoA/AOP) framework. To illustrate the role of molecular modelling in predictive toxicology, a case study was undertaken in which molecular modelling methodologies were employed to predict the activation of the peroxisome proliferator-activated nuclear receptor γ (PPARγ) as a potential molecular initiating event (MIE) for liver steatosis. A stepwise procedure combining different in silico approaches (virtual screening based on docking and pharmacophore filtering, and molecular field analysis) was developed to screen for PPARγ full agonists and to predict their transactivation activity (EC 50 ). The performance metrics of the classification model to predict PPARγ full agonists were balanced accuracy=81%, sensitivity=85% and specificity=76%. The 3D QSAR model developed to predict EC 50 of PPARγ full agonists had the following statistical parameters: q 2 cv =0.610, N opt =7, SEP cv =0.505, r 2 pr =0.552. To support the linkage of PPARγ agonism predictions to prosteatotic potential, molecular modelling was combined with independently performed mechanistic mining of available in vivo toxicity data followed by ToxPrint chemotypes analysis. The approaches investigated demonstrated a potential to predict the MIE, to facilitate the process of MoA/AOP elaboration, to increase the scientific confidence in AOP, and to become a basis for 3D chemotype development. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Relativistic three-dimensional Lippmann-Schwinger cross sections for space radiation applications

NASA Astrophysics Data System (ADS)

Werneth, C. M.; Xu, X.; Norman, R. B.; Maung, K. M.

2017-12-01

Radiation transport codes require accurate nuclear cross sections to compute particle fluences inside shielding materials. The Tripathi semi-empirical reaction cross section, which includes over 60 parameters tuned to nucleon-nucleus (NA) and nucleus-nucleus (AA) data, has been used in many of the world's best-known transport codes. Although this parameterization fits well to reaction cross section data, the predictive capability of any parameterization is questionable when it is used beyond the range of the data to which it was tuned. Using uncertainty analysis, it is shown that a relativistic three-dimensional Lippmann-Schwinger (LS3D) equation model based on Multiple Scattering Theory (MST) that uses 5 parameterizations-3 fundamental parameterizations to nucleon-nucleon (NN) data and 2 nuclear charge density parameterizations-predicts NA and AA reaction cross sections as well as the Tripathi cross section parameterization for reactions in which the kinetic energy of the projectile in the laboratory frame (TLab) is greater than 220 MeV/n. The relativistic LS3D model has the additional advantage of being able to predict highly accurate total and elastic cross sections. Consequently, it is recommended that the relativistic LS3D model be used for space radiation applications in which TLab > 220MeV /n .

Three-dimensional drift kinetic response of high- β plasmas in the DIII-D tokamak

DOE PAGES

Wang, Zhirui R.; Lanctot, Matthew J.; Liu, Y. Q.; ...

2015-04-07

A quantitative interpretation of the experimentally measured high pressure plasma response to externally applied three-dimensional (3D) magnetic field perturbations, across the no-wall Troyon limit, is achieved. The key to success is the self-consistent inclusion of the drift kinetic resonance effects in numerical modeling using the MARS-K code. This resolves an outstanding issue of ideal magneto-hydrodynamic model, which signi cantly over-predicts the plasma induced field ampli fication near the no-wall limit, as compared to experiments. The self-consistent drift kinetic model leads to quantitative agreement not only for the measured 3D field amplitude and toroidal phase, but also for the measured internalmore » 3D displacement of the plasma.« less

3D-QSAR studies on the inhibitory activity of trimethoprim analogues against Escherichia coli dihydrofolate reductase.

PubMed

Vijayaraj, Ramadoss; Devi, Mekapothula Lakshmi Vasavi; Subramanian, Venkatesan; Chattaraj, Pratim Kumar

2012-06-01

Three-dimensional quantitative structure activity relationship (3D-QSAR) study has been carried out on the Escherichia coli DHFR inhibitors 2,4-diamino-5-(substituted-benzyl)pyrimidine derivatives to understand the structural features responsible for the improved potency. To construct highly predictive 3D-QSAR models, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods were used. The predicted models show statistically significant cross-validated and non-cross-validated correlation coefficient of r2 CV and r2 nCV, respectively. The final 3D-QSAR models were validated using structurally diverse test set compounds. Analysis of the contour maps generated from CoMFA and CoMSIA methods reveals that the substitution of electronegative groups at the first and second position along with electropositive group at the third position of R2 substitution significantly increases the potency of the derivatives. The results obtained from the CoMFA and CoMSIA study delineate the substituents on the trimethoprim analogues responsible for the enhanced potency and also provide valuable directions for the design of new trimethoprim analogues with improved affinity. © 2012 John Wiley & Sons A/S.

Integrated Predictive Tools for Customizing Microstructure and Material Properties of Additively Manufactured Aerospace Components

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

Radhakrishnan, Balasubramaniam; Fattebert, Jean-Luc; Gorti, Sarma B.

Additive Manufacturing (AM) refers to a process by which digital three-dimensional (3-D) design data is converted to build up a component by depositing material layer-by-layer. United Technologies Corporation (UTC) is currently involved in fabrication and certification of several AM aerospace structural components made from aerospace materials. This is accomplished by using optimized process parameters determined through numerous design-of-experiments (DOE)-based studies. Certification of these components is broadly recognized as a significant challenge, with long lead times, very expensive new product development cycles and very high energy consumption. Because of these challenges, United Technologies Research Center (UTRC), together with UTC business unitsmore » have been developing and validating an advanced physics-based process model. The specific goal is to develop a physics-based framework of an AM process and reliably predict fatigue properties of built-up structures as based on detailed solidification microstructures. Microstructures are predicted using process control parameters including energy source power, scan velocity, deposition pattern, and powder properties. The multi-scale multi-physics model requires solution and coupling of governing physics that will allow prediction of the thermal field and enable solution at the microstructural scale. The state-of-the-art approach to solve these problems requires a huge computational framework and this kind of resource is only available within academia and national laboratories. The project utilized the parallel phase-fields codes at Oak Ridge National Laboratory (ORNL) and Lawrence Livermore National Laboratory (LLNL), along with the high-performance computing (HPC) capabilities existing at the two labs to demonstrate the simulation of multiple dendrite growth in threedimensions (3-D). The LLNL code AMPE was used to implement the UTRC phase field model that was previously developed for a model binary alloy, and the simulation results were compared against the UTRC simulation results, followed by extension of the UTRC model to simulate multiple dendrite growth in 3-D. The ORNL MEUMAPPS code was used to simulate dendritic growth in a model ternary alloy with the same equilibrium solidification range as the Ni-base alloy 718 using realistic model parameters, including thermodynamic integration with a Calphad based model for the ternary alloy. Implementation of the UTRC model in AMPE met with several numerical and parametric issues that were resolved and good comparison between the simulation results obtained by the two codes was demonstrated for two dimensional (2-D) dendrites. 3-D dendrite growth was then demonstrated with the AMPE code using nondimensional parameters obtained in 2-D simulations. Multiple dendrite growth in 2-D and 3-D were demonstrated using ORNL’s MEUMAPPS code using simple thermal boundary conditions. MEUMAPPS was then modified to incorporate the complex, time-dependent thermal boundary conditions obtained by UTRC’s thermal modeling of single track AM experiments to drive the phase field simulations. The results were in good agreement with UTRC’s experimental measurements.« less

Successful gas hydrate prospecting using 3D seismic - A case study for the Mt. Elbert prospect, Milne Point, North Slope Alaska

USGS Publications Warehouse

Inks, T.L.; Agena, W.F.

2008-01-01

In February 2007, the Mt. Elbert Prospect stratigraphic test well, Milne Point, North Slope Alaska encountered thick methane gas hydrate intervals, as predicted by 3D seismic interpretation and modeling. Methane gas hydrate-saturated sediment was found in two intervals, totaling more than 100 ft., identified and mapped based on seismic character and wavelet modeling.

How do generalized jamming transitions affect collective migration in confluent tissues?

NASA Astrophysics Data System (ADS)

Manning, M. Lisa

Recent experiments have demonstrated that tissues involved in embryonic development, lung function, wound healing, and cancer progression are close to fluid-to-solid, or ``jamming'' transitions. Theoretical models for confluent 2D tissues have also been shown to exhibit continuous rigidity transitions. However, in vivobiological systems can differ in significant ways from the simple 2D models. For example, many tissues are three-dimensional, mechanically heterogeneous, and/or composed of mechanosensitive cells interspersed with extracellular matrix. We have extended existing models for confluent tissues to capture these features, and we find interesting predictions for collective cell motion that are ultimately related to an underlying generalized jamming transition. For example, in 2D, we find that heterogeneous mixtures of cells spontaneously self-organize into rigid regions of stiffer cells interspersed with string-like groups of soft cells, reminiscent of cellular streaming seen in cancer. We also find that alignment interactions (of the sort often explored in self-propelled particle models) alter the transition and generate interesting flocked liquid and flocked solid collective migration patterns. Our model predicts that 3D tissues also exhibit a jamming transition governed by cell shape, as well as history-dependent aging, and we are currently exploring whether ECM-like interactions in 3D models might help explain compressional stiffening seen in experiments on human tissue.

Restoration of dimensional reduction in the random-field Ising model at five dimensions

NASA Astrophysics Data System (ADS)

Fytas, Nikolaos G.; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

2017-04-01

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D -2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D =5 . We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3 ≤D <6 to their values in the pure Ising model at D -2 dimensions, and we provide a clear verification of the Rushbrooke equality at all studied dimensions.

Restoration of dimensional reduction in the random-field Ising model at five dimensions.

PubMed

Fytas, Nikolaos G; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

2017-04-01

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D-2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D=5. We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3≤D<6 to their values in the pure Ising model at D-2 dimensions, and we provide a clear verification of the Rushbrooke equality at all studied dimensions.

3D gut-liver chip with a PK model for prediction of first-pass metabolism.

PubMed

Lee, Dong Wook; Ha, Sang Keun; Choi, Inwook; Sung, Jong Hwan

2017-11-07

Accurate prediction of first-pass metabolism is essential for improving the time and cost efficiency of drug development process. Here, we have developed a microfluidic gut-liver co-culture chip that aims to reproduce the first-pass metabolism of oral drugs. This chip consists of two separate layers for gut (Caco-2) and liver (HepG2) cell lines, where cells can be co-cultured in both 2D and 3D forms. Both cell lines were maintained well in the chip, verified by confocal microscopy and measurement of hepatic enzyme activity. We investigated the PK profile of paracetamol in the chip, and corresponding PK model was constructed, which was used to predict PK profiles for different chip design parameters. Simulation results implied that a larger absorption surface area and a higher metabolic capacity are required to reproduce the in vivo PK profile of paracetamol more accurately. Our study suggests the possibility of reproducing the human PK profile on a chip, contributing to accurate prediction of pharmacological effect of drugs.

Structured Light-Based 3D Reconstruction System for Plants.

PubMed

Nguyen, Thuy Tuong; Slaughter, David C; Max, Nelson; Maloof, Julin N; Sinha, Neelima

2015-07-29

Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants. This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the proposed structured light system to enhance textures on object surfaces) and software algorithms (including the proposed 3D point cloud registration and plant feature measurement). This paper demonstrates the ability to produce 3D models of whole plants created from multiple pairs of stereo images taken at different viewing angles, without the need to destructively cut away any parts of a plant. The ability to accurately predict phenotyping features, such as the number of leaves, plant height, leaf size and internode distances, is also demonstrated. Experimental results show that, for plants having a range of leaf sizes and a distance between leaves appropriate for the hardware design, the algorithms successfully predict phenotyping features in the target crops, with a recall of 0.97 and a precision of 0.89 for leaf detection and less than a 13-mm error for plant size, leaf size and internode distance.

RNA-Puzzles Round III: 3D RNA structure prediction of five riboswitches and one ribozyme

PubMed Central

Biesiada, Marcin; Boniecki, Michał J.; Chou, Fang-Chieh; Ferré-D'Amaré, Adrian R.; Das, Rhiju; Dunin-Horkawicz, Stanisław; Geniesse, Caleb; Kappel, Kalli; Kladwang, Wipapat; Krokhotin, Andrey; Łach, Grzegorz E.; Major, François; Mann, Thomas H.; Pachulska-Wieczorek, Katarzyna; Patel, Dinshaw J.; Piccirilli, Joseph A.; Popenda, Mariusz; Purzycka, Katarzyna J.; Ren, Aiming; Rice, Greggory M.; Santalucia, John; Tandon, Arpit; Trausch, Jeremiah J.; Wang, Jian; Weeks, Kevin M.; Williams, Benfeard; Xiao, Yi; Zhang, Dong; Zok, Tomasz

2017-01-01

RNA-Puzzles is a collective experiment in blind 3D RNA structure prediction. We report here a third round of RNA-Puzzles. Five puzzles, 4, 8, 12, 13, 14, all structures of riboswitch aptamers and puzzle 7, a ribozyme structure, are included in this round of the experiment. The riboswitch structures include biological binding sites for small molecules (S-adenosyl methionine, cyclic diadenosine monophosphate, 5-amino 4-imidazole carboxamide riboside 5′-triphosphate, glutamine) and proteins (YbxF), and one set describes large conformational changes between ligand-free and ligand-bound states. The Varkud satellite ribozyme is the most recently solved structure of a known large ribozyme. All puzzles have established biological functions and require structural understanding to appreciate their molecular mechanisms. Through the use of fast-track experimental data, including multidimensional chemical mapping, and accurate prediction of RNA secondary structure, a large portion of the contacts in 3D have been predicted correctly leading to similar topologies for the top ranking predictions. Template-based and homology-derived predictions could predict structures to particularly high accuracies. However, achieving biological insights from de novo prediction of RNA 3D structures still depends on the size and complexity of the RNA. Blind computational predictions of RNA structures already appear to provide useful structural information in many cases. Similar to the previous RNA-Puzzles Round II experiment, the prediction of non-Watson–Crick interactions and the observed high atomic clash scores reveal a notable need for an algorithm of improvement. All prediction models and assessment results are available at http://ahsoka.u-strasbg.fr/rnapuzzles/. PMID:28138060

Evaluating Clouds in Long-Term Cloud-Resolving Model Simulations with Observational Data

NASA Technical Reports Server (NTRS)

Zeng, Xiping; Tao, Wei-Kuo; Zhang, Minghua; Peters-Lidard, Christa; Lang, Stephen; Simpson, Joanne; Kumar, Sujay; Xie, Shaocheng; Eastman, Joseph L.; Shie, Chung-Lin;

Effects of inductive bias on computational evaluations of ligand-based modeling and on drug discovery

NASA Astrophysics Data System (ADS)

Cleves, Ann E.; Jain, Ajay N.

2008-03-01

Inductive bias is the set of assumptions that a person or procedure makes in making a prediction based on data. Different methods for ligand-based predictive modeling have different inductive biases, with a particularly sharp contrast between 2D and 3D similarity methods. A unique aspect of ligand design is that the data that exist to test methodology have been largely man-made, and that this process of design involves prediction. By analyzing the molecular similarities of known drugs, we show that the inductive bias of the historic drug discovery process has a very strong 2D bias. In studying the performance of ligand-based modeling methods, it is critical to account for this issue in dataset preparation, use of computational controls, and in the interpretation of results. We propose specific strategies to explicitly address the problems posed by inductive bias considerations.

Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort.

PubMed

Gao, Ying-Duo; Hu, Yuan; Crespo, Alejandro; Wang, Deping; Armacost, Kira A; Fells, James I; Fradera, Xavier; Wang, Hongwu; Wang, Huijun; Sherborne, Brad; Verras, Andreas; Peng, Zhengwei

2018-01-01

The 2016 D3R Grand Challenge 2 includes both pose and affinity or ranking predictions. This article is focused exclusively on affinity predictions submitted to the D3R challenge from a collaborative effort of the modeling and informatics group. Our submissions include ranking of 102 ligands covering 4 different chemotypes against the FXR ligand binding domain structure, and the relative binding affinity predictions of the two designated free energy subsets of 15 and 18 compounds. Using all the complex structures prepared in the same way allowed us to cover many types of workflows and compare their performances effectively. We evaluated typical workflows used in our daily structure-based design modeling support, which include docking scores, force field-based scores, QM/MM, MMGBSA, MD-MMGBSA, and MacroModel interaction energy estimations. The best performing methods for the two free energy subsets are discussed. Our results suggest that affinity ranking still remains very challenging; that the knowledge of more structural information does not necessarily yield more accurate predictions; and that visual inspection and human intervention are considerably important for ranking. Knowledge of the mode of action and protein flexibility along with visualization tools that depict polar and hydrophobic maps are very useful for visual inspection. QM/MM-based workflows were found to be powerful in affinity ranking and are encouraged to be applied more often. The standardized input and output enable systematic analysis and support methodology development and improvement for high level blinded predictions.

Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort

NASA Astrophysics Data System (ADS)

Gao, Ying-Duo; Hu, Yuan; Crespo, Alejandro; Wang, Deping; Armacost, Kira A.; Fells, James I.; Fradera, Xavier; Wang, Hongwu; Wang, Huijun; Sherborne, Brad; Verras, Andreas; Peng, Zhengwei

2018-01-01

The 2016 D3R Grand Challenge 2 includes both pose and affinity or ranking predictions. This article is focused exclusively on affinity predictions submitted to the D3R challenge from a collaborative effort of the modeling and informatics group. Our submissions include ranking of 102 ligands covering 4 different chemotypes against the FXR ligand binding domain structure, and the relative binding affinity predictions of the two designated free energy subsets of 15 and 18 compounds. Using all the complex structures prepared in the same way allowed us to cover many types of workflows and compare their performances effectively. We evaluated typical workflows used in our daily structure-based design modeling support, which include docking scores, force field-based scores, QM/MM, MMGBSA, MD-MMGBSA, and MacroModel interaction energy estimations. The best performing methods for the two free energy subsets are discussed. Our results suggest that affinity ranking still remains very challenging; that the knowledge of more structural information does not necessarily yield more accurate predictions; and that visual inspection and human intervention are considerably important for ranking. Knowledge of the mode of action and protein flexibility along with visualization tools that depict polar and hydrophobic maps are very useful for visual inspection. QM/MM-based workflows were found to be powerful in affinity ranking and are encouraged to be applied more often. The standardized input and output enable systematic analysis and support methodology development and improvement for high level blinded predictions.

Prediction of triple-charm molecular pentaquarks

NASA Astrophysics Data System (ADS)

Chen, Rui; Hosaka, Atsushi; Liu, Xiang

2017-12-01

In a one-boson-exchange model, we study molecular states of double-charm baryon [Ξc c(3621 )] and a charmed meson (D and D*). Our model indicates that there exist two possible triple-charm molecular pentaquarks, a Ξc cD state with I (JP)=0 (1 /2-), and a Ξc cD* state with I (JP)=0 (3 /2-), and we do not find bound solutions for isotriplet states. In addition, we also extend our formula to explore Ξc cB¯(*), Ξc cD¯(*), and Ξc cB(*) systems and find more possible heavy flavor molecular pentaquarks, a Ξc cB ¯ state with I (JP)=0 (1 /2-), a Ξc cB¯* state with I (JP)=0 (3 /2-), and Ξc cD¯*/Ξc cB* states with I (JP)=0 (1 /2-). Experimental research for these predicted triple-charm molecular pentaquarks is encouraged.

Development of 7TM receptor-ligand complex models using ligand-biased, semi-empirical helix-bundle repacking in torsion space: application to the agonist interaction of the human dopamine D2 receptor.

PubMed

Malo, Marcus; Persson, Ronnie; Svensson, Peder; Luthman, Kristina; Brive, Lars

2013-03-01

Prediction of 3D structures of membrane proteins, and of G-protein coupled receptors (GPCRs) in particular, is motivated by their importance in biological systems and the difficulties associated with experimental structure determination. In the present study, a novel method for the prediction of 3D structures of the membrane-embedded region of helical membrane proteins is presented. A large pool of candidate models are produced by repacking of the helices of a homology model using Monte Carlo sampling in torsion space, followed by ranking based on their geometric and ligand-binding properties. The trajectory is directed by weak initial restraints to orient helices towards the original model to improve computation efficiency, and by a ligand to guide the receptor towards a chosen conformational state. The method was validated by construction of the β1 adrenergic receptor model in complex with (S)-cyanopindolol using bovine rhodopsin as template. In addition, models of the dopamine D2 receptor were produced with the selective and rigid agonist (R)-N-propylapomorphine ((R)-NPA) present. A second quality assessment was implemented by evaluating the results from docking of a library of 29 ligands with known activity, which further discriminated between receptor models. Agonist binding and recognition by the dopamine D2 receptor is interpreted using the 3D structure model resulting from the approach. This method has a potential for modeling of all types of helical transmembrane proteins for which a structural template with sequence homology sufficient for homology modeling is not available or is in an incorrect conformational state, but for which sufficient empirical information is accessible.

How much detail is needed in modeling a transcranial magnetic stimulation figure-8 coil: Measurements and brain simulations

PubMed Central

Mandija, Stefano; Sommer, Iris E. C.; van den Berg, Cornelis A. T.; Neggers, Sebastiaan F. W.

2017-01-01

Background Despite TMS wide adoption, its spatial and temporal patterns of neuronal effects are not well understood. Although progress has been made in predicting induced currents in the brain using realistic finite element models (FEM), there is little consensus on how a magnetic field of a typical TMS coil should be modeled. Empirical validation of such models is limited and subject to several limitations. Methods We evaluate and empirically validate models of a figure-of-eight TMS coil that are commonly used in published modeling studies, of increasing complexity: simple circular coil model; coil with in-plane spiral winding turns; and finally one with stacked spiral winding turns. We will assess the electric fields induced by all 3 coil models in the motor cortex using a computer FEM model. Biot-Savart models of discretized wires were used to approximate the 3 coil models of increasing complexity. We use a tailored MR based phase mapping technique to get a full 3D validation of the incident magnetic field induced in a cylindrical phantom by our TMS coil. FEM based simulations on a meshed 3D brain model consisting of five tissues types were performed, using two orthogonal coil orientations. Results Substantial differences in the induced currents are observed, both theoretically and empirically, between highly idealized coils and coils with correctly modeled spiral winding turns. Thickness of the coil winding turns affect minimally the induced electric field, and it does not influence the predicted activation. Conclusion TMS coil models used in FEM simulations should include in-plane coil geometry in order to make reliable predictions of the incident field. Modeling the in-plane coil geometry is important to correctly simulate the induced electric field and to correctly make reliable predictions of neuronal activation PMID:28640923

ADPAC v1.0: User's Manual

NASA Technical Reports Server (NTRS)

Hall, Edward J.; Heidegger, Nathan J.; Delaney, Robert A.

1999-01-01

The overall objective of this study was to evaluate the effects of turbulence models in a 3-D numerical analysis on the wake prediction capability. The current version of the computer code resulting from this study is referred to as ADPAC v7 (Advanced Ducted Propfan Analysis Codes -Version 7). This report is intended to serve as a computer program user's manual for the ADPAC code used and modified under Task 15 of NASA Contract NAS3-27394. The ADPAC program is based on a flexible multiple-block and discretization scheme permitting coupled 2-D/3-D mesh block solutions with application to a wide variety of geometries. Aerodynamic calculations are based on a four-stage Runge-Kutta time-marching finite volume solution technique with added numerical dissipation. Steady flow predictions are accelerated by a multigrid procedure. Turbulence models now available in the ADPAC code are: a simple mixing-length model, the algebraic Baldwin-Lomax model with user defined coefficients, the one-equation Spalart-Allmaras model, and a two-equation k-R model. The consolidated ADPAC code is capable of executing in either a serial or parallel computing mode from a single source code.

The dynamic compressive behavior and constitutive modeling of D1 railway wheel steel over a wide range of strain rates and temperatures

NASA Astrophysics Data System (ADS)

Jing, Lin; Su, Xingya; Zhao, Longmao

The dynamic compressive behavior of D1 railway wheel steel at high strain rates was investigated using a split Hopkinson pressure bar (SHPB) apparatus. Three types of specimens, which were derived from the different positions (i.e., the rim, web and hub) of a railway wheel, were tested over a wide range of strain rates from 10-3 s-1 to 2.4 × 103 s-1 and temperatures from 213 K to 973 K. Influences of the strain rate and temperature on flow stress were discussed, and rate- and temperature-dependent constitutive relationships were assessed by the Cowper-Symonds model, Johnson-Cook model and a physically-based model, respectively. The experimental results show that the compressive true stress versus true strain response of D1 wheel steel is strain rate-dependent, and the strain hardening rate during the plastic flow stage decreases with the elevation of strain rate. Besides, the D1 wheel steel displays obvious temperature-dependence, and the third-type strain aging (3rd SA) is occurred at the temperature region of 673-973 K at a strain rate of ∼1500 s-1. Comparisons of experimental results with theoretical predictions indicate that the physically-based model has a better prediction capability for the 3rd SA characteristic of the tested D1 wheel steel.

AN ASSESSMENT OF THE ABILITY OF 3-D AIR QUALITY MODELS WITH CURRENT THERMODYNAMIC EQUILIBRIUM MODELS TO PREDICT AEROSOL NO3

EPA Science Inventory

The partitioning of total nitrate (TNO3) and total ammonium (TNH4) between gas and aerosol phases is studied with two thermodynamic equilibrium models, ISORROPIA and AIM, and three datasets: high time-resolution measurement data from the 1999 Atlanta SuperSite Experiment and from...

3D tumor microtissues as an in vitro testing platform for microenvironmentally-triggered drug delivery systems.

PubMed

Brancato, Virginia; Gioiella, Filomena; Profeta, Martina; Imparato, Giorgia; Guarnieri, Daniela; Urciuolo, Francesco; Melone, Pietro; Netti, Paolo A

2017-07-15

Therapeutic approaches based on nanomedicine have garnered great attention in cancer research. In vitro biological models that better mimic in vivo conditions are crucial tools to more accurately predict their therapeutic efficacy in vivo. In this work, a new 3D breast cancer microtissue has been developed to recapitulate the complexity of the tumor microenvironment and to test its efficacy as screening platform for drug delivery systems. The proposed 3D cancer model presents human breast adenocarcinoma cells and cancer-associated fibroblasts embedded in their own ECM, thus showing several features of an in vivo tumor, such as overexpression of metallo-proteinases (MMPs). After demonstrating at molecular and protein level the MMP2 overexpression in such tumor microtissues, we used them to test a recently validated formulation of endogenous MMP2-responsive nanoparticles (NP). The presence of the MMP2-sensitive linker allows doxorubicin release from NP only upon specific enzymatic cleavage of the peptide. The same NP without the MMP-sensitive linker and healthy breast microtissues were also produced to demonstrate NP specificity and selectivity. Cell viability after NP treatment confirmed that controlled drug delivery is achieved only in 3D tumor microtissues suggesting that the validation of therapeutic strategies in such 3D tumor model could predict human response. A major issue of modern cancer research is the development of accurate and predictive experimental models of human tumors consistent with tumor microenvironment and applicable as screening platforms for novel therapeutic strategies. In this work, we developed and validated a new 3D microtissue model of human breast tumor as a testing platform of anti-cancer drug delivery systems. To this aim, biodegradable nanoparticles responsive to physiological changes specifically occurring in tumor microenvironment were used. Our findings clearly demonstrate that the breast tumor microtissue well recapitulates in vivo physiological features of tumor tissue and elicits a specific response to microenvironmentally-responsive nanoparticles compared to healthy tissue. We believe this study is of particular interest for cancer research and paves the way to exploit tumor microtissues for several testing purposes. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Using 3D infrared imaging to calibrate and refine computational fluid dynamic modeling for large computer and data centers

NASA Astrophysics Data System (ADS)

Stockton, Gregory R.

2011-05-01

Over the last 10 years, very large government, military, and commercial computer and data center operators have spent millions of dollars trying to optimally cool data centers as each rack has begun to consume as much as 10 times more power than just a few years ago. In fact, the maximum amount of data computation in a computer center is becoming limited by the amount of available power, space and cooling capacity at some data centers. Tens of millions of dollars and megawatts of power are being annually spent to keep data centers cool. The cooling and air flows dynamically change away from any predicted 3-D computational fluid dynamic modeling during construction and as time goes by, and the efficiency and effectiveness of the actual cooling rapidly departs even farther from predicted models. By using 3-D infrared (IR) thermal mapping and other techniques to calibrate and refine the computational fluid dynamic modeling and make appropriate corrections and repairs, the required power for data centers can be dramatically reduced which reduces costs and also improves reliability.

3D-QSAR studies of some reversible Acetyl cholinesterase inhibitors based on CoMFA and ligand protein interaction fingerprints using PC-LS-SVM and PLS-LS-SVM.

PubMed

Ghafouri, Hamidreza; Ranjbar, Mohsen; Sakhteman, Amirhossein

2017-08-01

A great challenge in medicinal chemistry is to develop different methods for structural design based on the pattern of the previously synthesized compounds. In this study two different QSAR methods were established and compared for a series of piperidine acetylcholinesterase inhibitors. In one novel approach, PC-LS-SVM and PLS-LS-SVM was used for modeling 3D interaction descriptors, and in the other method the same nonlinear techniques were used to build QSAR equations based on field descriptors. Different validation methods were used to evaluate the models and the results revealed the more applicability and predictive ability of the model generated by field descriptors (Q 2 LOO-CV =1, R 2 ext =0.97). External validation criteria revealed that both methods can be used in generating reasonable QSAR models. It was concluded that due to ability of interaction descriptors in prediction of binding mode, using this approach can be implemented in future 3D-QSAR softwares. Copyright © 2017 Elsevier Ltd. All rights reserved.

Simulating nanoparticle transport in 3D geometries with MNM3D

NASA Astrophysics Data System (ADS)

Bianco, Carlo; Tosco, Tiziana; Sethi, Rajandrea

2017-04-01

The application of NP transport to real cases, such as the design of a field-scale injection or the prediction of the long term fate of nanoparticles (NPs) in the environment, requires the support of mathematical tools to effectively assess the expected NP mobility at the field scale. In general, micro- and nanoparticle transport in porous media is controlled by particle-particle and particle-porous media interactions, which are in turn affected by flow velocity and pore water chemistry. During the injection, a strong perturbation of the flow field is induced around the well, and the NP transport is mainly controlled by the consequent sharp variation of pore-water velocity. Conversely, when the injection is stopped, the particles are transported solely due to the natural flow, and the influence of groundwater geochemistry (ionic strength, IS, in particular) on the particle behaviour becomes predominant. Pore-water velocity and IS are therefore important parameters influencing particle transport in groundwater, and have to be taken into account by the numerical codes used to simulate NP transport. Several analytical and numerical tools have been developed in recent years to model the transport of colloidal particles in simplified geometry and boundary conditions. For instance, the numerical tool MNMs was developed by the authors of this work to simulate colloidal transport in 1D Cartesian and radial coordinates. Only few simulation tools are instead available for 3D colloid transport, and none of them implements direct correlations accounting for variations of groundwater IS and flow velocity. In this work a new modelling tool, MNM3D (Micro and Nanoparticle transport Model in 3D geometries), is proposed for the simulation of injection and transport of nanoparticle suspensions in generic complex scenarios. MNM3D implements a new formulation to account for the simultaneous dependency of the attachment and detachment kinetic coefficients on groundwater IS and velocity. The software was developed in the framework of the FP7 European research project NanoRem and can be used to predict the NP mobility at different stages of a nanoremediation application, both in the planning and design stages (i.e. support the design of the injection plan), and later to predict the long-term particle mobility after injection (i.e. support the monitoring, final fate of the injected particles). In this work MNM3D an integrated experimental-modelling procedure is used to assess and predict the nanoparticle transport in porous media at different spatial and time scales: laboratory tests are performed and interpreted using MNMs to characterize the nanoparticle mobility and derive the constitutive equations describing the suspension behavior in groundwater. MNM3D is then used to predict the NP transport at the field scale. The procedure is here applied to two practical cases: a 3D pilot scale injection of CARBO-IRON® in a large scale flume carried out at the VEGAS facilities in the framework of the NanoRem project; the long term fate of an hypothetical release of nanoparticles into the environment from a landfill is simulated.

DAT/SERT Selectivity of Flexible GBR 12909 Analogs Modeled Using 3D-QSAR Methods

PubMed Central

Gilbert, Kathleen M.; Boos, Terrence L.; Dersch, Christina M.; Greiner, Elisabeth; Jacobson, Arthur E.; Lewis, David; Matecka, Dorota; Prisinzano, Thomas E.; Zhang, Ying; Rothman, Richard B.; Rice, Kenner C.; Venanzi, Carol A.

2007-01-01

The dopamine reuptake inhibitor GBR 12909 (1-{2-[bis(4-fluorophenyl)methoxy]ethyl}-4-(3-phenylpropyl)piperazine, 1) and its analogs have been developed as tools to test the hypothesis that selective dopamine transporter (DAT) inhibitors will be useful therapeutics for cocaine addiction. This 3D-QSAR study focuses on the effect of substitutions in the phenylpropyl region of 1. CoMFA and CoMSIA techniques were used to determine a predictive and stable model for the DAT/serotonin transporter (SERT) selectivity (represented by pKi (DAT/SERT)) of a set of flexible analogs of 1, most of which have eight rotatable bonds. In the absence of a rigid analog to use as a 3D-QSAR template, six conformational families of analogs were constructed from six pairs of piperazine and piperidine template conformers identified by hierarchical clustering as representative molecular conformations. Three models stable to y-value scrambling were identified after a comprehensive CoMFA and CoMSIA survey with Region Focusing. Test set correlation validation led to an acceptable model, with q2 = 0.508, standard error of prediction = 0.601, two components, r2 = 0.685, standard error of estimate = 0.481, F value = 39, percent steric contribution = 65, and percent electrostatic contribution = 35. A CoMFA contour map identified areas of the molecule that affect pKi (DAT/SERT). This work outlines a protocol for deriving a stable and predictive model of the biological activity of a set of very flexible molecules. PMID:17127069

Development and validation of a computational model of the knee joint for the evaluation of surgical treatments for osteoarthritis

PubMed Central

Mootanah, R.; Imhauser, C.W.; Reisse, F.; Carpanen, D.; Walker, R.W.; Koff, M.F.; Lenhoff, M.W.; Rozbruch, S.R.; Fragomen, A.T.; Dewan, Z.; Kirane, Y.M.; Cheah, Pamela A.; Dowell, J.K.; Hillstrom, H.J.

2014-01-01

A three-dimensional (3D) knee joint computational model was developed and validated to predict knee joint contact forces and pressures for different degrees of malalignment. A 3D computational knee model was created from high-resolution radiological images to emulate passive sagittal rotation (full-extension to 65°-flexion) and weight acceptance. A cadaveric knee mounted on a six-degree-of-freedom robot was subjected to matching boundary and loading conditions. A ligament-tuning process minimised kinematic differences between the robotically loaded cadaver specimen and the finite element (FE) model. The model was validated by measured intra-articular force and pressure measurements. Percent full scale error between EE-predicted and in vitro-measured values in the medial and lateral compartments were 6.67% and 5.94%, respectively, for normalised peak pressure values, and 7.56% and 4.48%, respectively, for normalised force values. The knee model can accurately predict normalised intra-articular pressure and forces for different loading conditions and could be further developed for subject-specific surgical planning. PMID:24786914

Development and validation of a computational model of the knee joint for the evaluation of surgical treatments for osteoarthritis.

PubMed

Mootanah, R; Imhauser, C W; Reisse, F; Carpanen, D; Walker, R W; Koff, M F; Lenhoff, M W; Rozbruch, S R; Fragomen, A T; Dewan, Z; Kirane, Y M; Cheah, K; Dowell, J K; Hillstrom, H J

2014-01-01

A three-dimensional (3D) knee joint computational model was developed and validated to predict knee joint contact forces and pressures for different degrees of malalignment. A 3D computational knee model was created from high-resolution radiological images to emulate passive sagittal rotation (full-extension to 65°-flexion) and weight acceptance. A cadaveric knee mounted on a six-degree-of-freedom robot was subjected to matching boundary and loading conditions. A ligament-tuning process minimised kinematic differences between the robotically loaded cadaver specimen and the finite element (FE) model. The model was validated by measured intra-articular force and pressure measurements. Percent full scale error between FE-predicted and in vitro-measured values in the medial and lateral compartments were 6.67% and 5.94%, respectively, for normalised peak pressure values, and 7.56% and 4.48%, respectively, for normalised force values. The knee model can accurately predict normalised intra-articular pressure and forces for different loading conditions and could be further developed for subject-specific surgical planning.

Verification of the predictive capabilities of the 4C code cryogenic circuit model

NASA Astrophysics Data System (ADS)

Zanino, R.; Bonifetto, R.; Hoa, C.; Richard, L. Savoldi

2014-01-01

The 4C code was developed to model thermal-hydraulics in superconducting magnet systems and related cryogenic circuits. It consists of three coupled modules: a quasi-3D thermal-hydraulic model of the winding; a quasi-3D model of heat conduction in the magnet structures; an object-oriented a-causal model of the cryogenic circuit. In the last couple of years the code and its different modules have undergone a series of validation exercises against experimental data, including also data coming from the supercritical He loop HELIOS at CEA Grenoble. However, all this analysis work was done each time after the experiments had been performed. In this paper a first demonstration is given of the predictive capabilities of the 4C code cryogenic circuit module. To do that, a set of ad-hoc experimental scenarios have been designed, including different heating and control strategies. Simulations with the cryogenic circuit module of 4C have then been performed before the experiment. The comparison presented here between the code predictions and the results of the HELIOS measurements gives the first proof of the excellent predictive capability of the 4C code cryogenic circuit module.

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

Beckingham, Lauren E.; Peters, Catherine A.; Um, Wooyong

Although the impact of subsurface geochemical reactions on porosity is relatively well understood, changes in permeability remain difficult to estimate. In this work, pore-network modeling was used to predict permeability based on pore- and pore-throat size distributions determined from analysis of 2D scanning electron microscopy (SEM) images of thin sections and 3D X-ray computed microtomography (CMT) data. The analyzed specimens were a Viking sandstone sample from the Alberta sedimentary basin and an experimental column of reacted Hanford sediments. For the column, a decrease in permeability due to mineral precipitation was estimated, but the permeability estimates were dependent on imaging techniquemore » and resolution. X-ray CT imaging has the advantage of reconstructing a 3D pore network while 2D SEM imaging can easily analyze sub-grain and intragranular variations in mineralogy. Pore network models informed by analyses of 2D and 3D images at comparable resolutions produced permeability esti- mates with relatively good agreement. Large discrepancies in predicted permeabilities resulted from small variations in image resolution. Images with resolutions 0.4 to 4 lm predicted permeabilities differ- ing by orders of magnitude. While lower-resolution scans can analyze larger specimens, small pore throats may be missed due to resolution limitations, which in turn overestimates permeability in a pore-network model in which pore-to-pore conductances are statistically assigned. Conversely, high-res- olution scans are capable of capturing small pore throats, but if they are not actually flow-conducting predicted permeabilities will be below expected values. In addition, permeability is underestimated due to misinterpreting surface-roughness features as small pore throats. Comparison of permeability pre- dictions with expected and measured permeability values showed that the largest discrepancies resulted from the highest resolution images and the best predictions of permeability will result from images between 2 and 4 lm resolution. To reduce permeability underestimation from analyses of high-resolu- tion images, a resolution threshold between 3 and 15 lm was found to be effective, but it is not known whether this range is applicable beyond the samples studied here.« less

Can contaminant transport models predict breakthrough?

USGS Publications Warehouse

Peng, Wei-Shyuan; Hampton, Duane R.; Konikow, Leonard F.; Kambham, Kiran; Benegar, Jeffery J.

2000-01-01

A solute breakthrough curve measured during a two-well tracer test was successfully predicted in 1986 using specialized contaminant transport models. Water was injected into a confined, unconsolidated sand aquifer and pumped out 125 feet (38.3 m) away at the same steady rate. The injected water was spiked with bromide for over three days; the outflow concentration was monitored for a month. Based on previous tests, the horizontal hydraulic conductivity of the thick aquifer varied by a factor of seven among 12 layers. Assuming stratified flow with small dispersivities, two research groups accurately predicted breakthrough with three-dimensional (12-layer) models using curvilinear elements following the arc-shaped flowlines in this test. Can contaminant transport models commonly used in industry, that use rectangular blocks, also reproduce this breakthrough curve? The two-well test was simulated with four MODFLOW-based models, MT3D (FD and HMOC options), MODFLOWT, MOC3D, and MODFLOW-SURFACT. Using the same 12 layers and small dispersivity used in the successful 1986 simulations, these models fit almost as accurately as the models using curvilinear blocks. Subtle variations in the curves illustrate differences among the codes. Sensitivities of the results to number and size of grid blocks, number of layers, boundary conditions, and values of dispersivity and porosity are briefly presented. The fit between calculated and measured breakthrough curves degenerated as the number of layers and/or grid blocks decreased, reflecting a loss of model predictive power as the level of characterization lessened. Therefore, the breakthrough curve for most field sites can be predicted only qualitatively due to limited characterization of the hydrogeology and contaminant source strength.

Leveraging ISI Multi-Model Prediction for Navy Operations: Proposal to the Office of Naval Research

DTIC Science & Technology

2014-09-30

ISI Multi-Model Prediction for Navy Operations: Proposal to the Office of Naval Research PI: James L. Kinter III Director, Center for Ocean-Land...TYPE 3. DATES COVERED 00-00-2014 to 00-00-2014 4. TITLE AND SUBTITLE Leveraging ISI Multi-Model Prediction for Navy Operations: Proposal to the ... Office of Naval Research 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f

Actinometric measurement of j(O3-O(1D)) using a luminol detector

NASA Technical Reports Server (NTRS)

Bairai, Solomon T.; Stedman, Donald H.

1992-01-01

The photolysis frequency of ozone to singlet D oxygen atoms has been measured by means of a chemical actinometer using a luminol based detector. The instrument measures j(O3-O(1D)) with a precision of 10 percent. The data collected in winter and spring of 1991 is in agreement with model predictions and previously measured values. Data from a global solar radiometer can be used to estimate the effects of local cloudiness on j(O3-O(1D)).

Combined molecular modelling and 3D-QSAR study for understanding the inhibition of NQO1 by heterocyclic quinone derivatives.

PubMed

López-Lira, Claudia; Alzate-Morales, Jans H; Paulino, Margot; Mella-Raipán, Jaime; Salas, Cristian O; Tapia, Ricardo A; Soto-Delgado, Jorge

2018-01-01

A combination of three-dimensional quantitative structure-activity relationship (3D-QSAR), and molecular modelling methods were used to understand the potent inhibitory NAD(P)H:quinone oxidoreductase 1 (NQO1) activity of a set of 52 heterocyclic quinones. Molecular docking results indicated that some favourable interactions of key amino acid residues at the binding site of NQO1 with these quinones would be responsible for an improvement of the NQO1 activity of these compounds. The main interactions involved are hydrogen bond of the amino group of residue Tyr128, π-stacking interactions with Phe106 and Phe178, and electrostatic interactions with flavin adenine dinucleotide (FADH) cofactor. Three models were prepared by 3D-QSAR analysis. The models derived from Model I and Model III, shown leave-one-out cross-validation correlation coefficients (q 2 LOO ) of .75 and .73 as well as conventional correlation coefficients (R 2 ) of .93 and .95, respectively. In addition, the external predictive abilities of these models were evaluated using a test set, producing the predicted correlation coefficients (r 2 pred ) of .76 and .74, respectively. The good concordance between the docking results and 3D-QSAR contour maps provides helpful information about a rational modification of new molecules based in quinone scaffold, in order to design more potent NQO1 inhibitors, which would exhibit highly potent antitumor activity. © 2017 John Wiley & Sons A/S.

Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation

NASA Astrophysics Data System (ADS)

Grudinin, Sergei; Kadukova, Maria; Eisenbarth, Andreas; Marillet, Simon; Cazals, Frédéric

2016-09-01

The 2015 D3R Grand Challenge provided an opportunity to test our new model for the binding free energy of small molecules, as well as to assess our protocol to predict binding poses for protein-ligand complexes. Our pose predictions were ranked 3-9 for the HSP90 dataset, depending on the assessment metric. For the MAP4K dataset the ranks are very dispersed and equal to 2-35, depending on the assessment metric, which does not provide any insight into the accuracy of the method. The main success of our pose prediction protocol was the re-scoring stage using the recently developed Convex-PL potential. We make a thorough analysis of our docking predictions made with AutoDock Vina and discuss the effect of the choice of rigid receptor templates, the number of flexible residues in the binding pocket, the binding pocket size, and the benefits of re-scoring. However, the main challenge was to predict experimentally determined binding affinities for two blind test sets. Our affinity prediction model consisted of two terms, a pairwise-additive enthalpy, and a non pairwise-additive entropy. We trained the free parameters of the model with a regularized regression using affinity and structural data from the PDBBind database. Our model performed very well on the training set, however, failed on the two test sets. We explain the drawback and pitfalls of our model, in particular in terms of relative coverage of the test set by the training set and missed dynamical properties from crystal structures, and discuss different routes to improve it.

Analysis of riverine suspended particulate matter fluxes (Gulf of Lion, Mediterranean Sea) using a synergy of ocean color observations with a 3-D hydrodynamic sediment transport model

NASA Astrophysics Data System (ADS)

Le Fouest, Vincent; Chami, Malik; Verney, Romaric

2015-02-01

The export of riverine suspended particulate matter (SPM) in the coastal ocean has major implications for the biogeochemical cycles. In the Mediterranean Sea (France), the Rhone River inputs of SPM into the Gulf of Lion (GoL) are highly variable in time, which severely impedes the assessment of SPM fluxes. The objectives of this study are (i) to investigate the prediction of the land-to-ocean flux of SPM using the complementarity (i.e., synergy) between a hydrodynamic sediment transport model and satellite observations, and (ii) to analyze the spatial distribution of the SPM export. An original approach that combines the MARS-3D model with satellite ocean color data is proposed. Satellite-derived SPM and light penetration depth are used to initialize MARS-3D and to validate its predictions. A sensitivity analysis is performed to quantify the impact of riverine SPM size composition and settling rate on the horizontal export of SPM. The best agreement between the model and the satellite in terms of SPM spatial distribution and export is obtained for two conditions: (i) when the relative proportion of "heavy and fast" settling particles significantly increases relative to the "light and slow" ones, and (ii) when the settling rate of heavy and light SPM increases by fivefold. The synergy between MARS-3D and the satellite data improved the SPM flux predictions by 48% near the Rhone River mouth. Our results corroborate the importance of implementing satellite observations within initialization procedures of ocean models since data assimilation techniques may fail for river floods showing strong seasonal variability.

Transition of R&D into Operations at Fleet Numerical Meteorology and Oceanography Center

NASA Astrophysics Data System (ADS)

Clancy, R. M.

2006-12-01

The U.S. Navy's Fleet Numerical Meteorology and Oceanography Center (FNMOC) plays a significant role in the National capability for operational weather and ocean prediction through its operation of sophisticated global and regional meteorological and oceanographic models, extending from the top of the atmosphere to the bottom of the ocean. FNMOC uniquely satisfies the military's requirement for a global operational weather prediction capability based on software certified to DoD Information Assurance standards and operated in a secure classified computer environment protected from outside intrusion by DoD certified firewalls. FNMOC operates around-the-clock, 365 days per year and distributes products to military and civilian users around the world, both ashore and afloat, through a variety of means. FNMOC's customers include all branches of the Department of Defense, other government organizations such as the National Weather Service, private companies, a number of colleges and universities, and the general public. FNMOC employs three primary models, the Navy Operational Global Atmospheric Prediction System (NOGAPS), the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS), and the WaveWatch III model (WW3), along with a number of specialized models and related applications. NOGAPS is a global weather model, driving nearly all other FNMOC models and applications in some fashion. COAMPS is a high- resolution regional model that has proved to be particularly valuable for forecasting weather and ocean conditions in highly complex coastal areas. WW3 is a state-of-the-art ocean wave model that is employed both globally and regionally in support of a wide variety of naval operations. Other models support and supplement the main models with predictions of ocean thermal structure, ocean currents, sea-ice characteristics, and other data. Fleet Numerical operates at the leading edge of science and technology, and benefits greatly from collocation with its supporting R&D activity, the Marine Meteorology Division of the Naval Research Laboratory (NRL Code 7500). NRL Code 7500 is a world-class research organization, with focus on weather-related support for the warfighter. Fleet Numerical and NRL Code 7500 share space, data, software and computer systems, and together represent one of the largest concentrations of weather-related intellectual capital in the nation. As documented, for example, by the Board on Atmospheric Sciences and Climate (BASC) of the National Research Council, investment in R&D is crucial for maintaining state-of-the-art operational Numerical Weather Prediction (NWP) capabilities (see BASC, 1998). And collocation and close cooperation between research and operations, such as exists between NRL Code 7500 and Fleet Numerical, is the optimum arrangement for transitioning R&D quickly and cost-effectively into new and improved operational weather prediction capabilities.

Breast Organotypic Cancer Models.

PubMed

Carranza-Rosales, Pilar; Guzmán-Delgado, Nancy Elena; Carranza-Torres, Irma Edith; Viveros-Valdez, Ezequiel; Morán-Martínez, Javier

2018-03-20

Breast cancer is the most common cancer type diagnosed in women, it represents a critical public health problem worldwide, with 1,671,149 estimated new cases and nearly 571,000 related deaths. Research on breast cancer has mainly been conducted using two-dimensional (2D) cell cultures and animal models. The usefulness of these models is reflected in the vast knowledge accumulated over the past decades. However, considering that animal models are three-dimensional (3D) in nature, the validity of the studies using 2D cell cultures has recently been questioned. Although animal models are important in cancer research, ethical questions arise about their use and usefulness as there is no clear predictivity of human disease outcome and they are very expensive and take too much time to obtain results. The poor performance or failure of most cancer drugs suggests that preclinical research on cancer has been based on an over-dependence on inadequate animal models. For these reasons, in the last few years development of alternative models has been prioritized to study human breast cancer behavior, while maintaining a 3D microenvironment, and to reduce the number of experiments conducted in animals. One way to achieve this is using organotypic cultures, which are being more frequently explored in cancer research because they mimic tissue architecture in vivo. These characteristics make organotypic cultures a valuable tool in cancer research as an alternative to replace animal models and for predicting risk assessment in humans. This chapter describes the cultures of multicellular spheroids, organoids, 3D bioreactors, and tumor slices, which are the most widely used organotypic models in breast cancer research.

The urban energy balance of a lightweight low-rise neighborhood in Andacollo, Chile

NASA Astrophysics Data System (ADS)

Crawford, Ben; Krayenhoff, E. Scott; Cordy, Paul

2018-01-01

Worldwide, the majority of rapidly growing neighborhoods are found in the Global South. They often exhibit different building construction and development patterns than the Global North, and urban climate research in many such neighborhoods has to date been sparse. This study presents local-scale observations of net radiation ( Q * ) and sensible heat flux ( Q H ) from a lightweight low-rise neighborhood in the desert climate of Andacollo, Chile, and compares observations with results from a process-based urban energy-balance model (TUF3D) and a local-scale empirical model (LUMPS) for a 14-day period in autumn 2009. This is a unique neighborhood-climate combination in the urban energy-balance literature, and results show good agreement between observations and models for Q * and Q H . The unmeasured latent heat flux ( Q E ) is modeled with an updated version of TUF3D and two versions of LUMPS (a forward and inverse application). Both LUMPS implementations predict slightly higher Q E than TUF3D, which may indicate a bias in LUMPS parameters towards mid-latitude, non-desert climates. Overall, the energy balance is dominated by sensible and storage heat fluxes with mean daytime Bowen ratios of 2.57 (observed Q H /LUMPS Q E )-3.46 (TUF3D). Storage heat flux ( ΔQ S ) is modeled with TUF3D, the empirical objective hysteresis model (OHM), and the inverse LUMPS implementation. Agreement between models is generally good; the OHM-predicted diurnal cycle deviates somewhat relative to the other two models, likely because OHM coefficients are not specified for the roof and wall construction materials found in this neighborhood. New facet-scale and local-scale OHM coefficients are developed based on modeled ΔQ S and observed Q * . Coefficients in the empirical models OHM and LUMPS are derived from observations in primarily non-desert climates in European/North American neighborhoods and must be updated as measurements in lightweight low-rise (and other) neighborhoods in various climates become available.

The Volume of Three-Dimensional Cultures of Cancer Cells InVitro Influences Transcriptional Profile Differences and Similarities with Monolayer Cultures and Xenografted Tumors.

PubMed

Boghaert, Erwin R; Lu, Xin; Hessler, Paul E; McGonigal, Thomas P; Oleksijew, Anatol; Mitten, Michael J; Foster-Duke, Kelly; Hickson, Jonathan A; Santo, Vitor E; Brito, Catarina; Uziel, Tamar; Vaidya, Kedar S

2017-09-01

Improving the congruity of preclinical models with cancer as it is manifested in humans is a potential way to mitigate the high attrition rate of new cancer therapies in the clinic. In this regard, three-dimensional (3D) tumor cultures in vitro have recently regained interest as they have been acclaimed to have higher similarity to tumors in vivo than to cells grown in monolayers (2D). To identify cancer functions that are active in 3D rather than in 2D cultures, we compared the transcriptional profiles (TPs) of two non-small cell lung carcinoma cell lines, NCI-H1650 and EBC-1 grown in both conditions to the TP of xenografted tumors. Because confluence, diameter or volume can hypothetically alter TPs, we made intra- and inter-culture comparisons using samples with defined dimensions. As projected by Ingenuity Pathway Analysis (IPA), a limited number of signal transduction pathways operational in vivo were better represented by 3D than by 2D cultures in vitro. Growth of 2D and 3D cultures as well as xenografts induced major changes in the TPs of these 3 modes of culturing. Alterations of transcriptional network activation that were predicted to evolve similarly during progression of 3D cultures and xenografts involved the following functions: hypoxia, proliferation, cell cycle progression, angiogenesis, cell adhesion, and interleukin activation. Direct comparison of TPs of 3D cultures and xenografts to monolayer cultures yielded up-regulation of networks involved in hypoxia, TGF and Wnt signaling as well as regulation of epithelial mesenchymal transition. Differences in TP of 2D and 3D cancer cell cultures are subject to progression of the cultures. The emulation of the predicted cell functions in vivo is therefore not only determined by the type of culture in vitro but also by the confluence or diameter of the 2D or 3D cultures, respectively. Consequently, the successful implementation of 3D models will require phenotypic characterization to verify the relevance of applying these models for drug development. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Dietary Iodine Sufficiency and Moderate Insufficiency in the Lactating Mother and Nursing Infant: A Computational Perspective

PubMed Central

Fisher, W.; Wang, Jian; George, Nysia I.; Gearhart, Jeffery M.; McLanahan, Eva D.

2016-01-01

The Institute of Medicine recommends that lactating women ingest 290 μg iodide/d and a nursing infant, less than two years of age, 110 μg/d. The World Health Organization, United Nations Children’s Fund, and International Council for the Control of Iodine Deficiency Disorders recommend population maternal and infant urinary iodide concentrations ≥ 100 μg/L to ensure iodide sufficiency. For breast milk, researchers have proposed an iodide concentration range of 150–180 μg/L indicates iodide sufficiency for the mother and infant, however no national or international guidelines exist for breast milk iodine concentration. For the first time, a lactating woman and nursing infant biologically based model, from delivery to 90 days postpartum, was constructed to predict maternal and infant urinary iodide concentration, breast milk iodide concentration, the amount of iodide transferred in breast milk to the nursing infant each day and maternal and infant serum thyroid hormone kinetics. The maternal and infant models each consisted of three sub-models, iodide, thyroxine (T4), and triiodothyronine (T3). Using our model to simulate a maternal intake of 290 μg iodide/d, the average daily amount of iodide ingested by the nursing infant, after 4 days of life, gradually increased from 50 to 101 μg/day over 90 days postpartum. The predicted average lactating mother and infant urinary iodide concentrations were both in excess of 100 μg/L and the predicted average breast milk iodide concentration, 157 μg/L. The predicted serum thyroid hormones (T4, free T4 (fT4), and T3) in both the nursing infant and lactating mother were indicative of euthyroidism. The model was calibrated using serum thyroid hormone concentrations for lactating women from the United States and was successful in predicting serum T4 and fT4 levels (within a factor of two) for lactating women in other countries. T3 levels were adequately predicted. Infant serum thyroid hormone levels were adequately predicted for most data. For moderate iodide deficient conditions, where dietary iodide intake may range from 50 to 150 μg/d for the lactating mother, the model satisfactorily described the iodide measurements, although with some variation, in urine and breast milk. Predictions of serum thyroid hormones in moderately iodide deficient lactating women (50 μg/d) and nursing infants did not closely agree with mean reported serum thyroid hormone levels, however, predictions were usually within a factor of two. Excellent agreement between prediction and observation was obtained for a recent moderate iodide deficiency study in lactating women. Measurements included iodide levels in urine of infant and mother, iodide in breast milk, and serum thyroid hormone levels in infant and mother. A maternal iodide intake of 50 μg/d resulted in a predicted 29–32% reduction in serum T4 and fT4 in nursing infants, however the reduced serum levels of T4 and fT4 were within most of the published reference intervals for infant. This biologically based model is an important first step at integrating the rapid changes that occur in the thyroid system of the nursing newborn in order to predict adverse outcomes from exposure to thyroid acting chemicals, drugs, radioactive materials or iodine deficiency. PMID:26930410

Dietary Iodine Sufficiency and Moderate Insufficiency in the Lactating Mother and Nursing Infant: A Computational Perspective.

PubMed

Fisher, W; Wang, Jian; George, Nysia I; Gearhart, Jeffery M; McLanahan, Eva D

2016-01-01

The Institute of Medicine recommends that lactating women ingest 290 μg iodide/d and a nursing infant, less than two years of age, 110 μg/d. The World Health Organization, United Nations Children's Fund, and International Council for the Control of Iodine Deficiency Disorders recommend population maternal and infant urinary iodide concentrations ≥ 100 μg/L to ensure iodide sufficiency. For breast milk, researchers have proposed an iodide concentration range of 150-180 μg/L indicates iodide sufficiency for the mother and infant, however no national or international guidelines exist for breast milk iodine concentration. For the first time, a lactating woman and nursing infant biologically based model, from delivery to 90 days postpartum, was constructed to predict maternal and infant urinary iodide concentration, breast milk iodide concentration, the amount of iodide transferred in breast milk to the nursing infant each day and maternal and infant serum thyroid hormone kinetics. The maternal and infant models each consisted of three sub-models, iodide, thyroxine (T4), and triiodothyronine (T3). Using our model to simulate a maternal intake of 290 μg iodide/d, the average daily amount of iodide ingested by the nursing infant, after 4 days of life, gradually increased from 50 to 101 μg/day over 90 days postpartum. The predicted average lactating mother and infant urinary iodide concentrations were both in excess of 100 μg/L and the predicted average breast milk iodide concentration, 157 μg/L. The predicted serum thyroid hormones (T4, free T4 (fT4), and T3) in both the nursing infant and lactating mother were indicative of euthyroidism. The model was calibrated using serum thyroid hormone concentrations for lactating women from the United States and was successful in predicting serum T4 and fT4 levels (within a factor of two) for lactating women in other countries. T3 levels were adequately predicted. Infant serum thyroid hormone levels were adequately predicted for most data. For moderate iodide deficient conditions, where dietary iodide intake may range from 50 to 150 μg/d for the lactating mother, the model satisfactorily described the iodide measurements, although with some variation, in urine and breast milk. Predictions of serum thyroid hormones in moderately iodide deficient lactating women (50 μg/d) and nursing infants did not closely agree with mean reported serum thyroid hormone levels, however, predictions were usually within a factor of two. Excellent agreement between prediction and observation was obtained for a recent moderate iodide deficiency study in lactating women. Measurements included iodide levels in urine of infant and mother, iodide in breast milk, and serum thyroid hormone levels in infant and mother. A maternal iodide intake of 50 μg/d resulted in a predicted 29-32% reduction in serum T4 and fT4 in nursing infants, however the reduced serum levels of T4 and fT4 were within most of the published reference intervals for infant. This biologically based model is an important first step at integrating the rapid changes that occur in the thyroid system of the nursing newborn in order to predict adverse outcomes from exposure to thyroid acting chemicals, drugs, radioactive materials or iodine deficiency.

Development, Verification and Use of Gust Modeling in the NASA Computational Fluid Dynamics Code FUN3D

NASA Technical Reports Server (NTRS)

Bartels, Robert E.

2012-01-01

This paper presents the implementation of gust modeling capability in the CFD code FUN3D. The gust capability is verified by computing the response of an airfoil to a sharp edged gust. This result is compared with the theoretical result. The present simulations will be compared with other CFD gust simulations. This paper also serves as a users manual for FUN3D gust analyses using a variety of gust profiles. Finally, the development of an Auto-Regressive Moving-Average (ARMA) reduced order gust model using a gust with a Gaussian profile in the FUN3D code is presented. ARMA simulated results of a sequence of one-minus-cosine gusts is shown to compare well with the same gust profile computed with FUN3D. Proper Orthogonal Decomposition (POD) is combined with the ARMA modeling technique to predict the time varying pressure coefficient increment distribution due to a novel gust profile. The aeroelastic response of a pitch/plunge airfoil to a gust environment is computed with a reduced order model, and compared with a direct simulation of the system in the FUN3D code. The two results are found to agree very well.

Modeling local structure using crystal field and spin Hamiltonian parameters: the tetragonal FeK3+-OI2- defect center in KTaO3 crystal

NASA Astrophysics Data System (ADS)

Gnutek, P.; Y Yang, Z.; Rudowicz, C.

2009-11-01

The local structure and the spin Hamiltonian (SH) parameters, including the zero-field-splitting (ZFS) parameters D and (a+2F/3), and the Zeeman g factors g_{\\parallel } and g_{\\perp } , are theoretically investigated for the FeK3+-OI2- center in KTaO3 crystal. The microscopic SH (MSH) parameters are modeled within the framework of the crystal field (CF) theory employing the CF analysis (CFA) package, which also incorporates the MSH modules. Our approach takes into account the spin-orbit interaction as well as the spin-spin and spin-other-orbit interactions omitted in previous studies. The superposition model (SPM) calculations are carried out to provide input CF parameters for the CFA/MSH package. The combined SPM-CFA/MSH approach is used to consider various structural models for the FeK3+-OI2- defect center in KTaO3. This modeling reveals that the off-center displacement of the Fe3+ ions, Δ1(Fe3+), combined with an inward relaxation of the nearest oxygen ligands, Δ2(O2-), and the existence of the interstitial oxygen OI2- give rise to a strong tetragonal crystal field. This finding may explain the large ZFS experimentally observed for the FeK3+-OI2- center in KTaO3. Matching the theoretical MSH predictions with the available structural data as well as electron magnetic resonance (EMR) and optical spectroscopy data enables predicting reasonable ranges of values of Δ1(Fe3+) and Δ2(O2-) as well as the possible location of OI2- ligands around Fe3+ ions in KTaO3. The defect structure model obtained using the SPM-CFA/MSH approach reproduces very well the ranges of the experimental SH parameters D, g_{\\parallel } and g_{\\perp } and importantly yields not only the correct magnitude of D but also the sign, unlike previous studies. More reliable predictions may be achieved when experimental data on (a+2F/3) and/or crystal field energy levels become available. Comparison of our results with those arising from alternative models existing in the literature indicates considerable advantages of our method and presumably higher reliability of our predictions.

Demonstration of an Integrated Compliance Model for Predicting Copper Fate and Effects in DoD Harbors

DTIC Science & Technology

2008-12-01

shaped larvae (120 µm), (c) purple sea urchin (Strongylocentrotus purpuratus; adults, 5- to 7-cm diameter), (d) sea urchin pluteus larva (200 µm...development tests with mussels (M. galloprovin- cialis) and purple sea urchins (S. purpuratus) expressed as water concentration or whole-body residues...galloprovincialis (bay mussel), D. excentricus (sand dollar) and S. purpuratus (purple sea urchin ) by the integrated CH3D/seawater-BLM model for the

LIBP-Pred: web server for lipid binding proteins using structural network parameters; PDB mining of human cancer biomarkers and drug targets in parasites and bacteria.

PubMed

González-Díaz, Humberto; Munteanu, Cristian R; Postelnicu, Lucian; Prado-Prado, Francisco; Gestal, Marcos; Pazos, Alejandro

2012-03-01

Lipid-Binding Proteins (LIBPs) or Fatty Acid-Binding Proteins (FABPs) play an important role in many diseases such as different types of cancer, kidney injury, atherosclerosis, diabetes, intestinal ischemia and parasitic infections. Thus, the computational methods that can predict LIBPs based on 3D structure parameters became a goal of major importance for drug-target discovery, vaccine design and biomarker selection. In addition, the Protein Data Bank (PDB) contains 3000+ protein 3D structures with unknown function. This list, as well as new experimental outcomes in proteomics research, is a very interesting source to discover relevant proteins, including LIBPs. However, to the best of our knowledge, there are no general models to predict new LIBPs based on 3D structures. We developed new Quantitative Structure-Activity Relationship (QSAR) models based on 3D electrostatic parameters of 1801 different proteins, including 801 LIBPs. We calculated these electrostatic parameters with the MARCH-INSIDE software and they correspond to the entire protein or to specific protein regions named core, inner, middle, and surface. We used these parameters as inputs to develop a simple Linear Discriminant Analysis (LDA) classifier to discriminate 3D structure of LIBPs from other proteins. We implemented this predictor in the web server named LIBP-Pred, freely available at , along with other important web servers of the Bio-AIMS portal. The users can carry out an automatic retrieval of protein structures from PDB or upload their custom protein structural models from their disk created with LOMETS server. We demonstrated the PDB mining option performing a predictive study of 2000+ proteins with unknown function. Interesting results regarding the discovery of new Cancer Biomarkers in humans or drug targets in parasites have been discussed here in this sense.

Aircraft Measurements for Understanding Air-Sea Coupling and Improving Coupled Model Predictions

DTIC Science & Technology

2013-09-30

physical parameterizations of the coupled model in various large-scale forcing conditions. OBJECTIVES The NOAA WP-3D efforts of DYNAMO /LASP intend...various phases of the MJO; 3) to extend point measurements on island and ships to a broader area near the DYNAMO region; and 4) To obtain a suite of...upper ocean characteristics from a large number of AXBT/AXCTD data. In addition, as one of the unique measurement strategy of LASP/ DYNAMO WP-3D project

Structure prediction and analysis of MxaF from obligate, facultative and restricted facultative methylobacterium.

PubMed

Singh, Raghvendra Pratap; Singh, Ram Nageena; Srivastava, Manish K; Srivastava, Alok Kumar; Kumar, Sudheer; Dubey, Ramesh Chandra; Sharma, Arun Kumar

2012-01-01

Methylobacteria are ubiquitous in the biosphere which are capable of growing on C1 compounds such as formate, formaldehyde, methanol and methylamine as well as on a wide range of multi-carbon growth substrates such as C2, C3 and C4 compounds due to the methylotrophic enzymes methanol dehydrogenase (MDH). MDH is performing these functions with the help of a key protein mxaF. Unfortunately, detailed structural analysis and homology modeling of mxaF is remains undefined. Hence, the objective of this research is the characterization and three dimensional modeling of mxaF protein from three different methylotrophs by using I-TASSER server. The predicted model were further optimize and validate by Profile 3D, Errat, Verifiy3-D and PROCHECK server. Predicted and best evaluated models have been successfully deposited to PMDB database with PMDB ID PM0077505, PM0077506 and PM0077507. Active site identification revealed 11, 13 and 14 putative functional site residues in respected models. It may play a major role during protein-protein, and protein-cofactor interactions. This study can provide us an ab-initio and detail information to understand the structure, mechanism of action and regulation of mxaF protein.

Structure prediction and analysis of MxaF from obligate, facultative and restricted facultative methylobacterium

PubMed Central

Singh, Raghvendra Pratap; Singh, Ram Nageena; Srivastava, Manish K; Srivastava, Alok Kumar; Kumar, Sudheer; Dubey, Ramesh Chandra; Sharma, Arun Kumar

2012-01-01

Methylobacteria are ubiquitous in the biosphere which are capable of growing on C1 compounds such as formate, formaldehyde, methanol and methylamine as well as on a wide range of multi-carbon growth substrates such as C2, C3 and C4 compounds due to the methylotrophic enzymes methanol dehydrogenase (MDH). MDH is performing these functions with the help of a key protein mxaF. Unfortunately, detailed structural analysis and homology modeling of mxaF is remains undefined. Hence, the objective of this research is the characterization and three dimensional modeling of mxaF protein from three different methylotrophs by using I-TASSER server. The predicted model were further optimize and validate by Profile 3D, Errat, Verifiy3-D and PROCHECK server. Predicted and best evaluated models have been successfully deposited to PMDB database with PMDB ID PM0077505, PM0077506 and PM0077507. Active site identification revealed 11, 13 and 14 putative functional site residues in respected models. It may play a major role during protein-protein, and protein-cofactor interactions. This study can provide us an ab-initio and detail information to understand the structure, mechanism of action and regulation of mxaF protein. PMID:23275704

Ghosting in anaglyphic stereoscopic images

NASA Astrophysics Data System (ADS)

Woods, Andrew J.; Rourke, Tegan

2004-05-01

Anaglyphic 3D images are an easy way of displaying stereoscopic 3D images on a wide range of display types, e.g. CRT, LCD, print, etc. While the anaglyphic 3D image method is cheap and accessible, its use requires a compromise in stereoscopic image quality. A common problem with anaglyphic 3D images is ghosting. Ghosting (or crosstalk) is the leaking of an image to one eye, when it is intended exclusively for the other eye. Ghosting degrades the ability of the observer to fuse the stereoscopic image and hence the quality of the 3D image is reduced. Ghosting is present in various levels with most stereoscopic displays, however it is often particularly evident with anaglyphic 3D images. This paper describes a project whose aim was to characterize the presence of ghosting in anaglyphic 3D images due to spectral issues. The spectral response curves of several different display types and several different brands of anaglyph glasses were measured using a spectroradiometer or spectrophotometer. A mathematical model was then developed to predict the amount of crosstalk in anaglyphic 3D images when different combinations of displays and glasses are used, and therefore predict the best type of anaglyph glasses for use with a particular display type.

Translational Modeling in Schizophrenia: Predicting Human Dopamine D2 Receptor Occupancy.

PubMed

Johnson, Martin; Kozielska, Magdalena; Pilla Reddy, Venkatesh; Vermeulen, An; Barton, Hugh A; Grimwood, Sarah; de Greef, Rik; Groothuis, Geny M M; Danhof, Meindert; Proost, Johannes H

2016-04-01

To assess the ability of a previously developed hybrid physiology-based pharmacokinetic-pharmacodynamic (PBPKPD) model in rats to predict the dopamine D2 receptor occupancy (D2RO) in human striatum following administration of antipsychotic drugs. A hybrid PBPKPD model, previously developed using information on plasma concentrations, brain exposure and D2RO in rats, was used as the basis for the prediction of D2RO in human. The rat pharmacokinetic and brain physiology parameters were substituted with human population pharmacokinetic parameters and human physiological information. To predict the passive transport across the human blood-brain barrier, apparent permeability values were scaled based on rat and human brain endothelial surface area. Active efflux clearance in brain was scaled from rat to human using both human brain endothelial surface area and MDR1 expression. Binding constants at the D2 receptor were scaled based on the differences between in vitro and in vivo systems of the same species. The predictive power of this physiology-based approach was determined by comparing the D2RO predictions with the observed human D2RO of six antipsychotics at clinically relevant doses. Predicted human D2RO was in good agreement with clinically observed D2RO for five antipsychotics. Models using in vitro information predicted human D2RO well for most of the compounds evaluated in this analysis. However, human D2RO was under-predicted for haloperidol. The rat hybrid PBPKPD model structure, integrated with in vitro information and human pharmacokinetic and physiological information, constitutes a scientific basis to predict the time course of D2RO in man.

Geometrical modeling of complete dental shapes by using panoramic X-ray, digital mouth data and anatomical templates.

PubMed

Barone, Sandro; Paoli, Alessandro; Razionale, Armando Viviano

2015-07-01

In the field of orthodontic planning, the creation of a complete digital dental model to simulate and predict treatments is of utmost importance. Nowadays, orthodontists use panoramic radiographs (PAN) and dental crown representations obtained by optical scanning. However, these data do not contain any 3D information regarding tooth root geometries. A reliable orthodontic treatment should instead take into account entire geometrical models of dental shapes in order to better predict tooth movements. This paper presents a methodology to create complete 3D patient dental anatomies by combining digital mouth models and panoramic radiographs. The modeling process is based on using crown surfaces, reconstructed by optical scanning, and root geometries, obtained by adapting anatomical CAD templates over patient specific information extracted from radiographic data. The radiographic process is virtually replicated on crown digital geometries through the Discrete Radon Transform (DRT). The resulting virtual PAN image is used to integrate the actual radiographic data and the digital mouth model. This procedure provides the root references on the 3D digital crown models, which guide a shape adjustment of the dental CAD templates. The entire geometrical models are finally created by merging dental crowns, captured by optical scanning, and root geometries, obtained from the CAD templates. Copyright © 2015 Elsevier Ltd. All rights reserved.

Prediction of residual feed intake for first-lactation dairy cows using orthogonal polynomial random regression.

PubMed

Manafiazar, G; McFadden, T; Goonewardene, L; Okine, E; Basarab, J; Li, P; Wang, Z

2013-01-01

Residual Feed Intake (RFI) is a measure of energy efficiency. Developing an appropriate model to predict expected energy intake while accounting for multifunctional energy requirements of metabolic body weight (MBW), empty body weight (EBW), milk production energy requirements (MPER), and their nonlinear lactation profiles, is the key to successful prediction of RFI in dairy cattle. Individual daily actual energy intake and monthly body weight of 281 first-lactation dairy cows from 1 to 305 d in milk were recorded at the Dairy Research and Technology Centre of the University of Alberta (Edmonton, AB, Canada); individual monthly milk yield and compositions were obtained from the Dairy Herd Improvement Program. Combinations of different orders (1-5) of fixed (F) and random (R) factors were fitted using Legendre polynomial regression to model the nonlinear lactation profiles of MBW, EBW, and MPER over 301 d. The F5R3, F5R3, and F5R2 (subscripts indicate the order fitted) models were selected, based on the combination of the log-likelihood ratio test and the Bayesian information criterion, as the best prediction equations for MBW, EBW, and MPER, respectively. The selected models were used to predict daily individual values for these traits. To consider the body reserve changes, the differences of predicted EBW between 2 consecutive days were considered as the EBW change between these days. The smoothed total 301-d actual energy intake was then linearly regressed on the total 301-d predicted traits of MBW, EBW change, and MPER to obtain the first-lactation RFI (coefficient of determination=0.68). The mean of predicted daily average lactation RFI was 0 and ranged from -6.58 to 8.64 Mcal of NE(L)/d. Fifty-one percent of the animals had an RFI value below the mean (efficient) and 49% of them had an RFI value above the mean (inefficient). These results indicate that the first-lactation RFI can be predicted from its component traits with a reasonable coefficient of determination. The predicted RFI could be used in the dairy breeding program to increase profitability by selecting animals that are genetically superior in energy efficiency based on RFI, or through routinely measured traits, which are genetically correlated with RFI. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Role of dopamine D2 receptors in human reinforcement learning.

PubMed

Eisenegger, Christoph; Naef, Michael; Linssen, Anke; Clark, Luke; Gandamaneni, Praveen K; Müller, Ulrich; Robbins, Trevor W

2014-09-01

Influential neurocomputational models emphasize dopamine (DA) as an electrophysiological and neurochemical correlate of reinforcement learning. However, evidence of a specific causal role of DA receptors in learning has been less forthcoming, especially in humans. Here we combine, in a between-subjects design, administration of a high dose of the selective DA D2/3-receptor antagonist sulpiride with genetic analysis of the DA D2 receptor in a behavioral study of reinforcement learning in a sample of 78 healthy male volunteers. In contrast to predictions of prevailing models emphasizing DA's pivotal role in learning via prediction errors, we found that sulpiride did not disrupt learning, but rather induced profound impairments in choice performance. The disruption was selective for stimuli indicating reward, whereas loss avoidance performance was unaffected. Effects were driven by volunteers with higher serum levels of the drug, and in those with genetically determined lower density of striatal DA D2 receptors. This is the clearest demonstration to date for a causal modulatory role of the DA D2 receptor in choice performance that might be distinct from learning. Our findings challenge current reward prediction error models of reinforcement learning, and suggest that classical animal models emphasizing a role of postsynaptic DA D2 receptors in motivational aspects of reinforcement learning may apply to humans as well.

Role of Dopamine D2 Receptors in Human Reinforcement Learning

PubMed Central

Eisenegger, Christoph; Naef, Michael; Linssen, Anke; Clark, Luke; Gandamaneni, Praveen K; Müller, Ulrich; Robbins, Trevor W

2014-01-01

Influential neurocomputational models emphasize dopamine (DA) as an electrophysiological and neurochemical correlate of reinforcement learning. However, evidence of a specific causal role of DA receptors in learning has been less forthcoming, especially in humans. Here we combine, in a between-subjects design, administration of a high dose of the selective DA D2/3-receptor antagonist sulpiride with genetic analysis of the DA D2 receptor in a behavioral study of reinforcement learning in a sample of 78 healthy male volunteers. In contrast to predictions of prevailing models emphasizing DA's pivotal role in learning via prediction errors, we found that sulpiride did not disrupt learning, but rather induced profound impairments in choice performance. The disruption was selective for stimuli indicating reward, whereas loss avoidance performance was unaffected. Effects were driven by volunteers with higher serum levels of the drug, and in those with genetically determined lower density of striatal DA D2 receptors. This is the clearest demonstration to date for a causal modulatory role of the DA D2 receptor in choice performance that might be distinct from learning. Our findings challenge current reward prediction error models of reinforcement learning, and suggest that classical animal models emphasizing a role of postsynaptic DA D2 receptors in motivational aspects of reinforcement learning may apply to humans as well. PMID:24713613

Glyph-based analysis of multimodal directional distributions in vector field ensembles

NASA Astrophysics Data System (ADS)

Jarema, Mihaela; Demir, Ismail; Kehrer, Johannes; Westermann, Rüdiger

2015-04-01

Ensemble simulations are increasingly often performed in the geosciences in order to study the uncertainty and variability of model predictions. Describing ensemble data by mean and standard deviation can be misleading in case of multimodal distributions. We present first results of a glyph-based visualization of multimodal directional distributions in 2D and 3D vector ensemble data. Directional information on the circle/sphere is modeled using mixtures of probability density functions (pdfs), which enables us to characterize the distributions with relatively few parameters. The resulting mixture models are represented by 2D and 3D lobular glyphs showing direction, spread and strength of each principal mode of the distributions. A 3D extension of our approach is realized by means of an efficient GPU rendering technique. We demonstrate our method in the context of ensemble weather simulations.

Generalized thick strip modelling for vortex-induced vibration of long flexible cylinders

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

Bao, Y., E-mail: ybao@sjtu.edu.cn; Department of Aeronautics, Imperial College London, South Kensington Campus, London; Palacios, R., E-mail: r.palacios@imperial.ac.uk

2016-09-15

We propose a generalized strip modelling method that is computationally efficient for the VIV prediction of long flexible cylinders in three-dimensional incompressible flow. In order to overcome the shortcomings of conventional strip-theory-based 2D models, the fluid domain is divided into “thick” strips, which are sufficiently thick to locally resolve the small scale turbulence effects and three dimensionality of the flow around the cylinder. An attractive feature of the model is that we independently construct a three-dimensional scale resolving model for individual strips, which have local spanwise scale along the cylinder's axial direction and are only coupled through the structural modelmore » of the cylinder. Therefore, this approach is able to cover the full spectrum for fully resolved 3D modelling to 2D strip theory. The connection between these strips is achieved through the calculation of a tensioned beam equation, which is used to represent the dynamics of the flexible body. In the limit, however, a single “thick” strip would fill the full 3D domain. A parallel Fourier spectral/hp element method is employed to solve the 3D flow dynamics in the strip-domain, and then the VIV response prediction is achieved through the strip–structure interactions. Numerical tests on both laminar and turbulent flows as well as the comparison against the fully resolved DNS are presented to demonstrate the applicability of this approach.« less

TBIEM3D: A Computer Program for Predicting Ducted Fan Engine Noise. Version 1.1

NASA Technical Reports Server (NTRS)

Dunn, M. H.

1997-01-01

This document describes the usage of the ducted fan noise prediction program TBIEM3D (Thin duct - Boundary Integral Equation Method - 3 Dimensional). A scattering approach is adopted in which the acoustic pressure field is split into known incident and unknown scattered parts. The scattering of fan-generated noise by a finite length circular cylinder in a uniform flow field is considered. The fan noise is modeled by a collection of spinning point thrust dipoles. The program, based on a Boundary Integral Equation Method (BIEM), calculates circumferential modal coefficients of the acoustic pressure at user-specified field locations. The duct interior can be of the hard wall type or lined. The duct liner is axisymmetric, locally reactive, and can be uniform or axially segmented. TBIEM3D is written in the FORTRAN programming language. Input to TBIEM3D is minimal and consists of geometric and kinematic parameters. Discretization and numerical parameters are determined automatically by the code. Several examples are presented to demonstrate TBIEM3D capabilities.

Theoretical and Experimental Study of Bacterial Colony Growth in 3D

NASA Astrophysics Data System (ADS)

Shao, Xinxian; Mugler, Andrew; Nemenman, Ilya

2014-03-01

Bacterial cells growing in liquid culture have been well studied and modeled. However, in nature, bacteria often grow as biofilms or colonies in physically structured habitats. A comprehensive model for population growth in such conditions has not yet been developed. Based on the well-established theory for bacterial growth in liquid culture, we develop a model for colony growth in 3D in which a homogeneous colony of cells locally consume a diffusing nutrient. We predict that colony growth is initially exponential, as in liquid culture, but quickly slows to sub-exponential after nutrient is locally depleted. This prediction is consistent with our experiments performed with E. coli in soft agar. Our model provides a baseline to which studies of complex growth process, such as such as spatially and phenotypically heterogeneous colonies, must be compared.

Hints for new sources of flavour violation in meson mixing

NASA Astrophysics Data System (ADS)

Blanke, M.

2017-07-01

The recent results by the Fermilab-Lattice and MILC collaborations on the hadronic matrix elements entering B_{d,s} - bar{B}_{d,s} mixing show a significant tension of the measured values of the mass differences Δ M_{d,s} with their SM predictions. We review the implications of these results in the context of Constrained Minimal Flavour Violation models. In these models, the CKM elements γ and \\vert V_{ub}\\vert/\\vert V_{cb}\\vert can be determined from B_{d,s} - bar{B}_{d,s} mixing observables, yielding a prediction for γ below its tree-level value. Determining subsequently \\vert V_{cb}\\vert from the measured value of either Δ M_s or ɛ_K gives inconsistent results, with the tension being smallest in the Standard Model limit. This tension can be resolved if the flavour universality of new contributions to Δ F = 2 observables is broken. We briefly discuss the case of U(2)^3 flavour models as an illustrative example.

Clinical anthropometrics and body composition from 3D whole-body surface scans

PubMed Central

Ng, BK; Hinton, BJ; Fan, B; Kanaya, AM; Shepherd, JA

2017-01-01

BACKGROUND/OBJECTIVES Obesity is a significant worldwide epidemic that necessitates accessible tools for robust body composition analysis. We investigated whether widely available 3D body surface scanners can provide clinically relevant direct anthropometrics (circumferences, areas and volumes) and body composition estimates (regional fat/lean masses). SUBJECTS/METHODS Thirty-nine healthy adults stratified by age, sex and body mass index (BMI) underwent whole-body 3D scans, dual energy X-ray absorptiometry (DXA), air displacement plethysmography and tape measurements. Linear regressions were performed to assess agreement between 3D measurements and criterion methods. Linear models were derived to predict DXA body composition from 3D scan measurements. Thirty-seven external fitness center users underwent 3D scans and bioelectrical impedance analysis for model validation. RESULTS 3D body scan measurements correlated strongly to criterion methods: waist circumference R2 = 0.95, hip circumference R2 = 0.92, surface area R2 = 0.97 and volume R2 = 0.99. However, systematic differences were observed for each measure due to discrepancies in landmark positioning. Predictive body composition equations showed strong agreement for whole body (fat mass R2 = 0.95, root mean square error (RMSE) = 2.4 kg; fat-free mass R2 = 0.96, RMSE = 2.2 kg) and arms, legs and trunk (R2 = 0.79–0.94, RMSE = 0.5–1.7 kg). Visceral fat prediction showed moderate agreement (R2 = 0.75, RMSE = 0.11 kg). CONCLUSIONS 3D surface scanners offer precise and stable automated measurements of body shape and composition. Software updates may be needed to resolve measurement biases resulting from landmark positioning discrepancies. Further studies are justified to elucidate relationships between body shape, composition and metabolic health across sex, age, BMI and ethnicity groups, as well as in those with metabolic disorders. PMID:27329614

Investigation of Hill's optical turbulence model by means of direct numerical simulation.

PubMed

Muschinski, Andreas; de Bruyn Kops, Stephen M

2015-12-01

For almost four decades, Hill's "Model 4" [J. Fluid Mech. 88, 541 (1978) has played a central role in research and technology of optical turbulence. Based on Batchelor's generalized Obukhov-Corrsin theory of scalar turbulence, Hill's model predicts the dimensionless function h(κl(0), Pr) that appears in Tatarskii's well-known equation for the 3D refractive-index spectrum in the case of homogeneous and isotropic turbulence, Φn(κ)=0.033C2(n)κ(-11/3) h(κl(0), Pr). Here we investigate Hill's model by comparing numerical solutions of Hill's differential equation with scalar spectra estimated from direct numerical simulation (DNS) output data. Our DNS solves the Navier-Stokes equation for the 3D velocity field and the transport equation for the scalar field on a numerical grid containing 4096(3) grid points. Two independent DNS runs are analyzed: one with the Prandtl number Pr=0.7 and a second run with Pr=1.0 . We find very good agreement between h(κl(0), Pr) estimated from the DNS output data and h(κl(0), Pr) predicted by the Hill model. We find that the height of the Hill bump is 1.79 Pr(1/3), implying that there is no bump if Pr<0.17 . Both the DNS and the Hill model predict that the viscous-diffusive "tail" of h(κl(0), Pr) is exponential, not Gaussian.

Exploring tectonomagmatic controls on mid-ocean ridge faulting and morphology with 3-D numerical models

NASA Astrophysics Data System (ADS)

Howell, S. M.; Ito, G.; Behn, M. D.; Olive, J. A. L.; Kaus, B.; Popov, A.; Mittelstaedt, E. L.; Morrow, T. A.

2016-12-01

Previous two-dimensional (2-D) modeling studies of abyssal-hill scale fault generation and evolution at mid-ocean ridges have predicted that M, the ratio of magmatic to total extension, strongly influences the total slip, spacing, and rotation of large faults, as well as the morphology of the ridge axis. Scaling relations derived from these 2-D models broadly explain the globally observed decrease in abyssal hill spacing with increasing ridge spreading rate, as well as the formation of large-offset faults close to the ends of slow-spreading ridge segments. However, these scaling relations do not explain some higher resolution observations of segment-scale variability in fault spacing along the Chile Ridge and the Mid-Atlantic Ridge, where fault spacing shows no obvious correlation with M. This discrepancy between observations and 2-D model predictions illuminates the need for three-dimensional (3-D) numerical models that incorporate the effects of along-axis variations in lithospheric structure and magmatic accretion. To this end, we use the geodynamic modeling software LaMEM to simulate 3-D tectono-magmatic interactions in a visco-elasto-plastic lithosphere under extension. We model a single ridge segment subjected to an along-axis gradient in the rate of magma injection, which is simulated by imposing a mass source in a plane of model finite volumes beneath the ridge axis. Outputs of interest include characteristic fault offset, spacing, and along-axis gradients in seafloor morphology. We also examine the effects of along-axis variations in lithospheric thickness and off-axis thickening rate. The main objectives of this study are to quantify the relative importance of the amount of magmatic extension and the local lithospheric structure at a given along-axis location, versus the importance of along-axis communication of lithospheric stresses on the 3-D fault evolution and morphology of intermediate-spreading-rate ridges.

Use of artificial intelligence as an innovative donor-recipient matching model for liver transplantation: results from a multicenter Spanish study.

PubMed

Briceño, Javier; Cruz-Ramírez, Manuel; Prieto, Martín; Navasa, Miguel; Ortiz de Urbina, Jorge; Orti, Rafael; Gómez-Bravo, Miguel-Ángel; Otero, Alejandra; Varo, Evaristo; Tomé, Santiago; Clemente, Gerardo; Bañares, Rafael; Bárcena, Rafael; Cuervas-Mons, Valentín; Solórzano, Guillermo; Vinaixa, Carmen; Rubín, Angel; Colmenero, Jordi; Valdivieso, Andrés; Ciria, Rubén; Hervás-Martínez, César; de la Mata, Manuel

2014-11-01

There is an increasing discrepancy between the number of potential liver graft recipients and the number of organs available. Organ allocation should follow the concept of benefit of survival, avoiding human-innate subjectivity. The aim of this study is to use artificial-neural-networks (ANNs) for donor-recipient (D-R) matching in liver transplantation (LT) and to compare its accuracy with validated scores (MELD, D-MELD, DRI, P-SOFT, SOFT, and BAR) of graft survival. 64 donor and recipient variables from a set of 1003 LTs from a multicenter study including 11 Spanish centres were included. For each D-R pair, common statistics (simple and multiple regression models) and ANN formulae for two non-complementary probability-models of 3-month graft-survival and -loss were calculated: a positive-survival (NN-CCR) and a negative-loss (NN-MS) model. The NN models were obtained by using the Neural Net Evolutionary Programming (NNEP) algorithm. Additionally, receiver-operating-curves (ROC) were performed to validate ANNs against other scores. Optimal results for NN-CCR and NN-MS models were obtained, with the best performance in predicting the probability of graft-survival (90.79%) and -loss (71.42%) for each D-R pair, significantly improving results from multiple regressions. ROC curves for 3-months graft-survival and -loss predictions were significantly more accurate for ANN than for other scores in both NN-CCR (AUROC-ANN=0.80 vs. -MELD=0.50; -D-MELD=0.54; -P-SOFT=0.54; -SOFT=0.55; -BAR=0.67 and -DRI=0.42) and NN-MS (AUROC-ANN=0.82 vs. -MELD=0.41; -D-MELD=0.47; -P-SOFT=0.43; -SOFT=0.57, -BAR=0.61 and -DRI=0.48). ANNs may be considered a powerful decision-making technology for this dataset, optimizing the principles of justice, efficiency and equity. This may be a useful tool for predicting the 3-month outcome and a potential research area for future D-R matching models. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Collaborative Physical Chemistry Projects Involving Computational Chemistry

NASA Astrophysics Data System (ADS)

Whisnant, David M.; Howe, Jerry J.; Lever, Lisa S.

2000-02-01

The physical chemistry classes from three colleges have collaborated on two computational chemistry projects using Quantum CAChe 3.0 and Gaussian 94W running on Pentium II PCs. Online communication by email and the World Wide Web was an important part of the collaboration. In the first project, students used molecular modeling to predict benzene derivatives that might be possible hair dyes. They used PM3 and ZINDO calculations to predict the electronic spectra of the molecules and tested the predicted spectra by comparing some with experimental measurements. They also did literature searches for real hair dyes and possible health effects. In the final phase of the project they proposed a synthetic pathway for one compound. In the second project the students were asked to predict which isomer of a small carbon cluster (C3, C4, or C5) was responsible for a series of IR lines observed in the spectrum of a carbon star. After preliminary PM3 calculations, they used ab initio calculations at the HF/6-31G(d) and MP2/6-31G(d) level to model the molecules and predict their vibrational frequencies and rotational constants. A comparison of the predictions with the experimental spectra suggested that the linear isomer of the C5 molecule was responsible for the lines.

Evaluation of incremental reactivity and its uncertainty in Southern California.

PubMed

Martien, Philip T; Harley, Robert A; Milford, Jana B; Russell, Armistead G

2003-04-15

The incremental reactivity (IR) and relative incremental reactivity (RIR) of carbon monoxide and 30 individual volatile organic compounds (VOC) were estimated for the South Coast Air Basin using two photochemical air quality models: a 3-D, grid-based model and a vertically resolved trajectory model. Both models include an extended version of the SAPRC99 chemical mechanism. For the 3-D modeling, the decoupled direct method (DDM-3D) was used to assess reactivities. The trajectory model was applied to estimate uncertainties in reactivities due to uncertainties in chemical rate parameters, deposition parameters, and emission rates using Monte Carlo analysis with Latin hypercube sampling. For most VOC, RIRs were found to be consistent in rankings with those produced by Carter using a box model. However, 3-D simulations show that coastal regions, upwind of most of the emissions, have comparatively low IR but higher RIR than predicted by box models for C4-C5 alkenes and carbonyls that initiate the production of HOx radicals. Biogenic VOC emissions were found to have a lower RIR than predicted by box model estimates, because emissions of these VOC were mostly downwind of the areas of primary ozone production. Uncertainties in RIR of individual VOC were found to be dominated by uncertainties in the rate parameters of their primary oxidation reactions. The coefficient of variation (COV) of most RIR values ranged from 20% to 30%, whereas the COV of absolute incremental reactivity ranged from about 30% to 40%. In general, uncertainty and variability both decreased when relative rather than absolute reactivity metrics were used.

Predictions and Verification of an Isotope Marine Boundary Layer Model

NASA Astrophysics Data System (ADS)

Feng, X.; Posmentier, E. S.; Sonder, L. J.; Fan, N.

2017-12-01

A one-dimensional (1D), steady state isotope marine boundary layer (IMBL) model is constructed. The model includes meteorologically important features absent in Craig and Gordon type models, namely height-dependent diffusion/mixing and convergence of subsiding external air. Kinetic isotopic fractionation results from this height-dependent diffusion which starts as pure molecular diffusion at the air-water interface and increases linearly with height due to turbulent mixing. The convergence permits dry, isotopically depleted air subsiding adjacent to the model column to mix into ambient air. In δD-δ18O space, the model results fill a quadrilateral, of which three sides represent 1) vapor in equilibrium with various sea surface temperatures (SSTs) (high d18O boundary of quadrilateral); 2) mixture of vapor in equilibrium with seawater and vapor in the subsiding air (lower boundary depleted in both D and 18O); and 3) vapor that has experienced the maximum possible kinetic fractionation (high δD upper boundary). The results can be plotted in d-excess vs. δ18O space, indicating that these processes all cause variations in d-excess of MBL vapor. In particular, due to relatively high d-excess in the descending air, mixing of this air into the MBL causes an increase in d-excess, even without kinetic isotope fractionation. The model is tested by comparison with seven datasets of marine vapor isotopic ratios, with excellent correspondence; >95% of observational data fall within the quadrilateral area predicted by the model. The distribution of observations also highlights the significant influence of vapor from the nearby converging descending air on isotopic variations in the MBL. At least three factors may explain the <5% of observations that fall slightly outside of the predicted region in both δD-δ18O and d-excess - δ18O space: 1) variations in seawater isotopic ratios, 2) variations in isotopic composition of subsiding air, and 3) influence of sea spray. The model can be used for understanding the effects of boundary layer processes and meteorological conditions on isotopic composition of vapor within, and vapor fluxes through the MBL, and how changes in moisture source regions affect the isotopic composition of precipitation. The model can be applied to modern as well as paleo- climate conditions.

A sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction.

PubMed

Deng, Lei; Fan, Chao; Zeng, Zhiwen

2017-12-28

Direct prediction of the three-dimensional (3D) structures of proteins from one-dimensional (1D) sequences is a challenging problem. Significant structural characteristics such as solvent accessibility and contact number are essential for deriving restrains in modeling protein folding and protein 3D structure. Thus, accurately predicting these features is a critical step for 3D protein structure building. In this study, we present DeepSacon, a computational method that can effectively predict protein solvent accessibility and contact number by using a deep neural network, which is built based on stacked autoencoder and a dropout method. The results demonstrate that our proposed DeepSacon achieves a significant improvement in the prediction quality compared with the state-of-the-art methods. We obtain 0.70 three-state accuracy for solvent accessibility, 0.33 15-state accuracy and 0.74 Pearson Correlation Coefficient (PCC) for the contact number on the 5729 monomeric soluble globular protein dataset. We also evaluate the performance on the CASP11 benchmark dataset, DeepSacon achieves 0.68 three-state accuracy and 0.69 PCC for solvent accessibility and contact number, respectively. We have shown that DeepSacon can reliably predict solvent accessibility and contact number with stacked sparse autoencoder and a dropout approach.

Ribonucleotide reductase as a drug target against drug resistance Mycobacterium leprae: A molecular docking study.

PubMed

Mohanty, Partha Sarathi; Bansal, Avi Kumar; Naaz, Farah; Gupta, Umesh Datta; Dwivedi, Vivek Dhar; Yadava, Umesh

2018-06-01

Leprosy is a chronic infection of skin and nerve caused by Mycobacterium leprae. The treatment is based on standard multi drug therapy consisting of dapsone, rifampicin and clofazamine. The use of rifampicin alone or with dapsone led to the emergence of rifampicin-resistant Mycobacterium leprae strains. The emergence of drug-resistant leprosy put a hurdle in the leprosy eradication programme. The present study aimed to predict the molecular model of ribonucleotide reductase (RNR), the enzyme responsible for biosynthesis of nucleotides, to screen new drugs for treatment of drug-resistant leprosy. The study was conducted by retrieving RNR of M. leprae from GenBank. A molecular 3D model of M. leprae was predicted using homology modelling and validated. A total of 325 characters were included in the analysis. The predicted 3D model of RNR showed that the ϕ and φ angles of 251 (96.9%) residues were positioned in the most favoured regions. It was also conferred that 18 α-helices, 6 β turns, 2 γ turns and 48 helix-helix interactions contributed to the predicted 3D structure. Virtual screening of Food and Drug Administration approved drug molecules recovered 1829 drugs of which three molecules, viz., lincomycin, novobiocin and telithromycin, were taken for the docking study. It was observed that the selected drug molecules had a strong affinity towards the modelled protein RNR. This was evident from the binding energy of the drug molecules towards the modelled protein RNR (-6.10, -6.25 and -7.10). Three FDA-approved drugs, viz., lincomycin, novobiocin and telithromycin, could be taken for further clinical studies to find their efficacy against drug resistant leprosy. Copyright © 2018 Elsevier B.V. All rights reserved.

SimRNA: a coarse-grained method for RNA folding simulations and 3D structure prediction.

PubMed

Boniecki, Michal J; Lach, Grzegorz; Dawson, Wayne K; Tomala, Konrad; Lukasz, Pawel; Soltysinski, Tomasz; Rother, Kristian M; Bujnicki, Janusz M

2016-04-20

RNA molecules play fundamental roles in cellular processes. Their function and interactions with other biomolecules are dependent on the ability to form complex three-dimensional (3D) structures. However, experimental determination of RNA 3D structures is laborious and challenging, and therefore, the majority of known RNAs remain structurally uncharacterized. Here, we present SimRNA: a new method for computational RNA 3D structure prediction, which uses a coarse-grained representation, relies on the Monte Carlo method for sampling the conformational space, and employs a statistical potential to approximate the energy and identify conformations that correspond to biologically relevant structures. SimRNA can fold RNA molecules using only sequence information, and, on established test sequences, it recapitulates secondary structure with high accuracy, including correct prediction of pseudoknots. For modeling of complex 3D structures, it can use additional restraints, derived from experimental or computational analyses, including information about secondary structure and/or long-range contacts. SimRNA also can be used to analyze conformational landscapes and identify potential alternative structures. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Advanced fast 3D DSA model development and calibration for design technology co-optimization

NASA Astrophysics Data System (ADS)

Lai, Kafai; Meliorisz, Balint; Muelders, Thomas; Welling, Ulrich; Stock, Hans-Jürgen; Marokkey, Sajan; Demmerle, Wolfgang; Liu, Chi-Chun; Chi, Cheng; Guo, Jing

2017-04-01

Direct Optimization (DO) of a 3D DSA model is a more optimal approach to a DTCO study in terms of accuracy and speed compared to a Cahn Hilliard Equation solver. DO's shorter run time (10X to 100X faster) and linear scaling makes it scalable to the area required for a DTCO study. However, the lack of temporal data output, as opposed to prior art, requires a new calibration method. The new method involves a specific set of calibration patterns. The calibration pattern's design is extremely important when temporal data is absent to obtain robust model parameters. A model calibrated to a Hybrid DSA system with a set of device-relevant constructs indicates the effectiveness of using nontemporal data. Preliminary model prediction using programmed defects on chemo-epitaxy shows encouraging results and agree qualitatively well with theoretical predictions from a strong segregation theory.

Comparison of Approaches to the Prediction of Surface Wave Phase Velocity

NASA Astrophysics Data System (ADS)

Godfrey, K. E.; Dalton, C. A.; Hjorleifsdottir, V.; Ekstrom, G.

2017-12-01

Global seismic models provide crucial information about the state, composition, and dynamics of the Earth's interior, and in the shallow mantle these models are primarily constrained by observations of surface waves. Models developed by different groups have been constructed using different data sets and different techniques. While these models exhibit good agreement on the long-wavelength features, there is less consistency in the patterns and amplitude of smaller-scale heterogeneity. Here we investigate how approximations in the theoretical treatment of wave propagation and excitation influence the interpretation of measured phase delays and the tomographic images that result from inverting them. Synthetic seismograms were generated using SPECFEM3D_GLOBE for 42 earthquakes, 134 receiver locations, and two 3-D models of elastic Earth structure: S362ANI (Kustowski et al., 2008) and a rougher model constructed by adding realistic small-scale structure to S362ANI. Fundamental-mode Rayleigh and Love wave phase delays in the period range 35-250 seconds were measured using the approach of Ekström et al. (1997), for which PREM is the assumed reference Earth model. These measurements were compared to phase-delay predictions generated for the great-circle ray approximation, exact ray theory, and finite-frequency theory. We find that for both 3-D earth models exact ray theory provides the best fit to the measurements at short periods. At longer periods finite frequency theory provides the best fit. For the smooth earth model, the differences in fit for the various predictions are less significant at long periods than at shorter periods. The differences at long periods become more significant with increasing model roughness. In all cases, the agreement between predictions and measurements is best for paths located away from nodes in the source radiation pattern. The ability of the measured phase delays to recover the input Earth models is assessed through tests that explore the influence of parameterization, regularization, and crustal corrections.

Finite Element Analysis of Stresses Developed in the Blood Sac of a Left Ventricular Assist Device

PubMed Central

Haut Donahue, T. L.; Dehlin, W.; Gillespie, J.; Weiss, W.J.; Rosenberg, G.

2009-01-01

The goal of this research is to develop a 3D finite element (FE) model of a left ventricular assist device (LVAD) to predict stresses in the blood sac. The hyperelastic stress-strain curves for the segmented poly(ether polyurethane urea) blood sac were determined in both tension and compression using a servo-hydraulic testing system at various strain rates. Over the range of strain rates studied, the sac was not strain rate sensitive, however the material response was different for tension versus compression. The experimental tension and compression properties were used in a FE model that consisted of the pusher plate, blood sac and pump case. A quasi-static analysis was used to allow for nonlinearities due to contact and material deformation. The 3D FE model showed that blood sac stresses are not adversely affected by the location of the inlet and outlet ports of the device and that over the systolic ejection phase of the simulation the prediction of blood sac stresses from the full 3D model and an axisymmetric model are the same. Minimizing stresses in the blood sac will increase the longevity of the blood sac in vivo. PMID:19131267

The prediction of speech intelligibility in classrooms using computer models

NASA Astrophysics Data System (ADS)

Dance, Stephen; Dentoni, Roger

2005-04-01

Two classrooms were measured and modeled using the industry standard CATT model and the Web model CISM. Sound levels, reverberation times and speech intelligibility were predicted in these rooms using data for 7 octave bands. It was found that overall sound levels could be predicted to within 2 dB by both models. However, overall reverberation time was found to be accurately predicted by CATT 14% prediction error, but not by CISM, 41% prediction error. This compared to a 30% prediction error using classical theory. As for STI: CATT predicted within 11%, CISM to within 3% and Sabine to within 28% of the measured value. It should be noted that CISM took approximately 15 seconds to calculate, while CATT took 15 minutes. CISM is freely available on-line at www.whyverne.co.uk/acoustics/Pages/cism/cism.html

A computational modeling approach for the characterization of mechanical properties of 3D alginate tissue scaffolds.

PubMed

Nair, K; Yan, K C; Sun, W

2008-01-01

Scaffold guided tissue engineering is an innovative approach wherein cells are seeded onto biocompatible and biodegradable materials to form 3-dimensional (3D) constructs that, when implanted in the body facilitate the regeneration of tissue. Tissue scaffolds act as artificial extracellular matrix providing the environment conducive for tissue growth. Characterization of scaffold properties is necessary to understand better the underlying processes involved in controlling cell behavior and formation of functional tissue. We report a computational modeling approach to characterize mechanical properties of 3D gellike biomaterial, specifically, 3D alginate scaffold encapsulated with cells. Alginate inherent nonlinearity and variations arising from minute changes in its concentration and viscosity make experimental evaluation of its mechanical properties a challenging and time consuming task. We developed an in silico model to determine the stress-strain relationship of alginate based scaffolds from experimental data. In particular, we compared the Ogden hyperelastic model to other hyperelastic material models and determined that this model was the most suitable to characterize the nonlinear behavior of alginate. We further propose a mathematical model that represents the alginate material constants in Ogden model as a function of concentrations and viscosity. This study demonstrates the model capability to predict mechanical properties of 3D alginate scaffolds.

CoMFA and CoMSIA 3D-QSAR studies on S(6)-(4-nitrobenzyl)mercaptopurine riboside (NBMPR) analogs as inhibitors of human equilibrative nucleoside transporter 1 (hENT1).

PubMed

Gupte, Amol; Buolamwini, John K

2009-01-15

3D-QSAR (CoMFA and CoMSIA) studies were performed on human equlibrative nucleoside transporter (hENT1) inhibitors displaying K(i) values ranging from 10,000 to 0.7nM. Both CoMFA and CoMSIA analysis gave reliable models with q2 values >0.50 and r2 values >0.92. The models have been validated for their stability and robustness using group validation and bootstrapping techniques and for their predictive abilities using an external test set of nine compounds. The high predictive r2 values of the test set (0.72 for CoMFA model and 0.74 for CoMSIA model) reveals that the models can prove to be a useful tool for activity prediction of newly designed nucleoside transporter inhibitors. The CoMFA and CoMSIA contour maps identify features important for exhibiting good binding affinities at the transporter, and can thus serve as a useful guide for the design of potential equilibrative nucleoside transporter inhibitors.

B2B Models for DoD Acquisition

DTIC Science & Technology

2007-07-30

Internet, extranets, intranets, or private networks • In 2003 it represented about 11% of total B2B trade estimated at $13.5 trillion • Predicted to... B2B Models for DoD Acquisition 30 July 2007 by Magdi N. Kamel, Associate Professor Graduate School of Operational & Information Sciences...number. 1. REPORT DATE 30 JUL 2007 2. REPORT TYPE 3. DATES COVERED 00-00-2007 to 00-00-2007 4. TITLE AND SUBTITLE B2B Models for DoD

Predicting the Ability of Marine Mammal Populations to Compensate for Behavioral Disturbances

DTIC Science & Technology

2015-09-30

approaches, including simple theoretical models as well as statistical analysis of data rich conditions. Building on models developed for PCoD [2,3], we...conditions is population trajectory most likely to be affected (the central aim of PCoD ). For the revised model presented here, we include a population...averaged condition individuals (here used as a proxy for individual health as defined in PCoD ), and E is the quality of the environment in which the

Limitations to the use of two-dimensional thermal modeling of a nuclear waste repository

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

Davis, B.W.

1979-01-04

Thermal modeling of a nuclear waste repository is basic to most waste management predictive models. It is important that the modeling techniques accurately determine the time-dependent temperature distribution of the waste emplacement media. Recent modeling studies show that the time-dependent temperature distribution can be accurately modeled in the far-field using a 2-dimensional (2-D) planar numerical model; however, the near-field cannot be modeled accurately enough by either 2-D axisymmetric or 2-D planar numerical models for repositories in salt. The accuracy limits of 2-D modeling were defined by comparing results from 3-dimensional (3-D) TRUMP modeling with results from both 2-D axisymmetric andmore » 2-D planar. Both TRUMP and ADINAT were employed as modeling tools. Two-dimensional results from the finite element code, ADINAT were compared with 2-D results from the finite difference code, TRUMP; they showed almost perfect correspondence in the far-field. This result adds substantially to confidence in future use of ADINAT and its companion stress code ADINA for thermal stress analysis. ADINAT was found to be somewhat sensitive to time step and mesh aspect ratio. 13 figures, 4 tables.« less

Effects of the approximations of light propagation on quantitative photoacoustic tomography using two-dimensional photon diffusion equation and linearization

NASA Astrophysics Data System (ADS)

Okawa, Shinpei; Hirasawa, Takeshi; Kushibiki, Toshihiro; Ishihara, Miya

2017-12-01

Quantitative photoacoustic tomography (QPAT) employing a light propagation model will play an important role in medical diagnoses by quantifying the concentration of hemoglobin or a contrast agent. However, QPAT by the light propagation model with the three-dimensional (3D) radiative transfer equation (RTE) requires a huge computational load in the iterative forward calculations involved in the updating process to reconstruct the absorption coefficient. The approximations of the light propagation improve the efficiency of the image reconstruction for the QPAT. In this study, we compared the 3D/two-dimensional (2D) photon diffusion equation (PDE) approximating 3D RTE with the Monte Carlo simulation based on 3D RTE. Then, the errors in a 2D PDE-based linearized image reconstruction caused by the approximations were quantitatively demonstrated and discussed in the numerical simulations. It was clearly observed that the approximations affected the reconstructed absorption coefficient. The 2D PDE-based linearized algorithm succeeded in the image reconstruction of the region with a large absorption coefficient in the 3D phantom. The value reconstructed in the phantom experiment agreed with that in the numerical simulation, so that it was validated that the numerical simulation of the image reconstruction predicted the relationship between the true absorption coefficient of the target in the 3D medium and the reconstructed value with the 2D PDE-based linearized algorithm. Moreover, the the true absorption coefficient in 3D medium was estimated from the 2D reconstructed image on the basis of the prediction by the numerical simulation. The estimation was successful in the phantom experiment, although some limitations were revealed.

[Application and prospect of digital technology in the field of orthodontics].

PubMed

Zhou, Y H

2016-06-01

The three-dimensional(3D)digital technology has brought a revolutionary change in diagnostic planning and treatment strategy of orthodontics. Acquisition of 3D image data of the hard and soft tissues of the patients, diagnostic analysis and treatment prediction, and ultimately the individualized orthodontic appliance, will become the development trend and workflow of the 3D orthodontics. With the development of 3D digital technology, the traditional plaster model has been gradually replacing by 3D digital models. Meanwhile, 3D facial soft tissue scan and cone-beam CT scan have been gradually applied to clinical orthodontics, making it possible to get 3D virtual anatomical structure for patients. With the help of digital technology, the diagnostic process is much easier for orthodontist. However how to command the whole digital workflow and put it into practice in the daily work is still a long way to go. The purpose of this article is to enlighten the orthodontists interested in digital technology and discuss the future of digital orthodontics in China.

Matrix approach to uncertainty assessment and reduction for modeling terrestrial carbon cycle

NASA Astrophysics Data System (ADS)

Luo, Y.; Xia, J.; Ahlström, A.; Zhou, S.; Huang, Y.; Shi, Z.; Wang, Y.; Du, Z.; Lu, X.

2017-12-01

Terrestrial ecosystems absorb approximately 30% of the anthropogenic carbon dioxide emissions. This estimate has been deduced indirectly: combining analyses of atmospheric carbon dioxide concentrations with ocean observations to infer the net terrestrial carbon flux. In contrast, when knowledge about the terrestrial carbon cycle is integrated into different terrestrial carbon models they make widely different predictions. To improve the terrestrial carbon models, we have recently developed a matrix approach to uncertainty assessment and reduction. Specifically, the terrestrial carbon cycle has been commonly represented by a series of carbon balance equations to track carbon influxes into and effluxes out of individual pools in earth system models. This representation matches our understanding of carbon cycle processes well and can be reorganized into one matrix equation without changing any modeled carbon cycle processes and mechanisms. We have developed matrix equations of several global land C cycle models, including CLM3.5, 4.0 and 4.5, CABLE, LPJ-GUESS, and ORCHIDEE. Indeed, the matrix equation is generic and can be applied to other land carbon models. This matrix approach offers a suite of new diagnostic tools, such as the 3-dimensional (3-D) parameter space, traceability analysis, and variance decomposition, for uncertainty analysis. For example, predictions of carbon dynamics with complex land models can be placed in a 3-D parameter space (carbon input, residence time, and storage potential) as a common metric to measure how much model predictions are different. The latter can be traced to its source components by decomposing model predictions to a hierarchy of traceable components. Then, variance decomposition can help attribute the spread in predictions among multiple models to precisely identify sources of uncertainty. The highly uncertain components can be constrained by data as the matrix equation makes data assimilation computationally possible. We will illustrate various applications of this matrix approach to uncertainty assessment and reduction for terrestrial carbon cycle models.

The FALL3D Ash Cloud Dispersion Model and its Implementation at the Buenos Aires VAAC

NASA Astrophysics Data System (ADS)

Folch, A.; Suaya, M.; Costa, A.; Viramonte, J.

2009-12-01

Airborne volcanic ash and aerosols threat aerial navigation and affect the quality of air at medium to large distances downwind from the volcano. Airplane re-routing and airport disruption carry important socioeconomic consequences at regional and national levels. Models to forecast volcanic ash clouds constitute, together with satellite imagery, a valuable predictive tool during a crisis. FALL3D is an Eulerian ash cloud dispersion model based on the advection-diffusion-sedimentation equation. The model runs at any scale, from regional to global. The dispersion model is off-line coupled with global (e.g. GFS, NMM-b) and mesoscalar (e.g. NMM-b, WRF, ETA) meteorological models and with re-analysis datasets. FALL3D has been recently installed at the Buenos Aires VAAC, depending on the Argentinean National Meteorological Service (SMN). In this presentation we summarize the characteristics of the model and its implementation at the VAAC, including the different domains, the meteorological forecast inputs (ETA or GFS) and the scenarios assumed for some critical volcanoes (Chaitén, Llaima, Lascar, etc.). Pre-defined scenarios are necessary to give an early first order prediction when data is poor or unavailable. This is particularly critical in Central Andes, were most active volcanoes are located in remote areas with poor or inexistent monitoring.

Four-Phase Dendritic Model for the Prediction of Macrosegregation, Shrinkage Cavity, and Porosity in a 55-Ton Ingot

NASA Astrophysics Data System (ADS)

Ge, Honghao; Ren, Fengli; Li, Jun; Han, Xiujun; Xia, Mingxu; Li, Jianguo

2017-03-01

A four-phase dendritic model was developed to predict the macrosegregation, shrinkage cavity, and porosity during solidification. In this four-phase dendritic model, some important factors, including dendritic structure for equiaxed crystals, melt convection, crystals sedimentation, nucleation, growth, and shrinkage of solidified phases, were taken into consideration. Furthermore, in this four-phase dendritic model, a modified shrinkage criterion was established to predict shrinkage porosity (microporosity) of a 55-ton industrial Fe-3.3 wt pct C ingot. The predicted macrosegregation pattern and shrinkage cavity shape are in a good agreement with experimental results. The shrinkage cavity has a significant effect on the formation of positive segregation in hot top region, which generally forms during the last stage of ingot casting. The dendritic equiaxed grains also play an important role on the formation of A-segregation. A three-dimensional laminar structure of A-segregation in industrial ingot was, for the first time, predicted by using a 3D case simulation.

Testing the reliability of ice-cream cone model

NASA Astrophysics Data System (ADS)

Pan, Zonghao; Shen, Chenglong; Wang, Chuanbing; Liu, Kai; Xue, Xianghui; Wang, Yuming; Wang, Shui

2015-04-01

Coronal Mass Ejections (CME)'s properties are important to not only the physical scene itself but space-weather prediction. Several models (such as cone model, GCS model, and so on) have been raised to get rid of the projection effects within the properties observed by spacecraft. According to SOHO/ LASCO observations, we obtain the 'real' 3D parameters of all the FFHCMEs (front-side full halo Coronal Mass Ejections) within the 24th solar cycle till July 2012, by the ice-cream cone model. Considering that the method to obtain 3D parameters from the CME observations by multi-satellite and multi-angle has higher accuracy, we use the GCS model to obtain the real propagation parameters of these CMEs in 3D space and compare the results with which by ice-cream cone model. Then we could discuss the reliability of the ice-cream cone model.

WE-H-BRA-02: Radiobiological Modeling of Tumor Control Probability (TCP) and Radiation-Induced Pneumonitis (RP) for Lung Cancer Patients Treated with Monte Carlo-Based Lung SBRT

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

Pokhrel, D; Sood, S; Shen, X

2016-06-15

Purpose: To present radiobiological modeling of TCP using tumor size-adjusted BED(s-BED)and PTV(D99) to lung SBRT patients treated with X-ray Voxel Monte Carlo(XVMC) algorithm, apply parameterized Lyman-NTCP model to predict grade-2 RP and subsequently, compare with clinical outcomes/observations. Methods: Dosimetric parameters and clinical follow-up for XVMC-based lung-SBRT patients were retrospectively evaluated. Patients were treated at Novalis-TX with hybrid(2 non-coplanar partial-arcs plus 3–6 static-beams)plan using HD-MLC/6MV-SRS-beam.For TCP,s-BED modelling was utilized: TCP=EXP[sBED-TCD50]/k/(1.0+EXP[sBED-TCD50]/k), where k=31Gy corresponding to TCD50=0Gy and s-BED was defined as BED10 minus 10 times the tumor diameter(in centimeters)by Ohri et al.(IJROBP,2012). For 2-yr local-control, we used more-realistic MC-computed PTVD99 as amore » predictive parameter, s-BED(D99).Due to relatively shorter median follow-up interval(12-months),Kaplan-Meier curves were generated to estimate 2-yr observed local-control and compared to predicted-rate by TCP modeling. For NTCP, we employed parameterized Lyman-NTCP model utilizing normal-lung DVH and α/β=3Gy fitted to predict grade-2 RP after lung-SBRT. Results: Total 108 patients (137 tumors) treated for 35–70Gy in 3–5 fractions, either primary-lung(n=74)or metastatic-lung(n=53)tumors were included.F or the given prescription dose with MC-computed MUs, 2-yr local-control rates with s-BED(D99) was 87±8%. Kaplan-Meier generated observed local-control rate at 2-yr was 87.5%,suggesting that PTV(D99) could be a potential predictor (p-value=0.38). Observed vs predicted TCP for primary-lung tumors and metastatic tumors were 97% vs 88±7% and 94% vs 86±9%.NTCP model predicted well for symptomatic-RP with predicted vs observed (3±5% vs 2%). Radiographic and clinically significant RP was observed in 13% and 2% of patients. Higher rates of radiographic change were observed in patients who received >50Gy compared to ≤50Gy(24% vs 10%). Conclusion: Utilizing MC-computed PTVD99, our TCP results were well correlated with clinical outcome. The predicted grade-2 RP rate was comparable to clinical observations. Clinical application of these radiobiological models may potentially allow for target dose escalation and/or lung-toxicity reduction. Further validation of these radiobiological models with longer follow up interval for large cohorts of lung-SBRT patients is anticipated.« less

Automated identification of RNA 3D modules with discriminative power in RNA structural alignments.

PubMed

Theis, Corinna; Höner Zu Siederdissen, Christian; Hofacker, Ivo L; Gorodkin, Jan

2013-12-01

Recent progress in predicting RNA structure is moving towards filling the 'gap' in 2D RNA structure prediction where, for example, predicted internal loops often form non-canonical base pairs. This is increasingly recognized with the steady increase of known RNA 3D modules. There is a general interest in matching structural modules known from one molecule to other molecules for which the 3D structure is not known yet. We have created a pipeline, metaRNAmodules, which completely automates extracting putative modules from the FR3D database and mapping of such modules to Rfam alignments to obtain comparative evidence. Subsequently, the modules, initially represented by a graph, are turned into models for the RMDetect program, which allows to test their discriminative power using real and randomized Rfam alignments. An initial extraction of 22 495 3D modules in all PDB files results in 977 internal loop and 17 hairpin modules with clear discriminatory power. Many of these modules describe only minor variants of each other. Indeed, mapping of the modules onto Rfam families results in 35 unique locations in 11 different families. The metaRNAmodules pipeline source for the internal loop modules is available at http://rth.dk/resources/mrm.

D-dimer levels over time and the risk of recurrent venous thromboembolism: an update of the Vienna prediction model.

PubMed

Eichinger, Sabine; Heinze, Georg; Kyrle, Paul A

2014-01-02

Patients with unprovoked venous thromboembolism (VTE) can be stratified according to their recurrence risk based on their sex, the VTE location, and D-dimer measured 3 weeks after anticoagulation by the Vienna Prediction Model. We aimed to expand the model to also assess the recurrence risk from later points on. Five hundred and fifty-three patients with a first VTE were followed for a median of 68 months. We excluded patients with VTE provoked by a transient risk factor or female hormone intake, with a natural inhibitor deficiency, the lupus anticoagulant, or cancer. The study end point was recurrent VTE, which occurred in 150 patients. D-dimer levels did not substantially increase over time. Subdistribution hazard ratios (95% confidence intervals) dynamically changed from 2.43 (1.57 to 3.77) at 3 weeks to 2.27 (1.48 to 3.48), 1.98 (1.30 to 3.02) , and 1.73 (1.11 to 2.69) at 3, 9, and 15 months in men versus women, from 1.84 (1.00 to 3.43) to 1.68 (0.91 to 3.10), 1.49 (0.79 to 2.81) , and 1.44 (0.76 to 2.72) in patients with proximal deep vein thrombosis or pulmonary embolism compared with calf vein thrombosis, and from 1.30 (1.07 to 1.58) to 1.27 (1.06 to 1.51), 1.20 (1.02 to 1.41), and 1.13 (0.95 to 1.36) per doubling D-dimer. Using a dynamic landmark competing risks regression approach, we generated nomograms and a web-based calculator to calculate risk scores and recurrence rates from multiple times after anticoagulation. Risk of recurrent VTE after discontinuation of anticoagulation can be predicted from multiple random time points by integrating the patient's sex, location of first VTE, and serial D-dimer measurements.

Comparison between measured turbine stage performance and the predicted performance using quasi-3D flow and boundary layer analyses

NASA Technical Reports Server (NTRS)

Boyle, R. J.; Haas, J. E.; Katsanis, T.

1984-01-01

A method for calculating turbine stage performance is described. The usefulness of the method is demonstrated by comparing measured and predicted efficiencies for nine different stages. Comparisons are made over a range of turbine pressure ratios and rotor speeds. A quasi-3D flow analysis is used to account for complex passage geometries. Boundary layer analyses are done to account for losses due to friction. Empirical loss models are used to account for incidence, secondary flow, disc windage, and clearance losses.

Microfluidics‐based 3D cell culture models: Utility in novel drug discovery and delivery research

PubMed Central

Gupta, Nilesh; Liu, Jeffrey R.; Patel, Brijeshkumar; Solomon, Deepak E.; Vaidya, Bhuvaneshwar

2016-01-01

Abstract The implementation of microfluidic devices within life sciences has furthered the possibilities of both academic and industrial applications such as rapid genome sequencing, predictive drug studies, and single cell manipulation. In contrast to the preferred two‐dimensional cell‐based screening, three‐dimensional (3D) systems have more in vivo relevance as well as ability to perform as a predictive tool for the success or failure of a drug screening campaign. 3D cell culture has shown an adaptive response to the recent advancements in microfluidic technologies which has allowed better control over spheroid sizes and subsequent drug screening studies. In this review, we highlight the most significant developments in the field of microfluidic 3D culture over the past half‐decade with a special focus on their benefits and challenges down the lane. With the newer technologies emerging, implementation of microfluidic 3D culture systems into the drug discovery pipeline is right around the bend. PMID:29313007

Thermoelastic damping in microrings with circular cross-section

NASA Astrophysics Data System (ADS)

Li, Pu; Fang, Yuming; Zhang, Jianrun

2016-01-01

Predicting thermoelastic damping (TED) is crucial in the design of high Q micro-resonators. Microrings are often critical components in many micro-resonators. Some analytical models for TED in microrings have already been developed in the past. However, the previous works are limited to the microrings with rectangular cross-section. The temperature field in the rectangular cross-section is one-dimensional. This paper deals with TED in the microrings with circular cross-section. The temperature field in the circular cross-section is two-dimensional. This paper first presents a 2-D analytical model for TED in the microrings with circular cross-section. Only the two-dimensional heat conduction in the circular cross-section is considered. The heat conduction along the circumferential direction of the microring is neglected in the 2-D model. Then the 2-D model has been extended to cover the circumferential heat conduction, and a 3-D analytical model for TED has been developed. The analytical results from the present 2-D and 3-D models show good agreement with the numerical results of FEM model. The limitations of the present 2-D analytical model are assessed.

Low-cost structured-light based 3D capture system design

NASA Astrophysics Data System (ADS)

Dong, Jing; Bengtson, Kurt R.; Robinson, Barrett F.; Allebach, Jan P.

2014-03-01

Most of the 3D capture products currently in the market are high-end and pricey. They are not targeted for consumers, but rather for research, medical, or industrial usage. Very few aim to provide a solution for home and small business applications. Our goal is to fill in this gap by only using low-cost components to build a 3D capture system that can satisfy the needs of this market segment. In this paper, we present a low-cost 3D capture system based on the structured-light method. The system is built around the HP TopShot LaserJet Pro M275. For our capture device, we use the 8.0 Mpixel camera that is part of the M275. We augment this hardware with two 3M MPro 150 VGA (640 × 480) pocket projectors. We also describe an analytical approach to predicting the achievable resolution of the reconstructed 3D object based on differentials and small signal theory, and an experimental procedure for validating that the system under test meets the specifications for reconstructed object resolution that are predicted by our analytical model. By comparing our experimental measurements from the camera-projector system with the simulation results based on the model for this system, we conclude that our prototype system has been correctly configured and calibrated. We also conclude that with the analytical models, we have an effective means for specifying system parameters to achieve a given target resolution for the reconstructed object.

Atom-based 3D-QSAR, induced fit docking, and molecular dynamics simulations study of thieno[2,3-b]pyridines negative allosteric modulators of mGluR5.

PubMed

Vijaya Prabhu, Sitrarasu; Singh, Sanjeev Kumar

2018-05-28

Atom-based three dimensional-quantitative structure-activity relationship (3D-QSAR) model was developed on the basis of 5-point pharmacophore hypothesis (AARRR) with two hydrogen bond acceptors (A) and three aromatic rings for the derivatives of thieno[2,3-b]pyridine, which modulates the activity to inhibit the mGluR5 receptor. Generation of a highly predictive 3D-QSAR model was performed using the alignment of predicted pharmacophore hypothesis for the training set (R 2  = 0.84, SD = 0.26, F = 45.8, N = 29) and test set (Q 2  = 0.74, RMSE = 0.235, Pearson-R = 0.94, N = 9). The best pharmacophore hypothesis AARRR was selected, and developed three dimensional-quantitative structure activity relationship (3D-QSAR) model also supported the outcome of this study by means of favorable and unfavorable electron withdrawing group and hydrophobic regions of most active compound 42d and least active compound 18b. Following, induced fit docking and binding free energy calculations reveals the reliable binding orientation of the compounds. Finally, molecular dynamics simulations for 100 ns were performed to depict the protein-ligand stability. We anticipate that the resulted outcome could be supportive to discover potent negative allosteric modulators for metabotropic glutamate receptor 5 (mGluR5).

3-D model-based vehicle tracking.

PubMed

Lou, Jianguang; Tan, Tieniu; Hu, Weiming; Yang, Hao; Maybank, Steven J

2005-10-01

This paper aims at tracking vehicles from monocular intensity image sequences and presents an efficient and robust approach to three-dimensional (3-D) model-based vehicle tracking. Under the weak perspective assumption and the ground-plane constraint, the movements of model projection in the two-dimensional image plane can be decomposed into two motions: translation and rotation. They are the results of the corresponding movements of 3-D translation on the ground plane (GP) and rotation around the normal of the GP, which can be determined separately. A new metric based on point-to-line segment distance is proposed to evaluate the similarity between an image region and an instantiation of a 3-D vehicle model under a given pose. Based on this, we provide an efficient pose refinement method to refine the vehicle's pose parameters. An improved EKF is also proposed to track and to predict vehicle motion with a precise kinematics model. Experimental results with both indoor and outdoor data show that the algorithm obtains desirable performance even under severe occlusion and clutter.

Development of facial aging simulation system combined with three-dimensional shape prediction from facial photographs

NASA Astrophysics Data System (ADS)

Nagata, Takeshi; Matsuzaki, Kazutoshi; Taniguchi, Kei; Ogawa, Yoshinori; Imaizumi, Kazuhiko

2017-03-01

3D Facial aging changes in more than 10 years of identical persons are being measured at National Research Institute of Police Science. We performed machine learning using such measured data as teacher data and have developed the system which convert input 2D face image into 3D face model and simulate aging. Here, we report about processing and accuracy of our system.

Compound activity prediction using models of binding pockets or ligand properties in 3D

PubMed Central

Kufareva, Irina; Chen, Yu-Chen; Ilatovskiy, Andrey V.; Abagyan, Ruben

2014-01-01

Transient interactions of endogenous and exogenous small molecules with flexible binding sites in proteins or macromolecular assemblies play a critical role in all biological processes. Current advances in high-resolution protein structure determination, database development, and docking methodology make it possible to design three-dimensional models for prediction of such interactions with increasing accuracy and specificity. Using the data collected in the Pocketome encyclopedia, we here provide an overview of two types of the three-dimensional ligand activity models, pocket-based and ligand property-based, for two important classes of proteins, nuclear and G-protein coupled receptors. For half the targets, the pocket models discriminate actives from property matched decoys with acceptable accuracy (the area under ROC curve, AUC, exceeding 84%) and for about one fifth of the targets with high accuracy (AUC > 95%). The 3D ligand property field models performed better than 95% in half of the cases. The high performance models can already become a basis of activity predictions for new chemicals. Family-wide benchmarking of the models highlights strengths of both approaches and helps identify their inherent bottlenecks and challenges. PMID:23116466

A novel 3D human glioblastoma cell culture system for modeling drug and radiation responses

PubMed Central

Stevenson, Katrina; Gilmour, Lesley; Hamilton, Graham; Chalmers, Anthony J

2017-01-01

Abstract Background. Glioblastoma (GBM) is the most common primary brain tumor, with dismal prognosis. The failure of drug–radiation combinations with promising preclinical data to translate into effective clinical treatments may relate to the use of simplified 2-dimensional in vitro GBM cultures. Methods. We developed a customized 3D GBM culture system based on a polystyrene scaffold (Alvetex) that recapitulates key histological features of GBM and compared it with conventional 2D cultures with respect to their response to radiation and to molecular targeted agents for which clinical data are available. Results. In 3 patient-derived GBM lines, no difference in radiation sensitivity was observed between 2D and 3D cultures, as measured by clonogenic survival. Three different molecular targeted agents, for which robust clinical data are available were evaluated in 2D and 3D conditions: (i) temozolomide, which improves overall survival and is standard of care for GBM, exhibited statistically significant effects on clonogenic survival in both patient-derived cell lines when evaluated in the 3D model compared with only one cell line in 2D cells; (ii) bevacizumab, which has been shown to increase progression-free survival when added to standard chemoradiation in phase III clinical trials, exhibited marked radiosensitizing activity in our 3D model but had no effect on 2D cells; and (iii) erlotinib, which had no efficacy in clinical trials, displayed no activity in our 3D GBM model, but radiosensitized 2D cells. Conclusions. Our 3D model reliably predicted clinical efficacy, strongly supporting its clinical relevance and potential value in preclinical evaluation of drug–radiation combinations for GBM. PMID:27576873

Visual fatigue modeling for stereoscopic video shot based on camera motion

NASA Astrophysics Data System (ADS)

Shi, Guozhong; Sang, Xinzhu; Yu, Xunbo; Liu, Yangdong; Liu, Jing

2014-11-01

As three-dimensional television (3-DTV) and 3-D movie become popular, the discomfort of visual feeling limits further applications of 3D display technology. The cause of visual discomfort from stereoscopic video conflicts between accommodation and convergence, excessive binocular parallax, fast motion of objects and so on. Here, a novel method for evaluating visual fatigue is demonstrated. Influence factors including spatial structure, motion scale and comfortable zone are analyzed. According to the human visual system (HVS), people only need to converge their eyes to the specific objects for static cameras and background. Relative motion should be considered for different camera conditions determining different factor coefficients and weights. Compared with the traditional visual fatigue prediction model, a novel visual fatigue predicting model is presented. Visual fatigue degree is predicted using multiple linear regression method combining with the subjective evaluation. Consequently, each factor can reflect the characteristics of the scene, and the total visual fatigue score can be indicated according to the proposed algorithm. Compared with conventional algorithms which ignored the status of the camera, our approach exhibits reliable performance in terms of correlation with subjective test results.

Spatio-temporal interpolation of soil moisture in 3D+T using automated sensor network data

NASA Astrophysics Data System (ADS)

Gasch, C.; Hengl, T.; Magney, T. S.; Brown, D. J.; Gräler, B.

2014-12-01

Soil sensor networks provide frequent in situ measurements of dynamic soil properties at fixed locations, producing data in 2- or 3-dimensions and through time (2D+T and 3D+T). Spatio-temporal interpolation of 3D+T point data produces continuous estimates that can then be used for prediction at unsampled times and locations, as input for process models, and can simply aid in visualization of properties through space and time. Regression-kriging with 3D and 2D+T data has successfully been implemented, but currently the field of geostatistics lacks an analytical framework for modeling 3D+T data. Our objective is to develop robust 3D+T models for mapping dynamic soil data that has been collected with high spatial and temporal resolution. For this analysis, we use data collected from a sensor network installed on the R.J. Cook Agronomy Farm (CAF), a 37-ha Long-Term Agro-Ecosystem Research (LTAR) site in Pullman, WA. For five years, the sensors have collected hourly measurements of soil volumetric water content at 42 locations and five depths. The CAF dataset also includes a digital elevation model and derivatives, a soil unit description map, crop rotations, electromagnetic induction surveys, daily meteorological data, and seasonal satellite imagery. The soil-water sensor data, combined with the spatial and temporal covariates, provide an ideal dataset for developing 3D+T models. The presentation will include preliminary results and address main implementation strategies.

Mathematical modeling of sample stacking methods in microfluidic systems

NASA Astrophysics Data System (ADS)

Horek, Jon

Gradient focusing methods are a general class of experimental techniques used to simultaneously separate and increase the cross-sectionally averaged concentration of charged particle mixtures. In comparison, Field Amplified Sample Stacking (FASS) techniques first concentrate the collection of molecules before separating them. Together, we denote gradient focusing and FASS methods "sample stacking" and study the dynamics of a specific method, Temperature Gradient Focusing (TGF), in which an axial temperature gradient is applied along a channel filled with weak buffer. Gradients in electroosmotic fluid flow and electrophoretic species velocity create the simultaneous separating and concentrating mechanism mentioned above. In this thesis, we begin with the observation that very little has been done to model the dynamics of gradient focusing, and proceed to solve the fundamental equations of fluid mechanics and scalar transport, assuming the existence of slow axial variations and the Taylor-Aris dispersion coefficient. In doing so, asymptotic methods reduce the equations from 3D to 1D, and we arrive at a simple 1D model which can be used to predict the transient evolution of the cross-sectionally averaged analyte concentration. In the second half of this thesis, we run several numerical focusing experiments with a 3D finite volume code. Comparison of the 1D theory and 3D simulations illustrates not only that the asymptotic theory converges as a certain parameter tends to zero, but also that fairly large axial slip velocity gradients lead to quite small errors in predicted steady variance. Additionally, we observe that the axial asymmetry of the electrophoretic velocity model leads to asymmetric peak shapes, a violation of the symmetric Gaussians predicted by the 1D theory. We conclude with some observations on the effect of Peclet number and gradient strength on the performance of focusing experiments, and describe a method for experimental optimization. Such knowledge is useful for design of lab-on-a-chip devices.

SU-F-T-143: Implementation of a Correction-Based Output Model for a Compact Passively Scattered Proton Therapy System

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

Ferguson, S; Ahmad, S; Chen, Y

2016-06-15

Purpose: To commission and investigate the accuracy of an output (cGy/MU) prediction model for a compact passively scattered proton therapy system. Methods: A previously published output prediction model (Sahoo et al, Med Phys, 35, 5088–5097, 2008) was commissioned for our Mevion S250 proton therapy system. This model is a correction-based model that multiplies correction factors (d/MUwnc=ROFxSOBPF xRSFxSOBPOCFxOCRxFSFxISF). These factors accounted for changes in output due to options (12 large, 5 deep, and 7 small), modulation width M, range R, off-center, off-axis, field-size, and off-isocenter. In this study, the model was modified to ROFxSOBPFxRSFxOCRxFSFxISF-OCFxGACF by merging SOBPOCF and ISF for simplicitymore » and introducing a gantry angle correction factor (GACF). To commission the model, outputs over 1,000 data points were taken at the time of the system commissioning. The output was predicted by interpolation (1D for SOBPF, FSF, and GACF; 2D for RSF and OCR) with inverse-square calculation (ISF-OCR). The outputs of 273 combinations of R and M covering total 24 options were measured to test the model. To minimize fluence perturbation, scattered dose from range compensator and patient was not considered. The percent differences between the predicted (P) and measured (M) outputs were calculated to test the prediction accuracy ([P-M]/Mx100%). Results: GACF was required because of up to 3.5% output variation dependence on the gantry angle. A 2D interpolation was required for OCR because the dose distribution was not radially symmetric especially for the deep options. The average percent differences were −0.03±0.98% (mean±SD) and the differences of all the measurements fell within ±3%. Conclusion: It is concluded that the model can be clinically used for the compact passively scattered proton therapy system. However, great care should be taken when the field-size is less than 5×5 cm{sup 2} where a direct output measurement is required due to substantial output change by irregular block shape.« less

NATRIURETIC PEPTIDE SYSTEM GENE VARIANTS ARE ASSOCIATED WITH VENTRICULAR DYSFUNCTION AFTER CORONARY ARTERY BYPASS GRAFTING

PubMed Central

Fox, Amanda A.; Collard, Charles D.; Shernan, Stanton K.; Seidman, Christine E.; Seidman, Jonathan G.; Liu, Kuang-Yu; Muehlschlegel, Jochen D.; Perry, Tjorvi E.; Aranki, Sary F.; Lange, Christoph; Herman, Daniel S.; Meitinger, Thomas; Lichtner, Peter; Body, Simon C.

2009-01-01

Background Ventricular dysfunction (VnD) after primary coronary artery bypass grafting is associated with increased hospital stay and mortality. Natriuretic peptides have compensatory vasodilatory, natriuretic and paracrine influences on myocardial failure and ischemia. We hypothesized that natriuretic peptide system gene variants independently predict risk of VnD after primary coronary artery bypass grafting. Methods 1164 patients undergoing primary coronary artery bypass grafting with cardiopulmonary bypass at two institutions were prospectively enrolled. After prospectively defined exclusions, 697 Caucasian patients (76 with VnD) were analyzed. VnD was defined as need for ≥ 2 new inotropes and/or new mechanical ventricular support after coronary artery bypass grafting. 139 haplotype-tagging SNPs within 7 genes (NPPA; NPPB; NPPC; NPR1; NPR2; NPR3; CORIN) were genotyped. SNPs univariately associated with VnD were entered into logistic regression models adjusting for clinical covariates predictive of VnD. To control for multiple comparisons, permutation analyses were conducted for all SNP associations. Results After adjusting for clinical covariates and multiple comparisons within each gene, seven NPPA/NPPB SNPs (rs632793, rs6668352, rs549596, rs198388, rs198389, rs6676300, rs1009592) were associated with decreased risk of postoperative VnD (additive model; odds ratios 0.44–0.55; P = 0.010–0.036), and four NPR3 SNPs (rs700923, rs16890196, rs765199, rs700926) were associated with increased risk of postoperative VnD (recessive model; odds ratios 3.89–4.28; P = 0.007–0.034). Conclusions Genetic variation within the NPPA/NPPB and NPR3 genes is associated with risk of VnD after primary coronary artery bypass grafting. Knowledge of such genotypic predictors may result in better understanding of the molecular mechanisms underlying postoperative VnD. PMID:19326473

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

Smith, Kandler A; Santhanagopalan, Shriram; Yang, Chuanbo

Computer models are helping to accelerate the design and validation of next generation batteries and provide valuable insights not possible through experimental testing alone. Validated 3-D physics-based models exist for predicting electrochemical performance, thermal and mechanical response of cells and packs under normal and abuse scenarios. The talk describes present efforts to make the models better suited for engineering design, including improving their computation speed, developing faster processes for model parameter identification including under aging, and predicting the performance of a proposed electrode material recipe a priori using microstructure models.

Experimental design based 3-D QSAR analysis of steroid-protein interactions: Application to human CBG complexes

NASA Astrophysics Data System (ADS)

Norinder, Ulf

1990-12-01

An experimental design based 3-D QSAR analysis using a combination of principal component and PLS analysis is presented and applied to human corticosteroid-binding globulin complexes. The predictive capability of the created model is good. The technique can also be used as guidance when selecting new compounds to be investigated.

A TEST OF THERMODYNAMIC EQUILIBRIUM MODELS AND 3-D AIR QUALITY MODELS FOR PREDICTIONS OF AEROSOL NO3-

EPA Science Inventory

The inorganic species of sulfate, nitrate and ammonium constitute a major fraction of atmospheric aerosols. The behavior of nitrate is one of the most intriguing aspects of inorganic atmospheric aerosols because particulate nitrate concentrations depend not only on the amount of ...

Modeling the anaerobic digestion of cane-molasses vinasse: extension of the Anaerobic Digestion Model No. 1 (ADM1) with sulfate reduction for a very high strength and sulfate rich wastewater.

PubMed

Barrera, Ernesto L; Spanjers, Henri; Solon, Kimberly; Amerlinck, Youri; Nopens, Ingmar; Dewulf, Jo

2015-03-15

This research presents the modeling of the anaerobic digestion of cane-molasses vinasse, hereby extending the Anaerobic Digestion Model No. 1 with sulfate reduction for a very high strength and sulfate rich wastewater. Based on a sensitivity analysis, four parameters of the original ADM1 and all sulfate reduction parameters were calibrated. Although some deviations were observed between model predictions and experimental values, it was shown that sulfates, total aqueous sulfide, free sulfides, methane, carbon dioxide and sulfide in the gas phase, gas flow, propionic and acetic acids, chemical oxygen demand (COD), and pH were accurately predicted during model validation. The model showed high (±10%) to medium (10%-30%) accuracy predictions with a mean absolute relative error ranging from 1% to 26%, and was able to predict failure of methanogenesis and sulfidogenesis when the sulfate loading rate increased. Therefore, the kinetic parameters and the model structure proposed in this work can be considered as valid for the sulfate reduction process in the anaerobic digestion of cane-molasses vinasse when sulfate and organic loading rates range from 0.36 to 1.57 kg [Formula: see text]  m(-3) d(-1) and from 7.66 to 12 kg COD m(-3) d(-1), respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.

Numerical Analysis of AHSS Fracture in a Stretch-bending Test

NASA Astrophysics Data System (ADS)

Luo, Meng; Chen, Xiaoming; Shi, Ming F.; Shih, Hua-Chu

2010-06-01

Advanced High Strength Steels (AHSS) are increasingly used in the automotive industry due to their superior strength and substantial weight reduction advantage. However, their limited ductility gives rise to numerous manufacturing issues. One of them is the so-called `shear fracture' often observed on tight radii during stamping processes. Since traditional approaches, such as the Forming Limit Diagram (FLD), are unable to predict this type of fracture, efforts have been made to develop failure criteria that can predict shear fractures. In this paper, a recently developed Modified Mohr-Coulomb (MMC) ductile fracture criterion[1] is adopted to analyze the failure behavior of a Dual Phase (DP) steel sheet during stretch bending operations. The plasticity and ductile fracture of the present sheet are fully characterized by the Hill'48 orthotropic model and the MMC fracture model respectively. Finite Element models with three different element types (3D, shell and plane strain) were built for a Stretch Forming Simulator (SFS) test and numerical simulations with four different R/t ratios (die radius normalized by sheet thickness) were performed. It has been shown that the 3D and shell element models can accurately predict the failure location/mode, the upper die load-displacement responses as well as the wall stress and wrap angle at the onset of fracture for all R/t ratios. Furthermore, a series of parametric studies were conducted on the 3D element model, and the effects of tension level (clamping distance) and tooling friction on the failure modes/locations were investigated.

Testing the reliability of ice-cream cone model

NASA Astrophysics Data System (ADS)

Pan, Z.; Shen, C.; Wang, Y.; Liu, K.

2013-12-01

Coronal Mass Ejections (CME)'s properties are important to not only the physical scene itself but spaceweather prediction. Several models(such as cone model, GCS model, and so on) have been raised to get rid of the projection effects within the properties observated by spacecraft. According to SOHO/ LASCO observations, we obtain the 'real' 3D parameters of 33 FFHCMEs (front-side full halo Coronal Mass Ejections) within the 24th solar cycle by the ice-cream cone model. Considering that the method to obtain 3D parameters from the CME observations by multi-satellite and multi-angle has higher accuracy, we use the GCS model to obtain the real propagation parameters of these CMEs in 3D space and compare the results with which by ice-cream cone model. It was demonstrated that the correlation coefficient for the speeds by using these both methods is 0.97.

Delta: a new web-based 3D genome visualization and analysis platform.

PubMed

Tang, Bixia; Li, Feifei; Li, Jing; Zhao, Wenming; Zhang, Zhihua

2018-04-15

Delta is an integrative visualization and analysis platform to facilitate visually annotating and exploring the 3D physical architecture of genomes. Delta takes Hi-C or ChIA-PET contact matrix as input and predicts the topologically associating domains and chromatin loops in the genome. It then generates a physical 3D model which represents the plausible consensus 3D structure of the genome. Delta features a highly interactive visualization tool which enhances the integration of genome topology/physical structure with extensive genome annotation by juxtaposing the 3D model with diverse genomic assay outputs. Finally, by visually comparing the 3D model of the β-globin gene locus and its annotation, we speculated a plausible transitory interaction pattern in the locus. Experimental evidence was found to support this speculation by literature survey. This served as an example of intuitive hypothesis testing with the help of Delta. Delta is freely accessible from http://delta.big.ac.cn, and the source code is available at https://github.com/zhangzhwlab/delta. zhangzhihua@big.ac.cn. Supplementary data are available at Bioinformatics online.

Aerodynamic characteristics of the 40- by 80/80- by 120-foot wind tunnel at NASA Ames Research Center

NASA Technical Reports Server (NTRS)

Corsiglia, V. R.; Olson, L. E.; Falarski, M. D.

1984-01-01

The design and testing of vane sets and air-exchange inlet for the 40 x 80/80 x 120-ft wind tunnel at NASA Ames are reported. Boundary-layer analysis and 2D and 3D inviscid panel codes are employed in computer models of the system, and a 1/10-scale 2D facility and a 1/50-scale 3D model of the entire wind tunnel are used in experimental testing of the vane sets. The results are presented in graphs, photographs, drawings, and diagrams are discussed. Generally good agreement is found between the predicted and measured performance.

The Prospect of using Three-Dimensional Earth Models To Improve Nuclear Explosion Monitoring and Ground Motion Hazard Assessment

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

Zucca, J J; Walter, W R; Rodgers, A J

2008-11-19

The last ten years have brought rapid growth in the development and use of three-dimensional (3D) seismic models of Earth structure at crustal, regional and global scales. In order to explore the potential for 3D seismic models to contribute to important societal applications, Lawrence Livermore National Laboratory (LLNL) hosted a 'Workshop on Multi-Resolution 3D Earth Models to Predict Key Observables in Seismic Monitoring and Related Fields' on June 6 and 7, 2007 in Berkeley, California. The workshop brought together academic, government and industry leaders in the research programs developing 3D seismic models and methods for the nuclear explosion monitoring andmore » seismic ground motion hazard communities. The workshop was designed to assess the current state of work in 3D seismology and to discuss a path forward for determining if and how 3D Earth models and techniques can be used to achieve measurable increases in our capabilities for monitoring underground nuclear explosions and characterizing seismic ground motion hazards. This paper highlights some of the presentations, issues, and discussions at the workshop and proposes two specific paths by which to begin quantifying the potential contribution of progressively refined 3D seismic models in critical applied arenas. Seismic monitoring agencies are tasked with detection, location, and characterization of seismic activity in near real time. In the case of nuclear explosion monitoring or seismic hazard, decisions to further investigate a suspect event or to launch disaster relief efforts may rely heavily on real-time analysis and results. Because these are weighty decisions, monitoring agencies are regularly called upon to meticulously document and justify every aspect of their monitoring system. In order to meet this level of scrutiny and maintain operational robustness requirements, only mature technologies are considered for operational monitoring systems, and operational technology necessarily lags contemporary research. Current monitoring practice is to use relatively simple Earth models that generally afford analytical prediction of seismic observables (see Examples of Current Monitoring Practice below). Empirical relationships or corrections to predictions are often used to account for unmodeled phenomena, such as the generation of S-waves from explosions or the effect of 3-dimensional Earth structure on wave propagation. This approach produces fast and accurate predictions in areas where empirical observations are available. However, accuracy may diminish away from empirical data. Further, much of the physics is wrapped into an empirical relationship or correction, which limits the ability to fully understand the physical processes underlying the seismic observation. Every generation of seismology researchers works toward quantitative results, with leaders who are active at or near the forefront of what has been computationally possible. While recognizing that only a 3-dimensional model can capture the full physics of seismic wave generation and propagation in the Earth, computational seismology has, until recently, been limited to simplifying model parameterizations (e.g. 1D Earth models) that lead to efficient algorithms. What is different today is the fact that the largest and fastest machines are at last capable of evaluating the effects of generalized 3D Earth structure, at levels of detail that improve significantly over past efforts, with potentially wide application. Advances in numerical methods to compute travel times and complete seismograms for 3D models are enabling new ways to interpret available data. This includes algorithms such as the Fast Marching Method (Rawlison and Sambridge, 2004) for travel time calculations and full waveform methods such as the spectral element method (SEM; Komatitsch et al., 2002, Tromp et al., 2005), higher order Galerkin methods (Kaser and Dumbser, 2006; Dumbser and Kaser, 2006) and advances in more traditional Cartesian finite difference methods (e.g. Pitarka, 1999; Nilsson et al., 2007). The ability to compute seismic observables using a 3D model is only half of the challenge; models must be developed that accurately represent true Earth structure. Indeed, advances in seismic imaging have followed improvements in 3D computing capability (e.g. Tromp et al., 2005; Rawlinson and Urvoy, 2006). Advances in seismic imaging methods have been fueled in part by theoretical developments and the introduction of novel approaches for combining different seismological observables, both of which can increase the sensitivity of observations to Earth structure. Examples of such developments are finite-frequency sensitivity kernels for body-wave tomography (e.g. Marquering et al., 1998; Montelli et al., 2004) and joint inversion of receiver functions and surface wave group velocities (e.g. Julia et al., 2000).« less

Structured Light-Based 3D Reconstruction System for Plants

PubMed Central

Nguyen, Thuy Tuong; Slaughter, David C.; Max, Nelson; Maloof, Julin N.; Sinha, Neelima

2015-01-01

Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants.This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the proposed structured light system to enhance textures on object surfaces) and software algorithms (including the proposed 3D point cloud registration and plant feature measurement). This paper demonstrates the ability to produce 3D models of whole plants created from multiple pairs of stereo images taken at different viewing angles, without the need to destructively cut away any parts of a plant. The ability to accurately predict phenotyping features, such as the number of leaves, plant height, leaf size and internode distances, is also demonstrated. Experimental results show that, for plants having a range of leaf sizes and a distance between leaves appropriate for the hardware design, the algorithms successfully predict phenotyping features in the target crops, with a recall of 0.97 and a precision of 0.89 for leaf detection and less than a 13-mm error for plant size, leaf size and internode distance. PMID:26230701

The accuracy of a 2D and 3D dendritic tip scaling parameter in predicting the columnar to equiaxed transition (CET)

NASA Astrophysics Data System (ADS)

Seredyński, M.; Rebow, M.; Banaszek, J.

2016-09-01

The dendrite tip kinetics model accuracy relies on the reliability of the stability constant used, which is usually experimentally determined for 3D situations and applied to 2D models. The paper reports authors' attempts to cure the situation by deriving 2D dendritic tip scaling parameter for aluminium-based alloy: Al-4wt%Cu. The obtained parameter is then incorporated into the KGT dendritic growth model in order to compare it with the original 3D KGT counterpart and to derive two-dimensional and three-dimensional versions of the modified Hunt's analytical model for the columnar-to-equiaxed transition (CET). The conclusions drawn from the above analysis are further confirmed through numerical calculations of the two cases of Al-4wt%Cu metallic alloy solidification using the front tracking technique. Results, including the porous zone-under-cooled liquid front position, the calculated solutal under-cooling and a new predictor of the relative tendency to form an equiaxed zone, are shown, compared and discussed two numerical cases. The necessity to calculate sufficiently precise values of the tip scaling parameter in 2D and 3D is stressed.

A GRID OF THREE-DIMENSIONAL STELLAR ATMOSPHERE MODELS OF SOLAR METALLICITY. I. GENERAL PROPERTIES, GRANULATION, AND ATMOSPHERIC EXPANSION

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

Trampedach, Regner; Asplund, Martin; Collet, Remo

2013-05-20

Present grids of stellar atmosphere models are the workhorses in interpreting stellar observations and determining their fundamental parameters. These models rely on greatly simplified models of convection, however, lending less predictive power to such models of late-type stars. We present a grid of improved and more reliable stellar atmosphere models of late-type stars, based on deep, three-dimensional (3D), convective, stellar atmosphere simulations. This grid is to be used in general for interpreting observations and improving stellar and asteroseismic modeling. We solve the Navier Stokes equations in 3D and concurrent with the radiative transfer equation, for a range of atmospheric parameters,more » covering most of stellar evolution with convection at the surface. We emphasize the use of the best available atomic physics for quantitative predictions and comparisons with observations. We present granulation size, convective expansion of the acoustic cavity, and asymptotic adiabat as functions of atmospheric parameters.« less

Chinese time trade-off values for EQ-5D health states.

PubMed

Liu, Gordon G; Wu, Hongyan; Li, Minghui; Gao, Chen; Luo, Nan

2014-07-01

To generate a Chinese general population-based three-level EuroQol five-dimensios (EQ-5D-3L) social value set using the time trade-off method. The study sample was drawn from five cities in China: Beijing, Guangzhou, Shenyang, Chengdu, and Nanjing, using a quota sampling method. Utility values for a subset of 97 health states defined by the EQ-5D-3L descriptive system were directly elicited from the study sample using a modified Measurement and Valuation of Health protocol, with each respondent valuing 13 of the health states. The utility values for all 243 EQ-5D-3L health states were estimated on the basis of econometric models at both individual and aggregate levels. Various linear regression models using different model specifications were examined to determine the best model using predefined model selection criteria. The N3 model based on ordinary least square regression at the aggregate level yielded the best model fit, with a mean absolute error of 0.020, 7 and 0 states for which prediction errors were greater than 0.05 and 0.10, respectively, in absolute magnitude. This model passed tests for model misspecification (F = 2.7; P = 0.0509, Ramsey Regression Equation Specification Error Test), heteroskedasticity (χ(2) = 0.97; P = 0.3254, Breusch-Pagan/Cook-Weisberg test), and normality of the residuals (χ(2) = 1.285; P = 0.5259, Jarque-Bera test). The range of the predicted values (-0.149 to 0.887) was similar to those estimated in other countries. The study successfully developed Chinese utility values for EQ-5D-3L health states using the time trade-off method. It is the first attempt ever to develop a standardized instrument for quantifying quality-adjusted life-years in China. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Advanced 3D Geological Modelling Using Multi Geophysical Data in the Yamagawa Geothermal Field, Japan

NASA Astrophysics Data System (ADS)

Mochinaga, H.; Aoki, N.; Mouri, T.

2017-12-01

We propose a robust workflow of 3D geological modelling based on integrated analysis while honouring seismic, gravity, and wellbore data for exploration and development at flash steam geothermal power plants. We design the workflow using temperature logs at less than 10 well locations for practical use at an early stage of geothermal exploration and development. In the workflow, geostatistical technique, multi-attribute analysis, and artificial neural network are employed for the integration of multi geophysical data. The geological modelling is verified by using a 3D seismic data which was acquired in the Yamagawa Demonstration Area (approximately 36 km2), located at the city of Ibusuki in Kagoshima, Japan in 2015. Temperature-depth profiles are typically characterized by heat transfer of conduction, outflow, and up-flow which have low frequency trends. On the other hand, feed and injection zones with high permeability would cause high frequency perturbation on temperature-depth profiles. Each trend is supposed to be caused by different geological properties and subsurface structures. In this study, we estimate high frequency (> 2 cycles/km) and low frequency (< 1 cycle/km) models separately by means of different types of attribute volumes. These attributes are mathematically generated from P-impedance and density volumes derived from seismic inversion, an ant-tracking seismic volume, and a geostatistical temperature model prior to application of artificial neural network on the geothermal modelling. As a result, the band-limited stepwise approach predicts a more precise geothermal model than that of full-band temperature profiles at a time. Besides, lithofacies interpretation confirms reliability of the predicted geothermal model. The integrated interpretation is significantly consistent with geological reports from previous studies. Isotherm geobodies illustrate specific features of geothermal reservoir and cap rock, shallow aquifer, and its hydrothermal circulation in 3D visualization. The advanced workflow of 3D geological modelling is suitable for optimization of well locations for production and reinjection in geothermal fields.

Galactic evolution of oxygen. OH lines in 3D hydrodynamical model atmospheres

NASA Astrophysics Data System (ADS)

González Hernández, J. I.; Bonifacio, P.; Ludwig, H.-G.; Caffau, E.; Behara, N. T.; Freytag, B.

2010-09-01

Context. Oxygen is the third most common element in the Universe. The measurement of oxygen lines in metal-poor unevolved stars, in particular near-UV OH lines, can provide invaluable information about the properties of the Early Galaxy. Aims: Near-UV OH lines constitute an important tool to derive oxygen abundances in metal-poor dwarf stars. Therefore, it is important to correctly model the line formation of OH lines, especially in metal-poor stars, where 3D hydrodynamical models commonly predict cooler temperatures than plane-parallel hydrostatic models in the upper photosphere. Methods: We have made use of a grid of 52 3D hydrodynamical model atmospheres for dwarf stars computed with the code CO5BOLD, extracted from the more extended CIFIST grid. The 52 models cover the effective temperature range 5000-6500 K, the surface gravity range 3.5-4.5 and the metallicity range -3 < [Fe/H] < 0. Results: We determine 3D-LTE abundance corrections in all 52 3D models for several OH lines and ion{Fe}{i} lines of different excitation potentials. These 3D-LTE corrections are generally negative and reach values of roughly -1 dex (for the OH 3167 with excitation potential of approximately 1 eV) for the higher temperatures and surface gravities. Conclusions: We apply these 3D-LTE corrections to the individual O abundances derived from OH lines of a sample the metal-poor dwarf stars reported in Israelian et al. (1998, ApJ, 507, 805), Israelian et al. (2001, ApJ, 551, 833) and Boesgaard et al. (1999, AJ, 117, 492) by interpolating the stellar parameters of the dwarfs in the grid of 3D-LTE corrections. The new 3D-LTE [O/Fe] ratio still keeps a similar trend as the 1D-LTE, i.e., increasing towards lower [Fe/H] values. We applied 1D-NLTE corrections to 3D ion{Fe}{i} abundances and still see an increasing [O/Fe] ratio towards lower metallicites. However, the Galactic [O/Fe] ratio must be revisited once 3D-NLTE corrections become available for OH and Fe lines for a grid of 3D hydrodynamical model atmospheres.

Development of a transformation model to derive general population-based utility: Mapping the pruritus-visual analog scale (VAS) to the EQ-5D utility.

PubMed

Park, Sun-Young; Park, Eun-Ja; Suh, Hae Sun; Ha, Dongmun; Lee, Eui-Kyung

2017-08-01

Although nonpreference-based disease-specific measures are widely used in clinical studies, they cannot generate utilities for economic evaluation. A solution to this problem is to estimate utilities from disease-specific instruments using the mapping function. This study aimed to develop a transformation model for mapping the pruritus-visual analog scale (VAS) to the EuroQol 5-Dimension 3-Level (EQ-5D-3L) utility index in pruritus. A cross-sectional survey was conducted with a sample (n = 268) drawn from the general population of South Korea. Data were randomly divided into 2 groups, one for estimating and the other for validating mapping models. To select the best model, we developed and compared 3 separate models using demographic information and the pruritus-VAS as independent variables. The predictive performance was assessed using the mean absolute deviation and root mean square error in a separate dataset. Among the 3 models, model 2 using age, age squared, sex, and the pruritus-VAS as independent variables had the best performance based on the goodness of fit and model simplicity, with a log likelihood of 187.13. The 3 models had similar precision errors based on mean absolute deviation and root mean square error in the validation dataset. No statistically significant difference was observed between the mean observed and predicted values in all models. In conclusion, model 2 was chosen as the preferred mapping model. Outcomes measured as the pruritus-VAS can be transformed into the EQ-5D-3L utility index using this mapping model, which makes an economic evaluation possible when only pruritus-VAS data are available. © 2017 John Wiley & Sons, Ltd.

Using exposure prediction tools to link exposure and ...

EPA Pesticide Factsheets

A few different exposure prediction tools were evaluated for use in the new in vitro-based safety assessment paradigm using di-2-ethylhexyl phthalate (DEHP) and dibutyl phthalate (DnBP) as case compounds. Daily intake of each phthalate was estimated using both high-throughput (HT) prediction models such as the HT Stochastic Human Exposure and Dose Simulation model (SHEDS-HT) and the ExpoCast heuristic model and non-HT approaches based on chemical specific exposure estimations in the environment in conjunction with human exposure factors. Reverse dosimetry was performed using a published physiologically based pharmacokinetic (PBPK) model for phthalates and their metabolites to provide a comparison point. Daily intakes of DEHP and DnBP were estimated based on the urinary concentrations of their respective monoesters, mono-2-ethylhexyl phthalate (MEHP) and monobutyl phthalate (MnBP), reported in NHANES (2011–2012). The PBPK-reverse dosimetry estimated daily intakes at the 50th and 95th percentiles were 0.68 and 9.58 μg/kg/d and 0.089 and 0.68 μg/kg/d for DEHP and DnBP, respectively. For DEHP, the estimated median from PBPK-reverse dosimetry was about 3.6-fold higher than the ExpoCast estimate (0.68 and 0.18 μg/kg/d, respectively). For DnBP, the estimated median was similar to that predicted by ExpoCast (0.089 and 0.094 μg/kg/d, respectively). The SHEDS-HT prediction of DnBP intake from consumer product pathways alone was higher at 0.67 μg/kg/d. The PBPK-reve

Accumulation of 2,3,7,8-tetrachlorodibenzo-p-dioxin by rainbow trout (Onchorhynchus mykiss) at environmentally relevant dietary concentrations

USGS Publications Warehouse

Jones, Paul D.; Kannan, Kurunthachalam; Newsted, John L.; Tillitt, Donald E.; Williams, Lisa L.; Giesy, John P.

2001-01-01

Rainbow trout were fed a diet containing 1.8, 18, or 90 pg/g 3H-2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) for up to 320 d. Concentrations of TCDD were determined in muscle, liver, and ovaries at 100, 150, 200, and 250 d. Concentrations of TCDD reached an apparent steady-state concentration in liver after 100 d of exposure, whereas concentrations in other tissues continued to increase until 150 d of exposure. The greatest portion of the total mass of TCDD was present in the muscle tissue with lesser proportions in other organs. As the ovaries developed before spawning, an increase occurred in the total mass of TCDD present in this tissue. The assimilation rate of TCDD during the initial 100 d of the exposure was determined to be between 10 and 30%. This is somewhat less than estimates derived based on both uptake and elimination constants determined during shorter exposures. Biomagnification factors (BMFs) were estimated for all tissues and exposure concentrations, and at all exposure periods. Lipid-normalized BMFs for muscle ranged from 0.38 to 1.51, which is consistent with the value of 1.0 predicted from fugacity theory. Uptake and depuration rate constants were determined and used to predict individual organ TCDD concentrations. Comparison with observed values indicated that the model could be used to predict tissue concentrations from the known concentrations of TCDD in food. This model will allow more refined risk assessments by predicting TCDD concentrations in sensitive tissues such as developing eggs.

Prediction of individual response to anticancer therapy: historical and future perspectives.

PubMed

Unger, Florian T; Witte, Irene; David, Kerstin A

2015-02-01

Since the introduction of chemotherapy for cancer treatment in the early 20th century considerable efforts have been made to maximize drug efficiency and at the same time minimize side effects. As there is a great interpatient variability in response to chemotherapy, the development of predictive biomarkers is an ambitious aim for the rapidly growing research area of personalized molecular medicine. The individual prediction of response will improve treatment and thus increase survival and life quality of patients. In the past, cell cultures were used as in vitro models to predict in vivo response to chemotherapy. Several in vitro chemosensitivity assays served as tools to measure miscellaneous endpoints such as DNA damage, apoptosis and cytotoxicity or growth inhibition. Twenty years ago, the development of high-throughput technologies, e.g. cDNA microarrays enabled a more detailed analysis of drug responses. Thousands of genes were screened and expression levels were correlated to drug responses. In addition, mutation analysis became more and more important for the prediction of therapeutic success. Today, as research enters the area of -omics technologies, identification of signaling pathways is a tool to understand molecular mechanism underlying drug resistance. Combining new tissue models, e.g. 3D organoid cultures with modern technologies for biomarker discovery will offer new opportunities to identify new drug targets and in parallel predict individual responses to anticancer therapy. In this review, we present different currently used chemosensitivity assays including 2D and 3D cell culture models and several -omics approaches for the discovery of predictive biomarkers. Furthermore, we discuss the potential of these assays and biomarkers to predict the clinical outcome of individual patients and future perspectives.

The Impact of 3D Data Quality on Improving GNSS Performance Using City Models Initial Simulations

NASA Astrophysics Data System (ADS)

Ellul, C.; Adjrad, M.; Groves, P.

2016-10-01

There is an increasing demand for highly accurate positioning information in urban areas, to support applications such as people and vehicle tracking, real-time air quality detection and navigation. However systems such as GPS typically perform poorly in dense urban areas. A number of authors have made use of 3D city models to enhance accuracy, obtaining good results, but to date the influence of the quality of the 3D city model on these results has not been tested. This paper addresses the following question: how does the quality, and in particular the variation in height, level of generalization and completeness and currency of a 3D dataset, impact the results obtained for the preliminary calculations in a process known as Shadow Matching, which takes into account not only where satellite signals are visible on the street but also where they are predicted to be absent. We describe initial simulations to address this issue, examining the variation in elevation angle - i.e. the angle above which the satellite is visible, for three 3D city models in a test area in London, and note that even within one dataset using different available height values could cause a difference in elevation angle of up to 29°. Missing or extra buildings result in an elevation variation of around 85°. Variations such as these can significantly influence the predicted satellite visibility which will then not correspond to that experienced on the ground, reducing the accuracy of the resulting Shadow Matching process.

Prediction of Very High Reynolds Number Compressible Skin Friction

NASA Technical Reports Server (NTRS)

Carlson, John R.

1998-01-01

Flat plate skin friction calculations over a range of Mach numbers from 0.4 to 3.5 at Reynolds numbers from 16 million to 492 million using a Navier Stokes method with advanced turbulence modeling are compared with incompressible skin friction coefficient correlations. The semi-empirical correlation theories of van Driest; Cope; Winkler and Cha; and Sommer and Short T' are used to transform the predicted skin friction coefficients of solutions using two algebraic Reynolds stress turbulence models in the Navier-Stokes method PAB3D. In general, the predicted skin friction coefficients scaled well with each reference temperature theory though, overall the theory by Sommer and Short appeared to best collapse the predicted coefficients. At the lower Reynolds number 3 to 30 million, both the Girimaji and Shih, Zhu and Lumley turbulence models predicted skin-friction coefficients within 2% of the semi-empirical correlation skin friction coefficients. At the higher Reynolds numbers of 100 to 500 million, the turbulence models by Shih, Zhu and Lumley and Girimaji predicted coefficients that were 6% less and 10% greater, respectively, than the semi-empirical coefficients.

Comparative 1D and 3D numerical investigation of open-channel junction flows and energy losses

NASA Astrophysics Data System (ADS)

Luo, Hao; Fytanidis, Dimitrios K.; Schmidt, Arthur R.; García, Marcelo H.

2018-07-01

The complexity of open channel confluences stems from flow mixing, secondary circulation, post-confluence flow separation, contraction and backwater effects. These effects in turn result in a large number of parameters required to adequately quantify the junction induced hydraulic resistance and describe mean flow pattern and turbulent flow structures due to flow merging. The recent development in computing power advances the application of 3D Computational Fluid Dynamics (CFD) codes to visualize and understand the Confluence Hydrodynamic Zone (CHZ). Nevertheless, 1D approaches remain the mainstay in large drainage network or waterway system modeling considering computational efficiency and data availability. This paper presents (i) a modified 1D nonlinear dynamic model; (ii) a fully 3D non-hydrostatic, Reynolds-averaged Navier-Stokes Equations (RANS)-based, Computational Fluid Dynamics (CFD) model; (iii) an analysis of changing confluence hydrodynamics and 3D turbulent flow structure under various controls; (iv) a comparison of flow features (i.e. upstream water depths, energy losses and post-confluence contraction) predicted by 1D and 3D models; and (v) parameterization of 3D flow characteristics in 1D modeling through the computation of correction coefficients associated with contraction, energy and momentum. The present comprehensive 3D numerical investigation highlights the driving mechanisms for junction induced energy losses. Moreover, the comparative 1D and 3D study quantifies the deviation of 1D approximations and associated underlying assumptions from the 'true' resultant flow field. The study may also shed light on improving the accuracy of the 1D large network modeling through the parameterization of the complex 3D feature of the flow field and correction of interior boundary conditions at junctions of larger angles and/or with substantial lateral inflows. Moreover, the enclosed numerical investigations may enhance the understanding of the primary mechanisms contributing to hydraulic structure induced turbulent flow behavior and increased hydraulic resistance.

A novel soft tissue prediction methodology for orthognathic surgery based on probabilistic finite element modelling

PubMed Central

Borghi, Alessandro; Ruggiero, Federica; Badiali, Giovanni; Bianchi, Alberto; Marchetti, Claudio; Rodriguez-Florez, Naiara; Breakey, Richard W. F.; Jeelani, Owase; Dunaway, David J.; Schievano, Silvia

2018-01-01

Repositioning of the maxilla in orthognathic surgery is carried out for functional and aesthetic purposes. Pre-surgical planning tools can predict 3D facial appearance by computing the response of the soft tissue to the changes to the underlying skeleton. The clinical use of commercial prediction software remains controversial, likely due to the deterministic nature of these computational predictions. A novel probabilistic finite element model (FEM) for the prediction of postoperative facial soft tissues is proposed in this paper. A probabilistic FEM was developed and validated on a cohort of eight patients who underwent maxillary repositioning and had pre- and postoperative cone beam computed tomography (CBCT) scans taken. Firstly, a variables correlation assessed various modelling parameters. Secondly, a design of experiments (DOE) provided a range of potential outcomes based on uniformly distributed input parameters, followed by an optimisation. Lastly, the second DOE iteration provided optimised predictions with a probability range. A range of 3D predictions was obtained using the probabilistic FEM and validated using reconstructed soft tissue surfaces from the postoperative CBCT data. The predictions in the nose and upper lip areas accurately include the true postoperative position, whereas the prediction under-estimates the position of the cheeks and lower lip. A probabilistic FEM has been developed and validated for the prediction of the facial appearance following orthognathic surgery. This method shows how inaccuracies in the modelling and uncertainties in executing surgical planning influence the soft tissue prediction and it provides a range of predictions including a minimum and maximum, which may be helpful for patients in understanding the impact of surgery on the face. PMID:29742139

A novel soft tissue prediction methodology for orthognathic surgery based on probabilistic finite element modelling.

PubMed

Knoops, Paul G M; Borghi, Alessandro; Ruggiero, Federica; Badiali, Giovanni; Bianchi, Alberto; Marchetti, Claudio; Rodriguez-Florez, Naiara; Breakey, Richard W F; Jeelani, Owase; Dunaway, David J; Schievano, Silvia

2018-01-01

Repositioning of the maxilla in orthognathic surgery is carried out for functional and aesthetic purposes. Pre-surgical planning tools can predict 3D facial appearance by computing the response of the soft tissue to the changes to the underlying skeleton. The clinical use of commercial prediction software remains controversial, likely due to the deterministic nature of these computational predictions. A novel probabilistic finite element model (FEM) for the prediction of postoperative facial soft tissues is proposed in this paper. A probabilistic FEM was developed and validated on a cohort of eight patients who underwent maxillary repositioning and had pre- and postoperative cone beam computed tomography (CBCT) scans taken. Firstly, a variables correlation assessed various modelling parameters. Secondly, a design of experiments (DOE) provided a range of potential outcomes based on uniformly distributed input parameters, followed by an optimisation. Lastly, the second DOE iteration provided optimised predictions with a probability range. A range of 3D predictions was obtained using the probabilistic FEM and validated using reconstructed soft tissue surfaces from the postoperative CBCT data. The predictions in the nose and upper lip areas accurately include the true postoperative position, whereas the prediction under-estimates the position of the cheeks and lower lip. A probabilistic FEM has been developed and validated for the prediction of the facial appearance following orthognathic surgery. This method shows how inaccuracies in the modelling and uncertainties in executing surgical planning influence the soft tissue prediction and it provides a range of predictions including a minimum and maximum, which may be helpful for patients in understanding the impact of surgery on the face.

Comparison of 3D quantitative structure-activity relationship methods: Analysis of the in vitro antimalarial activity of 154 artemisinin analogues by hypothetical active-site lattice and comparative molecular field analysis

NASA Astrophysics Data System (ADS)

Woolfrey, John R.; Avery, Mitchell A.; Doweyko, Arthur M.

1998-03-01

Two three-dimensional quantitative structure-activity relationship (3D-QSAR) methods, comparative molecular field analysis (CoMFA) and hypothetical active site lattice (HASL), were compared with respect to the analysis of a training set of 154 artemisinin analogues. Five models were created, including a complete HASL and two trimmed versions, as well as two CoMFA models (leave-one-out standard CoMFA and the guided-region selection protocol). Similar r2 and q2 values were obtained by each method, although some striking differences existed between CoMFA contour maps and the HASL output. Each of the four predictive models exhibited a similar ability to predict the activity of a test set of 23 artemisinin analogues, although some differences were noted as to which compounds were described well by either model.

Development of a Low-Reynolds Number, Nonlinear kappa-epsilon Model for the Reduced Navier-Stokes Equations

NASA Technical Reports Server (NTRS)

Boger, David A.; Govindan, T. R.; McDonald, Henry

1997-01-01

Previous work at NASA LeRC has shown that flow distortions in aircraft engine inlet ducts can be significantly reduced by mounting vortex generators, or small wing sections, on the inside surface of the engine inlet. The placement of the vortex generators is an important factor in obtaining the optimal effect over a wide operating envelope. In this regard, the only alternative to a long and expensive test program which would search out this optimal configuration is a good prediction procedure which could narrow the field of search. Such a procedure has been developed in collaboration with NASA LeRC, and results obtained by NASA personnel indicate that it shows considerable promise for predicting the viscous turbulent flow in engine inlet ducts in the presence of vortex generators. The prediction tool is a computer code which numerically solves the reduced Navier-Stokes equations and so is commonly referred to as RNS3D. Obvious deficiencies in RNS3D have been addressed in previous work. Primarily, it is known that the predictions of the mean velocity field of a turbulent boundary layer flow approaching separation are not in good agreement with data. It was suggested that the use of an algebraic mixing-length turbulence model in RNS3D is at least partly to blame for this. Additionally, the current turbulence model includes an assumption of isotropy which will ultimately fail to capture turbulence-driven secondary flow known to exist in noncircular ducts.

Comparison of the performance of mental health, drug and alcohol comorbidities based on ICD-10-AM and medical records for predicting 12-month outcomes in trauma patients.

PubMed

Nguyen, Tu Q; Simpson, Pamela M; Braaf, Sandra C; Cameron, Peter A; Judson, Rodney; Gabbe, Belinda J

2018-06-05

Many outcome studies capture the presence of mental health, drug and alcohol comorbidities from administrative datasets and medical records. How these sources compare as predictors of patient outcomes has not been determined. The purpose of the present study was to compare mental health, drug and alcohol comorbidities based on ICD-10-AM coding and medical record documentation for predicting longer-term outcomes in injured patients. A random sample of patients (n = 500) captured by the Victorian State Trauma Registry was selected for the study. Retrospective medical record reviews were conducted to collect data about documented mental health, drug and alcohol comorbidities while ICD-10-AM codes were obtained from routinely collected hospital data. Outcomes at 12-months post-injury were the Glasgow Outcome Scale - Extended (GOS-E), European Quality of Life Five Dimensions (EQ-5D-3L), and return to work. Linear and logistic regression models, adjusted for age and gender, using medical record derived comorbidity and ICD-10-AM were compared using measures of calibration (Hosmer-Lemeshow statistic) and discrimination (C-statistic and R 2 ). There was no demonstrable difference in predictive performance between the medical record and ICD-10-AM models for predicting the GOS-E, EQ-5D-3L utility sore and EQ-5D-3L mobility, self-care, usual activities and pain/discomfort items. The area under the receiver operating characteristic (AUC) for models using medical record derived comorbidity (AUC 0.68, 95% CI: 0.63, 0.73) was higher than the model using ICD-10-AM data (AUC 0.62, 95% CI: 0.57, 0.67) for predicting the EQ-5D-3L anxiety/depression item. The discrimination of the model for predicting return to work was higher with inclusion of the medical record data (AUC 0.69, 95% CI: 0.63, 0.76) than the ICD-10-AM data (AUC 0.59, 95% CL: 0.52, 0.65). Mental health, drug and alcohol comorbidity information derived from medical record review was not clearly superior for predicting the majority of the outcomes assessed when compared to ICD-10-AM. While information available in medical records may be more comprehensive than in the ICD-10-AM, there appears to be little difference in the discriminative capacity of comorbidities coded in the two sources.

Pharmacophore Based 3D-QSAR, Virtual Screening and Docking Studies on Novel Series of HDAC Inhibitors with Thiophen Linker as Anticancer Agents.

PubMed

Patel, Preeti; Singh, Avineesh; Patel, Vijay K; Jain, Deepak K; Veerasamy, Ravichandran; Rajak, Harish

2016-01-01

Histone deacetylase (HDAC) inhibitors can reactivate gene expression and inhibit the growth and survival of cancer cells. To identify the important pharmacophoric features and correlate 3Dchemical structure with biological activity using 3D-QSAR and Pharmacophore modeling studies. The pharmacophore hypotheses were developed using e-pharmacophore script and phase module. Pharmacophore hypothesis represents the 3D arrangement of molecular features necessary for activity. A series of 55 compounds with wellassigned HDAC inhibitory activity were used for 3D-QSAR model development. Best 3D-QSAR model, which is a five partial least square (PLS) factor model with good statistics and predictive ability, acquired Q2 (0.7293), R2 (0.9811), cross-validated coefficient rcv 2=0.9807 and R2 pred=0.7147 with low standard deviation (0.0952). Additionally, the selected pharmacophore model DDRRR.419 was used as a 3D query for virtual screening against the ZINC database. In the virtual screening workflow, docking studies (HTVS, SP and XP) were carried out by selecting multiple receptors (PDB ID: 1T69, 1T64, 4LXZ, 4LY1, 3MAX, 2VQQ, 3C10, 1W22). Finally, six compounds were obtained based on high scoring function (dock score -11.2278-10.2222 kcal/mol) and diverse structures. The structure activity correlation was established using virtual screening, docking, energetic based pharmacophore modelling, pharmacophore, atom based 3D QSAR models and their validation. The outcomes of these studies could be further employed for the design of novel HDAC inhibitors for anticancer activity.

Transient Finite Element Analyses Developed to Model Fan Containment Impact Events

NASA Technical Reports Server (NTRS)

Pereira, J. Michael

1997-01-01

Research is underway to establish an increased level of confidence in existing numerical techniques for predicting transient behavior when the fan of a jet engine is released and impacts the fan containment system. To evaluate the predictive accuracy that can currently be obtained, researchers at the NASA Lewis Research Center used the DYNA 3D computer code to simulate large-scale subcomponent impact tests that were conducted at the University of Dayton Research Institute (UDRI) Impact Physics Lab. In these tests, 20- by 40-in. flat metal panels, contoured to the shape of a typical fan case, were impacted by the root section of a fan blade. The panels were oriented at an angle to the path of the projectile that would simulate the conditions in an actual blade-out event. The metal panels were modeled in DYNA 3D using a kinematic hardening model with the strain rate dependence of the yield stress governed by the Cowper-Simons rule. Failure was governed by the effective plastic strain criterion. The model of the fan blade and case just after impact is shown. By varying the maximum effective plastic strain, we obtained good qualitative agreement between the model and the experiments. Both the velocity required to penetrate the case and the deflection during impact compared well. This indicates that the failure criterion and constitutive model may be appropriate, but for DYNA 3D to be useful as a predictive tool, methods to determine accurate model parameters must be established. Simple methods for measuring model parameters are currently being developed. In addition, alternative constitutive models and failure criteria are being investigated.

Numerical Model for Predicting and Managing Heat Dissipation from a Neural Probe

DTIC Science & Technology

2013-05-10

Distance from Probe Centerline [m] x ‐  3D  Model y ‐  3D  Model r ‐ 2D Model 12 difficult, especially on a micro-scale level. For this reason...of the screws and nuts 180 m across. 20 were of plastic construction. An aluminum sample holder was constructed by the USNA Fabrication Lab...voltage drop across the reference resistor. C. Biosimulant Gel At first, a hydroxyethyl cellulose gel was considered for use as the biosimulant gel, but

Assessment of MARMOT Grain Growth Model

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

Fromm, B.; Zhang, Y.; Schwen, D.

2015-12-01

This report assesses the MARMOT grain growth model by comparing modeling predictions with experimental results from thermal annealing. The purpose here is threefold: (1) to demonstrate the validation approach of using thermal annealing experiments with non-destructive characterization, (2) to test the reconstruction capability and computation efficiency in MOOSE, and (3) to validate the grain growth model and the associated parameters that are implemented in MARMOT for UO 2. To assure a rigorous comparison, the 2D and 3D initial experimental microstructures of UO 2 samples were characterized using non-destructive Synchrotron x-ray. The same samples were then annealed at 2273K for grainmore » growth, and their initial microstructures were used as initial conditions for simulated annealing at the same temperature using MARMOT. After annealing, the final experimental microstructures were characterized again to compare with the results from simulations. So far, comparison between modeling and experiments has been done for 2D microstructures, and 3D comparison is underway. The preliminary results demonstrated the usefulness of the non-destructive characterization method for MARMOT grain growth model validation. A detailed analysis of the 3D microstructures is in progress to fully validate the current model in MARMOT.« less

Prediction Models for Dynamic Demand Response

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

Aman, Saima; Frincu, Marc; Chelmis, Charalampos

2015-11-02

As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D 2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D 2R, which we address inmore » this paper. Our first contribution is the formal definition of D 2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D 2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D 2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D 2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D 2R. Also, prediction models require just few days’ worth of data indicating that small amounts of historical training data can be used to make reliable predictions, simplifying the complexity of big data challenge associated with D 2R.« less

Biomarkers for predicting type 2 diabetes development-Can metabolomics improve on existing biomarkers?

PubMed

Savolainen, Otto; Fagerberg, Björn; Vendelbo Lind, Mads; Sandberg, Ann-Sofie; Ross, Alastair B; Bergström, Göran

2017-01-01

The aim was to determine if metabolomics could be used to build a predictive model for type 2 diabetes (T2D) risk that would improve prediction of T2D over current risk markers. Gas chromatography-tandem mass spectrometry metabolomics was used in a nested case-control study based on a screening sample of 64-year-old Caucasian women (n = 629). Candidate metabolic markers of T2D were identified in plasma obtained at baseline and the power to predict diabetes was tested in 69 incident cases occurring during 5.5 years follow-up. The metabolomics results were used as a standalone prediction model and in combination with established T2D predictive biomarkers for building eight T2D prediction models that were compared with each other based on their sensitivity and selectivity for predicting T2D. Established markers of T2D (impaired fasting glucose, impaired glucose tolerance, insulin resistance (HOMA), smoking, serum adiponectin)) alone, and in combination with metabolomics had the largest areas under the curve (AUC) (0.794 (95% confidence interval [0.738-0.850]) and 0.808 [0.749-0.867] respectively), with the standalone metabolomics model based on nine fasting plasma markers having a lower predictive power (0.657 [0.577-0.736]). Prediction based on non-blood based measures was 0.638 [0.565-0.711]). Established measures of T2D risk remain the best predictor of T2D risk in this population. Additional markers detected using metabolomics are likely related to these measures as they did not enhance the overall prediction in a combined model.

Biomarkers for predicting type 2 diabetes development—Can metabolomics improve on existing biomarkers?

PubMed Central

Savolainen, Otto; Fagerberg, Björn; Vendelbo Lind, Mads; Sandberg, Ann-Sofie; Ross, Alastair B.; Bergström, Göran

2017-01-01

Aim The aim was to determine if metabolomics could be used to build a predictive model for type 2 diabetes (T2D) risk that would improve prediction of T2D over current risk markers. Methods Gas chromatography-tandem mass spectrometry metabolomics was used in a nested case-control study based on a screening sample of 64-year-old Caucasian women (n = 629). Candidate metabolic markers of T2D were identified in plasma obtained at baseline and the power to predict diabetes was tested in 69 incident cases occurring during 5.5 years follow-up. The metabolomics results were used as a standalone prediction model and in combination with established T2D predictive biomarkers for building eight T2D prediction models that were compared with each other based on their sensitivity and selectivity for predicting T2D. Results Established markers of T2D (impaired fasting glucose, impaired glucose tolerance, insulin resistance (HOMA), smoking, serum adiponectin)) alone, and in combination with metabolomics had the largest areas under the curve (AUC) (0.794 (95% confidence interval [0.738–0.850]) and 0.808 [0.749–0.867] respectively), with the standalone metabolomics model based on nine fasting plasma markers having a lower predictive power (0.657 [0.577–0.736]). Prediction based on non-blood based measures was 0.638 [0.565–0.711]). Conclusions Established measures of T2D risk remain the best predictor of T2D risk in this population. Additional markers detected using metabolomics are likely related to these measures as they did not enhance the overall prediction in a combined model. PMID:28692646

Study on the activity of non-purine xanthine oxidase inhibitor by 3D-QSAR modeling and molecular docking

NASA Astrophysics Data System (ADS)

Li, Peizhen; Tian, Yueli; Zhai, Honglin; Deng, Fangfang; Xie, Meihong; Zhang, Xiaoyun

2013-11-01

Non-purine derivatives have been shown to be promising novel drug candidates as xanthine oxidase inhibitors. Based on three-dimensional quantitative structure-activity relationship (3D-QSAR) methods including comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), two 3D-QSAR models for a series of non-purine xanthine oxidase (XO) inhibitors were established, and their reliability was supported by statistical parameters. Combined 3D-QSAR modeling and the results of molecular docking between non-purine xanthine oxidase inhibitors and XO, the main factors that influenced activity of inhibitors were investigated, and the obtained results could explain known experimental facts. Furthermore, several new potential inhibitors with higher activity predicted were designed, which based on our analyses, and were supported by the simulation of molecular docking. This study provided some useful information for the development of non-purine xanthine oxidase inhibitors with novel structures.

DFT and 3D-QSAR Studies of Anti-Cancer Agents m-(4-Morpholinoquinazolin-2-yl) Benzamide Derivatives for Novel Compounds Design

NASA Astrophysics Data System (ADS)

Zhao, Siqi; Zhang, Guanglong; Xia, Shuwei; Yu, Liangmin

2018-06-01

As a group of diversified frameworks, quinazolin derivatives displayed a broad field of biological functions, especially as anticancer. To investigate the quantitative structure-activity relationship, 3D-QSAR models were generated with 24 quinazolin scaffold molecules. The experimental and predicted pIC50 values for both training and test set compounds showed good correlation, which proved the robustness and reliability of the generated QSAR models. The most effective CoMFA and CoMSIA were obtained with correlation coefficient r 2 ncv of 1.00 (both) and leave-one-out coefficient q 2 of 0.61 and 0.59, respectively. The predictive abilities of CoMFA and CoMSIA were quite good with the predictive correlation coefficients ( r 2 pred ) of 0.97 and 0.91. In addition, the statistic results of CoMFA and CoMSIA were used to design new quinazolin molecules.

Molecular docking and QSAR study on steroidal compounds as aromatase inhibitors.

PubMed

Dai, Yujie; Wang, Qiang; Zhang, Xiuli; Jia, Shiru; Zheng, Heng; Feng, Dacheng; Yu, Peng

2010-12-01

In order to develop more potent, selective and less toxic steroidal aromatase (AR) inhibitors, molecular docking, 2D and 3D hybrid quantitative structure-activity relationship (QSAR) study have been conducted using topological, molecular shape, spatial, structural and thermodynamic descriptors on 32 steroidal compounds. The molecular docking study shows that one or more hydrogen bonds with MET374 are one of the essential requirements for the optimum binding of ligands. The QSAR model obtained indicates that the aromatase inhibitory activity can be enhanced by increasing SIC, SC_3_C, Jurs_WNSA_1, Jurs_WPSA_1 and decreasing CDOCKER interaction energy (ECD), IAC_Total and Shadow_XZfrac. The predicted results shows that this model has a comparatively good predictive power which can be used in prediction of activity of new steroidal aromatase inhibitors. Copyright © 2010 Elsevier Masson SAS. All rights reserved.

Predicting Stress vs. Strain Behaviors of Thin-Walled High Pressure Die Cast Magnesium Alloy with Actual Pore Distribution

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

Choi, Kyoo Sil; Barker, Erin; Cheng, Guang

2016-01-06

In this paper, a three-dimensional (3D) microstructure-based finite element modeling method (i.e., extrinsic modeling method) is developed, which can be used in examining the effects of porosity on the ductility/fracture of Mg castings. For this purpose, AM60 Mg tensile samples were generated under high-pressure die-casting in a specially-designed mold. Before the tensile test, the samples were CT-scanned to obtain the pore distributions within the samples. 3D microstructure-based finite element models were then developed based on the obtained actual pore distributions of the gauge area. The input properties for the matrix material were determined by fitting the simulation result to themore » experimental result of a selected sample, and then used for all the other samples’ simulation. The results show that the ductility and fracture locations predicted from simulations agree well with the experimental results. This indicates that the developed 3D extrinsic modeling method may be used to examine the influence of various aspects of pore sizes/distributions as well as intrinsic properties (i.e., matrix properties) on the ductility/fracture of Mg castings.« less

Ash3d: A finite-volume, conservative numerical model for ash transport and tephra deposition

USGS Publications Warehouse

Schwaiger, Hans F.; Denlinger, Roger P.; Mastin, Larry G.

2012-01-01

We develop a transient, 3-D Eulerian model (Ash3d) to predict airborne volcanic ash concentration and tephra deposition during volcanic eruptions. This model simulates downwind advection, turbulent diffusion, and settling of ash injected into the atmosphere by a volcanic eruption column. Ash advection is calculated using time-varying pre-existing wind data and a robust, high-order, finite-volume method. Our routine is mass-conservative and uses the coordinate system of the wind data, either a Cartesian system local to the volcano or a global spherical system for the Earth. Volcanic ash is specified with an arbitrary number of grain sizes, which affects the fall velocity, distribution and duration of transport. Above the source volcano, the vertical mass distribution with elevation is calculated using a Suzuki distribution for a given plume height, eruptive volume, and eruption duration. Multiple eruptions separated in time may be included in a single simulation. We test the model using analytical solutions for transport. Comparisons of the predicted and observed ash distributions for the 18 August 1992 eruption of Mt. Spurr in Alaska demonstrate to the efficacy and efficiency of the routine.

3D statistical shape models incorporating 3D random forest regression voting for robust CT liver segmentation

NASA Astrophysics Data System (ADS)

Norajitra, Tobias; Meinzer, Hans-Peter; Maier-Hein, Klaus H.

2015-03-01

During image segmentation, 3D Statistical Shape Models (SSM) usually conduct a limited search for target landmarks within one-dimensional search profiles perpendicular to the model surface. In addition, landmark appearance is modeled only locally based on linear profiles and weak learners, altogether leading to segmentation errors from landmark ambiguities and limited search coverage. We present a new method for 3D SSM segmentation based on 3D Random Forest Regression Voting. For each surface landmark, a Random Regression Forest is trained that learns a 3D spatial displacement function between the according reference landmark and a set of surrounding sample points, based on an infinite set of non-local randomized 3D Haar-like features. Landmark search is then conducted omni-directionally within 3D search spaces, where voxelwise forest predictions on landmark position contribute to a common voting map which reflects the overall position estimate. Segmentation experiments were conducted on a set of 45 CT volumes of the human liver, of which 40 images were randomly chosen for training and 5 for testing. Without parameter optimization, using a simple candidate selection and a single resolution approach, excellent results were achieved, while faster convergence and better concavity segmentation were observed, altogether underlining the potential of our approach in terms of increased robustness from distinct landmark detection and from better search coverage.

The Predictive Value of Preoperative Health-Related Quality-of-Life Scores on Postoperative Patient-Reported Outcome Scores in Lumbar Spine Surgery

PubMed Central

Hey, Hwee Weng Dennis; Luo, Nan; Chin, Sze Yung; Lau, Eugene Tze Chun; Wang, Pei; Kumar, Naresh; Lau, Leok-Lim; Ruiz, John Nathaniel; Thambiah, Joseph Shanthakumar; Liu, Ka-Po Gabriel; Wong, Hee-Kit

2017-01-01

Study Design: A single-center, retrospective cohort study. Objective: To predict patient-reported outcomes (PROs) using preoperative health-related quality-of-life (HRQoL) scores by quantifying the correlation between them, so as to aid selection of surgical candidates and preoperative counselling. Methods: All patients who underwent single-level elective lumbar spine surgery over a 2-year period were divided into 3 diagnosis groups: spondylolisthesis, spinal stenosis, and disc herniation. Patient characteristics and health scores (Oswestry Low Back Pain and Disability Index [ODI], EQ-5D, and Short Form-36 version 2 [SF-36v2]) were collected at 6 and 24 months and compared between the 3 diagnosis groups. Multivariate modelling was performed to investigate the predictive value of each parameter, particularly preoperative ODI and EQ-5D, on postoperative ODI and EQ-5D scores for all the patients. Results: ODI and EQ-5D at 6 and 24 months improved significantly for all patients, especially in the disc herniation group, compared to the baseline. The magnitude of improvement in ODI and EQ-5D was predictable using preoperative ODI, EQ-5D, and SF-36v2 Mental Component Score. At 6 months, 1-point baseline ODI predicts for 0.7-point increase in changed ODI, and a 0.01-point increase in baseline EQ-5D predicts for 0.01-point decrease in changed EQ-5D score. At 24 months, 1-point baseline ODI predicts for 1-point increase in changed ODI, and a 0.01-point increase in baseline EQ-5D predicts for 0.009-point decrease in changed EQ-5D. A younger age is shown to be a positive predictor of ODI at 24 months. Conclusions: Poorer baseline health scores predict greater improvement in postoperative PROs at 6 and 24 months after the surgery. HRQoL scores can be used to decide on surgery and in preoperative counselling. PMID:29662746

The Predictive Value of Preoperative Health-Related Quality-of-Life Scores on Postoperative Patient-Reported Outcome Scores in Lumbar Spine Surgery.

PubMed

Hey, Hwee Weng Dennis; Luo, Nan; Chin, Sze Yung; Lau, Eugene Tze Chun; Wang, Pei; Kumar, Naresh; Lau, Leok-Lim; Ruiz, John Nathaniel; Thambiah, Joseph Shanthakumar; Liu, Ka-Po Gabriel; Wong, Hee-Kit

2018-04-01

A single-center, retrospective cohort study. To predict patient-reported outcomes (PROs) using preoperative health-related quality-of-life (HRQoL) scores by quantifying the correlation between them, so as to aid selection of surgical candidates and preoperative counselling. All patients who underwent single-level elective lumbar spine surgery over a 2-year period were divided into 3 diagnosis groups: spondylolisthesis, spinal stenosis, and disc herniation. Patient characteristics and health scores (Oswestry Low Back Pain and Disability Index [ODI], EQ-5D, and Short Form-36 version 2 [SF-36v2]) were collected at 6 and 24 months and compared between the 3 diagnosis groups. Multivariate modelling was performed to investigate the predictive value of each parameter, particularly preoperative ODI and EQ-5D, on postoperative ODI and EQ-5D scores for all the patients. ODI and EQ-5D at 6 and 24 months improved significantly for all patients, especially in the disc herniation group, compared to the baseline. The magnitude of improvement in ODI and EQ-5D was predictable using preoperative ODI, EQ-5D, and SF-36v2 Mental Component Score. At 6 months, 1-point baseline ODI predicts for 0.7-point increase in changed ODI, and a 0.01-point increase in baseline EQ-5D predicts for 0.01-point decrease in changed EQ-5D score. At 24 months, 1-point baseline ODI predicts for 1-point increase in changed ODI, and a 0.01-point increase in baseline EQ-5D predicts for 0.009-point decrease in changed EQ-5D. A younger age is shown to be a positive predictor of ODI at 24 months. Poorer baseline health scores predict greater improvement in postoperative PROs at 6 and 24 months after the surgery. HRQoL scores can be used to decide on surgery and in preoperative counselling.

CoMFA and CoMSIA studies on C-aryl glucoside SGLT2 inhibitors as potential anti-diabetic agents.

PubMed

Vyas, V K; Bhatt, H G; Patel, P K; Jalu, J; Chintha, C; Gupta, N; Ghate, M

2013-01-01

SGLT2 has become a target of therapeutic interest in diabetes research. CoMFA and CoMSIA studies were performed on C-aryl glucoside SGLT2 inhibitors (180 analogues) as potential anti-diabetic agents. Three different alignment strategies were used for the compounds. The best CoMFA and CoMSIA models were obtained by means of Distill rigid body alignment of training and test sets, and found statistically significant with cross-validated coefficients (q²) of 0.602 and 0.618, respectively, and conventional coefficients (r²) of 0.905 and 0.902, respectively. Both models were validated by a test set of 36 compounds giving satisfactory predicted correlation coefficients (r² pred) of 0.622 and 0.584 for CoMFA and CoMSIA models, respectively. A comparison was made with earlier 3D QSAR study on SGLT2 inhibitors, which shows that our 3D QSAR models are better than earlier models to predict good inhibitory activity. CoMFA and CoMSIA models generated in this work can provide useful information to design new compounds and helped in prediction of activity prior to synthesis.

Restoration of the Patient-Specific Anatomy of the Proximal and Distal Parts of the Humerus: Statistical Shape Modeling Versus Contralateral Registration Method.

PubMed

Vlachopoulos, Lazaros; Lüthi, Marcel; Carrillo, Fabio; Gerber, Christian; Székely, Gábor; Fürnstahl, Philipp

2018-04-18

In computer-assisted reconstructive surgeries, the contralateral anatomy is established as the best available reconstruction template. However, existing intra-individual bilateral differences or a pathological, contralateral humerus may limit the applicability of the method. The aim of the study was to evaluate whether a statistical shape model (SSM) has the potential to predict accurately the pretraumatic anatomy of the humerus from the posttraumatic condition. Three-dimensional (3D) triangular surface models were extracted from the computed tomographic data of 100 paired cadaveric humeri without a pathological condition. An SSM was constructed, encoding the characteristic shape variations among the individuals. To predict the patient-specific anatomy of the proximal (or distal) part of the humerus with the SSM, we generated segments of the humerus of predefined length excluding the part to predict. The proximal and distal humeral prediction (p-HP and d-HP) errors, defined as the deviation of the predicted (bone) model from the original (bone) model, were evaluated. For comparison with the state-of-the-art technique, i.e., the contralateral registration method, we used the same segments of the humerus to evaluate whether the SSM or the contralateral anatomy yields a more accurate reconstruction template. The p-HP error (mean and standard deviation, 3.8° ± 1.9°) using 85% of the distal end of the humerus to predict the proximal humeral anatomy was significantly smaller (p = 0.001) compared with the contralateral registration method. The difference between the d-HP error (mean, 5.5° ± 2.9°), using 85% of the proximal part of the humerus to predict the distal humeral anatomy, and the contralateral registration method was not significant (p = 0.61). The restoration of the humeral length was not significantly different between the SSM and the contralateral registration method. SSMs accurately predict the patient-specific anatomy of the proximal and distal aspects of the humerus. The prediction errors of the SSM depend on the size of the healthy part of the humerus. The prediction of the patient-specific anatomy of the humerus is of fundamental importance for computer-assisted reconstructive surgeries.