Incorporation of local structure into kriging models for the prediction of atomistic properties in the water decamer.

PubMed

Davie, Stuart J; Di Pasquale, Nicodemo; Popelier, Paul L A

2016-10-15

Machine learning algorithms have been demonstrated to predict atomistic properties approaching the accuracy of quantum chemical calculations at significantly less computational cost. Difficulties arise, however, when attempting to apply these techniques to large systems, or systems possessing excessive conformational freedom. In this article, the machine learning method kriging is applied to predict both the intra-atomic and interatomic energies, as well as the electrostatic multipole moments, of the atoms of a water molecule at the center of a 10 water molecule (decamer) cluster. Unlike previous work, where the properties of small water clusters were predicted using a molecular local frame, and where training set inputs (features) were based on atomic index, a variety of feature definitions and coordinate frames are considered here to increase prediction accuracy. It is shown that, for a water molecule at the center of a decamer, no single method of defining features or coordinate schemes is optimal for every property. However, explicitly accounting for the structure of the first solvation shell in the definition of the features of the kriging training set, and centring the coordinate frame on the atom-of-interest will, in general, return better predictions than models that apply the standard methods of feature definition, or a molecular coordinate frame. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Large-scale binding ligand prediction by improved patch-based method Patch-Surfer2.0

PubMed Central

Zhu, Xiaolei; Xiong, Yi; Kihara, Daisuke

2015-01-01

Motivation: Ligand binding is a key aspect of the function of many proteins. Thus, binding ligand prediction provides important insight in understanding the biological function of proteins. Binding ligand prediction is also useful for drug design and examining potential drug side effects. Results: We present a computational method named Patch-Surfer2.0, which predicts binding ligands for a protein pocket. By representing and comparing pockets at the level of small local surface patches that characterize physicochemical properties of the local regions, the method can identify binding pockets of the same ligand even if they do not share globally similar shapes. Properties of local patches are represented by an efficient mathematical representation, 3D Zernike Descriptor. Patch-Surfer2.0 has significant technical improvements over our previous prototype, which includes a new feature that captures approximate patch position with a geodesic distance histogram. Moreover, we constructed a large comprehensive database of ligand binding pockets that will be searched against by a query. The benchmark shows better performance of Patch-Surfer2.0 over existing methods. Availability and implementation: http://kiharalab.org/patchsurfer2.0/ Contact: dkihara@purdue.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25359888

Experimental test of quantum nonlocality in three-photon Greenberger-Horne-Zeilinger entanglement

PubMed

Pan; Bouwmeester; Daniell; Weinfurter; Zeilinger

2000-02-03

Bell's theorem states that certain statistical correlations predicted by quantum physics for measurements on two-particle systems cannot be understood within a realistic picture based on local properties of each individual particle-even if the two particles are separated by large distances. Einstein, Podolsky and Rosen first recognized the fundamental significance of these quantum correlations (termed 'entanglement' by Schrodinger) and the two-particle quantum predictions have found ever-increasing experimental support. A more striking conflict between quantum mechanical and local realistic predictions (for perfect correlations) has been discovered; but experimental verification has been difficult, as it requires entanglement between at least three particles. Here we report experimental confirmation of this conflict, using our recently developed method to observe three-photon entanglement, or 'Greenberger-Horne-Zeilinger' (GHZ) states. The results of three specific experiments, involving measurements of polarization correlations between three photons, lead to predictions for a fourth experiment; quantum physical predictions are mutually contradictory with expectations based on local realism. We find the results of the fourth experiment to be in agreement with the quantum prediction and in striking conflict with local realism.

Local plant adaptation across a subarctic elevational gradient

PubMed Central

Kardol, Paul; De Long, Jonathan R.; Wardle, David A.

2014-01-01

Predicting how plants will respond to global warming necessitates understanding of local plant adaptation to temperature. Temperature may exert selective effects on plants directly, and also indirectly through environmental factors that covary with temperature, notably soil properties. However, studies on the interactive effects of temperature and soil properties on plant adaptation are rare, and the role of abiotic versus biotic soil properties in plant adaptation to temperature remains untested. We performed two growth chamber experiments using soils and Bistorta vivipara bulbil ecotypes from a subarctic elevational gradient (temperature range: ±3°C) in northern Sweden to disentangle effects of local ecotype, temperature, and biotic and abiotic properties of soil origin on plant growth. We found partial evidence for local adaption to temperature. Although soil origin affected plant growth, we did not find support for local adaptation to either abiotic or biotic soil properties, and there were no interactive effects of soil origin with ecotype or temperature. Our results indicate that ecotypic variation can be an important driver of plant responses to the direct effects of increasing temperature, while responses to covariation in soil properties are of a phenotypic, rather than adaptive, nature. PMID:26064553

Energy landscapes for a machine learning application to series data

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

Ballard, Andrew J.; Stevenson, Jacob D.; Das, Ritankar

2016-03-28

Methods developed to explore and characterise potential energy landscapes are applied to the corresponding landscapes obtained from optimisation of a cost function in machine learning. We consider neural network predictions for the outcome of local geometry optimisation in a triatomic cluster, where four distinct local minima exist. The accuracy of the predictions is compared for fits using data from single and multiple points in the series of atomic configurations resulting from local geometry optimisation and for alternative neural networks. The machine learning solution landscapes are visualised using disconnectivity graphs, and signatures in the effective heat capacity are analysed in termsmore » of distributions of local minima and their properties.« less

From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks

PubMed Central

Cannistraci, Carlo Vittorio; Alanis-Lobato, Gregorio; Ravasi, Timothy

2013-01-01

Growth and remodelling impact the network topology of complex systems, yet a general theory explaining how new links arise between existing nodes has been lacking, and little is known about the topological properties that facilitate link-prediction. Here we investigate the extent to which the connectivity evolution of a network might be predicted by mere topological features. We show how a link/community-based strategy triggers substantial prediction improvements because it accounts for the singular topology of several real networks organised in multiple local communities - a tendency here named local-community-paradigm (LCP). We observe that LCP networks are mainly formed by weak interactions and characterise heterogeneous and dynamic systems that use self-organisation as a major adaptation strategy. These systems seem designed for global delivery of information and processing via multiple local modules. Conversely, non-LCP networks have steady architectures formed by strong interactions, and seem designed for systems in which information/energy storage is crucial. PMID:23563395

From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks.

PubMed

Cannistraci, Carlo Vittorio; Alanis-Lobato, Gregorio; Ravasi, Timothy

2013-01-01

Growth and remodelling impact the network topology of complex systems, yet a general theory explaining how new links arise between existing nodes has been lacking, and little is known about the topological properties that facilitate link-prediction. Here we investigate the extent to which the connectivity evolution of a network might be predicted by mere topological features. We show how a link/community-based strategy triggers substantial prediction improvements because it accounts for the singular topology of several real networks organised in multiple local communities - a tendency here named local-community-paradigm (LCP). We observe that LCP networks are mainly formed by weak interactions and characterise heterogeneous and dynamic systems that use self-organisation as a major adaptation strategy. These systems seem designed for global delivery of information and processing via multiple local modules. Conversely, non-LCP networks have steady architectures formed by strong interactions, and seem designed for systems in which information/energy storage is crucial.

Large-scale binding ligand prediction by improved patch-based method Patch-Surfer2.0.

PubMed

Zhu, Xiaolei; Xiong, Yi; Kihara, Daisuke

2015-03-01

Ligand binding is a key aspect of the function of many proteins. Thus, binding ligand prediction provides important insight in understanding the biological function of proteins. Binding ligand prediction is also useful for drug design and examining potential drug side effects. We present a computational method named Patch-Surfer2.0, which predicts binding ligands for a protein pocket. By representing and comparing pockets at the level of small local surface patches that characterize physicochemical properties of the local regions, the method can identify binding pockets of the same ligand even if they do not share globally similar shapes. Properties of local patches are represented by an efficient mathematical representation, 3D Zernike Descriptor. Patch-Surfer2.0 has significant technical improvements over our previous prototype, which includes a new feature that captures approximate patch position with a geodesic distance histogram. Moreover, we constructed a large comprehensive database of ligand binding pockets that will be searched against by a query. The benchmark shows better performance of Patch-Surfer2.0 over existing methods. http://kiharalab.org/patchsurfer2.0/ CONTACT: dkihara@purdue.edu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Soft sensor modeling based on variable partition ensemble method for nonlinear batch processes

NASA Astrophysics Data System (ADS)

Wang, Li; Chen, Xiangguang; Yang, Kai; Jin, Huaiping

2017-01-01

Batch processes are always characterized by nonlinear and system uncertain properties, therefore, the conventional single model may be ill-suited. A local learning strategy soft sensor based on variable partition ensemble method is developed for the quality prediction of nonlinear and non-Gaussian batch processes. A set of input variable sets are obtained by bootstrapping and PMI criterion. Then, multiple local GPR models are developed based on each local input variable set. When a new test data is coming, the posterior probability of each best performance local model is estimated based on Bayesian inference and used to combine these local GPR models to get the final prediction result. The proposed soft sensor is demonstrated by applying to an industrial fed-batch chlortetracycline fermentation process.

First principles predictions of electronic and elastic properties of BaPb2As2 in the ThCr2Si2-type structure

NASA Astrophysics Data System (ADS)

Bourourou, Y.; Amari, S.; Yahiaoui, I. E.; Bouhafs, B.

2018-01-01

A first-principles approach is used to predicts the electronic and elastic properties of BaPb2As2 superconductor compound, using full-potential linearized augmented plane wave plus local orbitals (FP-L/APW+lo) scheme within the local density approximation LDA. The calculated equilibrium structural parameter a agree well with the experiment while the c/a ratio is far away from the experimental result. The band structure, density of states, together with the charge density and chemical bonding are discussed. The calculated elastic constants for our compound indicate that it is mechanically stable at ambient pressure. Polycrystalline elastic moduli (Young's, Bulk, shear Modulus and the Poisson's ratio) were calculated according to the Voigte-Reusse-Hill (VRH) average.

Chemical and physical insight on the local properties of the phosphides XSiP2 (X = Be, Mg, Cd, Zn and Hg) under pressure: from first principles calculations

NASA Astrophysics Data System (ADS)

Ouahrani, Tarik

2013-09-01

Local properties of the XSiP2 (X = Be, Mg, Cd, Zn and Hg) compounds are revisited through the partition of static thermodynamic properties under pressure. We pay attention to the metallization that occurs when the investigated compounds undergo a phase transition from chalcopyrite to the NaCl structure. Electron localization function analysis shows that the local valence basin attractors values decrease as a function of pressure. As the pressure increases, the tetragonal distortion ( c/ a) diminishes while the degree of ionicity enhances. In addition, by means of atom in molecule approach, atomic-like local compressibility and pressures are analyzed. We found that the basins volumes of the investigated compounds in the NaCl phase have lower compressibilities than those in the chalcopyrite phase. According to the predicted core-valence basins, the phosphorus cation is found to be the more affected by the hydrostatic pressure.

Local thermal sensation modeling-a review on the necessity and availability of local clothing properties and local metabolic heat production.

PubMed

Veselá, S; Kingma, B R M; Frijns, A J H

2017-03-01

Local thermal sensation modeling gained importance due to developments in personalized and locally applied heating and cooling systems in office environments. The accuracy of these models depends on skin temperature prediction by thermophysiological models, which in turn rely on accurate environmental and personal input data. Environmental parameters are measured or prescribed, but personal factors such as clothing properties and metabolic rates have to be estimated. Data for estimating the overall values of clothing properties and metabolic rates are available in several papers and standards. However, local values are more difficult to retrieve. For local clothing, this study revealed that full and consistent data sets are not available in the published literature for typical office clothing sets. Furthermore, the values for local heat production were not verified for characteristic office activities, but were adapted empirically. Further analyses showed that variations in input parameters can lead to local skin temperature differences (∆T skin,loc  = 0.4-4.4°C). These differences can affect the local sensation output, where ∆T skin,loc  = 1°C is approximately one step on a 9-point thermal sensation scale. In conclusion, future research should include a systematic study of local clothing properties and the development of feasible methods for measuring and validating local heat production. © 2016 The Authors. Indoor Air published by John Wiley & Sons Ltd.

An EQT-cDFT approach to determine thermodynamic properties of confined fluids.

PubMed

Mashayak, S Y; Motevaselian, M H; Aluru, N R

2015-06-28

We present a continuum-based approach to predict the structure and thermodynamic properties of confined fluids at multiple length-scales, ranging from a few angstroms to macro-meters. The continuum approach is based on the empirical potential-based quasi-continuum theory (EQT) and classical density functional theory (cDFT). EQT is a simple and fast approach to predict inhomogeneous density and potential profiles of confined fluids. We use EQT potentials to construct a grand potential functional for cDFT. The EQT-cDFT-based grand potential can be used to predict various thermodynamic properties of confined fluids. In this work, we demonstrate the EQT-cDFT approach by simulating Lennard-Jones fluids, namely, methane and argon, confined inside slit-like channels of graphene. We show that the EQT-cDFT can accurately predict the structure and thermodynamic properties, such as density profiles, adsorption, local pressure tensor, surface tension, and solvation force, of confined fluids as compared to the molecular dynamics simulation results.

Evidence of sharp and diffuse domain walls in BiFeO3 by means of unit-cell-wise strain and polarization maps obtained with high resolution scanning transmission electron microscopy.

PubMed

Lubk, A; Rossell, M D; Seidel, J; He, Q; Yang, S Y; Chu, Y H; Ramesh, R; Hÿtch, M J; Snoeck, E

2012-07-27

Domain walls (DWs) substantially influence a large number of applications involving ferroelectric materials due to their limited mobility when shifted during polarization switching. The discovery of greatly enhanced conduction at BiFeO(3) DWs has highlighted yet another role of DWs as a local material state with unique properties. However, the lack of precise information on the local atomic structure is still hampering microscopical understanding of DW properties. Here, we examine the atomic structure of BiFeO(3) 109° DWs with pm precision by a combination of high-angle annular dark-field scanning transmission electron microscopy and a dedicated structural analysis. By measuring simultaneously local polarization and strain, we provide direct experimental proof for the straight DW structure predicted by ab initio calculations as well as the recently proposed theory of diffuse DWs, thus resolving a long-standing discrepancy between experimentally measured and theoretically predicted DW mobilities.

Soft sensor development for Mooney viscosity prediction in rubber mixing process based on GMMDJITGPR algorithm

NASA Astrophysics Data System (ADS)

Yang, Kai; Chen, Xiangguang; Wang, Li; Jin, Huaiping

2017-01-01

In rubber mixing process, the key parameter (Mooney viscosity), which is used to evaluate the property of the product, can only be obtained with 4-6h delay offline. It is quite helpful for the industry, if the parameter can be estimate on line. Various data driven soft sensors have been used to prediction in the rubber mixing. However, it always not functions well due to the phase and nonlinear property in the process. The purpose of this paper is to develop an efficient soft sensing algorithm to solve the problem. Based on the proposed GMMD local sample selecting criterion, the phase information is extracted in the local modeling. Using the Gaussian local modeling method within Just-in-time (JIT) learning framework, nonlinearity of the process is well handled. Efficiency of the new method is verified by comparing the performance with various mainstream soft sensors, using the samples from real industrial rubber mixing process.

Injection-Molded Long-Fiber Thermoplastic Composites: From Process Modeling to Prediction of Mechanical Properties

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

Nguyen, Ba Nghiep; Kunc, Vlastimil; Jin, Xiaoshi

2013-12-18

This article illustrates the predictive capabilities for long-fiber thermoplastic (LFT) composites that first simulate the injection molding of LFT structures by Autodesk® Simulation Moldflow® Insight (ASMI) to accurately predict fiber orientation and length distributions in these structures. After validating fiber orientation and length predictions against the experimental data, the predicted results are used by ASMI to compute distributions of elastic properties in the molded structures. In addition, local stress-strain responses and damage accumulation under tensile loading are predicted by an elastic-plastic damage model of EMTA-NLA, a nonlinear analysis tool implemented in ABAQUS® via user-subroutines using an incremental Eshelby-Mori-Tanaka approach. Predictedmore » stress-strain responses up to failure and damage accumulations are compared to the experimental results to validate the model.« less

SubCellProt: predicting protein subcellular localization using machine learning approaches.

PubMed

Garg, Prabha; Sharma, Virag; Chaudhari, Pradeep; Roy, Nilanjan

2009-01-01

High-throughput genome sequencing projects continue to churn out enormous amounts of raw sequence data. However, most of this raw sequence data is unannotated and, hence, not very useful. Among the various approaches to decipher the function of a protein, one is to determine its localization. Experimental approaches for proteome annotation including determination of a protein's subcellular localizations are very costly and labor intensive. Besides the available experimental methods, in silico methods present alternative approaches to accomplish this task. Here, we present two machine learning approaches for prediction of the subcellular localization of a protein from the primary sequence information. Two machine learning algorithms, k Nearest Neighbor (k-NN) and Probabilistic Neural Network (PNN) were used to classify an unknown protein into one of the 11 subcellular localizations. The final prediction is made on the basis of a consensus of the predictions made by two algorithms and a probability is assigned to it. The results indicate that the primary sequence derived features like amino acid composition, sequence order and physicochemical properties can be used to assign subcellular localization with a fair degree of accuracy. Moreover, with the enhanced accuracy of our approach and the definition of a prediction domain, this method can be used for proteome annotation in a high throughput manner. SubCellProt is available at www.databases.niper.ac.in/SubCellProt.

Very High Cycle Fatigue Failure Analysis and Life Prediction of Cr-Ni-W Gear Steel Based on Crack Initiation and Growth Behaviors.

PubMed

Deng, Hailong; Li, Wei; Sakai, Tatsuo; Sun, Zhenduo

2015-12-02

The unexpected failures of structural materials in very high cycle fatigue (VHCF) regime have been a critical issue in modern engineering design. In this study, the VHCF property of a Cr-Ni-W gear steel was experimentally investigated under axial loading with the stress ratio of R = -1, and a life prediction model associated with crack initiation and growth behaviors was proposed. Results show that the Cr-Ni-W gear steel exhibits the constantly decreasing S-N property without traditional fatigue limit, and the fatigue strength corresponding to 10⁸ cycles is around 485 MPa. The inclusion-fine granular area (FGA)-fisheye induced failure becomes the main failure mechanism in the VHCF regime, and the local stress around the inclusion play a key role. By using the finite element analysis of representative volume element, the local stress tends to increase with the increase of elastic modulus difference between inclusion and matrix. The predicted crack initiation life occupies the majority of total fatigue life, while the predicted crack growth life is only accounts for a tiny fraction. In view of the good agreement between the predicted and experimental results, the proposed VHCF life prediction model involving crack initiation and growth can be acceptable for inclusion-FGA-fisheye induced failure.

A Bridge from Optical to Infrared Galaxies: Explaining Local Properties, Predicting Galaxy Counts and the Cosmic Background Radiation

NASA Astrophysics Data System (ADS)

Totani, T.; Takeuchi, T. T.

2001-12-01

A new model of infrared galaxy counts and the cosmic background radiation (CBR) is developed by extending a model for optical/near-infrared galaxies. Important new characteristics of this model are that mass scale dependence of dust extinction is introduced based on the size-luminosity relation of optical galaxies, and that the big grain dust temperature T dust is calculated based on a physical consideration for energy balance, rather than using the empirical relation between T dust and total infrared luminosity L IR found in local galaxies, which has been employed in most of previous works. Consequently, the local properties of infrared galaxies, i.e., optical/infrared luminosity ratios, L IR-T dust correlation, and infrared luminosity function are outputs predicted by the model, while these have been inputs in a number of previous models. Our model indeed reproduces these local properties reasonably well. Then we make predictions for faint infrared counts (in 15, 60, 90, 170, 450, and 850 μ m) and CBR by this model. We found considerably different results from most of previous works based on the empirical L IR-T dust relation; especially, it is shown that the dust temperature of starbursting primordial elliptical galaxies is expected to be very high (40--80K). This indicates that intense starbursts of forming elliptical galaxies should have occurred at z ~ 2--3, in contrast to the previous results that significant starbursts beyond z ~ 1 tend to overproduce the far-infrared (FIR) CBR detected by COBE/FIRAS. On the other hand, our model predicts that the mid-infrared (MIR) flux from warm/nonequilibrium dust is relatively weak in such galaxies making FIR CBR, and this effect reconciles the prima facie conflict between the upper limit on MIR CBR from TeV gamma-ray observations and the COBE\\ detections of FIR CBR. The authors thank the financial support by the Japan Society for Promotion of Science.

Prediction of cell penetrating peptides by support vector machines.

PubMed

Sanders, William S; Johnston, C Ian; Bridges, Susan M; Burgess, Shane C; Willeford, Kenneth O

2011-07-01

Cell penetrating peptides (CPPs) are those peptides that can transverse cell membranes to enter cells. Once inside the cell, different CPPs can localize to different cellular components and perform different roles. Some generate pore-forming complexes resulting in the destruction of cells while others localize to various organelles. Use of machine learning methods to predict potential new CPPs will enable more rapid screening for applications such as drug delivery. We have investigated the influence of the composition of training datasets on the ability to classify peptides as cell penetrating using support vector machines (SVMs). We identified 111 known CPPs and 34 known non-penetrating peptides from the literature and commercial vendors and used several approaches to build training data sets for the classifiers. Features were calculated from the datasets using a set of basic biochemical properties combined with features from the literature determined to be relevant in the prediction of CPPs. Our results using different training datasets confirm the importance of a balanced training set with approximately equal number of positive and negative examples. The SVM based classifiers have greater classification accuracy than previously reported methods for the prediction of CPPs, and because they use primary biochemical properties of the peptides as features, these classifiers provide insight into the properties needed for cell-penetration. To confirm our SVM classifications, a subset of peptides classified as either penetrating or non-penetrating was selected for synthesis and experimental validation. Of the synthesized peptides predicted to be CPPs, 100% of these peptides were shown to be penetrating.

Micromechanics of Composite Materials Governed by Vector Constitutive Laws

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Aboudi, Jacob; Arnold, Steven M.

2017-01-01

The high-fidelity generalized method of cells micromechanics theory has been extended for the prediction of the effective property tensor and the corresponding local field distributions for composites whose constituents are governed by vector constitutive laws. As shown, the shear analogy, which can predict effective transverse properties, is not valid in the general three-dimensional case. Consequently, a general derivation is presented that is applicable to both continuously and discontinuously reinforced composites with arbitrary vector constitutive laws and periodic microstructures. Results are given for thermal and electric problems, effective properties and local field distributions, ordered and random microstructures, as well as complex geometries including woven composites. Comparisons of the theory's predictions are made to test data, numerical analysis, and classical expressions from the literature. Further, classical methods cannot provide the local field distributions in the composite, and it is demonstrated that, as the percolation threshold is approached, their predictions are increasingly unreliable. XXXX It has been observed that the bonding between the fibers and matrix in composite materials can be imperfect. In the context of thermal conductivity, such imperfect interfaces have been investigated in micromechanical models by Dunn and Taya (1993), Duan and Karihaloo (2007), Nan et al. (1997) and Hashin (2001). The present HFGMC micromechanical method, derived for perfectly bonded composite materials governed by vector constitutive laws, can be easily generalized to include the effects of weak bonding between the constituents. Such generalizations, in the context of the mechanical micromechanics problem, involve introduction of a traction-separation law at the fiber/matrix interface and have been presented by Aboudi (1987), Bednarcyk and Arnold (2002), Bednarcyk et al. (2004) and Aboudi et al. (2013) and will be addressed in the future.

A new computational strategy for identifying essential proteins based on network topological properties and biological information.

PubMed

Qin, Chao; Sun, Yongqi; Dong, Yadong

2017-01-01

Essential proteins are the proteins that are indispensable to the survival and development of an organism. Deleting a single essential protein will cause lethality or infertility. Identifying and analysing essential proteins are key to understanding the molecular mechanisms of living cells. There are two types of methods for predicting essential proteins: experimental methods, which require considerable time and resources, and computational methods, which overcome the shortcomings of experimental methods. However, the prediction accuracy of computational methods for essential proteins requires further improvement. In this paper, we propose a new computational strategy named CoTB for identifying essential proteins based on a combination of topological properties, subcellular localization information and orthologous protein information. First, we introduce several topological properties of the protein-protein interaction (PPI) network. Second, we propose new methods for measuring orthologous information and subcellular localization and a new computational strategy that uses a random forest prediction model to obtain a probability score for the proteins being essential. Finally, we conduct experiments on four different Saccharomyces cerevisiae datasets. The experimental results demonstrate that our strategy for identifying essential proteins outperforms traditional computational methods and the most recently developed method, SON. In particular, our strategy improves the prediction accuracy to 89, 78, 79, and 85 percent on the YDIP, YMIPS, YMBD and YHQ datasets at the top 100 level, respectively.

Significance of vapor phase chemical reactions on CVD rates predicted by chemically frozen and local thermochemical equilibrium boundary layer theories

NASA Technical Reports Server (NTRS)

Gokoglu, Suleyman A.

1988-01-01

This paper investigates the role played by vapor-phase chemical reactions on CVD rates by comparing the results of two extreme theories developed to predict CVD mass transport rates in the absence of interfacial kinetic barrier: one based on chemically frozen boundary layer and the other based on local thermochemical equilibrium. Both theories consider laminar convective-diffusion boundary layers at high Reynolds numbers and include thermal (Soret) diffusion and variable property effects. As an example, Na2SO4 deposition was studied. It was found that gas phase reactions have no important role on Na2SO4 deposition rates and on the predictions of the theories. The implications of the predictions of the two theories to other CVD systems are discussed.

DeepLoc: prediction of protein subcellular localization using deep learning.

PubMed

Almagro Armenteros, José Juan; Sønderby, Casper Kaae; Sønderby, Søren Kaae; Nielsen, Henrik; Winther, Ole

2017-11-01

The prediction of eukaryotic protein subcellular localization is a well-studied topic in bioinformatics due to its relevance in proteomics research. Many machine learning methods have been successfully applied in this task, but in most of them, predictions rely on annotation of homologues from knowledge databases. For novel proteins where no annotated homologues exist, and for predicting the effects of sequence variants, it is desirable to have methods for predicting protein properties from sequence information only. Here, we present a prediction algorithm using deep neural networks to predict protein subcellular localization relying only on sequence information. At its core, the prediction model uses a recurrent neural network that processes the entire protein sequence and an attention mechanism identifying protein regions important for the subcellular localization. The model was trained and tested on a protein dataset extracted from one of the latest UniProt releases, in which experimentally annotated proteins follow more stringent criteria than previously. We demonstrate that our model achieves a good accuracy (78% for 10 categories; 92% for membrane-bound or soluble), outperforming current state-of-the-art algorithms, including those relying on homology information. The method is available as a web server at http://www.cbs.dtu.dk/services/DeepLoc. Example code is available at https://github.com/JJAlmagro/subcellular_localization. The dataset is available at http://www.cbs.dtu.dk/services/DeepLoc/data.php. jjalma@dtu.dk. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Modeling and Testing of the Viscoelastic Properties of a Graphite Nanoplatelet/Epoxy Composite

NASA Technical Reports Server (NTRS)

Odegard, Gregory M.; Gates, Thomas S.

2005-01-01

In order to facilitate the interpretation of experimental data, a micromechanical modeling procedure is developed to predict the viscoelastic properties of a graphite nanoplatelet/epoxy composite as a function of volume fraction and nanoplatelet diameter. The predicted storage and loss moduli for the composite are compared to measured values from the same material using three test methods; Dynamical Mechanical Analysis, nanoindentation, and quasi-static tensile tests. In most cases, the model and experiments indicate that for increasing volume fractions of nanoplatelets, both the storage and loss moduli increase. Also, the results indicate that for nanoplatelet sizes above 15 microns, nanoindentation is capable of measuring properties of individual constituents of a composite system. Comparison of the predicted values to the measured data helps illustrate the relative similarities and differences between the bulk and local measurement techniques.

Predicting the structure of screw dislocations in nanoporous materials

NASA Astrophysics Data System (ADS)

Walker, Andrew M.; Slater, Ben; Gale, Julian D.; Wright, Kate

2004-10-01

Extended microscale crystal defects, including dislocations and stacking faults, can radically alter the properties of technologically important materials. Determining the atomic structure and the influence of defects on properties remains a major experimental and computational challenge. Using a newly developed simulation technique, the structure of the 1/2a <100> screw dislocation in nanoporous zeolite A has been modelled. The predicted channel structure has a spiral form that resembles a nanoscale corkscrew. Our findings suggest that the dislocation will enhance the transport of molecules from the surface to the interior of the crystal while retarding transport parallel to the surface. Crucially, the dislocation creates an activated, locally chiral environment that may have enantioselective applications. These predictions highlight the influence that microscale defects have on the properties of structurally complex materials, in addition to their pivotal role in crystal growth.

Physical properties of hydrate‐bearing sediments

USGS Publications Warehouse

Waite, William F.; Santamarina, J.C.; Cortes, D.D.; Dugan, Brandon; Espinoza, D.N.; Germaine, J.; Jang, J.; Jung, J.W.; Kneafsey, T.J.; Shin, H.; Soga, K.; Winters, William J.; Yun, T.S.

2009-01-01

Methane gas hydrates, crystalline inclusion compounds formed from methane and water, are found in marine continental margin and permafrost sediments worldwide. This article reviews the current understanding of phenomena involved in gas hydrate formation and the physical properties of hydrate‐bearing sediments. Formation phenomena include pore‐scale habit, solubility, spatial variability, and host sediment aggregate properties. Physical properties include thermal properties, permeability, electrical conductivity and permittivity, small‐strain elastic P and S wave velocities, shear strength, and volume changes resulting from hydrate dissociation. The magnitudes and interdependencies of these properties are critically important for predicting and quantifying macroscale responses of hydrate‐bearing sediments to changes in mechanical, thermal, or chemical boundary conditions. These predictions are vital for mitigating borehole, local, and regional slope stability hazards; optimizing recovery techniques for extracting methane from hydrate‐bearing sediments or sequestering carbon dioxide in gas hydrate; and evaluating the role of gas hydrate in the global carbon cycle.

Coolant-side heat-transfer rates for a hydrogen-oxygen rocket and a new technique for data correlation

NASA Technical Reports Server (NTRS)

Schacht, R. L.; Quentmeyer, R. J.

1973-01-01

An experimental investigation was conducted to determine the coolant-side, heat transfer coefficients for a liquid cooled, hydrogen-oxygen rocket thrust chamber. Heat transfer rates were determined from measurements of local hot gas wall temperature, local coolant temperature, and local coolant pressure. A correlation incorporating an integration technique for the transport properties needed near the pseudocritical temperature of liquid hydrogen gives a satisfactory prediction of hot gas wall temperatures.

Physiologically Based Pharmacokinetic Modeling in Lead Optimization. 1. Evaluation and Adaptation of GastroPlus To Predict Bioavailability of Medchem Series.

PubMed

Daga, Pankaj R; Bolger, Michael B; Haworth, Ian S; Clark, Robert D; Martin, Eric J

2018-03-05

When medicinal chemists need to improve bioavailability (%F) within a chemical series during lead optimization, they synthesize new series members with systematically modified properties mainly by following experience and general rules of thumb. More quantitative models that predict %F of proposed compounds from chemical structure alone have proven elusive. Global empirical %F quantitative structure-property (QSPR) models perform poorly, and projects have too little data to train local %F QSPR models. Mechanistic oral absorption and physiologically based pharmacokinetic (PBPK) models simulate the dissolution, absorption, systemic distribution, and clearance of a drug in preclinical species and humans. Attempts to build global PBPK models based purely on calculated inputs have not achieved the <2-fold average error needed to guide lead optimization. In this work, local GastroPlus PBPK models are instead customized for individual medchem series. The key innovation was building a local QSPR for a numerically fitted effective intrinsic clearance (CL loc ). All inputs are subsequently computed from structure alone, so the models can be applied in advance of synthesis. Training CL loc on the first 15-18 rat %F measurements gave adequate predictions, with clear improvements up to about 30 measurements, and incremental improvements beyond that.

Micro Finite Element models of the vertebral body: Validation of local displacement predictions.

PubMed

Costa, Maria Cristiana; Tozzi, Gianluca; Cristofolini, Luca; Danesi, Valentina; Viceconti, Marco; Dall'Ara, Enrico

2017-01-01

The estimation of local and structural mechanical properties of bones with micro Finite Element (microFE) models based on Micro Computed Tomography images depends on the quality bone geometry is captured, reconstructed and modelled. The aim of this study was to validate microFE models predictions of local displacements for vertebral bodies and to evaluate the effect of the elastic tissue modulus on model's predictions of axial forces. Four porcine thoracic vertebrae were axially compressed in situ, in a step-wise fashion and scanned at approximately 39μm resolution in preloaded and loaded conditions. A global digital volume correlation (DVC) approach was used to compute the full-field displacements. Homogeneous, isotropic and linear elastic microFE models were generated with boundary conditions assigned from the interpolated displacement field measured from the DVC. Measured and predicted local displacements were compared for the cortical and trabecular compartments in the middle of the specimens. Models were run with two different tissue moduli defined from microindentation data (12.0GPa) and a back-calculation procedure (4.6GPa). The predicted sum of axial reaction forces was compared to the experimental values for each specimen. MicroFE models predicted more than 87% of the variation in the displacement measurements (R2 = 0.87-0.99). However, model predictions of axial forces were largely overestimated (80-369%) for a tissue modulus of 12.0GPa, whereas differences in the range 10-80% were found for a back-calculated tissue modulus. The specimen with the lowest density showed a large number of elements strained beyond yield and the highest predictive errors. This study shows that the simplest microFE models can accurately predict quantitatively the local displacements and qualitatively the strain distribution within the vertebral body, independently from the considered bone types.

A critical examination of the validity of simplified models for radiant heat transfer analysis.

NASA Technical Reports Server (NTRS)

Toor, J. S.; Viskanta, R.

1972-01-01

Examination of the directional effects of the simplified models by comparing the experimental data with the predictions based on simple and more detailed models for the radiation characteristics of surfaces. Analytical results indicate that the constant property diffuse and specular models do not yield the upper and lower bounds on local radiant heat flux. In general, the constant property specular analysis yields higher values of irradiation than the constant property diffuse analysis. A diffuse surface in the enclosure appears to destroy the effect of specularity of the other surfaces. Semigray and gray analyses predict the irradiation reasonably well provided that the directional properties and the specularity of the surfaces are taken into account. The uniform and nonuniform radiosity diffuse models are in satisfactory agreement with each other.

Evaluating the utility of mid-infrared spectral subspaces for predicting soil properties.

PubMed

Sila, Andrew M; Shepherd, Keith D; Pokhariyal, Ganesh P

2016-04-15

We propose four methods for finding local subspaces in large spectral libraries. The proposed four methods include (a) cosine angle spectral matching; (b) hit quality index spectral matching; (c) self-organizing maps and (d) archetypal analysis methods. Then evaluate prediction accuracies for global and subspaces calibration models. These methods were tested on a mid-infrared spectral library containing 1907 soil samples collected from 19 different countries under the Africa Soil Information Service project. Calibration models for pH, Mehlich-3 Ca, Mehlich-3 Al, total carbon and clay soil properties were developed for the whole library and for the subspace. Root mean square error of prediction was used to evaluate predictive performance of subspace and global models. The root mean square error of prediction was computed using a one-third-holdout validation set. Effect of pretreating spectra with different methods was tested for 1st and 2nd derivative Savitzky-Golay algorithm, multiplicative scatter correction, standard normal variate and standard normal variate followed by detrending methods. In summary, the results show that global models outperformed the subspace models. We, therefore, conclude that global models are more accurate than the local models except in few cases. For instance, sand and clay root mean square error values from local models from archetypal analysis method were 50% poorer than the global models except for subspace models obtained using multiplicative scatter corrected spectra with which were 12% better. However, the subspace approach provides novel methods for discovering data pattern that may exist in large spectral libraries.

Magnetism and local symmetry breaking in a Mott insulator with strong spin orbit interactions

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

Lu, L.; Song, M.; Liu, W.

2017-02-09

Study of the combined effects of strong electronic correlations with spin-orbit coupling (SOC) represents a central issue in quantum materials research. Predicting emergent properties represents a huge theoretical problem since the presence of SOC implies that the spin is not a good quantum number. Existing theories propose the emergence of a multitude of exotic quantum phases, distinguishable by either local point symmetry breaking or local spin expectation values, even in materials with simple cubic crystal structure such as Ba 2NaOsO 6. Experimental tests of these theories by local probes are highly sought for. Our local measurements designed to concurrently probemore » spin and orbital/lattice degrees of freedom of Ba 2NaOsO 6 provide such tests. As a result, we show that a canted ferromagnetic phase which is preceded by local point symmetry breaking is stabilized at low temperatures, as predicted by quantum theories involving multipolar spin interactions.« less

Local-global analysis of crack growth in continuously reinfoced ceramic matrix composites

NASA Technical Reports Server (NTRS)

Ballarini, Roberto; Ahmed, Shamim

1989-01-01

This paper describes the development of a mathematical model for predicting the strength and micromechanical failure characteristics of continuously reinforced ceramic matrix composites. The local-global analysis models the vicinity of a propagating crack tip as a local heterogeneous region (LHR) consisting of spring-like representation of the matrix, fibers and interfaces. Parametric studies are conducted to investigate the effects of LHR size, component properties, and interface conditions on the strength and sequence of the failure processes in the unidirectional composite system.

Plasticity and Kinky Chemistry of Carbon Nanotubes

NASA Technical Reports Server (NTRS)

Srivastava, Deepak; Dzegilenko, Fedor

2000-01-01

Since their discovery in 1991, carbon nanotubes have been the subject of intense research interest based on early predictions of their unique mechanical, electronic, and chemical properties. Materials with the predicted unique properties of carbon nanotubes are of great interest for use in future generations of aerospace vehicles. For their structural properties, carbon nanotubes could be used as reinforcing fibers in ultralight multifunctional composites. For their electronic properties, carbon nanotubes offer the potential of very high-speed, low-power computing elements, high-density data storage, and unique sensors. In a continuing effort to model and predict the properties of carbon nanotubes, Ames accomplished three significant results during FY99. First, accurate values of the nanomechanics and plasticity of carbon nanotubes based on quantum molecular dynamics simulations were computed. Second, the concept of mechanical deformation catalyzed-kinky-chemistry as a means to control local chemistry of nanotubes was discovered. Third, the ease of nano-indentation of silicon surfaces with carbon nanotubes was established. The elastic response and plastic failure mechanisms of single-wall nanotubes were investigated by means of quantum molecular dynamics simulations.

Development of procedures for calculating stiffness and damping properties of elastomers. Part 3: The effects of temperature, dissipation level and geometry

NASA Technical Reports Server (NTRS)

Smalley, A. J.; Tessarzik, J. M.

1975-01-01

Effects of temperature, dissipation level and geometry on the dynamic behavior of elastomer elements were investigated. Force displacement relationships in elastomer elements and the effects of frequency, geometry and temperature upon these relationships are reviewed. Based on this review, methods of reducing stiffness and damping data for shear and compression test elements to material properties (storage and loss moduli) and empirical geometric factors are developed and tested using previously generated experimental data. A prediction method which accounts for large amplitudes of deformation is developed on the assumption that their effect is to increase temperature through the elastomers, thereby modifying the local material properties. Various simple methods of predicting the radial stiffness of ring cartridge elements are developed and compared. Material properties were determined from the shear specimen tests as a function of frequency and temperature. Using these material properties, numerical predictions of stiffness and damping for cartridge and compression specimens were made and compared with corresponding measurements at different temperatures, with encouraging results.

Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties

NASA Astrophysics Data System (ADS)

Xie, Tian; Grossman, Jeffrey C.

2018-04-01

The use of machine learning methods for accelerating the design of crystalline materials usually requires manually constructed feature vectors or complex transformation of atom coordinates to input the crystal structure, which either constrains the model to certain crystal types or makes it difficult to provide chemical insights. Here, we develop a crystal graph convolutional neural networks framework to directly learn material properties from the connection of atoms in the crystal, providing a universal and interpretable representation of crystalline materials. Our method provides a highly accurate prediction of density functional theory calculated properties for eight different properties of crystals with various structure types and compositions after being trained with 1 04 data points. Further, our framework is interpretable because one can extract the contributions from local chemical environments to global properties. Using an example of perovskites, we show how this information can be utilized to discover empirical rules for materials design.

New approach to predict photoallergic potentials of chemicals based on murine local lymph node assay.

PubMed

Maeda, Yosuke; Hirosaki, Haruka; Yamanaka, Hidenori; Takeyoshi, Masahiro

2018-05-23

Photoallergic dermatitis, caused by pharmaceuticals and other consumer products, is a very important issue in human health. However, S10 guidelines of the International Conference on Harmonization do not recommend the existing prediction methods for photoallergy because of their low predictability in human cases. We applied local lymph node assay (LLNA), a reliable, quantitative skin sensitization prediction test, to develop a new photoallergy prediction method. This method involves a three-step approach: (1) ultraviolet (UV) absorption analysis; (2) determination of no observed adverse effect level for skin phototoxicity based on LLNA; and (3) photoallergy evaluation based on LLNA. Photoallergic potential of chemicals was evaluated by comparing lymph node cell proliferation among groups treated with chemicals with minimal effect levels of skin sensitization and skin phototoxicity under UV irradiation (UV+) or non-UV irradiation (UV-). A case showing significant difference (P < .05) in lymph node cell proliferation rates between UV- and UV+ groups was considered positive for photoallergic reaction. After testing 13 chemicals, seven human photoallergens tested positive and the other six, with no evidence of causing photoallergic dermatitis or UV absorption, tested negative. Among these chemicals, both doxycycline hydrochloride and minocycline hydrochloride were tetracycline antibiotics with different photoallergic properties, and the new method clearly distinguished between the photoallergic properties of these chemicals. These findings suggested high predictability of our method; therefore, it is promising and effective in predicting human photoallergens. Copyright © 2018 John Wiley & Sons, Ltd.

Capturing non-local interactions by long short-term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone angles, contact numbers and solvent accessibility.

PubMed

Heffernan, Rhys; Yang, Yuedong; Paliwal, Kuldip; Zhou, Yaoqi

2017-09-15

The accuracy of predicting protein local and global structural properties such as secondary structure and solvent accessible surface area has been stagnant for many years because of the challenge of accounting for non-local interactions between amino acid residues that are close in three-dimensional structural space but far from each other in their sequence positions. All existing machine-learning techniques relied on a sliding window of 10-20 amino acid residues to capture some 'short to intermediate' non-local interactions. Here, we employed Long Short-Term Memory (LSTM) Bidirectional Recurrent Neural Networks (BRNNs) which are capable of capturing long range interactions without using a window. We showed that the application of LSTM-BRNN to the prediction of protein structural properties makes the most significant improvement for residues with the most long-range contacts (|i-j| >19) over a previous window-based, deep-learning method SPIDER2. Capturing long-range interactions allows the accuracy of three-state secondary structure prediction to reach 84% and the correlation coefficient between predicted and actual solvent accessible surface areas to reach 0.80, plus a reduction of 5%, 10%, 5% and 10% in the mean absolute error for backbone ϕ , ψ , θ and τ angles, respectively, from SPIDER2. More significantly, 27% of 182724 40-residue models directly constructed from predicted C α atom-based θ and τ have similar structures to their corresponding native structures (6Å RMSD or less), which is 3% better than models built by ϕ and ψ angles. We expect the method to be useful for assisting protein structure and function prediction. The method is available as a SPIDER3 server and standalone package at http://sparks-lab.org . yaoqi.zhou@griffith.edu.au or yuedong.yang@griffith.edu.au. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Route Prediction on Tracking Data to Location-Based Services

NASA Astrophysics Data System (ADS)

Petróczi, Attila István; Gáspár-Papanek, Csaba

Wireless networks have become so widespread, it is beneficial to determine the ability of cellular networks for localization. This property enables the development of location-based services, providing useful information. These services can be improved by route prediction under the condition of using simple algorithms, because of the limited capabilities of mobile stations. This study gives alternative solutions for this problem of route prediction based on a specific graph model. Our models provide the opportunity to reach our destinations with less effort.

The Evolution of the Cluster X-ray Scaling Relations in the Wide Angle ROSAT Pointed Survey Sample at 0.6 < z < 1.0

NASA Technical Reports Server (NTRS)

Maughan, B. J.; Jones, L. R.; Ebeling, H.; Scharf, C.

2006-01-01

The X-ray properties of a sample of 11 high-redshift (0.6 < z < 1 .O) clusters observed with Chardm and/or XMM-Newton are used to investigate the evolution of the cluster scaling relations. The observed evolution in the normalization of the L-T, M-T, M(sub 2)-T and M-L relations is consistent with simple self-similar predictions, in which the properties of clusters reflect the properties of the Universe at their redshift of observation. Under the assumption that the model of self-similar evolution is correct and that the local systems formed via a single spherical collapse, the high-redshift L-T relation is consistent with the high-z clusters having virialized at a significantly higher redshift than the local systems. The data are also consistent with the more realistic scenario of clusters forming via the continuous accretion of material. The slope of the L-T relation at high redshift (B = 3.32 +/- 0.37) is consistent with the local relation, and significantly steeper than the self-similar prediction of B = 2. This suggests that the same non-gravitational processes are responsible for steepening the local and high-z relations, possibly occurring universally at z is approximately greater than 1 or in the early stages of the cluster formation, prior to their observation. The properties of the intracluster medium at high redshift are found to be similar to those in the local Universe. The mean surface-brightness profile slope for the sample is Beta = 0.66 +/- 0.05, the mean gas mass fractions within R(sub 2500(z)) and R(200(z)) are 0.069 +/- 0.012 and 0.11 +/- 0.02, respectively, and the mean metallicity of the sample is 0.28 +/- 0.11 Z(sub solar).

Utterance rate and linguistic properties as determinants of lexical dysfluencies in children who stutter

PubMed Central

Howell, Peter; Au-Yeung, James; Pilgrim, Lesley

2007-01-01

Two important determinants of variation in stuttering frequency are utterance rate and the linguistic properties of the words being spoken. Little is known how these determinants interrelate. It is hypothesized that those linguistic factors that lead to change in word duration, alter utterance rate locally within an utterance that then gives rise to an increase in stuttering frequency. According to the hypothesis, utterance rate variation should occur locally within the linguistic segments in an utterance that is known to increase the likelihood of stuttering. The hypothesis is tested using length of tone unit as the linguistic factor. Three predictions are confirmed: Utterance rate varies locally within the tone units and this local variation affects stuttering frequency; stuttering frequency is positively related to the length of tone units; variations in utterance rate are correlated with tone unit length. Alternative theoretical formulations of these findings are considered. PMID:9921672

Auxiliary field diffusion Monte Carlo calculations of light and medium-mass nuclei with local chiral interactions

NASA Astrophysics Data System (ADS)

Lonardoni, D.; Gandolfi, S.; Lynn, J. E.; Petrie, C.; Carlson, J.; Schmidt, K. E.; Schwenk, A.

2018-04-01

Quantum Monte Carlo methods have recently been employed to study properties of nuclei and infinite matter using local chiral effective-field-theory interactions. In this work, we present a detailed description of the auxiliary field diffusion Monte Carlo algorithm for nuclei in combination with local chiral two- and three-nucleon interactions up to next-to-next-to-leading order. We show results for the binding energy, charge radius, charge form factor, and Coulomb sum rule in nuclei with 3 ≤A ≤16 . Particular attention is devoted to the effect of different operator structures in the three-body force for different cutoffs. The outcomes suggest that local chiral interactions fit to few-body observables give a very good description of the ground-state properties of nuclei up to 16O, with the exception of one fit for the softer cutoff which predicts overbinding in larger nuclei.

The Effect of General Statistical Fiber Misalignment on Predicted Damage Initiation in Composites

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Aboudi, Jacob; Arnold, Steven M.

2014-01-01

A micromechanical method is employed for the prediction of unidirectional composites in which the fiber orientation can possess various statistical misalignment distributions. The method relies on the probability-weighted averaging of the appropriate concentration tensor, which is established by the micromechanical procedure. This approach provides access to the local field quantities throughout the constituents, from which initiation of damage in the composite can be predicted. In contrast, a typical macromechanical procedure can determine the effective composite elastic properties in the presence of statistical fiber misalignment, but cannot provide the local fields. Fully random fiber distribution is presented as a special case using the proposed micromechanical method. Results are given that illustrate the effects of various amounts of fiber misalignment in terms of the standard deviations of in-plane and out-of-plane misalignment angles, where normal distributions have been employed. Damage initiation envelopes, local fields, effective moduli, and strengths are predicted for polymer and ceramic matrix composites with given normal distributions of misalignment angles, as well as fully random fiber orientation.

Numerical simulation of hypersonic inlet flows with equilibrium or finite rate chemistry

NASA Technical Reports Server (NTRS)

Yu, Sheng-Tao; Hsieh, Kwang-Chung; Shuen, Jian-Shun; Mcbride, Bonnie J.

1988-01-01

An efficient numerical program incorporated with comprehensive high temperature gas property models has been developed to simulate hypersonic inlet flows. The computer program employs an implicit lower-upper time marching scheme to solve the two-dimensional Navier-Stokes equations with variable thermodynamic and transport properties. Both finite-rate and local-equilibrium approaches are adopted in the chemical reaction model for dissociation and ionization of the inlet air. In the finite rate approach, eleven species equations coupled with fluid dynamic equations are solved simultaneously. In the local-equilibrium approach, instead of solving species equations, an efficient chemical equilibrium package has been developed and incorporated into the flow code to obtain chemical compositions directly. Gas properties for the reaction products species are calculated by methods of statistical mechanics and fit to a polynomial form for C(p). In the present study, since the chemical reaction time is comparable to the flow residence time, the local-equilibrium model underpredicts the temperature in the shock layer. Significant differences of predicted chemical compositions in shock layer between finite rate and local-equilibrium approaches have been observed.

Mathematical modeling and experimental validation of the spatial distribution of boron in the root of Arabidopsis thaliana identify high boron accumulation in the tip and predict a distinct root tip uptake function.

PubMed

Shimotohno, Akie; Sotta, Naoyuki; Sato, Takafumi; De Ruvo, Micol; Marée, Athanasius F M; Grieneisen, Verônica A; Fujiwara, Toru

2015-04-01

Boron, an essential micronutrient, is transported in roots of Arabidopsis thaliana mainly by two different types of transporters, BORs and NIPs (nodulin26-like intrinsic proteins). Both are plasma membrane localized, but have distinct transport properties and patterns of cell type-specific accumulation with different polar localizations, which are likely to affect boron distribution. Here, we used mathematical modeling and an experimental determination to address boron distributions in the root. A computational model of the root is created at the cellular level, describing the boron transporters as observed experimentally. Boron is allowed to diffuse into roots, in cells and cell walls, and to be transported over plasma membranes, reflecting the properties of the different transporters. The model predicts that a region around the quiescent center has a higher concentration of soluble boron than other portions. To evaluate this prediction experimentally, we determined the boron distribution in roots using laser ablation-inductivity coupled plasma-mass spectrometry. The analysis indicated that the boron concentration is highest near the tip and is lower in the more proximal region of the meristem zone, similar to the pattern of soluble boron distribution predicted by the model. Our model also predicts that upward boron flux does not continuously increase from the root tip toward the mature region, indicating that boron taken up in the root tip is not efficiently transported to shoots. This suggests that root tip-absorbed boron is probably used for local root growth, and that instead it is the more mature root regions which have a greater role in transporting boron toward the shoots. © The Author 2015. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.

Mathematical Modeling and Experimental Validation of the Spatial Distribution of Boron in the Root of Arabidopsis thaliana Identify High Boron Accumulation in the Tip and Predict a Distinct Root Tip Uptake Function

PubMed Central

Shimotohno, Akie; Sotta, Naoyuki; Sato, Takafumi; De Ruvo, Micol; Marée, Athanasius F.M.; Grieneisen, Verônica A.; Fujiwara, Toru

2015-01-01

Boron, an essential micronutrient, is transported in roots of Arabidopsis thaliana mainly by two different types of transporters, BORs and NIPs (nodulin26-like intrinsic proteins). Both are plasma membrane localized, but have distinct transport properties and patterns of cell type-specific accumulation with different polar localizations, which are likely to affect boron distribution. Here, we used mathematical modeling and an experimental determination to address boron distributions in the root. A computational model of the root is created at the cellular level, describing the boron transporters as observed experimentally. Boron is allowed to diffuse into roots, in cells and cell walls, and to be transported over plasma membranes, reflecting the properties of the different transporters. The model predicts that a region around the quiescent center has a higher concentration of soluble boron than other portions. To evaluate this prediction experimentally, we determined the boron distribution in roots using laser ablation-inductivity coupled plasma-mass spectrometry. The analysis indicated that the boron concentration is highest near the tip and is lower in the more proximal region of the meristem zone, similar to the pattern of soluble boron distribution predicted by the model. Our model also predicts that upward boron flux does not continuously increase from the root tip toward the mature region, indicating that boron taken up in the root tip is not efficiently transported to shoots. This suggests that root tip-absorbed boron is probably used for local root growth, and that instead it is the more mature root regions which have a greater role in transporting boron toward the shoots. PMID:25670713

Quantitative prediction of radio frequency induced local heating derived from measured magnetic field maps in magnetic resonance imaging: A phantom validation at 7 T

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

Zhang, Xiaotong; Liu, Jiaen; Van de Moortele, Pierre-Francois

2014-12-15

Electrical Properties Tomography (EPT) technique utilizes measurable radio frequency (RF) coil induced magnetic fields (B1 fields) in a Magnetic Resonance Imaging (MRI) system to quantitatively reconstruct the local electrical properties (EP) of biological tissues. Information derived from the same data set, e.g., complex numbers of B1 distribution towards electric field calculation, can be used to estimate, on a subject-specific basis, local Specific Absorption Rate (SAR). SAR plays a significant role in RF pulse design for high-field MRI applications, where maximum local tissue heating remains one of the most constraining limits. The purpose of the present work is to investigate themore » feasibility of such B1-based local SAR estimation, expanding on previously proposed EPT approaches. To this end, B1 calibration was obtained in a gelatin phantom at 7 T with a multi-channel transmit coil, under a particular multi-channel B1-shim setting (B1-shim I). Using this unique set of B1 calibration, local SAR distribution was subsequently predicted for B1-shim I, as well as for another B1-shim setting (B1-shim II), considering a specific set of parameter for a heating MRI protocol consisting of RF pulses plaid at 1% duty cycle. Local SAR results, which could not be directly measured with MRI, were subsequently converted into temperature change which in turn were validated against temperature changes measured by MRI Thermometry based on the proton chemical shift.« less

Predicting residue-wise contact orders in proteins by support vector regression.

PubMed

Song, Jiangning; Burrage, Kevin

2006-10-03

The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Energy Absorption of Expansion Tube Considering Local Buckling Characteristics

NASA Astrophysics Data System (ADS)

Ahn, Kwang-Hyun; Kim, Jin-Sung; Huh, Hoon

This paper deals with the crash energy absorption and the local buckling characteristics of the expansion tube during the tube expanding processes. In order to improve energy absorption capacity of expansion tubes, local buckling characteristics of an expansion tube must be considered. The local buckling load and the absorbed energy during the expanding process were calculated for various types of tubes and punch shapes with finite element analysis. The energy absorption capacity of the expansion tube is influenced by the tube and the punch shape. The material properties of tubes are also important parameter for energy absorption. During the expanding process, local buckling occurs in some cases, which causes significant decreasing the absorbed energy of the expansion tube. Therefore, it is important to predict the local buckling load accurately to improve the energy absorption capacity of the expansion tube. Local buckling takes place relatively easily at the large punch angle and expansion ratio. Local buckling load is also influenced by both the tube radius and the thickness. In prediction of the local buckling load, modified Plantema equation was used for strain hardening and strain rate hardening. The modified Plantema equation shows a good agreement with the numerical result.

Local functional descriptors for surface comparison based binding prediction

PubMed Central

2012-01-01

Background Molecular recognition in proteins occurs due to appropriate arrangements of physical, chemical, and geometric properties of an atomic surface. Similar surface regions should create similar binding interfaces. Effective methods for comparing surface regions can be used in identifying similar regions, and to predict interactions without regard to the underlying structural scaffold that creates the surface. Results We present a new descriptor for protein functional surfaces and algorithms for using these descriptors to compare protein surface regions to identify ligand binding interfaces. Our approach uses descriptors of local regions of the surface, and assembles collections of matches to compare larger regions. Our approach uses a variety of physical, chemical, and geometric properties, adaptively weighting these properties as appropriate for different regions of the interface. Our approach builds a classifier based on a training corpus of examples of binding sites of the target ligand. The constructed classifiers can be applied to a query protein providing a probability for each position on the protein that the position is part of a binding interface. We demonstrate the effectiveness of the approach on a number of benchmarks, demonstrating performance that is comparable to the state-of-the-art, with an approach with more generality than these prior methods. Conclusions Local functional descriptors offer a new method for protein surface comparison that is sufficiently flexible to serve in a variety of applications. PMID:23176080

Performance of local correlation methods for halogen bonding: The case of Br{sub 2}–(H{sub 2}O){sub n},n = 4,5 clusters and Br{sub 2}@5{sup 12}6{sup 2} clathrate cage

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

Batista-Romero, Fidel A.; Bernal-Uruchurtu, Margarita I.; Hernández-Lamoneda, Ramón, E-mail: ramon@uaem.mx

The performance of local correlation methods is examined for the interactions present in clusters of bromine with water where the combined effect of hydrogen bonding (HB), halogen bonding (XB), and hydrogen-halogen (HX) interactions lead to many interesting properties. Local methods reproduce all the subtleties involved such as many-body effects and dispersion contributions provided that specific methodological steps are followed. Additionally, they predict optimized geometries that are nearly free of basis set superposition error that lead to improved estimates of spectroscopic properties. Taking advantage of the local correlation energy partitioning scheme, we compare the different interaction environments present in small clustersmore » and those inside the 5{sup 12}6{sup 2} clathrate cage. This analysis allows a clear identification of the reasons supporting the use of local methods for large systems where non-covalent interactions play a key role.« less

Analytical and Experimental Characterization of Thick-Section Fiber-Metal Laminates

DTIC Science & Technology

2013-06-01

individual metal layers as loading increases. The off-axis deformation properties of the prepreg layers were modeled by using equivalent constraint models...the degraded stiffness of the prepreg layer is found. At each loading step the stiffness properties of individual layers are calculated. These...predicts stress-strain curves on-axis, additional work is needed to study the local interactions between metal and prepreg layers as damage occurs in each

Predicting structural classes of proteins by incorporating their global and local physicochemical and conformational properties into general Chou's PseAAC.

PubMed

Contreras-Torres, Ernesto

2018-06-02

In this study, I introduce novel global and local 0D-protein descriptors based on a statistical quantity named Total Sum of Squares (TSS). This quantity represents the sum of the squares differences of amino acid properties from the arithmetic mean property. As an extension, the amino acid-types and amino acid-groups formalisms are used for describing zones of interest in proteins. To assess the effectiveness of the proposed descriptors, a Nearest Neighbor model for predicting the major four protein structural classes was built. This model has a success rate of 98.53% on the jackknife cross-validation test; this performance being superior to other reported methods despite the simplicity of the predictor. Additionally, this predictor has an average success rate of 98.35% in different cross-validation tests performed. A value of 0.98 for the Kappa statistic clearly discriminates this model from a random predictor. The results obtained by the Nearest Neighbor model demonstrated the ability of the proposed descriptors not only to reflect relevant biochemical information related to the structural classes of proteins but also to allow appropriate interpretability. It can thus be expected that the current method may play a supplementary role to other existing approaches for protein structural class prediction and other protein attributes. Copyright © 2018 Elsevier Ltd. All rights reserved.

A density distribution algorithm for bone incorporating local orthotropy, modal analysis and theories of cellular solids.

PubMed

Impelluso, Thomas J

2003-06-01

An algorithm for bone remodeling is presented which allows for both a redistribution of density and a continuous change of principal material directions for the orthotropic material properties of bone. It employs a modal analysis to add density for growth and a local effective strain based analysis to redistribute density. General re-distribution functions are presented. The model utilizes theories of cellular solids to relate density and strength. The code predicts the same general density distributions and local orthotropy as observed in reality.

Electronic structure Fermi liquid theory of high Tc superconductors: Comparison of predictions with experiments

NASA Technical Reports Server (NTRS)

Yu, Jaejun; Freeman, A. J.

1991-01-01

Predictions of local density functional (LDF) calculations of the electronic structure and transport properties of high T(sub c) superconductors are presented. As evidenced by the excellent agreement with both photoemission and positron annihilation experiments, a Fermi liquid nature of the 'normal' state of the high T(sub c) superconductors become clear for the metallic phase of these oxides. In addition, LDF predictions on the normal state transport properties are qualitatively in agreement with experiments on single crystals. It is emphasized that the signs of the Hall coefficients for the high T(sub c) superconductors are not consistent with the types of dopants (e.g., electron-doped or hole-doped) but are determined by the topology of the Fermi surfaces obtained from the LDF calculations.

Molecular properties of the N-terminal extension of the fission yeast kinesin-5, Cut7.

PubMed

Edamatsu, M

2016-02-11

Kinesin-5 plays an essential role in spindle formation and function, and serves as a potential target for anti-cancer drugs. The aim of this study was to elucidate the molecular properties of the N-terminal extension of the Schizosaccharomyces pombe kinesin-5, Cut7. This extension is rich in charged amino acids and predicted to be intrinsically disordered. In S. pombe cells, a Cut7 construct lacking half the N-terminal extension failed to localize along the spindle microtubules and formed a monopolar spindle. However, a construct lacking the entire N-terminal extension exhibited normal localization and formed a typical bipolar spindle. In addition, in vitro analyses revealed that the truncated Cut7 constructs demonstrated similar motile velocities and directionalities as the wild-type motor protein, but the microtubule landing rates were significantly reduced. These findings suggest that the N-terminal extension is not required for normal Cut7 intracellular localization or function, but alters the microtubule-binding properties of this protein in vitro.

Modeling of Melt-Infiltrated SiC/SiC Composite Properties

NASA Technical Reports Server (NTRS)

Mital, Subodh K.; Bednarcyk, Brett A.; Arnold, Steven M.; Lang, Jerry

2009-01-01

The elastic properties of a two-dimensional five-harness melt-infiltrated silicon carbide fiber reinforced silicon carbide matrix (MI SiC/SiC) ceramic matrix composite (CMC) were predicted using several methods. Methods used in this analysis are multiscale laminate analysis, micromechanics-based woven composite analysis, a hybrid woven composite analysis, and two- and three-dimensional finite element analyses. The elastic properties predicted are in good agreement with each other as well as with the available measured data. However, the various methods differ from each other in three key areas: (1) the fidelity provided, (2) the efforts required for input data preparation, and (3) the computational resources required. Results also indicate that efficient methods are also able to provide a reasonable estimate of local stress fields.

Micro Finite Element models of the vertebral body: Validation of local displacement predictions

PubMed Central

Costa, Maria Cristiana; Tozzi, Gianluca; Cristofolini, Luca; Danesi, Valentina; Viceconti, Marco

2017-01-01

The estimation of local and structural mechanical properties of bones with micro Finite Element (microFE) models based on Micro Computed Tomography images depends on the quality bone geometry is captured, reconstructed and modelled. The aim of this study was to validate microFE models predictions of local displacements for vertebral bodies and to evaluate the effect of the elastic tissue modulus on model’s predictions of axial forces. Four porcine thoracic vertebrae were axially compressed in situ, in a step-wise fashion and scanned at approximately 39μm resolution in preloaded and loaded conditions. A global digital volume correlation (DVC) approach was used to compute the full-field displacements. Homogeneous, isotropic and linear elastic microFE models were generated with boundary conditions assigned from the interpolated displacement field measured from the DVC. Measured and predicted local displacements were compared for the cortical and trabecular compartments in the middle of the specimens. Models were run with two different tissue moduli defined from microindentation data (12.0GPa) and a back-calculation procedure (4.6GPa). The predicted sum of axial reaction forces was compared to the experimental values for each specimen. MicroFE models predicted more than 87% of the variation in the displacement measurements (R2 = 0.87–0.99). However, model predictions of axial forces were largely overestimated (80–369%) for a tissue modulus of 12.0GPa, whereas differences in the range 10–80% were found for a back-calculated tissue modulus. The specimen with the lowest density showed a large number of elements strained beyond yield and the highest predictive errors. This study shows that the simplest microFE models can accurately predict quantitatively the local displacements and qualitatively the strain distribution within the vertebral body, independently from the considered bone types. PMID:28700618

Universal structural parameter to quantitatively predict metallic glass properties

DOE PAGES

Ding, Jun; Cheng, Yong-Qiang; Sheng, Howard; ...

2016-12-12

Quantitatively correlating the amorphous structure in metallic glasses (MGs) with their physical properties has been a long-sought goal. Here we introduce flexibility volume' as a universal indicator, to bridge the structural state the MG is in with its properties, on both atomic and macroscopic levels. The flexibility volume combines static atomic volume with dynamics information via atomic vibrations that probe local configurational space and interaction between neighbouring atoms. We demonstrate that flexibility volume is a physically appropriate parameter that can quantitatively predict the shear modulus, which is at the heart of many key properties of MGs. Moreover, the new parametermore » correlates strongly with atomic packing topology, and also with the activation energy for thermally activated relaxation and the propensity for stress-driven shear transformations. These correlations are expected to be robust across a very wide range of MG compositions, processing conditions and length scales.« less

New developments in tribomechanical modeling of automotive sheet steel forming

NASA Astrophysics Data System (ADS)

Khandeparkar, Tushar; Chezan, Toni; van Beeck, Jeroen

2018-05-01

Forming of automotive sheet metal body panels is a complex process influenced by both the material properties and contact conditions in the forming tooling. Material properties are described by the material constitutive behavior and the material flow into the forming die can be described by the tribological system. This paper investigates the prediction accuracy of the forming process using the Tata Steel state of the art description of the material constitutive behavior in combination with different friction models. A cross-die experiment is used to investigate the accuracy of local deformation modes typically seen in automotive sheet metal forming operations. Results of advanced friction models as well as the classical Coulomb friction description are compared to the experimentally measured strain distribution and material draw-in. Two hot-dip galvanized coated steel forming grades were used for the investigations. The results show that the accuracy of the simulation is not guaranteed by the advanced friction models for the entire investigated blank holder force range, both globally and locally. A measurable difference between the calculated and measured local strains is seen for both studied models even in the case where the global indicator, i.e. the draw-in, is well predicted.

Specific excitatory connectivity for feature integration in mouse primary visual cortex

PubMed Central

Molina-Luna, Patricia; Roth, Morgane M.

2017-01-01

Local excitatory connections in mouse primary visual cortex (V1) are stronger and more prevalent between neurons that share similar functional response features. However, the details of how functional rules for local connectivity shape neuronal responses in V1 remain unknown. We hypothesised that complex responses to visual stimuli may arise as a consequence of rules for selective excitatory connectivity within the local network in the superficial layers of mouse V1. In mouse V1 many neurons respond to overlapping grating stimuli (plaid stimuli) with highly selective and facilitatory responses, which are not simply predicted by responses to single gratings presented alone. This complexity is surprising, since excitatory neurons in V1 are considered to be mainly tuned to single preferred orientations. Here we examined the consequences for visual processing of two alternative connectivity schemes: in the first case, local connections are aligned with visual properties inherited from feedforward input (a ‘like-to-like’ scheme specifically connecting neurons that share similar preferred orientations); in the second case, local connections group neurons into excitatory subnetworks that combine and amplify multiple feedforward visual properties (a ‘feature binding’ scheme). By comparing predictions from large scale computational models with in vivo recordings of visual representations in mouse V1, we found that responses to plaid stimuli were best explained by assuming feature binding connectivity. Unlike under the like-to-like scheme, selective amplification within feature-binding excitatory subnetworks replicated experimentally observed facilitatory responses to plaid stimuli; explained selective plaid responses not predicted by grating selectivity; and was consistent with broad anatomical selectivity observed in mouse V1. Our results show that visual feature binding can occur through local recurrent mechanisms without requiring feedforward convergence, and that such a mechanism is consistent with visual responses and cortical anatomy in mouse V1. PMID:29240769

Diffusion of Small Sticky Nanoparticles in a Polymer Melt: A Dynamic Light Scattering Study

NASA Astrophysics Data System (ADS)

Carroll, Bobby; Bocharova, Vera; Cheng, Shiwang; Yamamoto, Umi; Kisliuk, Alex; Schweizer, Ken; Sokolov, Alexei

The study of dynamics in complex fluids such as polymers has gained a broad interest in advanced materials and biomedical applications. Of particular interest is the motion of nanoparticles in these systems, which influences the mechanical and structural properties of composite materials, properties of colloidal systems, and biochemical processes in biological systems. Theoretical work predicts a violation of Stokes-Einstein (SE) relationship for diffusion of small nanoparticles in strongly-entangled polymer melt systems, with diffusion of nanoparticles much faster than expected DSE. It is attributed to differences between local and macroscopic viscosity. In this study, the diffusion of nanoparticles in polymer melts below and above entanglement molecular weight is measured using dynamic light scattering. The measured results are compared with simulations that provide quantitative predictions for SE violations. Our results are two-fold: (1) diffusion at lower molecular weights is slower than expected DSE due to chain absorption; and (2) diffusion becomes much (20 times) faster than DSE, at higher entanglements due to a reduced local viscosity.

An EQT-based cDFT approach for thermodynamic properties of confined fluid mixtures

NASA Astrophysics Data System (ADS)

Motevaselian, M. H.; Aluru, N. R.

2017-04-01

We present an empirical potential-based quasi-continuum theory (EQT) to predict the structure and thermodynamic properties of confined fluid mixtures. The central idea in the EQT is to construct potential energies that integrate important atomistic details into a continuum-based model such as the Nernst-Planck equation. The EQT potentials can be also used to construct the excess free energy functional, which is required for the grand potential in the classical density functional theory (cDFT). In this work, we use the EQT-based grand potential to predict various thermodynamic properties of a confined binary mixture of hydrogen and methane molecules inside graphene slit channels of different widths. We show that the EQT-cDFT predictions for the structure, surface tension, solvation force, and local pressure tensor profiles are in good agreement with the molecular dynamics simulations. Moreover, we study the effect of different bulk compositions and channel widths on the thermodynamic properties. Our results reveal that the composition of methane in the mixture can significantly affect the ordering of molecules and thermodynamic properties under confinement. In addition, we find that graphene is selective to methane molecules.

Significant-Loophole-Free Test of Bell's Theorem with Entangled Photons.

PubMed

Giustina, Marissa; Versteegh, Marijn A M; Wengerowsky, Sören; Handsteiner, Johannes; Hochrainer, Armin; Phelan, Kevin; Steinlechner, Fabian; Kofler, Johannes; Larsson, Jan-Åke; Abellán, Carlos; Amaya, Waldimar; Pruneri, Valerio; Mitchell, Morgan W; Beyer, Jörn; Gerrits, Thomas; Lita, Adriana E; Shalm, Lynden K; Nam, Sae Woo; Scheidl, Thomas; Ursin, Rupert; Wittmann, Bernhard; Zeilinger, Anton

2015-12-18

Local realism is the worldview in which physical properties of objects exist independently of measurement and where physical influences cannot travel faster than the speed of light. Bell's theorem states that this worldview is incompatible with the predictions of quantum mechanics, as is expressed in Bell's inequalities. Previous experiments convincingly supported the quantum predictions. Yet, every experiment requires assumptions that provide loopholes for a local realist explanation. Here, we report a Bell test that closes the most significant of these loopholes simultaneously. Using a well-optimized source of entangled photons, rapid setting generation, and highly efficient superconducting detectors, we observe a violation of a Bell inequality with high statistical significance. The purely statistical probability of our results to occur under local realism does not exceed 3.74×10^{-31}, corresponding to an 11.5 standard deviation effect.

Localization through surface folding in solid foams under compression.

PubMed

Reis, P M; Corson, F; Boudaoud, A; Roman, B

2009-07-24

We report a combined experimental and theoretical study of the compression of a solid foam coated with a thin elastic film. Past a critical compression threshold, a pattern of localized folds emerges with a characteristic size that is imposed by an instability of the thin surface film. We perform optical surface measurements of the statistical properties of these localization zones and find that they are characterized by robust exponential tails in the strain distributions. Following a hybrid continuum and statistical approach, we develop a theory that accurately describes the nucleation and length scale of these structures and predicts the characteristic strains associated with the localized regions.

Comparison study of global and local approaches describing critical phenomena on the Polish stock exchange market

NASA Astrophysics Data System (ADS)

Czarnecki, Łukasz; Grech, Dariusz; Pamuła, Grzegorz

2008-12-01

We confront global and local methods to analyze the financial crash-like events on the Polish financial market from the critical phenomena point of view. These methods are based on the analysis of log-periodicity and the local fractal properties of financial time series in the vicinity of phase transitions (crashes). The whole history (1991-2008) of Warsaw Stock Exchange Index (WIG) describing the largest developing financial market in Europe, is analyzed in a daily time horizon. We find that crash-like events on the Polish financial market are described better by the log-divergent price model decorated with log-periodic behavior than the corresponding power-law-divergent price model. Predictions coming from log-periodicity scenario are verified for all main crashes that took place in WIG history. It is argued that crash predictions within log-periodicity model strongly depend on the amount of data taken to make a fit and therefore are likely to contain huge inaccuracies. Turning to local fractal description, we calculate the so-called local (time dependent) Hurst exponent H for the WIG time series and we find the dependence between the behavior of the local fractal properties of the WIG time series and the crashes appearance on the financial market. The latter method seems to work better than the global approach - both for developing as for developed markets. The current situation on the market, particularly related to the Fed intervention in September’07 and the situation on the market immediately after this intervention is also analyzed from the fractional Brownian motion point of view.

Enhancement of Optical Nonlinearities in Composite Media and Structures via Local Fields and Electromagnetic Coupling Effects

NASA Technical Reports Server (NTRS)

Smith, David D.

2002-01-01

This talk will review the linear and nonlinear optical properties of metal nanoparticles and dielectric microparticles, with an emphasis on local field effects, and whispering gallery modes (WGMs), as well as the conjunction of these two effects for enhanced Raman. In particular, enhanced optical properties that result from electromagnetic coupling effects will be discussed in the context of Mie scattering from concentric spheres and bispheres. Predictions of mode splitting and photonic bandgaps in micro-spheres will be presented and will be shown to be analogous to effects that occur in coupled resonator optical waveguides (CROW). Slow and fast light in SCISSOR / CROW configurations will also be discussed.

Phase-field Model for Interstitial Loop Growth Kinetics and Thermodynamic and Kinetic Models of Irradiated Fe-Cr Alloys

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

Li, Yulan; Hu, Shenyang Y.; Sun, Xin

2011-06-15

Microstructure evolution kinetics in irradiated materials has strongly spatial correlation. For example, void and second phases prefer to nucleate and grow at pre-existing defects such as dislocations, grain boundaries, and cracks. Inhomogeneous microstructure evolution results in inhomogeneity of microstructure and thermo-mechanical properties. Therefore, the simulation capability for predicting three dimensional (3-D) microstructure evolution kinetics and its subsequent impact on material properties and performance is crucial for scientific design of advanced nuclear materials and optimal operation conditions in order to reduce uncertainty in operational and safety margins. Very recently the meso-scale phase-field (PF) method has been used to predict gas bubblemore » evolution, void swelling, void lattice formation and void migration in irradiated materials,. Although most results of phase-field simulations are qualitative due to the lake of accurate thermodynamic and kinetic properties of defects, possible missing of important kinetic properties and processes, and the capability of current codes and computers for large time and length scale modeling, the simulations demonstrate that PF method is a promising simulation tool for predicting 3-D heterogeneous microstructure and property evolution, and providing microstructure evolution kinetics for higher scale level simulations of microstructure and property evolution such as mean field methods. This report consists of two parts. In part I, we will present a new phase-field model for predicting interstitial loop growth kinetics in irradiated materials. The effect of defect (vacancy/interstitial) generation, diffusion and recombination, sink strength, long-range elastic interaction, inhomogeneous and anisotropic mobility on microstructure evolution kinetics is taken into account in the model. The model is used to study the effect of elastic interaction on interstitial loop growth kinetics, the interstitial flux, and sink strength of interstitial loop for interstitials. In part II, we present a generic phase field model and discuss the thermodynamic and kinetic properties in phase-field models including the reaction kinetics of radiation defects and local free energy of irradiated materials. In particular, a two-sublattice thermodynamic model is suggested to describe the local free energy of alloys with irradiated defects. Fe-Cr alloy is taken as an example to explain the required thermodynamic and kinetic properties for quantitative phase-field modeling. Finally the great challenges in phase-field modeling will be discussed.« less

Galaxy Formation At Extreme Redshifts: Semi-Analytic Model Predictions And Challenges For Observations

NASA Astrophysics Data System (ADS)

Yung, L. Y. Aaron; Somerville, Rachel S.

2017-06-01

The well-established Santa Cruz semi-analytic galaxy formation framework has been shown to be quite successful at explaining observations in the local Universe, as well as making predictions for low-redshift observations. Recently, metallicity-based gas partitioning and H2-based star formation recipes have been implemented in our model, replacing the legacy cold-gas based recipe. We then use our revised model to explore the high-redshift Universe and make predictions up to z = 15. Although our model is only calibrated to observations from the local universe, our predictions seem to match incredibly well with mid- to high-redshift observational constraints available-to-date, including rest-frame UV luminosity functions and the reionization history as constrained by CMB and IGM observations. We provide predictions for individual and statistical galaxy properties at a wide range of redshifts (z = 4 - 15), including objects that are too far or too faint to be detected with current facilities. And using our model predictions, we also provide forecasted luminosity functions and other observables for upcoming studies with JWST.

Towards the chemometric dissection of peptide - HLA-A*0201 binding affinity: comparison of local and global QSAR models

NASA Astrophysics Data System (ADS)

Doytchinova, Irini A.; Walshe, Valerie; Borrow, Persephone; Flower, Darren R.

2005-03-01

The affinities of 177 nonameric peptides binding to the HLA-A*0201 molecule were measured using a FACS-based MHC stabilisation assay and analysed using chemometrics. Their structures were described by global and local descriptors, QSAR models were derived by genetic algorithm, stepwise regression and PLS. The global molecular descriptors included molecular connectivity χ indices, κ shape indices, E-state indices, molecular properties like molecular weight and log P, and three-dimensional descriptors like polarizability, surface area and volume. The local descriptors were of two types. The first used a binary string to indicate the presence of each amino acid type at each position of the peptide. The second was also position-dependent but used five z-scales to describe the main physicochemical properties of the amino acids forming the peptides. The models were developed using a representative training set of 131 peptides and validated using an independent test set of 46 peptides. It was found that the global descriptors could not explain the variance in the training set nor predict the affinities of the test set accurately. Both types of local descriptors gave QSAR models with better explained variance and predictive ability. The results suggest that, in their interactions with the MHC molecule, the peptide acts as a complicated ensemble of multiple amino acids mutually potentiating each other.

PatchSurfers: Two methods for local molecular property-based binding ligand prediction.

PubMed

Shin, Woong-Hee; Bures, Mark Gregory; Kihara, Daisuke

2016-01-15

Protein function prediction is an active area of research in computational biology. Function prediction can help biologists make hypotheses for characterization of genes and help interpret biological assays, and thus is a productive area for collaboration between experimental and computational biologists. Among various function prediction methods, predicting binding ligand molecules for a target protein is an important class because ligand binding events for a protein are usually closely intertwined with the proteins' biological function, and also because predicted binding ligands can often be directly tested by biochemical assays. Binding ligand prediction methods can be classified into two types: those which are based on protein-protein (or pocket-pocket) comparison, and those that compare a target pocket directly to ligands. Recently, our group proposed two computational binding ligand prediction methods, Patch-Surfer, which is a pocket-pocket comparison method, and PL-PatchSurfer, which compares a pocket to ligand molecules. The two programs apply surface patch-based descriptions to calculate similarity or complementarity between molecules. A surface patch is characterized by physicochemical properties such as shape, hydrophobicity, and electrostatic potentials. These properties on the surface are represented using three-dimensional Zernike descriptors (3DZD), which are based on a series expansion of a 3 dimensional function. Utilizing 3DZD for describing the physicochemical properties has two main advantages: (1) rotational invariance and (2) fast comparison. Here, we introduce Patch-Surfer and PL-PatchSurfer with an emphasis on PL-PatchSurfer, which is more recently developed. Illustrative examples of PL-PatchSurfer performance on binding ligand prediction as well as virtual drug screening are also provided. Copyright © 2015 Elsevier Inc. All rights reserved.

Spin localization, magnetic ordering, and electronic properties of strongly correlated Ln2O3 sesquioxides (Ln=La, Ce, Pr, Nd)

NASA Astrophysics Data System (ADS)

El-Kelany, Kh. E.; Ravoux, C.; Desmarais, J. K.; Cortona, P.; Pan, Y.; Tse, J. S.; Erba, A.

2018-06-01

Lanthanide sesquioxides are strongly correlated materials characterized by highly localized unpaired electrons in the f band. Theoretical descriptions based on standard density functional theory (DFT) formulations are known to be unable to correctly describe their peculiar electronic and magnetic features. In this study, electronic and magnetic properties of the first four lanthanide sesquioxides in the series are characterized through a reliable description of spin localization as ensured by hybrid functionals of the DFT, which include a fraction of nonlocal Fock exchange. Because of the high localization of the f electrons, multiple metastable electronic configurations are possible for their ground state depending on the specific partial occupation of the f orbitals: the most stable configuration is here found and characterized for all systems. Magnetic ordering is explicitly investigated, and the higher stability of an antiferromagnetic configuration with respect to the ferromagnetic one is predicted. The critical role of the fraction of exchange on the description of their electronic properties (notably, on spin localization and on the electronic band gap) is addressed. In particular, a recently proposed theoretical approach based on a self-consistent definition—through the material dielectric response—of the optimal fraction of exchange in hybrid functionals is applied to these strongly correlated materials.

Conscious Vision Proceeds from Global to Local Content in Goal-Directed Tasks and Spontaneous Vision.

PubMed

Campana, Florence; Rebollo, Ignacio; Urai, Anne; Wyart, Valentin; Tallon-Baudry, Catherine

2016-05-11

The reverse hierarchy theory (Hochstein and Ahissar, 2002) makes strong, but so far untested, predictions on conscious vision. In this theory, local details encoded in lower-order visual areas are unconsciously processed before being automatically and rapidly combined into global information in higher-order visual areas, where conscious percepts emerge. Contingent on current goals, local details can afterward be consciously retrieved. This model therefore predicts that (1) global information is perceived faster than local details, (2) global information is computed regardless of task demands during early visual processing, and (3) spontaneous vision is dominated by global percepts. We designed novel textured stimuli that are, as opposed to the classic Navon's letters, truly hierarchical (i.e., where global information is solely defined by local information but where local and global orientations can still be manipulated separately). In line with the predictions, observers were systematically faster reporting global than local properties of those stimuli. Second, global information could be decoded from magneto-encephalographic data during early visual processing regardless of task demands. Last, spontaneous subjective reports were dominated by global information and the frequency and speed of spontaneous global perception correlated with the accuracy and speed in the global task. No such correlation was observed for local information. We therefore show that information at different levels of the visual hierarchy is not equally likely to become conscious; rather, conscious percepts emerge preferentially at a global level. We further show that spontaneous reports can be reliable and are tightly linked to objective performance at the global level. Is information encoded at different levels of the visual system (local details in low-level areas vs global shapes in high-level areas) equally likely to become conscious? We designed new hierarchical stimuli and provide the first empirical evidence based on behavioral and MEG data that global information encoded at high levels of the visual hierarchy dominates perception. This result held both in the presence and in the absence of task demands. The preferential emergence of percepts at high levels can account for two properties of conscious vision, namely, the dominance of global percepts and the feeling of visual richness reported independently of the perception of local details. Copyright © 2016 the authors 0270-6474/16/365200-14$15.00/0.

Variations on a theme - the evolution of hydrocarbon solids. I. Compositional and spectral modelling - the eRCN and DG models

NASA Astrophysics Data System (ADS)

Jones, A. P.

2012-04-01

Context. The compositional properties of hydrogenated amorphous carbons are known to evolve in response to the local conditions. Aims: We present a model for low-temperature, amorphous hydrocarbon solids, based on the microphysical properties of random and defected networks of carbon and hydrogen atoms, that can be used to study and predict the evolution of their properties in the interstellar medium. Methods: We adopt an adaptable and prescriptive approach to model these materials, which is based on a random covalent network (RCN) model, extended here to a full compositional derivation (the eRCN model), and a defective graphite (DG) model for the hydrogen poorer materials where the eRCN model is no longer valid. Results: We provide simple expressions that enable the determination of the structural, infrared and spectral properties of amorphous hydrocarbon grains as a function of the hydrogen atomic fraction, XH. Structural annealing, resulting from hydrogen atom loss, results in a transition from H-rich, aliphatic-rich to H-poor, aromatic-rich materials. Conclusions: The model predicts changes in the optical properties of hydrogenated amorphous carbon dust in response to the likely UV photon-driven and/or thermal annealing processes resulting, principally, from the radiation field in the environment. We show how this dust component will evolve, compositionally and structurally in the interstellar medium in response to the local conditions. Appendices A and B are available in electronic form at http://www.aanda.org

Probing the localization of magnetic dichroism by atomic-size astigmatic and vortex electron beams.

PubMed

Negi, Devendra Singh; Idrobo, Juan Carlos; Rusz, Ján

2018-03-05

We report localization of a magnetic dichroic signal on atomic columns in electron magnetic circular dichroism (EMCD), probed by beam distorted by four-fold astigmatism and electron vortex beam. With astigmatic probe, magnetic signal to noise ratio can be enhanced by blocking the intensity from the central part of probe. However, the simulations show that for atomic resolution magnetic measurements, vortex beam is a more effective probe, with much higher magnetic signal to noise ratio. For all considered beam shapes, the optimal SNR constrains the signal detection at low collection angles of approximately 6-8 mrad. Irrespective of the material thickness, the magnetic signal remains strongly localized within the probed atomic column with vortex beam, whereas for astigmatic probes, the magnetic signal originates mostly from the nearest neighbor atomic columns. Due to excellent signal localization at probing individual atomic columns, vortex beams are predicted to be a strong candidate for studying the crystal site specific magnetic properties, magnetic properties at interfaces, or magnetism arising from individual atomic impurities.

Auxiliary field diffusion Monte Carlo calculations of light and medium-mass nuclei with local chiral interactions

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

Lonardoni, D.; Gandolfi, S.; Lynn, J. E.

Quantum Monte Carlo methods have recently been employed to study properties of nuclei and infinite matter using local chiral effective-field-theory interactions. In this paper, we present a detailed description of the auxiliary field diffusion Monte Carlo algorithm for nuclei in combination with local chiral two- and three-nucleon interactions up to next-to-next-to-leading order. We show results for the binding energy, charge radius, charge form factor, and Coulomb sum rule in nuclei withmore » $$3{\\le}A{\\le}16$$. Particular attention is devoted to the effect of different operator structures in the three-body force for different cutoffs. Finally, the outcomes suggest that local chiral interactions fit to few-body observables give a very good description of the ground-state properties of nuclei up to $$^{16}\\mathrm{O}$$, with the exception of one fit for the softer cutoff which predicts overbinding in larger nuclei.« less

Auxiliary field diffusion Monte Carlo calculations of light and medium-mass nuclei with local chiral interactions

DOE PAGES

Lonardoni, D.; Gandolfi, S.; Lynn, J. E.; ...

2018-04-24

Quantum Monte Carlo methods have recently been employed to study properties of nuclei and infinite matter using local chiral effective-field-theory interactions. In this paper, we present a detailed description of the auxiliary field diffusion Monte Carlo algorithm for nuclei in combination with local chiral two- and three-nucleon interactions up to next-to-next-to-leading order. We show results for the binding energy, charge radius, charge form factor, and Coulomb sum rule in nuclei withmore » $$3{\\le}A{\\le}16$$. Particular attention is devoted to the effect of different operator structures in the three-body force for different cutoffs. Finally, the outcomes suggest that local chiral interactions fit to few-body observables give a very good description of the ground-state properties of nuclei up to $$^{16}\\mathrm{O}$$, with the exception of one fit for the softer cutoff which predicts overbinding in larger nuclei.« less

Covariate selection with iterative principal component analysis for predicting physical

USDA-ARS?s Scientific Manuscript database

Local and regional soil data can be improved by coupling new digital soil mapping techniques with high resolution remote sensing products to quantify both spatial and absolute variation of soil properties. The objective of this research was to advance data-driven digital soil mapping techniques for ...

Three-dimensional prediction of soil physical, chemical, and hydrological properties in a forested catchment of the Santa Catalina CZO

NASA Astrophysics Data System (ADS)

Shepard, C.; Holleran, M.; Lybrand, R. A.; Rasmussen, C.

2014-12-01

Understanding critical zone evolution and function requires an accurate assessment of local soil properties. Two-dimensional (2D) digital soil mapping provides a general assessment of soil characteristics across a sampled landscape, but lacks the ability to predict soil properties with depth. The utilization of mass-preserving spline functions enable the extrapolation of soil properties with depth, extending predictive functions to three-dimensions (3D). The present study was completed in the Marshall Gulch (MG) catchment, located in the Santa Catalina Mountains, 30 km northwest of Tucson, Arizona, as part of the Santa Catalina-Jemez Mountains Critical Zone Observatory. Twenty-four soil pits were excavated and described following standard procedures. Mass-preserving splines were used to extrapolate mass carbon (kg C m-2); percent clay, silt, and sand (%); sodium mass flux (kg Na m-2); and pH for 24 sampled soil pits in 1-cm depth increments. Saturated volumetric water content (θs) and volumetric water content at 10 kPa (θ10) were predicted using ROSETTA and established empirical relationships. The described profiles were all sampled to differing depths; to compensate for the unevenness of the profile descriptions, the soil depths were standardized from 0.0 to 1.0 and then split into five equal standard depth sections. A logit-transformation was used to normalize the target variables. Step-wise regressions were calculated using available environmental covariates to predict the properties of each variable across the catchment in each depth section, and interpolated model residuals added back to the predicted layers to generate the final soil maps. Logit-transformed R2 for the predictive functions varied widely, ranging from 0.20 to 0.79, with logit-transformed RMSE ranging from 0.15 to 2.77. The MG catchment was further classified into clusters with similar properties based on the environmental covariates, and representative depth functions for each target variable in each cluster calculated. Mass-preserving splines combined with stepwise regressions are an effective tool for predicting soil physical, chemical, and hydrological properties with depth, enhancing our understanding of the critical zone.

Characterization of essential proteins based on network topology in proteins interaction networks

NASA Astrophysics Data System (ADS)

Bakar, Sakhinah Abu; Taheri, Javid; Zomaya, Albert Y.

2014-06-01

The identification of essential proteins is theoretically and practically important as (1) it is essential to understand the minimal surviving requirements for cellular lives, and (2) it provides fundamental for development of drug. As conducting experimental studies to identify essential proteins are both time and resource consuming, here we present a computational approach in predicting them based on network topology properties from protein-protein interaction networks of Saccharomyces cerevisiae. The proposed method, namely EP3NN (Essential Proteins Prediction using Probabilistic Neural Network) employed a machine learning algorithm called Probabilistic Neural Network as a classifier to identify essential proteins of the organism of interest; it uses degree centrality, closeness centrality, local assortativity and local clustering coefficient of each protein in the network for such predictions. Results show that EP3NN managed to successfully predict essential proteins with an accuracy of 95% for our studied organism. Results also show that most of the essential proteins are close to other proteins, have assortativity behavior and form clusters/sub-graph in the network.

Numerical analysis of the Anderson localization

NASA Astrophysics Data System (ADS)

Markoš, P.

2006-10-01

The aim of this paper is to demonstrate, by simple numerical simulations, the main transport properties of disordered electron systems. These systems undergo the metal insulator transition when either Fermi energy crosses the mobility edge or the strength of the disorder increases over critical value. We study how disorder affects the energy spectrum and spatial distribution of electronic eigenstates in the diffusive and insulating regime, as well as in the critical region of the metal-insulator transition. Then, we introduce the transfer matrix and conductance, and we discuss how the quantum character of the electron propagation influences the transport properties of disordered samples. In the weakly disordered systems, the weak localization and anti-localization as well as the universal conductance fluctuation are numerically simulated and discussed. The localization in the one dimensional system is described and interpreted as a purely quantum effect. Statistical properties of the conductance in the critical and localized regimes are demonstrated. Special attention is given to the numerical study of the transport properties of the critical regime and to the numerical verification of the single parameter scaling theory of localization. Numerical data for the critical exponent in the orthogonal models in dimension 2 < d, ≤ 5 are compared with theoretical predictions. We argue that the discrepancy between the theory and numerical data is due to the absence of the self-averaging of transmission quantities. This complicates the analytical analysis of the disordered systems. Finally, theoretical methods of description of weakly disordered systems are explained and their possible generalization to the localized regime is discussed. Since we concentrate on the one-electron propagation at zero temperature, no effects of electron-electron interaction and incoherent scattering are discussed in the paper.

Assessment of the amide-I local modes in gamma- and beta-turns of peptides.

PubMed

Wang, Jianping

2009-07-14

The amide-I local modes, mainly the C[double bond, length as m-dash]O stretching vibrations, form the structural basis of femtosecond 2D IR spectroscopy in characterizing backbone structures and dynamics of peptides and proteins. In this work, a density functional theory (DFT) level of computational assessment of the amide-I local modes in oligomers mostly in the turn conformations was carried out. It is shown that local mode properties, including transition frequencies and transition dipole magnitudes and orientations, are slightly conformational dependent. However, the distributions of these properties in the peptide oligomers are narrow and have mean values almost identical to those from an isolated peptide monomer, justifying the prevalent use of a uniform local mode in modeling the 1D and 2D IR spectra. In addition, it is shown that the transition dipole magnitude and orientation of the peptide monomer predicted by the DFT calculations can be well approximated by electrostatic potential-based transition charge schemes, e.g. Merz-Singh-Kollman, CHELP, as well as CHELPG.

The Portevin–Le Chatelier effect: a review of experimental findings

PubMed Central

Yilmaz, Ahmet

2011-01-01

The Portevin–Le Chatelier (PLC) effect manifests itself as an unstable plastic flow during tensile tests of some dilute alloys under certain regimes of strain rate and temperature. The plastic strain becomes localized in the form of bands which move along a specimen gauge in various ways as the PLC effect occurs. Because the localization of strain causes degradation of the inherent structural properties and surface quality of materials, understanding the effect is crucial for the effective use of alloys. The characteristic behaviors of localized strain bands and techniques commonly used to study the PLC effect are summarized in this review. A brief overview of experimental findings, the effect of material properties and test parameters on the PLC effect, and some discussion on the mechanisms of the effect are included. Tests for predicting the early failure of structural materials due to embrittlement induced by the PLC effect are also discussed. PMID:27877450

Estimation of local stresses and elastic properties of a mortar sample by FFT computation of fields on a 3D image

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

Escoda, J.; Departement Materiaux et Mecanique des Composants, Electricite de France, Moret-sur-Loing; Willot, F., E-mail: francois.willot@ensmp.f

2011-05-15

This study concerns the prediction of the elastic properties of a 3D mortar image, obtained by micro-tomography, using a combined image segmentation and numerical homogenization approach. The microstructure is obtained by segmentation of the 3D image into aggregates, voids and cement paste. Full-fields computations of the elastic response of mortar are undertaken using the Fast Fourier Transform method. Emphasis is made on highly-contrasted properties between aggregates and matrix, to anticipate needs for creep or damage computation. The representative volume element, i.e. the volume size necessary to compute the effective properties with a prescribed accuracy, is given. Overall, the volumes usedmore » in this work were sufficient to estimate the effective response of mortar with a precision of 5%, 6% and 10% for contrast ratios of 100, 1000 and 10,000, resp. Finally, a statistical and local characterization of the component of the stress field parallel to the applied loading is carried out.« less

Predicting chroma from luma with frequency domain intra prediction

NASA Astrophysics Data System (ADS)

Egge, Nathan E.; Valin, Jean-Marc

2015-03-01

This paper describes a technique for performing intra prediction of the chroma planes based on the reconstructed luma plane in the frequency domain. This prediction exploits the fact that while RGB to YUV color conversion has the property that it decorrelates the color planes globally across an image, there is still some correlation locally at the block level.1 Previous proposals compute a linear model of the spatial relationship between the luma plane (Y) and the two chroma planes (U and V).2 In codecs that use lapped transforms this is not possible since transform support extends across the block boundaries3 and thus neighboring blocks are unavailable during intra- prediction. We design a frequency domain intra predictor for chroma that exploits the same local correlation with lower complexity than the spatial predictor and which works with lapped transforms. We then describe a low- complexity algorithm that directly uses luma coefficients as a chroma predictor based on gain-shape quantization and band partitioning. An experiment is performed that compares these two techniques inside the experimental Daala video codec and shows the lower complexity algorithm to be a better chroma predictor.

Excitons in boron nitride single layer

NASA Astrophysics Data System (ADS)

Galvani, Thomas; Paleari, Fulvio; Miranda, Henrique P. C.; Molina-Sánchez, Alejandro; Wirtz, Ludger; Latil, Sylvain; Amara, Hakim; Ducastelle, François

2016-09-01

Boron nitride single layer belongs to the family of two-dimensional materials whose optical properties are currently receiving considerable attention. Strong excitonic effects have already been observed in the bulk and still stronger effects are predicted for single layers. We present here a detailed study of these properties by combining ab initio calculations and a tight-binding Wannier analysis in both real and reciprocal space. Due to the simplicity of the band structure with single valence (π ) and conduction (π*) bands the tight-binding analysis becomes quasiquantitative with only two adjustable parameters and provides tools for a detailed analysis of the exciton properties. Strong deviations from the usual hydrogenic model are evidenced. The ground-state exciton is not a genuine Frenkel exciton, but a very localized tightly bound one. The other ones are similar to those found in transition-metal dichalcogenides and, although more localized, can be described within a Wannier-Mott scheme.

CLUES to the past: Local Group progenitors amongst high-redshift Lyman break galaxies

NASA Astrophysics Data System (ADS)

Dayal, Pratika; Libeskind, Noam I.; Dunlop, James S.

2013-06-01

We use state-of-the-art numerical simulations to explore the observability and the expected physical properties of the progenitors of the Local Group galaxies at z ≃ 6-8, within 1 billion years of the big bang. We find that the most massive progenitors of the Milky Way (MW) and Andromeda (M31) at z ≃ 6 and 7 are predicted to have absolute ultraviolet (UV) continuum magnitudes MUV ≃ -17 to -18, suggesting that their analogues lie close to the detection limits of the deepest near-infrared (IR) surveys conducted to date [i.e. Hubble Space Telescope Wide Field Camera 3/IR Ultra Deep Field (UDF)12]. This in turn confirms that the majority of currently known z ≃ 6-8 galaxies are expected to be the seeds of present-day galaxies which are more massive than L* spirals. We also discuss the properties of the Local Group progenitors at these early epochs, extending down to absolute magnitudes MUV ≃ -13. The most massive MW/M31 progenitors at z ≃ 7 have stellar masses M* ≃ 107.5-8 M⊙, stellar metallicities Z* ˜ 3-6 per cent Z⊙, and predicted observed UV continuum slopes β ≃ -2.4 to -2.5.

Spatial prediction of near surface soil water retention functions using hydrogeophysics

NASA Astrophysics Data System (ADS)

Gibson, J. P.; Franz, T. E.

2017-12-01

The hydrological community often turns to widely available spatial datasets such as SSURGO to characterize the spatial variability of soil across a landscape of interest. This has served as a reasonable first approximation when lacking localized soil data. However, previous work has shown that information loss within land surface models primarily stems from parameterization. Localized soil sampling is both expensive and time intense, and thus a need exists in connecting spatial datasets with ground observations. Given that hydrogeophysics is data-dense, rapid, and relatively easy to adopt, it is a promising technique to help dovetail localized soil sampling with larger spatial datasets. In this work, we utilize 2 geophysical techniques; cosmic ray neutron probe and electromagnetic induction, to identify temporally stable soil moisture patterns. This is achieved by measuring numerous times over a range of wet to dry field conditions in order to apply an empirical orthogonal function. We then present measured water retention functions of shallow cores extracted within each temporally stable zone. Lastly, we use soil moisture patterns as a covariate to predict soil hydraulic properties in areas without measurement and validate using a leave-one-out cross validation analysis. Using these approaches to better constrain soil hydraulic property variability, we speculate that further research can better estimate hydrologic fluxes in areas of interest.

Accounting for spatial variation of trabecular anisotropy with subject-specific finite element modeling moderately improves predictions of local subchondral bone stiffness at the proximal tibia.

PubMed

Nazemi, S Majid; Kalajahi, S Mehrdad Hosseini; Cooper, David M L; Kontulainen, Saija A; Holdsworth, David W; Masri, Bassam A; Wilson, David R; Johnston, James D

2017-07-05

Previously, a finite element (FE) model of the proximal tibia was developed and validated against experimentally measured local subchondral stiffness. This model indicated modest predictions of stiffness (R 2 =0.77, normalized root mean squared error (RMSE%)=16.6%). Trabecular bone though was modeled with isotropic material properties despite its orthotropic anisotropy. The objective of this study was to identify the anisotropic FE modeling approach which best predicted (with largest explained variance and least amount of error) local subchondral bone stiffness at the proximal tibia. Local stiffness was measured at the subchondral surface of 13 medial/lateral tibial compartments using in situ macro indentation testing. An FE model of each specimen was generated assuming uniform anisotropy with 14 different combinations of cortical- and tibial-specific density-modulus relationships taken from the literature. Two FE models of each specimen were also generated which accounted for the spatial variation of trabecular bone anisotropy directly from clinical CT images using grey-level structure tensor and Cowin's fabric-elasticity equations. Stiffness was calculated using FE and compared to measured stiffness in terms of R 2 and RMSE%. The uniform anisotropic FE model explained 53-74% of the measured stiffness variance, with RMSE% ranging from 12.4 to 245.3%. The models which accounted for spatial variation of trabecular bone anisotropy predicted 76-79% of the variance in stiffness with RMSE% being 11.2-11.5%. Of the 16 evaluated finite element models in this study, the combination of Synder and Schneider (for cortical bone) and Cowin's fabric-elasticity equations (for trabecular bone) best predicted local subchondral bone stiffness. Copyright © 2017 Elsevier Ltd. All rights reserved.

Elastic properties of fcc Fe-Mn-X (X = Cr, Co, Ni, Cu) alloys studied by the combinatorial thin film approach and ab initio calculations.

PubMed

Reeh, S; Kasprzak, M; Klusmann, C D; Stalf, F; Music, D; Ekholm, M; Abrikosov, I A; Schneider, J M

2013-06-19

The elastic properties of fcc Fe-Mn-X (X = Cr, Co, Ni, Cu) alloys with additions of up to 8 at.% X were studied by combinatorial thin film growth and characterization and by ab initio calculations using the disordered local moments (DLM) approach. The lattice parameter and Young's modulus values change only marginally with X. The calculations and experiments are in good agreement. We demonstrate that the elastic properties of transition metal alloyed Fe-Mn can be predicted by the DLM model.

Comparisons of rational engineering correlations of thermophoretically-augmented particle mass transfer with STAN5-predictions for developing boundary layers

NASA Technical Reports Server (NTRS)

Gokoglu, S. A.; Rosner, D. E.

1984-01-01

Modification of the code STAN5 to properly include thermophoretic mass transport, and examination of selected test cases developing boundary layers which include variable properties, viscous dissipation, transition to turbulence and transpiration cooling. Under conditions representative of current and projected GT operation, local application of St(M)/St(M),o correlations evidently provides accurate and economical engineering design predictions, especially for suspended particles characterized by Schmidt numbers outside of the heavy vapor range.

Exploring the potential of 3D Zernike descriptors and SVM for protein-protein interface prediction.

PubMed

Daberdaku, Sebastian; Ferrari, Carlo

2018-02-06

The correct determination of protein-protein interaction interfaces is important for understanding disease mechanisms and for rational drug design. To date, several computational methods for the prediction of protein interfaces have been developed, but the interface prediction problem is still not fully understood. Experimental evidence suggests that the location of binding sites is imprinted in the protein structure, but there are major differences among the interfaces of the various protein types: the characterising properties can vary a lot depending on the interaction type and function. The selection of an optimal set of features characterising the protein interface and the development of an effective method to represent and capture the complex protein recognition patterns are of paramount importance for this task. In this work we investigate the potential of a novel local surface descriptor based on 3D Zernike moments for the interface prediction task. Descriptors invariant to roto-translations are extracted from circular patches of the protein surface enriched with physico-chemical properties from the HQI8 amino acid index set, and are used as samples for a binary classification problem. Support Vector Machines are used as a classifier to distinguish interface local surface patches from non-interface ones. The proposed method was validated on 16 classes of proteins extracted from the Protein-Protein Docking Benchmark 5.0 and compared to other state-of-the-art protein interface predictors (SPPIDER, PrISE and NPS-HomPPI). The 3D Zernike descriptors are able to capture the similarity among patterns of physico-chemical and biochemical properties mapped on the protein surface arising from the various spatial arrangements of the underlying residues, and their usage can be easily extended to other sets of amino acid properties. The results suggest that the choice of a proper set of features characterising the protein interface is crucial for the interface prediction task, and that optimality strongly depends on the class of proteins whose interface we want to characterise. We postulate that different protein classes should be treated separately and that it is necessary to identify an optimal set of features for each protein class.

The design and modeling of periodic materials with novel properties

NASA Astrophysics Data System (ADS)

Berger, Jonathan Bernard

Cellular materials are ubiquitous in our world being found in natural and engineered systems as structural materials, sound and energy absorbers, heat insulators and more. Stochastic foams made of polymers, metals and even ceramics find wide use due to their novel properties when compared to monolithic materials. Properties of these so called hybrid materials, those that combine materials or materials and space, are derived from the localization of thermomechanical stresses and strains on the mesoscale as a function of cell topology. The effects of localization can only be generalized in stochastic materials arising from their inherent potential complexity, possessing variations in local chemistry, microstructural inhomogeneity and topological variations. Ordered cellular materials on the other hand, such as lattices and honeycombs, make for much easier study, often requiring analysis of only a single unit-cell. Theoretical bounds predict that hybrid materials have the potential to push design envelopes offering lighter stiffer and stronger materials. Hybrid materials can achieve very low and even negative coefficients of thermal expansion (CTE) while retaining a relatively high stiffness -- properties completely unmatched by monolithic materials. In the first chapter of this thesis a two-dimensional lattice is detailed that possess near maximum stiffness, relative to the tightest theoretical bound, and low, zero and even appreciably negative thermal expansion. Its CTE and stiffness are given in closed form as a function of geometric parameters and the material properties. This result is confirmed with finite elements (FE) and experiment. In the second chapter the compressive stiffness of three-dimensional ordered foams, both closed and open cell, are predicted with FE and the results placed in property space in terms of stiffness and density. A novel structure is identified that effectively achieves theoretical bounds for Young's, shear and bulk modulus simultaneously, over a wide range of relative densities, greatly expanding the property space of available materials with a pragmatic manufacturable structure. A variety of other novel and previously studied ordered foam topologies are also presented that are largely representative of the spectrum of performance of such materials, shedding insight into the behavior of all cellular materials.

Multiscale finite element modeling of sheet molding compound (SMC) composite structure based on stochastic mesostructure reconstruction

DOE PAGES

Chen, Zhangxing; Huang, Tianyu; Shao, Yimin; ...

2018-03-15

Predicting the mechanical behavior of the chopped carbon fiber Sheet Molding Compound (SMC) due to spatial variations in local material properties is critical for the structural performance analysis but is computationally challenging. Such spatial variations are induced by the material flow in the compression molding process. In this work, a new multiscale SMC modeling framework and the associated computational techniques are developed to provide accurate and efficient predictions of SMC mechanical performance. The proposed multiscale modeling framework contains three modules. First, a stochastic algorithm for 3D chip-packing reconstruction is developed to efficiently generate the SMC mesoscale Representative Volume Element (RVE)more » model for Finite Element Analysis (FEA). A new fiber orientation tensor recovery function is embedded in the reconstruction algorithm to match reconstructions with the target characteristics of fiber orientation distribution. Second, a metamodeling module is established to improve the computational efficiency by creating the surrogates of mesoscale analyses. Third, the macroscale behaviors are predicted by an efficient multiscale model, in which the spatially varying material properties are obtained based on the local fiber orientation tensors. Our approach is further validated through experiments at both meso- and macro-scales, such as tensile tests assisted by Digital Image Correlation (DIC) and mesostructure imaging.« less

Sequence-dependent modelling of local DNA bending phenomena: curvature prediction and vibrational analysis.

PubMed

Vlahovicek, K; Munteanu, M G; Pongor, S

1999-01-01

Bending is a local conformational micropolymorphism of DNA in which the original B-DNA structure is only distorted but not extensively modified. Bending can be predicted by simple static geometry models as well as by a recently developed elastic model that incorporate sequence dependent anisotropic bendability (SDAB). The SDAB model qualitatively explains phenomena including affinity of protein binding, kinking, as well as sequence-dependent vibrational properties of DNA. The vibrational properties of DNA segments can be studied by finite element analysis of a model subjected to an initial bending moment. The frequency spectrum is obtained by applying Fourier analysis to the displacement values in the time domain. This analysis shows that the spectrum of the bending vibrations quite sensitively depends on the sequence, for example the spectrum of a curved sequence is characteristically different from the spectrum of straight sequence motifs of identical basepair composition. Curvature distributions are genome-specific, and pronounced differences are found between protein-coding and regulatory regions, respectively, that is, sites of extreme curvature and/or bendability are less frequent in protein-coding regions. A WWW server is set up for the prediction of curvature and generation of 3D models from DNA sequences (http:@www.icgeb.trieste.it/dna).

Multiscale finite element modeling of sheet molding compound (SMC) composite structure based on stochastic mesostructure reconstruction

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

Chen, Zhangxing; Huang, Tianyu; Shao, Yimin

Predicting the mechanical behavior of the chopped carbon fiber Sheet Molding Compound (SMC) due to spatial variations in local material properties is critical for the structural performance analysis but is computationally challenging. Such spatial variations are induced by the material flow in the compression molding process. In this work, a new multiscale SMC modeling framework and the associated computational techniques are developed to provide accurate and efficient predictions of SMC mechanical performance. The proposed multiscale modeling framework contains three modules. First, a stochastic algorithm for 3D chip-packing reconstruction is developed to efficiently generate the SMC mesoscale Representative Volume Element (RVE)more » model for Finite Element Analysis (FEA). A new fiber orientation tensor recovery function is embedded in the reconstruction algorithm to match reconstructions with the target characteristics of fiber orientation distribution. Second, a metamodeling module is established to improve the computational efficiency by creating the surrogates of mesoscale analyses. Third, the macroscale behaviors are predicted by an efficient multiscale model, in which the spatially varying material properties are obtained based on the local fiber orientation tensors. Our approach is further validated through experiments at both meso- and macro-scales, such as tensile tests assisted by Digital Image Correlation (DIC) and mesostructure imaging.« less

Scaling properties of multitension domain wall networks

NASA Astrophysics Data System (ADS)

Oliveira, M. F.; Martins, C. J. A. P.

2015-02-01

We study the asymptotic scaling properties of domain wall networks with three different tensions in various cosmological epochs. We discuss the conditions under which a scale-invariant evolution of the network (which is well established for simpler walls) still applies and also consider the limiting case where defects are locally planar and the curvature is concentrated in the junctions. We present detailed quantitative predictions for scaling densities in various contexts, which should be testable by means of future high-resolution numerical simulations.

Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy

PubMed Central

Pottier, Julien; Malenovský, Zbyněk; Psomas, Achilleas; Homolová, Lucie; Schaepman, Michael E.; Choler, Philippe; Thuiller, Wilfried; Guisan, Antoine; Zimmermann, Niklaus E.

2014-01-01

Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data. PMID:25079495

Predicting spiral wave patterns from cell properties in a model of biological self-organization.

PubMed

Geberth, Daniel; Hütt, Marc-Thorsten

2008-09-01

In many biological systems, biological variability (i.e., systematic differences between the system components) can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In principle, the distribution of single-element properties should thus allow predicting features of such patterns. For a mathematical model of a paradigmatic and well-studied pattern formation process, spiral waves of cAMP signaling in colonies of the slime mold Dictyostelium discoideum, we explore this possibility and observe a pronounced anticorrelation between spiral waves and cell properties (namely, the firing rate) and particularly a clustering of spiral wave tips in regions devoid of spontaneously firing (pacemaker) cells. Furthermore, we observe local inhomogeneities in the distribution of spiral chiralities, again induced by the pacemaker distribution. We show that these findings can be explained by a simple geometrical model of spiral wave generation.

First-principles study of the elastic and thermodynamic properties of CaSiO(3) perovskite.

PubMed

Liu, Z J; Sun, X W; Chen, Q F; Cai, L C; Wu, H Y; Ge, S H

2007-06-20

The thermodynamic and elastic properties of CaSiO(3) perovskite are investigated at high pressures and temperatures using the plane wave pseudopotential method within the local density approximation. The athermal elastic moduli of CaSiO(3) perovskite are calculated as a function of pressure up to 200 GPa. The calculated results are in excellent agreement with available experimental data at high pressure, and compare favourably with other pseudopotential predictions over the pressure regime studied. It is also found that the elastic anisotropy drops rapidly with the increase of pressure initially, and then decreases more slowly at higher pressures. The thermodynamic properties of CaSiO(3) perovskite are predicted using the quasi-harmonic Debye model for the first time; the heat capacity and the thermal expansion coefficient agree with the observed values at ambient conditions and the other calculations at high pressures and temperatures.

Predicting spiral wave patterns from cell properties in a model of biological self-organization

NASA Astrophysics Data System (ADS)

Geberth, Daniel; Hütt, Marc-Thorsten

2008-09-01

In many biological systems, biological variability (i.e., systematic differences between the system components) can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In principle, the distribution of single-element properties should thus allow predicting features of such patterns. For a mathematical model of a paradigmatic and well-studied pattern formation process, spiral waves of cAMP signaling in colonies of the slime mold Dictyostelium discoideum, we explore this possibility and observe a pronounced anticorrelation between spiral waves and cell properties (namely, the firing rate) and particularly a clustering of spiral wave tips in regions devoid of spontaneously firing (pacemaker) cells. Furthermore, we observe local inhomogeneities in the distribution of spiral chiralities, again induced by the pacemaker distribution. We show that these findings can be explained by a simple geometrical model of spiral wave generation.

Development of a High-Resolution, Single-Photon X-Ray Detector

NASA Technical Reports Server (NTRS)

Seidel, George M.

1996-01-01

Research on the development of a low-temperature, magnetic bolometer for x-ray detection is reported. The principal accomplishments during the first phase of this research are as follows. (1) We have constructed SQUID magnetometers and detected both 122 keV and 6 keV x-rays in relatively larger metallic samples with high quantum efficiency. (2) The magnetic properties of a metal sample with localized paramagnetic spins have been measured and found to agree with theoretical expectations. (3) The size of the magnetic response of the sample to x-rays is in agreement with predictions based on the properties of the sample and sensitivity of the magnetometer, supporting the prediction that a resolution of 1 eV at 10 keV should be achievable.

Continuum limit of the vibrational properties of amorphous solids.

PubMed

Mizuno, Hideyuki; Shiba, Hayato; Ikeda, Atsushi

2017-11-14

The low-frequency vibrational and low-temperature thermal properties of amorphous solids are markedly different from those of crystalline solids. This situation is counterintuitive because all solid materials are expected to behave as a homogeneous elastic body in the continuum limit, in which vibrational modes are phonons that follow the Debye law. A number of phenomenological explanations for this situation have been proposed, which assume elastic heterogeneities, soft localized vibrations, and so on. Microscopic mean-field theories have recently been developed to predict the universal non-Debye scaling law. Considering these theoretical arguments, it is absolutely necessary to directly observe the nature of the low-frequency vibrations of amorphous solids and determine the laws that such vibrations obey. Herein, we perform an extremely large-scale vibrational mode analysis of a model amorphous solid. We find that the scaling law predicted by the mean-field theory is violated at low frequency, and in the continuum limit, the vibrational modes converge to a mixture of phonon modes that follow the Debye law and soft localized modes that follow another universal non-Debye scaling law.

Air cushioning in drop impact

NASA Astrophysics Data System (ADS)

de Ruiter, Jolet; Oh, Jung; van den Ende, Dirk; Mugele, Frieder

2011-11-01

Liquid drops impacting on solid surfaces deform under the influence of the ambient gas that needs to be squeezed out before a true solid-liquid contact can be established. We demonstrate experimentally the existence of this theoretically predicted air layer and follow its evolution with time for moderate impact speeds (We ~ 1 ... 10) using reflection interference microscopy with a thickness resolution of approximately 10nm. For a wide range of fluid properties (ρ, γ, η) we find a very robust generic behavior that includes the predicted formation of a dimple in the center of the drop with a local minimum of the air film thickness at its boundary. Depending on We as well as the fluid properties, a skating layer of more or less constant thickness as well as a second local minimum of the air film thickness farther away from the drop center develop in time. Eventually, solid-liquid contact is generated via random nucleation event. The nucleation spot spreads across the drop-substrate interface within a few milliseconds. This process can lead to the entrapment of an air bubble.

Continuum limit of the vibrational properties of amorphous solids

PubMed Central

Mizuno, Hideyuki; Ikeda, Atsushi

2017-01-01

The low-frequency vibrational and low-temperature thermal properties of amorphous solids are markedly different from those of crystalline solids. This situation is counterintuitive because all solid materials are expected to behave as a homogeneous elastic body in the continuum limit, in which vibrational modes are phonons that follow the Debye law. A number of phenomenological explanations for this situation have been proposed, which assume elastic heterogeneities, soft localized vibrations, and so on. Microscopic mean-field theories have recently been developed to predict the universal non-Debye scaling law. Considering these theoretical arguments, it is absolutely necessary to directly observe the nature of the low-frequency vibrations of amorphous solids and determine the laws that such vibrations obey. Herein, we perform an extremely large-scale vibrational mode analysis of a model amorphous solid. We find that the scaling law predicted by the mean-field theory is violated at low frequency, and in the continuum limit, the vibrational modes converge to a mixture of phonon modes that follow the Debye law and soft localized modes that follow another universal non-Debye scaling law. PMID:29087941

DNA-linked NanoParticle Lattices with Diamond Symmetry: Stability, Shape and Optical Properties

NASA Astrophysics Data System (ADS)

Emamy, Hamed; Tkachenko, Alexei; Gang, Oleg; Starr, Francis

The linking of nanoparticles (NP) by DNA has been proven to be an effective means to create NP lattices with specific order. Lattices with diamond symmetry are predicted to offer novel photonic properties, but self-assembly of such lattices has proven to be challenging due to the low packing fraction, sensitivity to bond orientation, and local heterogeneity. Recently, we reported an approach to create diamond NP lattices based on the association between anisotropic particles with well-defined tetravalent DNA binding topology and isotropically functionalized NP. Here, we use molecular dynamics simulations to evaluate the Gibbs free energy of these lattices, and thereby determine the stability of these lattices as a function of NP size and DNA stiffness. We also predict the equilibrium shape for the cubic diamond crystallite using the Wulff construction method. Specifically, we predict the equilibrium shape using the surface energy for different crystallographic planes. We evaluate surface energy directly form molecular dynamics simulation, which we correlate with theoretical estimates from the expected number of broken DNA bonds along a facet. Furthermore we study the optical properties of this structure, e.g optical bandgap.

Spatial prediction of near surface soil water retention functions using hydrogeophysics and empirical orthogonal functions

NASA Astrophysics Data System (ADS)

Gibson, Justin; Franz, Trenton E.

2018-06-01

The hydrological community often turns to widely available spatial datasets such as the NRCS Soil Survey Geographic database (SSURGO) to characterize the spatial variability of soil properties. When used to spatially characterize and parameterize watershed models, this has served as a reasonable first approximation when lacking localized or incomplete soil data. Within agriculture, soil data has been left relatively coarse when compared to numerous other data sources measured. This is because localized soil sampling is both expensive and time intense, thus a need exists in better connecting spatial datasets with ground observations. Given that hydrogeophysics is data-dense, rapid, non-invasive, and relatively easy to adopt, it is a promising technique to help dovetail localized soil sampling with spatially exhaustive datasets. In this work, we utilize two common near surface geophysical methods, cosmic-ray neutron probe and electromagnetic induction, to identify temporally stable spatial patterns of measured geophysical properties in three 65 ha agricultural fields in western Nebraska. This is achieved by repeat geophysical observations of the same study area across a range of wet to dry field conditions in order to evaluate with an empirical orthogonal function. Shallow cores were then extracted within each identified zone and water retention functions were generated in the laboratory. Using EOF patterns as a covariate, we quantify the predictive skill of estimating soil hydraulic properties in areas without measurement using a bootstrap validation analysis. Results indicate that sampling locations informed via repeat hydrogeophysical surveys, required only five cores to reduce the cross-validation root mean squared error by an average of 64% as compared to soil parameters predicted by a commonly used benchmark, SSURGO and ROSETTA. The reduction to five strategically located samples within the 65 ha fields reduces sampling efforts by up to ∼90% as compared to the common practice of soil grid sampling every 1 ha.

Thermodynamic and Structural Properties of Methanol-Water Solutions Using Non-Additive Interaction Models

PubMed Central

Zhong, Yang; Warren, G. Lee; Patel, Sandeep

2014-01-01

We study bulk structural and thermodynamic properties of methanol-water solutions via molecular dynamics simulations using novel interaction potentials based on the charge equilibration (fluctuating charge) formalism to explicitly account for molecular polarization at the atomic level. The study uses the TIP4P-FQ potential for water-water interactions, and the CHARMM-based (Chemistry at HARvard Molecular Mechanics) fluctuating charge potential for methanol-methanol and methanol-water interactions. In terms of bulk solution properties, we discuss liquid densities, enthalpies of mixing, dielectric constants, self-diffusion constants, as well as structural properties related to local hydrogen bonding structure as manifested in radial distribution functions and cluster analysis. We further explore the electronic response of water and methanol in the differing local environments established by the interaction of each species predominantly with molecules of the other species. The current force field for the alcohol-water interaction performs reasonably well for most properties, with the greatest deviation from experiment observed for the excess mixing enthalpies, which are predicted to be too favorable. This is qualitatively consistent with the overestimation of the methanol-water gas-phase interaction energy for the lowest-energy conformer (methanol as proton donor). Hydration free energies for methanol in TIP4P-FQ water are predicted to be −5.6±0.2 kcal/mole, in respectable agreement with the experimental value of −5.1 kcal/mole. With respect to solution micro-structure, the present cluster analysis suggests that the micro-scale environment for concentrations where select thermodynamic quantities reach extremal values is described by a bi-percolating network structure. PMID:18074339

A high figure of merit localized surface plasmon sensor based on a gold nanograting on the top of a gold planar film

NASA Astrophysics Data System (ADS)

Zhang, Zu-Yin; Wang, Li-Na; Hu, Hai-Feng; Li, Kang-Wen; Ma, Xun-Peng; Song, Guo-Feng

2013-10-01

We investigate the sensitivity and figure of merit (FOM) of a localized surface plasmon (LSP) sensor with gold nanograting on the top of planar metallic film. The sensitivity of the localized surface plasmon sensor is 317 nm/RIU, and the FOM is predicted to be above 8, which is very high for a localized surface plasmon sensor. By employing the rigorous coupled-wave analysis (RCWA) method, we analyze the distribution of the magnetic field and find that the sensing property of our proposed system is attributed to the interactions between the localized surface plasmon around the gold nanostrips and the surface plasmon polarition on the surface of the gold planar metallic film. These findings are important for developing high FOM localized surface plasmon sensors.

Universities scale like cities.

PubMed

van Raan, Anthony F J

2013-01-01

Recent studies of urban scaling show that important socioeconomic city characteristics such as wealth and innovation capacity exhibit a nonlinear, particularly a power law scaling with population size. These nonlinear effects are common to all cities, with similar power law exponents. These findings mean that the larger the city, the more disproportionally they are places of wealth and innovation. Local properties of cities cause a deviation from the expected behavior as predicted by the power law scaling. In this paper we demonstrate that universities show a similar behavior as cities in the distribution of the 'gross university income' in terms of total number of citations over 'size' in terms of total number of publications. Moreover, the power law exponents for university scaling are comparable to those for urban scaling. We find that deviations from the expected behavior can indeed be explained by specific local properties of universities, particularly the field-specific composition of a university, and its quality in terms of field-normalized citation impact. By studying both the set of the 500 largest universities worldwide and a specific subset of these 500 universities--the top-100 European universities--we are also able to distinguish between properties of universities with as well as without selection of one specific local property, the quality of a university in terms of its average field-normalized citation impact. It also reveals an interesting observation concerning the working of a crucial property in networked systems, preferential attachment.

Life prediction of different commercial dental implants as influence by uncertainties in their fatigue material properties and loading conditions.

PubMed

Pérez, M A

2012-12-01

Probabilistic analyses allow the effect of uncertainty in system parameters to be determined. In the literature, many researchers have investigated static loading effects on dental implants. However, the intrinsic variability and uncertainty of most of the main problem parameters are not accounted for. The objective of this research was to apply a probabilistic computational approach to predict the fatigue life of three different commercial dental implants considering the variability and uncertainty in their fatigue material properties and loading conditions. For one of the commercial dental implants, the influence of its diameter in the fatigue life performance was also studied. This stochastic technique was based on the combination of a probabilistic finite element method (PFEM) and a cumulative damage approach known as B-model. After 6 million of loading cycles, local failure probabilities of 0.3, 0.4 and 0.91 were predicted for the Lifecore, Avinent and GMI implants, respectively (diameter of 3.75mm). The influence of the diameter for the GMI implant was studied and the results predicted a local failure probability of 0.91 and 0.1 for the 3.75mm and 5mm, respectively. In all cases the highest failure probability was located at the upper screw-threads. Therefore, the probabilistic methodology proposed herein may be a useful tool for performing a qualitative comparison between different commercial dental implants. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Progressive Failure Analysis of Composite Stiffened Panels

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Yarrington, Phillip W.; Collier, Craig S.; Arnold, Steven M.

2006-01-01

A new progressive failure analysis capability for stiffened composite panels has been developed based on the combination of the HyperSizer stiffened panel design/analysis/optimization software with the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC). MAC/GMC discretizes a composite material s microstructure into a number of subvolumes and solves for the stress and strain state in each while providing the homogenized composite properties as well. As a result, local failure criteria may be employed to predict local subvolume failure and the effects of these local failures on the overall composite response. When combined with HyperSizer, MAC/GMC is employed to represent the ply level composite material response within the laminates that constitute a stiffened panel. The effects of local subvolume failures can then be tracked as loading on the stiffened panel progresses. Sample progressive failure results are presented at both the composite laminate and the composite stiffened panel levels. Deformation and failure model predictions are compared with experimental data from the World Wide Failure Exercise for AS4/3501-6 graphite/epoxy laminates.

Local Patterns to Global Architectures: Influences of Network Topology on Human Learning.

PubMed

Karuza, Elisabeth A; Thompson-Schill, Sharon L; Bassett, Danielle S

2016-08-01

A core question in cognitive science concerns how humans acquire and represent knowledge about their environments. To this end, quantitative theories of learning processes have been formalized in an attempt to explain and predict changes in brain and behavior. We connect here statistical learning approaches in cognitive science, which are rooted in the sensitivity of learners to local distributional regularities, and network science approaches to characterizing global patterns and their emergent properties. We focus on innovative work that describes how learning is influenced by the topological properties underlying sensory input. The confluence of these theoretical approaches and this recent empirical evidence motivate the importance of scaling-up quantitative approaches to learning at both the behavioral and neural levels. Copyright © 2016 Elsevier Ltd. All rights reserved.

Towards soil property retrieval from space: Proof of concept using in situ observations

NASA Astrophysics Data System (ADS)

Bandara, Ranmalee; Walker, Jeffrey P.; Rüdiger, Christoph

2014-05-01

Soil moisture is a key variable that controls the exchange of water and energy fluxes between the land surface and the atmosphere. However, the temporal evolution of soil moisture is neither easy to measure nor monitor at large scales because of its high spatial variability. This is mainly a result of the local variation in soil properties and vegetation cover. Thus, land surface models are normally used to predict the evolution of soil moisture and yet, despite their importance, these models are based on low-resolution soil property information or typical values. Therefore, the availability of more accurate and detailed soil parameter data than are currently available is vital, if regional or global soil moisture predictions are to be made with the accuracy required for environmental applications. The proposed solution is to estimate the soil hydraulic properties via model calibration to remotely sensed soil moisture observation, with in situ observations used as a proxy in this proof of concept study. Consequently, the feasibility is assessed, and the level of accuracy that can be expected determined, for soil hydraulic property estimation of duplex soil profiles in a semi-arid environment using near-surface soil moisture observations under naturally occurring conditions. The retrieved soil hydraulic parameters were then assessed by their reliability to predict the root zone soil moisture using the Joint UK Land Environment Simulator model. When using parameters that were retrieved using soil moisture observations, the root zone soil moisture was predicted to within an accuracy of 0.04 m3/m3, which is an improvement of ∼0.025 m3/m3 on predictions that used published values or pedo-transfer functions.

Probing the localization of magnetic dichroism by atomic-size astigmatic and vortex electron beams

DOE PAGES

Negi, Devendra Singh; Idrobo, Juan Carlos; Rusz, Ján

2018-03-05

We report localization of a magnetic dichroic signal on atomic columns in electron magnetic circular dichroism (EMCD), probed by beam distorted by four-fold astigmatism and electron vortex beam. With astigmatic probe, magnetic signal to noise ratio can be enhanced by blocking the intensity from the central part of probe. However, the simulations show that for atomic resolution magnetic measurements, vortex beam is a more effective probe, with much higher magnetic signal to noise ratio. For all considered beam shapes, the optimal SNR constrains the signal detection at low collection angles of approximately 6–8 mrad. Irrespective of the material thickness, themore » magnetic signal remains strongly localized within the probed atomic column with vortex beam, whereas for astigmatic probes, the magnetic signal originates mostly from the nearest neighbor atomic columns. Due to excellent signal localization at probing individual atomic columns, vortex beams are predicted to be a strong candidate for studying the crystal site specific magnetic properties, magnetic properties at interfaces, or magnetism arising from individual atomic impurities.« less

Probing the localization of magnetic dichroism by atomic-size astigmatic and vortex electron beams

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

Negi, Devendra Singh; Idrobo, Juan Carlos; Rusz, Ján

We report localization of a magnetic dichroic signal on atomic columns in electron magnetic circular dichroism (EMCD), probed by beam distorted by four-fold astigmatism and electron vortex beam. With astigmatic probe, magnetic signal to noise ratio can be enhanced by blocking the intensity from the central part of probe. However, the simulations show that for atomic resolution magnetic measurements, vortex beam is a more effective probe, with much higher magnetic signal to noise ratio. For all considered beam shapes, the optimal SNR constrains the signal detection at low collection angles of approximately 6–8 mrad. Irrespective of the material thickness, themore » magnetic signal remains strongly localized within the probed atomic column with vortex beam, whereas for astigmatic probes, the magnetic signal originates mostly from the nearest neighbor atomic columns. Due to excellent signal localization at probing individual atomic columns, vortex beams are predicted to be a strong candidate for studying the crystal site specific magnetic properties, magnetic properties at interfaces, or magnetism arising from individual atomic impurities.« less

Dynamic evolutions of electron properties: A theoretical study for condensed-phase β-HMX under shock loading

NASA Astrophysics Data System (ADS)

He, Zheng-Hua; Chen, Jun; Wu, Qiang; Ji, Guang-Fu

2017-11-01

We present the density functional theory (DFT) calculations for microscopic electron properties of β-HMX under shock loading. The metallization pressure is determined to be within 30-55 GPa. The frontier molecular orbitals mainly localize on N-NO2 groups initially and disperse with pressure increase, while HOMO and LUMO orbitals trend to aggregate with each other. The deformation of N-NO2 groups and enhanced hydrogen-bonding interactions cause the electron delocalization and lower the band gap, inducing the reaction initiation finally. Our results show that using the electron properties can reliably predict the initial decomposition of energetic materials under shock loading.

Mathematical modeling analysis of intratumoral disposition of anticancer agents and drug delivery systems.

PubMed

Popilski, Hen; Stepensky, David

2015-05-01

Solid tumors are characterized by complex morphology. Numerous factors relating to the composition of the cells and tumor stroma, vascularization and drainage of fluids affect the local microenvironment within a specific location inside the tumor. As a result, the intratumoral drug/drug delivery system (DDS) disposition following systemic or local administration is non-homogeneous and its complexity reflects the differences in the local microenvironment. Mathematical models can be used to analyze the intratumoral drug/DDS disposition and pharmacological effects and to assist in choice of optimal anticancer treatment strategies. The mathematical models that have been applied by different research groups to describe the intratumoral disposition of anticancer drugs/DDSs are summarized in this article. The properties of these models and of their suitability for prediction of the drug/DDS intratumoral disposition and pharmacological effects are reviewed. Currently available mathematical models appear to neglect some of the major factors that govern the drug/DDS intratumoral disposition, and apparently possess limited prediction capabilities. More sophisticated and detailed mathematical models and their extensive validation are needed for reliable prediction of different treatment scenarios and for optimization of drug treatment in the individual cancer patients.

Analysis of Fiber Clustering in Composite Materials Using High-Fidelity Multiscale Micromechanics

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Aboudi, Jacob; Arnold, Steven M.

2015-01-01

A new multiscale micromechanical approach is developed for the prediction of the behavior of fiber reinforced composites in presence of fiber clustering. The developed method is based on a coupled two-scale implementation of the High-Fidelity Generalized Method of Cells theory, wherein both the local and global scales are represented using this micromechanical method. Concentration tensors and effective constitutive equations are established on both scales and linked to establish the required coupling, thus providing the local fields throughout the composite as well as the global properties and effective nonlinear response. Two nondimensional parameters, in conjunction with actual composite micrographs, are used to characterize the clustering of fibers in the composite. Based on the predicted local fields, initial yield and damage envelopes are generated for various clustering parameters for a polymer matrix composite with both carbon and glass fibers. Nonlinear epoxy matrix behavior is also considered, with results in the form of effective nonlinear response curves, with varying fiber clustering and for two sets of nonlinear matrix parameters.

Lagrangian statistics of mesoscale turbulence in a natural environment: The Agulhas return current.

PubMed

Carbone, Francesco; Gencarelli, Christian N; Hedgecock, Ian M

2016-12-01

The properties of mesoscale geophysical turbulence in an oceanic environment have been investigated through the Lagrangian statistics of sea surface temperature measured by a drifting buoy within the Agulhas return current, where strong temperature mixing produces locally sharp temperature gradients. By disentangling the large-scale forcing which affects the small-scale statistics, we found that the statistical properties of intermittency are identical to those obtained from the multifractal prediction in the Lagrangian frame for the velocity trajectory. The results suggest a possible universality of turbulence scaling.

Consideration of some factors affecting low-frequency fuselage noise transmission for propeller aircraft

NASA Technical Reports Server (NTRS)

Mixson, J. S.; Roussos, L. A.

1986-01-01

Possible reasons for disagreement between measured and predicted trends of sidewall noise transmission at low frequency are investigated using simplified analysis methods. An analytical model combining incident plane acoustic waves with an infinite flat panel is used to study the effects of sound incidence angle, plate structural properties, frequency, absorption, and the difference between noise reduction and transmission loss. Analysis shows that these factors have significant effects on noise transmission but they do not account for the differences between measured and predicted trends at low frequencies. An analytical model combining an infinite flat plate with a normally incident acoustic wave having exponentially decaying magnitude along one coordinate is used to study the effect of a localized source distribution such as is associated with propeller noise. Results show that the localization brings the predicted low-frequency trend of noise transmission into better agreement with measured propeller results. This effect is independent of low-frequency stiffness effects that have been previously reported to be associated with boundary conditions.

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

Schultz, Peter A.

For the purposes of making reliable first-principles predictions of defect energies in semiconductors, it is crucial to distinguish between effective-mass-like defects, which cannot be treated accurately with existing supercell methods, and deep defects, for which density functional theory calculations can yield reliable predictions of defect energy levels. The gallium antisite defect GaAs is often associated with the 78/203 meV shallow double acceptor in Ga-rich gallium arsenide. Within a conceptual framework of level patterns, analyses of structure and spin stabilization can be used within a supercell approach to distinguish localized deep defect states from shallow acceptors such as B As. Thismore » systematic approach determines that the gallium antisite supercell results has signatures inconsistent with an effective mass state and cannot be the 78/203 shallow double acceptor. Lastly, the properties of the Ga antisite in GaAs are described, total energy calculations that explicitly map onto asymptotic discrete localized bulk states predict that the Ga antisite is a deep double acceptor and has at least one deep donor state.« less

Quasi-particle energy spectra in local reduced density matrix functional theory.

PubMed

Lathiotakis, Nektarios N; Helbig, Nicole; Rubio, Angel; Gidopoulos, Nikitas I

2014-10-28

Recently, we introduced [N. N. Lathiotakis, N. Helbig, A. Rubio, and N. I. Gidopoulos, Phys. Rev. A 90, 032511 (2014)] local reduced density matrix functional theory (local RDMFT), a theoretical scheme capable of incorporating static correlation effects in Kohn-Sham equations. Here, we apply local RDMFT to molecular systems of relatively large size, as a demonstration of its computational efficiency and its accuracy in predicting single-electron properties from the eigenvalue spectrum of the single-particle Hamiltonian with a local effective potential. We present encouraging results on the photoelectron spectrum of molecular systems and the relative stability of C20 isotopes. In addition, we propose a modelling of the fractional occupancies as functions of the orbital energies that further improves the efficiency of the method useful in applications to large systems and solids.

On the role of fluctuations in the modeling of complex systems.

NASA Astrophysics Data System (ADS)

Droz, Michel; Pekalski, Andrzej

2016-09-01

The study of models is ubiquitous in sciences like physics, chemistry, ecology, biology or sociology. Models are used to explain experimental facts or to make new predictions. For any system, one can distinguish several levels of description. In the simplest mean-field like description the dynamics is described in terms of spatially averaged quantities while in a microscopic approach local properties are taken into account and local fluctuations for the relevant variables are present. The properties predicted by these two different approaches may be drastically different. In a large body of research literature concerning complex systems this problem is often overlooked and simple mean-field like approximation are used without asking the question of the robustness of the corresponding predictions. The goal of this paper is twofold, first to illustrate the importance of the fluctuations in a self-contained and pedagogical way, by revisiting two different classes of problems where thorough investigations have been conducted (equilibrium and non-equilibrium statistical physics). Second, we present our original research on the dynamics of population of annual plants which are competing among themselves for just one resource (water) through a stochastic dynamics. Depending on the observable considered, the mean-field like and microscopic approaches agree or totally disagree. There is not a general criterion allowing to decide a priori when the two approaches will agree.

Macro-architectured cellular materials: Properties, characteristic modes, and prediction methods

NASA Astrophysics Data System (ADS)

Ma, Zheng-Dong

2017-12-01

Macro-architectured cellular (MAC) material is defined as a class of engineered materials having configurable cells of relatively large (i.e., visible) size that can be architecturally designed to achieve various desired material properties. Two types of novel MAC materials, negative Poisson's ratio material and biomimetic tendon reinforced material, were introduced in this study. To estimate the effective material properties for structural analyses and to optimally design such materials, a set of suitable homogenization methods was developed that provided an effective means for the multiscale modeling of MAC materials. First, a strain-based homogenization method was developed using an approach that separated the strain field into a homogenized strain field and a strain variation field in the local cellular domain superposed on the homogenized strain field. The principle of virtual displacements for the relationship between the strain variation field and the homogenized strain field was then used to condense the strain variation field onto the homogenized strain field. The new method was then extended to a stress-based homogenization process based on the principle of virtual forces and further applied to address the discrete systems represented by the beam or frame structures of the aforementioned MAC materials. The characteristic modes and the stress recovery process used to predict the stress distribution inside the cellular domain and thus determine the material strengths and failures at the local level are also discussed.

The rheology and microstructure of aging thermoreversible colloidal gels & attractive driven glasses

NASA Astrophysics Data System (ADS)

Wagner, Norman; Gordon, Melissa; Kloxin, Christopher

The properties of colloidal gels and glasses are known to change with age, but the particle-level mechanisms by which aging occurs is are fully understood, which limits our ability to predict macroscopic behavior in these systems. In this work, we quantitatively relate rheological aging to structural aging of a model, homogenous gel and attractive driven glass by simultaneously measuring the bulk properties and gel microstructure using rheometry and small angle neutron scattering (Rheo-SANS), respectively. Specifically, we develop a quantitative and predictive relationship between the macroscopic properties and the underlying microstructure (i . e . , the effective strength of attraction) of an aging colloidal gel and attractive driven glass and study it as a function of the thermal and shear history. Analysis with mode coupling theory is consistent with local particle rearrangements as the mechanism of aging, which lead to monotonically increasing interaction strengths in a continuously evolving material and strongly supports aging as a trajectory in the free energy landscape dominated by local particle relaxations. The analyses and conclusions of this study may be 1) industrially relevant to products that age on commercial timescales, such as paints and pharmaceuticals, 2) applicable to other dynamically arrested systems, such as metallic glasses, and 3) used in the design of new materials. NIST Center for Neutron Research CNS cooperative agreement number #70NANB12H239 and NASA Grant No. NNX15AI19H.

Exploiting Locality in Quantum Computation for Quantum Chemistry.

PubMed

McClean, Jarrod R; Babbush, Ryan; Love, Peter J; Aspuru-Guzik, Alán

2014-12-18

Accurate prediction of chemical and material properties from first-principles quantum chemistry is a challenging task on traditional computers. Recent developments in quantum computation offer a route toward highly accurate solutions with polynomial cost; however, this solution still carries a large overhead. In this Perspective, we aim to bring together known results about the locality of physical interactions from quantum chemistry with ideas from quantum computation. We show that the utilization of spatial locality combined with the Bravyi-Kitaev transformation offers an improvement in the scaling of known quantum algorithms for quantum chemistry and provides numerical examples to help illustrate this point. We combine these developments to improve the outlook for the future of quantum chemistry on quantum computers.

Combining Satellite Measurements and Numerical Flood Prediction Models to Save Lives and Property from Flooding

NASA Astrophysics Data System (ADS)

Saleh, F.; Garambois, P. A.; Biancamaria, S.

2017-12-01

Floods are considered the major natural threats to human societies across all continents. Consequences of floods in highly populated areas are more dramatic with losses of human lives and substantial property damage. This risk is projected to increase with the effects of climate change, particularly sea-level rise, increasing storm frequencies and intensities and increasing population and economic assets in such urban watersheds. Despite the advances in computational resources and modeling techniques, significant gaps exist in predicting complex processes and accurately representing the initial state of the system. Improving flood prediction models and data assimilation chains through satellite has become an absolute priority to produce accurate flood forecasts with sufficient lead times. The overarching goal of this work is to assess the benefits of the Surface Water Ocean Topography SWOT satellite data from a flood prediction perspective. The near real time methodology is based on combining satellite data from a simulator that mimics the future SWOT data, numerical models, high resolution elevation data and real-time local measurement in the New York/New Jersey area.

Prediction and characterization of heat-affected zone formation in tin-bismuth alloys due to nickel-aluminum multilayer foil reaction

DOE PAGES

Hooper, R. J.; Davis, C. G.; Johns, P. M.; ...

2015-06-26

Reactive multilayer foils have the potential to be used as local high intensity heat sources for a variety of applications. In this study, most of the past research effort concerning these materials have focused on understanding the structure-property relationships of the foils that govern the energy released during a reaction. To improve the ability of researchers to more rapidly develop technologies based on reactive multilayer foils, a deeper and more predictive understanding of the relationship between the heat released from the foil and microstructural evolution in the neighboring materials is needed. This work describes the development of a numerical modelmore » for the purpose of predicting heat affected zone size in substrate materials. The model is experimentally validated using a commercially available Ni-Al multilayer foils and alloys from the Sn-Bi binary system. To accomplish this, phenomenological models for predicting the variation of physical properties (i.e., thermal conductivity, density, and heat capacity) with temperature and composition in the Sn-Bi system were utilized using literature data.« less

Decoupling the Effects of Mass Density and Hydrogen-, Oxygen-, and Aluminum-Based Defects on Optoelectronic Properties of Realistic Amorphous Alumina.

PubMed

Riffet, Vanessa; Vidal, Julien

2017-06-01

The search for functional materials is currently hindered by the difficulty to find significant correlation between constitutive properties of a material and its functional properties. In the case of amorphous materials, the diversity of local structures, chemical composition, impurities and mass densities makes such a connection difficult to be addressed. In this Letter, the relation between refractive index and composition has been investigated for amorphous AlO x materials, including nonstoichiometric AlO x , emphasizing the role of structural defects and the absence of effect of the band gap variation. It is found that the Newton-Drude (ND) relation predicts the refractive index from mass density with a rather high level of precision apart from some structures displaying structural defects. Our results show especially that O- and Al-based defects act as additive local disturbance in the vicinity of band gap, allowing us to decouple the mass density effects from defect effects (n = n[ND] + Δn defect ).

Nanoscale hotspots due to nonequilibrium thermal transport.

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

Sinha, Sanjiv; Goodson, Kenneth E.

2004-01-01

Recent experimental and modeling efforts have been directed towards the issue of temperature localization and hotspot formation in the vicinity of nanoscale heat generating devices. The nonequilibrium transport conditions which develop around these nanoscale devices results in elevated temperatures near the heat source which can not be predicted by continuum diffusion theory. Efforts to determine the severity of this temperature localization phenomena in silicon devices near and above room temperature are of technological importance to the development of microelectronics and other nanotechnologies. In this work, we have developed a new modeling tool in order to explore the magnitude of themore » additional thermal resistance which forms around nanoscale hotspots from temperatures of 100-1000K. The models are based on a two fluid approximation in which thermal energy is transferred between ''stationary'' optical phonons and fast propagating acoustic phonon modes. The results of the model have shown excellent agreement with experimental results of localized hotspots in silicon at lower temperatures. The model predicts that the effect of added thermal resistance due to the nonequilibrium phonon distribution is greatest at lower temperatures, but is maintained out to temperatures of 1000K. The resistance predicted by the numerical code can be easily integrated with continuum models in order to predict the temperature distribution around nanoscale heat sources with improved accuracy. Additional research efforts also focused on the measurements of the thermal resistance of silicon thin films at higher temperatures, with a focus on polycrystalline silicon. This work was intended to provide much needed experimental data on the thermal transport properties for micro and nanoscale devices built with this material. Initial experiments have shown that the exposure of polycrystalline silicon to high temperatures may induce recrystallization and radically increase the thermal transport properties at room temperature. In addition, the defect density was observed to play a major role in the rate of change in thermal resistivity as a function of temperature.« less

Toward an Integrative Computational Model of the Guinea Pig Cardiac Myocyte

PubMed Central

Gauthier, Laura Doyle; Greenstein, Joseph L.; Winslow, Raimond L.

2012-01-01

The local control theory of excitation-contraction (EC) coupling asserts that regulation of calcium (Ca2+) release occurs at the nanodomain level, where openings of single L-type Ca2+ channels (LCCs) trigger openings of small clusters of ryanodine receptors (RyRs) co-localized within the dyad. A consequence of local control is that the whole-cell Ca2+ transient is a smooth continuous function of influx of Ca2+ through LCCs. While this so-called graded release property has been known for some time, its functional importance to the integrated behavior of the cardiac ventricular myocyte has not been fully appreciated. We previously formulated a biophysically based model, in which LCCs and RyRs interact via a coarse-grained representation of the dyadic space. The model captures key features of local control using a low-dimensional system of ordinary differential equations. Voltage-dependent gain and graded Ca2+ release are emergent properties of this model by virtue of the fact that model formulation is closely based on the sub-cellular basis of local control. In this current work, we have incorporated this graded release model into a prior model of guinea pig ventricular myocyte electrophysiology, metabolism, and isometric force production. The resulting integrative model predicts the experimentally observed causal relationship between action potential (AP) shape and timing of Ca2+ and force transients, a relationship that is not explained by models lacking the graded release property. Model results suggest that even relatively subtle changes in AP morphology that may result, for example, from remodeling of membrane transporter expression in disease or spatial variation in cell properties, may have major impact on the temporal waveform of Ca2+ transients, thus influencing tissue level electromechanical function. PMID:22783206

Toward an integrative computational model of the Guinea pig cardiac myocyte.

PubMed

Gauthier, Laura Doyle; Greenstein, Joseph L; Winslow, Raimond L

2012-01-01

The local control theory of excitation-contraction (EC) coupling asserts that regulation of calcium (Ca(2+)) release occurs at the nanodomain level, where openings of single L-type Ca(2+) channels (LCCs) trigger openings of small clusters of ryanodine receptors (RyRs) co-localized within the dyad. A consequence of local control is that the whole-cell Ca(2+) transient is a smooth continuous function of influx of Ca(2+) through LCCs. While this so-called graded release property has been known for some time, its functional importance to the integrated behavior of the cardiac ventricular myocyte has not been fully appreciated. We previously formulated a biophysically based model, in which LCCs and RyRs interact via a coarse-grained representation of the dyadic space. The model captures key features of local control using a low-dimensional system of ordinary differential equations. Voltage-dependent gain and graded Ca(2+) release are emergent properties of this model by virtue of the fact that model formulation is closely based on the sub-cellular basis of local control. In this current work, we have incorporated this graded release model into a prior model of guinea pig ventricular myocyte electrophysiology, metabolism, and isometric force production. The resulting integrative model predicts the experimentally observed causal relationship between action potential (AP) shape and timing of Ca(2+) and force transients, a relationship that is not explained by models lacking the graded release property. Model results suggest that even relatively subtle changes in AP morphology that may result, for example, from remodeling of membrane transporter expression in disease or spatial variation in cell properties, may have major impact on the temporal waveform of Ca(2+) transients, thus influencing tissue level electromechanical function.

Potential of EnMAP spaceborne imaging spectroscopy for the prediction of common surface soil properties and expected accuracy

NASA Astrophysics Data System (ADS)

Chabrillat, Sabine; Foerster, Saskia; Steinberg, Andreas; Stevens, Antoine; Segl, Karl

2016-04-01

There is a renewed awareness of the finite nature of the world's soil resources, growing concern about soil security, and significant uncertainties about the carrying capacity of the planet. As a consequence, soil scientists are being challenged to provide regular assessments of soil conditions from local through to global scales. However, only a few countries have the necessary survey and monitoring programs to meet these new needs and existing global data sets are out-of-date. A particular issue is the clear demand for a new area-wide regional to global coverage with accurate, up-to-date, and spatially referenced soil information as expressed by the modeling scientific community, farmers and land users, and policy and decision makers. Soil spectroscopy from remote sensing observations based on studies from the laboratory scale to the airborne scale has been shown to be a proven method for the quantitative prediction of key soil surface properties in local areas for exposed soils in appropriate surface conditions such as low vegetation cover and low water content. With the upcoming launch of the next generation of hyperspectral satellite sensors in the next 3 to 5 years (EnMAP, HISUI, PRISMA, SHALOM), a great potential for the global mapping and monitoring of soil properties is appearing. Nevertheless, the capabilities to extend the soil properties current spectral modeling from local to regional scales are still to be demonstrated using robust methods. In particular, three central questions are at the forefront of research nowadays: a) methodological developments toward improved algorithms and operational tools for the extraction of soil properties, b) up scaling from the laboratory into space domain, and c) demonstration of the potential of upcoming satellite systems and expected accuracy of soil maps. In this study, airborne imaging spectroscopy data from several test sites are used to simulate EnMAP satellite images at 30 m scale. Then, different soil algorithms are examined based on the analyses of chemical-physical features from the soil spectral reflectance and/or multivariate established techniques such as Partial-Least Squares PLS, Support-Vector Machine SVM, to determine common surface soil properties, in particular soil organic carbon (SOC), clay and iron oxide content. Results show that EnMAP is able to predict clay, free iron oxide, and SOC with an RV2 between 0.53 and 0.67 compared to airborne imagery with RV2 between 0.64 and 0.74. The correlation between EnMAP and airborne imagery prediction results is high (Pearson coefficients between 0.84 and 0.91). Furthermore, spatial distribution is coherent between the airborne mapping and simulated EnMAP mapping as shown with a spatial structure analysis. In general, this paper demonstrates the high potential of upcoming spaceborne hyperspectral missions for soil science studies but also shows the need for future adapted strategies to fulfill the entire potential of soil spectroscopy for orbital utilization.

High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models.

PubMed

Forkuor, Gerald; Hounkpatin, Ozias K L; Welp, Gerhard; Thiel, Michael

2017-01-01

Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties-sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen-in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models-multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)-were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness, coloration and saturation were prominent predictors in digital soil mapping. Considering the increased availability of freely available Remote Sensing data (e.g. Landsat, SRTM, Sentinels), soil information at local and regional scales in data poor regions such as West Africa can be improved with relatively little financial and human resources.

Vortex shedding from obstacles: theoretical frequency prediction

NASA Astrophysics Data System (ADS)

Pier, Benoît

2001-11-01

The existence of self-sustained oscillations in spatially developing systems is closely related to the presence of a locally absolutely unstable region. A recent investigation of a ``synthetic wake'' (a wake with no solid obstacle and no reverse flow region) has proved [Pier and Huerre, J. Fluid Mech. 435, 145 (2001)] that the observed Kármán vortex street is a nonlinear elephant global mode. The same criterion is now shown to hold for real obstacles. Local properties are derived from the unperturbed basic flow computed by enforcing a symmetry condition on the central line. Application of the theoretical criterion then yields the expected Strouhal vortex shedding frequency. The thus predicted frequency is in excellent agreement with direct numerical simulations of the complete flow. The use of the frequency selection mechanism to control the vortex shedding will also be discussed.

Coupling between apical tension and basal adhesion allow epithelia to collectively sense and respond to substrate topography over long distances.

PubMed

Broaders, Kyle E; Cerchiari, Alec E; Gartner, Zev J

2015-12-01

Epithelial sheets fold into complex topographies that contribute to their function in vivo. Cells can sense and respond to substrate topography in their immediate vicinity by modulating their interfacial mechanics, but the extent to which these mechanical properties contribute to their ability to sense substrate topography across length scales larger than a single cell has not been explored in detail. To study the relationship between the interfacial mechanics of single cells and their collective behavior as tissues, we grew cell-sheets on substrates engraved with surface features spanning macroscopic length-scales. We found that many epithelial cell-types sense and respond to substrate topography, even when it is locally nearly planar. Cells clear or detach from regions of local negative curvature, but not from regions with positive or no curvature. We investigated this phenomenon using a finite element model where substrate topography is coupled to epithelial response through a balance of tissue contractility and adhesive forces. The model correctly predicts the focal sites of cell-clearing and epithelial detachment. Furthermore, the model predicts that local tissue response to substrate curvature is a function of the surrounding topography of the substrate across long distances. Analysis of cell-cell and cell-substrate contact angles suggests a relationship between these single-cell interfacial properties, epithelial interfacial properties, and collective epithelial response to substrate topography. Finally, we show that contact angles change upon activation of oncogenes or inhibition of cell-contractility, and that these changes correlate with collective epithelial response. Our results demonstrate that in mechanically integrated epithelial sheets, cell contractility can be transmitted through multiple cells and focused by substrate topography to affect a behavioral response at distant sites.

Optical Properties of the Crescent–Shaped Nanohole Antenna

PubMed Central

Wu, Liz Y.; Ross, Benjamin M.; Lee, Luke P.

2009-01-01

We present the first optical study of large–area random arrays of crescent–shaped nanoholes. The crescent–shaped nanohole antennae, fabricated using wafer–scale nanosphere lithography, provide a complement to crescent–shaped nanostructures, called nanocrescents, which have been established as powerful plasmonic biosensors. With both systematic experimental and computational analysis, we characterize the optical properties of crescent–shaped nanohole antennae, and demonstrate tunability of their optical response by varying all key geometric parameters. Crescent–shaped nanoholes have reproducible sub–10 nm tips and are sharper than corresponding nanocrescents, resulting in higher local field enhancement (LFE), which is predicted to be |E|/|E0| = 1500. In addition, the crescent–shaped nanohole hole–based geometry offers increased integratability and the potential to nanoconfine analyte in “hot–spot” regions—increasing biomolecular sensitivity and allowing localized nanoscale optical control of biological functions. PMID:19354226

Enhancing membrane protein subcellular localization prediction by parallel fusion of multi-view features.

PubMed

Yu, Dongjun; Wu, Xiaowei; Shen, Hongbin; Yang, Jian; Tang, Zhenmin; Qi, Yong; Yang, Jingyu

2012-12-01

Membrane proteins are encoded by ~ 30% in the genome and function importantly in the living organisms. Previous studies have revealed that membrane proteins' structures and functions show obvious cell organelle-specific properties. Hence, it is highly desired to predict membrane protein's subcellular location from the primary sequence considering the extreme difficulties of membrane protein wet-lab studies. Although many models have been developed for predicting protein subcellular locations, only a few are specific to membrane proteins. Existing prediction approaches were constructed based on statistical machine learning algorithms with serial combination of multi-view features, i.e., different feature vectors are simply serially combined to form a super feature vector. However, such simple combination of features will simultaneously increase the information redundancy that could, in turn, deteriorate the final prediction accuracy. That's why it was often found that prediction success rates in the serial super space were even lower than those in a single-view space. The purpose of this paper is investigation of a proper method for fusing multiple multi-view protein sequential features for subcellular location predictions. Instead of serial strategy, we propose a novel parallel framework for fusing multiple membrane protein multi-view attributes that will represent protein samples in complex spaces. We also proposed generalized principle component analysis (GPCA) for feature reduction purpose in the complex geometry. All the experimental results through different machine learning algorithms on benchmark membrane protein subcellular localization datasets demonstrate that the newly proposed parallel strategy outperforms the traditional serial approach. We also demonstrate the efficacy of the parallel strategy on a soluble protein subcellular localization dataset indicating the parallel technique is flexible to suite for other computational biology problems. The software and datasets are available at: http://www.csbio.sjtu.edu.cn/bioinf/mpsp.

Beyond local effective material properties for metamaterials

NASA Astrophysics Data System (ADS)

Mnasri, K.; Khrabustovskyi, A.; Stohrer, C.; Plum, M.; Rockstuhl, C.

2018-02-01

To discuss the properties of metamaterials on physical grounds and to consider them in applications, effective material parameters are usually introduced and assigned to a given metamaterial. In most cases, only weak spatial dispersion is considered. It allows to assign local material properties, e.g., a permittivity and a permeability. However, this turned out to be insufficient. To solve this problem, we study here the effective properties of metamaterials with constitutive relations beyond a local response and take strong spatial dispersion into account. This research requires two contributions. First, bulk properties in terms of eigenmodes need to be studied. We particularly investigate the isofrequency surfaces of their dispersion relation are investigated and compared to those of an actual metamaterial. The significant improvement to effectively describe it provides evidence for the necessity to use nonlocal material laws in the effective description of metamaterials. Second, to be able to capitalize on such constitutive relations, also interface conditions need to be known. They are derived in this contribution for our form of the nonlocality using a generalized (weak) formulation of Maxwell's equations. Based on such interface conditions, Fresnel expressions are obtained that predict the amplitude of the reflected and transmitted plane wave upon illuminating a slab of such a nonlocal metamaterial. This all together offers the necessary means for the in-depth analysis of metamaterials characterized by strong spatial dispersion. The general formulation we choose here renders our approach applicable to a wide class of metamaterials.

Universities Scale Like Cities

PubMed Central

van Raan, Anthony F. J.

2013-01-01

Recent studies of urban scaling show that important socioeconomic city characteristics such as wealth and innovation capacity exhibit a nonlinear, particularly a power law scaling with population size. These nonlinear effects are common to all cities, with similar power law exponents. These findings mean that the larger the city, the more disproportionally they are places of wealth and innovation. Local properties of cities cause a deviation from the expected behavior as predicted by the power law scaling. In this paper we demonstrate that universities show a similar behavior as cities in the distribution of the ‘gross university income’ in terms of total number of citations over ‘size’ in terms of total number of publications. Moreover, the power law exponents for university scaling are comparable to those for urban scaling. We find that deviations from the expected behavior can indeed be explained by specific local properties of universities, particularly the field-specific composition of a university, and its quality in terms of field-normalized citation impact. By studying both the set of the 500 largest universities worldwide and a specific subset of these 500 universities -the top-100 European universities- we are also able to distinguish between properties of universities with as well as without selection of one specific local property, the quality of a university in terms of its average field-normalized citation impact. It also reveals an interesting observation concerning the working of a crucial property in networked systems, preferential attachment. PMID:23544062

Predicting surface vibration from underground railways through inhomogeneous soil

NASA Astrophysics Data System (ADS)

Jones, Simon; Hunt, Hugh

2012-04-01

Noise and vibration from underground railways is a major source of disturbance to inhabitants near subways. To help designers meet noise and vibration limits, numerical models are used to understand vibration propagation from these underground railways. However, the models commonly assume the ground is homogeneous and neglect to include local variability in the soil properties. Such simplifying assumptions add a level of uncertainty to the predictions which is not well understood. The goal of the current paper is to quantify the effect of soil inhomogeneity on surface vibration. The thin-layer method (TLM) is suggested as an efficient and accurate means of simulating vibration from underground railways in arbitrarily layered half-spaces. Stochastic variability of the soil's elastic modulus is introduced using a K-L expansion; the modulus is assumed to have a log-normal distribution and a modified exponential covariance kernel. The effect of horizontal soil variability is investigated by comparing the stochastic results for soils varied only in the vertical direction to soils with 2D variability. Results suggest that local soil inhomogeneity can significantly affect surface velocity predictions; 90 percent confidence intervals showing 8 dB averages and peak values up to 12 dB are computed. This is a significant source of uncertainty and should be considered when using predictions from models assuming homogeneous soil properties. Furthermore, the effect of horizontal variability of the elastic modulus on the confidence interval appears to be negligible. This suggests that only vertical variation needs to be taken into account when modelling ground vibration from underground railways.

Prediction of Building Limestone Physical and Mechanical Properties by Means of Ultrasonic P-Wave Velocity

PubMed Central

Concu, Giovanna; De Nicolo, Barbara; Valdes, Monica

2014-01-01

The aim of this study was to evaluate ultrasonic P-wave velocity as a feature for predicting some physical and mechanical properties that describe the behavior of local building limestone. To this end, both ultrasonic testing and compressive tests were carried out on several limestone specimens and statistical correlation between ultrasonic velocity and density, compressive strength, and modulus of elasticity was studied. The effectiveness of ultrasonic velocity was evaluated by regression, with the aim of observing the coefficient of determination r 2 between ultrasonic velocity and the aforementioned parameters, and the mathematical expressions of the correlations were found and discussed. The strong relations that were established between ultrasonic velocity and limestone properties indicate that these parameters can be reasonably estimated by means of this nondestructive parameter. This may be of great value in a preliminary phase of the diagnosis and inspection of stone masonry conditions, especially when the possibility of sampling material cores is reduced. PMID:24511286

Prediction of building limestone physical and mechanical properties by means of ultrasonic P-wave velocity.

PubMed

Concu, Giovanna; De Nicolo, Barbara; Valdes, Monica

2014-01-01

The aim of this study was to evaluate ultrasonic P-wave velocity as a feature for predicting some physical and mechanical properties that describe the behavior of local building limestone. To this end, both ultrasonic testing and compressive tests were carried out on several limestone specimens and statistical correlation between ultrasonic velocity and density, compressive strength, and modulus of elasticity was studied. The effectiveness of ultrasonic velocity was evaluated by regression, with the aim of observing the coefficient of determination r(2) between ultrasonic velocity and the aforementioned parameters, and the mathematical expressions of the correlations were found and discussed. The strong relations that were established between ultrasonic velocity and limestone properties indicate that these parameters can be reasonably estimated by means of this nondestructive parameter. This may be of great value in a preliminary phase of the diagnosis and inspection of stone masonry conditions, especially when the possibility of sampling material cores is reduced.

Hybrid density functional theory band structure engineering in hematite

NASA Astrophysics Data System (ADS)

Pozun, Zachary D.; Henkelman, Graeme

2011-06-01

We present a hybrid density functional theory (DFT) study of doping effects in α-Fe2O3, hematite. Standard DFT underestimates the band gap by roughly 75% and incorrectly identifies hematite as a Mott-Hubbard insulator. Hybrid DFT accurately predicts the proper structural, magnetic, and electronic properties of hematite and, unlike the DFT+U method, does not contain d-electron specific empirical parameters. We find that using a screened functional that smoothly transitions from 12% exact exchange at short ranges to standard DFT at long range accurately reproduces the experimental band gap and other material properties. We then show that the antiferromagnetic symmetry in the pure α-Fe2O3 crystal is broken by all dopants and that the ligand field theory correctly predicts local magnetic moments on the dopants. We characterize the resulting band gaps for hematite doped by transition metals and the p-block post-transition metals. The specific case of Pd doping is investigated in order to correlate calculated doping energies and optical properties with experimentally observed photocatalytic behavior.

Strain-Dependent Edge Structures in MoS2 Layers.

PubMed

Tinoco, Miguel; Maduro, Luigi; Masaki, Mukai; Okunishi, Eiji; Conesa-Boj, Sonia

2017-11-08

Edge structures are low-dimensional defects unavoidable in layered materials of the transition metal dichalcogenides (TMD) family. Among the various types of such structures, the armchair (AC) and zigzag (ZZ) edge types are the most common. It has been predicted that the presence of intrinsic strain localized along these edges structures can have direct implications for the customization of their electronic properties. However, pinning down the relation between local structure and electronic properties at these edges is challenging. Here, we quantify the local strain field that arises at the edges of MoS 2 flakes by combining aberration-corrected transmission electron microscopy (TEM) with the geometrical-phase analysis (GPA) method. We also provide further insight on the possible effects of such edge strain on the resulting electronic behavior by means of electron energy loss spectroscopy (EELS) measurements. Our results reveal that the two-dominant edge structures, ZZ and AC, induce the formation of different amounts of localized strain fields. We also show that by varying the free edge curvature from concave to convex, compressive strain turns into tensile strain. These results pave the way toward the customization of edge structures in MoS 2 , which can be used to engineer the properties of layered materials and thus contribute to the optimization of the next generation of atomic-scale electronic devices built upon them.

From local uncertainty to global predictions: Making predictions on fractal basins

PubMed Central

2018-01-01

In nonlinear systems long term dynamics is governed by the attractors present in phase space. The presence of a chaotic saddle gives rise to basins of attraction with fractal boundaries and sometimes even to Wada boundaries. These two phenomena involve extreme difficulties in the prediction of the future state of the system. However, we show here that it is possible to make statistical predictions even if we do not have any previous knowledge of the initial conditions or the time series of the system until it reaches its final state. In this work, we develop a general method to make statistical predictions in systems with fractal basins. In particular, we have applied this new method to the Duffing oscillator for a choice of parameters where the system possesses the Wada property. We have computed the statistical properties of the Duffing oscillator for different phase space resolutions, to obtain information about the global dynamics of the system. The key idea is that the fraction of initial conditions that evolve towards each attractor is scale free—which we illustrate numerically. We have also shown numerically how having partial information about the initial conditions of the system does not improve in general the predictions in the Wada regions. PMID:29668687

Partial Shade Stress Test for Thin-Film Photovoltaic Modules: Preprint

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

Silverman, Timothy J.; Deceglie, Michael G.; Deline, Chris

2015-09-02

Partial shade of monolithic thin-film PV modules can cause reverse-bias conditions leading to permanent damage. In this work, we propose a partial shade stress test for thin-film PV modules that quantifies permanent performance loss. We designed the test with the aid of a computer model that predicts the local voltage, current and temperature stress that result from partial shade. The model predicts the module-scale interactions among the illumination pattern, the electrical properties of the photovoltaic material and the thermal properties of the module package. The test reproduces shading and loading conditions that may occur in the field. It accounts formore » reversible light-induced performance changes and for additional stress that may be introduced by light-enhanced reverse breakdown. We present simulated and experimental results from the application of the proposed test.« less

Radiation signatures from a locally energized flaring loop

NASA Technical Reports Server (NTRS)

Emslie, A. G.; Vlahos, L.

1980-01-01

The radiation signatures from a locally energized solar flare loop based on the physical properties of the energy release mechanisms were consistent with hard X-ray, microwave, and EUV observations for plausible source parameters. It was found that a suprathermal tail of high energy electrons is produced by the primary energy release, and that the number of energetic charged particles ejected into the interplanetary medium in the model is consistent with observations. The radiation signature model predicts that the intrinsic polarization of the hard X-ray burst should increase over the photon energy range of 20 to 100 keV.

Local Variation of Hashtag Spike Trains and Popularity in Twitter

PubMed Central

Sanlı, Ceyda; Lambiotte, Renaud

2015-01-01

We draw a parallel between hashtag time series and neuron spike trains. In each case, the process presents complex dynamic patterns including temporal correlations, burstiness, and all other types of nonstationarity. We propose the adoption of the so-called local variation in order to uncover salient dynamical properties, while properly detrending for the time-dependent features of a signal. The methodology is tested on both real and randomized hashtag spike trains, and identifies that popular hashtags present regular and so less bursty behavior, suggesting its potential use for predicting online popularity in social media. PMID:26161650

Synchronization of three electrochemical oscillators: From local to global coupling

NASA Astrophysics Data System (ADS)

Liu, Yifan; Sebek, Michael; Mori, Fumito; Kiss, István Z.

2018-04-01

We investigate the formation of synchronization patterns in an oscillatory nickel electrodissolution system in a network obtained by superimposing local and global coupling with three electrodes. We explored the behavior through numerical simulations using kinetic ordinary differential equations, Kuramoto type phase models, and experiments, in which the local to global coupling could be tuned by cross resistances between the three nickel wires. At intermediate coupling strength with predominant global coupling, two of the three oscillators, whose natural frequencies are closer, can synchronize. By adding even a relatively small amount of local coupling (about 9%-25%), a spatially organized partially synchronized state can occur where one of the two synchronized elements is in the center. A formula was derived for predicting the critical coupling strength at which full synchronization will occur independent of the permutation of the natural frequencies of the oscillators over the network. The formula correctly predicts the variation of the critical coupling strength as a function of the global coupling fraction, e.g., with local coupling the critical coupling strength is about twice than that required with global coupling. The results show the importance of the topology of the network on the synchronization properties in a simple three-oscillator setup and could provide guidelines for decrypting coupling topology from identification of synchronization patterns.

From Complex B1 Mapping to Local SAR Estimation for Human Brain MR Imaging Using Multi-channel Transceiver Coil at 7T

PubMed Central

Zhang, Xiaotong; Schmitter, Sebastian; Van de Moortel, Pierre-François; Liu, Jiaen

2014-01-01

Elevated Specific Absorption Rate (SAR) associated with increased main magnetic field strength remains as a major safety concern in ultra-high-field (UHF) Magnetic Resonance Imaging (MRI) applications. The calculation of local SAR requires the knowledge of the electric field induced by radiofrequency (RF) excitation, and the local electrical properties of tissues. Since electric field distribution cannot be directly mapped in conventional MR measurements, SAR estimation is usually performed using numerical model-based electromagnetic simulations which, however, are highly time consuming and cannot account for the specific anatomy and tissue properties of the subject undergoing a scan. In the present study, starting from the measurable RF magnetic fields (B1) in MRI, we conducted a series of mathematical deduction to estimate the local, voxel-wise and subject-specific SAR for each single coil element using a multi-channel transceiver array coil. We first evaluated the feasibility of this approach in numerical simulations including two different human head models. We further conducted experimental study in a physical phantom and in two human subjects at 7T using a multi-channel transceiver head coil. Accuracy of the results is discussed in the context of predicting local SAR in the human brain at UHF MRI using multi-channel RF transmission. PMID:23508259

Snowpack spatial variability: Towards understanding its effect on remote sensing measurements and snow slope stability

NASA Astrophysics Data System (ADS)

Marshall, Hans-Peter

The distribution of water in the snow-covered areas of the world is an important climate change indicator, and it is a vital component of the water cycle. At local and regional scales, the snow water equivalent (SWE), the amount of liquid water a given area of the snowpack represents, is very important for water resource management, flood forecasting, and prediction of available hydropower energy. Measurements from only a few automatic weather stations, such as the SNOTEL network, or sparse manual snowpack measurements are typically extrapolated for estimating SWE over an entire basin. Widespread spatial variability in the distribution of SWE and snowpack stratigraphy at local scales causes large errors in these basin estimates. Remote sensing measurements offer a promising alternative, due to their large spatial coverage and high temporal resolution. Although snow cover extent can currently be estimated from remote sensing data, accurately quantifying SWE from remote sensing measurements has remained difficult, due to a high sensitivity to variations in grain size and stratigraphy. In alpine snowpacks, the large degree of spatial variability of snowpack properties and geometry, caused by topographic, vegetative, and microclimatic effects, also makes prediction of snow avalanches very difficult. Ground-based radar and penetrometer measurements can quickly and accurately characterize snowpack properties and SWE in the field. A portable lightweight radar was developed, and allows a real-time estimate of SWE to within 10%, as well as measurements of depths of all major density transitions within the snowpack. New analysis techniques developed in this thesis allow accurate estimates of mechanical properties and an index of grain size to be retrieved from the SnowMicroPenetrometer. These two tools together allow rapid characterization of the snowpack's geometry, mechanical properties, and SWE, and are used to guide a finite element model to study the stress distribution on a slope. The ability to accurately characterize snowpack properties at much higher resolutions and spatial extent than previously possible will hopefully help lead to a more complete understanding of spatial variability, its effect on remote sensing measurements and snow slope stability, and result in improvements in avalanche prediction and accuracy of SWE estimates from space.

Local stresses in metal matrix composites subjected to thermal and mechanical loading

NASA Technical Reports Server (NTRS)

Highsmith, Alton L.; Shin, Donghee; Naik, Rajiv A.

1990-01-01

An elasticity solution has been used to analyze matrix stresses near the fiber/matrix interface in continuous fiber-reinforced metal-matrix composites, modeling the micromechanics in question in terms of a cylindrical fiber and cylindrical matrix sheath which is embedded in an orthotropic medium representing the composite. The model's predictions for lamina thermal and mechanical properties are applied to a laminate analysis determining ply-level stresses due to thermomechanical loading. A comparison is made between these results, which assume cylindrical symmetry, and the predictions yielded by a FEM model in which the fibers are arranged in a square array.

Lead optimization using matched molecular pairs: inclusion of contextual information for enhanced prediction of HERG inhibition, solubility, and lipophilicity.

PubMed

Papadatos, George; Alkarouri, Muhammad; Gillet, Valerie J; Willett, Peter; Kadirkamanathan, Visakan; Luscombe, Christopher N; Bravi, Gianpaolo; Richmond, Nicola J; Pickett, Stephen D; Hussain, Jameed; Pritchard, John M; Cooper, Anthony W J; Macdonald, Simon J F

2010-10-25

Previous studies of the analysis of molecular matched pairs (MMPs) have often assumed that the effect of a substructural transformation on a molecular property is independent of the context (i.e., the local structural environment in which that transformation occurs). Experiments with large sets of hERG, solubility, and lipophilicity data demonstrate that the inclusion of contextual information can enhance the predictive power of MMP analyses, with significant trends (both positive and negative) being identified that are not apparent when using conventional, context-independent approaches.

Whole-body and local RF absorption in human models as a function of anatomy and position within 1.5T MR body coil.

PubMed

Murbach, Manuel; Neufeld, Esra; Kainz, Wolfgang; Pruessmann, Klaas P; Kuster, Niels

2014-02-01

Radiofrequency energy deposition in magnetic resonance imaging must be limited to prevent excessive heating of the patient. Correlations of radiofrequency absorption with large-scale anatomical features (e.g., height) are investigated in this article. The specific absorption rate (SAR), as the pivotal parameter for quantifying absorbed radiofrequency, increases with the radial dimension of the patient and therefore with the large-scale anatomical properties. The absorbed energy in six human models has been modeled in different Z-positions (head to knees) within a 1.5T bodycoil. For a fixed B1+ incident field, the whole-body SAR can be up to 2.5 times higher (local SAR up to seven times) in obese adult models compared to children. If the exposure is normalized to 4 W/kg whole-body SAR, the local SAR can well-exceed the limits for local transmit coils and shows intersubject variations of up to a factor of three. The correlations between anatomy and induced local SAR are weak for normalized exposure, but strong for a fixed B1+ field, suggesting that anatomical properties could be used for fast SAR predictions. This study demonstrates that a representative virtual human population is indispensable for the investigation of local SAR levels. Copyright © 2013 Wiley Periodicals, Inc.

The Perfect Burrow, but for What? Identifying Local Habitat Conditions Promoting the Presence of the Host and Vector Species in the Kazakh Plague System

PubMed Central

Wilschut, Liesbeth; Addink, Elisabeth; Ageyev, Vladimir; Yeszhanov, Aidyn; Sapozhnikov, Valerij; Belayev, Alexander; Davydova, Tania; Eagle, Sally; Begon, Mike

2015-01-01

Introduction The wildlife plague system in the Pre-Balkhash desert of Kazakhstan has been a subject of study for many years. Much progress has been made in generating a method of predicting outbreaks of the disease (infection by the gram negative bacterium Yersinia pestis) but existing methods are not yet accurate enough to inform public health planning. The present study aimed to identify characteristics of individual mammalian host (Rhombomys opimus) burrows related to and potentially predictive of the presence of R.opimus and the dominant flea vectors (Xenopsylla spp.). Methods Over four seasons, burrow characteristics, their current occupancy status, and flea and tick burden of the occupants were recorded in the field. A second data set was generated of long term occupancy trends by recording the occupancy status of specific burrows over multiple occasions. Generalised linear mixed models were constructed to identify potential burrow properties predictive of either occupancy or flea burden. Results At the burrow level, it was identified that a burrow being occupied by Rhombomys, and remaining occupied, were both related to the characteristics of the sediment in which the burrow was constructed. The flea burden of Rhombomys in a burrow was found to be related to the tick burden. Further larger scale properties were also identified as being related to both Rhombomys and flea presence, including latitudinal position and the season. Conclusions Therefore, in advancing our current predictions of plague in Kazakhstan, we must consider the landscape at this local level to increase our accuracy in predicting the dynamics of gerbil and flea populations. Furthermore this demonstrates that in other zoonotic systems, it may be useful to consider the distribution and location of suitable habitat for both host and vector species at this fine scale to accurately predict future epizootics. PMID:26325073

General relationships between ultrasonic attenuation and dispersion

NASA Technical Reports Server (NTRS)

Odonnell, M.; Jaynes, E. T.; Miller, J. G.

1978-01-01

General relationships between the ultrasonic attenuation and dispersion are presented. The validity of these nonlocal relationships hinges only on the properties of causality and linearity, and does not depend upon details of the mechanism responsible for the attenuation and dispersion. Approximate, nearly local relationships are presented and are demonstrated to predict accurately the ultrasonic dispersion in solutions of hemoglobin from the results of attenuation measurements.

Viscous electron flow in mesoscopic two-dimensional electron gas

NASA Astrophysics Data System (ADS)

Gusev, G. M.; Levin, A. D.; Levinson, E. V.; Bakarov, A. K.

2018-02-01

We report electrical and magneto transport measurements in mesoscopic size, two-dimensional (2D) electron gas in a GaAs quantum well. Remarkably, we find that the probe configuration and sample geometry strongly affects the temperature evolution of local resistance. We attribute all transport properties to the presence of hydrodynamic effects. Experimental results confirm the theoretically predicted significance of viscous flow in mesoscopic devices.

Path (un)predictability of two interacting cracks in polycarbonate sheets using Digital Image Correlation.

PubMed

Koivisto, J; Dalbe, M-J; Alava, M J; Santucci, S

2016-08-31

Crack propagation is tracked here with Digital Image Correlation analysis in the test case of two cracks propagating in opposite directions in polycarbonate, a material with high ductility and a large Fracture Process Zone (FPZ). Depending on the initial distances between the two crack tips, one may observe different complex crack paths with in particular a regime where the two cracks repel each other prior to being attracted. We show by strain field analysis how this can be understood according to the principle of local symmetry: the propagation is to the direction where the local shear - mode KII in fracture mechanics language - is zero. Thus the interactions exhibited by the cracks arise from symmetry, from the initial geometry, and from the material properties which induce the FPZ. This complexity makes any long-range prediction of the path(s) impossible.

Orientation selectivity sharpens motion detection in Drosophila

PubMed Central

Fisher, Yvette E.; Silies, Marion; Clandinin, Thomas R.

2015-01-01

SUMMARY Detecting the orientation and movement of edges in a scene is critical to visually guided behaviors of many animals. What are the circuit algorithms that allow the brain to extract such behaviorally vital visual cues? Using in vivo two-photon calcium imaging in Drosophila, we describe direction selective signals in the dendrites of T4 and T5 neurons, detectors of local motion. We demonstrate that this circuit performs selective amplification of local light inputs, an observation that constrains motion detection models and confirms a core prediction of the Hassenstein-Reichardt Correlator (HRC). These neurons are also orientation selective, responding strongly to static features that are orthogonal to their preferred axis of motion, a tuning property not predicted by the HRC. This coincident extraction of orientation and direction sharpens directional tuning through surround inhibition and reveals a striking parallel between visual processing in flies and vertebrate cortex, suggesting a universal strategy for motion processing. PMID:26456048

LT-STM/STS studies of clean armchair edge

NASA Astrophysics Data System (ADS)

Ju, Zheng; Zhang, Wenhan; Wu, Weida; Weida Wu Team

It was predicted and observed that the passivated zigzag edges of graphene host highly localized edge state. This edge state is predicted to be spin-polarized, which is appealing for spintronic applications. In contrast, no edge state was expected at passivated armchair graphene edge. Here we report low temperature scanning tunneling microscopy and spectroscopy (STM/STS) studies of electronic properties of clean monoatomic step edges on cleaved surface of HOPG. Most of step edges are armchair edges, in agreement with previous STM results. We observed only (√{ 3} ×√{ 3}) R30° superstructure near armchair edges, which has been reported in previous STM studies. On the other hand, no honeycomb superstructure was observed in our STM data. In addition, our STM results reveal an intriguing localized electronic state at clean armchair edges. Spectroscopic and spatial evolution of this edge state will be presented. This work is supported by NSF DMR-1506618.

Localization and loss of coherence in molecular double slit experiments

NASA Astrophysics Data System (ADS)

Langer, Burkhard; Becker, Uwe

2009-11-01

In their famous paper Einstein, Podolsky and Rosen questioned 1935 the completeness of quantum mechanics concerning a local realistic description of our reality. They argued on the basis of superpositions of position and momentum states against the inherent non-locality and loss of information on prior conditions by quantum mechanics. This pioneering proposal was, however, too vague to be implemented in any experimental proof. Consequently, angular momentum related variables such as the polarization of light became the working horse of all experiments proving the EPR predictions. However, the spin and its related polarization properties are abstract quantities compared to position and momentum. Here we present the first evidence that non-locality and loss of prior quantum state information occurs also for position in ordinary space. This shows that the tunnelling effect and entanglement are inherently correlated

Real-Time Ligand Binding Pocket Database Search Using Local Surface Descriptors

PubMed Central

Chikhi, Rayan; Sael, Lee; Kihara, Daisuke

2010-01-01

Due to the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of a particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two dimensional pseudo-Zernike moments or the 3D Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark study employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed. PMID:20455259

Real-time ligand binding pocket database search using local surface descriptors.

PubMed

Chikhi, Rayan; Sael, Lee; Kihara, Daisuke

2010-07-01

Because of the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two-dimensional pseudo-Zernike moments or the three-dimensional Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark studies employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed.

A new wave front shape-based approach for acoustic source localization in an anisotropic plate without knowing its material properties.

PubMed

Sen, Novonil; Kundu, Tribikram

2018-07-01

Estimating the location of an acoustic source in a structure is an important step towards passive structural health monitoring. Techniques for localizing an acoustic source in isotropic structures are well developed in the literature. Development of similar techniques for anisotropic structures, however, has gained attention only in the recent years and has a scope of further improvement. Most of the existing techniques for anisotropic structures either assume a straight line wave propagation path between the source and an ultrasonic sensor or require the material properties to be known. This study considers different shapes of the wave front generated during an acoustic event and develops a methodology to localize the acoustic source in an anisotropic plate from those wave front shapes. An elliptical wave front shape-based technique was developed first, followed by the development of a parametric curve-based technique for non-elliptical wave front shapes. The source coordinates are obtained by minimizing an objective function. The proposed methodology does not assume a straight line wave propagation path and can predict the source location without any knowledge of the elastic properties of the material. A numerical study presented here illustrates how the proposed methodology can accurately estimate the source coordinates. Copyright © 2018 Elsevier B.V. All rights reserved.

Coastal storm monitoring in Virginia

USGS Publications Warehouse

Wicklein, Shaun M.; Bennett, Mark

2014-01-01

Coastal communities in Virginia are prone to flooding, particularly during hurricanes, nor’easters, and other coastal low-pressure systems. These weather systems affect public safety, personal and public property, and valuable infrastructure, such as transportation, water and sewer, and electric-supply networks. Local emergency managers, utility operators, and the public are tasked with making difficult decisions regarding evacuations, road closures, and post-storm recovery efforts as a result of coastal flooding. In coastal Virginia these decisions often are made on the basis of anecdotal knowledge from past events or predictions based on data from monitoring sites located far away from the affected area that may not reflect local conditions. Preventing flood hazards, such as hurricane-induced storm surge, from becoming human disasters requires an understanding of the relative risks that flooding poses to specific communities. The risk to life and property can be very high if decisions about evacuations and road closures are made too late or not at all.

Modeling of the gate-controlled Kondo effect at carbon point defects in graphene

NASA Astrophysics Data System (ADS)

May, Daniel; Lo, Po-Wei; Deltenre, Kira; Henke, Anika; Mao, Jinhai; Jiang, Yuhang; Li, Guohong; Andrei, Eva Y.; Guo, Guang-Yu; Anders, Frithjof B.

2018-04-01

We study the magnetic properties in the vicinity of a single carbon defect in a monolayer of graphene. We include the unbound σ orbital and the vacancy-induced bound π state in an effective two-orbital single-impurity model. The local magnetic moments are stabilized by the Coulomb interaction as well as a significant ferromagnetic Hund's rule coupling between the orbitals predicted by a density functional theory calculation. A hybridization between the orbitals and the Dirac fermions is generated by the curvature of the graphene sheet in the vicinity of the vacancy. We present results for the local spectral function calculated using Wilson's numerical renormalization group approach for a realistic graphene band structure and find three different regimes depending on the filling, the controlling chemical potential, and the hybridization strength. These different regions are characterized by different magnetic properties. The calculated spectral functions qualitatively agree with recent scanning tunneling spectra on graphene vacancies.

Adaptive Optics Images of the Galactic Center: Using Empirical Noise-maps to Optimize Image Analysis

NASA Astrophysics Data System (ADS)

Albers, Saundra; Witzel, Gunther; Meyer, Leo; Sitarski, Breann; Boehle, Anna; Ghez, Andrea M.

2015-01-01

Adaptive Optics images are one of the most important tools in studying our Galactic Center. In-depth knowledge of the noise characteristics is crucial to optimally analyze this data. Empirical noise estimates - often represented by a constant value for the entire image - can be greatly improved by computing the local detector properties and photon noise contributions pixel by pixel. To comprehensively determine the noise, we create a noise model for each image using the three main contributors—photon noise of stellar sources, sky noise, and dark noise. We propagate the uncertainties through all reduction steps and analyze the resulting map using Starfinder. The estimation of local noise properties helps to eliminate fake detections while improving the detection limit of fainter sources. We predict that a rigorous understanding of noise allows a more robust investigation of the stellar dynamics in the center of our Galaxy.

Singlet oxygen explicit dosimetry to predict local tumor control for HPPH-mediated photodynamic therapy

NASA Astrophysics Data System (ADS)

Penjweini, Rozhin; Kim, Michele M.; Ong, Yi Hong; Zhu, Timothy C.

2017-02-01

This preclinical study examines four dosimetric quantities (light fluence, photosensitizer photobleaching ratio, PDT dose, and reacted singlet oxygen ([1O2]rx)) to predict local control rate (LCR) for 2-(1-Hexyloxyethyl)-2-devinyl pyropheophorbide (HPPH)-mediated photodynamic therapy (PDT). Mice bearing radiation-induced fibrosarcoma (RIF) tumors were treated with different in-air fluences (135, 250 and 350 J/cm2) and in-air fluence rates (50, 75 and 150 mW/cm2) at 0.25 mg/kg HPPH and a drug-light interval of 24 hours using a 1 cm diameter collimated laser beam at 665 nm wavelength. A macroscopic model was used to calculate ([1O2]rx)) based on in vivo explicit dosimetry of the initial tissue oxygenation, photosensitizer concentration, and tissue optical properties. PDT dose was defined as a temporal integral of drug concentration and fluence rate (φ) at a 3 mm tumor depth. Light fluence rate was calculated throughout the treatment volume based on Monte-Carlo simulation and measured tissue optical properties. The tumor volume of each mouse was tracked for 30 days after PDT and Kaplan-Meier analyses for LCR were performed based on a tumor volume <=100 mm3, for four dose metrics: fluence, HPPH photobleaching rate, PDT dose, and ([1O2]rx)). The results of this study showed that ([1O2]rx)) is the best dosimetric quantity that can predict tumor response and correlate with LCR.

Signature properties of water: Their molecular electronic origins

PubMed Central

Jones, Andrew P.; Cipcigan, Flaviu S.; Crain, Jason; Martyna, Glenn J.

2015-01-01

Water challenges our fundamental understanding of emergent materials properties from a molecular perspective. It exhibits a uniquely rich phenomenology including dramatic variations in behavior over the wide temperature range of the liquid into water’s crystalline phases and amorphous states. We show that many-body responses arising from water’s electronic structure are essential mechanisms harnessed by the molecule to encode for the distinguishing features of its condensed states. We treat the complete set of these many-body responses nonperturbatively within a coarse-grained electronic structure derived exclusively from single-molecule properties. Such a “strong coupling” approach generates interaction terms of all symmetries to all orders, thereby enabling unique transferability to diverse local environments such as those encountered along the coexistence curve. The symmetries of local motifs that can potentially emerge are not known a priori. Consequently, electronic responses unfiltered by artificial truncation are then required to embody the terms that tip the balance to the correct set of structures. Therefore, our fully responsive molecular model produces, a simple, accurate, and intuitive picture of water’s complexity and its molecular origin, predicting water’s signature physical properties from ice, through liquid–vapor coexistence, to the critical point. PMID:25941394

Mixed valency and site-preference chemistry for cerium and its compounds: A predictive density-functional theory study

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

Alam, Aftab; Johnson, Duane D.

Cerium and its technologically relevant compounds are examples of anomalous mixed valency, originating from two competing oxidation states—itinerant Ce4+ and localized Ce3+. Under applied stress, anomalous transitions are observed but not well understood. Here we treat mixed valency as an “alloy” problem involving two valences with competing and numerous site-occupancy configurations. We use density-functional theory with Hubbard U (i.e., DFT+U) to evaluate the effective valence and predict properties, including controlling the valence by pseudoternary alloying. For Ce and its compounds, such as (Ce,La)2(Fe,Co)14B permanent magnets, we find a stable mixed-valent α state near the spectroscopic value of νs=3.53. Ce valencymore » in compounds depends on its steric volume and local chemistry. For La doping, Ce valency shifts towards γ-like Ce3+, as expected from steric volume; for Co doping, valency depends on local Ce-site chemistry and steric volume. Our approach captures the key origins of anomalous valency and site-preference chemistry in complex compounds.« less

The Density Functional Theory of Flies: Predicting distributions of interacting active organisms

NASA Astrophysics Data System (ADS)

Kinkhabwala, Yunus; Valderrama, Juan; Cohen, Itai; Arias, Tomas

On October 2nd, 2016, 52 people were crushed in a stampede when a crowd panicked at a religious gathering in Ethiopia. The ability to predict the state of a crowd and whether it is susceptible to such transitions could help prevent such catastrophes. While current techniques such as agent based models can predict transitions in emergent behaviors of crowds, the assumptions used to describe the agents are often ad hoc and the simulations are computationally expensive making their application to real-time crowd prediction challenging. Here, we pursue an orthogonal approach and ask whether a reduced set of variables, such as the local densities, are sufficient to describe the state of a crowd. Inspired by the theoretical framework of Density Functional Theory, we have developed a system that uses only measurements of local densities to extract two independent crowd behavior functions: (1) preferences for locations and (2) interactions between individuals. With these two functions, we have accurately predicted how a model system of walking Drosophila melanogaster distributes itself in an arbitrary 2D environment. In addition, this density-based approach measures properties of the crowd from only observations of the crowd itself without any knowledge of the detailed interactions and thus it can make predictions about the resulting distributions of these flies in arbitrary environments, in real-time. This research was supported in part by ARO W911NF-16-1-0433.

Monte Carlo method for photon heating using temperature-dependent optical properties.

PubMed

Slade, Adam Broadbent; Aguilar, Guillermo

2015-02-01

The Monte Carlo method for photon transport is often used to predict the volumetric heating that an optical source will induce inside a tissue or material. This method relies on constant (with respect to temperature) optical properties, specifically the coefficients of scattering and absorption. In reality, optical coefficients are typically temperature-dependent, leading to error in simulation results. The purpose of this study is to develop a method that can incorporate variable properties and accurately simulate systems where the temperature will greatly vary, such as in the case of laser-thawing of frozen tissues. A numerical simulation was developed that utilizes the Monte Carlo method for photon transport to simulate the thermal response of a system that allows temperature-dependent optical and thermal properties. This was done by combining traditional Monte Carlo photon transport with a heat transfer simulation to provide a feedback loop that selects local properties based on current temperatures, for each moment in time. Additionally, photon steps are segmented to accurately obtain path lengths within a homogenous (but not isothermal) material. Validation of the simulation was done using comparisons to established Monte Carlo simulations using constant properties, and a comparison to the Beer-Lambert law for temperature-variable properties. The simulation is able to accurately predict the thermal response of a system whose properties can vary with temperature. The difference in results between variable-property and constant property methods for the representative system of laser-heated silicon can become larger than 100K. This simulation will return more accurate results of optical irradiation absorption in a material which undergoes a large change in temperature. This increased accuracy in simulated results leads to better thermal predictions in living tissues and can provide enhanced planning and improved experimental and procedural outcomes. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Spectral properties of the temporal evolution of brain network structure.

PubMed

Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

2015-12-01

The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems.

Spectral properties of the temporal evolution of brain network structure

NASA Astrophysics Data System (ADS)

Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

2015-12-01

The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems.

Multi-fidelity machine learning models for accurate bandgap predictions of solids

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

Pilania, Ghanshyam; Gubernatis, James E.; Lookman, Turab

Here, we present a multi-fidelity co-kriging statistical learning framework that combines variable-fidelity quantum mechanical calculations of bandgaps to generate a machine-learned model that enables low-cost accurate predictions of the bandgaps at the highest fidelity level. Additionally, the adopted Gaussian process regression formulation allows us to predict the underlying uncertainties as a measure of our confidence in the predictions. In using a set of 600 elpasolite compounds as an example dataset and using semi-local and hybrid exchange correlation functionals within density functional theory as two levels of fidelities, we demonstrate the excellent learning performance of the method against actual high fidelitymore » quantum mechanical calculations of the bandgaps. The presented statistical learning method is not restricted to bandgaps or electronic structure methods and extends the utility of high throughput property predictions in a significant way.« less

Multi-fidelity machine learning models for accurate bandgap predictions of solids

DOE PAGES

Pilania, Ghanshyam; Gubernatis, James E.; Lookman, Turab

2016-12-28

Here, we present a multi-fidelity co-kriging statistical learning framework that combines variable-fidelity quantum mechanical calculations of bandgaps to generate a machine-learned model that enables low-cost accurate predictions of the bandgaps at the highest fidelity level. Additionally, the adopted Gaussian process regression formulation allows us to predict the underlying uncertainties as a measure of our confidence in the predictions. In using a set of 600 elpasolite compounds as an example dataset and using semi-local and hybrid exchange correlation functionals within density functional theory as two levels of fidelities, we demonstrate the excellent learning performance of the method against actual high fidelitymore » quantum mechanical calculations of the bandgaps. The presented statistical learning method is not restricted to bandgaps or electronic structure methods and extends the utility of high throughput property predictions in a significant way.« less

[Local Regression Algorithm Based on Net Analyte Signal and Its Application in Near Infrared Spectral Analysis].

PubMed

Zhang, Hong-guang; Lu, Jian-gang

2016-02-01

Abstract To overcome the problems of significant difference among samples and nonlinearity between the property and spectra of samples in spectral quantitative analysis, a local regression algorithm is proposed in this paper. In this algorithm, net signal analysis method(NAS) was firstly used to obtain the net analyte signal of the calibration samples and unknown samples, then the Euclidean distance between net analyte signal of the sample and net analyte signal of calibration samples was calculated and utilized as similarity index. According to the defined similarity index, the local calibration sets were individually selected for each unknown sample. Finally, a local PLS regression model was built on each local calibration sets for each unknown sample. The proposed method was applied to a set of near infrared spectra of meat samples. The results demonstrate that the prediction precision and model complexity of the proposed method are superior to global PLS regression method and conventional local regression algorithm based on spectral Euclidean distance.

Using Multispectral and Elevation Data to Predict Soil Properties for a Better Management of Fertilizers at Field Scale

NASA Astrophysics Data System (ADS)

Drouin, Ariane; Michaud, Aubert; Sylvain, Jean-Daniel; N'Dayegamiye, Adrien; Gasser, Marc-Olivier; Nolin, Michel; Perron, Isabelle; Grenon, Lucie; Beaudin, Isabelle; Desjardins, Jacques; Côté, Noémi

2013-04-01

This project aims at developing and validating an operational integrated management and localized approach at field scale using remote sensing data. It is realized in order to support the competitiveness of agricultural businesses, to ensure soil productivity in the long term and prevent diffuse contamination of surface waters. Our intention is to help agrienvironmental advisors and farmers in the consideration of spatial variability of soil properties in the management of fields. The proposed approach of soil properties recognition is based on the combination of elevation data and multispectral satellite imagery (Landsat) within statistical models. The method is based on the use of the largest possible number of satellite images to cover the widest range of soil moisture variability. Several spectral indices are calculated for each image (normalized brightness index, soil color index, organic matter index, etc.). The assignation of soils is based on a calibration procedure making use of the spatial soil database available in Canada. It includes soil profile point data associated to a database containing the information collected in the field. Three soil properties are predicted and mapped: A horizon texture, B horizon texture and drainage class. All the spectral indices, elevation data and soil data are combined in a discriminant analysis that produces discriminant functions. These are then used to produce maps of soil properties. In addition, from mapping soil properties, management zones are delineated within the field. The delineation of management zones with relatively similar soil properties is created to enable farmers to manage their fertilizers by taking greater account of their soils. This localized or precision management aims to adjust the application of fertilizer according to the real needs of soils and to reduce costs for farmers and the exports of nutrients to the stream. Mapping of soil properties will be validated in three agricultural regions in Quebec through an experimental field protocol (spatial sampling by management zones). Soils will be sampled, but crop yields under different nitrogen rates will also be assessed. Specifically, in each of the management areas defined, five different doses of nitrogen were applied (0, 50, 100, 150, 200 kg N / ha) on corn fields. In fall, the corn is harvested to assess differences in yields between the management areas and also in terms of doses of nitrogen. Ultimately, on the basis of well-established management areas, showing contrasting soil properties, the farmer will be able to ensure optimal correction of soil acidity, nitrogen fertilization, richness of soil in P and K, and improve soil drainage and physical properties. Environmentally, the principles of integrated and localized management carries significant benefits, particularly in terms of reduction of diffuse nutrient pollution.

Probing the structural and dynamical properties of liquid water with models including non-local electron correlation

NASA Astrophysics Data System (ADS)

Del Ben, Mauro; Hutter, Jürg; VandeVondele, Joost

2015-08-01

Water is a ubiquitous liquid that displays a wide range of anomalous properties and has a delicate structure that challenges experiment and simulation alike. The various intermolecular interactions that play an important role, such as repulsion, polarization, hydrogen bonding, and van der Waals interactions, are often difficult to reproduce faithfully in atomistic models. Here, electronic structure theories including all these interactions at equal footing, which requires the inclusion of non-local electron correlation, are used to describe structure and dynamics of bulk liquid water. Isobaric-isothermal (NpT) ensemble simulations based on the Random Phase Approximation (RPA) yield excellent density (0.994 g/ml) and fair radial distribution functions, while various other density functional approximations produce scattered results (0.8-1.2 g/ml). Molecular dynamics simulation in the microcanonical (NVE) ensemble based on Møller-Plesset perturbation theory (MP2) yields dynamical properties in the condensed phase, namely, the infrared spectrum and diffusion constant. At the MP2 and RPA levels of theory, ice is correctly predicted to float on water, resolving one of the anomalies as resulting from a delicate balance between van der Waals and hydrogen bonding interactions. For several properties, obtaining quantitative agreement with experiment requires correction for nuclear quantum effects (NQEs), highlighting their importance, for structure, dynamics, and electronic properties. A computed NQE shift of 0.6 eV for the band gap and absorption spectrum illustrates the latter. Giving access to both structure and dynamics of condensed phase systems, non-local electron correlation will increasingly be used to study systems where weak interactions are of paramount importance.

Discriminating a deep gallium antisite defect from shallow acceptors in GaAs using supercell calculations

DOE PAGES

Schultz, Peter A.

2016-03-01

For the purposes of making reliable first-principles predictions of defect energies in semiconductors, it is crucial to distinguish between effective-mass-like defects, which cannot be treated accurately with existing supercell methods, and deep defects, for which density functional theory calculations can yield reliable predictions of defect energy levels. The gallium antisite defect GaAs is often associated with the 78/203 meV shallow double acceptor in Ga-rich gallium arsenide. Within a conceptual framework of level patterns, analyses of structure and spin stabilization can be used within a supercell approach to distinguish localized deep defect states from shallow acceptors such as B As. Thismore » systematic approach determines that the gallium antisite supercell results has signatures inconsistent with an effective mass state and cannot be the 78/203 shallow double acceptor. Lastly, the properties of the Ga antisite in GaAs are described, total energy calculations that explicitly map onto asymptotic discrete localized bulk states predict that the Ga antisite is a deep double acceptor and has at least one deep donor state.« less

Conformational equilibria of alkanes in aqueous solution: relationship to water structure near hydrophobic solutes.

PubMed Central

Ashbaugh, H S; Garde, S; Hummer, G; Kaler, E W; Paulaitis, M E

1999-01-01

Conformational free energies of butane, pentane, and hexane in water are calculated from molecular simulations with explicit waters and from a simple molecular theory in which the local hydration structure is estimated based on a proximity approximation. This proximity approximation uses only the two nearest carbon atoms on the alkane to predict the local water density at a given point in space. Conformational free energies of hydration are subsequently calculated using a free energy perturbation method. Quantitative agreement is found between the free energies obtained from simulations and theory. Moreover, free energy calculations using this proximity approximation are approximately four orders of magnitude faster than those based on explicit water simulations. Our results demonstrate the accuracy and utility of the proximity approximation for predicting water structure as the basis for a quantitative description of n-alkane conformational equilibria in water. In addition, the proximity approximation provides a molecular foundation for extending predictions of water structure and hydration thermodynamic properties of simple hydrophobic solutes to larger clusters or assemblies of hydrophobic solutes. PMID:10423414

Global and Local Approaches Describing Critical Phenomena on the Developing and Developed Financial Markets

NASA Astrophysics Data System (ADS)

Grech, Dariusz

We define and confront global and local methods to analyze the financial crash-like events on the financial markets from the critical phenomena point of view. These methods are based respectively on the analysis of log-periodicity and on the local fractal properties of financial time series in the vicinity of phase transitions (crashes). The log-periodicity analysis is made in a daily time horizon, for the whole history (1991-2008) of Warsaw Stock Exchange Index (WIG) connected with the largest developing financial market in Europe. We find that crash-like events on the Polish financial market are described better by the log-divergent price model decorated with log-periodic behavior than by the power-law-divergent price model usually discussed in log-periodic scenarios for developed markets. Predictions coming from log-periodicity scenario are verified for all main crashes that took place in WIG history. It is argued that crash predictions within log-periodicity model strongly depend on the amount of data taken to make a fit and therefore are likely to contain huge inaccuracies. Next, this global analysis is confronted with the local fractal description. To do so, we provide calculation of the so-called local (time dependent) Hurst exponent H loc for the WIG time series and for main US stock market indices like DJIA and S&P 500. We point out dependence between the behavior of the local fractal properties of financial time series and the crashes appearance on the financial markets. We conclude that local fractal method seems to work better than the global approach - both for developing and developed markets. The very recent situation on the market, particularly related to the Fed intervention in September 2007 and the situation immediately afterwards is also analyzed within fractal approach. It is shown in this context how the financial market evolves through different phases of fractional Brownian motion. Finally, the current situation on American market is analyzed in fractal language. This is to show how far we still are from the end of recession and from the beginning of a new boom on US financial market or on other world leading stocks.

A hierarchical spatial model for well yield in complex aquifers

NASA Astrophysics Data System (ADS)

Montgomery, J.; O'sullivan, F.

2017-12-01

Efficiently siting and managing groundwater wells requires reliable estimates of the amount of water that can be produced, or the well yield. This can be challenging to predict in highly complex, heterogeneous fractured aquifers due to the uncertainty around local hydraulic properties. Promising statistical approaches have been advanced in recent years. For instance, kriging and multivariate regression analysis have been applied to well test data with limited but encouraging levels of prediction accuracy. Additionally, some analytical solutions to diffusion in homogeneous porous media have been used to infer "effective" properties consistent with observed flow rates or drawdown. However, this is an under-specified inverse problem with substantial and irreducible uncertainty. We describe a flexible machine learning approach capable of combining diverse datasets with constraining physical and geostatistical models for improved well yield prediction accuracy and uncertainty quantification. Our approach can be implemented within a hierarchical Bayesian framework using Markov Chain Monte Carlo, which allows for additional sources of information to be incorporated in priors to further constrain and improve predictions and reduce the model order. We demonstrate the usefulness of this approach using data from over 7,000 wells in a fractured bedrock aquifer.

Direct laser interference patterning of magnetic thin films

NASA Astrophysics Data System (ADS)

Aktag, Aliekber

Recently, patterned magnetic thin films have attracted much attention for a variety of applications such as high density magnetic recording, magnetoresistive sensing, and magnetic random access memories. In the case of magnetic recording, one scheme calls for the films to be patterned into single domain "dots", where every dot represents a thermally stable bit. In this thesis, we extended a technique called direct laser interference patterning (DLIP), originally developed by Polushkin and co-workers, to pattern and locally modify the materials properties of magnetic thin films. In this technique, a high-intensity Nd:YAG pulse laser beam was split into two, three, or four beams, which are then recombined to interfere on a sample surface. The interference intensity maxima can modify the local materials properties of the film through local "annealing" or, more drastically, by ablation. We carried out some preliminary investigations of the DLIP process in several films including co-sputtered Co-C, amorphous Dy/Co:SiO2 multilayers, and Co/SiO2 multilayers in order to refine our techniques. We successfully produced regular arrays of lines, dots, or antidots formed by ablation of the thin film. The preliminary studies also showed that, in the regime of more modest pulse energies, it is possible to modify the magnetic properties of the films without noticeably changing the film topography. We then prepared perpendicular magnetic anisotropy Co/Pt multilayers with a SiO x passivation layer and applied DLIP at fairly modest intensities to pattern the film. We then studied the structural and magnetic changes that occurred in some detail. X-ray diffraction scans showed the Co/Pt:SiO x multilayer films to be nanocrystalline before and after patterning. Atomic force microscopy images showed no evidence for topographic changes of the Co/Pt:SiOx during patterning. In contrast, magnetic force microscopy showed regular periodic dot arrays, indicating that the local magnetic properties were significantly affected by the patterning process. Alternating-gradient-force magnetometry and magneto-optic measurements also showed that the magnetic properties were markedly changed by the DLIP process. Our results offer strong evidence that local heating causes the moments to change from perpendicular to in-plane, with the consequent formation of an "anisotropy lattice": dots of in-plane magnetization within a matrix of perpendicular magnetization. We also carried out some optical interference calculations to predict the light intensity distributions for two, three, and four interfering beams of light. We found that the patterns could be controlled by varying the angles of incidence, the polarizations of the beams, and the wavelength and intensity of the beams, and that a wide variety of patterns are possible. The predicted patterns were in quite good agreement with those observed experimentally.

Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network.

PubMed

Lyons, James; Dehzangi, Abdollah; Heffernan, Rhys; Sharma, Alok; Paliwal, Kuldip; Sattar, Abdul; Zhou, Yaoqi; Yang, Yuedong

2014-10-30

Because a nearly constant distance between two neighbouring Cα atoms, local backbone structure of proteins can be represented accurately by the angle between C(αi-1)-C(αi)-C(αi+1) (θ) and a dihedral angle rotated about the C(αi)-C(αi+1) bond (τ). θ and τ angles, as the representative of structural properties of three to four amino-acid residues, offer a description of backbone conformations that is complementary to φ and ψ angles (single residue) and secondary structures (>3 residues). Here, we report the first machine-learning technique for sequence-based prediction of θ and τ angles. Predicted angles based on an independent test have a mean absolute error of 9° for θ and 34° for τ with a distribution on the θ-τ plane close to that of native values. The average root-mean-square distance of 10-residue fragment structures constructed from predicted θ and τ angles is only 1.9Å from their corresponding native structures. Predicted θ and τ angles are expected to be complementary to predicted ϕ and ψ angles and secondary structures for using in model validation and template-based as well as template-free structure prediction. The deep neural network learning technique is available as an on-line server called Structural Property prediction with Integrated DEep neuRal network (SPIDER) at http://sparks-lab.org. Copyright © 2014 Wiley Periodicals, Inc.

Local reionization histories with a merger tree of the HII regions

NASA Astrophysics Data System (ADS)

Chardin, Jonathan; Aubert, Dominique; Ocvirk, Pierre

2014-08-01

Aims: We investigate simple properties of the initial stage of the reionization process around progenitors of galaxies, such as the extent of the initial HII region before its fusion with the UV background, and the duration of its propagation. Methods: We used a set of four reionization simulations with different resolutions and ionizing source prescriptions. By using a merger tree of the HII regions we compiled a catalog of the HII region properties. When the ionized regions undergo a major-merger event, we considered that they belong to the global UV background. From the lifetime of the region and from their volume until this moment we drew typical local reionization histories as a function of time and investigated the relation between these histories and the halo mass progenitors of the regions. We then used an average mass accretion history model (AMAH) to extrapolate the halo mass inside the region from high z to z = 0 to predict the past reionization histories of galaxies we see today. Results: We found that the later an HII region appears during the reionization period, the shorter their related lifetime is and the smaller their volume before they merge with the global UV background. Quantitatively, the duration and extent of the initial growth of an HII region is strongly dependent on the mass of the inner halo and can be as long as ~50% of the reionization epoch. We found that the more massive a halo is today, the earlier it appears and the larger is the extension and the longer the propagation duration of its HII region. Quantitative predictions differ depending on the box size or the source model: small simulated volumes are affected by proximity effects between HII regions, and halo-based source models predict smaller regions and slower I-front expansion than models that use star particles as ionizing sources. Applying this extrapolation to Milky Way-type halos leads to a maximal extent of 1.1 Mpc/h for the initial HII region that established itself in ~150-200 ± 20 Myr. This is consistent with the prediction made using constrained Local Group simulations. For halos with masses similar to those of the Local Group (MW + M31), our result suggests that statistically it has not been influenced by an external front coming from a Virgo-like cluster.

Machine learning properties of materials and molecules with entropy-regularized kernels

NASA Astrophysics Data System (ADS)

Ceriotti, Michele; Bartók, Albert; CsáNyi, GáBor; de, Sandip

Application of machine-learning methods to physics, chemistry and materials science is gaining traction as a strategy to obtain accurate predictions of the properties of matter at a fraction of the typical cost of quantum mechanical electronic structure calculations. In this endeavor, one can leverage general-purpose frameworks for supervised-learning. It is however very important that the input data - for instance the positions of atoms in a molecule or solid - is processed into a form that reflects all the underlying physical symmetries of the problem, and that possesses the regularity properties that are required by machine-learning algorithms. Here we introduce a general strategy to build a representation of this kind. We will start from existing approaches to compare local environments (basically, groups of atoms), and combine them using techniques borrowed from optimal transport theory, discussing the relation between this idea and additive energy decompositions. We will present a few examples demonstrating the potential of this approach as a tool to predict molecular and materials' properties with an accuracy on par with state-of-the-art electronic structure methods. MARVEL NCCR (Swiss National Science Foundation) and ERC StG HBMAP (European Research Council, G.A. 677013).

Discrete-element modeling of nacre-like materials: Effects of random microstructures on strain localization and mechanical performance

NASA Astrophysics Data System (ADS)

Abid, Najmul; Mirkhalaf, Mohammad; Barthelat, Francois

2018-03-01

Natural materials such as nacre, collagen, and spider silk are composed of staggered stiff and strong inclusions in a softer matrix. This type of hybrid microstructure results in remarkable combinations of stiffness, strength, and toughness and it now inspires novel classes of high-performance composites. However, the analytical and numerical approaches used to predict and optimize the mechanics of staggered composites often neglect statistical variations and inhomogeneities, which may have significant impacts on modulus, strength, and toughness. Here we present an analysis of localization using small representative volume elements (RVEs) and large scale statistical volume elements (SVEs) based on the discrete element method (DEM). DEM is an efficient numerical method which enabled the evaluation of more than 10,000 microstructures in this study, each including about 5,000 inclusions. The models explore the combined effects of statistics, inclusion arrangement, and interface properties. We find that statistical variations have a negative effect on all properties, in particular on the ductility and energy absorption because randomness precipitates the localization of deformations. However, the results also show that the negative effects of random microstructures can be offset by interfaces with large strain at failure accompanied by strain hardening. More specifically, this quantitative study reveals an optimal range of interface properties where the interfaces are the most effective at delaying localization. These findings show how carefully designed interfaces in bioinspired staggered composites can offset the negative effects of microstructural randomness, which is inherent to most current fabrication methods.

Constraining the physical properties of compositionally distinctive surfaces on Mars from overlapping THEMIS observations

NASA Astrophysics Data System (ADS)

Ahern, A.; Rogers, D.

2017-12-01

Better constraints on the physical properties (e.g. grain size, rock abundance, cohesion, porosity and amount of induration) of Martian surface materials can lead to greater understanding of outcrop origin (e.g. via sedimentary, effusive volcanic, pyroclastic processes). Many outcrop surfaces on Mars likely contain near-surface (<3 cm) vertical heterogeneity in physical properties due to thin sediment cover, induration, and physical weathering, that can obscure measurement of the bulk thermal conductivity of the outcrop materials just below. Fortunately, vertical heterogeneity within near-surface materials can result in unique, and possibly predictable, diurnal and seasonal temperature patterns. The KRC thermal model has been utilized in a number of previous studies to predict thermal inertia of surface materials on Mars. Here we use KRC to model surface temperatures from overlapping Mars Odyssey THEMIS surface temperature observations that span multiple seasons and local times, in order to constrain both the nature of vertical heterogeneity and the underlying outcrop thermal inertia for various spectrally distinctive outcrops on Mars. We utilize spectral observations from TES and CRISM to constrain the particle size of the uppermost surface. For this presentation, we will focus specifically on chloride-bearing units in Terra Sirenum and Meridiani Planum, as well as mafic and feldspathic bedrock locations with distinct spectral properties, yet uncertain origins, in Noachis Terra and Nili Fossae. We find that many of these surfaces exhibit variations in apparent thermal inertia with season and local time that are consistent with low thermal inertia materials overlying higher thermal inertia substrates. Work is ongoing to compare surface temperature measurements with modeled two-layer scenarios in order to constrain the top layer thickness and bottom layer thermal inertia. The information will be used to better interpret the origins of these distinctive outcrops.

Toward an Accurate Theoretical Framework for Describing Ensembles for Proteins under Strongly Denaturing Conditions

PubMed Central

Tran, Hoang T.; Pappu, Rohit V.

2006-01-01

Our focus is on an appropriate theoretical framework for describing highly denatured proteins. In high concentrations of denaturants, proteins behave like polymers in a good solvent and ensembles for denatured proteins can be modeled by ignoring all interactions except excluded volume (EV) effects. To assay conformational preferences of highly denatured proteins, we quantify a variety of properties for EV-limit ensembles of 23 two-state proteins. We find that modeled denatured proteins can be best described as follows. Average shapes are consistent with prolate ellipsoids. Ensembles are characterized by large correlated fluctuations. Sequence-specific conformational preferences are restricted to local length scales that span five to nine residues. Beyond local length scales, chain properties follow well-defined power laws that are expected for generic polymers in the EV limit. The average available volume is filled inefficiently, and cavities of all sizes are found within the interiors of denatured proteins. All properties characterized from simulated ensembles match predictions from rigorous field theories. We use our results to resolve between conflicting proposals for structure in ensembles for highly denatured states. PMID:16766618

Passive Imaging in Nondiffuse Acoustic Wavefields

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

Mulargia, Francesco; Castellaro, Silvia

2008-05-30

A main property of diffuse acoustic wavefields is that, taken any two points, each of them can be seen as the source of waves and the other as the recording station. This property is shown to follow simply from array azimuthal selectivity and Huygens principle in a locally isotropic wavefield. Without time reversal, this property holds approximately also in anisotropic azimuthally uniform wavefields, implying much looser constraints for undistorted passive imaging than those required by a diffuse field. A notable example is the seismic noise field, which is generally nondiffuse, but is found to be compatible with a finite aperturemore » anisotropic uniform wavefield. The theoretical predictions were confirmed by an experiment on seismic noise in the mainland of Venice, Italy.« less

Relationship between mechanical-property and energy-absorption trends for composite tubes

NASA Technical Reports Server (NTRS)

Farley, Gary L.

1992-01-01

U.S. Army helicopters are designed to dissipate prescribed levels of crash impact kinetic energy without compromising the integrity of the fuselage. Because of the complexity of the energy-absorption process it is imperative for designers of energy-absorbing structures to develop an in-depth understanding of how and why composite structures absorb energy. A description of the crushing modes and mechanisms of energy absorption for composite tubes and beams is presented. Three primary crushing modes of composite structures including transverse shearing, lamina bending, and local buckling are described. The experimental data presented show that fiber and matrix mechanical properties and laminate stiffness and strength mechanical properties cannot reliably predict the energy-absorption response of composite tubes.

Electrical Transport Properties of Liquid Al-Cu Alloys

NASA Astrophysics Data System (ADS)

Thakore, B. Y.; Khambholja, S. G.; Suthar, P. H.; Jani, A. R.

2010-06-01

Electrical transport properties viz. electrical resistivity, thermoelectric power and thermal conductivity of liquid Al-Cu alloys as a function of Cu concentration have been studied in the present paper. Ashcroft empty core model potential has been used to incorporate the ion-electron interaction. To incorporate the exchange and correlation effects, five different forms of local field correction functions viz. Hartree, Taylor, Ichimaru et al., Farid et al. and Sarkar et al. have been used. The transport properties of binary system have been studied using Faber-Ziman formulation combined with Ashcroft-Langreth (AL) partial structure factor. The computed values of electrical resistivity are compared with experimental data and for low Cu concentration, good agreement has been observed. Further, thermoelectric power and thermal conductivity have also been predicted.

Interpolation Approaches for Characterizing Spatial Variability of Soil Properties in Tuz Lake Basin of Turkey

NASA Astrophysics Data System (ADS)

Gorji, Taha; Sertel, Elif; Tanik, Aysegul

2017-12-01

Soil management is an essential concern in protecting soil properties, in enhancing appropriate soil quality for plant growth and agricultural productivity, and in preventing soil erosion. Soil scientists and decision makers require accurate and well-distributed spatially continuous soil data across a region for risk assessment and for effectively monitoring and managing soils. Recently, spatial interpolation approaches have been utilized in various disciplines including soil sciences for analysing, predicting and mapping distribution and surface modelling of environmental factors such as soil properties. The study area selected in this research is Tuz Lake Basin in Turkey bearing ecological and economic importance. Fertile soil plays a significant role in agricultural activities, which is one of the main industries having great impact on economy of the region. Loss of trees and bushes due to intense agricultural activities in some parts of the basin lead to soil erosion. Besides, soil salinization due to both human-induced activities and natural factors has exacerbated its condition regarding agricultural land development. This study aims to compare capability of Local Polynomial Interpolation (LPI) and Radial Basis Functions (RBF) as two interpolation methods for mapping spatial pattern of soil properties including organic matter, phosphorus, lime and boron. Both LPI and RBF methods demonstrated promising results for predicting lime, organic matter, phosphorous and boron. Soil samples collected in the field were used for interpolation analysis in which approximately 80% of data was used for interpolation modelling whereas the remaining for validation of the predicted results. Relationship between validation points and their corresponding estimated values in the same location is examined by conducting linear regression analysis. Eight prediction maps generated from two different interpolation methods for soil organic matter, phosphorus, lime and boron parameters were examined based on R2 and RMSE values. The outcomes indicate that RBF performance in predicting lime, organic matter and boron put forth better results than LPI. However, LPI shows better results for predicting phosphorus.

Local properties of magnetic reconnection in nonlinear resistive- and extended-magnetohydrodynamic toroidal simulations of the sawtooth crash

DOE PAGES

Beidler, M. T.; Cassak, P. A.; Jardin, S. C.; ...

2016-12-15

We diagnose local properties of magnetic reconnection during a sawtooth crash employing the three-dimensional toroidal, extended-magnetohydrodynamic (MHD) code M3D-C 1. To do so, we sample simulation data in the plane in which reconnection occurs, the plane perpendicular to the helical (m, n) = (1, 1) mode at the q = 1 surface, where m and n are the poloidal and toroidal mode numbers and q is the safety factor. We study the nonlinear evolution of a particular test equilibrium in a non-reduced field representation using both resistive-MHD and extended-MHD models. We find growth rates for the extended-MHD reconnection process exhibitmore » a nonlinear acceleration and greatly exceed that of the resistive-MHD model, as is expected from previous experimental, theoretical, and computational work. We compare the properties of reconnection in the two simulations, revealing the reconnecting current sheets are locally different in the two models and we present the first observation of the quadrupole out-of-plane Hall magnetic field that appears during extended-MHD reconnection in a 3D toroidal simulation (but not in resistive-MHD). We also explore the dependence on toroidal angle of the properties of reconnection as viewed in the plane perpendicular to the helical magnetic field, finding qualitative and quantitative effects due to changes in the symmetry of the reconnection process. Furthermore, this study is potentially important for a wide range of magnetically confined fusion applications, from confirming simulations with extended-MHD effects are sufficiently resolved to describe reconnection, to quantifying local reconnection rates for purposes of understanding and predicting transport, not only at the q = 1 rational surface for sawteeth, but also at higher order rational surfaces that play a role in disruptions and edge-confinement degradation.« less

Near-edge band structures and band gaps of Cu-based semiconductors predicted by the modified Becke-Johnson potential plus an on-site Coulomb U

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

Zhang, Yubo; Zhang, Jiawei; Wang, Youwei

Diamond-like Cu-based multinary semiconductors are a rich family of materials that hold promise in a wide range of applications. Unfortunately, accurate theoretical understanding of the electronic properties of these materials is hindered by the involvement of Cu d electrons. Density functional theory (DFT) based calculations using the local density approximation or generalized gradient approximation often give qualitative wrong electronic properties of these materials, especially for narrow-gap systems. The modified Becke-Johnson (mBJ) method has been shown to be a promising alternative to more elaborate theory such as the GW approximation for fast materials screening and predictions. However, straightforward applications of themore » mBJ method to these materials still encounter significant difficulties because of the insufficient treatment of the localized d electrons. We show that combining the promise of mBJ potential and the spirit of the well-established DFT + U method leads to a much improved description of the electronic structures, including the most challenging narrow-gap systems. A survey of the band gaps of about 20 Cu-based semiconductors calculated using the mBJ + U method shows that the results agree with reliable values to within ±0.2 eV.« less

Theoretical models for electrochemical impedance spectroscopy and local ζ-potential of unfolded proteins in nanopores

NASA Astrophysics Data System (ADS)

Vitarelli, Michael J.; Talaga, David S.

2013-09-01

Single solid-state nanopores find increasing use for electrical detection and/or manipulation of macromolecules. These applications exploit the changes in signals due to the geometry and electrical properties of the molecular species found within the nanopore. The sensitivity and resolution of such measurements are also influenced by the geometric and electrical properties of the nanopore. This paper continues the development of an analytical theory to predict the electrochemical impedance spectra of nanopores by including the influence of the presence of an unfolded protein using the variable topology finite Warburg impedance model previously published by the authors. The local excluded volume of, and charges present on, the segment of protein sampled by the nanopore are shown to influence the shape and peak frequency of the electrochemical impedance spectrum. An analytical theory is used to relate the capacitive response of the electrical double layer at the surface of the protein to both the charge density at the protein surface and the more commonly measured zeta potential. Illustrative examples show how the theory predicts that the varying sequential regions of surface charge density and excluded volume dictated by the protein primary structure may allow for an impedance-based approach to identifying unfolded proteins.

Quantitative evaluation of orbital hybridization in carbon nanotubes under radial deformation using π-orbital axis vector

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

Ohnishi, Masato, E-mail: masato.ohnishi@rift.mech.tohoku.ac.jp; Suzuki, Ken; Miura, Hideo, E-mail: hmiura@rift.mech.tohoku.ac.jp

2015-04-15

When a radial strain is applied to a carbon nanotube (CNT), the increase in local curvature induces orbital hybridization. The effect of the curvature-induced orbital hybridization on the electronic properties of CNTs, however, has not been evaluated quantitatively. In this study, the strength of orbital hybridization in CNTs under homogeneous radial strain was evaluated quantitatively. Our analyses revealed the detailed procedure of the change in electronic structure of CNTs. In addition, the dihedral angle, the angle between π-orbital axis vectors of adjacent atoms, was found to effectively predict the strength of local orbital hybridization in deformed CNTs.

Energy-absorption capability of composite tubes and beams. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Farley, Gary L.; Jones, Robert M.

1989-01-01

In this study the objective was to develop a method of predicting the energy-absorption capability of composite subfloor beam structures. Before it is possible to develop such an analysis capability, an in-depth understanding of the crushing process of composite materials must be achieved. Many variables affect the crushing process of composite structures, such as the constituent materials' mechanical properties, specimen geometry, and crushing speed. A comprehensive experimental evaluation of tube specimens was conducted to develop insight into how composite structural elements crush and what are the controlling mechanisms. In this study the four characteristic crushing modes, transverse shearing, brittle fracturing, lamina bending, and local buckling were identified and the mechanisms that control the crushing process defined. An in-depth understanding was developed of how material properties affect energy-absorption capability. For example, an increase in fiber and matrix stiffness and failure strain can, depending upon the configuration of the tube, increase energy-absorption capability. An analysis to predict the energy-absorption capability of composite tube specimens was developed and verified. Good agreement between experiment and prediction was obtained.

Charged Particle Detection: Potential of Love Wave Acoustic Devices

NASA Astrophysics Data System (ADS)

Pedrick, Michael; Tittmann, Bernhard

2006-03-01

An investigation of the dependence of film density on group and phase velocities in a Love Wave Device shows potential for acoustic-based charged particle detection (CPD). Exposure of an ion sensitive photoresist to charged particles causes localized changes in density through either scission or cross-linking. A theoretical model was developed to study ion fluence effects on Love Wave sensitivity based on: ion energy, effective density changes, layer thickness and mode selection. The model is based on a Poly(Methyl Methacralate) (PMMA) film deposited on a Quartz substrate. The effect of Helium ion fluence on the properties of PMMA has previously been studied. These guidelines were used as an initial basis for the prediction of helium ion detection in a PMMA layer. Procedures for experimental characterization of ion effects on the material properties of PMMA are reviewed. Techniques for experimental validation of the predicted velocity shifts are discussed. A Love Wave Device for CPD could potentially provide a cost-effective alternative to semiconductor or photo-based counterparts. The potential for monitoring ion implantation effects on material properties is also discussed.

First principles calculation of thermo-mechanical properties of thoria using Quantum ESPRESSO

NASA Astrophysics Data System (ADS)

Malakkal, Linu; Szpunar, Barbara; Zuniga, Juan Carlos; Siripurapu, Ravi Kiran; Szpunar, Jerzy A.

2016-05-01

In this work, we have used Quantum ESPRESSO (QE), an open source first principles code, based on density-functional theory, plane waves, and pseudopotentials, along with quasi-harmonic approximation (QHA) to calculate the thermo-mechanical properties of thorium dioxide (ThO2). Using Python programming language, our group developed qe-nipy-advanced, an interface to QE, which can evaluate the structural and thermo-mechanical properties of materials. We predicted the phonon contribution to thermal conductivity (kL) using the Slack model. We performed the calculations within local density approximation (LDA) and generalized gradient approximation (GGA) with the recently proposed version for solids (PBEsol). We employed a Monkhorst-Pack 5 × 5 × 5 k-points mesh in reciprocal space with a plane wave cut-off energy of 150 Ry to obtain the convergence of the structure. We calculated the dynamical matrices of the lattice on a 4 × 4 × 4 mesh. We have predicted the heat capacity, thermal expansion and the phonon contribution to thermal conductivity, as a function of temperature up to 1400K, and compared them with the previous work and known experimental results.

pDHS-SVM: A prediction method for plant DNase I hypersensitive sites based on support vector machine.

PubMed

Zhang, Shanxin; Zhou, Zhiping; Chen, Xinmeng; Hu, Yong; Yang, Lindong

2017-08-07

DNase I hypersensitive sites (DHSs) are accessible chromatin regions hypersensitive to cleavages by DNase I endonucleases. DHSs are indicative of cis-regulatory DNA elements (CREs), all of which play important roles in global gene expression regulation. It is helpful for discovering CREs by recognition of DHSs in genome. To accelerate the investigation, it is an important complement to develop cost-effective computational methods to identify DHSs. However, there is a lack of tools used for identifying DHSs in plant genome. Here we presented pDHS-SVM, a computational predictor to identify plant DHSs. To integrate the global sequence-order information and local DNA properties, reverse complement kmer and dinucleotide-based auto covariance of DNA sequences were applied to construct the feature space. In this work, fifteen physical-chemical properties of dinucleotides were used and Support Vector Machine (SVM) was employed. To further improve the performance of the predictor and extract an optimized subset of nucleotide physical-chemical properties positive for the DHSs, a heuristic nucleotide physical-chemical property selection algorithm was introduced. With the optimized subset of properties, experimental results of Arabidopsis thaliana and rice (Oryza sativa) showed that pDHS-SVM could achieve accuracies up to 87.00%, and 85.79%, respectively. The results indicated the effectiveness of proposed method for predicting DHSs. Furthermore, pDHS-SVM could provide a helpful complement for predicting CREs in plant genome. Our implementation of the novel proposed method pDHS-SVM is freely available as source code, at https://github.com/shanxinzhang/pDHS-SVM. Copyright © 2017 Elsevier Ltd. All rights reserved.

Auditory Time-Frequency Masking for Spectrally and Temporally Maximally-Compact Stimuli

PubMed Central

Laback, Bernhard; Savel, Sophie; Ystad, Sølvi; Balazs, Peter; Meunier, Sabine; Kronland-Martinet, Richard

2016-01-01

Many audio applications perform perception-based time-frequency (TF) analysis by decomposing sounds into a set of functions with good TF localization (i.e. with a small essential support in the TF domain) using TF transforms and applying psychoacoustic models of auditory masking to the transform coefficients. To accurately predict masking interactions between coefficients, the TF properties of the model should match those of the transform. This involves having masking data for stimuli with good TF localization. However, little is known about TF masking for mathematically well-localized signals. Most existing masking studies used stimuli that are broad in time and/or frequency and few studies involved TF conditions. Consequently, the present study had two goals. The first was to collect TF masking data for well-localized stimuli in humans. Masker and target were 10-ms Gaussian-shaped sinusoids with a bandwidth of approximately one critical band. The overall pattern of results is qualitatively similar to existing data for long maskers. To facilitate implementation in audio processing algorithms, a dataset provides the measured TF masking function. The second goal was to assess the potential effect of auditory efferents on TF masking using a modeling approach. The temporal window model of masking was used to predict present and existing data in two configurations: (1) with standard model parameters (i.e. without efferents), (2) with cochlear gain reduction to simulate the activation of efferents. The ability of the model to predict the present data was quite good with the standard configuration but highly degraded with gain reduction. Conversely, the ability of the model to predict existing data for long maskers was better with than without gain reduction. Overall, the model predictions suggest that TF masking can be affected by efferent (or other) effects that reduce cochlear gain. Such effects were avoided in the experiment of this study by using maximally-compact stimuli. PMID:27875575

Auditory Time-Frequency Masking for Spectrally and Temporally Maximally-Compact Stimuli.

PubMed

Necciari, Thibaud; Laback, Bernhard; Savel, Sophie; Ystad, Sølvi; Balazs, Peter; Meunier, Sabine; Kronland-Martinet, Richard

2016-01-01

Many audio applications perform perception-based time-frequency (TF) analysis by decomposing sounds into a set of functions with good TF localization (i.e. with a small essential support in the TF domain) using TF transforms and applying psychoacoustic models of auditory masking to the transform coefficients. To accurately predict masking interactions between coefficients, the TF properties of the model should match those of the transform. This involves having masking data for stimuli with good TF localization. However, little is known about TF masking for mathematically well-localized signals. Most existing masking studies used stimuli that are broad in time and/or frequency and few studies involved TF conditions. Consequently, the present study had two goals. The first was to collect TF masking data for well-localized stimuli in humans. Masker and target were 10-ms Gaussian-shaped sinusoids with a bandwidth of approximately one critical band. The overall pattern of results is qualitatively similar to existing data for long maskers. To facilitate implementation in audio processing algorithms, a dataset provides the measured TF masking function. The second goal was to assess the potential effect of auditory efferents on TF masking using a modeling approach. The temporal window model of masking was used to predict present and existing data in two configurations: (1) with standard model parameters (i.e. without efferents), (2) with cochlear gain reduction to simulate the activation of efferents. The ability of the model to predict the present data was quite good with the standard configuration but highly degraded with gain reduction. Conversely, the ability of the model to predict existing data for long maskers was better with than without gain reduction. Overall, the model predictions suggest that TF masking can be affected by efferent (or other) effects that reduce cochlear gain. Such effects were avoided in the experiment of this study by using maximally-compact stimuli.

Underground localization using dual magnetic field sequence measurement and pose graph SLAM for directional drilling

NASA Astrophysics Data System (ADS)

Park, Byeolteo; Myung, Hyun

2014-12-01

With the development of unconventional gas, the technology of directional drilling has become more advanced. Underground localization is the key technique of directional drilling for real-time path following and system control. However, there are problems such as vibration, disconnection with external infrastructure, and magnetic field distortion. Conventional methods cannot solve these problems in real time or in various environments. In this paper, a novel underground localization algorithm using a re-measurement of the sequence of the magnetic field and pose graph SLAM (simultaneous localization and mapping) is introduced. The proposed algorithm exploits the property of the drilling system that the body passes through the previous pass. By comparing the recorded measurement from one magnetic sensor and the current re-measurement from another magnetic sensor, the proposed algorithm predicts the pose of the drilling system. The performance of the algorithm is validated through simulations and experiments.

Combining electronic structure and many-body theory with large databases: A method for predicting the nature of 4 f states in Ce compounds

NASA Astrophysics Data System (ADS)

Herper, H. C.; Ahmed, T.; Wills, J. M.; Di Marco, I.; Björkman, T.; Iuşan, D.; Balatsky, A. V.; Eriksson, O.

2017-08-01

Recent progress in materials informatics has opened up the possibility of a new approach to accessing properties of materials in which one assays the aggregate properties of a large set of materials within the same class in addition to a detailed investigation of each compound in that class. Here we present a large scale investigation of electronic properties and correlated magnetism in Ce-based compounds accompanied by a systematic study of the electronic structure and 4 f -hybridization function of a large body of Ce compounds. We systematically study the electronic structure and 4 f -hybridization function of a large body of Ce compounds with the goal of elucidating the nature of the 4 f states and their interrelation with the measured Kondo energy in these compounds. The hybridization function has been analyzed for more than 350 data sets (being part of the IMS database) of cubic Ce compounds using electronic structure theory that relies on a full-potential approach. We demonstrate that the strength of the hybridization function, evaluated in this way, allows us to draw precise conclusions about the degree of localization of the 4 f states in these compounds. The theoretical results are entirely consistent with all experimental information, relevant to the degree of 4 f localization for all investigated materials. Furthermore, a more detailed analysis of the electronic structure and the hybridization function allows us to make precise statements about Kondo correlations in these systems. The calculated hybridization functions, together with the corresponding density of states, reproduce the expected exponential behavior of the observed Kondo temperatures and prove a consistent trend in real materials. This trend allows us to predict which systems may be correctly identified as Kondo systems. A strong anticorrelation between the size of the hybridization function and the volume of the systems has been observed. The information entropy for this set of systems is about 0.42. Our approach demonstrates the predictive power of materials informatics when a large number of materials is used to establish significant trends. This predictive power can be used to design new materials with desired properties. The applicability of this approach for other correlated electron systems is discussed.

Earthquakes triggered by fluid extraction

USGS Publications Warehouse

Segall, P.

1989-01-01

Seismicity is correlated in space and time with production from some oil and gas fields where pore pressures have declined by several tens of megapascals. Reverse faulting has occurred both above and below petroleum reservoirs, and normal faulting has occurred on the flanks of at least one reservoir. The theory of poroelasticity requires that fluid extraction locally alter the state of stress. Calculations with simple geometries predict stress perturbations that are consistent with observed earthquake locations and focal mechanisms. Measurements of surface displacement and strain, pore pressure, stress, and poroelastic rock properties in such areas could be used to test theoretical predictions and improve our understanding of earthquake mechanics. -Author

First-principles calculations for elastic properties of OsB 2 under pressure

NASA Astrophysics Data System (ADS)

Yang, Jun-Wei; Chen, Xiang-Rong; Luo, Fen; Ji, Guang-Fu

2009-11-01

The structure, elastic properties and elastic anisotropy of orthorhombic OsB 2 are investigated by density functional theory method with the ultrasoft pseudopotential scheme in the frame of the generalized gradient approximation (GGA) as well as local density approximation (LDA). The obtained structural parameters, elastic constants, elastic anisotropy and Debye temperature for OsB 2 under pressure are consistent with the available experimental data and other theoretical results. It is found that the elastic constants, bulk modulus and Debye temperature of OsB 2 tend to increase with increasing pressure. It is predicted that OsB 2 is not a superhard material from our calculations.

Phase lag deduced information in photo-thermal actuation for nano-mechanical systems characterization

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

Bijster, R. J. F., E-mail: roy.bijster@tno.nl; Vreugd, J. de; Sadeghian, H.

2014-08-18

In photo-thermal actuation, heat is added locally to a micro-cantilever by means of a laser. A fraction of the irradiation is absorbed, yielding thermal stresses and deformations in the structure. Harmonic modulation of the laser power causes the cantilever to oscillate. Moreover, a phase lag is introduced which is very sensitive to the spot location and the cantilever properties. This phase lag is theoretically predicted and experimentally verified. Combined with thermo-mechanical properties of the cantilever and its geometry, the location of the laser spot, the thermal diffusivity, and the layer thicknesses of the cantilever can be extracted.

Dynamical properties of dissipative XYZ Heisenberg lattices

NASA Astrophysics Data System (ADS)

Rota, R.; Minganti, F.; Biella, A.; Ciuti, C.

2018-04-01

We study dynamical properties of dissipative XYZ Heisenberg lattices where anisotropic spin-spin coupling competes with local incoherent spin flip processes. In particular, we explore a region of the parameter space where dissipative magnetic phase transitions for the steady state have been recently predicted by mean-field theories and exact numerical methods. We investigate the asymptotic decay rate towards the steady state both in 1D (up to the thermodynamical limit) and in finite-size 2D lattices, showing that critical dynamics does not occur in 1D, but it can emerge in 2D. We also analyze the behavior of individual homodyne quantum trajectories, which reveal the nature of the transition.

Electronic structure properties of UO2 as a Mott insulator

NASA Astrophysics Data System (ADS)

Sheykhi, Samira; Payami, Mahmoud

2018-06-01

In this work using the density functional theory (DFT), we have studied the structural, electronic and magnetic properties of uranium dioxide with antiferromagnetic 1k-, 2k-, and 3k-order structures. Ordinary approximations in DFT, such as the local density approximation (LDA) or generalized gradient approximation (GGA), usually predict incorrect metallic behaviors for this strongly correlated electron system. Using Hubbard term correction for f-electrons, LDA+U method, as well as using the screened Heyd-Scuseria-Ernzerhof (HSE) hybrid functional for the exchange-correlation (XC), we have obtained the correct ground-state behavior as an insulator, with band gaps in good agreement with experiment.

Factors which predict violence victimization in Nigeria

PubMed Central

Fry, Lincoln J.

2014-01-01

Background: Violence is a major public health issue, globally as well as in the African continent. This paper looks at Nigeria and begins the process of identifying the factors that predict interpersonal violence in that country. The purpose is to interpret the implications of the results presented here for violence prevention programmes in Nigeria. Materials and Methods: The study is based on the responses of 2324 Nigerians included in Round Four of the Afrobarometer surveys. The study concentrates on 579 respondents who reported either they or someone else in their family had been the victim of violence, defined as being physically attacked, in the past year. Results: A logistical regression analysis revealed five significant factors that predicted interpersonal violence: being the victim of a property crime, the fear of crime, the respondents faith, whethera police station was in the local area and poverty. The findings revealed that 43.7% of the sample had been victimised within the past year and 18.8% had been the victim of both violent and property crimes. One surprising findingwas the number of respondents who were re-victimised; 75% of violence victims also had been property crime victims. Conclusions: These findings suggest that target hardening should be the basis to plan, implement and evaluate violence prevention programmes in Nigeria. Prevention personnel and/or law enforcement need to respond to reported incidents of property and/or violence victimisation and attempt to prepare victims to protect both their premises and their persons in the future. PMID:24970968

LOCALIZER: subcellular localization prediction of both plant and effector proteins in the plant cell

PubMed Central

Sperschneider, Jana; Catanzariti, Ann-Maree; DeBoer, Kathleen; Petre, Benjamin; Gardiner, Donald M.; Singh, Karam B.; Dodds, Peter N.; Taylor, Jennifer M.

2017-01-01

Pathogens secrete effector proteins and many operate inside plant cells to enable infection. Some effectors have been found to enter subcellular compartments by mimicking host targeting sequences. Although many computational methods exist to predict plant protein subcellular localization, they perform poorly for effectors. We introduce LOCALIZER for predicting plant and effector protein localization to chloroplasts, mitochondria, and nuclei. LOCALIZER shows greater prediction accuracy for chloroplast and mitochondrial targeting compared to other methods for 652 plant proteins. For 107 eukaryotic effectors, LOCALIZER outperforms other methods and predicts a previously unrecognized chloroplast transit peptide for the ToxA effector, which we show translocates into tobacco chloroplasts. Secretome-wide predictions and confocal microscopy reveal that rust fungi might have evolved multiple effectors that target chloroplasts or nuclei. LOCALIZER is the first method for predicting effector localisation in plants and is a valuable tool for prioritizing effector candidates for functional investigations. LOCALIZER is available at http://localizer.csiro.au/. PMID:28300209

Influence of Oil on Refrigerant Evaporator Performance

NASA Astrophysics Data System (ADS)

Kim, Jong-Soo; Nagata, Karsuya; Katsuta, Masafumi; Tomosugi, Hiroyuki; Kikuchi, Kouichiro; Horichi, Toshiaki

In vapor compression refrigeration system using oil-lubricated compressors, some amount of oil is always circulated through the system. Oil circulation can have a significant influence on the evaporator performance of automotive air conditioner which is especially required to cool quickly the car interior after a period standing in the sun. An experimental investigation was carried out an electrically heated horizontal tube to measure local heat transfer coefficients for various flow rates and heat fluxes during forced convection boiling of pure refrigerant R12 and refrigerant-oil mixtures (0-11% oil concentration by weight) and the results were compared with oil free performance. Local heat transfer coefficients increased at the region of low vapor quality by the addition of oil. On the other hand, because the oil-rich liquid film was formed on the heat transfer surface, heat transfer coefficients gradually decreased as the vapor quality became higher. Average heat transfer coefficient reached a maximum at about 4% oil concentration and this trend agreed well with the results of Green and Furse. Previous correlations, using the properties of the refrigerant-oil mixture, could not predict satisfactorily the local heat transfer coefficients data. New correlation modified by oil concentration factor was developed for predicting the corresponding heat transfer coefficient for refrigerant-oil mixture convection boiling. The maximum percent deviation between predicted and measured heat transfer coefficient was within ±30%.

High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models

PubMed Central

Welp, Gerhard; Thiel, Michael

2017-01-01

Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties–sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen–in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models–multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)–were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness, coloration and saturation were prominent predictors in digital soil mapping. Considering the increased availability of freely available Remote Sensing data (e.g. Landsat, SRTM, Sentinels), soil information at local and regional scales in data poor regions such as West Africa can be improved with relatively little financial and human resources. PMID:28114334

A Simplified Model of Moisture Transport in Hydrophilic Porous Media With Applications to Pharmaceutical Tablets.

PubMed

Klinzing, Gerard R; Zavaliangos, Antonios

2016-08-01

This work establishes a predictive model that explicitly recognizes microstructural parameters in the description of the overall mass uptake and local gradients of moisture into tablets. Model equations were formulated based on local tablet geometry to describe the transient uptake of moisture. An analytical solution to a simplified set of model equations was solved to predict the overall mass uptake and moisture gradients with the tablets. The analytical solution takes into account individual diffusion mechanisms in different scales of porosity and diffusion into the solid phase. The time constant of mass uptake was found to be a function of several key material properties, such as tablet relative density, pore tortuosity, and equilibrium moisture content of the material. The predictions of the model are in excellent agreement with experimental results for microcrystalline cellulose tablets without the need for parameter fitting. The model presented provides a new method to analyze the transient uptake of moisture into hydrophilic materials with the knowledge of only a few fundamental material and microstructural parameters. In addition, the model allows for quick and insightful predictions of moisture diffusion for a variety of practical applications including pharmaceutical tablets, porous polymer systems, or cementitious materials. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

A predictability study of Lorenz's 28-variable model as a dynamical system

NASA Technical Reports Server (NTRS)

Krishnamurthy, V.

1993-01-01

The dynamics of error growth in a two-layer nonlinear quasi-geostrophic model has been studied to gain an understanding of the mathematical theory of atmospheric predictability. The growth of random errors of varying initial magnitudes has been studied, and the relation between this classical approach and the concepts of the nonlinear dynamical systems theory has been explored. The local and global growths of random errors have been expressed partly in terms of the properties of an error ellipsoid and the Liapunov exponents determined by linear error dynamics. The local growth of small errors is initially governed by several modes of the evolving error ellipsoid but soon becomes dominated by the longest axis. The average global growth of small errors is exponential with a growth rate consistent with the largest Liapunov exponent. The duration of the exponential growth phase depends on the initial magnitude of the errors. The subsequent large errors undergo a nonlinear growth with a steadily decreasing growth rate and attain saturation that defines the limit of predictability. The degree of chaos and the largest Liapunov exponent show considerable variation with change in the forcing, which implies that the time variation in the external forcing can introduce variable character to the predictability.

Orbiter Boundary Layer Transition Prediction Tool Enhancements

NASA Technical Reports Server (NTRS)

Berry, Scott A.; King, Rudolph A.; Kegerise, Michael A.; Wood, William A.; McGinley, Catherine B.; Berger, Karen T.; Anderson, Brian P.

2010-01-01

Updates to an analytic tool developed for Shuttle support to predict the onset of boundary layer transition resulting from thermal protection system damage or repair are presented. The boundary layer transition tool is part of a suite of tools that analyze the local aerothermodynamic environment to enable informed disposition of damage for making recommendations to fly as is or to repair. Using mission specific trajectory information and details of each d agmea site or repair, the expected time (and thus Mach number) of transition onset is predicted to help define proper environments for use in subsequent thermal and stress analysis of the thermal protection system and structure. The boundary layer transition criteria utilized within the tool were updated based on new local boundary layer properties obtained from high fidelity computational solutions. Also, new ground-based measurements were obtained to allow for a wider parametric variation with both protuberances and cavities and then the resulting correlations were calibrated against updated flight data. The end result is to provide correlations that allow increased confidence with the resulting transition predictions. Recently, a new approach was adopted to remove conservatism in terms of sustained turbulence along the wing leading edge. Finally, some of the newer flight data are also discussed in terms of how these results reflect back on the updated correlations.

Laser-induced damage in biological tissue: Role of complex and dynamic optical properties of the medium

NASA Astrophysics Data System (ADS)

Ahmed, Elharith M.

Since its invention in the early 1960's, the laser has been used as a tool for surgical, therapeutic, and diagnostic purposes. To achieve maximum effectiveness with the greatest margin of safety it is important to understand the mechanisms of light propagation through tissue and how that light affects living cells. Lasers with novel output characteristics for medical and military applications are too often implemented prior to proper evaluation with respect to tissue optical properties and human safety. Therefore, advances in computational models that describe light propagation and the cellular responses to laser exposure, without the use of animal models, are of considerable interest. Here, a physics-based laser-tissue interaction model was developed to predict the spatial and temporal temperature and pressure rise during laser exposure to biological tissues. Our new model also takes into account the dynamic nature of tissue optical properties and their impact on the induced temperature and pressure profiles. The laser-induced retinal damage is attributed to the formation of microbubbles formed around melanosomes in the retinal pigment epithelium (RPE) and the damage mechanism is assumed to be photo-thermal. Selective absorption by melanin creates these bubbles that expand and collapse around melanosomes, destroying cell membranes and killing cells. The Finite Element (FE) approach taken provides suitable ground for modeling localized pigment absorption which leads to a non-uniform temperature distribution within pigmented cells following laser pulse exposure. These hot-spots are sources for localized thermo-elastic stresses which lead to rapid localized expansions that manifest themselves as microbubbles and lead to microcavitations. Model predictions for the interaction of lasers at wavelengths of 193, 694, 532, 590, 1314, 1540, 2000, and 2940 nm with biological tissues were generated and comparisons were made with available experimental data for the retina, cornea or the skin. Good agreement between model and experimental results established the validity of the model.

Meso-Scale Experimental & Numerical Studies for Predicting Macro-scale Performance of Advanced Reactive Materials (ARMs)

DTIC Science & Technology

2015-04-01

of impact-initiated reactions in Ti-Al-B based reactive materials in the form of compacts of powders of different sizes and morphologies . The major...More specifically, the influence of material-inherent elastic/plastic properties and reactant configuration (e.g., porosity, morphology , spacing...materials in the form of compacts of powders of different sizes and morphologies . The major goal is to delineate how processes of localized deformation and

Calculative techniques for transonic flows about certain classes of wing body combinations

NASA Technical Reports Server (NTRS)

Stahara, S. S.; Spreiter, J. R.

1972-01-01

Procedures based on the method of local linearization and transonic equivalence rule were developed for predicting properties of transonic flows about certain classes of wing-body combinations. The procedures are applicable to transonic flows with free stream Mach number in the ranges near one, below the lower critical and above the upper critical. Theoretical results are presented for surface and flow field pressure distributions for both lifting and nonlifting situations.

Application and analysis of debris-flow early warning system in Wenchuan earthquake-affected area

NASA Astrophysics Data System (ADS)

Liu, D. L.; Zhang, S. J.; Yang, H. J.; Zhao, L. Q.; Jiang, Y. H.; Tang, D.; Leng, X. P.

2016-02-01

The activities of debris flow (DF) in the Wenchuan earthquake-affected area significantly increased after the earthquake on 12 May 2008. The safety of the lives and property of local people is threatened by DFs. A physics-based early warning system (EWS) for DF forecasting was developed and applied in this earthquake area. This paper introduces an application of the system in the Wenchuan earthquake-affected area and analyzes the prediction results via a comparison to the DF events triggered by the strong rainfall events reported by the local government. The prediction accuracy and efficiency was first compared with a contribution-factor-based system currently used by the weather bureau of Sichuan province. The storm on 17 August 2012 was used as a case study for this comparison. The comparison shows that the false negative rate and false positive rate of the new system is, respectively, 19 and 21 % lower than the system based on the contribution factors. Consequently, the prediction accuracy is obviously higher than the system based on the contribution factors with a higher operational efficiency. On the invitation of the weather bureau of Sichuan province, the authors upgraded their prediction system of DF by using this new system before the monsoon of Wenchuan earthquake-affected area in 2013. Two prediction cases on 9 July 2013 and 10 July 2014 were chosen to further demonstrate that the new EWS has high stability, efficiency, and prediction accuracy.

FE-Analysis of Stretch-Blow Moulded Bottles Using an Integrative Process Simulation

NASA Astrophysics Data System (ADS)

Hopmann, C.; Michaeli, W.; Rasche, S.

2011-05-01

The two-stage stretch-blow moulding process has been established for the large scale production of high quality PET containers with excellent mechanical and optical properties. The total production costs of a bottle are significantly caused by the material costs. Due to this dominant share of the bottle material, the PET industry is interested in reducing the total production costs by an optimised material efficiency. However, a reduced material inventory means decreasing wall thicknesses and therewith a reduction of the bottle properties (e.g. mechanical properties, barrier properties). Therefore, there is often a trade-off between a minimal bottle weight and adequate properties of the bottle. In order to achieve the objectives Computer Aided Engineering (CAE) techniques can assist the designer of new stretch-blow moulded containers. Hence, tools such as the process simulation and the structural analysis have become important in the blow moulding sector. The Institute of Plastics Processing (IKV) at RWTH Aachen University, Germany, has developed an integrative three-dimensional process simulation which models the complete path of a preform through a stretch-blow moulding machine. At first, the reheating of the preform is calculated by a thermal simulation. Afterwards, the inflation of the preform to a bottle is calculated by finite element analysis (FEA). The results of this step are e.g. the local wall thickness distribution and the local biaxial stretch ratios. Not only the material distribution but also the material properties that result from the deformation history of the polymer have significant influence on the bottle properties. Therefore, a correlation between the material properties and stretch ratios is considered in an integrative simulation approach developed at IKV. The results of the process simulation (wall thickness, stretch ratios) are transferred to a further simulation program and mapped on the bottles FE mesh. This approach allows a local determination of the material properties and thus a more accurate prediction of the bottle properties. The approach was applied both for a mechanical structural analysis and for a barrier analysis. First results point out that the approach can improve the FE analysis and might be a helpful tool for designing new stretch-blow moulded bottles.

Instrumental record of debris flow initiation during natural rainfall: Implications for modeling slope stability

USGS Publications Warehouse

Montgomery, D.R.; Schmidt, K.M.; Dietrich, W.E.; McKean, J.

2009-01-01

The middle of a hillslope hollow in the Oregon Coast Range failed and mobilized as a debris flow during heavy rainfall in November 1996. Automated pressure transducers recorded high spatial variability of pore water pressure within the area that mobilized as a debris flow, which initiated where local upward flow from bedrock developed into overlying colluvium. Postfailure observations of the bedrock surface exposed in the debris flow scar reveal a strong spatial correspondence between elevated piezometric response and water discharging from bedrock fractures. Measurements of apparent root cohesion on the basal (Cb) and lateral (Cl) scarp demonstrate substantial local variability, with areally weighted values of Cb = 0.1 and Cl = 4.6 kPa. Using measured soil properties and basal root strength, the widely used infinite slope model, employed assuming slope parallel groundwater flow, provides a poor prediction of hydrologie conditions at failure. In contrast, a model including lateral root strength (but neglecting lateral frictional strength) gave a predicted critical value of relative soil saturation that fell within the range defined by the arithmetic and geometric mean values at the time of failure. The 3-D slope stability model CLARA-W, used with locally observed pore water pressure, predicted small areas with lower factors of safety within the overall slide mass at sites consistent with field observations of where the failure initiated. This highly variable and localized nature of small areas of high pore pressure that can trigger slope failure means, however, that substantial uncertainty appears inevitable for estimating hydrologie conditions within incipient debris flows under natural conditions. Copyright 2009 by the American Geophysical Union.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Predicting the Velocity Dispersions of the Dwarf Satellite Galaxies of Andromeda

NASA Astrophysics Data System (ADS)

McGaugh, Stacy S.

2016-05-01

Dwarf Spheroidal galaxies in the Local Group are the faintest and most diffuse stellar systems known. They exhibit large mass discrepancies, making them popular laboratories for studying the missing mass problem. The PANDAS survey of M31 revealed dozens of new examples of such dwarfs. As these systems were discovered, it was possible to use the observed photometric properties to predict their stellar velocity dispersions with the modified gravity theory MOND. These predictions, made in advance of the observations, have since been largely confirmed. A unique feature of MOND is that a structurally identical dwarf will behave differently when it is or is not subject to the external field of a massive host like Andromeda. The role of this "external field effect" is critical in correctly predicting the velocity dispersions of dwarfs that deviate from empirical scaling relations. With continued improvement in the observational data, these systems could provide a test of the strong equivalence principle.

Development of Tripropellant CFD Design Code

NASA Technical Reports Server (NTRS)

Farmer, Richard C.; Cheng, Gary C.; Anderson, Peter G.

1998-01-01

A tripropellant, such as GO2/H2/RP-1, CFD design code has been developed to predict the local mixing of multiple propellant streams as they are injected into a rocket motor. The code utilizes real fluid properties to account for the mixing and finite-rate combustion processes which occur near an injector faceplate, thus the analysis serves as a multi-phase homogeneous spray combustion model. Proper accounting of the combustion allows accurate gas-side temperature predictions which are essential for accurate wall heating analyses. The complex secondary flows which are predicted to occur near a faceplate cannot be quantitatively predicted by less accurate methodology. Test cases have been simulated to describe an axisymmetric tripropellant coaxial injector and a 3-dimensional RP-1/LO2 impinger injector system. The analysis has been shown to realistically describe such injector combustion flowfields. The code is also valuable to design meaningful future experiments by determining the critical location and type of measurements needed.

A pseudo-elastic effective material property representation of the costal cartilage for use in finite element models of the whole human body.

PubMed

Forman, Jason L; de Dios, Eduardo del Pozo; Kent, Richard W

2010-12-01

Injury-predictive finite element (FE) models of the chest must reproduce the structural coupling behavior of the costal cartilage accurately. Gross heterogeneities (the perichondrium and calcifications) may cause models developed based on local material properties to erroneously predict the structural behavior of cartilage segments. This study sought to determine the pseudo-elastic effective material properties required to reproduce the structural behavior of the costal cartilage under loading similar to what might occur in a frontal automobile collision. Twenty-eight segments of cadaveric costal cartilage were subjected to cantilever-like, dynamic loading. Three limited-mesh FE models were then developed for each specimen, having element sizes of 10 mm (typical of current whole-body FE models), 3 mm, and 2 mm. The cartilage was represented as a homogeneous, isotropic, linear elastic material. The elastic moduli of the cartilage models were optimized to fit the anterior-posterior (x-axis) force versus displacement responses observed in the experiments. For a subset of specimens, additional model validation tests were performed under a second boundary condition. The pseudo-elastic effective moduli ranged from 4.8 to 49 MPa, with an average and standard deviation of 22 ± 13.6 MPa. The models were limited in their ability to reproduce the lateral (y-axis) force responses observed in the experiments. The prediction of the x-axis and y-axis forces in the second boundary condition varied. Neither the effective moduli nor the model fit were significantly affected (Student's t-test, p < 0.05) by the model mesh density. The average pseudo-elastic effective moduli were significantly (p < 0.05) greater than local costal cartilage modulus values reported in the literature. These results are consistent with the presence of stiffening heterogeneities within the costal cartilage structure. These effective modulus values may provide guidance for the representation of the costal cartilage in whole-body FE models where these heterogeneities cannot be modeled distinctly.

The watercolor illusion and neon color spreading: a unified analysis of new cases and neural mechanisms

NASA Astrophysics Data System (ADS)

Pinna, Baingio; Grossberg, Stephen

2005-10-01

Coloration and figural properties of neon color spreading and the watercolor illusion are studied using phenomenal and psychophysical observations. Coloration properties of both effects can be reduced to a common limiting condition, a nearby color transition called the two-dot limiting case, which clarifies their perceptual similarities and dissimilarities. The results are explained by the FACADE neural model of biological vision. The model proposes how local properties of color transitions activate spatial competition among nearby perceptual boundaries, with boundaries of lower-contrast edges weakened by competition more than boundaries of higher-contrast edges. This asymmetry induces spreading of more color across these boundaries than conversely. The model also predicts how depth and figure-ground effects are generated in these illusions.

Large-scale Cortical Network Properties Predict Future Sound-to-Word Learning Success

PubMed Central

Sheppard, John Patrick; Wang, Ji-Ping; Wong, Patrick C. M.

2013-01-01

The human brain possesses a remarkable capacity to interpret and recall novel sounds as spoken language. These linguistic abilities arise from complex processing spanning a widely distributed cortical network and are characterized by marked individual variation. Recently, graph theoretical analysis has facilitated the exploration of how such aspects of large-scale brain functional organization may underlie cognitive performance. Brain functional networks are known to possess small-world topologies characterized by efficient global and local information transfer, but whether these properties relate to language learning abilities remains unknown. Here we applied graph theory to construct large-scale cortical functional networks from cerebral hemodynamic (fMRI) responses acquired during an auditory pitch discrimination task and found that such network properties were associated with participants’ future success in learning words of an artificial spoken language. Successful learners possessed networks with reduced local efficiency but increased global efficiency relative to less successful learners and had a more cost-efficient network organization. Regionally, successful and less successful learners exhibited differences in these network properties spanning bilateral prefrontal, parietal, and right temporal cortex, overlapping a core network of auditory language areas. These results suggest that efficient cortical network organization is associated with sound-to-word learning abilities among healthy, younger adults. PMID:22360625

An integrative model of the cardiac ventricular myocyte incorporating local control of Ca2+ release.

PubMed Central

Greenstein, Joseph L; Winslow, Raimond L

2002-01-01

The local control theory of excitation-contraction (EC) coupling in cardiac muscle asserts that L-type Ca(2+) current tightly controls Ca(2+) release from the sarcoplasmic reticulum (SR) via local interaction of closely apposed L-type Ca(2+) channels (LCCs) and ryanodine receptors (RyRs). These local interactions give rise to smoothly graded Ca(2+)-induced Ca(2+) release (CICR), which exhibits high gain. In this study we present a biophysically detailed model of the normal canine ventricular myocyte that conforms to local control theory. The model formulation incorporates details of microscopic EC coupling properties in the form of Ca(2+) release units (CaRUs) in which individual sarcolemmal LCCs interact in a stochastic manner with nearby RyRs in localized regions where junctional SR membrane and transverse-tubular membrane are in close proximity. The CaRUs are embedded within and interact with the global systems of the myocyte describing ionic and membrane pump/exchanger currents, SR Ca(2+) uptake, and time-varying cytosolic ion concentrations to form a model of the cardiac action potential (AP). The model can reproduce both the detailed properties of EC coupling, such as variable gain and graded SR Ca(2+) release, and whole-cell phenomena, such as modulation of AP duration by SR Ca(2+) release. Simulations indicate that the local control paradigm predicts stable APs when the L-type Ca(2+) current is adjusted in accord with the balance between voltage- and Ca(2+)-dependent inactivation processes as measured experimentally, a scenario where common pool models become unstable. The local control myocyte model provides a means for studying the interrelationship between microscopic and macroscopic behaviors in a manner that would not be possible in experiments. PMID:12496068

Shear-mediated contributions to the effective properties of soft acoustic metamaterials including negative index

PubMed Central

Forrester, Derek Michael; Pinfield, Valerie J.

2015-01-01

Here we show that, for sub-wavelength particles in a fluid, viscous losses due to shear waves and their influence on neighbouring particles significantly modify the effective acoustic properties, and thereby the conditions at which negative acoustic refraction occurs. Building upon earlier single particle scattering work, we adopt a multiple scattering approach to derive the effective properties (density, bulk modulus, wavenumber). We show,through theoretical prediction, the implications for the design of “soft” (ultrasonic) metamaterials based on locally-resonant sub-wavelength porous rubber particles, through selection of particle size and concentration, and demonstrate tunability of the negative speed zones by modifying the viscosity of the suspending medium. For these lossy materials with complex effective properties, we confirm the use of phase angles to define the backward propagation condition in preference to “single-” and “double-negative” designations. PMID:26686414

Tuning the thermoelectric properties of YNiBi half-Heusler alloy

NASA Astrophysics Data System (ADS)

Sharma, Sonu; Kumar, Pradeep

2018-04-01

A detail comparison between the results obtained for the electronic and transport properties of YNiBi half-Heusler alloy by local density approximation (LDA) and generalized gradient approximation (GGA) functionals with and without spin–orbit coupling (SOC) is presented. In the presence of SOC both functionals provide ∼30% smaller band gap. The transport coefficients computed without SOC confirm that YNiBi is a promising p-type thermoelectric material. However, with SOC at higher temperature, Seebeck coefficient was found to be negative because of the bipolar effects. Without SOC the computed power factor (PF) is found to be closer to the experimental value, while in the presence of SOC we have obtained comparatively smaller PF. No importance of SOC has been observed in the calculations of transport properties of the compound. The appropriate Ti doping in place of Y is predicted to significantly enhance the thermoelectric properties of YNiBi compound.

Prediction of Antibacterial Activity from Physicochemical Properties of Antimicrobial Peptides

PubMed Central

Melo, Manuel N.; Ferre, Rafael; Feliu, Lídia; Bardají, Eduard; Planas, Marta; Castanho, Miguel A. R. B.

2011-01-01

Consensus is gathering that antimicrobial peptides that exert their antibacterial action at the membrane level must reach a local concentration threshold to become active. Studies of peptide interaction with model membranes do identify such disruptive thresholds but demonstrations of the possible correlation of these with the in vivo onset of activity have only recently been proposed. In addition, such thresholds observed in model membranes occur at local peptide concentrations close to full membrane coverage. In this work we fully develop an interaction model of antimicrobial peptides with biological membranes; by exploring the consequences of the underlying partition formalism we arrive at a relationship that provides antibacterial activity prediction from two biophysical parameters: the affinity of the peptide to the membrane and the critical bound peptide to lipid ratio. A straightforward and robust method to implement this relationship, with potential application to high-throughput screening approaches, is presented and tested. In addition, disruptive thresholds in model membranes and the onset of antibacterial peptide activity are shown to occur over the same range of locally bound peptide concentrations (10 to 100 mM), which conciliates the two types of observations. PMID:22194847

ClusPro: an automated docking and discrimination method for the prediction of protein complexes.

PubMed

Comeau, Stephen R; Gatchell, David W; Vajda, Sandor; Camacho, Carlos J

2004-01-01

Predicting protein interactions is one of the most challenging problems in functional genomics. Given two proteins known to interact, current docking methods evaluate billions of docked conformations by simple scoring functions, and in addition to near-native structures yield many false positives, i.e. structures with good surface complementarity but far from the native. We have developed a fast algorithm for filtering docked conformations with good surface complementarity, and ranking them based on their clustering properties. The free energy filters select complexes with lowest desolvation and electrostatic energies. Clustering is then used to smooth the local minima and to select the ones with the broadest energy wells-a property associated with the free energy at the binding site. The robustness of the method was tested on sets of 2000 docked conformations generated for 48 pairs of interacting proteins. In 31 of these cases, the top 10 predictions include at least one near-native complex, with an average RMSD of 5 A from the native structure. The docking and discrimination method also provides good results for a number of complexes that were used as targets in the Critical Assessment of PRedictions of Interactions experiment. The fully automated docking and discrimination server ClusPro can be found at http://structure.bu.edu

Damping in Space Constructions

NASA Astrophysics Data System (ADS)

de Vreugd, Jan; de Lange, Dorus; Winters, Jasper; Human, Jet; Kamphues, Fred; Tabak, Erik

2014-06-01

Monolithic structures are often used in optomechanical designs for space applications to achieve high dimensional stability and to prevent possible backlash and friction phenomena. The capacity of monolithic structures to dissipate mechanical energy is however limited due to the high Q-factor, which might result in high stresses during dynamic launch loads like random vibration, sine sweeps and shock. To reduce the Q-factor in space applications, the effect of constrained layer damping (CLD) is investigated in this work. To predict the damping increase, the CLD effect is implemented locally at the supporting struts in an existing FE model of an optical instrument. Numerical simulations show that the effect of local damping treatment in this instrument could reduce the vibrational stresses with 30-50%. Validation experiments on a simple structure showed good agreement between measured and predicted damping properties. This paper presents material characterization, material modeling, numerical implementation of damping models in finite element code, numerical results on space hardware and the results of validation experiments.

Superconducting terahertz mixer using a transition-edge microbolometer

NASA Technical Reports Server (NTRS)

Prober, D. E.

1993-01-01

We present a new device concept for a mixer element for THz frequencies. This uses a superconducting transition-edge microbridge biased at the center of its superconducting transition near 4.2 K. It is fed from an antenna or waveguide structure. Power from a local oscillator and an RF signal produce a temperature and resulting resistance variation at the difference frequency. The new aspect is the use of a very short bridge in which rapid (less than 0.1 ns) outdiffusion of hot electrons occurs. This gives large intermediate frequency (IF) response. The mixer offers about 4 GHz IF bandwidth, about 80 ohm RF resistive impedance, good match to the IF amplifier, and requires only 1-20 nW of local oscillator power. The upper RF frequency is determined by antenna or waveguide properties. Predicted mixer conversion efficiency is 1/8, and predicted double-sideband receiver noise temperatures are 260 and 90 K for transition widths of 0.1 and 0.5 Tc, respectively.

A biomechanical model of agonist-initiated contraction in the asthmatic airway.

PubMed

Brook, B S; Peel, S E; Hall, I P; Politi, A Z; Sneyd, J; Bai, Y; Sanderson, M J; Jensen, O E

2010-01-31

This paper presents a modelling framework in which the local stress environment of airway smooth muscle (ASM) cells may be predicted and cellular responses to local stress may be investigated. We consider an elastic axisymmetric model of a layer of connective tissue and circumferential ASM fibres embedded in parenchymal tissue and model the active contractile force generated by ASM via a stress acting along the fibres. A constitutive law is proposed that accounts for active and passive material properties as well as the proportion of muscle to connective tissue. The model predicts significantly different contractile responses depending on the proportion of muscle to connective tissue in the remodelled airway. We find that radial and hoop-stress distributions in remodelled muscle layers are highly heterogenous with distinct regions of compression and tension. Such patterns of stress are likely to have important implications, from a mechano-transduction perspective, on contractility, short-term cytoskeletal adaptation and long-term airway remodelling in asthma. Copyright 2009 Elsevier B.V. All rights reserved.

Large exchange anisotropy in quasi-one-dimensional spin-1/2 fluoride antiferromagnets with a d (z2)1 ground state

NASA Astrophysics Data System (ADS)

Kurzydłowski, D.; Grochala, W.

2017-10-01

Hybrid density functional calculations are performed for a variety of systems containing d9 ions (C u2 + and A g2 + ) and exhibiting quasi-one-dimensional magnetic properties. In particular, we study fluorides containing these ions in a rarely encountered compressed octahedral coordination that forces the unpaired electron into the local d (z2) orbital. We predict that such systems should exhibit exchange anisotropies surpassing that of S r2Cu O3 , one of the best realizations of a one-dimensional system known to date. In particular, we predict that the interchain coupling in the A g2 + -containing [AgF ] [B F4 ] system should be nearly four orders of magnitude smaller than the intrachain interaction. Our results indicate that quasi-one-dimensional spin-1/2 systems containing chains with spin sites in the d (z2)1 local ground state could constitute a versatile model for testing modern theories of quantum many-body physics in the solid state.

Dynamic localization and shear-induced hopping of particles: A way to understand the rheology of dense colloidal dispersions

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

Jiang, Tianying; Zukoski, Charles F., E-mail: czukoski@illinois.edu

2014-09-01

For decades, attempts have been made to understand the formation of colloidal glasses and gels by linking suspension mechanics to particle properties where details of size, shape, and spatial dependencies of pair potentials present a bewildering array of variables that can be manipulated to achieve observed properties. Despite the range of variables that control suspension properties, one consistent observation is the remarkably similarity of flow properties observed as particle properties are varied. Understanding the underlying origins of the commonality in those behaviors (e.g., shear-thinning with increasing stress, diverging zero shear rate viscosity with increasing volume fraction, development of a dynamicmore » yield stress plateau with increases in volume faction or strength of attraction, development of two characteristic relaxation times probed in linear viscoelasticity, the creation of a rubbery plateau modulus at high strain frequencies, and shear-thickening) remains a challenge. Recently, naïve mode coupling and dynamic localization theories have been developed to capture collective behavior giving rise to formation of colloidal glasses and gels. This approach characterizes suspension mechanics of strongly interacting particles in terms of sluggish long-range particle diffusion modulated by varying particle interactions and volume fraction. These theories capture the scaling of the modulus with the volume fraction and strength of interparticle attraction, the frequency dependence of the moduli at the onset of the gel/glass transition, together with the divergence of the zero shear rate viscosity and cessation of diffusivity for hard sphere systems as close packing is approached. In this study, we explore the generality of the predictions of dynamic localization theory for systems of particles composed of bimodal particle size distributions experiencing weak interactions. We find that the mechanical properties of these suspensions are well captured within the framework of dynamic localization theory and that suspension mechanics can be understood in terms of a dynamical potential barrier, the magnitude of which governs the zero shear rate viscosity, and onset of a dynamic yield stress plateau as volume fraction or strength of interaction is raised.« less

Magnetic properties of Gd intermetallics

DOE PAGES

Petit, Leon; Szotek, Zdzislawa; Jackson, Jerome; ...

2017-04-06

Here, using first-principles calculations, based on disordered local moment theory, combined with the self-interaction corrected local spin density approximation, we study magnetic interactions in GdX intermetallics for X = Cu, Zn, Ga, Cd, and Mg. Our predicted magnetic orders and ordering temperatures both at zero and other pressures agree well with experiments including the large increase in the Curie temperature of GdCd under pressure that is shown by our own experimental measurements. From our results it emerges that the Ruderman-Kittel-Kasuya-Yosida interaction on its own can not explain the observed behaviour under pressure, and that the magnetic ordering mechanism is stronglymore » influenced by the occupations of both Gd and anion d-bands.« less

Review of incursive, hyperincursive and anticipatory systems-foundation of anticipation in electromagnetism

NASA Astrophysics Data System (ADS)

Dubois, Daniel M.

2000-05-01

The main purpose of this paper is to show that anticipation is not only a property of biosystems but is also a fundamental property of physical systems. In electromagnetism, the anticipation is related to the Lorentz transform. In this framework the anticipation is a strong anticipation because it is not based on a prediction from a model of the physical system but is embedded in the fundamental system. So, Robert Rosen's anticipatory systems deal with weak anticipation. Contrary to Robert Rosen's affirmation, anticipation is thus not a characteristic of living systems. Finality is implicitly embedded in any system and thus the final cause of Aristotle is implicitly embedded in any physical and biological systems, contrary to what Robert Rosen argued. This paper will review some incursive and hyperincursive systems giving rise to strong anticipation. Space-time incursive parabolic systems show non-local properties. Hyperincursive crisp systems are related to catastrophe theory. Finally it will be shown that incursive and hyperincursive anticipatory systems could model properties of biosystems like free will, game strategy, theorem creation, etc. Anticipation is not only related to predictions but to decisions: hyperincursive systems create multiple choices and a decision process selects one choice. So, anticipation is not a final goal, like in cybernetics and system science, but is a fundamental property of physical and biological systems.

Drude weight fluctuations in many-body localized systems

NASA Astrophysics Data System (ADS)

Filippone, Michele; Brouwer, Piet W.; Eisert, Jens; von Oppen, Felix

2016-11-01

We numerically investigate the distribution of Drude weights D of many-body states in disordered one-dimensional interacting electron systems across the transition to a many-body localized phase. Drude weights are proportional to the spectral curvatures induced by magnetic fluxes in mesoscopic rings. They offer a method to relate the transition to the many-body localized phase to transport properties. In the delocalized regime, we find that the Drude weight distribution at a fixed disorder configuration agrees well with the random-matrix-theory prediction P (D ) ∝(γ2+D2) -3 /2 , although the distribution width γ strongly fluctuates between disorder realizations. A crossover is observed towards a distribution with different large-D asymptotics deep in the many-body localized phase, which however differs from the commonly expected Cauchy distribution. We show that the average distribution width <γ >, rescaled by L Δ ,Δ being the average level spacing in the middle of the spectrum and L the systems size, is an efficient probe of the many-body localization transition, as it increases (vanishes) exponentially in the delocalized (localized) phase.

Constitutive Modeling of Nanotube-Reinforced Polymer Composite Systems

NASA Technical Reports Server (NTRS)

Odegard, Gregory M.; Harik, Vasyl M.; Wise, Kristopher E.; Gates, Thomas S.

2004-01-01

In this study, a technique has been proposed for developing constitutive models for polymer composite systems reinforced with single-walled carbon nanotubes (SWNT). Since the polymer molecules are on the same size scale as the nanotubes, the interaction at the polymer/nanotube interface is highly dependent on the local molecular structure and bonding. At these small length scales, the lattice structures of the nanotube and polymer chains cannot be considered continuous, and the bulk mechanical properties of the SWNT/polymer composites can no longer be determined through traditional micromechanical approaches that are formulated using continuum mechanics. It is proposed herein that the nanotube, the local polymer near the nanotube, and the nanotube/polymer interface can be modeled as an effective continuum fiber using an equivalent-continuum modeling method. The effective fiber retains the local molecular structure and bonding information and serves as a means for incorporating micromechanical analyses for the prediction of bulk mechanical properties of SWNT/polymer composites with various nanotube sizes and orientations. As an example, the proposed approach is used for the constitutive modeling of two SWNT/polyethylene composite systems, one with continuous and aligned SWNT and the other with discontinuous and randomly aligned nanotubes.

Constitutive Modeling of Nanotube-Reinforced Polymer Composite Systems

NASA Technical Reports Server (NTRS)

Odegard, Gregory M.; Harik, Vasyl M.; Wise, Kristopher E.; Gates, Thomas S.

2001-01-01

In this study, a technique has been proposed for developing constitutive models for polymer composite systems reinforced with single-walled carbon nanotubes (SWNT). Since the polymer molecules are on the same size scale as the nanotubes, the interaction at the polymer/nanotube interface is highly dependent on the local molecular structure and bonding. At these small length scales, the lattice structures of the nanotube and polymer chains cannot be considered continuous, and the bulk mechanical properties of the SWNT/polymer composites can no longer be determined through traditional micromechanical approaches that are formulated using continuum mechanics. It is proposed herein that the nanotube, the local polymer near the nanotube, and the nanotube/polymer interface can be modeled as an effective continuum fiber using an equivalent-continuum modeling method. The effective fiber retains the local molecular structure and bonding information and serves as a means for incorporating micromechanical analyses for the prediction of bulk mechanical properties of SWNT/polymer composites with various nanotube sizes and orientations. As an example, the proposed approach is used for the constitutive modeling of two SWNT/polyethylene composite systems, one with continuous and aligned SWNT and the other with discontinuous and randomly aligned nanotubes.

Characterization of Triaxial Braided Composite Material Properties for Impact Simulation

NASA Technical Reports Server (NTRS)

Roberts, Gary D.; Goldberg, Robert K.; Biniendak, Wieslaw K.; Arnold, William A.; Littell, Justin D.; Kohlman, Lee W.

2009-01-01

The reliability of impact simulations for aircraft components made with triaxial braided carbon fiber composites is currently limited by inadequate material property data and lack of validated material models for analysis. Improvements to standard quasi-static test methods are needed to account for the large unit cell size and localized damage within the unit cell. The deformation and damage of a triaxial braided composite material was examined using standard quasi-static in-plane tension, compression, and shear tests. Some modifications to standard test specimen geometries are suggested, and methods for measuring the local strain at the onset of failure within the braid unit cell are presented. Deformation and damage at higher strain rates is examined using ballistic impact tests on 61- by 61- by 3.2-mm (24- by 24- by 0.125-in.) composite panels. Digital image correlation techniques were used to examine full-field deformation and damage during both quasi-static and impact tests. An impact analysis method is presented that utilizes both local and global deformation and failure information from the quasi-static tests as input for impact simulations. Improvements that are needed in test and analysis methods for better predictive capability are examined.

Structural, electronic, and thermodynamic properties of curium dioxide: Density functional theory calculations

NASA Astrophysics Data System (ADS)

Hou, Ling; Li, Wei-Dong; Wang, Fangwei; Eriksson, Olle; Wang, Bao-Tian

2017-12-01

We present a systematic investigation of the structural, magnetic, electronic, mechanical, and thermodynamic properties of CmO2 with the local density approximation (LDA)+U and the generalized gradient approximation (GGA)+U approaches. The strong Coulomb repulsion and the spin-orbit coupling (SOC) effects on the lattice structures, electronic density of states, and band gaps are carefully studied, and compared with other A O2 (A =U , Np, Pu, and Am). The ferromagnetic configuration with half-metallic character is predicted to be energetically stable while a charge-transfer semiconductor is predicted for the antiferromagnetic configuration. The elastic constants and phonon spectra show that the fluorite structure is mechanically and dynamically stable. Based on the first-principles phonon density of states, the lattice vibrational energy is calculated using the quasiharmonic approximation. Then, the Gibbs free energy, thermal expansion coefficient, specific heat, and entropy are obtained and compared with experimental data. The mode Grüneisen parameters are presented to analyze the anharmonic properties. The Slack relation is applied to obtain the lattice thermal conductivity in temperature range of 300-1600 K. The phonon group velocities are also calculated to investigate the heat transfer. For all these properties, if available, we compare the results of CmO2 with other A O2 .

Beyond the standard two-film theory: Computational fluid dynamics simulations for carbon dioxide capture in a wetted wall column

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

Wang, Chao; Xu, Zhijie; Lai, Canhai

The standard two-film theory (STFT) is a diffusion-based mechanism that can be used to describe gas mass transfer across liquid film. Fundamental assumptions of the STFT impose serious limitations on its ability to predict mass transfer coefficients. To better understand gas absorption across liquid film in practical situations, a multiphase computational fluid dynamics (CFD) model fully equipped with mass transport and chemistry capabilities has been developed for solvent-based carbon dioxide (CO 2) capture to predict the CO 2 mass transfer coefficient in a wetted wall column. The hydrodynamics is modeled using a volume of fluid method, and the diffusive andmore » reactive mass transfer between the two phases is modeled by adopting a one-fluid formulation. We demonstrate that the proposed CFD model can naturally account for the influence of many important factors on the overall mass transfer that cannot be quantitatively explained by the STFT, such as the local variation in fluid velocities and properties, flow instabilities, and complex geometries. The CFD model also can predict the local mass transfer coefficient variation along the column height, which the STFT typically does not consider.« less

Beyond the standard two-film theory: Computational fluid dynamics simulations for carbon dioxide capture in a wetted wall column

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

Wang, Chao; Xu, Zhijie; Lai, Canhai

The standard two-film theory (STFT) is a diffusion-based mechanism that can be used to describe gas mass transfer across liquid film. Fundamental assumptions of the STFT impose serious limitations on its ability to predict mass transfer coefficients. To better understand gas absorption across liquid film in practical situations, a multiphase computational fluid dynamics (CFD) model fully equipped with mass transport and chemistry capabilities has been developed for solvent-based carbon dioxide (CO2) capture to predict the CO2 mass transfer coefficient in a wetted wall column. The hydrodynamics is modeled using a volume of fluid method, and the diffusive and reactive massmore » transfer between the two phases is modeled by adopting a one-fluid formulation. We demonstrate that the proposed CFD model can naturally account for the influence of many important factors on the overall mass transfer that cannot be quantitatively explained by the STFT, such as the local variation in fluid velocities and properties, flow instabilities, and complex geometries. The CFD model also can predict the local mass transfer coefficient variation along the column height, which the STFT typically does not consider.« less

Micromechanics and Piezo Enhancements of HyperSizer

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Bednarcyk, Brett A.; Yarrington, Phillip; Collier, Craig S.

2006-01-01

The commercial HyperSizer aerospace-composite-material-structure-sizing software has been enhanced by incorporating capabilities for representing coupled thermal, piezoelectric, and piezomagnetic effects on the levels of plies, laminates, and stiffened panels. This enhancement is based on a formulation similar to that of the pre-existing HyperSizer capability for representing thermal effects. As a result of this enhancement, the electric and/or magnetic response of a material or structure to a mechanical or thermal load, or its mechanical response to an applied electric or magnetic field can be predicted. In another major enhancement, a capability for representing micromechanical effects has been added by establishment of a linkage between HyperSizer and Glenn Research Center s Micromechanics Analysis Code With Generalized Method of Cells (MAC/GMC) computer program, which was described in several prior NASA Tech Briefs articles. The linkage enables Hyper- Sizer to localize to the fiber and matrix level rather than only to the ply level, making it possible to predict local failures and to predict properties of plies from those of the component fiber and matrix materials. Advanced graphical user interfaces and database structures have been developed to support the new HyperSizer micromechanics capabilities.

Turbulent heat transfer prediction method for application to scramjet engines

NASA Technical Reports Server (NTRS)

Pinckney, S. Z.

1974-01-01

An integral method for predicting boundary layer development in turbulent flow regions on two-dimensional or axisymmetric bodies was developed. The method has the capability of approximating nonequilibrium velocity profiles as well as the local surface friction in the presence of a pressure gradient. An approach was developed for the problem of predicting the heat transfer in a turbulent boundary layer in the presence of a high pressure gradient. The solution was derived with particular emphasis on its applicability to supersonic combustion; thus, the effects of real gas flows were included. The resulting integrodifferential boundary layer method permits the estimation of cooling reguirements for scramjet engines. Theoretical heat transfer results are compared with experimental combustor and noncombustor heat transfer data. The heat transfer method was used in the development of engine design concepts which will produce an engine with reduced cooling requirements. The Langley scramjet engine module was designed by utilizing these design concepts and this engine design is discussed along with its corresponding cooling requirements. The heat transfer method was also used to develop a combustor cooling correlation for a combustor whose local properties are computed one dimensionally by assuming a linear area variation and a given heat release schedule.

Beyond the standard two-film theory: Computational fluid dynamics simulations for carbon dioxide capture in a wetted wall column

DOE PAGES

Wang, Chao; Xu, Zhijie; Lai, Canhai; ...

2018-03-27

The standard two-film theory (STFT) is a diffusion-based mechanism that can be used to describe gas mass transfer across liquid film. Fundamental assumptions of the STFT impose serious limitations on its ability to predict mass transfer coefficients. To better understand gas absorption across liquid film in practical situations, a multiphase computational fluid dynamics (CFD) model fully equipped with mass transport and chemistry capabilities has been developed for solvent-based carbon dioxide (CO 2) capture to predict the CO 2 mass transfer coefficient in a wetted wall column. The hydrodynamics is modeled using a volume of fluid method, and the diffusive andmore » reactive mass transfer between the two phases is modeled by adopting a one-fluid formulation. We demonstrate that the proposed CFD model can naturally account for the influence of many important factors on the overall mass transfer that cannot be quantitatively explained by the STFT, such as the local variation in fluid velocities and properties, flow instabilities, and complex geometries. The CFD model also can predict the local mass transfer coefficient variation along the column height, which the STFT typically does not consider.« less

Atomic scale imaging of magnetic circular dichroism by achromatic electron microscopy.

PubMed

Wang, Zechao; Tavabi, Amir H; Jin, Lei; Rusz, Ján; Tyutyunnikov, Dmitry; Jiang, Hanbo; Moritomo, Yutaka; Mayer, Joachim; Dunin-Borkowski, Rafal E; Yu, Rong; Zhu, Jing; Zhong, Xiaoyan

2018-03-01

In order to obtain a fundamental understanding of the interplay between charge, spin, orbital and lattice degrees of freedom in magnetic materials and to predict and control their physical properties 1-3 , experimental techniques are required that are capable of accessing local magnetic information with atomic-scale spatial resolution. Here, we show that a combination of electron energy-loss magnetic chiral dichroism 4 and chromatic-aberration-corrected transmission electron microscopy, which reduces the focal spread of inelastically scattered electrons by orders of magnitude when compared with the use of spherical aberration correction alone, can achieve atomic-scale imaging of magnetic circular dichroism and provide element-selective orbital and spin magnetic moments atomic plane by atomic plane. This unique capability, which we demonstrate for Sr 2 FeMoO 6 , opens the door to local atomic-level studies of spin configurations in a multitude of materials that exhibit different types of magnetic coupling, thereby contributing to a detailed understanding of the physical origins of magnetic properties of materials at the highest spatial resolution.

Modeling coupled thermal-hydrological-chemical processes in theunsaturated fractured rock of Yucca Mountain, Nevada: Heterogeneity andseepage

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

Mukhopadhyay, Sumit; Sonnenthal, Eric L.; Spycher, Nicolas

An understanding of processes affecting seepage intoemplacement tunnels is needed for correctly predicting the performance ofunderground radioactive waste repositories. It has been previouslyestimated that the capillary and vaporization barriers in the unsaturatedfractured rock of Yucca Mountain are enough to prevent seepage underpresent day infiltration conditions. It has also been thought that asubstantially elevated infiltration flux will be required to causeseepage after the thermal period is over. While coupledthermal-hydrological-chemical (THC) changes in Yucca Mountain host rockdue to repository heating has been previously investigated, those THCmodels did not incorporate elements of the seepage model. In this paper,we combine the THC processes inmore » unsaturated fractured rock with theprocesses affecting seepage. We observe that the THC processes alter thehydrological properties of the fractured rock through mineralprecipitation and dissolution. We show that such alteration in thehydrological properties of the rock often leads to local flow channeling.We conclude that such local flow channeling may result in seepage undercertain conditions, even with nonelevated infiltrationfluxes.« less

Synthesis, crystal structure analysis, molecular docking studies and density functional theory predictions of the local reactive properties and degradation properties of a novel halochalcone

NASA Astrophysics Data System (ADS)

Arshad, Suhana; Pillai, Renjith Raveendran; Zainuri, Dian Alwani; Khalib, Nuridayanti Che; Razak, Ibrahim Abdul; Armaković, Stevan; Armaković, Sanja J.

2017-09-01

In the present study, single crystals of E)-3-(3,5-dichlorophenyl)-1-(4-fluorophenyl)prop-2-en-1-one, were prepared and structurally characterized by single crystal X-ray diffraction analysis. The molecular structure crystallized in monoclinic crystal system with P21/c space group. Sensitivity of the title molecule towards electrophilic attacks has been examined by calculations of average localized ionization energies (ALIE) and their mapping to electron density surface. Further determination of atoms that could be important reactive centres has been performed by calculations of Fukui functions. Sensitivity of title molecule towards autoxidation and hydrolysis mechanisms has been assessed by calculations of bond dissociation energies and radial distribution functions (RDF), respectively. Also, in order to explore possible binding mode of the title compound towards Dihydrofolate reductase enzyme, we have utilized in silico molecular docking to explore possible binding modes of the title compound with the DHFR enzyme.

Constitutive Modeling of Nanotube-Reinforced Polymer Composites

NASA Technical Reports Server (NTRS)

Odegard, G. M.; Gates, T. S.; Wise, K. E.; Park, C.; Siochi, E. J.; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

In this study, a technique is presented for developing constitutive models for polymer composite systems reinforced with single-walled carbon nanotubes (SWNT). Because the polymer molecules are on the same size scale as the nanotubes, the interaction at the polymer/nanotube interface is highly dependent on the local molecular structure and bonding. At these small length scales, the lattice structures of the nanotube and polymer chains cannot be considered continuous, and the bulk mechanical properties can no longer be determined through traditional micromechanical approaches that are formulated by using continuum mechanics. It is proposed herein that the nanotube, the local polymer near the nanotube, and the nanotube/polymer interface can be modeled as an effective continuum fiber using an equivalent-continuum modeling method. The effective fiber serves as a means for incorporating micromechanical analyses for the prediction of bulk mechanical properties of SWNT/polymer composites with various nanotube lengths, concentrations, and orientations. As an example, the proposed approach is used for the constitutive modeling of two SWNT/polyimide composite systems.

Corrosion behavior of a superduplex stainless steel in chloride aqueous solution

NASA Astrophysics Data System (ADS)

Dabalà, Manuele; Calliari, Irene; Variola, Alessandra

2004-04-01

Super duplex stainless steels (SDSS) have been widely used as structural materials for chemical plants (especially in those engaged in phosphoric acid production), in the hydrometallurgy industries, and as materials for offshore applications due to their excellent corrosion resistance in chloride environments, compared with other commercial types of ferritic stainless steels. These alloys also possess superior weldability and better mechanical properties than austenitic stainless steels. However, due to their two-phase structure, the nature of which is very dependent on their composition and thermal history, the behavior of SDSS regarding localized corrosion appears difficult to predict, especially in chloride environments. To improve their final properties, the effect of the partition of the alloying elements between the two phases, and the composition and microstructure of each phase are the key to understanding the localized corrosion phenomena of SDSS. This paper concerns the effects of the SDSS microstructure and heat treatment on the SDSS corrosion resistance in aqueous solutions, containing different amounts of NaCl at room temperature.

Electronic Interfacial Effects in Epitaxial Heterostructures based on LaMnO3.

NASA Astrophysics Data System (ADS)

Christen, Hans M.; Varela, M.; Lee, H. N.; Kim, D. H.; Chisholm, M. F.; Cantoni, C.; Petit, L.; Schulthess, T. C.; Lowndes, D. H.

2006-03-01

Studies of chemically abrupt interfaces provide an ideal platform to study the effects of discontinuities and asymmetries of the electronic configuration on the transport and magnetic properties of complex oxides. In addition, the behavior of complex materials near interfaces plays the most crucial role not only in devices and nanostructures but also in complex structures in the form of composites and superlattices, including artificial multiferroics. Interfaces in the ABO3 perovskite system are particularly attractive because structurally similar oxides with fundamentally different physical properties can be integrated epitaxially. To explore the electronic effects at interfaces and to probe the physical properties that result from local electronic changes, we have synthesized structures containing LaMnO3 and insulating perovskites using pulsed laser deposition. The local electron energy loss spectroscopy (EELS) capability of a scanning transmission electron microscope (STEM) is used to probe the electronic configuration in the LaMnO3 films as a function of the distance from the interfaces. The results are compared to macroscopic measurements and theoretical predictions. Research sponsored by the U.S. Department of Energy under contract DE-AC05-00OR22725 with the Oak Ridge National Laboratory, managed by UT-Battelle, LLC.

Depth and Motion Prediction for Earth Penetrators

DTIC Science & Technology

1978-06-01

multiple-layer targets. For targets with accurately knowni properties , the final-depth results are accurate ihný pret AM all13 EIIW FINVS S WLT n.- U lass S...Project hAl611o2AT2?, Task A2, Work Unit󈧊, " Effectiveness of Earth Penetrators in Various Geologic Environments." Mr. R. S. Bernard conducted the... effects in the selective destruction of localized targets (airfields, factories, utilities, etc.). The effectiveness of these weapons, however, is

A Study on Flexural Properties of Sandwich Structures with Fiber/Metal Laminate Face Sheets

NASA Astrophysics Data System (ADS)

Dariushi, S.; Sadighi, M.

2013-10-01

In this work, a new family of sandwich structures with fiber metal laminate (FML) faces is investigated. FMLs have benefits over both metal and fiber reinforced composites. To investigate the bending properties of sandwich beams with FML faces and compare with similar sandwich beams with fibrous composite faces, 6 groups of specimen with different layer arrangements were made and tested. Results show that FML faces have good resistance against transverse local loads and minimize stress concentration and local deformations of skin and core under the loading tip. In addition, FML faces have a good integrity even after plateau region of foam cores and prevent from catastrophic failures, which cannot be seen in fibrous composite faces. Also, FML faces are lighter than metal faces and have better connection with foam cores. Sandwich beams with FML faces have a larger elastic region because of simultaneous deformation of top and bottom faces and larger failure strain thanks to good durability of FMLs. A geometrical nonlinear classical theory is used to predict force-deflection behavior. In this model an explicit formula between symmetrical sandwich beams deflections and applied force which can be useful for designers, is derived. Good agreement is obtained between the analytical predictions and experimental results. Also, analytical results are compared with small deformation solution in a parametric study, and the effects of geometric parameters on difference between linear and nonlinear results are discussed.

Evaluation of structure-reactivity descriptors and biological activity spectra of 4-(6-methoxy-2-naphthyl)-2-butanone using spectroscopic techniques

NASA Astrophysics Data System (ADS)

Agrawal, Megha; Deval, Vipin; Gupta, Archana; Sangala, Bagvanth Reddy; Prabhu, S. S.

2016-10-01

The structure and several spectroscopic features along with reactivity parameters of the compound 4-(6-methoxy-2-naphthyl)-2-butanone (Nabumetone) have been studied using experimental techniques and tools derived from quantum chemical calculations. Structure optimization is followed by force field calculations based on density functional theory (DFT) at the B3LYP/6-311++G(d,p) level of theory. The vibrational spectra have been interpreted with the aid of normal coordinate analysis. UV-visible spectrum and the effect of solvent have been discussed. The electronic properties such as HOMO and LUMO energies have been determined by TD-DFT approach. In order to understand various aspects of pharmacological sciences several new chemical reactivity descriptors - chemical potential, global hardness and electrophilicity have been evaluated. Local reactivity descriptors - Fukui functions and local softnesses have also been calculated to find out the reactive sites within molecule. Aqueous solubility and lipophilicity have been calculated which are crucial for estimating transport properties of organic molecules in drug development. Estimation of biological effects, toxic/side effects has been made on the basis of prediction of activity spectra for substances (PASS) prediction results and their analysis by Pharma Expert software. Using the THz-TDS technique, the frequency-dependent absorptions of NBM have been measured in the frequency range up to 3 THz.

ULF waves at comets Halley and Giacobini-Zinner - Comparison with simulations

NASA Astrophysics Data System (ADS)

Le, G.; Russell, C. T.; Gary, S. P.; Smith, E. J.; Riedler, W.; Schwingenschuh, K.

1989-09-01

A comparison is made between observations and numerical simulations of magnetic fluctuations near the proton and water group ion cyclotron frequencies as a function of distance from the comets Halley and Giacobini-Zinner. The amplitude of waves due to different cyclotron resonant instabilities is monitored by examining the amplitude of waves near the gyrofrequency of the respective ions, measured in by the ICE spacecraft. The results are compared with a one-dimensional electromagnetic hybrid simulation of two-ion pickup based on the predictions of Gary et al. (1989). The observations are consistent with the prediction that amplitudes are dependent on the properties of the injected beams and the local injection rate.

Energy landscapes for machine learning

NASA Astrophysics Data System (ADS)

Ballard, Andrew J.; Das, Ritankar; Martiniani, Stefano; Mehta, Dhagash; Sagun, Levent; Stevenson, Jacob D.; Wales, David J.

Machine learning techniques are being increasingly used as flexible non-linear fitting and prediction tools in the physical sciences. Fitting functions that exhibit multiple solutions as local minima can be analysed in terms of the corresponding machine learning landscape. Methods to explore and visualise molecular potential energy landscapes can be applied to these machine learning landscapes to gain new insight into the solution space involved in training and the nature of the corresponding predictions. In particular, we can define quantities analogous to molecular structure, thermodynamics, and kinetics, and relate these emergent properties to the structure of the underlying landscape. This Perspective aims to describe these analogies with examples from recent applications, and suggest avenues for new interdisciplinary research.

Mitochondrial transit peptide exhibits cell penetration ability and efficiently delivers macromolecules to mitochondria.

PubMed

Jain, Aastha; Chugh, Archana

2016-09-01

Mitochondrial malfunction under various circumstances can lead to a variety of disorders. Effective targeting of macromolecules (drugs) is important for restoration of mitochondrial function and treatment of related disorders. We have designed a novel cell-penetrating mitochondrial transit peptide (CpMTP) for delivery of macromolecules to mitochondria. Comparison between properties of cell-penetrating peptides (CPPs) and mitochondrial signal sequences enabled prediction of peptides with dual ability for cellular translocation and mitochondrial localization. Among the predicted peptides, CpMTP translocates across HeLa cells and shows successful delivery of noncovalently conjugated cargo molecules to mitochondria. CpMTP may have applications in transduction and transfection of mitochondria for therapeutics. © 2016 Federation of European Biochemical Societies.

Introducing anisotropic Minkowski functionals and quantitative anisotropy measures for local structure analysis in biomedical imaging

NASA Astrophysics Data System (ADS)

Wismüller, Axel; De, Titas; Lochmüller, Eva; Eckstein, Felix; Nagarajan, Mahesh B.

2013-03-01

The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level structures. To quantify the anisotropy characterized by our approach, we further introduce a method to compute a quantitative measure motivated by a technique utilized in MR diffusion tensor imaging, namely fractional anisotropy. We showcase the applicability of our method in the research context of characterizing the local structure properties of trabecular bone micro-architecture in the proximal femur as visualized on multi-detector CT. To this end, AMFs were computed locally for each pixel of ROIs extracted from the head, neck and trochanter regions. Fractional anisotropy was then used to quantify the local anisotropy of the trabecular structures found in these ROIs and to compare its distribution in different anatomical regions. Our results suggest a significantly greater concentration of anisotropic trabecular structures in the head and neck regions when compared to the trochanter region (p < 10-4). We also evaluated the ability of such AMFs to predict bone strength in the femoral head of proximal femur specimens obtained from 50 donors. Our results suggest that such AMFs, when used in conjunction with multi-regression models, can outperform more conventional features such as BMD in predicting failure load. We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding directional attributes of local structure, which may be useful in a wide scope of biomedical imaging applications.

Introducing Anisotropic Minkowski Functionals and Quantitative Anisotropy Measures for Local Structure Analysis in Biomedical Imaging

PubMed Central

Wismüller, Axel; De, Titas; Lochmüller, Eva; Eckstein, Felix; Nagarajan, Mahesh B.

2017-01-01

The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level structures. To quantify the anisotropy characterized by our approach, we further introduce a method to compute a quantitative measure motivated by a technique utilized in MR diffusion tensor imaging, namely fractional anisotropy. We showcase the applicability of our method in the research context of characterizing the local structure properties of trabecular bone micro-architecture in the proximal femur as visualized on multi-detector CT. To this end, AMFs were computed locally for each pixel of ROIs extracted from the head, neck and trochanter regions. Fractional anisotropy was then used to quantify the local anisotropy of the trabecular structures found in these ROIs and to compare its distribution in different anatomical regions. Our results suggest a significantly greater concentration of anisotropic trabecular structures in the head and neck regions when compared to the trochanter region (p < 10−4). We also evaluated the ability of such AMFs to predict bone strength in the femoral head of proximal femur specimens obtained from 50 donors. Our results suggest that such AMFs, when used in conjunction with multi-regression models, can outperform more conventional features such as BMD in predicting failure load. We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding directional attributes of local structure, which may be useful in a wide scope of biomedical imaging applications. PMID:29170580

Investigation of spray characteristics for flashing injection of fuels containing dissolved air and superheated fuels

NASA Technical Reports Server (NTRS)

Solomon, A. S. P.; Chen, L. D.; Faeth, G. M.

1982-01-01

The flow, atomization and spreading of flashing injector flowing liquids containing dissolved gases (jet/air) as well as superheated liquids (Freon II) were considered. The use of a two stage expansion process separated by an expansion chamber, ws found to be beneficial for flashing injection particularly for dissolved gas systems. Both locally homogeneous and separated flow models provided good predictions of injector flow properties. Conventional correlations for drop sizes from pressure atomized and airblast injectors were successfully modified, using the separated flow model to prescribe injector exit conditions, to correlate drop size measurements. Additional experimental results are provided for spray angle and combustion properties of sprays from flashing injectors.

First-principles studies on infrared properties of semiconducting graphene monoxide

NASA Astrophysics Data System (ADS)

Pu, H. H.; Mattson, E. C.; Rhim, S. H.; Gajdardziksa-Josifovska, M.; Hirschmugl, C. J.; Weinert, M.; Chen, J. H.

2013-10-01

Graphene monoxide (GMO), a recently proposed 2D crystalline material in the graphene family, is attractive for next-generation nanoelectronics because of its predicted tunable band gap. As a guide to GMO experimental characterization, we calculate the vibrational properties and obtain three infrared active vibration modes (B1u, B2u, and B3u) and six Raman active modes (B1g, B2g, 2B3g, and 2Ag) for intrinsic GMO. The frequencies of the infrared active modes depend on both local structural deformations and interactions between adjacent GMO layers. These results are consistent with experimental observations and provide a means of estimating the number of layers in intrinsic GMO.

The Impact of Soil Moisture Initialization On Seasonal Precipitation Forecasts

NASA Technical Reports Server (NTRS)

Koster, R. D.; Suarez, M. J.; Tyahla, L.; Houser, Paul (Technical Monitor)

2002-01-01

Some studies suggest that the proper initialization of soil moisture in a forecasting model may contribute significantly to the accurate prediction of seasonal precipitation, especially over mid-latitude continents. In order for the initialization to have any impact at all, however, two conditions must be satisfied: (1) the initial soil moisture anomaly must be "remembered" into the forecasted season, and (2) the atmosphere must respond in a predictable way to the soil moisture anomaly. In our previous studies, we identified the key land surface and atmospheric properties needed to satisfy each condition. Here, we tie these studies together with an analysis of an ensemble of seasonal forecasts. Initial soil moisture conditions for the forecasts are established by forcing the land surface model with realistic precipitation prior to the start of the forecast period. As expected, the impacts on forecasted precipitation (relative to an ensemble of runs that do not utilize soil moisture information) tend to be localized over the small fraction of the earth with all of the required land and atmosphere properties.

Evaluation of the Linear and Second-Order NLO Properties of Molecular Crystals within the Local Field Theory: Electron Correlation Effects, Choice of XC Functional, ZPVA Contributions, and Impact of the Geometry in the Case of 2-Methyl-4-nitroaniline.

PubMed

Seidler, Tomasz; Stadnicka, Katarzyna; Champagne, Benoît

2014-05-13

The linear [χ((1))] and second-order nonlinear [χ((2))] optical susceptibilities of the 2-methyl-4-nitroaniline (MNA) crystal are calculated within the local field theory, which consists of first computing the molecular properties, accounting for the dressing effects of the surroundings, and then taking into account the local field effects. Several aspects of these calculations are tackled with the aim of monitoring the convergence of the χ((1)) and χ((2)) predictions with respect to experiment by accounting for the effects of (i) the dressing field within successive approximations, of (ii) the first-order ZPVA corrections, and of (iii) the geometry. With respect to the reference CCSD-based results, besides double hybrid functionals, the most reliable exchange-correlation functionals are LC-BLYP for the static χ((1)) and CAM-B3LYP (and M05-2X, to a lesser extent) for the dynamic χ((1)) but they strongly underestimate χ((2)). Double hybrids perform better for χ((2)) but not necessarily for χ((1)), and, moreover, their performances are much similar to MP2, which is known to slightly overestimate β, with respect to high-level coupled-clusters calculations and, therefore, χ((2)). Other XC functionals with less HF exchange perform poorly with overestimations/underestimations of χ((1))/χ((2)), whereas the HF method leads to underestimations of both. The first-order ZPVA corrections, estimated at the B3LYP level, are usually small but not negligible. Indeed, after ZPVA corrections, the molecular polarizabilities and first hyperpolarizabilities increase by 2% and 5%, respectively, whereas their impact is magnified on the macroscopic responses with enhancements of χ((1)) by up to 5% and of χ((2)) by as much as 10%-12% at λ = 1064 nm. The geometry plays also a key role in view of predicting accurate susceptibilities, particularly for push-pull π-conjugated compounds such as MNA. So, the geometry optimized using periodic boundary conditions is characterized by an overestimated bond length alternation, which gives larger molecular properties and even larger macroscopic responses, because of the local field factor amplification effects. Our best estimates based on experimental geometries, charge dressing field, ZPVA correction, and CCSD molecular properties lead to an overestimation of χ((1)) by 12% in the static limit and 7% at λ = 1064 nm. For χ((2)), the difference, with respect to the experiment, is satisfactory and of the order of one standard deviation.

Detecting Local Ligand-Binding Site Similarity in Non-Homologous Proteins by Surface Patch Comparison

PubMed Central

Sael, Lee; Kihara, Daisuke

2012-01-01

Functional elucidation of proteins is one of the essential tasks in biology. Function of a protein, specifically, small ligand molecules that bind to a protein, can be predicted by finding similar local surface regions in binding sites of known proteins. Here, we developed an alignment free local surface comparison method for predicting a ligand molecule which binds to a query protein. The algorithm, named Patch-Surfer, represents a binding pocket as a combination of segmented surface patches, each of which is characterized by its geometrical shape, the electrostatic potential, the hydrophobicity, and the concaveness. Representing a pocket by a set of patches is effective to absorb difference of global pocket shape while capturing local similarity of pockets. The shape and the physicochemical properties of surface patches are represented using the 3D Zernike descriptor, which is a series expansion of mathematical 3D function. Two pockets are compared using a modified weighted bipartite matching algorithm, which matches similar patches from the two pockets. Patch-Surfer was benchmarked on three datasets, which consist in total of 390 proteins that bind to one of 21 ligands. Patch-Surfer showed superior performance to existing methods including a global pocket comparison method, Pocket-Surfer, which we have previously introduced. Particularly, as intended, the accuracy showed large improvement for flexible ligand molecules, which bind to pockets in different conformations. PMID:22275074

Detecting local ligand-binding site similarity in nonhomologous proteins by surface patch comparison.

PubMed

Sael, Lee; Kihara, Daisuke

2012-04-01

Functional elucidation of proteins is one of the essential tasks in biology. Function of a protein, specifically, small ligand molecules that bind to a protein, can be predicted by finding similar local surface regions in binding sites of known proteins. Here, we developed an alignment free local surface comparison method for predicting a ligand molecule which binds to a query protein. The algorithm, named Patch-Surfer, represents a binding pocket as a combination of segmented surface patches, each of which is characterized by its geometrical shape, the electrostatic potential, the hydrophobicity, and the concaveness. Representing a pocket by a set of patches is effective to absorb difference of global pocket shape while capturing local similarity of pockets. The shape and the physicochemical properties of surface patches are represented using the 3D Zernike descriptor, which is a series expansion of mathematical 3D function. Two pockets are compared using a modified weighted bipartite matching algorithm, which matches similar patches from the two pockets. Patch-Surfer was benchmarked on three datasets, which consist in total of 390 proteins that bind to one of 21 ligands. Patch-Surfer showed superior performance to existing methods including a global pocket comparison method, Pocket-Surfer, which we have previously introduced. Particularly, as intended, the accuracy showed large improvement for flexible ligand molecules, which bind to pockets in different conformations. Copyright © 2011 Wiley Periodicals, Inc.

Correlation of transarterial transport of various dextrans with their physicochemical properties.

PubMed

Elmalak, O; Lovich, M A; Edelman, E

2000-11-01

Local vascular drug delivery provides elevated concentrations of drug in the target tissue while minimizing systemic side effects. To better characterize local pharmacokinetics we examined the arterial transport of locally applied dextran and dextran derivatives in vivo. Using a two-compartment pharmacokinetic model to correct the measured transmural flux of these compounds for systemic redistribution and elimination as delivered from a photopolymerizable hydrogel surrounding rat carotid arteries, we found that the diffusivities and the transendothelial permeabilities were strongly dependent on molecular weight and charge. For neutral dextrans, the effective diffusive resistance in the media increased with molecular weight approximately 4.1-fold between the molecular weights of 10 and 282 kDa. Similarly, endothelial resistance increased 28-fold over the same molecular weight range. The effective medial diffusive resistance was unaffected by cationic charge as such molecules moved identically to neutral compounds, but increased approximately 40% when dextrans were negatively charged. Transendothelial resistance was 20-fold lower for the cationic dextrans, and 11-fold higher for the anionic dextrans, when both were compared to neutral counterparts. These results suggest that, while low molecular weight drugs will rapidly traverse the arterial wall with the endothelium posing a minimal barrier, the reverse is true for high molecular weight agents. With these data, the deposition and distribution of locally released vasotherapeutic compounds might be predicted based upon chemical properties, such as molecular weight and charge.

Underlying Mechanisms of Cooperativity, Input Specificity, and Associativity of Long-Term Potentiation Through a Positive Feedback of Local Protein Synthesis.

PubMed

Hao, Lijie; Yang, Zhuoqin; Lei, Jinzhi

2018-01-01

Long-term potentiation (LTP) is a specific form of activity-dependent synaptic plasticity that is a leading mechanism of learning and memory in mammals. The properties of cooperativity, input specificity, and associativity are essential for LTP; however, the underlying mechanisms are unclear. Here, based on experimentally observed phenomena, we introduce a computational model of synaptic plasticity in a pyramidal cell to explore the mechanisms responsible for the cooperativity, input specificity, and associativity of LTP. The model is based on molecular processes involved in synaptic plasticity and integrates gene expression involved in the regulation of neuronal activity. In the model, we introduce a local positive feedback loop of protein synthesis at each synapse, which is essential for bimodal response and synapse specificity. Bifurcation analysis of the local positive feedback loop of brain-derived neurotrophic factor (BDNF) signaling illustrates the existence of bistability, which is the basis of LTP induction. The local bifurcation diagram provides guidance for the realization of LTP, and the projection of whole system trajectories onto the two-parameter bifurcation diagram confirms the predictions obtained from bifurcation analysis. Moreover, model analysis shows that pre- and postsynaptic components are required to achieve the three properties of LTP. This study provides insights into the mechanisms underlying the cooperativity, input specificity, and associativity of LTP, and the further construction of neural networks for learning and memory.

Transport, Structural and Mechanical Properties of Quaternary FeVTiAl Alloy

NASA Astrophysics Data System (ADS)

Bhat, Tahir Mohiuddin; Gupta, Dinesh C.

2016-11-01

The electronic, structural, magnetic and transport properties of FeVTiAl quaternary alloy have been investigated within the framework of density functional theory. The material is a completely spin-polarized half-metallic ferromagnet in its ground state with F-43m structure. The structural stability was further confirmed by elastic constants in the cubic phase with high Young's modulus and brittle nature. The present study predicts an energy band gap of 0.72 eV in a localized minority spin channel at equilibrium lattice parameter of 6.00 Å. The transport properties of the material are discussed based on the Seebeck coefficient, and electrical and thermal conductivity coefficients. The alloy presents large values of Seebeck coefficients, ~39 μV K-1 at room temperature (300 K), and has an excellent thermoelectric performance with ZT = ~0.8.

Strain hardening behavior during manufacturing of tube shapes by hydroforming

NASA Astrophysics Data System (ADS)

Park, Hyun Kyu; Yi, Hyae Kyung; Van Tyne, Chester J.; Moon, Young Hoon

2009-12-01

Safe and robust process design relies on knowledge of the evolution of the mechanical properties in a tube during hydroforming. The manufacturing of tubular shapes generally consists of three main stages: bending, preforming, and expansion. The latter is usually called hydroforming. As a result of these three steps, the final product's strain hardening history is nonlinear. In the present study, the strain hardening behavior during hydroforming was experimentally investigated. The variation of local flow stress and/or local hardness was used as an index of the strain hardening during the various steps and the local flow stress and/or local hardness were used with respective correlations to determine the effective strain. The strain hardening behavior during hydroforming after preforming has been successfully analyzed by using the relationships between hardness, flow stress, and effective strain for variable pre-strains prior to hydroforming. The comparison of predicted hardness with measured hardness confirms that the methodology used in this study is feasible, and that the strain hardening behavior can be quantitatively estimated with good accuracy.

Singlet oxygen explicit dosimetry to predict long-term local tumor control for BPD-mediated photodynamic therapy

NASA Astrophysics Data System (ADS)

Kim, Michele M.; Penjweini, Rozhin; Ong, Yi Hong; Zhu, Timothy C.

2017-02-01

Photodynamic therapy (PDT) is a well-established treatment modality for cancer and other malignant diseases; however, quantities such as light fluence, photosensitizer photobleaching rate, and PDT dose do not fully account for all of the dynamic interactions between the key components involved. In particular, fluence rate (Φ) effects are not accounted for, which has a large effect on the oxygen consumption rate. In this preclinical study, reacted singlet oxygen [1O2]rx was investigated as a dosimetric quantity for PDT outcome. The ability of [1O2]rx to predict the long-term local tumor control rate (LCR) for BPD-mediated PDT was examined. Mice bearing radioactivelyinduced fibrosarcoma (RIF) tumors were treated with different in-air fluences (250, 300, and 350 J/cm2) and in-air ϕ (75, 100, and150 mW/cm2) with a BPD dose of 1 mg/kg and a drug-light interval of 3 hours. Treatment was delivered with a collimated laser beam of 1 cm diameter at 690 nm. Explicit dosimetry of initial tissue oxygen concentration, tissue optical properties, and BPD concentration was used to calculate [1O2]rx. Φ was calculated for the treatment volume based on Monte-Carlo simulations and measured tissue optical properties. Kaplan-Meier analyses for LCR were done for an endpoint of tumor volume <= 100 mm3 using four dose metrics: light fluence, photosensitizer photobleaching rate, PDT dose, and [1O2]rx. PDT dose was defined as the product of the timeintegral of photosensitizer concentration and Φ at a 3 mm tumor depth. Preliminary studies show that [1O2]rx better correlates with LCR and is an effective dosimetric quantity that can predict treatment outcome.

Singlet oxygen explicit dosimetry to predict long-term local tumor control for Photofrin-mediated photodynamic therapy

NASA Astrophysics Data System (ADS)

Penjweini, Rozhin; Kim, Michele M.; Ong, Yi Hong; Zhu, Timothy C.

2017-02-01

Although photodynamic therapy (PDT) is an established modality for the treatment of cancer, current dosimetric quantities do not account for the variations in PDT oxygen consumption for different fluence rates (φ). In this study we examine the efficacy of reacted singlet oxygen concentration ([1O2]rx) to predict long-term local control rate (LCR) for Photofrin-mediated PDT. Radiation-induced fibrosarcoma (RIF) tumors in the right shoulders of female C3H mice are treated with different in-air fluences of 225-540 J/cm2 and in-air fluence rate (φair) of 50 and 75 mW/cm2 at 5 mg/kg Photofrin and a drug-light interval of 24 hours using a 1 cm diameter collimated laser beam at 630 nm wavelength. [1O2]rx is calculated by using a macroscopic model based on explicit dosimetry of Photofrin concentration, tissue optical properties, tissue oxygenation and blood flow changes during PDT. The tumor volume of each mouse is tracked for 90 days after PDT and Kaplan-Meier analyses for LCR are performed based on a tumor volume <=100 mm3, for the four dose metrics light fluence, photosensitizer photobleaching rate, PDT dose and [1O2]rx. PDT dose is defined as a temporal integral of photosensitizer concentration and Φ at a 3 mm tumor depth. φ is calculated throughout the treatment volume based on Monte-Carlo simulation and measured tissue optical properties. Our preliminary studies show that [1O2]rx is the best dosimetric quantity that can predict tumor response and correlate with LCR. Moreover, [1O2]rx calculated using the blood flow changes was in agreement with [1O2]rx calculated based on the actual tissue oxygenation.

A Numerical Process Control Method for Circular-Tube Hydroforming Prediction

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

Johnson, Kenneth I.; Nguyen, Ba Nghiep; Davies, Richard W.

2004-03-01

This paper describes the development of a solution control method that tracks the stresses, strains and mechanical behavior of a tube during hydroforming to estimate the proper axial feed (end-feed) and internal pressure loads through time. The analysis uses the deformation theory of plasticity and Hill?s criterion to describe the plastic flow. Before yielding, the pressure and end-feed increments are estimated based on the initial tube geometry, elastic properties and yield stress. After yielding, the pressure increment is calculated based on the tube geometry at the previous solution increment and the current hoop stress increment. The end-feed increment is computedmore » from the increment of the axial plastic strain. Limiting conditions such as column buckling (of long tubes), local axi-symmetric wrinkling of shorter tubes, and bursting due to localized wall thinning are considered. The process control method has been implemented in the Marc finite element code. Hydroforming simulations using this process control method were conducted to predict the load histories for controlled expansion of 6061-T4 aluminum tubes within a conical die shape and under free hydroforming conditions. The predicted loading paths were transferred to the hydroforming equipment to form the conical and free-formed tube shapes. The model predictions and experimental results are compared for deformed shape, strains and the extent of forming at rupture.« less

Transport lattice models of heat transport in skin with spatially heterogeneous, temperature-dependent perfusion.

PubMed

Gowrishankar, T R; Stewart, Donald A; Martin, Gregory T; Weaver, James C

2004-11-17

Investigation of bioheat transfer problems requires the evaluation of temporal and spatial distributions of temperature. This class of problems has been traditionally addressed using the Pennes bioheat equation. Transport of heat by conduction, and by temperature-dependent, spatially heterogeneous blood perfusion is modeled here using a transport lattice approach. We represent heat transport processes by using a lattice that represents the Pennes bioheat equation in perfused tissues, and diffusion in nonperfused regions. The three layer skin model has a nonperfused viable epidermis, and deeper regions of dermis and subcutaneous tissue with perfusion that is constant or temperature-dependent. Two cases are considered: (1) surface contact heating and (2) spatially distributed heating. The model is relevant to the prediction of the transient and steady state temperature rise for different methods of power deposition within the skin. Accumulated thermal damage is estimated by using an Arrhenius type rate equation at locations where viable tissue temperature exceeds 42 degrees C. Prediction of spatial temperature distributions is also illustrated with a two-dimensional model of skin created from a histological image. The transport lattice approach was validated by comparison with an analytical solution for a slab with homogeneous thermal properties and spatially distributed uniform sink held at constant temperatures at the ends. For typical transcutaneous blood gas sensing conditions the estimated damage is small, even with prolonged skin contact to a 45 degrees C surface. Spatial heterogeneity in skin thermal properties leads to a non-uniform temperature distribution during a 10 GHz electromagnetic field exposure. A realistic two-dimensional model of the skin shows that tissue heterogeneity does not lead to a significant local temperature increase when heated by a hot wire tip. The heat transport system model of the skin was solved by exploiting the mathematical analogy between local thermal models and local electrical (charge transport) models, thereby allowing robust, circuit simulation software to obtain solutions to Kirchhoff's laws for the system model. Transport lattices allow systematic introduction of realistic geometry and spatially heterogeneous heat transport mechanisms. Local representations for both simple, passive functions and more complex local models can be easily and intuitively included into the system model of a tissue.

Ion Bernstein instability as a possible source for oxygen ion cyclotron harmonic waves

NASA Astrophysics Data System (ADS)

Min, Kyungguk; Denton, Richard E.; Liu, Kaijun; Gary, S. Peter; Spence, Harlan E.

2017-05-01

This paper demonstrates that an ion Bernstein instability can be a possible source for recently reported electromagnetic waves with frequencies at or near the singly ionized oxygen ion cyclotron frequency, ΩO+, and its harmonics. The particle measurements during strong wave activity revealed a relatively high concentration of oxygen ions (˜15%) whose phase space density exhibits a local peak at energy ˜20 keV. Given that the electron plasma-to-cyclotron frequency ratio is ωpe/Ωe≳1, this energy corresponds to the particle speed v/vA≳0.3, where vA is the oxygen Alfvén speed. Using the observational key plasma parameters, a simplified ion velocity distribution is constructed, where the local peak in the oxygen ion velocity distribution is represented by an isotropic shell distribution. Kinetic linear dispersion theory then predicts unstable Bernstein modes at or near the harmonics of ΩO+ and at propagation quasi-perpendicular to the background magnetic field, B0. If the cold ions are mostly protons, these unstable modes are characterized by a low compressibility (|δB∥|2/|δB|2≲0.01), a small phase speed (vph˜0.2vA), a relatively small ratio of the electric field energy to the magnetic field energy (between 10-4 and 10-3), and the Poynting vector directed almost parallel to B0. These linear properties are overall in good agreement with the properties of the observed waves. We demonstrate that superposition of the predicted unstable Bernstein modes at quasi-perpendicular propagation can produce the observed polarization properties, including the minimum variance direction on average almost parallel to B0.

Prediction of protein secondary structure content for the twilight zone sequences.

PubMed

Homaeian, Leila; Kurgan, Lukasz A; Ruan, Jishou; Cios, Krzysztof J; Chen, Ke

2007-11-15

Secondary protein structure carries information about local structural arrangements, which include three major conformations: alpha-helices, beta-strands, and coils. Significant majority of successful methods for prediction of the secondary structure is based on multiple sequence alignment. However, multiple alignment fails to provide accurate results when a sequence comes from the twilight zone, that is, it is characterized by low (<30%) homology. To this end, we propose a novel method for prediction of secondary structure content through comprehensive sequence representation, called PSSC-core. The method uses a multiple linear regression model and introduces a comprehensive feature-based sequence representation to predict amount of helices and strands for sequences from the twilight zone. The PSSC-core method was tested and compared with two other state-of-the-art prediction methods on a set of 2187 twilight zone sequences. The results indicate that our method provides better predictions for both helix and strand content. The PSSC-core is shown to provide statistically significantly better results when compared with the competing methods, reducing the prediction error by 5-7% for helix and 7-9% for strand content predictions. The proposed feature-based sequence representation uses a comprehensive set of physicochemical properties that are custom-designed for each of the helix and strand content predictions. It includes composition and composition moment vectors, frequency of tetra-peptides associated with helical and strand conformations, various property-based groups like exchange groups, chemical groups of the side chains and hydrophobic group, auto-correlations based on hydrophobicity, side-chain masses, hydropathy, and conformational patterns for beta-sheets. The PSSC-core method provides an alternative for predicting the secondary structure content that can be used to validate and constrain results of other structure prediction methods. At the same time, it also provides useful insight into design of successful protein sequence representations that can be used in developing new methods related to prediction of different aspects of the secondary protein structure. (c) 2007 Wiley-Liss, Inc.

Statistics of natural binaural sounds.

PubMed

Młynarski, Wiktor; Jost, Jürgen

2014-01-01

Binaural sound localization is usually considered a discrimination task, where interaural phase (IPD) and level (ILD) disparities at narrowly tuned frequency channels are utilized to identify a position of a sound source. In natural conditions however, binaural circuits are exposed to a stimulation by sound waves originating from multiple, often moving and overlapping sources. Therefore statistics of binaural cues depend on acoustic properties and the spatial configuration of the environment. Distribution of cues encountered naturally and their dependence on physical properties of an auditory scene have not been studied before. In the present work we analyzed statistics of naturally encountered binaural sounds. We performed binaural recordings of three auditory scenes with varying spatial configuration and analyzed empirical cue distributions from each scene. We have found that certain properties such as the spread of IPD distributions as well as an overall shape of ILD distributions do not vary strongly between different auditory scenes. Moreover, we found that ILD distributions vary much weaker across frequency channels and IPDs often attain much higher values, than can be predicted from head filtering properties. In order to understand the complexity of the binaural hearing task in the natural environment, sound waveforms were analyzed by performing Independent Component Analysis (ICA). Properties of learned basis functions indicate that in natural conditions soundwaves in each ear are predominantly generated by independent sources. This implies that the real-world sound localization must rely on mechanisms more complex than a mere cue extraction.

Statistics of Natural Binaural Sounds

PubMed Central

Młynarski, Wiktor; Jost, Jürgen

2014-01-01

Binaural sound localization is usually considered a discrimination task, where interaural phase (IPD) and level (ILD) disparities at narrowly tuned frequency channels are utilized to identify a position of a sound source. In natural conditions however, binaural circuits are exposed to a stimulation by sound waves originating from multiple, often moving and overlapping sources. Therefore statistics of binaural cues depend on acoustic properties and the spatial configuration of the environment. Distribution of cues encountered naturally and their dependence on physical properties of an auditory scene have not been studied before. In the present work we analyzed statistics of naturally encountered binaural sounds. We performed binaural recordings of three auditory scenes with varying spatial configuration and analyzed empirical cue distributions from each scene. We have found that certain properties such as the spread of IPD distributions as well as an overall shape of ILD distributions do not vary strongly between different auditory scenes. Moreover, we found that ILD distributions vary much weaker across frequency channels and IPDs often attain much higher values, than can be predicted from head filtering properties. In order to understand the complexity of the binaural hearing task in the natural environment, sound waveforms were analyzed by performing Independent Component Analysis (ICA). Properties of learned basis functions indicate that in natural conditions soundwaves in each ear are predominantly generated by independent sources. This implies that the real-world sound localization must rely on mechanisms more complex than a mere cue extraction. PMID:25285658

Investigation of the electronic, magnetic and optical properties of {\\sf Co}_{\\sf 2}{\\sf CrZ} (Z = Si, Ge) under pressure—a density functional theory study

NASA Astrophysics Data System (ADS)

Seema, K.; Kumar, Ranjan

2014-01-01

The structural, electronic, magnetic and optical properties of Co-based Heusler compounds, Co2CrZ (Z = Si, Ge), are studied using first-principle density functional theory. The calculations are performed within the generalized gradient approximation. Our calculated structural parameters at 0 GPa agree well with previous available results. The calculated magnetic moment agrees well with the Slater-Pauling (SP) rule. We have studied the effect of pressure on the electronic and magnetic properties of Co2CrSi and Co2CrGe. With an increase in applied pressure, a decrease in cell volume is observed. Under application of external pressure, the valence band and conduction band are shifted downward which leads to a modification of electronic structure. There exists an indirect band gap along Γ-X for both the alloys. Co2CrSi and Co2CrGe retain 100% spin polarization up to 60 and 50 GPa, respectively. The local magnetic moments of the Co and Si (Ge) atoms increase with an increase in pressure whereas the local magnetic moment of the Cr atom decreases. In addition, the optical properties such as dielectric function, absorption spectra, optical conductivity and energy loss function of these alloys have also been investigated. To our knowledge this is the first theoretical prediction of the pressure dependence of the structural, electronic, magnetic and optical properties of Co2CrSi and Co2CrGe.

Novel 3D bio-macromolecular bilinear descriptors for protein science: Predicting protein structural classes.

PubMed

Marrero-Ponce, Yovani; Contreras-Torres, Ernesto; García-Jacas, César R; Barigye, Stephen J; Cubillán, Néstor; Alvarado, Ysaías J

2015-06-07

In the present study, we introduce novel 3D protein descriptors based on the bilinear algebraic form in the ℝ(n) space on the coulombic matrix. For the calculation of these descriptors, macromolecular vectors belonging to ℝ(n) space, whose components represent certain amino acid side-chain properties, were used as weighting schemes. Generalization approaches for the calculation of inter-amino acidic residue spatial distances based on Minkowski metrics are proposed. The simple- and double-stochastic schemes were defined as approaches to normalize the coulombic matrix. The local-fragment indices for both amino acid-types and amino acid-groups are presented in order to permit characterizing fragments of interest in proteins. On the other hand, with the objective of taking into account specific interactions among amino acids in global or local indices, geometric and topological cut-offs are defined. To assess the utility of global and local indices a classification model for the prediction of the major four protein structural classes, was built with the Linear Discriminant Analysis (LDA) technique. The developed LDA-model correctly classifies the 92.6% and 92.7% of the proteins on the training and test sets, respectively. The obtained model showed high values of the generalized square correlation coefficient (GC(2)) on both the training and test series. The statistical parameters derived from the internal and external validation procedures demonstrate the robustness, stability and the high predictive power of the proposed model. The performance of the LDA-model demonstrates the capability of the proposed indices not only to codify relevant biochemical information related to the structural classes of proteins, but also to yield suitable interpretability. It is anticipated that the current method will benefit the prediction of other protein attributes or functions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Nano-Enabled Approaches to Chemical Imaging in Biosystems

DOE PAGES

Retterer, Scott T.; Morrell-Falvey, Jennifer L.; Doktycz, Mitchel John

2018-02-28

Understanding and predicting how biosystems function require knowledge about the dynamic physicochemical environments with which they interact and alter by their presence. Yet, identifying specific components, tracking the dynamics of the system, and monitoring local environmental conditions without disrupting biosystem function present significant challenges for analytical measurements. Nanomaterials, by their very size and nature, can act as probes and interfaces to biosystems and offer solutions to some of these challenges. At the nanoscale, material properties emerge that can be exploited for localizing biomolecules and making chemical measurements at cellular and subcellular scales. Here, we review advances in chemical imaging enabledmore » by nanoscale structures, in the use of nanoparticles as chemical and environmental probes, and in the development of micro- and nanoscale fluidic devices to define and manipulate local environments and facilitate chemical measurements of complex biosystems. As a result, integration of these nano-enabled methods will lead to an unprecedented understanding of biosystem function.« less

On Hokusai's Great wave off Kanagawa: localization, linearity and a rogue wave in sub-Antarctic waters.

PubMed

Dudley, J M; Sarano, V; Dias, F

2013-06-20

The Hokusai woodcut entitled The great wave off Kanagawa has been interpreted as an unusually large storm wave, likely to be classed as a rogue wave, and possibly generated from nonlinear wave dynamics (J. H. E. Cartwright and H. Nakamura, Notes Rec. R. Soc. 63 , 119-135 (2009)). In this paper, we present a complementary discussion of this hypothesis, discussing in particular how linear and nonlinear mechanisms can both contribute to the emergence of rogue wave events. By making reference to the Great wave 's simultaneous transverse and longitudinal localization, we show that the purely linear mechanism of directional focusing also predicts characteristics consistent with those of the Great wave . In addition, we discuss the properties of a particular rogue wave photographed on the open ocean in sub-Antarctic waters, which shows two-dimensional localization and breaking dynamics remarkably similar to Hokusai's depiction in the woodcut.

On Hokusai's Great wave off Kanagawa: localization, linearity and a rogue wave in sub-Antarctic waters

PubMed Central

Dudley, J. M.; Sarano, V.; Dias, F.

2013-01-01

The Hokusai woodcut entitled The great wave off Kanagawa has been interpreted as an unusually large storm wave, likely to be classed as a rogue wave, and possibly generated from nonlinear wave dynamics (J. H. E. Cartwright and H. Nakamura, Notes Rec. R. Soc. 63, 119–135 (2009)). In this paper, we present a complementary discussion of this hypothesis, discussing in particular how linear and nonlinear mechanisms can both contribute to the emergence of rogue wave events. By making reference to the Great wave's simultaneous transverse and longitudinal localization, we show that the purely linear mechanism of directional focusing also predicts characteristics consistent with those of the Great wave. In addition, we discuss the properties of a particular rogue wave photographed on the open ocean in sub-Antarctic waters, which shows two-dimensional localization and breaking dynamics remarkably similar to Hokusai's depiction in the woodcut. PMID:24687148

Flexoelectricity in Carbon Nanostructures: Nanotubes, Fullerenes, and Nanocones.

PubMed

Kvashnin, Alexander G; Sorokin, Pavel B; Yakobson, Boris I

2015-07-16

We report theoretical analysis of the electronic flexoelectric effect associated with nanostructures of sp(2) carbon (curved graphene). Through the density functional theory calculations, we establish the universality of the linear dependence of flexoelectric atomic dipole moments on local curvature in various carbon networks (carbon nanotubes, fullerenes with high and low symmetry, and nanocones). The usefulness of such dependence is in the possibility to extend the analysis of any carbon systems with local deformations with respect to their electronic properties. This result is exemplified by exploring of flexoelectric effect in carbon nanocones that display large dipole moment, cumulative over their surface yet surprisingly scaling exactly linearly with the length, and with sine-law dependence on the apex angle, dflex ~ L sin(α). Our study points out the opportunity of predicting the electric dipole moment distribution on complex graphene-based nanostructures based only on the local curvature information.

Nano-Enabled Approaches to Chemical Imaging in Biosystems

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

Retterer, Scott T.; Morrell-Falvey, Jennifer L.; Doktycz, Mitchel John

Understanding and predicting how biosystems function require knowledge about the dynamic physicochemical environments with which they interact and alter by their presence. Yet, identifying specific components, tracking the dynamics of the system, and monitoring local environmental conditions without disrupting biosystem function present significant challenges for analytical measurements. Nanomaterials, by their very size and nature, can act as probes and interfaces to biosystems and offer solutions to some of these challenges. At the nanoscale, material properties emerge that can be exploited for localizing biomolecules and making chemical measurements at cellular and subcellular scales. Here, we review advances in chemical imaging enabledmore » by nanoscale structures, in the use of nanoparticles as chemical and environmental probes, and in the development of micro- and nanoscale fluidic devices to define and manipulate local environments and facilitate chemical measurements of complex biosystems. As a result, integration of these nano-enabled methods will lead to an unprecedented understanding of biosystem function.« less

Diffusion and transport in locally disordered driven lattices

NASA Astrophysics Data System (ADS)

Wulf, Thomas; Okupnik, Alexander; Schmelcher, Peter

2016-09-01

We study the effect of disorder on the particle density evolution in a classical Hamiltonian driven lattice setup. If the disorder is localized within a finite sub-domain of the lattice, the emergence of strong tails in the density distribution which even increases towards larger positions is shown, thus yielding a highly non-Gaussian particle density evolution. As the key underlying mechanism, we identify the conversion between different components of the unperturbed systems mixed phase space which is induced by the disorder. Based on the introduction of individual conversion rates between chaotic and regular components, a theoretical model is developed which correctly predicts the scaling of the particle density. The effect of disorder on the transport properties is studied where a significant enhancement of the transport for cases of localized disorder is shown, thereby contrasting strongly the merely weak modification of the transport for global disorder.

Generalized non-Local Resistance Expression and its Application in F/N/F Spintronic Structure with Graphene Channel

NASA Astrophysics Data System (ADS)

Wei, Huazhou; Fu, Shiwei

We report our work on the spin transport properties in the F/N/F(ferromagnets/normal metal/ferromagnets) spintronic structure from a new theoretical perspective. A significant problem in the field is to explain the inferior measured order of magnitude for spin lifetime. Based on the known non-local resistance formula and the mechanism analysis of spin-flipping within the interfaces between F and N, we analytically derive a broadly applicable new non-local resistance expression and a generalized Hanle curve formula. After employing them in the F/N/F structure under different limits, especially in the case of graphene channel, we find that the fitting from experimental data would yield a longer spin lifetime, which approaches its theoretical predicted value in graphene. The authors acknowledge the financial support by China University of Petroleum-Beijing and the Key Laboratory of Optical Detection Technology for Oil and Gas in this institution.

Diagnostic Peptide Discovery: Prioritization of Pathogen Diagnostic Markers Using Multiple Features

PubMed Central

Carmona, Santiago J.; Sartor, Paula A.; Leguizamón, María S.; Campetella, Oscar E.; Agüero, Fernán

2012-01-01

The availability of complete pathogen genomes has renewed interest in the development of diagnostics for infectious diseases. Synthetic peptide microarrays provide a rapid, high-throughput platform for immunological testing of potential B-cell epitopes. However, their current capacity prevent the experimental screening of complete “peptidomes”. Therefore, computational approaches for prediction and/or prioritization of diagnostically relevant peptides are required. In this work we describe a computational method to assess a defined set of molecular properties for each potential diagnostic target in a reference genome. Properties such as sub-cellular localization or expression level were evaluated for the whole protein. At a higher resolution (short peptides), we assessed a set of local properties, such as repetitive motifs, disorder (structured vs natively unstructured regions), trans-membrane spans, genetic polymorphisms (conserved vs. divergent regions), predicted B-cell epitopes, and sequence similarity against human proteins and other potential cross-reacting species (e.g. other pathogens endemic in overlapping geographical locations). A scoring function based on these different features was developed, and used to rank all peptides from a large eukaryotic pathogen proteome. We applied this method to the identification of candidate diagnostic peptides in the protozoan Trypanosoma cruzi, the causative agent of Chagas disease. We measured the performance of the method by analyzing the enrichment of validated antigens in the high-scoring top of the ranking. Based on this measure, our integrative method outperformed alternative prioritizations based on individual properties (such as B-cell epitope predictors alone). Using this method we ranked 10 million 12-mer overlapping peptides derived from the complete T. cruzi proteome. Experimental screening of 190 high-scoring peptides allowed the identification of 37 novel epitopes with diagnostic potential, while none of the low scoring peptides showed significant reactivity. Many of the metrics employed are dependent on standard bioinformatic tools and data, so the method can be easily extended to other pathogen genomes. PMID:23272069

Improving prediction of heterodimeric protein complexes using combination with pairwise kernel.

PubMed

Ruan, Peiying; Hayashida, Morihiro; Akutsu, Tatsuya; Vert, Jean-Philippe

2018-02-19

Since many proteins become functional only after they interact with their partner proteins and form protein complexes, it is essential to identify the sets of proteins that form complexes. Therefore, several computational methods have been proposed to predict complexes from the topology and structure of experimental protein-protein interaction (PPI) network. These methods work well to predict complexes involving at least three proteins, but generally fail at identifying complexes involving only two different proteins, called heterodimeric complexes or heterodimers. There is however an urgent need for efficient methods to predict heterodimers, since the majority of known protein complexes are precisely heterodimers. In this paper, we use three promising kernel functions, Min kernel and two pairwise kernels, which are Metric Learning Pairwise Kernel (MLPK) and Tensor Product Pairwise Kernel (TPPK). We also consider the normalization forms of Min kernel. Then, we combine Min kernel or its normalization form and one of the pairwise kernels by plugging. We applied kernels based on PPI, domain, phylogenetic profile, and subcellular localization properties to predicting heterodimers. Then, we evaluate our method by employing C-Support Vector Classification (C-SVC), carrying out 10-fold cross-validation, and calculating the average F-measures. The results suggest that the combination of normalized-Min-kernel and MLPK leads to the best F-measure and improved the performance of our previous work, which had been the best existing method so far. We propose new methods to predict heterodimers, using a machine learning-based approach. We train a support vector machine (SVM) to discriminate interacting vs non-interacting protein pairs, based on informations extracted from PPI, domain, phylogenetic profiles and subcellular localization. We evaluate in detail new kernel functions to encode these data, and report prediction performance that outperforms the state-of-the-art.

Developing and applying uncertain global climate change projections for regional water management planning

NASA Astrophysics Data System (ADS)

Groves, David G.; Yates, David; Tebaldi, Claudia

2008-12-01

Climate change may impact water resources management conditions in difficult-to-predict ways. A key challenge for water managers is how to incorporate highly uncertain information about potential climate change from global models into local- and regional-scale water management models and tools to support local planning. This paper presents a new method for developing large ensembles of local daily weather that reflect a wide range of plausible future climate change scenarios while preserving many statistical properties of local historical weather patterns. This method is demonstrated by evaluating the possible impact of climate change on the Inland Empire Utilities Agency service area in southern California. The analysis shows that climate change could impact the region, increasing outdoor water demand by up to 10% by 2040, decreasing local water supply by up to 40% by 2040, and decreasing sustainable groundwater yields by up to 15% by 2040. The range of plausible climate projections suggests the need for the region to augment its long-range water management plans to reduce its vulnerability to climate change.

Structural, electronic, elastic, and thermal properties of CaNiH3 perovskite obtained from first-principles calculations

NASA Astrophysics Data System (ADS)

Benlamari, S.; Bendjeddou, H.; Boulechfar, R.; Amara Korba, S.; Meradji, H.; Ahmed, R.; Ghemid, S.; Khenata, R.; Omran, S. Bin

2018-03-01

A theoretical study of the structural, elastic, electronic, mechanical, and thermal properties of the perovskite-type hydride CaNiH3 is presented. This study is carried out via first-principles full potential (FP) linearized augmented plane wave plus local orbital (LAPW+lo) method designed within the density functional theory (DFT). To treat the exchange–correlation energy/potential for the total energy calculations, the local density approximation (LDA) of Perdew–Wang (PW) and the generalized gradient approximation (GGA) of Perdew–Burke–Ernzerhof (PBE) are used. The three independent elastic constants (C 11, C 12, and C 44) are calculated from the direct computation of the stresses generated by small strains. Besides, we report the variation of the elastic constants as a function of pressure as well. From the calculated elastic constants, the mechanical character of CaNiH3 is predicted. Pertaining to the thermal properties, the Debye temperature is estimated from the average sound velocity. To further comprehend this compound, the quasi-harmonic Debye model is used to analyze the thermal properties. From the calculations, we find that the obtained results of the lattice constant (a 0), bulk modulus (B 0), and its pressure derivative ({B}0^{\\prime }) are in good agreement with the available theoretical as well as experimental results. Similarly, the obtained electronic band structure demonstrates the metallic character of this perovskite-type hydride.

Linear and Branched PEIs (Polyethylenimines) and Their Property Space.

PubMed

Lungu, Claudiu N; Diudea, Mircea V; Putz, Mihai V; Grudziński, Ireneusz P

2016-04-13

A chemical property space defines the adaptability of a molecule to changing conditions and its interaction with other molecular systems determining a pharmacological response. Within a congeneric molecular series (compounds with the same derivatization algorithm and thus the same brute formula) the chemical properties vary in a monotonic manner, i.e., congeneric compounds share the same chemical property space. The chemical property space is a key component in molecular design, where some building blocks are functionalized, i.e., derivatized, and eventually self-assembled in more complex systems, such as enzyme-ligand systems, of which (physico-chemical) properties/bioactivity may be predicted by QSPR/QSAR (quantitative structure-property/activity relationship) studies. The system structure is determined by the binding type (temporal/permanent; electrostatic/covalent) and is reflected in its local electronic (and/or magnetic) properties. Such nano-systems play the role of molecular devices, important in nano-medicine. In the present article, the behavior of polyethylenimine (PEI) macromolecules (linear LPEI and branched BPEI, respectively) with respect to the glucose oxidase enzyme GOx is described in terms of their (interacting) energy, geometry and topology, in an attempt to find the best shape and size of PEIs to be useful for a chosen (nanochemistry) purpose.

Linear and Branched PEIs (Polyethylenimines) and Their Property Space

PubMed Central

Lungu, Claudiu N.; Diudea, Mircea V.; Putz, Mihai V.; Grudziński, Ireneusz P.

2016-01-01

A chemical property space defines the adaptability of a molecule to changing conditions and its interaction with other molecular systems determining a pharmacological response. Within a congeneric molecular series (compounds with the same derivatization algorithm and thus the same brute formula) the chemical properties vary in a monotonic manner, i.e., congeneric compounds share the same chemical property space. The chemical property space is a key component in molecular design, where some building blocks are functionalized, i.e., derivatized, and eventually self-assembled in more complex systems, such as enzyme-ligand systems, of which (physico-chemical) properties/bioactivity may be predicted by QSPR/QSAR (quantitative structure-property/activity relationship) studies. The system structure is determined by the binding type (temporal/permanent; electrostatic/covalent) and is reflected in its local electronic (and/or magnetic) properties. Such nano-systems play the role of molecular devices, important in nano-medicine. In the present article, the behavior of polyethylenimine (PEI) macromolecules (linear LPEI and branched BPEI, respectively) with respect to the glucose oxidase enzyme GOx is described in terms of their (interacting) energy, geometry and topology, in an attempt to find the best shape and size of PEIs to be useful for a chosen (nanochemistry) purpose. PMID:27089324

Introducing local property tax for fiscal decentralization and local authority autonomy

NASA Astrophysics Data System (ADS)

Dimopoulos, Thomas; Labropoulos, Tassos; Hadjimitsis, Diafantos G.

2015-06-01

Charles Tiebout (1956), in his work "A Pure Theory of Local Expenditures", provides a vision of the workings of the local public sector, acknowledging many similarities to the features of a competitive market, however omitting any references to local taxation. Contrary to other researchers' claim that the Tiebout model and the theory of fiscal decentralization are by no means synonymous, this paper aims to expand Tiebout's theory, by adding the local property tax in the context, introducing a fair, ad valorem property taxation system based on the automated assessment of the value of real estate properties within the boundaries of local authorities. Computer Assisted Mass Appraisal methodology integrated with Remote Sensing technology and GIS analysis is applied to local authorities' property registries and cadastral data, building a spatial relational database and providing data to be statistically processed through Multiple Regression Analysis modeling. The proposed scheme accomplishes economy of scale using CAMA procedures on one hand, but also succeeds in making local authorities self-sufficient through a decentralized, fair, locally calibrated property taxation model, providing rational income administration.

Evaluating Predictive Uncertainty of Hyporheic Exchange Modelling

NASA Astrophysics Data System (ADS)

Chow, R.; Bennett, J.; Dugge, J.; Wöhling, T.; Nowak, W.

2017-12-01

Hyporheic exchange is the interaction of water between rivers and groundwater, and is difficult to predict. One of the largest contributions to predictive uncertainty for hyporheic fluxes have been attributed to the representation of heterogeneous subsurface properties. This research aims to evaluate which aspect of the subsurface representation - the spatial distribution of hydrofacies or the model for local-scale (within-facies) heterogeneity - most influences the predictive uncertainty. Also, we seek to identify data types that help reduce this uncertainty best. For this investigation, we conduct a modelling study of the Steinlach River meander, in Southwest Germany. The Steinlach River meander is an experimental site established in 2010 to monitor hyporheic exchange at the meander scale. We use HydroGeoSphere, a fully integrated surface water-groundwater model, to model hyporheic exchange and to assess the predictive uncertainty of hyporheic exchange transit times (HETT). A highly parameterized complex model is built and treated as `virtual reality', which is in turn modelled with simpler subsurface parameterization schemes (Figure). Then, we conduct Monte-Carlo simulations with these models to estimate the predictive uncertainty. Results indicate that: Uncertainty in HETT is relatively small for early times and increases with transit times. Uncertainty from local-scale heterogeneity is negligible compared to uncertainty in the hydrofacies distribution. Introducing more data to a poor model structure may reduce predictive variance, but does not reduce predictive bias. Hydraulic head observations alone cannot constrain the uncertainty of HETT, however an estimate of hyporheic exchange flux proves to be more effective at reducing this uncertainty. Figure: Approach for evaluating predictive model uncertainty. A conceptual model is first developed from the field investigations. A complex model (`virtual reality') is then developed based on that conceptual model. This complex model then serves as the basis to compare simpler model structures. Through this approach, predictive uncertainty can be quantified relative to a known reference solution.

Subsidence from underground mining; environmental analysis and planning considerations

USGS Publications Warehouse

Lee, Fitzhugh T.; Abel, John F.

1983-01-01

Subsidence, a universal process that occurs in response to the voids created by extracting solids or liquids from beneath the Earth's surface, is controlled by many factors including mining methods, depth of extraction, thickness of deposit, and topography, as well as the in situ properties of the rock mass above the deposit. The impacts of subsidence are potentially severe in terms of damage to surface utility lines and structures, changes in surface-water and ground-water conditions, and effects on vegetation and animals. Although subsidence cannot be eliminated, it can be reduced or controlled in areas where deformation of the ground surface would produce dangerous or costly effects. Subsidence prediction is highly developed in Europe where there are comparatively uniform mining conditions and a long history of field measurements. Much of this mining has been carried out beneath crowded urban and industrial areas where accurate predictions have facilitated use of the surface and reduced undesirable impacts. Concerted efforts to understand subsidence processes in the United States are recent. Empirical methods of subsidence analysis and prediction based on local conditions seem better suited to the current state of knowledge of the varied geologic and topographic conditions in domestic coal mining regions than do theoretical/mathematical approaches. In order to develop broadly applicable subsidence prediction methods and models for the United States, more information is needed on magnitude and timing of ground movements and geologic properties.

Where Are All of the Gas-bearing Local Dwarf Galaxies? Quantifying Possible Impacts of Reionization

NASA Astrophysics Data System (ADS)

Tollerud, Erik J.; Peek, J. E. G.

2018-04-01

We present an approach for comparing the detections and non-detections of Local Group (LG) dwarf galaxies in large H I surveys to the predictions of a suite of n-body simulations of the LG. This approach depends primarily on a set of empirical scaling relations to connect the simulations to the observations, rather than making strong theoretical assumptions. We then apply this methodology to the Galactic Arecibo L-band Feed Array Hi (GALFA-HI) Compact Cloud Catalog (CCC), and compare it to the suite Exploring the Local Volume In Simulations (ELVIS) of simulations. This approach reveals a strong tension between the naïve results of the model and the observations: while there are no LG dwarfs in the GALFA-HI CCC, the simulations predict ∼10. Applying a simple model of reionization can resolve this tension by preventing low-mass halos from forming gas. However, and if this effect operates as expected, the observations provide a constraint on the mass scale of the dwarf galaxy that reionization impacts. Combined with the observed properties of Leo T, the halo virial mass scale at which reionization impacts dwarf galaxy gas content is constrained to be ∼ {10}8.5 {M}ȯ , independent of any assumptions about star formation.

On the phenomenon of curved microcracks in /(S)/90n/s laminates - Their shapes, initiation angles and locations

NASA Technical Reports Server (NTRS)

Hu, Shoufeng; Bark, Jong S.; Nairn, John A.

1993-01-01

A variational analysis of the stress state in microcracked cross-ply laminates has been used to investigate the phenomenon of curved microcracking in /(S)/90n/s laminates. Previous investigators proposed that the initiation and orientation of curved microcracks are controlled by local maxima and stress trajectories of the principal stresses. We have implemented a principal stress model using a variational mechanics stress analysis and we were able to make predictions about curved microcracks. The predictions agree well with experimental observations and therefore support the assertion that the variational analysis gives an accurate stress state that is useful for modeling the microcracking properties of cross-ply laminates. An important prediction about curved microcracks is that they are a late stage of microcracking damage. They occur only when the crack density of straight microcracks exceeds the critical crack density for curved microcracking. The predicted critical crack density for curved microcracking agrees well with experimental observations.

Cluster dynamics and cluster size distributions in systems of self-propelled particles

NASA Astrophysics Data System (ADS)

Peruani, F.; Schimansky-Geier, L.; Bär, M.

2010-12-01

Systems of self-propelled particles (SPP) interacting by a velocity alignment mechanism in the presence of noise exhibit rich clustering dynamics. Often, clusters are responsible for the distribution of (local) information in these systems. Here, we investigate the properties of individual clusters in SPP systems, in particular the asymmetric spreading behavior of clusters with respect to their direction of motion. In addition, we formulate a Smoluchowski-type kinetic model to describe the evolution of the cluster size distribution (CSD). This model predicts the emergence of steady-state CSDs in SPP systems. We test our theoretical predictions in simulations of SPP with nematic interactions and find that our simple kinetic model reproduces qualitatively the transition to aggregation observed in simulations.

Microwave thermal ablation: Effects of tissue properties variations on predictive models for treatment planning.

PubMed

Lopresto, Vanni; Pinto, Rosanna; Farina, Laura; Cavagnaro, Marta

2017-08-01

Microwave thermal ablation (MTA) therapy for cancer treatments relies on the absorption of electromagnetic energy at microwave frequencies to induce a very high and localized temperature increase, which causes an irreversible thermal damage in the target zone. Treatment planning in MTA is based on experimental observations of ablation zones in ex vivo tissue, while predicting the treatment outcomes could be greatly improved by reliable numerical models. In this work, a fully dynamical simulation model is exploited to look at effects of temperature-dependent variations in the dielectric and thermal properties of the targeted tissue on the prediction of the temperature increase and the extension of the thermally coagulated zone. In particular, the influence of measurement uncertainty of tissue parameters on the numerical results is investigated. Numerical data were compared with data from MTA experiments performed on ex vivo bovine liver tissue at 2.45GHz, with a power of 60W applied for 10min. By including in the simulation model an uncertainty budget (CI=95%) of ±25% in the properties of the tissue due to inaccuracy of measurements, numerical results were achieved in the range of experimental data. Obtained results also showed that the specific heat especially influences the extension of the thermally coagulated zone, with an increase of 27% in length and 7% in diameter when a variation of -25% is considered with respect to the value of the reference simulation model. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

A program for automatically predicting supramolecular aggregates and its application to urea and porphin [A programme for the automated geometry prediction of supra-molecular aggregates and its application to the examples of urea and porphin

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

Sachse, Torsten; Martinez, Todd J.; Dietzek, Benjamin

Not only the molecular structure but also the presence or absence of aggregates determines many properties of organic materials. Theoretical investigation of such aggregates requires the prediction of a suitable set of diverse structures. Here, we present the open–source program EnergyScan for the unbiased prediction of geometrically diverse sets of small aggregates. Its bottom–up approach is complementary to existing ones by performing a detailed scan of an aggregate's potential energy surface, from which diverse local energy minima are selected. We crossvalidate this approach by predicting both literature–known and heretofore unreported geometries of the urea dimer. We also predict a diversemore » set of dimers of the less intensely studied case of porphin, which we investigate further using quantum chemistry. For several dimers, we find strong deviations from a reference absorption spectrum, which we explain using computed transition densities. Furthermore, this proof of principle clearly shows that EnergyScan successfully predicts aggregates exhibiting large structural and spectral diversity.« less

A program for automatically predicting supramolecular aggregates and its application to urea and porphin [A programme for the automated geometry prediction of supra-molecular aggregates and its application to the examples of urea and porphin

DOE PAGES

Sachse, Torsten; Martinez, Todd J.; Dietzek, Benjamin; ...

2018-01-03

Not only the molecular structure but also the presence or absence of aggregates determines many properties of organic materials. Theoretical investigation of such aggregates requires the prediction of a suitable set of diverse structures. Here, we present the open–source program EnergyScan for the unbiased prediction of geometrically diverse sets of small aggregates. Its bottom–up approach is complementary to existing ones by performing a detailed scan of an aggregate's potential energy surface, from which diverse local energy minima are selected. We crossvalidate this approach by predicting both literature–known and heretofore unreported geometries of the urea dimer. We also predict a diversemore » set of dimers of the less intensely studied case of porphin, which we investigate further using quantum chemistry. For several dimers, we find strong deviations from a reference absorption spectrum, which we explain using computed transition densities. Furthermore, this proof of principle clearly shows that EnergyScan successfully predicts aggregates exhibiting large structural and spectral diversity.« less

ILS Localizer Performance Prediction of an Alford 1B Array Near a Limited Access Road at the New Orleans Airport.

DOT National Transportation Integrated Search

1974-08-01

The Transportation Systems Center (TSC) ILS Localizer Performance Prediction Model was used to predict the derogation to an Alford 1B Localizer caused by vehicular traffic traveling on a roadway to be located in front of the localizer. Several differ...

Graph wavelet alignment kernels for drug virtual screening.

PubMed

Smalter, Aaron; Huan, Jun; Lushington, Gerald

2009-06-01

In this paper, we introduce a novel statistical modeling technique for target property prediction, with applications to virtual screening and drug design. In our method, we use graphs to model chemical structures and apply a wavelet analysis of graphs to summarize features capturing graph local topology. We design a novel graph kernel function to utilize the topology features to build predictive models for chemicals via Support Vector Machine classifier. We call the new graph kernel a graph wavelet-alignment kernel. We have evaluated the efficacy of the wavelet-alignment kernel using a set of chemical structure-activity prediction benchmarks. Our results indicate that the use of the kernel function yields performance profiles comparable to, and sometimes exceeding that of the existing state-of-the-art chemical classification approaches. In addition, our results also show that the use of wavelet functions significantly decreases the computational costs for graph kernel computation with more than ten fold speedup.

Energy landscapes for a machine-learning prediction of patient discharge

NASA Astrophysics Data System (ADS)

Das, Ritankar; Wales, David J.

2016-06-01

The energy landscapes framework is applied to a configuration space generated by training the parameters of a neural network. In this study the input data consists of time series for a collection of vital signs monitored for hospital patients, and the outcomes are patient discharge or continued hospitalisation. Using machine learning as a predictive diagnostic tool to identify patterns in large quantities of electronic health record data in real time is a very attractive approach for supporting clinical decisions, which have the potential to improve patient outcomes and reduce waiting times for discharge. Here we report some preliminary analysis to show how machine learning might be applied. In particular, we visualize the fitting landscape in terms of locally optimal neural networks and the connections between them in parameter space. We anticipate that these results, and analogues of thermodynamic properties for molecular systems, may help in the future design of improved predictive tools.

Comparison of radiation parametrizations within the HARMONIE-AROME NWP model

NASA Astrophysics Data System (ADS)

Rontu, Laura; Lindfors, Anders V.

2018-05-01

Downwelling shortwave radiation at the surface (SWDS, global solar radiation flux), given by three different parametrization schemes, was compared to observations in the HARMONIE-AROME numerical weather prediction (NWP) model experiments over Finland in spring 2017. Simulated fluxes agreed well with each other and with the observations in the clear-sky cases. In the cloudy-sky conditions, all schemes tended to underestimate SWDS at the daily level, as compared to the measurements. Large local and temporal differences between the model results and observations were seen, related to the variations and uncertainty of the predicted cloud properties. The results suggest a possibility to benefit from the use of different radiative transfer parametrizations in a NWP model to obtain perturbations for the fine-resolution ensemble prediction systems. In addition, we recommend usage of the global radiation observations for the standard validation of the NWP models.

Bioinformatics analysis of the predicted polyprenol reductase genes in higher plants

NASA Astrophysics Data System (ADS)

Basyuni, M.; Wati, R.

2018-03-01

The present study evaluates the bioinformatics methods to analyze twenty-four predicted polyprenol reductase genes from higher plants on GenBank as well as predicted the structure, composition, similarity, subcellular localization, and phylogenetic. The physicochemical properties of plant polyprenol showed diversity among the observed genes. The percentage of the secondary structure of plant polyprenol genes followed the ratio order of α helix > random coil > extended chain structure. The values of chloroplast but not signal peptide were too low, indicated that few chloroplast transit peptide in plant polyprenol reductase genes. The possibility of the potential transit peptide showed variation among the plant polyprenol reductase, suggested the importance of understanding the variety of peptide components of plant polyprenol genes. To clarify this finding, a phylogenetic tree was drawn. The phylogenetic tree shows several branches in the tree, suggested that plant polyprenol reductase genes grouped into divergent clusters in the tree.

Learning structure-property relationship in crystalline materials: A study of lanthanide-transition metal alloys

NASA Astrophysics Data System (ADS)

Pham, Tien-Lam; Nguyen, Nguyen-Duong; Nguyen, Van-Doan; Kino, Hiori; Miyake, Takashi; Dam, Hieu-Chi

2018-05-01

We have developed a descriptor named Orbital Field Matrix (OFM) for representing material structures in datasets of multi-element materials. The descriptor is based on the information regarding atomic valence shell electrons and their coordination. In this work, we develop an extension of OFM called OFM1. We have shown that these descriptors are highly applicable in predicting the physical properties of materials and in providing insights on the materials space by mapping into a low embedded dimensional space. Our experiments with transition metal/lanthanide metal alloys show that the local magnetic moments and formation energies can be accurately reproduced using simple nearest-neighbor regression, thus confirming the relevance of our descriptors. Using kernel ridge regressions, we could accurately reproduce formation energies and local magnetic moments calculated based on first-principles, with mean absolute errors of 0.03 μB and 0.10 eV/atom, respectively. We show that meaningful low-dimensional representations can be extracted from the original descriptor using descriptive learning algorithms. Intuitive prehension on the materials space, qualitative evaluation on the similarities in local structures or crystalline materials, and inference in the designing of new materials by element substitution can be performed effectively based on these low-dimensional representations.

Schizophrenia classification using functional network features

NASA Astrophysics Data System (ADS)

Rish, Irina; Cecchi, Guillermo A.; Heuton, Kyle

2012-03-01

This paper focuses on discovering statistical biomarkers (features) that are predictive of schizophrenia, with a particular focus on topological properties of fMRI functional networks. We consider several network properties, such as node (voxel) strength, clustering coefficients, local efficiency, as well as just a subset of pairwise correlations. While all types of features demonstrate highly significant statistical differences in several brain areas, and close to 80% classification accuracy, the most remarkable results of 93% accuracy are achieved by using a small subset of only a dozen of most-informative (lowest p-value) correlation features. Our results suggest that voxel-level correlations and functional network features derived from them are highly informative about schizophrenia and can be used as statistical biomarkers for the disease.

Electronic properties of Laves phase ZrFe{sub 2} using Compton spectroscopy

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

Bhatt, Samir, E-mail: sameerbhatto11@gmail.com; Kumar, Kishor; Ahuja, B. L.

First-ever experimental Compton profile of Laves phase ZrFe{sub 2}, using indigenous 20 Ci {sup 137}Cs Compton spectrometer, is presented. To analyze the experimental electron momentum density, we have deduced the theoretical Compton profiles using density functional theory (DFT) and hybridization of DFT and Hartree-Fock scheme within linear combination of atomic orbitals (LCAO) method. The energy bands and density of states are also calculated using LCAO prescription. The theoretical profile based on local density approximation gives a better agreement with the experimental profile than other reported schemes. The present investigations validate the inclusion of correlation potential of Perdew-Zunger in predicting themore » electronic properties of ZrFe{sub 2}.« less

The evolution history of the extended solar neighbourhood

NASA Astrophysics Data System (ADS)

Just, Andreas; Sysoliatina, Kseniia; Koutsouridou, Ioanna

2018-04-01

Our detailed analytic local disc model (JJ-model) quantifies the interrelation between kinematic properties (e.g. velocity dispersions and asymmetric drift), spatial parameters (scale-lengths and vertical density profiles), and properties of stellar sub-populations (age and abundance distributions). We discuss a radial extension of the disc evolution model representing an inside-out growth of the thin disc with constant thickness. Based on metallicity distributions of APOGEE red clump stars we derive the AMR as function of galactrocentric distance and show that mono-abundance as well as mono-age populations are flaring. The predictions of the JJ-model are consistent with the TGAS-RAVE data, which provide a significant improvement of the kinematic data and unbiased distances for more than 250,000 stars.

Can voter-approved tax levies provide fiscal advantages and stability for local public health agencies?

PubMed

Schmalzried, Hans D; Fallon, L Fleming

2013-01-01

Major funding cuts have occurred throughout the United States public health system during the past several years. Funding for local public health agency (LPHA) services and programs is obtained through a patchwork of sources that vary both within and among states. Even though local city and county sources provide a significant proportion of funding for LPHAs, information available in the literature about these revenues is sparse and is not clearly described. This study focused on a single specific revenue stream included in the local sources (local city and county) category: funds voted on directly by the public. The primary purpose of this study was to examine whether this type of funding source provided fiscal advantages for LPHAs. Specifically, we wanted to see how sensitive levy votes were to changing general economic conditions. A questionnaire to collect LPHA levy data was developed, approved, and mailed to county boards of elections in Ohio (n = 88). Elections officials were asked to provide voting results for all LPHA levy ballot attempts since 1994 regardless of outcome. In the study period (1994 through 2011), 250 LPHA property tax levies were placed on election ballots in Ohio. LPHAs were successful in 155 (62.0%) and unsuccessful in 95 (38.0%) attempts. Over the 18-year period, the most noteworthy outcome was a 94.6% pass rate for renewal levies. Our study demonstrated that voter-approved tax levies provide some fiscal advantages for LPHAs: higher per capita revenues than those who have to rely on other sources of income and predictable revenue streams. This translates into more funds being available for public health programs and services. Property tax levies allow citizens to make direct investments in their local health departments.

Homeostatic maintenance via degradation and repair of elastic fibers under tension

NASA Astrophysics Data System (ADS)

Alves, Calebe; Araújo, Ascanio D.; Oliveira, Cláudio L. N.; Imsirovic, Jasmin; Bartolák-Suki, Erzsébet; Andrade, José S.; Suki, Béla

2016-06-01

Cellular maintenance of the extracellular matrix requires an effective regulation that balances enzymatic degradation with the repair of collagen fibrils and fibers. Here, we investigate the long-term maintenance of elastic fibers under tension combined with diffusion of general degradative and regenerative particles associated with digestion and repair processes. Computational results show that homeostatic fiber stiffness can be achieved by assuming that cells periodically probe fiber stiffness to adjust the production and release of degradative and regenerative particles. However, this mechanism is unable to maintain a homogeneous fiber. To account for axial homogeneity, we introduce a robust control mechanism that is locally governed by how the binding affinity of particles is modulated by mechanical forces applied to the ends of the fiber. This model predicts diameter variations along the fiber that are in agreement with the axial distribution of collagen fibril diameters obtained from scanning electron microscopic images of normal rat thoracic aorta. The model predictions match the experiments only when the applied force on the fiber is in the range where the variance of local stiffness along the fiber takes a minimum value. Our model thus predicts that the biophysical properties of the fibers play an important role in the long-term regulatory maintenance of these fibers.

A systems approach to hemostasis: 3. Thrombus consolidation regulates intrathrombus solute transport and local thrombin activity

PubMed Central

Welsh, John D.; Tomaiuolo, Maurizio; Wu, Jie; Colace, Thomas V.; Diamond, Scott L.

2014-01-01

Hemostatic thrombi formed after a penetrating injury have a distinctive structure in which a core of highly activated, closely packed platelets is covered by a shell of less-activated, loosely packed platelets. We have shown that differences in intrathrombus molecular transport emerge in parallel with regional differences in platelet packing density and predicted that these differences affect thrombus growth and stability. Here we test that prediction in a mouse vascular injury model. The studies use a novel method for measuring thrombus contraction in vivo and a previously characterized mouse line with a defect in integrin αIIbβ3 outside-in signaling that affects clot retraction ex vivo. The results show that the mutant mice have a defect in thrombus consolidation following vascular injury, resulting in an increase in intrathrombus transport rates and, as predicted by computational modeling, a decrease in thrombin activity and platelet activation in the thrombus core. Collectively, these data (1) demonstrate that in addition to the activation state of individual platelets, the physical properties of the accumulated mass of adherent platelets is critical in determining intrathrombus agonist distribution and platelet activation and (2) define a novel role for integrin signaling in the regulation of intrathrombus transport rates and localization of thrombin activity. PMID:24951426

Energy- and wave-based beam-tracing prediction of room-acoustical parameters using different boundary conditions.

PubMed

Yousefzadeh, Behrooz; Hodgson, Murray

2012-09-01

A beam-tracing model was used to study the acoustical responses of three empty, rectangular rooms with different boundary conditions. The model is wave-based (accounting for sound phase) and can be applied to rooms with extended-reaction surfaces that are made of multiple layers of solid, fluid, or poroelastic materials-the acoustical properties of these surfaces are calculated using Biot theory. Three room-acoustical parameters were studied in various room configurations: sound strength, reverberation time, and RApid Speech Transmission Index. The main objective was to investigate the effects of modeling surfaces as either local or extended reaction on predicted values of these three parameters. Moreover, the significance of modeling interference effects was investigated, including the study of sound phase-change on surface reflection. Modeling surfaces as of local or extended reaction was found to be significant for surfaces consisting of multiple layers, specifically when one of the layers is air. For multilayers of solid materials with an air-cavity, this was most significant around their mass-air-mass resonance frequencies. Accounting for interference effects made significant changes in the predicted values of all parameters. Modeling phase change on reflection, on the other hand, was found to be relatively much less significant.

Magnesium acceptor in gallium nitride. II. Koopmans-tuned Heyd-Scuseria-Ernzerhof hybrid functional calculations of its dual nature and optical properties

NASA Astrophysics Data System (ADS)

Demchenko, D. O.; Diallo, I. C.; Reshchikov, M. A.

2018-05-01

The problem of magnesium acceptor in gallium nitride is that experimental photoluminescence measurements clearly reveal a shallow defect state, while most theoretical predictions favor a localized polaronic defect state. To resolve this contradiction, we calculate properties of magnesium acceptor using the Heyd-Scuseria-Ernzerhof (HSE) hybrid functional, tuned to fulfill the generalized Koopmans condition. We test Koopmans tuning of HSE for defect calculations in GaN using two contrasting test cases: a deep state of gallium vacancy and a shallow state of magnesium acceptor. The obtained parametrization of HSE allows calculations of optical properties of acceptors using neutral defect-state eigenvalues, without relying on corrections due to charged defects in periodic supercells. Optical transitions and vibrational properties of M gGa defect are analyzed to bring the dual (shallow and deep) nature of this defect into accord with experimental photoluminescence measurements of the ultraviolet band in Mg-doped GaN samples.

The archetype-genome exemplar in molecular dynamics and continuum mechanics

NASA Astrophysics Data System (ADS)

Greene, M. Steven; Li, Ying; Chen, Wei; Liu, Wing Kam

2014-04-01

We argue that mechanics and physics of solids rely on a fundamental exemplar: the apparent properties of a system depend on the building blocks that comprise it. Building blocks are referred to as archetypes and apparent system properties as the system genome. Three entities are of importance: the archetype properties, the conformation of archetypes, and the properties of interactions activated by that conformation. The combination of these entities into the system genome is called assembly. To show the utility of the archetype-genome exemplar, this work presents the mathematical ingredients and computational implementation of theories in solid mechanics that are (1) molecular and (2) continuum manifestations of the assembly process. Both coarse-grained molecular dynamics (CGMD) and the archetype-blending continuum (ABC) theories are formulated then applied to polymer nanocomposites (PNCs) to demonstrate the impact the components of the assembly triplet have on a material genome. CGMD simulations demonstrate the sensitivity of nanocomposite viscosities and diffusion coefficients to polymer chain types (archetype), polymer-nanoparticle interaction potentials (interaction), and the structural configuration (conformation) of dispersed nanoparticles. ABC simulations show the contributions of bulk polymer (archetype) properties, occluded region of bound rubber (interaction) properties, and microstructural binary images (conformation) to predictions of linear damping properties, the Payne effect, and localization/size effects in the same class of PNC material. The paper is light on mathematics. Instead, the focus is on the usefulness of the archetype-genome exemplar to predict system behavior inaccessible to classical theories by transitioning mechanics away from heuristic laws to mechanism-based ones. There are two core contributions of this research: (1) presentation of a fundamental axiom—the archetype-genome exemplar—to guide theory development in computational mechanics, and (2) demonstrations of its utility in modern theoretical realms: CGMD, and generalized continuum mechanics.

Fine-Tuning Tomato Agronomic Properties by Computational Genome Redesign

PubMed Central

Carrera, Javier; Fernández del Carmen, Asun; Fernández-Muñoz, Rafael; Rambla, Jose Luis; Pons, Clara; Jaramillo, Alfonso; Elena, Santiago F.; Granell, Antonio

2012-01-01

Considering cells as biofactories, we aimed to optimize its internal processes by using the same engineering principles that large industries are implementing nowadays: lean manufacturing. We have applied reverse engineering computational methods to transcriptomic, metabolomic and phenomic data obtained from a collection of tomato recombinant inbreed lines to formulate a kinetic and constraint-based model that efficiently describes the cellular metabolism from expression of a minimal core of genes. Based on predicted metabolic profiles, a close association with agronomic and organoleptic properties of the ripe fruit was revealed with high statistical confidence. Inspired in a synthetic biology approach, the model was used for exploring the landscape of all possible local transcriptional changes with the aim of engineering tomato fruits with fine-tuned biotechnological properties. The method was validated by the ability of the proposed genomes, engineered for modified desired agronomic traits, to recapitulate experimental correlations between associated metabolites. PMID:22685389

Properties of ultra low frequency upstream waves at Venus and Saturn: A comparison

NASA Technical Reports Server (NTRS)

Orlowski, D. S.; Russell, C. T.; Krauss-Varban, D.; Omidi, N.

1995-01-01

The upstream regions of all planets, except Pluto, have been investigated, using in situ spacecraft measurements and a variety of analysis techniques. The detailed studies at Earth indicate that these waves are generated locally in the magnetically connected solar wind by the interaction with ions backstreaming from the shock. However, since the properties of the solar wind vary with heliocentric distance and since properties of planetary shocks depend on plasma beta, interplanetary magnetic field (IMF) spiral angle and Mach number, the amount of heating, acceleration efficiencies, etc. significantly change with heliocentric distance. In turn the waves seen at each planet propagate not in the same but different (physical) propagation modes. In this paper we compare the ULF wave observations at an outer and an inner planet. We use the results of the ratio, quantites easily derivable with sufficient accuracy at each planet. We use the full electromagnetic dispersion relation for comparison with theoretical predictions.

Ultra-Flexibility and Unusual Electronic, Magnetic and Chemical Properties of Waved Graphenes and Nanoribbons

PubMed Central

Pan, Hui; Chen, Bin

2014-01-01

Two-dimensional materials have attracted increasing attention because of their particular properties and potential applications in next-generation nanodevices. In this work, we investigate the physical and chemical properties of waved graphenes/nanoribbons based on first-principles calculations. We show that waved graphenes are compressible up to a strain of 50% and ultra-flexible because of the vanishing in-plane stiffness. The conductivity of waved graphenes is reduced due to charge decoupling under high compression. Our analysis of pyramidalization angles predicts that the chemistry of waved graphenes can be easily controlled by modulating local curvatures. We further demonstrate that band gaps of armchair waved graphene nanoribbons decrease with the increase of compression if they are asymmetrical in geometry, while increase if symmetrical. For waved zigzag nanoribbons, their anti-ferromagnetic states are strongly enhanced by increasing compression. The versatile functions of waved graphenes enable their applications in multi-functional nanodevices and sensors. PMID:24569444

The importance of stress percolation patterns in rocks and other polycrystalline materials.

PubMed

Burnley, P C

2013-01-01

A new framework for thinking about the deformation behavior of rocks and other heterogeneous polycrystalline materials is proposed, based on understanding the patterns of stress transmission through these materials. Here, using finite element models, I show that stress percolates through polycrystalline materials that have heterogeneous elastic and plastic properties of the same order as those found in rocks. The pattern of stress percolation is related to the degree of heterogeneity in and statistical distribution of the elastic and plastic properties of the constituent grains in the aggregate. The development of these stress patterns leads directly to shear localization, and their existence provides insight into the formation of rhythmic features such as compositional banding and foliation in rocks that are reacting or dissolving while being deformed. In addition, this framework provides a foundation for understanding and predicting the macroscopic rheology of polycrystalline materials based on single-crystal elastic and plastic mechanical properties.

The importance of stress percolation patterns in rocks and other polycrystalline materials

PubMed Central

Burnley, P.C.

2013-01-01

A new framework for thinking about the deformation behavior of rocks and other heterogeneous polycrystalline materials is proposed, based on understanding the patterns of stress transmission through these materials. Here, using finite element models, I show that stress percolates through polycrystalline materials that have heterogeneous elastic and plastic properties of the same order as those found in rocks. The pattern of stress percolation is related to the degree of heterogeneity in and statistical distribution of the elastic and plastic properties of the constituent grains in the aggregate. The development of these stress patterns leads directly to shear localization, and their existence provides insight into the formation of rhythmic features such as compositional banding and foliation in rocks that are reacting or dissolving while being deformed. In addition, this framework provides a foundation for understanding and predicting the macroscopic rheology of polycrystalline materials based on single-crystal elastic and plastic mechanical properties. PMID:23823992

Towards in vivo focal cortical dysplasia phenotyping using quantitative MRI.

PubMed

Adler, Sophie; Lorio, Sara; Jacques, Thomas S; Benova, Barbora; Gunny, Roxana; Cross, J Helen; Baldeweg, Torsten; Carmichael, David W

2017-01-01

Focal cortical dysplasias (FCDs) are a range of malformations of cortical development each with specific histopathological features. Conventional radiological assessment of standard structural MRI is useful for the localization of lesions but is unable to accurately predict the histopathological features. Quantitative MRI offers the possibility to probe tissue biophysical properties in vivo and may bridge the gap between radiological assessment and ex-vivo histology. This review will cover histological, genetic and radiological features of FCD following the ILAE classification and will explain how quantitative voxel- and surface-based techniques can characterise these features. We will provide an overview of the quantitative MRI measures available, their link with biophysical properties and finally the potential application of quantitative MRI to the problem of FCD subtyping. Future research linking quantitative MRI to FCD histological properties should improve clinical protocols, allow better characterisation of lesions in vivo and tailored surgical planning to the individual.

Simulation Studies of Mechanical Properties of Novel Silica Nano-structures

NASA Astrophysics Data System (ADS)

Muralidharan, Krishna; Torras Costa, Joan; Trickey, Samuel B.

2006-03-01

Advances in nanotechnology and the importance of silica as a technological material continue to stimulate computational study of the properties of possible novel silica nanostructures. Thus we have done classical molecular dynamics (MD) and multi-scale quantum mechanical (QM/MD) simulation studies of the mechanical properties of single-wall and multi-wall silica nano-rods of varying dimensions. Such nano-rods have been predicted by Mallik et al. to be unusually strong in tensile failure. Here we compare failure mechanisms of such nano-rods under tension, compression, and bending. The concurrent multi-scale QM/MD studies use the general PUPIL system (Torras et al.). In this case, PUPIL provides automated interoperation of the MNDO Transfer Hamiltonian QM code (Taylor et al.) and a locally written MD code. Embedding of the QM-forces domain is via the scheme of Mallik et al. Work supported by NSF ITR award DMR-0325553.

Computational investigations of the band structure, and thermodynamic and optical features of thorium-based oxide ThGeO4 using the full-potential linearized augmented plane-wave plus local orbital approach

NASA Astrophysics Data System (ADS)

Chiker, F.; Khachai, H.; Mathieu, C.; Bin-Omran, S.; Kada, Belkacem; Sun, Xiao-Wei; Sandeep; Rai, D. P.; Khenata, R.

2018-05-01

In this study, first-principles investigations were performed using the full-potential linearized augmented plane-wave method of the structural and optoelectronic properties of thorium germinate (ThGeO4), a high-K dielectric material. Under ambient conditions, the structural properties calculated for ThGeO4 in the zircon phase were in excellent agreement with the available experimental data. Furthermore, using the modified Becke -Johnson correction method, the calculated band gaps and optical constants accurately described this compound. Finally, the thermal properties were predicted over a temperature range of 0-700 K and pressures up to 11 GPa using the quasi-harmonic Debye model, where the variations in the heat capacity, primitive cell volume, and thermal expansion coefficients were determined successfully.

Evaluation of friction heating in cavitating high pressure Diesel injector nozzles

NASA Astrophysics Data System (ADS)

Salemi, R.; Koukouvinis, P.; Strotos, G.; McDavid, R.; Wang, Lifeng; Li, Jason; Marengo, M.; Gavaises, M.

2015-12-01

Variation of fuel properties occurring during extreme fuel pressurisation in Diesel fuel injectors relative to those under atmospheric pressure and room temperature conditions may affect significantly fuel delivery, fuel injection temperature, injector durability and thus engine performance. Indicative results of flow simulations during the full injection event of a Diesel injector are presented. In addition to the Navier-Stokes equations, the enthalpy conservation equation is considered for predicting the fuel temperature. Cavitation is simulated using an Eulerian-Lagrangian cavitation model fully coupled with the flow equations. Compressible bubble dynamics based on the R-P equation also consider thermal effects. Variable fuel properties function of the local pressure and temperature are taken from literature and correspond to a reference so-called summer Diesel fuel. Fuel pressurisation up to 3000bar pressure is considered while various wall temperature boundary conditions are tested in order to compare their effect relative to those of the fuel heating caused during the depressurisation of the fuel as it passes through the injection orifices. The results indicate formation of strong temperature gradients inside the fuel injector while heating resulting from the extreme friction may result to local temperatures above the fuel's boiling point. Predictions indicate bulk fuel temperature increase of more than 100°C during the opening phase of the needle valve. Overall, it is concluded that such effects are significant for the injector performance and should be considered in relevant simulation tools.

A quantum chemistry study on surface reactivity of pristine and carbon-substituted AlN nanotubes

NASA Astrophysics Data System (ADS)

Mahdaviani, Amir; Esrafili, Mehdi D.; Esrafili, Ali; Behzadi, Hadi

2013-09-01

A density functional theory investigation was performed to predict the surface reactivity of pristine and carbon-substituted (6,0) single-walled aluminum nitride nanotubes (AlNNTs). The properties determined include the electrostatic potentials VS(r) and average local ionization energies ĪS(r) on the surfaces of the investigated tubes. According to computed VS(r) results, the Al/N atoms in edge or cap regions show a different reactivity pattern than those at the middle portion of the tubes. Due to the carbon-substitution at the either Al or N sites of the tubes, the negative regions associated with nitrogen atoms are stronger than before. The prediction of surface reactivity and regioselectivity using average local ionization energies has been verified by atomic hydrogen chemisorption energies calculated for AlNNTs at the B3LYP/6-31 G* level. There is an acceptable correlation between the minima of ĪS(r) and the atomic hydrogen chemisorption energies, demonstrating that ĪS(r) provides an effective means for rapidly and economically assessing the relative reactivities of finite sized AlNNTs.

Flood-tracking chart for the Withlacoochee and Little River Basins in south-central Georgia and northern Florida

USGS Publications Warehouse

Gotvald, Anthony J.; McCallum, Brian E.; Painter, Jaime A.

2014-01-01

The U.S. Geological Survey (USGS), in cooperation with other Federal, State, and local agencies, operates a flood-monitoring system in the Withlacoochee and Little River Basins. This system is a network of automated river stage stations (ten are shown on page 2 of this publication) that transmit stage data through satellite telemetry to the USGS in Atlanta, Georgia and the National Weather Service (NWS) in Peachtree City, Georgia. During floods, the public and emergency response agencies use this information to make decisions about road closures, evacuations, and other public safety issues. This Withlacoochee and Little River Basins flood-tracking chart can be used by local citizens and emergency response personnel to record the latest river stage and predicted flood-crest information along the Withlacoochee River, Little River, and Okapilco Creek in south-central Georgia and northern Florida. By comparing the current stage (water-surface level above a datum) and predicted flood crest to the recorded peak stages of previous floods, emergency response personnel and residents can make informed decisions concerning the threat to life and property.

Last Glacial loess in the conterminous USA

USGS Publications Warehouse

Bettis, E. Arthur; Muhs, Daniel R.; Roberts, Helen M.; Wintle, Ann G.

2003-01-01

The conterminous United States contains an extensive and generally well-studied record of Last Glacial loess. The loess occurs in diverse physiographic provinces, and under a wide range of climatic and ecological conditions. Both glacial and non-glacia lloess sources are present, and many properties of the loess vary systematically with distance from loess sources. United States' mid-continent Last Glacial loess is probably the thickest in the world, and our calculated mass accumulation rates (MARs) are as high as 17,500 g/m2/yr at the Bignell Hill locality in Nebraska, and many near-source localities have MARs greater than 1500 g/m2/yr. These MARs are high relative to rates calculated in other loess provinces around the world. Recent models of LastGlacial dust sources fail to predict the extent and magnitude of dust flux from the mid-continent of the United States. A better understanding of linkages between climate, ice sheet behaviour, routing of glacial meltwater, land surface processes beyond the ice margin, and vegetation is needed to improve the predictive capabilities of models simulating dust flux from this region.

Presurgery resting-state local graph-theory measures predict neurocognitive outcomes after brain surgery in temporal lobe epilepsy.

PubMed

Doucet, Gaelle E; Rider, Robert; Taylor, Nathan; Skidmore, Christopher; Sharan, Ashwini; Sperling, Michael; Tracy, Joseph I

2015-04-01

This study determined the ability of resting-state functional connectivity (rsFC) graph-theory measures to predict neurocognitive status postsurgery in patients with temporal lobe epilepsy (TLE) who underwent anterior temporal lobectomy (ATL). A presurgical resting-state functional magnetic resonance imaging (fMRI) condition was collected in 16 left and 16 right TLE patients who underwent ATL. In addition, patients received neuropsychological testing pre- and postsurgery in verbal and nonverbal episodic memory, language, working memory, and attention domains. Regarding the functional data, we investigated three graph-theory properties (local efficiency, distance, and participation), measuring segregation, integration and centrality, respectively. These measures were only computed in regions of functional relevance to the ictal pathology, or the cognitive domain. Linear regression analyses were computed to predict the change in each neurocognitive domain. Our analyses revealed that cognitive outcome was successfully predicted with at least 68% of the variance explained in each model, for both TLE groups. The only model not significantly predictive involved nonverbal episodic memory outcome in right TLE. Measures involving the healthy hippocampus were the most common among the predictors, suggesting that enhanced integration of this structure with the rest of the brain may improve cognitive outcomes. Regardless of TLE group, left inferior frontal regions were the best predictors of language outcome. Working memory outcome was predicted mostly by right-sided regions, in both groups. Overall, the results indicated our integration measure was the most predictive of neurocognitive outcome. In contrast, our segregation measure was the least predictive. This study provides evidence that presurgery rsFC measures may help determine neurocognitive outcomes following ATL. The results have implications for refining our understanding of compensatory reorganization and predicting cognitive outcome after ATL. The results are encouraging with regard to the clinical relevance of using graph-theory measures in presurgical algorithms in the setting of TLE. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.

The Predictive Capability of Conditioned Simulation of Discrete Fracture Networks using Structural and Hydraulic Data from the ONKALO Underground Research Facility, Finland

NASA Astrophysics Data System (ADS)

Williams, T. R. N.; Baxter, S.; Hartley, L.; Appleyard, P.; Koskinen, L.; Vanhanarkaus, O.; Selroos, J. O.; Munier, R.

2017-12-01

Discrete fracture network (DFN) models provide a natural analysis framework for rock conditions where flow is predominately through a series of connected discrete features. Mechanistic models to predict the structural patterns of networks are generally intractable due to inherent uncertainties (e.g. deformation history) and as such fracture characterisation typically involves empirical descriptions of fracture statistics for location, intensity, orientation, size, aperture etc. from analyses of field data. These DFN models are used to make probabilistic predictions of likely flow or solute transport conditions for a range of applications in underground resource and construction projects. However, there are many instances when the volumes in which predictions are most valuable are close to data sources. For example, in the disposal of hazardous materials such as radioactive waste, accurate predictions of flow-rates and network connectivity around disposal areas are required for long-term safety evaluation. The problem at hand is thus: how can probabilistic predictions be conditioned on local-scale measurements? This presentation demonstrates conditioning of a DFN model based on the current structural and hydraulic characterisation of the Demonstration Area at the ONKALO underground research facility. The conditioned realisations honour (to a required level of similarity) the locations, orientations and trace lengths of fractures mapped on the surfaces of the nearby ONKALO tunnels and pilot drillholes. Other data used as constraints include measurements from hydraulic injection tests performed in pilot drillholes and inflows to the subsequently reamed experimental deposition holes. Numerical simulations using this suite of conditioned DFN models provides a series of prediction-outcome exercises detailing the reliability of the DFN model to make local-scale predictions of measured geometric and hydraulic properties of the fracture system; and provides an understanding of the reduction in uncertainty in model predictions for conditioned DFN models honouring different aspects of this data.

Strong anticipation and long-range cross-correlation: Application of detrended cross-correlation analysis to human behavioral data

NASA Astrophysics Data System (ADS)

Delignières, Didier; Marmelat, Vivien

2014-01-01

In this paper, we analyze empirical data, accounting for coordination processes between complex systems (bimanual coordination, interpersonal coordination, and synchronization with a fractal metronome), by using a recently proposed method: detrended cross-correlation analysis (DCCA). This work is motivated by the strong anticipation hypothesis, which supposes that coordination between complex systems is not achieved on the basis of local adaptations (i.e., correction, predictions), but results from a more global matching of complexity properties. Indeed, recent experiments have evidenced a very close correlation between the scaling properties of the series produced by two coordinated systems, despite a quite weak local synchronization. We hypothesized that strong anticipation should result in the presence of long-range cross-correlations between the series produced by the two systems. Results allow a detailed analysis of the effects of coordination on the fluctuations of the series produced by the two systems. In the long term, series tend to present similar scaling properties, with clear evidence of long-range cross-correlation. Short-term results strongly depend on the nature of the task. Simulation studies allow disentangling the respective effects of noise and short-term coupling processes on DCCA results, and suggest that the matching of long-term fluctuations could be the result of short-term coupling processes.

Multi-Spectral Cloud Retrievals from Moderate Image Spectrometer (MODIS)

NASA Technical Reports Server (NTRS)

Platnick, Steven

2004-01-01

MODIS observations from the NASA EOS Terra spacecraft (1030 local time equatorial sun-synchronous crossing) launched in December 1999 have provided a unique set of Earth observation data. With the launch of the NASA EOS Aqua spacecraft (1330 local time crossing! in May 2002: two MODIS daytime (sunlit) and nighttime observations are now available in a 24-hour period allowing some measure of diurnal variability. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate modeling, climate change studies, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. An overview of the instrument and cloud algorithms will be presented along with various examples, including an initial analysis of several operational global gridded (Level-3) cloud products from the two platforms. Statistics of cloud optical and microphysical properties as a function of latitude for land and Ocean regions will be shown. Current algorithm research efforts will also be discussed.

Epidemic Process over the Commute Network in a Metropolitan Area

PubMed Central

Yashima, Kenta; Sasaki, Akira

2014-01-01

An understanding of epidemiological dynamics is important for prevention and control of epidemic outbreaks. However, previous studies tend to focus only on specific areas, indicating that application to another area or intervention strategy requires a similar time-consuming simulation. Here, we study the epidemic dynamics of the disease-spread over a commute network, using the Tokyo metropolitan area as an example, in an attempt to elucidate the general properties of epidemic spread over a commute network that could be used for a prediction in any metropolitan area. The model is formulated on the basis of a metapopulation network in which local populations are interconnected by actual commuter flows in the Tokyo metropolitan area and the spread of infection is simulated by an individual-based model. We find that the probability of a global epidemic as well as the final epidemic sizes in both global and local populations, the timing of the epidemic peak, and the time at which the epidemic reaches a local population are mainly determined by the joint distribution of the local population sizes connected by the commuter flows, but are insensitive to geographical or topological structure of the network. Moreover, there is a strong relation between the population size and the time that the epidemic reaches this local population and we are able to determine the reason for this relation as well as its dependence on the commute network structure and epidemic parameters. This study shows that the model based on the connection between the population size classes is sufficient to predict both global and local epidemic dynamics in metropolitan area. Moreover, the clear relation of the time taken by the epidemic to reach each local population can be used as a novel measure for intervention; this enables efficient intervention strategies in each local population prior to the actual arrival. PMID:24905831

Correlation between the band gap expansion and melting temperature depression of nanostructured semiconductors

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

Li, Jianwei, E-mail: jwl189@163.com; Zhao, Xinsheng; Liu, Xinjuan

The band gap and melting temperature of a semiconductor are tunable with the size and shape of the specimen at the nanometer scale, and related mechanisms remain as yet unclear. In order to understand the common origin of the size and shape effect on these two seemingly irrelevant properties, we clarify, correlate, formulate, and quantify these two properties of GaAs, GaN, InP, and InN nanocrystals from the perspectives of bond order-length-strength correlation using the core-shell configuration. The consistency in the theoretical predictions, experimental observations, and numerical calculations verify that the broken-bond-induced local bond contraction and strength gain dictates the bandmore » gap expansion, while the atomic cohesive energy loss due to bond number reduction depresses the melting point. The fraction of the under-coordinated atoms in the skin shell quantitatively determines the shape and size dependency. The atomic under-coordination in the skin down to a depth of two atomic layers inducing a change in the local chemical bond is the common physical origin.« less

Structure and stability of CaH 2 surfaces: on the possibility of electron-rich surfaces in metal hydrides for catalysis

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

Ong, Phuong-Vu; Johnson, Lewis E.; Hosono, Hideo

Structure, thermodynamic stability, and electronic properties of CaH 2 surfaces in (001),(110), and (111) crystallographic orientations are investigated using ab initio modeling. We show that stoichiometric surfaces terminated with a hydrogen atomic plane are the most energetically favorable and discuss properties of hydrogen vacancies (VH) at these surfaces. The average calculated work function of the most stable pristine surfaces (~5.2 eV) is in agree-ment with experimental data for powder samples. Neutral hydrogen vacancies host localized electrons and induce defect states in the band gap, thereby shifting the effective work function to much lower values of ~2.7 eV. Surface VH aremore » predicted to aggregate into dimers and form electron-rich centers (e -)Ca 2+(e -) stable to over 800 K. These results suggest that hydrogen-deficient surfaces of CaH 2 can host a large concentration of localized electrons and, thus, give rise to new catalytic functionalities involving electron transfer between the surface, catalysts supported on it, and reacting species.« less

Machine learning of molecular properties: Locality and active learning

NASA Astrophysics Data System (ADS)

Gubaev, Konstantin; Podryabinkin, Evgeny V.; Shapeev, Alexander V.

2018-06-01

In recent years, the machine learning techniques have shown great potent1ial in various problems from a multitude of disciplines, including materials design and drug discovery. The high computational speed on the one hand and the accuracy comparable to that of density functional theory on another hand make machine learning algorithms efficient for high-throughput screening through chemical and configurational space. However, the machine learning algorithms available in the literature require large training datasets to reach the chemical accuracy and also show large errors for the so-called outliers—the out-of-sample molecules, not well-represented in the training set. In the present paper, we propose a new machine learning algorithm for predicting molecular properties that addresses these two issues: it is based on a local model of interatomic interactions providing high accuracy when trained on relatively small training sets and an active learning algorithm of optimally choosing the training set that significantly reduces the errors for the outliers. We compare our model to the other state-of-the-art algorithms from the literature on the widely used benchmark tests.

Indenting a Thin Floating Film: Force and First-fold Formation

NASA Astrophysics Data System (ADS)

Ripp, Monica; Paulsen, Joseph

2017-11-01

When a thin elastic sheet is gently pushed into a liquid bath, a pattern of radial wrinkles is generated where the film is locally compressed. Despite the simplicity of this setting, basic questions remain about the mechanics and morphology of indented thin films. Recent work shows that traditional post-buckling analysis must be supplanted with an analysis where wrinkles completely relax compressive stresses. Support for this ``far-from-threshold'' theory has been built on measurements of wrinkle extent and wavelength, but direct force measurements have been absent. Here we measure the force response of floating ultrathin ( 100 nm) polystyrene films in indentation experiments. Our measurements are in good agreement with recent predictions for two regimes of poking: Early on force depends on film properties (thickness and Young's modulus) and later is independent of film properties, simply transferring forces from the substrate (gravity and surface tension) to the poker. At larger indentations compression localizes into a single fold. We present scaling arguments and experiments that show the existing model of this transition must be modified. NSF IGERT, NSF CAREER.

Chromatic patchy particles: Effects of specific interactions on liquid structure

DOE PAGES

Vasilyev, Oleg A.; Tkachenko, Alexei V.; Klumov, Boris A.

2015-07-13

We study the structural and thermodynamic properties of patchy particle liquids, with a special focus on the role of “color,” i.e., specific interactions between individual patches. A possible experimental realization of such “chromatic” interactions is by decorating the particle patches with single-stranded DNA linkers. The complementarity of the linkers can promote selective bond formation between predetermined pairs of patches. By using MD simulations, we compare the local connectivity, the bond orientation order, and other structural properties of the aggregates formed by the “colored” and “colorless” systems. The analysis is done for spherical particles with two different patch arrangements (tetrahedral andmore » cubic). It is found that the aggregated (liquid) phase of the “colorless” patchy particles is better connected, denser and typically has stronger local order than the corresponding “colored” one. This, in turn, makes the colored liquid less stable thermodynamically. Specifically, we predict that in a typical case the chromatic interactions should increase the relative stability of the crystalline phase with respect to the disordered liquid, thus expanding its region in the phase diagram.« less

Network-based model of the growth of termite nests

NASA Astrophysics Data System (ADS)

Eom, Young-Ho; Perna, Andrea; Fortunato, Santo; Darrouzet, Eric; Theraulaz, Guy; Jost, Christian

2015-12-01

We present a model for the growth of the transportation network inside nests of the social insect subfamily Termitinae (Isoptera, termitidae). These nests consist of large chambers (nodes) connected by tunnels (edges). The model based on the empirical analysis of the real nest networks combined with pruning (edge removal, either random or weighted by betweenness centrality) and a memory effect (preferential growth from the latest added chambers) successfully predicts emergent nest properties (degree distribution, size of the largest connected component, average path lengths, backbone link ratios, and local graph redundancy). The two pruning alternatives can be associated with different genuses in the subfamily. A sensitivity analysis on the pruning and memory parameters indicates that Termitinae networks favor fast internal transportation over efficient defense strategies against ant predators. Our results provide an example of how complex network organization and efficient network properties can be generated from simple building rules based on local interactions and contribute to our understanding of the mechanisms that come into play for the formation of termite networks and of biological transportation networks in general.

Business Centre Development Model of Airport Area in Supporting Airport Sustainability in Indonesia

NASA Astrophysics Data System (ADS)

Setiawan, MI; Surjokusumo, S.; Ma'soem, DM; Johan, J.; Hasyim, C.; Kurniasih, N.; Sukoco, A.; Dhaniarti, I.; Suyono, J.; Sudapet, IN; Nasihien, RD; Mudjanarko, SW; Wulandari, A.; Ahmar, Ansari S.; Wajdi, MBN

2018-01-01

Airport is expected to play the role in enhancing the economic level of the region, especially the local people around the airport. The Aero City concept in developing an airport might also develop a city centreed in the airport that combining airport oriented business development, business actors and local people around the airport area. This study aims to generate development model of business centre at the airports in Indonesia. This is a mixed method based study. The population includes 296 airports under government management, government subsidiary and military. By using stratified random sampling, there were 151 sample airports. The results show that business centre development in the airport area will be related with the airport management and the commercial property (business centre) growth at the airport. Aero City in Indonesia can be developed by partnership system between government and private sector that consists of construction, development, and implementation of commercial property such as hotel, apartment, retail, office, etc. Based on the result of T-Value test, Airport Performance variable predicted to have significant influence on Gross Regional Domestic Product Central Business District performance.

Mapping Plant Diversity and Composition Across North Carolina Piedmont Forest Landscapes Using Lidar-Hyperspectral Remote Sensing

NASA Astrophysics Data System (ADS)

Hakkenberg, Christopher R.

Forest modification, from local stress to global change, has given rise to efforts to model, map, and monitor critical properties of forest communities like structure, composition, and diversity. Predictive models based on data from spatially-nested field plots and LiDAR-hyperspectral remote sensing systems are one particularly effective means towards the otherwise prohibitively resource-intensive task of consistently characterizing forest community dynamics at landscape scales. However, to date, most predictive models fail to account for actual (rather than idealized) species and community distributions, are unsuccessful in predicting understory components in structurally and taxonomically heterogeneous forests, and may suffer from diminished predictive accuracy due to incongruity in scale and precision between field plot samples, remotely-sensed data, and target biota of varying size and density. This three-part study addresses these and other concerns in the modeling and mapping of emergent properties of forest communities by shifting the scope of prediction from the individual or taxon to the whole stand or community. It is, after all, at the stand scale where emergent properties like functional processes, biodiversity, and habitat aggregate and manifest. In the first study, I explore the relationship between forest structure (a proxy for successional demographics and resource competition) and tree species diversity in the North Carolina Piedmont, highlighting the empirical basis and potential for utilizing forest structure from LiDAR in predictive models of tree species diversity. I then extend these conclusions to map landscape pattern in multi-scale vascular plant diversity as well as turnover in community-continua at varying compositional resolutions in a North Carolina Piedmont landscape using remotely-sensed LiDAR-hyperspectral estimates of topography, canopy structure, and foliar biochemistry. Recognizing that the distinction between correlation and causation mirrors that between knowledge and understanding, all three studies distinguish between prediction of pattern and inference of process. Thus, in addition to advancing mapping methodologies relevant to a range of forest ecosystem management and monitoring applications, all three studies are noteworthy for assessing the ecological relationship between environmental predictors and emergent landscape patterns in plant composition and diversity in North Carolina Piedmont forests.

ACE phenotyping in human heart.

PubMed

Tikhomirova, Victoria E; Kost, Olga A; Kryukova, Olga V; Golukhova, Elena Z; Bulaeva, Naida I; Zholbaeva, Aigerim Z; Bokeria, Leo A; Garcia, Joe G N; Danilov, Sergei M

2017-01-01

Angiotensin-converting enzyme (ACE), which metabolizes many peptides and plays a key role in blood pressure regulation and vascular remodeling, is expressed as a type-1 membrane glycoprotein on the surface of different cells, including endothelial cells of the heart. We hypothesized that the local conformation and, therefore, the properties of heart ACE could differ from lung ACE due to different microenvironment in these organs. We performed ACE phenotyping (ACE levels, conformation and kinetic characteristics) in the human heart and compared it with that in the lung. ACE activity in heart tissues was 10-15 lower than that in lung. Various ACE effectors, LMW endogenous ACE inhibitors and HMW ACE-binding partners, were shown to be present in both heart and lung tissues. "Conformational fingerprint" of heart ACE (i.e., the pattern of 17 mAbs binding to different epitopes on the ACE surface) significantly differed from that of lung ACE, which reflects differences in the local conformations of these ACEs, likely controlled by different ACE glycosylation in these organs. Substrate specificity and pH-optima of the heart and lung ACEs also differed. Moreover, even within heart the apparent ACE activities, the local ACE conformations, and the content of ACE inhibitors differ in atria and ventricles. Significant differences in the local conformations and kinetic properties of heart and lung ACEs demonstrate tissue specificity of ACE and provide a structural base for the development of mAbs able to distinguish heart and lung ACEs as a potential blood test for predicting atrial fibrillation risk.

Local thermal energy as a structural indicator in glasses.

PubMed

Zylberg, Jacques; Lerner, Edan; Bar-Sinai, Yohai; Bouchbinder, Eran

2017-07-11

Identifying heterogeneous structures in glasses-such as localized soft spots-and understanding structure-dynamics relations in these systems remain major scientific challenges. Here, we derive an exact expression for the local thermal energy of interacting particles (the mean local potential energy change caused by thermal fluctuations) in glassy systems by a systematic low-temperature expansion. We show that the local thermal energy can attain anomalously large values, inversely related to the degree of softness of localized structures in a glass, determined by a coupling between internal stresses-an intrinsic signature of glassy frustration-anharmonicity and low-frequency vibrational modes. These anomalously large values follow a fat-tailed distribution, with a universal exponent related to the recently observed universal [Formula: see text] density of states of quasilocalized low-frequency vibrational modes. When the spatial thermal energy field-a "softness field"-is considered, this power law tail manifests itself by highly localized spots, which are significantly softer than their surroundings. These soft spots are shown to be susceptible to plastic rearrangements under external driving forces, having predictive powers that surpass those of the normal modes-based approach. These results offer a general, system/model-independent, physical/observable-based approach to identify structural properties of quiescent glasses and relate them to glassy dynamics.

Local active information storage as a tool to understand distributed neural information processing

PubMed Central

Wibral, Michael; Lizier, Joseph T.; Vögler, Sebastian; Priesemann, Viola; Galuske, Ralf

2013-01-01

Every act of information processing can in principle be decomposed into the component operations of information storage, transfer, and modification. Yet, while this is easily done for today's digital computers, the application of these concepts to neural information processing was hampered by the lack of proper mathematical definitions of these operations on information. Recently, definitions were given for the dynamics of these information processing operations on a local scale in space and time in a distributed system, and the specific concept of local active information storage was successfully applied to the analysis and optimization of artificial neural systems. However, no attempt to measure the space-time dynamics of local active information storage in neural data has been made to date. Here we measure local active information storage on a local scale in time and space in voltage sensitive dye imaging data from area 18 of the cat. We show that storage reflects neural properties such as stimulus preferences and surprise upon unexpected stimulus change, and in area 18 reflects the abstract concept of an ongoing stimulus despite the locally random nature of this stimulus. We suggest that LAIS will be a useful quantity to test theories of cortical function, such as predictive coding. PMID:24501593

A local leaky-box model for the local stellar surface density-gas surface density-gas phase metallicity relation

NASA Astrophysics Data System (ADS)

Zhu, Guangtun Ben; Barrera-Ballesteros, Jorge K.; Heckman, Timothy M.; Zakamska, Nadia L.; Sánchez, Sebastian F.; Yan, Renbin; Brinkmann, Jonathan

2017-07-01

We revisit the relation between the stellar surface density, the gas surface density and the gas-phase metallicity of typical disc galaxies in the local Universe with the SDSS-IV/MaNGA survey, using the star formation rate surface density as an indicator for the gas surface density. We show that these three local parameters form a tight relationship, confirming previous works (e.g. by the PINGS and CALIFA surveys), but with a larger sample. We present a new local leaky-box model, assuming star-formation history and chemical evolution is localized except for outflowing materials. We derive closed-form solutions for the evolution of stellar surface density, gas surface density and gas-phase metallicity, and show that these parameters form a tight relation independent of initial gas density and time. We show that, with canonical values of model parameters, this predicted relation match the observed one well. In addition, we briefly describe a pathway to improving the current semi-analytic models of galaxy formation by incorporating the local leaky-box model in the cosmological context, which can potentially explain simultaneously multiple properties of Milky Way-type disc galaxies, such as the size growth and the global stellar mass-gas metallicity relation.

Predicted persistence and response times of linear and cyclic volatile methylsiloxanes in global and local environments.

PubMed

Kim, Jaeshin; Mackay, Donald; Whelan, Michael John

2018-03-01

We investigated the response times of eight volatile methylsiloxanes (VMSs) in environmental systems at different scales from local to global, with a particular focus on overall loss rates after cessation of emissions. In part, this is driven by proposals to restrict the use of some of these compounds in certain products in Europe. The GloboPOP model estimated low absolute Arctic Contamination Potentials for all VMSs and rapid response times in all media except sediment. VMSs are predicted to be distributed predominantly in air where they react with OH radicals, leading to short response times. After cessation of emissions VMSs concentrations in the environment are expected to decrease rapidly from current levels. Response times in specific water and sediment systems were evaluated using a dynamic QWASI model. Response times were sensitive to both physico-chemical properties and environmental characteristics. Degradation was predicted to play the most important role in determining response times in water and sediment. In the case of the lowest molecular weight VMSs such as L2 and D3, response times were essentially independent of environmental characteristics due to fast hydrolysis in water and sediment. However, response times for the other VMSs are system-specific. They are relatively short in shallow water bodies but increase with depth due to the diminishing role of volatilization on concentration change as volume to surface area ratio increases. In sediment, degradation and resuspension rates also contribute most to the response times. The estimated response times for local environments are useful for planning future monitoring programs. Copyright © 2017 Elsevier Ltd. All rights reserved.

An instantaneous spatiotemporal model to predict a bicyclist's Black Carbon exposure based on mobile noise measurements

NASA Astrophysics Data System (ADS)

Dekoninck, Luc; Botteldooren, Dick; Int Panis, Luc

2013-11-01

Several studies have shown that a significant amount of daily air pollution exposure, in particular Black Carbon (BC), is inhaled during trips. Assessing this contribution to exposure remains difficult because on the one hand local air pollution maps lack spatio-temporal resolution, at the other hand direct measurement of particulate matter concentration remains expensive. This paper proposes to use in-traffic noise measurements in combination with geographical and meteorological information for predicting BC exposure during commuting trips. Mobile noise measurements are cheaper and easier to perform than mobile air pollution measurements and can easily be used in participatory sensing campaigns. The uniqueness of the proposed model lies in the choice of noise indicators that goes beyond the traditional overall A-weighted noise level used in previous work. Noise and BC exposures are both related to the traffic intensity but also to traffic speed and traffic dynamics. Inspired by theoretical knowledge on the emission of noise and BC, the low frequency engine related noise and the difference between high frequency and low frequency noise that indicates the traffic speed, are introduced in the model. In addition, it is shown that splitting BC in a local and a background component significantly improves the model. The coefficients of the proposed model are extracted from 200 commuter bicycle trips. The predicted average exposure over a single trip correlates with measurements with a Pearson coefficient of 0.78 using only four parameters: the low frequency noise level, wind speed, the difference between high and low frequency noise and a street canyon index expressing local air pollution dispersion properties.

The Star Formation Rate Efficiency of Neutral Atomic-Dominated Hydrogen Gas in the Ooutskirts of Star-Forming Galaxies From z approx. 1 to z approx. 3

NASA Technical Reports Server (NTRS)

Rafelski, Marc; Gardner, Jonathan P.; Fumagalli, Michele; Neeleman, Marcel; Teplitz, Harry I.; Grogin, Norman; Koekemoer, Anton M.; Scarlata, Claudia

2016-01-01

Current observational evidence suggests that the star formation rate (SFR)efficiency of neutral atomic hydrogen gas measured in damped Ly(alpha) systems (DLAs) at z approx. 3 is more than 10 times lower than predicted by the Kennicutt-Schmidt (KS)relation. To understand the origin of this deficit, and to investigate possible evolution with redshift and galaxy properties, we measure the SFR efficiency of atomic gas at z approx. 1, z approx. 2, and z approx. 3 around star-forming galaxies. We use new robust photometric redshifts in the Hubble Ultra Deep Field to create galaxy stacks in these three redshift bins, and measure the SFR efficiency by combining DLA absorber statistics with the observed rest-frame UV emission in the galaxies' outskirts. We find that the SFR efficiency of H I gas at z > 1 is approx. 1%-3% of that predicted by the KS relation. Contrary to simulations and models that predict a reduced SFR efficiency with decreasing metallicity and thus with increasing redshift, we find no significant evolution in the SFR efficiency with redshift. Our analysis instead suggests that the reduced SFR efficiency is driven by the low molecular content of this atomic-dominated phase, with metallicity playing a secondary effect in regulating the conversion between atomic and molecular gas. This interpretation is supported by the similarity between the observed SFR efficiency and that observed in local atomic-dominated gas, such as in the outskirts of local spiral galaxies and local dwarf galaxies.

The Potential Effect of Sea Level Rise on Coastal Property Values

NASA Astrophysics Data System (ADS)

O'Donnell, J.

2015-12-01

It is well established that one consequence of increasing global sea level is that the frequency of flooding at low-lying coastal sites will increase. We review recent evidence that the effects coastal geometry will create substantial spatial variations in the changes in flooding frequency with scales of order 100km. Using a simple model of the evolution of coastal property values we demonstrate that a consequence of sea level rise is that the appreciation of coastal properties will peak, and then decline relative to higher properties. The time when the value reach a maximum is shown to depend upon the demand for the coastal property, and the local rate of change of flooding frequency due to sea level rise. The simple model is then extended to include, in an elementary manner, the effects on the value of adjacent but higher properties. We show that the effect of increased flooding frequency of the lower properties leads to an accelerated appreciation of the value of upland properties and an accelerated decline in the value of the coastal properties. We then provide some example calculations for selected sites. We conclude with a discussion of comparisons of the prediction of the analyses to recent data, and then comments on the impact of sea level rise on tax base of coastal communities.

Effect of pesticide fate parameters and their uncertainty on the selection of 'worst-case' scenarios of pesticide leaching to groundwater.

PubMed

Vanderborght, Jan; Tiktak, Aaldrik; Boesten, Jos J T I; Vereecken, Harry

2011-03-01

For the registration of pesticides in the European Union, model simulations for worst-case scenarios are used to demonstrate that leaching concentrations to groundwater do not exceed a critical threshold. A worst-case scenario is a combination of soil and climate properties for which predicted leaching concentrations are higher than a certain percentile of the spatial concentration distribution within a region. The derivation of scenarios is complicated by uncertainty about soil and pesticide fate parameters. As the ranking of climate and soil property combinations according to predicted leaching concentrations is different for different pesticides, the worst-case scenario for one pesticide may misrepresent the worst case for another pesticide, which leads to 'scenario uncertainty'. Pesticide fate parameter uncertainty led to higher concentrations in the higher percentiles of spatial concentration distributions, especially for distributions in smaller and more homogeneous regions. The effect of pesticide fate parameter uncertainty on the spatial concentration distribution was small when compared with the uncertainty of local concentration predictions and with the scenario uncertainty. Uncertainty in pesticide fate parameters and scenario uncertainty can be accounted for using higher percentiles of spatial concentration distributions and considering a range of pesticides for the scenario selection. Copyright © 2010 Society of Chemical Industry.

Ultrasound Elastography for Estimation of Regional Strain of Multilayered Hydrogels and Tissue-Engineered Cartilage

PubMed Central

Chung, Chen-Yuan; Heebner, Joseph; Baskaran, Harihara; Welter, Jean F.; Mansour, Joseph M.

2015-01-01

Tissue-engineered (TE) cartilage constructs tend to develop inhomogeneously, thus, to predict the mechanical performance of the tissue, conventional biomechanical testing, which yields average material properties, is of limited value. Rather, techniques for evaluating regional and depth-dependent properties of TE cartilage, preferably non-destructively, are required. The purpose of this study was to build upon our previous results and to investigate the feasibility of using ultrasound elastography to non-destructively assess the depth-dependent biomechanical characteristics of TE cartilage while in a sterile bioreactor. As a proof-of-concept, and to standardize an assessment protocol, a well-characterized three-layered hydrogel construct was used as a surrogate for TE cartilage, and was studied under controlled incremental compressions. The strain field of the construct predicted by elastography was then validated by comparison with a poroelastic finite-element analysis (FEA). On average, the differences between the strains predicted by elastography and the FEA were within 10%. Subsequently engineered cartilage tissue was evaluated in the same test fixture. Results from these examinations showed internal regions where the local strain was 1–2 orders of magnitude greater than that near the surface. These studies document the feasibility of using ultrasound to evaluate the mechanical behaviors of maturing TE constructs in a sterile environment. PMID:26077987

DFT Predictions of Electronic, Transport, and Bulk Properties of Cubic Antifluorite A2B Compounds (A = Li, Na, B = O,S,Se)

NASA Astrophysics Data System (ADS)

Malozovsky, Yuriy; Franklin, Lashounda; Bagayoko, Diola

We present results from ab-initio,self-consistent calculations of electronic, transport, and bulk properties of cubic antifluorite (anti-CaF2) compounds A2B (A = Li, Na, B = O, S, Se). Our computations employed the local density approximation (LDA) potential of Ceperley and Alder and the linear combination of atomic orbital (LCAO) formalism. The implementation of the LCAO formalism followed the Bagayoko, Zhao, and Williams method, as enhanced by Ekuma and Franklin (BZW-EF). Consequently, our calculations search for and attained the ground states of the systems under study, as required by DFT; our results therefore possess the full, physical content of DFT. We discuss band structures, band gaps, and related properties of these materials, including calculated, total and partial densities of states (DOS and PDOS), effective masses of charge carriers, equilibrium lattice constants, and the bulk moduli of cubic antifluorite compounds A2B (A = Li, Na, B = O, S, Se). Our results are predictions in some cases, due to the lack of experimental data. Work funded in part by the US Department of Energy (DOE), National Nuclear Security Administration (NNSA) (Award No.DE-NA0002630), the National Science Foundation (NSF) (Award No, 1503226), LaSPACE, and LONI-SUBR.

Synthesis and characterization of (Sn,Zn)O alloys

DOE PAGES

Bikowski, Andre; Holder, Aaron; Peng, Haowei; ...

2016-09-29

SnO exhibits electrical properties that render it promising for solar energy conversion applications, but it also has a strongly indirect band gap. Recent theoretical calculations predict that this disadvantage can be mitigated by isovalent alloying with other group-II oxides such as ZnO. Here, we synthesized new metastable isovalent (Sn,Zn)O alloy thin films by combinatorial reactive co-sputtering and characterized their structural, optical and electrical properties. The alloying of ZnO into SnO leads to a change of the valence state of the tin from Sn 0 via Sn 2+ to Sn 4+, which can be counteracted by reducing the oxygen partial pressuremore » during the deposition. The optical characterization of the smooth <10 at. % Sn 1-xZn xO thin films showed an increase in the absorption coefficient in the range from 1 to 2 eV, which is consistent with the theoretical predictions for the isovalent alloying. However, the experimentally observed alloying effect may be convoluted with the effect of local variations of the Sn oxidation state. As a result, this effect would have to be minimized to improve the (Sn,Zn)O optical and electrical properties for their use as absorbers in solar energy conversion applications.« less

Spatial processing in the auditory cortex of the macaque monkey

NASA Astrophysics Data System (ADS)

Recanzone, Gregg H.

2000-10-01

The patterns of cortico-cortical and cortico-thalamic connections of auditory cortical areas in the rhesus monkey have led to the hypothesis that acoustic information is processed in series and in parallel in the primate auditory cortex. Recent physiological experiments in the behaving monkey indicate that the response properties of neurons in different cortical areas are both functionally distinct from each other, which is indicative of parallel processing, and functionally similar to each other, which is indicative of serial processing. Thus, auditory cortical processing may be similar to the serial and parallel "what" and "where" processing by the primate visual cortex. If "where" information is serially processed in the primate auditory cortex, neurons in cortical areas along this pathway should have progressively better spatial tuning properties. This prediction is supported by recent experiments that have shown that neurons in the caudomedial field have better spatial tuning properties than neurons in the primary auditory cortex. Neurons in the caudomedial field are also better than primary auditory cortex neurons at predicting the sound localization ability across different stimulus frequencies and bandwidths in both azimuth and elevation. These data support the hypothesis that the primate auditory cortex processes acoustic information in a serial and parallel manner and suggest that this may be a general cortical mechanism for sensory perception.

Computational Search for Specific Magnetoelectronic Characteristics

NASA Astrophysics Data System (ADS)

Pickett, Warren E.

1997-08-01

Many aspects of the coupling between magnetic state (ferro- or antiferromagnetic) and the electronic properties of a material can be predicted reliably from local spin density (LSD) calculations. Such calculations are routinely used to interpret data, but so far little actual prediction of new materials has been attempted. We present here the application of LSD methods to look for half-metallic (HM) antiferromagnetic (AFM) compounds. These materials will have unusual properties, such as 100% spin-polarized transport with no net magnetic field, and the possibility of a novel type of superconductivity. The double perovskite crystal structure was chosen, due to some experience with it and its simplicity, and magnetic ions M',M'' were chosen in the expectation that their moments in the La_2M'M''O6 compound would be equal in magnitude and could be induced to align in an antiparallel manner, giving zero total magnetization. Results for six compounds, with magnetic ions chosen from the 3d transition series, will be described. Three HM AFM states have been found, as well as several HM ferromagnetic states.

Prediction of the structure of fuel sprays in gas turbine combustors

NASA Technical Reports Server (NTRS)

Shuen, J. S.

1985-01-01

The structure of fuel sprays in a combustion chamber is theoretically investigated using computer models of current interest. Three representative spray models are considered: (1) a locally homogeneous flow (LHF) model, which assumes infinitely fast interphase transport rates; (2) a deterministic separated flow (DSF) model, which considers finite rates of interphase transport but ignores effects of droplet/turbulence interactions; and (3) a stochastic separated flow (SSF) model, which considers droplet/turbulence interactions using random sampling for turbulence properties in conjunction with random-walk computations for droplet motion and transport. Two flow conditions are studied to investigate the influence of swirl on droplet life histories and the effects of droplet/turbulence interactions on flow properties. Comparison of computed results with the experimental data show that general features of the flow structure can be predicted with reasonable accuracy using the two separated flow models. In contrast, the LHF model overpredicts the rate of development of the flow. While the SSF model provides better agreement with measurements than the DSF model, definitive evaluation of the significance of droplet/turbulence interaction is not achieved due to uncertainties in the spray initial conditions.

Upscaling the diffusion equations in particulate media made of highly conductive particles. I. Theoretical aspects.

PubMed

Vassal, J-P; Orgéas, L; Favier, D; Auriault, J-L; Le Corre, S

2008-01-01

Many analytical and numerical works have been devoted to the prediction of macroscopic effective transport properties in particulate media. Usually, structure and properties of macroscopic balance and constitutive equations are stated a priori. In this paper, the upscaling of the transient diffusion equations in concentrated particulate media with possible particle-particle interfacial barriers, highly conductive particles, poorly conductive matrix, and temperature-dependent physical properties is revisited using the homogenization method based on multiple scale asymptotic expansions. This method uses no a priori assumptions on the physics at the macroscale. For the considered physics and microstructures and depending on the order of magnitude of dimensionless Biot and Fourier numbers, it is shown that some situations cannot be homogenized. For other situations, three different macroscopic models are identified, depending on the quality of particle-particle contacts. They are one-phase media, following the standard heat equation and Fourier's law. Calculations of the effective conductivity tensor and heat capacity are proved to be uncoupled. Linear and steady state continuous localization problems must be solved on representative elementary volumes to compute the effective conductivity tensors for the two first models. For the third model, i.e., for highly resistive contacts, the localization problem becomes simpler and discrete whatever the shape of particles. In paper II [Vassal, Phys. Rev. E 77, 011303 (2008)], diffusion through networks of slender, wavy, entangled, and oriented fibers is considered. Discrete localization problems can then be obtained for all models, as well as semianalytical or fully analytical expressions of the corresponding effective conductivity tensors.

A Framework for Local Mechanical Characterization of Atherosclerotic Plaques: Combination of Ultrasound Displacement Imaging and Inverse Finite Element Analysis.

PubMed

Akyildiz, Ali C; Hansen, Hendrik H G; Nieuwstadt, Harm A; Speelman, Lambert; De Korte, Chris L; van der Steen, Antonius F W; Gijsen, Frank J H

2016-04-01

Biomechanical models have the potential to predict plaque rupture. For reliable models, correct material properties of plaque components are a prerequisite. This study presents a new technique, where high resolution ultrasound displacement imaging and inverse finite element (FE) modeling is combined, to estimate material properties of plaque components. Iliac arteries with plaques were excised from 6 atherosclerotic pigs and subjected to an inflation test with pressures ranging from 10 to 120 mmHg. The arteries were imaged with high frequency 40 MHz ultrasound. Deformation maps of the plaques were reconstructed by cross correlation of the ultrasound radiofrequency data. Subsequently, the arteries were perfusion fixed for histology and structural components were identified. The histological data were registered to the ultrasound data to construct FE model of the plaques. Material properties of the arterial wall and the intima of the atherosclerotic plaques were estimated using a grid search method. The computed displacement fields showed good agreement with the measured displacement fields, implying that the FE models were able to capture local inhomogeneities within the plaque. On average, nonlinear stiffening of both the wall and the intima was observed, and the wall of the atheroslcerotic porcine iliac arteries was markedly stiffer than the intima (877 ± 459 vs. 100 ± 68 kPa at 100 mmHg). The large spread in the data further illustrates the wide variation of the material properties. We demonstrated the feasibility of a mixed experimental-numerical framework to determine the material properties of arterial wall and intima of atherosclerotic plaques from intact arteries, and concluded that, due to the observed variation, plaque specific properties are required for accurate stress simulations.

Modeling Biophysical and Biological Properties From the Characteristics of the Molecular Electron Density, Electron Localization and Delocalization Matrices, and the Electrostatic Potential

PubMed Central

Matta*, Chérif F

2014-01-01

The electron density and the electrostatic potential are fundamentally related to the molecular hamiltonian, and hence are the ultimate source of all properties in the ground- and excited-states. The advantages of using molecular descriptors derived from these fundamental scalar fields, both accessible from theory and from experiment, in the formulation of quantitative structure-to-activity and structure-to-property relationships, collectively abbreviated as QSAR, are discussed. A few such descriptors encode for a wide variety of properties including, for example, electronic transition energies, pKa's, rates of ester hydrolysis, NMR chemical shifts, DNA dimers binding energies, π-stacking energies, toxicological indices, cytotoxicities, hepatotoxicities, carcinogenicities, partial molar volumes, partition coefficients (log P), hydrogen bond donor capacities, enzyme–substrate complementarities, bioisosterism, and regularities in the genetic code. Electronic fingerprinting from the topological analysis of the electron density is shown to be comparable and possibly superior to Hammett constants and can be used in conjunction with traditional bulk and liposolubility descriptors to accurately predict biological activities. A new class of descriptors obtained from the quantum theory of atoms in molecules' (QTAIM) localization and delocalization indices and bond properties, cast in matrix format, is shown to quantify transferability and molecular similarity meaningfully. Properties such as “interacting quantum atoms (IQA)” energies which are expressible into an interaction matrix of two body terms (and diagonal one body “self” terms, as IQA energies) can be used in the same manner. The proposed QSAR-type studies based on similarity distances derived from such matrix representatives of molecular structure necessitate extensive investigation before their utility is unequivocally established. © 2014 The Author and the Journal of Computational Chemistry Published by Wiley Periodicals, Inc. PMID:24777743

Spatial and temporal variations of aerosols around Beijing in summer 2006: 2. Local and column aerosol optical properties

NASA Astrophysics Data System (ADS)

Matsui, H.; Koike, M.; Kondo, Y.; Takegawa, N.; Fast, J. D.; PöSchl, U.; Garland, R. M.; Andreae, M. O.; Wiedensohler, A.; Sugimoto, N.; Zhu, T.

2010-11-01

Model calculations were conducted using the Weather Research and Forecasting model coupled with chemistry (WRF-chem) for the region around Beijing, China, in the summer of 2006, when the CAREBeijing-2006 intensive campaign was conducted. In this paper, we interpret aerosol optical properties in terms of aerosol mass concentrations and their chemical compositions by linking model calculations with measurements. The model calculations generally captured the observed variability of various surface and column aerosol optical parameters in and around Beijing. At the surface, the spatial and temporal variations of aerosol absorption and scattering coefficients corresponded well to those of elemental carbon and sulfate mass concentrations, respectively, and were controlled by local-scale (<100 km and <24 hours) and regional-scale (<500 km and <3 days) emissions, respectively. The contribution of secondary aerosols and their water uptake increased with altitude within the planetary boundary layer. This variation led to a considerable increase in column aerosol optical depth and was responsible for the differences in regional and temporal variations between surface and column aerosol optical properties around Beijing. These processes are expected to be common in other megacity regions as well. Model calculations, however, underestimated or overestimated the absolute levels of aerosol optical properties in and around Beijing by up to 60%. Sensitivity studies showed that these discrepancies were mostly due to the uncertainties in aerosol mixing state and aerosol density (affecting mass extinction efficiency) in the model calculations. Good agreement with measurements is achieved when these aerosol properties are accurately predicted or assumed; however, significant bias can result when these properties are inadequately treated, even if total aerosol mass concentrations are reproduced well in the model calculations.

Should coastal planners have concern over where land ice is melting?

PubMed Central

Larour, Eric; Ivins, Erik R.; Adhikari, Surendra

2017-01-01

There is a general consensus among Earth scientists that melting of land ice greatly contributes to sea-level rise (SLR) and that future warming will exacerbate the risks posed to human civilization. As land ice is lost to the oceans, both the Earth’s gravitational and rotational potentials are perturbed, resulting in strong spatial patterns in SLR, termed sea-level fingerprints. We lack robust forecasting models for future ice changes, which diminishes our ability to use these fingerprints to accurately predict local sea-level (LSL) changes. We exploit an advanced mathematical property of adjoint systems and determine the exact gradient of sea-level fingerprints with respect to local variations in the ice thickness of all of the world’s ice drainage systems. By exhaustively mapping these fingerprint gradients, we form a new diagnosis tool, henceforth referred to as gradient fingerprint mapping (GFM), that readily allows for improved assessments of future coastal inundation or emergence. We demonstrate that for Antarctica and Greenland, changes in the predictions of inundation at major port cities depend on the location of the drainage system. For example, in London, GFM shows LSL that is significantly affected by changes on the western part of the Greenland Ice Sheet (GrIS), whereas in New York, LSL change predictions are greatly sensitive to changes in the northeastern portions of the GrIS. We apply GFM to 293 major port cities to allow coastal planners to readily calculate LSL change as more reliable predictions of cryospheric mass changes become available. PMID:29152565

Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data

NASA Astrophysics Data System (ADS)

Leonarduzzi, Elena; Molnar, Peter; McArdell, Brian W.

2017-08-01

A high-resolution gridded daily precipitation data set was combined with a landslide inventory containing over 2000 events in the period 1972-2012 to analyze rainfall thresholds which lead to landsliding in Switzerland. We colocated triggering rainfall to landslides, developed distributions of triggering and nontriggering rainfall event properties, and determined rainfall thresholds and intensity-duration ID curves and validated their performance. The best predictive performance was obtained by the intensity-duration ID threshold curve, followed by peak daily intensity Imax and mean event intensity Imean. Event duration by itself had very low predictive power. A single country-wide threshold of Imax = 28 mm/d was extended into space by regionalization based on surface erodibility and local climate (mean daily precipitation). It was found that wetter local climate and lower erodibility led to significantly higher rainfall thresholds required to trigger landslides. However, we showed that the improvement in model performance due to regionalization was marginal and much lower than what can be achieved by having a high-quality landslide database. Reference cases in which the landslide locations and timing were randomized and the landslide sample size was reduced showed the sensitivity of the Imax rainfall threshold model. Jack-knife and cross-validation experiments demonstrated that the model was robust. The results reported here highlight the potential of using rainfall ID threshold curves and rainfall threshold values for predicting the occurrence of landslides on a country or regional scale with possible applications in landslide warning systems, even with daily data.

Further evaluation of quantitative structure--activity relationship models for the prediction of the skin sensitization potency of selected fragrance allergens.

PubMed

Patlewicz, Grace Y; Basketter, David A; Pease, Camilla K Smith; Wilson, Karen; Wright, Zoe M; Roberts, David W; Bernard, Guillaume; Arnau, Elena Giménez; Lepoittevin, Jean-Pierre

2004-02-01

Fragrance substances represent a very diverse group of chemicals; a proportion of them are associated with the ability to cause allergic reactions in the skin. Efforts to find substitute materials are hindered by the need to undertake animal testing for determining both skin sensitization hazard and potency. One strategy to avoid such testing is through an understanding of the relationships between chemical structure and skin sensitization, so-called structure-activity relationships. In recent work, we evaluated 2 groups of fragrance chemicals -- saturated aldehydes and alpha,beta-unsaturated aldehydes. Simple quantitative structure-activity relationship (QSAR) models relating the EC3 values [derived from the local lymph node assay (LLNA)] to physicochemical properties were developed for both sets of aldehydes. In the current study, we evaluated an additional group of carbonyl-containing compounds to test the predictive power of the developed QSARs and to extend their scope. The QSAR models were used to predict EC3 values of 10 newly selected compounds. Local lymph node assay data generated for these compounds demonstrated that the original QSARs were fairly accurate, but still required improvement. Development of these QSAR models has provided us with a better understanding of the potential mechanisms of action for aldehydes, and hence how to avoid or limit allergy. Knowledge generated from this work is being incorporated into new/improved rules for sensitization in the expert toxicity prediction system, deductive estimation of risk from existing knowledge (DEREK).

Regional Assessment of Storm-triggered Shall Landslide Risks using the SLIDE (SLope-Infiltration-Distributed Equilibrium) Model

NASA Astrophysics Data System (ADS)

Hong, Y.; Kirschbaum, D. B.; Fukuoka, H.

2011-12-01

The key to advancing the predictability of rainfall-triggered landslides is to use physically based slope-stability models that simulate the dynamical response of the subsurface moisture to spatiotemporal variability of rainfall in complex terrains. An early warning system applying such physical models has been developed to predict rainfall-induced shallow landslides over Java Island in Indonesia and Honduras. The prototyped early warning system integrates three major components: (1) a susceptibility mapping or hotspot identification component based on a land surface geospatial database (topographical information, maps of soil properties, and local landslide inventory etc.); (2) a satellite-based precipitation monitoring system (http://trmm.gsfc.nasa.gov) and a precipitation forecasting model (i.e. Weather Research Forecast); and (3) a physically-based, rainfall-induced landslide prediction model SLIDE (SLope-Infiltration-Distributed Equilibrium). The system utilizes the modified physical model to calculate a Factor of Safety (FS) that accounts for the contribution of rainfall infiltration and partial saturation to the shear strength of the soil in topographically complex terrains. The system's prediction performance has been evaluated using a local landslide inventory. In Java Island, Indonesia, evaluation of SLIDE modeling results by local news reports shows that the system successfully predicted landslides in correspondence to the time of occurrence of the real landslide events. Further study of SLIDE is implemented in Honduras where Hurricane Mitch triggered widespread landslides in 1998. Results shows within the approximately 1,200 square kilometers study areas, the values of hit rates reached as high as 78% and 75%, while the error indices were 35% and 49%. Despite positive model performance, the SLIDE model is limited in the early warning system by several assumptions including, using general parameter calibration rather than in situ tests and neglecting geologic information. Advantages and limitations of this model will be discussed with respect to future applications of landslide assessment and prediction over large scales. In conclusion, integration of spatially distributed remote sensing precipitation products and in-situ datasets and physical models in this prototype system enable us to further develop a regional early warning tool in the future for forecasting storm-induced landslides.

Prediction of progressive damage and strength of plain weave composites using the finite element method

NASA Astrophysics Data System (ADS)

Srirengan, Kanthikannan

The overall objective of this research was to develop the finite element code required to efficiently predict the strength of plain weave composite structures. Towards which, three-dimensional conventional progressive damage analysis was implemented to predict the strength of plain weave composites subjected to periodic boundary conditions. Also, modal technique for three-dimensional global/local stress analysis was developed to predict the failure initiation in plain weave composite structures. The progressive damage analysis was used to study the effect of quadrature order, mesh refinement and degradation models on the predicted damage and strength of plain weave composites subjected to uniaxial tension in the warp tow direction. A 1/32sp{nd} part of the representative volume element of a symmetrically stacked configuration was analyzed. The tow geometry was assumed to be sinusoidal. Graphite/Epoxy system was used. Maximum stress criteria and combined stress criteria were used to predict failure in the tows and maximum principal stress criterion was used to predict failure in the matrix. Degradation models based on logical reasoning, micromechanics idealization and experimental comparisons were used to calculate the effective material properties with of damage. Modified Newton-Raphson method was used to determine the incremental solution for each applied strain level. Using a refined mesh and the discount method based on experimental comparisons, the progressive damage and the strength of plain weave composites of waviness ratios 1/3 and 1/6 subjected to uniaxial tension in the warp direction have been characterized. Plain weave composites exhibit a brittle response in uniaxial tension. The strength decreases significantly with the increase in waviness ratio. Damage initiation and collapse were caused dominantly due to intra-tow cracking and inter-tow debonding respectively. The predicted strength of plain weave composites of racetrack geometry and waviness ratio 1/25.7 was compared with analytical predictions and experimental findings and was found to match well. To evaluate the performance of the modal technique, failure initiation in a short woven composite cantilevered plate subjected to end moment and transverse end load was predicted. The global/local predictions were found to reasonably match well with the conventional finite element predictions.

Tailored high-resolution numerical weather forecasts for energy efficient predictive building control

NASA Astrophysics Data System (ADS)

Stauch, V. J.; Gwerder, M.; Gyalistras, D.; Oldewurtel, F.; Schubiger, F.; Steiner, P.

2010-09-01

The high proportion of the total primary energy consumption by buildings has increased the public interest in the optimisation of buildings' operation and is also driving the development of novel control approaches for the indoor climate. In this context, the use of weather forecasts presents an interesting and - thanks to advances in information and predictive control technologies and the continuous improvement of numerical weather prediction (NWP) models - an increasingly attractive option for improved building control. Within the research project OptiControl (www.opticontrol.ethz.ch) predictive control strategies for a wide range of buildings, heating, ventilation and air conditioning (HVAC) systems, and representative locations in Europe are being investigated with the aid of newly developed modelling and simulation tools. Grid point predictions for radiation, temperature and humidity of the high-resolution limited area NWP model COSMO-7 (see www.cosmo-model.org) and local measurements are used as disturbances and inputs into the building system. The control task considered consists in minimizing energy consumption whilst maintaining occupant comfort. In this presentation, we use the simulation-based OptiControl methodology to investigate the impact of COSMO-7 forecasts on the performance of predictive building control and the resulting energy savings. For this, we have selected building cases that were shown to benefit from a prediction horizon of up to 3 days and therefore, are particularly suitable for the use of numerical weather forecasts. We show that the controller performance is sensitive to the quality of the weather predictions, most importantly of the incident radiation on differently oriented façades. However, radiation is characterised by a high temporal and spatial variability in part caused by small scale and fast changing cloud formation and dissolution processes being only partially represented in the COSMO-7 grid point predictions. On the other hand, buildings are affected by particularly local weather conditions at the building site. To overcome this discrepancy, we make use of local measurements to statistically adapt the COSMO-7 model output to the meteorological conditions at the building. For this, we have developed a general correction algorithm that exploits systematic properties of the COSMO-7 prediction error and explicitly estimates the degree of temporal autocorrelation using online recursive estimation. The resulting corrected predictions are improved especially for the first few hours being the most crucial for the predictive controller and, ultimately for the reduction of primary energy consumption using predictive control. The use of numerical weather forecasts in predictive building automation is one example in a wide field of weather dependent advanced energy saving technologies. Our work particularly highlights the need for the development of specifically tailored weather forecast products by (statistical) postprocessing in order to meet the requirements of specific applications.

Downward continuation of gravity information from satellite to satellite tracking or satellite gradiometry in local areas

NASA Technical Reports Server (NTRS)

Rummel, R.

1975-01-01

Integral formulas in the parameter domain are used instead of a representation by spherical harmonics. The neglected regions will cause a truncation error. The application of the discrete form of the integral equations connecting the satellite observations with surface gravity anomalies is discussed in comparison with the least squares prediction method. One critical point of downward continuation is the proper choice of the boundary surface. Practical feasibilities are in conflict with theoretical considerations. The properties of different approaches for this question are analyzed.

The Galics Project: Virtual Galaxy: from Cosmological N-body Simulations

NASA Astrophysics Data System (ADS)

Guiderdoni, B.

The GalICS project develops extensive semi-analytic post-processing of large cosmological simulations to describe hierarchical galaxy formation. The multiwavelength statistical properties of high-redshift and local galaxies are predicted within the large-scale structures. The fake catalogs and mock images that are generated from the outputs are used for the analysis and preparation of deep surveys. The whole set of results is now available in an on-line database that can be easily queried. The GalICS project represents a first step towards a 'Virtual Observatory of virtual galaxies'.

Satellite Estimates of the Direct Radiative Forcing of Biomass Burning Aerosols Over South America and Africa

NASA Technical Reports Server (NTRS)

Christopher, Sundar A.; Wang, Min; Kliche, Donna V.; Berendes, Todd; Welch, Ronald M.; Yang, S.K.

1997-01-01

Atmospheric aerosol particles, both natural and anthropogenic are important to the earth's radiative balance. Therefore it is important to provide adequate validation information on the spatial, temporal and radiative properties of aerosols. This will enable us to predict realistic global estimates of aerosol radiative effects more confidently. The current study utilizes 66 AVHRR LAC (Local Area Coverage) and coincident Earth Radiation Budget Experiment (ERBE) images to characterize the fires, smoke and radiative forcings of biomass burning aerosols over four major ecosystems of South America.

Thermophysical ESEM and TEM Characterization of Carbon Fibers CTE, Spectroscopy and Roughness Studies at High Temperatures

NASA Technical Reports Server (NTRS)

Ochoa, Ozden O.

2004-01-01

Accurate determination of the transverse properties of carbon fibers is important for assessment and prediction of local material as well as global structural response of composite components. However the measurements are extremely difficult due to the very small diameters of the fibers (few microns only) and must be conducted within a microscope. In this work, environmental scanning electron microscope (ESEM) and transmission electron microscope (TEM) are used to determine the transverse coefficient of thermal expansion of different carbon fibers as a function of temperature.

Prediction of CpG-island function: CpG clustering vs. sliding-window methods

PubMed Central

2010-01-01

Background Unmethylated stretches of CpG dinucleotides (CpG islands) are an outstanding property of mammal genomes. Conventionally, these regions are detected by sliding window approaches using %G + C, CpG observed/expected ratio and length thresholds as main parameters. Recently, clustering methods directly detect clusters of CpG dinucleotides as a statistical property of the genome sequence. Results We compare sliding-window to clustering (i.e. CpGcluster) predictions by applying new ways to detect putative functionality of CpG islands. Analyzing the co-localization with several genomic regions as a function of window size vs. statistical significance (p-value), CpGcluster shows a higher overlap with promoter regions and highly conserved elements, at the same time showing less overlap with Alu retrotransposons. The major difference in the prediction was found for short islands (CpG islets), often exclusively predicted by CpGcluster. Many of these islets seem to be functional, as they are unmethylated, highly conserved and/or located within the promoter region. Finally, we show that window-based islands can spuriously overlap several, differentially regulated promoters as well as different methylation domains, which might indicate a wrong merge of several CpG islands into a single, very long island. The shorter CpGcluster islands seem to be much more specific when concerning the overlap with alternative transcription start sites or the detection of homogenous methylation domains. Conclusions The main difference between sliding-window approaches and clustering methods is the length of the predicted islands. Short islands, often differentially methylated, are almost exclusively predicted by CpGcluster. This suggests that CpGcluster may be the algorithm of choice to explore the function of these short, but putatively functional CpG islands. PMID:20500903

Numerical implementation of non-local polycrystal plasticity using fast Fourier transforms

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

Lebensohn, Ricardo A.; Needleman, Alan

Here, we present the numerical implementation of a non-local polycrystal plasticity theory using the FFT-based formulation of Suquet and co-workers. Gurtin (2002) non-local formulation, with geometry changes neglected, has been incorporated in the EVP-FFT algorithm of Lebensohn et al. (2012). Numerical procedures for the accurate estimation of higher order derivatives of micromechanical fields, required for feedback into single crystal constitutive relations, are identified and applied. A simple case of a periodic laminate made of two fcc crystals with different plastic properties is first used to assess the soundness and numerical stability of the proposed algorithm and to study the influencemore » of different model parameters on the predictions of the non-local model. Different behaviors at grain boundaries are explored, and the one consistent with the micro-clamped condition gives the most pronounced size effect. The formulation is applied next to 3-D fcc polycrystals, illustrating the possibilities offered by the proposed numerical scheme to analyze the mechanical response of polycrystalline aggregates in three dimensions accounting for size dependence arising from plastic strain gradients with reasonable computing times.« less

Numerical implementation of non-local polycrystal plasticity using fast Fourier transforms

DOE PAGES

Lebensohn, Ricardo A.; Needleman, Alan

2016-03-28

Here, we present the numerical implementation of a non-local polycrystal plasticity theory using the FFT-based formulation of Suquet and co-workers. Gurtin (2002) non-local formulation, with geometry changes neglected, has been incorporated in the EVP-FFT algorithm of Lebensohn et al. (2012). Numerical procedures for the accurate estimation of higher order derivatives of micromechanical fields, required for feedback into single crystal constitutive relations, are identified and applied. A simple case of a periodic laminate made of two fcc crystals with different plastic properties is first used to assess the soundness and numerical stability of the proposed algorithm and to study the influencemore » of different model parameters on the predictions of the non-local model. Different behaviors at grain boundaries are explored, and the one consistent with the micro-clamped condition gives the most pronounced size effect. The formulation is applied next to 3-D fcc polycrystals, illustrating the possibilities offered by the proposed numerical scheme to analyze the mechanical response of polycrystalline aggregates in three dimensions accounting for size dependence arising from plastic strain gradients with reasonable computing times.« less

Site-selective local fluorination of graphene induced by focused ion beam irradiation.

PubMed

Li, Hu; Daukiya, Lakshya; Haldar, Soumyajyoti; Lindblad, Andreas; Sanyal, Biplab; Eriksson, Olle; Aubel, Dominique; Hajjar-Garreau, Samar; Simon, Laurent; Leifer, Klaus

2016-01-29

The functionalization of graphene remains an important challenge for numerous applications expected by this fascinating material. To keep advantageous properties of graphene after modification or functionalization of its structure, local approaches are a promising road. A novel technique is reported here that allows precise site-selective fluorination of graphene. The basic idea of this approach consists in the local radicalization of graphene by focused ion beam (FIB) irradiation and simultaneous introduction of XeF2 gas. A systematic series of experiments were carried out to outline the relation between inserted defect creation and the fluorination process. Based on a subsequent X-ray photoelectron spectroscopy (XPS) analysis, a 6-fold increase of the fluorine concentration on graphene under simultaneous irradiation was observed when compared to fluorination under normal conditions. The fluorine atoms are predominately localized at the defects as indicated from scanning tunneling microscopy (STM). The experimental findings are confirmed by density functional theory which predicts a strong increase of the binding energy of fluorine atoms when bound to the defect sites. The developed technique allows for local fluorination of graphene without using resists and has potential to be a general enabler of site-selective functionalization of graphene using a wide range of gases.

Site-selective local fluorination of graphene induced by focused ion beam irradiation

NASA Astrophysics Data System (ADS)

Li, Hu; Daukiya, Lakshya; Haldar, Soumyajyoti; Lindblad, Andreas; Sanyal, Biplab; Eriksson, Olle; Aubel, Dominique; Hajjar-Garreau, Samar; Simon, Laurent; Leifer, Klaus

2016-01-01

The functionalization of graphene remains an important challenge for numerous applications expected by this fascinating material. To keep advantageous properties of graphene after modification or functionalization of its structure, local approaches are a promising road. A novel technique is reported here that allows precise site-selective fluorination of graphene. The basic idea of this approach consists in the local radicalization of graphene by focused ion beam (FIB) irradiation and simultaneous introduction of XeF2 gas. A systematic series of experiments were carried out to outline the relation between inserted defect creation and the fluorination process. Based on a subsequent X-ray photoelectron spectroscopy (XPS) analysis, a 6-fold increase of the fluorine concentration on graphene under simultaneous irradiation was observed when compared to fluorination under normal conditions. The fluorine atoms are predominately localized at the defects as indicated from scanning tunneling microscopy (STM). The experimental findings are confirmed by density functional theory which predicts a strong increase of the binding energy of fluorine atoms when bound to the defect sites. The developed technique allows for local fluorination of graphene without using resists and has potential to be a general enabler of site-selective functionalization of graphene using a wide range of gases.

Local-spin-density calculations for iron: Effect of spin interpolation on ground-state properties

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

MacLaren, J.M.; Clougherty, D.P.; Albers, R.C.

1990-08-15

Scalar-relativistic self-consistent linear muffin-tin orbital (LMTO) calculations for bcc and fcc Fe have been performed with several different local approximations to the exchange and correlation energy density and potential. Overall, in contrast to the conclusions of previous studies, we find that the local-spin-density approximation to exchange and correlation can provide an adequate description of bulk Fe {ital provided} that a proper parametrization of the correlation energy density and potential of the homogeneous electron gas over both spin and density is used. Lattice constants, found from the position of the minimum of the total energy as a function of Wigner-Seitz radius,more » agree to within 1% (for {ital s},{ital p},{ital d} LMTO's only) and within 1--2% (for {ital s},{ital p},{ital d},{ital f} LMTO's) of the experimental lattice constants for all forms used for the local correlation. The best agreement, however, was obtained using a local correlation potential derived from the Vosko-Wilk-Nusair form for the spin dependence of the correlation energy density. The calculation performed with this correlation potential was also the only calculation to correctly predict a bcc ferromagnetic ground state.« less

Evolution of Local Mutation Rate and Its Determinants.

PubMed

Terekhanova, Nadezhda V; Seplyarskiy, Vladimir B; Soldatov, Ruslan A; Bazykin, Georgii A

2017-05-01

Mutation rate varies along the human genome, and part of this variation is explainable by measurable local properties of the DNA molecule. Moreover, mutation rates differ between orthologous genomic regions of different species, but the drivers of this change are unclear. Here, we use data on human divergence from chimpanzee, human rare polymorphism, and human de novo mutations to predict the substitution rate at orthologous regions of non-human mammals. We show that the local mutation rates are very similar between human and apes, implying that their variation has a strong underlying cryptic component not explainable by the known genomic features. Mutation rates become progressively less similar in more distant species, and these changes are partially explainable by changes in the local genomic features of orthologous regions, most importantly, in the recombination rate. However, they are much more rapid, implying that the cryptic component underlying the mutation rate is more ephemeral than the known genomic features. These findings shed light on the determinants of mutation rate evolution. local mutation rate, molecular evolution, recombination rate. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Adaptation to implied tilt: extensive spatial extrapolation of orientation gradients

PubMed Central

Roach, Neil W.; Webb, Ben S.

2013-01-01

To extract the global structure of an image, the visual system must integrate local orientation estimates across space. Progress is being made toward understanding this integration process, but very little is known about whether the presence of structure exerts a reciprocal influence on local orientation coding. We have previously shown that adaptation to patterns containing circular or radial structure induces tilt-aftereffects (TAEs), even in locations where the adapting pattern was occluded. These spatially “remote” TAEs have novel tuning properties and behave in a manner consistent with adaptation to the local orientation implied by the circular structure (but not physically present) at a given test location. Here, by manipulating the spatial distribution of local elements in noisy circular textures, we demonstrate that remote TAEs are driven by the extrapolation of orientation structure over remarkably large regions of visual space (more than 20°). We further show that these effects are not specific to adapting stimuli with polar orientation structure, but require a gradient of orientation change across space. Our results suggest that mechanisms of visual adaptation exploit orientation gradients to predict the local pattern content of unfilled regions of space. PMID:23882243

Continuum-Scale Modeling of Shear Banding in Bulk Metallic Glass-Matrix Composites

NASA Astrophysics Data System (ADS)

Gibbons, Michael

Metallic glasses represent a relatively new class of materials that have demonstrated enormous potential for functional and structural applications due to the unique set of properties attributed to them as a result of the disordered isotropic structure with metallically bonded elements. Amorphous metals benefit from the strong nature of the metallic bonds, but lack the crystallographic structure and polycrystalline nature of traditional metals which unsurprisingly has huge implications on the material properties, as all deformation mechanisms associated with a lattice are suppressed. This results in excellent strength, a high elastic strain limit, exceptional hardness, and improved corrosion and wear resistance. "Bulk" metallic glasses (BMG) represent the amorphous metals which can be produced at the cm length-scale, thus greatly expanding their applicability for structural applications. However, due to the catastrophic nature of the failure produced upon yielding, monolithic metallic glasses are seldomly used for structural applications. Bulk metallic glass-matrix composites (BMGMCs), however, are able to combine the excellent strength, hardness, and elastic strain limit of amorphous metallic glass with a ductile crystalline phase to achieve extraordinary toughness with minimal degradation in strength. In order to explore the mechanical interactions between the amorphous and crystalline phases, a full-field micromechanical model which couples the free-volume based constitutive behavior for the matrix phase with standard rate-dependent crystal plasticity for the dendrites, and its implementation via an elastic-viscoplastic Fast-Fourier Transform (FFT) solver. The model is calibrated to macroscale stress-strain data for Ti-Zr-V-Cu-Be BMGMCs with varying composition and furthermore by comparing the deformation behavior associated with the shear bands predicted by the model, to the artifacts observed from characterization microscopy analysis on the same failed BMGMC tensile specimens in which the macroscopic composite behavior predicted by the model was validated with. The FFT-based deformation modeling is then exercised to study the nature and origin of shear bands in metallic glass composites. Synthetic 3D microstructures were produced using images of real BMGMCs, and then subjected to uniaxial tension deformation simulations. The findings indicate that in BMGMCs, local inhomogeneities in the glass phase are less influential on the mechanical performance than the contrast in individual phase properties and the spatial distribution of the microstructure. Due to the strong contrast in mechanical properties between the phases, highly heterogeneous stress fields develop, contributing to regionally confined free-volume generation, localized flow and softening in the glass. These softened regions can link and plastic flow then rapidly localizes into a thin shear band with planar like geometry. The availability of finely resolved (spatially and temporally) 3D deformation maps allow for the determination of the mechanism corresponding with these macroscopic stick-slip oscillations apparent in the stress-strain curves. In addition to shedding light on the nature of shear banding in bulk metallic glass-matrix composites, this work also demonstrates the feasibility of using a spectral-based continuum-scale model to efficiently predict the microstructure and individual phase properties that lead to new materials, superior to those found using only experimental techniques.

Graph pyramids for protein function prediction

PubMed Central

2015-01-01

Background Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Methods Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Results Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data. PMID:26044522

Graph pyramids for protein function prediction.

PubMed

Sandhan, Tushar; Yoo, Youngjun; Choi, Jin; Kim, Sun

2015-01-01

Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data.

Dengue Vector Dynamics (Aedes aegypti) Influenced by Climate and Social Factors in Ecuador: Implications for Targeted Control

PubMed Central

Stewart Ibarra, Anna M.; Ryan, Sadie J.; Beltrán, Efrain; Mejía, Raúl; Silva, Mercy; Muñoz, Ángel

2013-01-01

Background Dengue fever, a mosquito-borne viral disease, is now the fastest spreading tropical disease globally. Previous studies indicate that climate and human behavior interact to influence dengue virus and vector (Aedes aegypti) population dynamics; however, the relative effects of these variables depends on local ecology and social context. We investigated the roles of climate and socio-ecological factors on Ae. aegypti population dynamics in Machala, a city in southern coastal Ecuador where dengue is hyper-endemic. Methods/Principal findings We studied two proximate urban localities where we monitored weekly Ae. aegypti oviposition activity (Nov. 2010-June 2011), conducted seasonal pupal surveys, and surveyed household to identify dengue risk factors. The results of this study provide evidence that Ae. aegypti population dynamics are influenced by social risk factors that vary by season and lagged climate variables that vary by locality. Best-fit models to predict the presence of Ae. aegypti pupae included parameters for household water storage practices, access to piped water, the number of households per property, condition of the house and patio, and knowledge and perceptions of dengue. Rainfall and minimum temperature were significant predictors of oviposition activity, although the effect of rainfall varied by locality due to differences in types of water storage containers. Conclusions These results indicate the potential to reduce the burden of dengue in this region by conducting focused vector control interventions that target high-risk households and containers in each season and by developing predictive models using climate and non-climate information. These findings provide the region's public health sector with key information for conducting time and location-specific vector control campaigns, and highlight the importance of local socio-ecological studies to understand dengue dynamics. See Text S1 for an executive summary in Spanish. PMID:24324542

Thermodynamic and kinetic modeling of Mn-Ni-Si precipitates in low-Cu reactor pressure vessel steels

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

Ke, Huibin; Wells, Peter; Edmondson, Philip D.

Formation of large volume fractions of Mn-Ni-Si precipitates (MNSPs) causes excess irradiation embrittlement of reactor pressure vessel (RPV) steels at high, extended-life fluences. Thus, a new and unique, semi-empirical cluster dynamics model was developed to study the evolution of MNSPs in low-Cu RPV steels. The model is based on CALPHAD thermodynamics and radiation enhanced diffusion kinetics. The thermodynamics dictates the compositional and temperature dependence of the free energy reductions that drive precipitation. The model treats both homogeneous and heterogeneous nucleation, where the latter occurs on cascade damage, like dislocation loops. The model has only four adjustable parameters that were fitmore » to an atom probe tomography (APT) database. The model predictions are in semi-quantitative agreement with systematic Mn, Ni and Si composition variations in alloys characterized by APT, including a sensitivity to local tip-to-tip variations even in the same steel. The model predicts that heterogeneous nucleation plays a critical role in MNSP formation in lower alloy Ni contents. Single variable assessments of compositional effects show that Ni plays a dominant role, while even small variations in irradiation temperature can have a large effect on the MNSP evolution. Within typical RPV steel ranges, Mn and Si have smaller effects. Furthermore, the delayed but then rapid growth of MNSPs to large volume fractions at high fluence is well predicted by the model. For purposes of illustration, the effect of MNSPs on transition temperature shifts are presented based on well-established microstructure-property and property-property models.« less

Thermodynamic and kinetic modeling of Mn-Ni-Si precipitates in low-Cu reactor pressure vessel steels

DOE PAGES

Ke, Huibin; Wells, Peter; Edmondson, Philip D.; ...

2017-07-12

Formation of large volume fractions of Mn-Ni-Si precipitates (MNSPs) causes excess irradiation embrittlement of reactor pressure vessel (RPV) steels at high, extended-life fluences. Thus, a new and unique, semi-empirical cluster dynamics model was developed to study the evolution of MNSPs in low-Cu RPV steels. The model is based on CALPHAD thermodynamics and radiation enhanced diffusion kinetics. The thermodynamics dictates the compositional and temperature dependence of the free energy reductions that drive precipitation. The model treats both homogeneous and heterogeneous nucleation, where the latter occurs on cascade damage, like dislocation loops. The model has only four adjustable parameters that were fitmore » to an atom probe tomography (APT) database. The model predictions are in semi-quantitative agreement with systematic Mn, Ni and Si composition variations in alloys characterized by APT, including a sensitivity to local tip-to-tip variations even in the same steel. The model predicts that heterogeneous nucleation plays a critical role in MNSP formation in lower alloy Ni contents. Single variable assessments of compositional effects show that Ni plays a dominant role, while even small variations in irradiation temperature can have a large effect on the MNSP evolution. Within typical RPV steel ranges, Mn and Si have smaller effects. Furthermore, the delayed but then rapid growth of MNSPs to large volume fractions at high fluence is well predicted by the model. For purposes of illustration, the effect of MNSPs on transition temperature shifts are presented based on well-established microstructure-property and property-property models.« less

PETRORISK: a risk assessment framework for petroleum substances.

PubMed

Redman, Aaron D; Parkerton, Thomas F; Comber, Mike H I; Paumen, Miriam Leon; Eadsforth, Charles V; Dmytrasz, Bhodan; King, Duncan; Warren, Christopher S; den Haan, Klaas; Djemel, Nadia

2014-07-01

PETRORISK is a modeling framework used to evaluate environmental risk of petroleum substances and human exposure through these routes due to emissions under typical use conditions as required by the European regulation for the Registration, Evaluation, Authorization and Restriction of Chemicals (REACH). Petroleum substances are often complex substances comprised of hundreds to thousands of individual hydrocarbons. The physicochemical, fate, and effects properties of the individual constituents within a petroleum substance can vary over several orders of magnitude, complicating risk assessment. PETRORISK combines the risk assessment strategies used on single chemicals with the hydrocarbon block approach to model complex substances. Blocks are usually defined by available analytical characterization data on substances that are expressed in terms of mass fractions for different structural chemical classes that are specified as a function of C number or boiling point range. The physicochemical and degradation properties of the blocks are determined by the properties of representative constituents in that block. Emissions and predicted exposure concentrations (PEC) are then modeled using mass-weighted individual representative constituents. Overall risk for various environmental compartments at the regional and local level is evaluated by comparing the PECs for individual representative constituents to corresponding predicted no-effect concentrations (PNEC) derived using the Target Lipid Model. Risks to human health are evaluated using the overall predicted human dose resulting from multimedia environmental exposure to a substance-specific derived no-effect level (DNEL). A case study is provided to illustrate how this modeling approach has been applied to assess the risks of kerosene manufacture and use as a fuel. © 2014 SETAC.

Ageing of polymer bonds: a coupled chemomechanical modelling approach

NASA Astrophysics Data System (ADS)

Dippel, Benedikt; Johlitz, Michael; Lion, Alexander

2014-05-01

With the increasing number of requirements on joinings, it gets more and more important to understand and predict an assemblies properties. Nowadays, in industrial applications, combinations of different materials get more common. In most of those cases, it is, besides other advantages, useful to connect such parts with adhesives to avoid local cells. Thus, the knowledge about the mechanical behaviour of adhesives over the whole time of utilisation is an essential element of engineering. As it is well known, ageing due to environmental influences such as oxygen, radiation, ozone and others plays a major role in polymers properties. So, for the prediction of applicability over the whole lifetime of a technical component, the change in mechanical properties due to ageing is necessary. In this contribution, we introduce a material model which takes into account the internal structure of an adhesive. Therefore, an interphase zone is introduced. In the interphase, which is developed due to the contact of an adhesive with an adherent, the materials properties change continuously from the surface to the centre of the joint, where the polymer is in a bulky state. Built up on this geometry dependency, the materials ageing as a function of the position is described. To model the change of the polymers state, we use a parameter representing chain scission processes and another one for the reformation of a new network. In a last step, the model is transferred into a finite element code for exemplary calculations.

Deleterious Thermal Effects due to Randomized Flow Paths in Pebble Bed, and Particle Bed Style Reactors

NASA Technical Reports Server (NTRS)

Moran, Robert P.

2013-01-01

Reactor fuel rod surface area that is perpendicular to coolant flow direction (+S) i.e. perpendicular to the P creates areas of coolant stagnation leading to increased coolant temperatures resulting in localized changes in fluid properties. Changes in coolant fluid properties caused by minor increases in temperature lead to localized reductions in coolant mass flow rates leading to localized thermal instabilities. Reductions in coolant mass flow rates result in further increases in local temperatures exacerbating changes to coolant fluid properties leading to localized thermal runaway. Unchecked localized thermal runaway leads to localized fuel melting. Reactor designs with randomized flow paths are vulnerable to localized thermal instabilities, localized thermal runaway, and localized fuel melting.

Summary of Research Report

NASA Technical Reports Server (NTRS)

Elishakoff, Isaac

1998-01-01

Ten papers, published in various publications, on buckling, and the effects of imperfections on various structures are presented. These papers are: (1) Buckling mode localization in elastic plates due to misplacement in the stiffner location; (2) On vibrational imperfection sensitivity on Augusti's model structure in the vicinity of a non-linear static state; (3) Imperfection sensitivity due to elastic moduli in the Roorda Koiter frame; (4) Buckling mode localization in a multi-span periodic structure with a disorder in a single span; (5) Prediction of natural frequency and buckling load variability due to uncertainty in material properties by convex modeling; (6) Derivation of multi-dimensional ellipsoidal convex model for experimental data; (7) Passive control of buckling deformation via Anderson localization phenomenon; (8)Effect of the thickness and initial im perfection on buckling on composite cylindrical shells: asymptotic analysis and numerical results by BOSOR4 and PANDA2; (9) Worst case estimation of homology design by convex analysis; (10) Buckling of structures with uncertain imperfections - Personal perspective.

Determination of foveal location using scanning laser polarimetry.

PubMed

VanNasdale, Dean A; Elsner, Ann E; Weber, Anke; Miura, Masahiro; Haggerty, Bryan P

2009-03-25

The fovea is the retinal location responsible for our most acute vision. There are several methods used to localize the fovea, but the fovea is not always easily identifiable. Landmarks used to determine the foveal location are variable in normal subjects and localization becomes even more difficult in instances of retinal disease. In normal subjects, the photoreceptor axons that make up the Henle fiber layer are cylindrical and the radial orientation of these fibers is centered on the fovea. The Henle fiber layer exhibits form birefringence, which predictably changes polarized light in scanning laser polarimetry imaging. In this study 3 graders were able to repeatably identify the fovea in 35 normal subjects using near infrared image types with differing polarization content. There was little intra-grader, inter-grader, and inter-image variability in the graded foveal position for 5 of the 6 image types examined, with accuracy sufficient for clinical purposes. This study demonstrates that scanning laser polarimetry imaging can localize the fovea by using structural properties inherent in the central macula.

The valence-fluctuating ground state of plutonium

DOE PAGES

Janoschek, Marc; Das, Pinaki; Chakrabarti, Bismayan; ...

2015-07-10

A central issue in material science is to obtain understanding of the electronic correlations that control complex materials. Such electronic correlations frequently arise because of the competition of localized and itinerant electronic degrees of freedom. Although the respective limits of well-localized or entirely itinerant ground states are well understood, the intermediate regime that controls the functional properties of complex materials continues to challenge theoretical understanding. We have used neutron spectroscopy to investigate plutonium, which is a prototypical material at the brink between bonding and nonbonding configurations. In addition, our study reveals that the ground state of plutonium is governed bymore » valence fluctuations, that is, a quantum mechanical superposition of localized and itinerant electronic configurations as recently predicted by dynamical mean field theory. Our results not only resolve the long-standing controversy between experiment and theory on plutonium’s magnetism but also suggest an improved understanding of the effects of such electronic dichotomy in complex materials.« less

New Insights Concerning the Local Interstellar medium

NASA Astrophysics Data System (ADS)

Linsky, Jeffrey L.; Redfield, Seth

2015-08-01

We have been analyzing HST high-resolution ultraviolet spectra of nearby stars to measure the radial velocities, turbulence, temperature, and depletions on warm diffuse interstellar gas within a few parsecs of the Sun. These data reveal a picture of many partially-ionized warm gas clouds, each with their own vector velocity and physical characteristics. This picture has been recently challenged by Gry and Jenkins (2014), who argue for a single nonrigid cloud surrounding the Sun. We present a test of these two very different morphological structure by checking how well each predicts the radial velocities in a new data set (Malamut et al. 2014) that was not available when both models were constructed. We find that the multicloud model (Redfield & Linsky 2008) provides a much better fit to the new data. We compare the new IBEX results for the temperature and velocity of inflowing He gas (McComas et al. 2015) with the properties of the Local Interstellar Cloud and the G cloud. We also show a preliminary three-dimensional model for the local interstellar medium.

Counting ions and other nucleophiles at surfaces by chemical trapping.

PubMed

Cuccovia, Iolanda Midea; da Silva Lima, Filipe; Chaimovich, Hernan

2017-10-01

The interfaces of membranes and other aggregates are determined by the polarity, electrical charge, molecular volume, degrees of motional freedom and packing density of the head groups of the amphiphiles. These properties also determine the type of bound ion (ion selectivity) and its local density, i.e. concentration defined by choosing an appropriate volume element at the aggregate interface. Bulk and local ion concentrations can differ by orders of magnitude. The relationships between ion (or other compound) concentrations in the bulk solvent and in the interface are complex but, in some cases, well established. As the local ion concentration, rather than that in the bulk, controls a variety of properties of membranes, micelles, vesicles and other objects of theoretical and applied interests, measurement of local (interfacial, bound) ion concentrations is of relevance for understanding and characterizing such aggregates. Many experimental methods for estimating ion distributions between the bulk solution and the interface provide indirect estimates because they are based on concentration-dependent properties, rather than concentration measurements. Dediazoniation, i.e. the loss of N 2 , of a substituted diazophenyl derivative provides a tool for determining the number of nucleophiles (including neutral or negatively charged ions) surrounding the diazophenyl derivative prior to the dediazoniation event. This reaction, defined as chemical trapping, and the appropriate reference points obtained in bulk solution allow direct measurements of local concentrations of a variety of nucleophiles at the surface of membranes and other aggregates. Here we review our contributions of our research group to the use, and understanding, of this method and applications of chemical trapping to the description of local concentrations of ions and other nucleophiles in micelles, reverse micelles, vesicles and solvent mixtures. Among other results, we have shown that interfacial water determines micellar shape, zwitterionic vesicle-forming amphiphiles display ion selectivity and urea does not accumulate at micellar interfaces. We have also shown that reaction products can be predicted from the composition of the initial state, even in non-ideal solvent mixtures, supporting the usefulness of chemical trapping as a method to determine local concentrations. In addition, we have analysed the mechanism of dediazoniation, both on theoretical and experimental basis, and concluded that the formation of a free phenyl cation is not a necessary part of the reaction pathway.

Biomechanics of Atherosclerotic Coronary Plaque: Site, Stability and In Vivo Elasticity Modeling

PubMed Central

Ohayon, Jacques; Finet, Gérard; Le Floc’h, Simon; Cloutier, Guy; Gharib, Ahmed M.; Heroux, Julie; Pettigrew, Roderic I.

2016-01-01

Coronary atheroma develop in local sites that are widely variable among patients and are considerably variable in their vulnerability for rupture. This article summarizes studies conducted by our collaborative laboratories on predictive biomechanical modeling of coronary plaques. It aims to give insights into the role of biomechanics in the development and localization of atherosclerosis, the morphologic features that determine vulnerable plaque stability, and emerging in vivo imaging techniques that may detect and characterize vulnerable plaque. Composite biomechanical and hemodynamic factors that influence the actual site of development of plaques have been studied. Plaque vulnerability, in vivo, is more challenging to assess. Important steps have been made in defining the biomechanical factors that are predictive of plaque rupture and the likelihood of this occurring if characteristic features are known. A critical key in defining plaque vulnerability is the accurate quantification of both the morphology and the mechanical properties of the diseased arteries. Recently, an early IVUS based palpography technique developed to assess local strain, elasticity and mechanical instabilities has been successfully revisited and improved to account for complex plaque geometries. This is based on an initial best estimation of the plaque components’ contours, allowing subsequent iteration for elastic modulus assessment as a basis for plaque stability determination. The improved method has also been preliminarily evaluated in patients with successful histologic correlation. Further clinical evaluation and refinement are on the horizon. PMID:24043605

Capturing strain localization behind a geosynthetic-reinforced soil wall

NASA Astrophysics Data System (ADS)

Lai, Timothy Y.; Borja, Ronaldo I.; Duvernay, Blaise G.; Meehan, Richard L.

2003-04-01

This paper presents the results of finite element (FE) analyses of shear strain localization that occurred in cohesionless soils supported by a geosynthetic-reinforced retaining wall. The innovative aspects of the analyses include capturing of the localized deformation and the accompanying collapse mechanism using a recently developed embedded strong discontinuity model. The case study analysed, reported in previous publications, consists of a 3.5-m tall, full-scale reinforced wall model deforming in plane strain and loaded by surcharge at the surface to failure. Results of the analysis suggest strain localization developing from the toe of the wall and propagating upward to the ground surface, forming a curved failure surface. This is in agreement with a well-documented failure mechanism experienced by the physical wall model showing internal failure surfaces developing behind the wall as a result of the surface loading. Important features of the analyses include mesh sensitivity studies and a comparison of the localization properties predicted by different pre-localization constitutive models, including a family of three-invariant elastoplastic constitutive models appropriate for frictional/dilatant materials. Results of the analysis demonstrate the potential of the enhanced FE method for capturing a collapse mechanism characterized by the presence of a failure, or slip, surface through earthen materials.

Transport lattice models of heat transport in skin with spatially heterogeneous, temperature-dependent perfusion

PubMed Central

Gowrishankar, TR; Stewart, Donald A; Martin, Gregory T; Weaver, James C

2004-01-01

Background Investigation of bioheat transfer problems requires the evaluation of temporal and spatial distributions of temperature. This class of problems has been traditionally addressed using the Pennes bioheat equation. Transport of heat by conduction, and by temperature-dependent, spatially heterogeneous blood perfusion is modeled here using a transport lattice approach. Methods We represent heat transport processes by using a lattice that represents the Pennes bioheat equation in perfused tissues, and diffusion in nonperfused regions. The three layer skin model has a nonperfused viable epidermis, and deeper regions of dermis and subcutaneous tissue with perfusion that is constant or temperature-dependent. Two cases are considered: (1) surface contact heating and (2) spatially distributed heating. The model is relevant to the prediction of the transient and steady state temperature rise for different methods of power deposition within the skin. Accumulated thermal damage is estimated by using an Arrhenius type rate equation at locations where viable tissue temperature exceeds 42°C. Prediction of spatial temperature distributions is also illustrated with a two-dimensional model of skin created from a histological image. Results The transport lattice approach was validated by comparison with an analytical solution for a slab with homogeneous thermal properties and spatially distributed uniform sink held at constant temperatures at the ends. For typical transcutaneous blood gas sensing conditions the estimated damage is small, even with prolonged skin contact to a 45°C surface. Spatial heterogeneity in skin thermal properties leads to a non-uniform temperature distribution during a 10 GHz electromagnetic field exposure. A realistic two-dimensional model of the skin shows that tissue heterogeneity does not lead to a significant local temperature increase when heated by a hot wire tip. Conclusions The heat transport system model of the skin was solved by exploiting the mathematical analogy between local thermal models and local electrical (charge transport) models, thereby allowing robust, circuit simulation software to obtain solutions to Kirchhoff's laws for the system model. Transport lattices allow systematic introduction of realistic geometry and spatially heterogeneous heat transport mechanisms. Local representations for both simple, passive functions and more complex local models can be easily and intuitively included into the system model of a tissue. PMID:15548324

Derogation of Localizer Course Due to Proposed Water Tower Peterson Field, Colorado

DOT National Transportation Integrated Search

1974-10-01

The additional derogation to the localizer front and back courses caused by a water tower placed near the localizer site is predicted. This prediction is made with the Transportation Systems Center (TSC) localizer model. This additional derogation to...

A Comparison of Predictive Thermo and Water Solvation Property Prediction Tools and Experimental Data for Selected Traditional Chemical Warfare Agents and Simulants II: COSMO RS and COSMOTherm

DTIC Science & Technology

2017-04-01

A COMPARISON OF PREDICTIVE THERMO AND WATER SOLVATION PROPERTY PREDICTION TOOLS AND EXPERIMENTAL DATA FOR...4. TITLE AND SUBTITLE A Comparison of Predictive Thermo and Water Solvation Property Prediction Tools and Experimental Data for Selected...1  2.  EXPERIMENTAL PROCEDURE

Probing microscopic material properties inside simulated membranes through spatially resolved three-dimensional local pressure fields and surface tensions

PubMed Central

Kasson, Peter M.; Hess, Berk; Lindahl, Erik

2013-01-01

Cellular lipid membranes are spatially inhomogeneous soft materials. Materials properties such as pressure and surface tension thus show important microscopic-scale variation that is critical to many biological functions. We present a means to calculate pressure and surface tension in a 3D-resolved manner within molecular-dynamics simulations and show how such measurements can yield important insight. We also present the first corrections to local virial and pressure fields to account for the constraints typically used in lipid simulations that otherwise cause problems in highly oriented systems such as bilayers. Based on simulations of an asymmetric bacterial ion channel in a POPC bilayer, we demonstrate how 3D-resolved pressure can probe for both short-range and long-range effects from the protein on the membrane environment. We also show how surface tension is a sensitive metric for inter-leaflet equilibrium and can be used to detect even subtle imbalances between bilayer leaflets in a membrane-protein simulation. Since surface tension is known to modulate the function of many proteins, this effect is an important consideration for predictions of ion channel function. We outline a strategy by which our local pressure measurements, which we make available within a version of the GROMACS simulation package, may be used to design optimally equilibrated membrane-protein simulations. PMID:23318532

Flood management: prediction of microbial contamination in large-scale floods in urban environments.

PubMed

Taylor, Jonathon; Lai, Ka Man; Davies, Mike; Clifton, David; Ridley, Ian; Biddulph, Phillip

2011-07-01

With a changing climate and increased urbanisation, the occurrence and the impact of flooding is expected to increase significantly. Floods can bring pathogens into homes and cause lingering damp and microbial growth in buildings, with the level of growth and persistence dependent on the volume and chemical and biological content of the flood water, the properties of the contaminating microbes, and the surrounding environmental conditions, including the restoration time and methods, the heat and moisture transport properties of the envelope design, and the ability of the construction material to sustain the microbial growth. The public health risk will depend on the interaction of these complex processes and the vulnerability and susceptibility of occupants in the affected areas. After the 2007 floods in the UK, the Pitt review noted that there is lack of relevant scientific evidence and consistency with regard to the management and treatment of flooded homes, which not only put the local population at risk but also caused unnecessary delays in the restoration effort. Understanding the drying behaviour of flooded buildings in the UK building stock under different scenarios, and the ability of microbial contaminants to grow, persist, and produce toxins within these buildings can help inform recovery efforts. To contribute to future flood management, this paper proposes the use of building simulations and biological models to predict the risk of microbial contamination in typical UK buildings. We review the state of the art with regard to biological contamination following flooding, relevant building simulation, simulation-linked microbial modelling, and current practical considerations in flood remediation. Using the city of London as an example, a methodology is proposed that uses GIS as a platform to integrate drying models and microbial risk models with the local building stock and flood models. The integrated tool will help local governments, health authorities, insurance companies and residents to better understand, prepare for and manage a large-scale flood in urban environments. Copyright © 2011 Elsevier Ltd. All rights reserved.

Dedicated Low Latitude Diurnal CO2 Frost Observation Campaigns by the Mars Climate Sounder

NASA Astrophysics Data System (ADS)

Piqueux, S.; Kass, D. M.; Kleinboehl, A.; Hayne, P. O.; Heavens, N. G.; McCleese, D. J.; Schofield, J. T.; Shirley, J. H.

2017-12-01

In December 2016 (Ls≈280, MY33) and July 2017 (Ls≈30, MY34), the Mars Climate Sounder (MCS) onboard the Mars Reconnaissance Orbiter (MRO) conducted two distinct observation campaigns. The first one aimed at 1) confirming the presence of low latitude diurnal CO2 frost on Mars, and 2) refining the estimated mass of carbon dioxide condensed at the surface, whereas the second campaign was designed to 3) search for temporally and spatially varying spectral characteristics indicative of frost properties (i.e., crystal size, contamination, etc.) and relationship to the regolith. To meet these goals, MCS acquired thermal infrared observations of the surface and atmosphere at variable local times (≈1.70-3.80 h Local True Solar Time) and in the 10°-50°N latitude band where very low thermal inertia material (<< 100 Jm-2K-1s-0.5) is present. Atmospherically corrected surface brightness temperatures were retrieved in a wavelength region around 32 μm (MCS channel B1) as well as at 12 μm, 16 μm and 22 μm (MCS channels A4, A1, A5) where possible. A preliminary analysis of the data suggests a good general agreement between these new observations and earlier predictions in terms of frost distribution and spectral properties. In addition, pre-frost deposition surface cooling rates are found to be consistent with those predicted by numerical models (i.e., 1-2K per hour). Finally, we observe buffered surface temperatures near the local frost point, indicating a surface emissivity ≈1. (i.e., optically thin frost layers, or dust contaminated frost, or slab-like ice) and no discernable frost metamorphism. We will present a detailed analysis of these new and unique observations, and elaborate on the potential relationship between the regolith and this recurring frost cycle.

Using Bayesian methods to predict climate impacts on groundwater availability and agricultural production in Punjab, India

NASA Astrophysics Data System (ADS)

Russo, T. A.; Devineni, N.; Lall, U.

2015-12-01

Lasting success of the Green Revolution in Punjab, India relies on continued availability of local water resources. Supplying primarily rice and wheat for the rest of India, Punjab supports crop irrigation with a canal system and groundwater, which is vastly over-exploited. The detailed data required to physically model future impacts on water supplies agricultural production is not readily available for this region, therefore we use Bayesian methods to estimate hydrologic properties and irrigation requirements for an under-constrained mass balance model. Using measured values of historical precipitation, total canal water delivery, crop yield, and water table elevation, we present a method using a Markov chain Monte Carlo (MCMC) algorithm to solve for a distribution of values for each unknown parameter in a conceptual mass balance model. Due to heterogeneity across the state, and the resolution of input data, we estimate model parameters at the district-scale using spatial pooling. The resulting model is used to predict the impact of precipitation change scenarios on groundwater availability under multiple cropping options. Predicted groundwater declines vary across the state, suggesting that crop selection and water management strategies should be determined at a local scale. This computational method can be applied in data-scarce regions across the world, where water resource management is required to resolve competition between food security and available resources in a changing climate.

Science communication and vernal pool conservation: a study of local decision maker attitudes in a knowledge-action system.

PubMed

McGreavy, Bridie; Webler, Thomas; Calhoun, Aram J K

2012-03-01

In this study, we describe local decision maker attitudes towards vernal pools to inform science communication and enhance vernal pool conservation efforts. We conducted interviews with town planning board and conservation commission members (n = 9) from two towns in the State of Maine in the northeastern United States. We then mailed a questionnaire to a stratified random sample of planning board members in August and September 2007 with a response rate of 48.4% (n = 320). The majority of survey respondents favored the protection and conservation of vernal pools in their towns. Decision makers were familiar with the term "vernal pool" and demonstrated positive attitudes to vernal pools in general. General appreciation and willingness to conserve vernal pools predicted support for the 2006 revisions to the Natural Resource Protection Act regulating Significant Vernal Pools. However, 48% of respondents were unaware of this law and neither prior knowledge of the law nor workshop attendance predicted support for the vernal pool law. Further, concerns about private property rights and development restrictions predicted disagreement with the vernal pool law. We conclude that science communication must rely on specific frames of reference, be sensitive to cultural values, and occur in an iterative system to link knowledge and action in support of vernal pool conservation. Copyright © 2011 Elsevier Ltd. All rights reserved.

Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning

NASA Astrophysics Data System (ADS)

Bereau, Tristan; DiStasio, Robert A.; Tkatchenko, Alexandre; von Lilienfeld, O. Anatole

2018-06-01

Classical intermolecular potentials typically require an extensive parametrization procedure for any new compound considered. To do away with prior parametrization, we propose a combination of physics-based potentials with machine learning (ML), coined IPML, which is transferable across small neutral organic and biologically relevant molecules. ML models provide on-the-fly predictions for environment-dependent local atomic properties: electrostatic multipole coefficients (significant error reduction compared to previously reported), the population and decay rate of valence atomic densities, and polarizabilities across conformations and chemical compositions of H, C, N, and O atoms. These parameters enable accurate calculations of intermolecular contributions—electrostatics, charge penetration, repulsion, induction/polarization, and many-body dispersion. Unlike other potentials, this model is transferable in its ability to handle new molecules and conformations without explicit prior parametrization: All local atomic properties are predicted from ML, leaving only eight global parameters—optimized once and for all across compounds. We validate IPML on various gas-phase dimers at and away from equilibrium separation, where we obtain mean absolute errors between 0.4 and 0.7 kcal/mol for several chemically and conformationally diverse datasets representative of non-covalent interactions in biologically relevant molecules. We further focus on hydrogen-bonded complexes—essential but challenging due to their directional nature—where datasets of DNA base pairs and amino acids yield an extremely encouraging 1.4 kcal/mol error. Finally, and as a first look, we consider IPML for denser systems: water clusters, supramolecular host-guest complexes, and the benzene crystal.

Using the structure of natural scenes and sounds to predict neural response properties in the brain

NASA Astrophysics Data System (ADS)

Deweese, Michael

2014-03-01

The natural scenes and sounds we encounter in the world are highly structured. The fact that animals and humans are so efficient at processing these sensory signals compared with the latest algorithms running on the fastest modern computers suggests that our brains can exploit this structure. We have developed a sparse mathematical representation of speech that minimizes the number of active model neurons needed to represent typical speech sounds. The model learns several well-known acoustic features of speech such as harmonic stacks, formants, onsets and terminations, but we also find more exotic structures in the spectrogra representation of sound such as localized checkerboard patterns and frequency-modulated excitatory subregions flanked by suppressive sidebands. Moreover, several of these novel features resemble neuronal receptive fields reported in the Inferior Colliculus (IC), as well as auditory thalamus (MGBv) and primary auditory cortex (A1), and our model neurons exhibit the same tradeoff in spectrotemporal resolution as has been observed in IC. To our knowledge, this is the first demonstration that receptive fields of neurons in the ascending mammalian auditory pathway beyond the auditory nerve can be predicted based on coding principles and the statistical properties of recorded sounds. We have also developed a biologically-inspired neural network model of primary visual cortex (V1) that can learn a sparse representation of natural scenes using spiking neurons and strictly local plasticity rules. The representation learned by our model is in good agreement with measured receptive fields in V1, demonstrating that sparse sensory coding can be achieved in a realistic biological setting.

Predicting grid-size-dependent fracture strains of DP980 with a microstructure-based post-necking model

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

Cheng, G.; Hu, X. H.; Choi, K. S.

Ductile fracture is a local phenomenon, and it is well established that fracture strain levels depend on both stress triaxiality and the resolution (grid size) of strain measurements. Two-dimensional plane strain post-necking models with different representative volume element (RVE) sizes are used to predict the size-dependent fracture strain of a commercial dual-phase steel, DP980. The models are generated from the actual microstructures, and the individual phase flow properties and literature-based individual phase damage parameters for the Johnson-Cook model are used for ferrite and martensite. A monotonic relationship is predicted: the smaller the model size, the higher the fracture strain. Thus,more » a general framework is developed to quantify the size-dependent fracture strains for multiphase materials. In addition to the RVE sizes, the influences of intrinsic microstructure features, i.e., the flow curve and fracture strains of the two constituent phases, on the predicted fracture strains also are examined. Application of the derived fracture strain versus RVE size relationship is demonstrated with large clearance trimming simulations with different element sizes.« less

Fatigue Strength Prediction for Titanium Alloy TiAl6V4 Manufactured by Selective Laser Melting

NASA Astrophysics Data System (ADS)

Leuders, Stefan; Vollmer, Malte; Brenne, Florian; Tröster, Thomas; Niendorf, Thomas

2015-09-01

Selective laser melting (SLM), as a metalworking additive manufacturing technique, received considerable attention from industry and academia due to unprecedented design freedom and overall balanced material properties. However, the fatigue behavior of SLM-processed materials often suffers from local imperfections such as micron-sized pores. In order to enable robust designs of SLM components used in an industrial environment, further research regarding process-induced porosity and its impact on the fatigue behavior is required. Hence, this study aims at a transfer of fatigue prediction models, established for conventional process-routes, to the field of SLM materials. By using high-resolution computed tomography, load increase tests, and electron microscopy, it is shown that pore-based fatigue strength predictions for a titanium alloy TiAl6V4 have become feasible. However, the obtained accuracies are subjected to scatter, which is probably caused by the high defect density even present in SLM materials manufactured following optimized processing routes. Based on thorough examination of crack surfaces and crack initiation sites, respectively, implications for optimization of prediction accuracy of the models in focus are deduced.

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

Ceder, Gerbrand

Novel materials are often the enabler for new energy technologies. In ab-initio computational materials science, method are developed to predict the behavior of materials starting from the laws of physics, so that properties can be predicted before compounds have to be synthesized and tested. As such, a virtual materials laboratory can be constructed, saving time and money. The objectives of this program were to develop first-principles theory to predict the structure and thermodynamic stability of materials. Since its inception the program focused on the development of the cluster expansion to deal with the increased complexity of complex oxides. This researchmore » led to the incorporation of vibrational degrees of freedom in ab-initio thermodynamics, developed methods for multi-component cluster expansions, included the explicit configurational degrees of freedom of localized electrons, developed the formalism for stability in aqueous environments, and culminated in the first ever approach to produce exact ground state predictions of the cluster expansion. Many of these methods have been disseminated to the larger theory community through the Materials Project, pymatgen software, or individual codes. We summarize three of the main accomplishments.« less

Prediction of transmittance spectra for transparent composite electrodes with ultra-thin metal layers

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

Zhao, Zhao; Alford, T. L., E-mail: TA@asu.edu; Khorasani, Arash Elhami

2015-11-28

Recent interest in indium-free transparent composite-electrodes (TCEs) has motivated theoretical and experimental efforts to better understand and enhance their electrical and optical properties. Various tools have been developed to calculate the optical transmittance of multilayer thin-film structures based on the transfer-matrix method. However, the factors that affect the accuracy of these calculations have not been investigated very much. In this study, two sets of TCEs, TiO{sub 2}/Au/TiO{sub 2} and TiO{sub 2}/Ag/TiO{sub 2}, were fabricated to study the factors that affect the accuracy of transmittance predictions. We found that the predicted transmittance can deviate significantly from measured transmittance for TCEs thatmore » have ultra-thin plasmonic metal layers. The ultrathin metal layer in the TCE is typically discontinuous. When light interacts with the metallic islands in this discontinuous layer, localized surface plasmons are generated. This causes extra light absorption, which then leads to the actual transmittance being lower than the predicted transmittance.« less

Another baryon miracle? Testing solutions to the `missing dwarfs' problem

NASA Astrophysics Data System (ADS)

Trujillo-Gomez, Sebastian; Schneider, Aurel; Papastergis, Emmanouil; Reed, Darren S.; Lake, George

2018-04-01

The dearth of dwarf galaxies in the local Universe is hard to reconcile with the large number of low-mass haloes expected within the concordance Λ cold dark matter (ΛCDM) paradigm. In this paper, we perform a systematic evaluation of the uncertainties affecting the measurement of dark matter halo abundance using galaxy kinematics. Using a large sample of dwarf galaxies with spatially resolved kinematics, we derive a correction to obtain the abundance of galaxies as a function of maximum circular velocity - a direct probe of halo mass - from the line-of-sight velocity function in the Local Volume. This method provides a direct means of comparing the predictions of theoretical models and simulations (including non-standard cosmologies and novel galaxy formation physics) to the observational constraints. The new `galactic Vmax' function is steeper than the line-of-sight velocity function but still shallower than the theoretical CDM expectation, implying that unaccounted baryonic physics may be necessary to reduce the predicted abundance of galaxies. Using the galactic Vmax function, we investigate the theoretical effects of feedback-powered outflows and photoevaporation of gas due to reionization. At the 3σ confidence level, we find that feedback and reionization are not effective enough to reconcile the disagreement. In the case of maximum baryonic effects, the theoretical prediction still deviates significantly from the observations for Vmax < 60 km s-1. CDM predicts at least 1.8 times more galaxies with Vmax = 50 km s-1 and 2.5 times more than observed at 30 km s-1. Recent hydrodynamic simulations seem to resolve the discrepancy but disagree with the properties of observed galaxies with spatially resolved kinematics. This abundance problem might point to the need to modify cosmological predictions at small scales.

Predicting Spike Occurrence and Neuronal Responsiveness from LFPs in Primary Somatosensory Cortex

PubMed Central

Storchi, Riccardo; Zippo, Antonio G.; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E. M.

2012-01-01

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role. PMID:22586452

Accurate Prediction of Inducible Transcription Factor Binding Intensities In Vivo

PubMed Central

Siepel, Adam; Lis, John T.

2012-01-01

DNA sequence and local chromatin landscape act jointly to determine transcription factor (TF) binding intensity profiles. To disentangle these influences, we developed an experimental approach, called protein/DNA binding followed by high-throughput sequencing (PB–seq), that allows the binding energy landscape to be characterized genome-wide in the absence of chromatin. We applied our methods to the Drosophila Heat Shock Factor (HSF), which inducibly binds a target DNA sequence element (HSE) following heat shock stress. PB–seq involves incubating sheared naked genomic DNA with recombinant HSF, partitioning the HSF–bound and HSF–free DNA, and then detecting HSF–bound DNA by high-throughput sequencing. We compared PB–seq binding profiles with ones observed in vivo by ChIP–seq and developed statistical models to predict the observed departures from idealized binding patterns based on covariates describing the local chromatin environment. We found that DNase I hypersensitivity and tetra-acetylation of H4 were the most influential covariates in predicting changes in HSF binding affinity. We also investigated the extent to which DNA accessibility, as measured by digital DNase I footprinting data, could be predicted from MNase–seq data and the ChIP–chip profiles for many histone modifications and TFs, and found GAGA element associated factor (GAF), tetra-acetylation of H4, and H4K16 acetylation to be the most predictive covariates. Lastly, we generated an unbiased model of HSF binding sequences, which revealed distinct biophysical properties of the HSF/HSE interaction and a previously unrecognized substructure within the HSE. These findings provide new insights into the interplay between the genomic sequence and the chromatin landscape in determining transcription factor binding intensity. PMID:22479205

Predicting spike occurrence and neuronal responsiveness from LFPs in primary somatosensory cortex.

PubMed

Storchi, Riccardo; Zippo, Antonio G; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E M

2012-01-01

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neuronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role.

Prediction of Mechanical Properties of Polymers With Various Force Fields

NASA Technical Reports Server (NTRS)

Odegard, Gregory M.; Clancy, Thomas C.; Gates, Thomas S.

2005-01-01

The effect of force field type on the predicted elastic properties of a polyimide is examined using a multiscale modeling technique. Molecular Dynamics simulations are used to predict the atomic structure and elastic properties of the polymer by subjecting a representative volume element of the material to bulk and shear finite deformations. The elastic properties of the polyimide are determined using three force fields: AMBER, OPLS-AA, and MM3. The predicted values of Young s modulus and shear modulus of the polyimide are compared with experimental values. The results indicate that the mechanical properties of the polyimide predicted with the OPLS-AA force field most closely matched those from experiment. The results also indicate that while the complexity of the force field does not have a significant effect on the accuracy of predicted properties, small differences in the force constants and the functional form of individual terms in the force fields determine the accuracy of the force field in predicting the elastic properties of the polyimide.

A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves

NASA Astrophysics Data System (ADS)

Montzka, Carsten; Herbst, Michael; Weihermüller, Lutz; Verhoef, Anne; Vereecken, Harry

2017-07-01

Agroecosystem models, regional and global climate models, and numerical weather prediction models require adequate parameterization of soil hydraulic properties. These properties are fundamental for describing and predicting water and energy exchange processes at the transition zone between solid earth and atmosphere, and regulate evapotranspiration, infiltration and runoff generation. Hydraulic parameters describing the soil water retention (WRC) and hydraulic conductivity (HCC) curves are typically derived from soil texture via pedotransfer functions (PTFs). Resampling of those parameters for specific model grids is typically performed by different aggregation approaches such a spatial averaging and the use of dominant textural properties or soil classes. These aggregation approaches introduce uncertainty, bias and parameter inconsistencies throughout spatial scales due to nonlinear relationships between hydraulic parameters and soil texture. Therefore, we present a method to scale hydraulic parameters to individual model grids and provide a global data set that overcomes the mentioned problems. The approach is based on Miller-Miller scaling in the relaxed form by Warrick, that fits the parameters of the WRC through all sub-grid WRCs to provide an effective parameterization for the grid cell at model resolution; at the same time it preserves the information of sub-grid variability of the water retention curve by deriving local scaling parameters. Based on the Mualem-van Genuchten approach we also derive the unsaturated hydraulic conductivity from the water retention functions, thereby assuming that the local parameters are also valid for this function. In addition, via the Warrick scaling parameter λ, information on global sub-grid scaling variance is given that enables modellers to improve dynamical downscaling of (regional) climate models or to perturb hydraulic parameters for model ensemble output generation. The present analysis is based on the ROSETTA PTF of Schaap et al. (2001) applied to the SoilGrids1km data set of Hengl et al. (2014). The example data set is provided at a global resolution of 0.25° at https://doi.org/10.1594/PANGAEA.870605.

The role played by self-orientational properties in nematics of colloids with molecules axially symmetric.

PubMed

Alarcón-Waess, O

2010-04-14

The self-orientational structure factor as well as the short-time self-orientational diffusion coefficient is computed for colloids composed by nonspherical molecules. To compute the short-time dynamics the hydrodynamic interactions are not taken into account. The hard molecules with at least one symmetry axis considered are: rods, spherocylinders, and tetragonal parallelepipeds. Because both orientational properties in study are written in terms of the second and fourth order parameters, these automatically hold the features of the order parameters. That is, they present a discontinuity for first order transitions, determining in this way the spinodal line. In order to analyze the nematic phase only, we choose the appropriate values for the representative quantities that characterize the molecules. Different formalisms are used to compute the structural properties: de Gennes-Landau approach, Smoluchowski equation and computer simulations. Some of the necessary inputs are taken from literature. Our results show that the self-orientational properties play an important role in the characterization and the localization of axially symmetric phases. While the self-structure decreases throughout the nematics, the short-time self-diffusion does not decrease but rather increases. We study the evolution of the second and fourth order parameters; we find different responses for axial and biaxial nematics, predicting the possibility of a biaxial nematics in tetragonal parallelepiped molecules. By considering the second order in the axial-biaxial phase transition, with the support of the self-orientational structure factor, we are able to propose the density at which this occurs. The short-time dynamics is able to predict a different value in the axial and the biaxial phases. Because the different behavior of the fourth order parameter, the diffusion coefficient is lower for a biaxial phase than for an axial one. Therefore the self-structure factor is able to localize continuous phase transitions involving axially symmetric phases and the short-time self-orientational diffusion is able to distinguish the ordered phase by considering the degree of alignment, that is, axial or biaxial.

Thermophysical properties of liquid UO2, ZrO2 and corium by molecular dynamics and predictive models

NASA Astrophysics Data System (ADS)

Kim, Woong Kee; Shim, Ji Hoon; Kaviany, Massoud

2017-08-01

Predicting the fate of accident-melted nuclear fuel-cladding requires the understanding of the thermophysical properties which are lacking or have large scatter due to high-temperature experimental challenges. Using equilibrium classical molecular dynamics (MD), we predict the properties of melted UO2 and ZrO2 and compare them with the available experimental data and the predictive models. The existing interatomic potential models have been developed mainly for the polymorphic solid phases of these oxides, so they cannot be used to predict all the properties accurately. We compare and decipher the distinctions of those MD predictions using the specific property-related autocorrelation decays. The predicted properties are density, specific heat, heat of fusion, compressibility, viscosity, surface tension, and the molecular and electronic thermal conductivities. After the comparisons, we provide readily usable temperature-dependent correlations (including UO2-ZrO2 compounds, i.e. corium melt).

The Optoelectronic Properties of Nanoparticles from First Principles Calculations

NASA Astrophysics Data System (ADS)

Brawand, Nicholas Peter

The tunable optoelectronic properties of nanoparticles through the modification of their size, shape, and surface chemistry, make them promising platforms for numerous applications, including electronic and solar conversion devices. However, the rational design and optimization of nanostructured materials remain open challenges, e.g. due to difficulties in controlling and reproducing synthetic processes and in precise atomic-scale characterization. Hence, the need for accurate theoretical predictions, which can complement and help interpret experiments and provide insight into the underlying physical properties of nanostructured materials. This dissertation focuses on the development and application of first principles calculations to predict the optoelectronic properties of nanoparticles. Novel methods based on density functional theory are developed, implemented, and applied to predict both optical and charge transport properties. In particular, the generalization of dielectric dependent hybrid functionals to finite systems is introduced and shown to yield highly accurate electronic structure properties of molecules and nanoparticles, including photoemission and absorption properties. In addition, an implementation of constrained density functional theory is discussed, for the calculation of hopping transport in nanoparticle systems. The implementation was verified against literature results and compared against other methods used to compute transport properties, showing that some methods used in the literature give unphysical results for thermally disordered systems. Furthermore, the constrained density functional theory implementation was coupled to the self-consistent image charge method, making it possible to include image charge effects self-consistently when predicting charge transport properties of nanoparticles near interfaces. The methods developed in this dissertation were then applied to study the optoelectronic and transport properties of specific systems, in particular, silicon and lead chalcogenide nanoparticles. In the case of Si, blinking in oxidized Si nanoparticles was addressed. Si dangling bonds at the surface were found to introduce defect states which, depending on their charge and local stress conditions, may give rise to ON and OFF states responsible for exponential blinking statistics. We also investigated, engineering of band edge positions of nanoparticles through post-synthetic surface chemistry modification, with a focus on lead chalcogenides. In collaboration with experiment, we demonstrated how band edge positions of lead sulfide nanoparticles can be tuned by over 2.0 eV. We established a clear relationship between ligand dipole moments and nanoparticle band edge shifts which can be used to engineer nanoparticles for optoelectronic applications. Calculations of transport properties focused on charge transfer in silicon and lead chalcogenide nanoparticles. Si nanoparticles with deep defects and shallow impurities were investigated, showing that shallow defects may be more detrimental to charge transport than previously assumed. In the case of lead chalcogenide nanoparticles, hydrogen was found to form complexes with defects which can be used to remove potentially detrimental charge traps in nanoparticle solids. The methods and results presented in this dissertation are expected to help guide engineering of nanoparticles for future device applications.

Local suppression of collectivity in the N=80 isotones at the Z=58 subshell closure

NASA Astrophysics Data System (ADS)

Bauer, C.; Rainovski, G.; Pietralla, N.; Bianco, D.; Blazhev, A.; Bloch, T.; Bönig, S.; Damyanova, A.; Danchev, M.; Gladnishki, K. A.; Kröll, T.; Leske, J.; Lo Iudice, N.; Möller, T.; Moschner, K.; Pakarinen, J.; Reiter, P.; Scheck, M.; Seidlitz, M.; Siebeck, B.; Stahl, C.; Stegmann, R.; Stora, T.; Stoyanov, Ch.; Tarpanov, D.; Vermeulen, M. J.; Voulot, D.; Warr, N.; Wenander, F.; Werner, V.; De Witte, H.

2013-08-01

Background: Recent data on N=80 isotones have suggested that the proton π(1g7/2) subshell closure at Z=58 has an impact on the properties of low-lying collective states.Purpose: Knowledge of the B(E2;21+→01+) value of 140Nd is needed in order to test this conjecture.Method: The unstable, neutron-rich nucleus 140Nd was investigated via projectile Coulomb excitation at the REX-ISOLDE facility with the MINIBALL spectrometer.Results: The B(E2) value of 33(2) W.u. expands the N=80 systematics beyond the Z=58 subshell closure.Conclusions: The measurement demonstrates that the reduced collectivity of 138Ce is a local effect possibly due to the Z=58 subshell closure and requests refined theoretical calculations. The latter predict a smoothly increasing trend.

Invariance of visual operations at the level of receptive fields

PubMed Central

Lindeberg, Tony

2013-01-01

The brain is able to maintain a stable perception although the visual stimuli vary substantially on the retina due to geometric transformations and lighting variations in the environment. This paper presents a theory for achieving basic invariance properties already at the level of receptive fields. Specifically, the presented framework comprises (i) local scaling transformations caused by objects of different size and at different distances to the observer, (ii) locally linearized image deformations caused by variations in the viewing direction in relation to the object, (iii) locally linearized relative motions between the object and the observer and (iv) local multiplicative intensity transformations caused by illumination variations. The receptive field model can be derived by necessity from symmetry properties of the environment and leads to predictions about receptive field profiles in good agreement with receptive field profiles measured by cell recordings in mammalian vision. Indeed, the receptive field profiles in the retina, LGN and V1 are close to ideal to what is motivated by the idealized requirements. By complementing receptive field measurements with selection mechanisms over the parameters in the receptive field families, it is shown how true invariance of receptive field responses can be obtained under scaling transformations, affine transformations and Galilean transformations. Thereby, the framework provides a mathematically well-founded and biologically plausible model for how basic invariance properties can be achieved already at the level of receptive fields and support invariant recognition of objects and events under variations in viewpoint, retinal size, object motion and illumination. The theory can explain the different shapes of receptive field profiles found in biological vision, which are tuned to different sizes and orientations in the image domain as well as to different image velocities in space-time, from a requirement that the visual system should be invariant to the natural types of image transformations that occur in its environment. PMID:23894283

Integration of social perceptions, behaviors, and economic valuations of groundwater quality as an ecosystem service following exurban development

NASA Astrophysics Data System (ADS)

Godsey, S.; Larson, D. M.; Ohr, C. A.; Kobs-Nawotniak, S. E.; Lohse, K. A.; Lybecker, D.; Hale, R. L.; Stoutenborough, J.

2015-12-01

Millions of people rely on groundwater as a key, provisioning ecosystem service (ES). Our previous data suggested that drinking water nitrate concentrations and exurban development have significantly increased in the last three decades in Pocatello, Idaho, USA. Increased nitrate can lead to changes in ES and human values (such as water quality, people's knowledge, and housing values). We predicted people who tested their water quality would be aware of nitrate contamination and its potential to affect their housing prices, and they would choose to invest in home drinking water treatment systems. To test these hypotheses, we measured nitrate concentrations in hundreds of drinking water wells in years 1985, 1994, 2004, and 2015. We conducted a randomized public survey to determine the degrees to which: (1) people tested their private well water for nitrate and (2) were concerned about health issues related to contamination; (3) how important water quality is for determining local property values; and (4) if people treat their drinking water. We then developed a biophysical model to understand how exurban growth, local geology, and time influenced groundwater nitrate. Finally, we applied an economic, hedonic model to determine if groundwater nitrate concentrations negatively correlated to property values. Aquifer boundaries, slope, rock and soil type were significant predictors of nitrate (ordinary least squares, α <0.05). The hedonic model suggested that although nitrate and local housing values were spatially heterogeneous and increasing through time, exurban growth and nitrate alone were not strong predictors of water quality or property values. We also present an integrated biophysical, economic, and social model to better understand people's perceptions and behaviors of local nitrate pollution. Interdisciplinary ES and valuation may require multiple data types and integrated models to understand how ES and human values are influenced by exurban growth.

Survey of the Heritability and Sparse Architecture of Gene Expression Traits across Human Tissues.

PubMed

Wheeler, Heather E; Shah, Kaanan P; Brenner, Jonathon; Garcia, Tzintzuni; Aquino-Michaels, Keston; Cox, Nancy J; Nicolae, Dan L; Im, Hae Kyung

2016-11-01

Understanding the genetic architecture of gene expression traits is key to elucidating the underlying mechanisms of complex traits. Here, for the first time, we perform a systematic survey of the heritability and the distribution of effect sizes across all representative tissues in the human body. We find that local h2 can be relatively well characterized with 59% of expressed genes showing significant h2 (FDR < 0.1) in the DGN whole blood cohort. However, current sample sizes (n ≤ 922) do not allow us to compute distal h2. Bayesian Sparse Linear Mixed Model (BSLMM) analysis provides strong evidence that the genetic contribution to local expression traits is dominated by a handful of genetic variants rather than by the collective contribution of a large number of variants each of modest size. In other words, the local architecture of gene expression traits is sparse rather than polygenic across all 40 tissues (from DGN and GTEx) examined. This result is confirmed by the sparsity of optimal performing gene expression predictors via elastic net modeling. To further explore the tissue context specificity, we decompose the expression traits into cross-tissue and tissue-specific components using a novel Orthogonal Tissue Decomposition (OTD) approach. Through a series of simulations we show that the cross-tissue and tissue-specific components are identifiable via OTD. Heritability and sparsity estimates of these derived expression phenotypes show similar characteristics to the original traits. Consistent properties relative to prior GTEx multi-tissue analysis results suggest that these traits reflect the expected biology. Finally, we apply this knowledge to develop prediction models of gene expression traits for all tissues. The prediction models, heritability, and prediction performance R2 for original and decomposed expression phenotypes are made publicly available (https://github.com/hakyimlab/PrediXcan).

Mapping Arid Vegetation Species Distributions in the White Mountains, Eastern California, Using AVIRIS, Topography, and Geology

NASA Technical Reports Server (NTRS)

VandeVen, C.; Weiss, S. B.

2001-01-01

Our challenge is to model plant species distributions in complex montane environments using disparate sources of data, including topography, geology, and hyperspectral data. From an ecologist's point of view, species distributions are determined by local environment and disturbance history, while spectral data are 'ancillary.' However, a remote sensor's perspective says that spectral data provide picture of what vegetation is there, topographic and geologic data are ancillary. In order to bridge the gap, all available data should be used to get the best possible prediction of species distributions using complex multivariate techniques implemented on a GIS. Vegetation reflects local climatic and nutrient conditions, both of which can be modeled, allowing predictive mapping of vegetation distributions. Geologic substrate strongly affects chemical, thermal, and physical properties of soils, while climatic conditions are determined by local topography. As elevation increases, precipitation increases and temperature decreases. Aspect, slope, and surrounding topography determine potential insolation, so that south-facing slopes are warmer and north-facing slopes cooler at a given elevation. Topographic position (ridge, slope, canyon, or meadow) and slope angle affect sediment accumulation and soil depth. These factors combine as complex environmental gradients, and underlie many features of plant distributions. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data, digital elevation models, digitized geologic maps, and 378 ground control points were used to predictively map species distributions in the central and southern White Mountains, along the western boundary of the Basin and Range province. Minimum Noise Fraction (MNF) bands were calculated from the visible and near-infrared AVIRIS bands, and combined with digitized geologic maps and topographic variables using Canonical Correspondence Analysis (CCA). CCA allows for modeling species 'envelopes' in multidimensional environmental space, which can then be projected across entire landscapes.

A validation of the fibre orientation and fibre length attrition prediction for long fibre-reinforced thermoplastics

NASA Astrophysics Data System (ADS)

Hopmann, Ch.; Weber, M.; van Haag, J.; Schöngart, M.

2015-05-01

To improve the mechanical performance of polymeric parts, fibre reinforcement has established in industrial applications during the last decades. Next to the widely used Short Fibre-reinforced Thermoplastics (SFT) the use of Long Fibre-reinforced Thermoplastics (LFT) is increasingly growing. Especially for non-polar polymeric matrices like polypropylene (PP), longer fibres can significantly improve the mechanical performance. As with every kind of discontinuous fibre reinforcement the fibre orientations (FO) show a high impact on the mechanical properties. On the contrary to SFT where the local fibre length distribution (FLD) can be often neglected, for LFT the FLD show a high impact on the material's properties and has to be taken into account in equal measure to the FOD. Recently numerical models are available in commercial filling simulation software and allow predicting both the local FOD and FLD in LFT parts. The aim of this paper is to compare i.) the FOD results and ii) the FLD results from available orientation- and fibre length attrition-models to those obtained from experimental data. The investigations are conducted by the use of different injection moulded specimens made from long glass fibre reinforced PP. In order to determine the FOD, selected part sections are examined by means of Computed Tomographic (CT) analyses. The fully three dimensional measurement of the FOD is then performed by digital image processing using grey scale correlation. The FLD results are also obtained by using digital image processing after a thermal pyrolytic separation of the polymeric matrix from the fibres. Further the FOD and the FLD are predicted by using a reduced strain closure (RSC) as well as an anisotropic rotary diffusion - reduced strain closure model (ARD-RSC) and Phelps-Tucker fibre length attrition model implemented in the commercial filling software Moldflow, Autodesk Inc., San Rafael, CA, USA.

A validation of the fibre orientation and fibre length attrition prediction for long fibre-reinforced thermoplastics

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

Hopmann, Ch.; Weber, M.; Haag, J. van

2015-05-22

To improve the mechanical performance of polymeric parts, fibre reinforcement has established in industrial applications during the last decades. Next to the widely used Short Fibre-reinforced Thermoplastics (SFT) the use of Long Fibre-reinforced Thermoplastics (LFT) is increasingly growing. Especially for non-polar polymeric matrices like polypropylene (PP), longer fibres can significantly improve the mechanical performance. As with every kind of discontinuous fibre reinforcement the fibre orientations (FO) show a high impact on the mechanical properties. On the contrary to SFT where the local fibre length distribution (FLD) can be often neglected, for LFT the FLD show a high impact on themore » material’s properties and has to be taken into account in equal measure to the FOD. Recently numerical models are available in commercial filling simulation software and allow predicting both the local FOD and FLD in LFT parts. The aim of this paper is to compare i.) the FOD results and ii) the FLD results from available orientation- and fibre length attrition-models to those obtained from experimental data. The investigations are conducted by the use of different injection moulded specimens made from long glass fibre reinforced PP. In order to determine the FOD, selected part sections are examined by means of Computed Tomographic (CT) analyses. The fully three dimensional measurement of the FOD is then performed by digital image processing using grey scale correlation. The FLD results are also obtained by using digital image processing after a thermal pyrolytic separation of the polymeric matrix from the fibres. Further the FOD and the FLD are predicted by using a reduced strain closure (RSC) as well as an anisotropic rotary diffusion - reduced strain closure model (ARD-RSC) and Phelps-Tucker fibre length attrition model implemented in the commercial filling software Moldflow, Autodesk Inc., San Rafael, CA, USA.« less

Tunable diblock copolypeptide hydrogel depots for local delivery of hydrophobic molecules in healthy and injured central nervous system

PubMed Central

Zhang, Shanshan; Anderson, Mark A.; Ao, Yan; Khakh, Baljit S.; Fan, Jessica; Deming, Timothy J.; Sofroniew, Michael V.

2014-01-01

Many hydrophobic small molecules are available to regulate gene expression and other cellular functions. Locally restricted application of such molecules in the central nervous system (CNS) would be desirable in many experimental and therapeutic settings, but is limited by a lack of innocuous vehicles able to load and easily deliver hydrophobic cargo. Here, we tested the potential for diblock copolypeptide hydrogels (DCH) to serve as such vehicles. In vitro tests on loading and release were conducted with cholesterol and the anti-cancer agent, temozolomide (TMZ). Loading of hydrophobic cargo modified DCH physical properties such as stiffness and viscosity, but these could readily be tuned to desired ranges by modifying DCH concentration, amino acid composition or chain lengths. Different DCH formulations exhibited different loading capacities and different rates of release. For example, comparison of different DCH with increasing alanine contents showed corresponding increases in both cargo loading capacity and time for cargo release. In vivo tests were conducted with tamoxifen, a small synthetic hydrophobic molecule widely used to regulate transgene expression. Tamoxifen released from DCH depots injected into healthy or injured CNS efficiently activated reporter gene expression in a locally restricted manner in transgenic mice. These findings demonstrate the facile and predictable tunability of DCH to achieve a wide range of loading capacities and release profiles of hydrophobic cargos while retaining CNS compatible physical properties. In addition, the findings show that DCH depots injected into the CNS can efficiently deliver small hydrophobic molecules that regulate gene expression in local cells. PMID:24314556

From neurons to circuits: linear estimation of local field potentials.

PubMed

Rasch, Malte; Logothetis, Nikos K; Kreiman, Gabriel

2009-11-04

Extracellular physiological recordings are typically separated into two frequency bands: local field potentials (LFPs) (a circuit property) and spiking multiunit activity (MUA). Recently, there has been increased interest in LFPs because of their correlation with functional magnetic resonance imaging blood oxygenation level-dependent measurements and the possibility of studying local processing and neuronal synchrony. To further understand the biophysical origin of LFPs, we asked whether it is possible to estimate their time course based on the spiking activity from the same electrode or nearby electrodes. We used "signal estimation theory" to show that a linear filter operation on the activity of one or a few neurons can explain a significant fraction of the LFP time course in the macaque monkey primary visual cortex. The linear filter used to estimate the LFPs had a stereotypical shape characterized by a sharp downstroke at negative time lags and a slower positive upstroke for positive time lags. The filter was similar across different neocortical regions and behavioral conditions, including spontaneous activity and visual stimulation. The estimations had a spatial resolution of approximately 1 mm and a temporal resolution of approximately 200 ms. By considering a causal filter, we observed a temporal asymmetry such that the positive time lags in the filter contributed more to the LFP estimation than the negative time lags. Additionally, we showed that spikes occurring within approximately 10 ms of spikes from nearby neurons yielded better estimation accuracies than nonsynchronous spikes. In summary, our results suggest that at least some circuit-level local properties of the field potentials can be predicted from the activity of one or a few neurons.

From neurons to circuits: linear estimation of local field potentials

PubMed Central

Rasch, Malte; Logthetis, Nikos K.; Kreiman, Gabriel

2010-01-01

Extracellular physiological recordings are typically separated into two frequency bands: local field potentials (LFPs, a circuit property) and spiking multi-unit activity (MUA). There has been increased interest in LFPs due to their correlation with fMRI measurements and the possibility of studying local processing and neuronal synchrony. To further understand the biophysical origin of LFPs, we asked whether it is possible to estimate their time course based on the spiking activity from the same or nearby electrodes. We used Signal Estimation Theory to show that a linear filter operation on the activity of one/few neurons can explain a significant fraction of the LFP time course in the macaque primary visual cortex. The linear filter used to estimate the LFPs had a stereotypical shape characterized by a sharp downstroke at negative time lags and a slower positive upstroke for positve time lags. The filter was similar across neocortical regions and behavioral conditions including spontaneous activity and visual stimulation. The estimations had a spatial resolution of ~1 mm and a temporal resolution of ~200 ms. By considering a causal filter, we observed a temporal asymmetry such that the positive time lags in the filter contributed more to the LFP estimation than negative time lags. Additionally, we showed that spikes occurring within ~10 ms of spikes from nearby neurons yielded better estimation accuracies than nonsynchronous spikes. In sum, our results suggest that at least some circuit-level local properties of the field potentials can be predicted from the activity of one or a few neurons. PMID:19889990

ACE phenotyping in human heart

PubMed Central

Tikhomirova, Victoria E.; Kost, Olga A.; Kryukova, Olga V.; Golukhova, Elena Z.; Bulaeva, Naida I.; Zholbaeva, Aigerim Z.; Bokeria, Leo A.; Garcia, Joe G. N.

2017-01-01

Aims Angiotensin-converting enzyme (ACE), which metabolizes many peptides and plays a key role in blood pressure regulation and vascular remodeling, is expressed as a type-1 membrane glycoprotein on the surface of different cells, including endothelial cells of the heart. We hypothesized that the local conformation and, therefore, the properties of heart ACE could differ from lung ACE due to different microenvironment in these organs. Methods and results We performed ACE phenotyping (ACE levels, conformation and kinetic characteristics) in the human heart and compared it with that in the lung. ACE activity in heart tissues was 10–15 lower than that in lung. Various ACE effectors, LMW endogenous ACE inhibitors and HMW ACE-binding partners, were shown to be present in both heart and lung tissues. “Conformational fingerprint” of heart ACE (i.e., the pattern of 17 mAbs binding to different epitopes on the ACE surface) significantly differed from that of lung ACE, which reflects differences in the local conformations of these ACEs, likely controlled by different ACE glycosylation in these organs. Substrate specificity and pH-optima of the heart and lung ACEs also differed. Moreover, even within heart the apparent ACE activities, the local ACE conformations, and the content of ACE inhibitors differ in atria and ventricles. Conclusions Significant differences in the local conformations and kinetic properties of heart and lung ACEs demonstrate tissue specificity of ACE and provide a structural base for the development of mAbs able to distinguish heart and lung ACEs as a potential blood test for predicting atrial fibrillation risk. PMID:28771512

Importance of tread inertia and damping on the tyre/road contact stiffness

NASA Astrophysics Data System (ADS)

Winroth, J.; Andersson, P. B. U.; Kropp, W.

2014-10-01

Predicting tyre/road interaction processes like roughness excitation, stick-slip, stick-snap, wear and traction requires detailed information about the road surface, the tyre dynamics and the local deformation of the tread at the interface. Aspects of inertia and damping when the tread is locally deformed are often neglected in many existing tyre/road interaction models. The objective of this paper is to study how the dynamic features of the tread affect contact forces and contact stiffness during local deformation. This is done by simulating the detailed contact between an elastic layer and a rough road surface using a previously developed numerical time domain contact model. Road roughness on length scales smaller than the discretisation scale is included by the addition of nonlinear contact springs between each pair of contact elements. The dynamic case, with an elastic layer impulse response extending in time, is compared with the case where the corresponding quasi-static response is used. Results highlight the difficulty of estimating a constant contact stiffness as it increases during the indentation process between the elastic layer and the rough road surface. The stiffness-indentation relation additionally depends on how rapidly the contact develops; a faster process gives a stiffer contact. Material properties like loss factor and density also alter the contact development. This work implies that dynamic properties of the local tread deformation may be of importance when simulating contact details during normal tyre/road interaction conditions. There are however indications that the significant effect of damping could approximately be included as an increased stiffness in a quasi-static tread model.

Changes in Gene Expression Predicting Local Control in Cervical Cancer: Results from Radiation Therapy Oncology Group 0128

PubMed Central

Weidhaas, Joanne B.; Li, Shu-Xia; Winter, Kathryn; Ryu, Janice; Jhingran, Anuja; Miller, Bridgette; Dicker, Adam P.; Gaffney, David

2009-01-01

Purpose To evaluate the potential of gene expression signatures to predict response to treatment in locally advanced cervical cancer treated with definitive chemotherapy and radiation. Experimental Design Tissue biopsies were collected from patients participating in Radiation Therapy Oncology Group (RTOG) 0128, a phase II trial evaluating the benefit of celecoxib in addition to cisplatin chemotherapy and radiation for locally advanced cervical cancer. Gene expression profiling was done and signatures of pretreatment, mid-treatment (before the first implant), and “changed” gene expression patterns between pre- and mid-treatment samples were determined. The ability of the gene signatures to predict local control versus local failure was evaluated. Two-group t test was done to identify the initial gene set separating these end points. Supervised classification methods were used to enrich the gene sets. The results were further validated by leave-one-out and 2-fold cross-validation. Results Twenty-two patients had suitable material from pretreatment samples for analysis, and 13 paired pre- and mid-treatment samples were obtained. The changed gene expression signatures between the pre- and mid-treatment biopsies predicted response to treatment, separating patients with local failures from those who achieved local control with a seven-gene signature. The in-sample prediction rate, leave-one-out prediction rate, and 2-fold prediction rate are 100% for this seven-gene signature. This signature was enriched for cell cycle genes. Conclusions Changed gene expression signatures during therapy in cervical cancer can predict outcome as measured by local control. After further validation, such findings could be applied to direct additional therapy for cervical cancer patients treated with chemotherapy and radiation. PMID:19509178

Local thermal energy as a structural indicator in glasses

NASA Astrophysics Data System (ADS)

Zylberg, Jacques; Lerner, Edan; Bar-Sinai, Yohai; Bouchbinder, Eran

2017-07-01

Identifying heterogeneous structures in glasses—such as localized soft spots—and understanding structure-dynamics relations in these systems remain major scientific challenges. Here, we derive an exact expression for the local thermal energy of interacting particles (the mean local potential energy change caused by thermal fluctuations) in glassy systems by a systematic low-temperature expansion. We show that the local thermal energy can attain anomalously large values, inversely related to the degree of softness of localized structures in a glass, determined by a coupling between internal stresses—an intrinsic signature of glassy frustration—anharmonicity and low-frequency vibrational modes. These anomalously large values follow a fat-tailed distribution, with a universal exponent related to the recently observed universal ω4ω4 density of states of quasilocalized low-frequency vibrational modes. When the spatial thermal energy field—a “softness field”—is considered, this power law tail manifests itself by highly localized spots, which are significantly softer than their surroundings. These soft spots are shown to be susceptible to plastic rearrangements under external driving forces, having predictive powers that surpass those of the normal modes-based approach. These results offer a general, system/model-independent, physical/observable-based approach to identify structural properties of quiescent glasses and relate them to glassy dynamics.

Incremental online learning in high dimensions.

PubMed

Vijayakumar, Sethu; D'Souza, Aaron; Schaal, Stefan

2005-12-01

Locally weighted projection regression (LWPR) is a new algorithm for incremental nonlinear function approximation in high-dimensional spaces with redundant and irrelevant input dimensions. At its core, it employs nonparametric regression with locally linear models. In order to stay computationally efficient and numerically robust, each local model performs the regression analysis with a small number of univariate regressions in selected directions in input space in the spirit of partial least squares regression. We discuss when and how local learning techniques can successfully work in high-dimensional spaces and review the various techniques for local dimensionality reduction before finally deriving the LWPR algorithm. The properties of LWPR are that it (1) learns rapidly with second-order learning methods based on incremental training, (2) uses statistically sound stochastic leave-one-out cross validation for learning without the need to memorize training data, (3) adjusts its weighting kernels based on only local information in order to minimize the danger of negative interference of incremental learning, (4) has a computational complexity that is linear in the number of inputs, and (5) can deal with a large number of-possibly redundant-inputs, as shown in various empirical evaluations with up to 90 dimensional data sets. For a probabilistic interpretation, predictive variance and confidence intervals are derived. To our knowledge, LWPR is the first truly incremental spatially localized learning method that can successfully and efficiently operate in very high-dimensional spaces.

Numerical Estimation of the Elastic Properties of Thin-Walled Structures Manufactured from Short-Fiber-Reinforced Thermoplastics

NASA Astrophysics Data System (ADS)

Altenbach, H.; Naumenko, K.; L'vov, G. I.; Pilipenko, S. N.

2003-05-01

A model which allows us to estimate the elastic properties of thin-walled structures manufactured by injection molding is presented. The starting step is the numerical prediction of the microstructure of a short-fiber-reinforced composite developed during the filling stage of the manufacturing process. For this purpose, the Moldflow Plastic Insight® commercial program is used. As a result of simulating the filling process, a second-rank orientation tensor characterizing the microstructure of the material is obtained. The elastic properties of the prepared material locally depend on the orientational distribution of fibers. The constitutive equation is formulated by means of orientational averaging for a given orientation tensor. The tensor of elastic material properties is computed and translated into the format for a stress-strain analysis based on the ANSYSÒ finite-element code. The numerical procedure and the convergence of results are discussed for a thin strip, a rectangular plate, and a shell of revolution. The influence of manufacturing conditions on the stress-strain state of statically loaded thin-walled elements is illustrated.

Novel technique for online characterization of cartilaginous tissue properties.

PubMed

Yuan, Tai-Yi; Huang, Chun-Yuh; Yong Gu, Wei

2011-09-01

The goal of tissue engineering is to use substitutes to repair and restore organ function. Bioreactors are an indispensable tool for monitoring and controlling the unique environment for engineered constructs to grow. However, in order to determine the biochemical properties of engineered constructs, samples need to be destroyed. In this study, we developed a novel technique to nondestructively online-characterize the water content and fixed charge density of cartilaginous tissues. A new technique was developed to determine the tissue mechano-electrochemical properties nondestructively. Bovine knee articular cartilage and lumbar annulus fibrosus were used in this study to demonstrate that this technique could be used on different types of tissue. The results show that our newly developed method is capable of precisely predicting the water volume fraction (less than 3% disparity) and fixed charge density (less than 16.7% disparity) within cartilaginous tissues. This novel technique will help to design a new generation of bioreactors which are able to actively determine the essential properties of the engineered constructs, as well as regulate the local environment to achieve the optimal conditions for cultivating constructs.

Insight into the localized surface plasmon resonance property of core-satellite nanostructures: Theoretical prediction and experimental validation.

PubMed

Song, Dongxing; Jing, Dengwei

2017-11-01

Regulation of the localized surface plasmon resonance (LSPR) of nanoparticles by changing the dielectric constant of the surrounding medium has been exploited in many practical applications. In this study, using Ag-nanodot-decorated SiO 2 nanoparticles (Ag-decorated SiO 2 NPs) with different solvents, we investigated the potential of using such core-satellite nanostructures as a liquid sensor for the determination of melamine. The dielectric constant effect of the surrounding medium on the LSPR property was given particular attention. It was found that colloids with water as solvent display a LSPR shift of 14nm, and this value was 18nm for ethanol. For colloids with methanol and glycol as solvents, the peak shifts are negligible. Finite-difference time-domain (FDTD) simulations were used to assign the LSPR peaks of Ag-decorated SiO 2 NPs and to monitor the effect of the substrate and solvent on the LSPR properties. In the calculations, the wavelength positions of the LSPR peaks for Ag-decorated SiO 2 NPs in various solvents were successfully predicted in the order methanol

Dynamical properties of the S =1/2 random Heisenberg chain

NASA Astrophysics Data System (ADS)

Shu, Yu-Rong; Dupont, Maxime; Yao, Dao-Xin; Capponi, Sylvain; Sandvik, Anders W.

2018-03-01

We study dynamical properties at finite temperature (T ) of Heisenberg spin chains with random antiferromagnetic exchange couplings, which realize the random singlet phase in the low-energy limit, using three complementary numerical methods: exact diagonalization, matrix-product-state algorithms, and stochastic analytic continuation of quantum Monte Carlo results in imaginary time. Specifically, we investigate the dynamic spin structure factor S (q ,ω ) and its ω →0 limit, which are closely related to inelastic neutron scattering and nuclear magnetic resonance (NMR) experiments (through the spin-lattice relaxation rate 1 /T1 ). Our study reveals a continuous narrow band of low-energy excitations in S (q ,ω ) , extending throughout the q space, instead of being restricted to q ≈0 and q ≈π as found in the uniform system. Close to q =π , the scaling properties of these excitations are well captured by the random-singlet theory, but disagreements also exist with some aspects of the predicted q dependence further away from q =π . Furthermore we also find spin diffusion effects close to q =0 that are not contained within the random-singlet theory but give non-negligible contributions to the mean 1 /T1 . To compare with NMR experiments, we consider the distribution of the local relaxation rates 1 /T1 . We show that the local 1 /T1 values are broadly distributed, approximately according to a stretched exponential. The mean 1 /T1 first decreases with T , but below a crossover temperature it starts to increase and likely diverges in the limit of a small nuclear resonance frequency ω0. Although a similar divergent behavior has been predicted and experimentally observed for the static uniform susceptibility, this divergent behavior of the mean 1 /T1 has never been experimentally observed. Indeed, we show that the divergence of the mean 1 /T1 is due to rare events in the disordered chains and is concealed in experiments, where the typical 1 /T1 value is accessed.

Discontinuities Characteristics of the Upper Jurassic Arab-D Reservoir Equivalent Tight Carbonates Outcrops, Central Saudi Arabia

NASA Astrophysics Data System (ADS)

Abdlmutalib, Ammar; Abdullatif, Osman

2017-04-01

Jurassic carbonates represent an important part of the Mesozoic petroleum system in the Arabian Peninsula in terms of source rocks, reservoirs, and seals. Jurassic Outcrop equivalents are well exposed in central Saudi Arabia and which allow examining and measuring different scales of geological heterogeneities that are difficult to collect from the subsurface due to limitations of data and techniques. Identifying carbonates Discontinuities characteristics at outcrops might help to understand and predict their properties and behavior in the subsurface. The main objective of this study is to identify the lithofacies and the discontinuities properties of the upper Jurassic carbonates of the Arab D member and the Jubaila Formation (Arab-D reservoir) based on their outcrop equivalent strata in central Saudi Arabia. The sedimentologic analysis revealed several lithofacies types that vary in their thickness, abundances, cyclicity and vertical and lateral stacking patterns. The carbonates lithofacies included mudstone, wackestone, packstone, and grainstone. These lithofacies indicate deposition within tidal flat, skeletal banks and shallow to deep lagoonal paleoenvironmental settings. Field investigations of the outcrops revealed two types of discontinuities within Arab D Member and Upper Jubaila. These are depositional discontinuities and tectonic fractures and which all vary in their orientation, intensity, spacing, aperture and displacements. It seems that both regional and local controls have affected the fracture development within these carbonate rocks. On the regional scale, the fractures seem to be structurally controlled by the Central Arabian Graben System, which affected central Saudi Arabia. While, locally, at the outcrop scale, stratigraphic, depositional and diagenetic controls appear to have influenced the fracture development and intensity. The fracture sets and orientations identified on outcrops show similarity to those fracture sets revealed in the upper Jurassic carbonates in the subsurface which suggest inter-relationships. Therefore, the integration of discontinuities characteristics revealed from the Arab-D outcrop with subsurface data might help to understand and predict discontinuity properties and patterns of the Arab-D reservoir in the subsurface.

Fatigue damage characterization of braided and woven fiber reinforced polymer matrix composites at room and elevated temperatures

NASA Astrophysics Data System (ADS)

Montesano, John

The use of polymer matrix composites (PMC) for manufacturing primary load-bearing structural components has significantly increased in many industrial applications. Specifically in the aerospace industry, PMCs are also being considered for elevated temperature applications. Current aerospace-grade composite components subjected to fatigue loading are over-designed due to insufficient understanding of the material failure processes, and due to the lack of available generic fatigue prediction models. A comprehensive literature survey reveals that there are few fatigue studies conducted on woven and braided fabric reinforced PMC materials, and even fewer at elevated temperatures. It is therefore the objective of this study to characterize and subsequently model the elevated temperature fatigue behaviour of a triaxial braided PMC, and to investigate the elevated temperature fatigue properties of two additional woven PMCs. An extensive experimental program is conducted using a unique test protocol on the braided and woven composites, which consists of static and fatigue testing at various test temperatures. The development of mechanically-induced damage is monitored using a combination of non-destructive techniques which included infrared thermography, fiber optic sensors and edge replication. The observed microscopic damage development is quantified and correlated to the exhibited macroscopic material behaviour at all test temperatures. The fiber-dominated PMC materials considered in this study did not exhibit notable time- or temperature-dependent static properties. However, fatigue tests reveal that the local damage development is in fact notably influenced by temperature. The elevated temperature environment increases the toughness of the thermosetting polymers, which results in consistently slower fatigue crack propagation rates for the respective composite materials. This has a direct impact on the stiffness degradation rate and the fatigue lives for the braided and woven composites under investigation. The developed analytical fatigue damage prediction model, which is based on actual observed damage mechanisms, accurately predicted the development of damage and the corresponding stiffness degradation for the braided PMC, for all test temperatures. An excellent correlation was found between the experimental and the predicted results to within a 2% accuracy. The prediction model adequately captured the local temperature-induced phenomenon exhibited by the braided PMC material. The results presented in this study are novel for a braided composite material subjected to elevated temperature fatigue.

A priori calculations of the free energy of formation from solution of polymorphic self-assembled monolayers.

PubMed

Reimers, Jeffrey R; Panduwinata, Dwi; Visser, Johan; Chin, Yiing; Tang, Chunguang; Goerigk, Lars; Ford, Michael J; Sintic, Maxine; Sum, Tze-Jing; Coenen, Michiel J J; Hendriksen, Bas L M; Elemans, Johannes A A W; Hush, Noel S; Crossley, Maxwell J

2015-11-10

Modern quantum chemical electronic structure methods typically applied to localized chemical bonding are developed to predict atomic structures and free energies for meso-tetraalkylporphyrin self-assembled monolayer (SAM) polymorph formation from organic solution on highly ordered pyrolytic graphite surfaces. Large polymorph-dependent dispersion-induced substrate-molecule interactions (e.g., -100 kcal mol(-1) to -150 kcal mol(-1) for tetratrisdecylporphyrin) are found to drive SAM formation, opposed nearly completely by large polymorph-dependent dispersion-induced solvent interactions (70-110 kcal mol(-1)) and entropy effects (25-40 kcal mol(-1) at 298 K) favoring dissolution. Dielectric continuum models of the solvent are used, facilitating consideration of many possible SAM polymorphs, along with quantum mechanical/molecular mechanical and dispersion-corrected density functional theory calculations. These predict and interpret newly measured and existing high-resolution scanning tunnelling microscopy images of SAM structure, rationalizing polymorph formation conditions. A wide range of molecular condensed matter properties at room temperature now appear suitable for prediction and analysis using electronic structure calculations.

Developing a local least-squares support vector machines-based neuro-fuzzy model for nonlinear and chaotic time series prediction.

PubMed

Miranian, A; Abdollahzade, M

2013-02-01

Local modeling approaches, owing to their ability to model different operating regimes of nonlinear systems and processes by independent local models, seem appealing for modeling, identification, and prediction applications. In this paper, we propose a local neuro-fuzzy (LNF) approach based on the least-squares support vector machines (LSSVMs). The proposed LNF approach employs LSSVMs, which are powerful in modeling and predicting time series, as local models and uses hierarchical binary tree (HBT) learning algorithm for fast and efficient estimation of its parameters. The HBT algorithm heuristically partitions the input space into smaller subdomains by axis-orthogonal splits. In each partitioning, the validity functions automatically form a unity partition and therefore normalization side effects, e.g., reactivation, are prevented. Integration of LSSVMs into the LNF network as local models, along with the HBT learning algorithm, yield a high-performance approach for modeling and prediction of complex nonlinear time series. The proposed approach is applied to modeling and predictions of different nonlinear and chaotic real-world and hand-designed systems and time series. Analysis of the prediction results and comparisons with recent and old studies demonstrate the promising performance of the proposed LNF approach with the HBT learning algorithm for modeling and prediction of nonlinear and chaotic systems and time series.

Experimental test of visuomotor updating models that explain perisaccadic mislocalization.

PubMed

Van Wetter, Sigrid M C I; Van Opstal, A John

2008-10-23

Localization of a brief visual target is inaccurate when presented around saccade onset. Perisaccadic mislocalization is maximal in the saccade direction and varies systematically with the target-saccade onset disparity. It has been hypothesized that this effect is either due to a sluggish representation of eye position, to low-pass filtering of the visual event, to saccade-induced compression of visual space, or to a combination of these effects. Despite their differences, these schemes all predict that the pattern of localization errors varies systematically with the saccade amplitude and kinematics. We tested these predictions for the double-step paradigm by analyzing the errors for saccades of widely varying amplitudes. Our data show that the measured error patterns are only mildly influenced by the primary-saccade amplitude over a large range of saccade properties. An alternative possibility, better accounting for the data, assumes that around saccade onset perceived target location undergoes a uniform shift in the saccade direction that varies with amplitude only for small saccades. The strength of this visual effect saturates at about 10 deg and also depends on target duration. Hence, we propose that perisaccadic mislocalization results from errors in visual-spatial perception rather than from sluggish oculomotor feedback.

The melting point of lithium: an orbital-free first-principles molecular dynamics study

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

Chen, Mohan; Hung, Linda; Huang, Chen

2013-08-25

The melting point of liquid lithium near zero pressure is studied with large-scale orbital-free first-principles molecular dynamics (OF-FPMD) in the isobaric-isothermal ensemble. Here, we adopt the Wang-Govind-Carter (WGC) functional as our kinetic energy density functional (KEDF) and construct a bulk-derived local pseudopotential (BLPS) for Li. Our simulations employ both the ‘heat-until-melts’ method and the coexistence method. We predict 465 K as an upper bound of the melting point of Li from the ‘heat-until-melts’ method, while we predict 434 K as the melting point of Li from the coexistence method. These values compare well with an experimental melting point of 453more » K at zero pressure. Furthermore, we calculate a few important properties of liquid Li including the diffusion coefficients, pair distribution functions, static structure factors, and compressibilities of Li at 470 K and 725 K in the canonical ensemble. This theoretically-obtained results show good agreement with known experimental results, suggesting that OF-FPMD using a non-local KEDF and a BLPS is capable of accurately describing liquid metals.« less

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

Beidler, M. T.; Cassak, P. A.; Jardin, S. C.

We diagnose local properties of magnetic reconnection during a sawtooth crash employing the three-dimensional toroidal, extended-magnetohydrodynamic (MHD) code M3D-C 1. To do so, we sample simulation data in the plane in which reconnection occurs, the plane perpendicular to the helical (m, n) = (1, 1) mode at the q = 1 surface, where m and n are the poloidal and toroidal mode numbers and q is the safety factor. We study the nonlinear evolution of a particular test equilibrium in a non-reduced field representation using both resistive-MHD and extended-MHD models. We find growth rates for the extended-MHD reconnection process exhibitmore » a nonlinear acceleration and greatly exceed that of the resistive-MHD model, as is expected from previous experimental, theoretical, and computational work. We compare the properties of reconnection in the two simulations, revealing the reconnecting current sheets are locally different in the two models and we present the first observation of the quadrupole out-of-plane Hall magnetic field that appears during extended-MHD reconnection in a 3D toroidal simulation (but not in resistive-MHD). We also explore the dependence on toroidal angle of the properties of reconnection as viewed in the plane perpendicular to the helical magnetic field, finding qualitative and quantitative effects due to changes in the symmetry of the reconnection process. Furthermore, this study is potentially important for a wide range of magnetically confined fusion applications, from confirming simulations with extended-MHD effects are sufficiently resolved to describe reconnection, to quantifying local reconnection rates for purposes of understanding and predicting transport, not only at the q = 1 rational surface for sawteeth, but also at higher order rational surfaces that play a role in disruptions and edge-confinement degradation.« less

Manipulation of local optical properties and structures in molybdenum-disulfide monolayers using electric field-assisted near-field techniques.

PubMed

Nozaki, Junji; Fukumura, Musashi; Aoki, Takaaki; Maniwa, Yutaka; Yomogida, Yohei; Yanagi, Kazuhiro

2017-04-05

Remarkable optical properties, such as quantum light emission and large optical nonlinearity, have been observed in peculiar local sites of transition metal dichalcogenide monolayers, and the ability to tune such properties is of great importance for their optoelectronic applications. For that purpose, it is crucial to elucidate and tune their local optical properties simultaneously. Here, we develop an electric field-assisted near-field technique. Using this technique we can clarify and tune the local optical properties simultaneously with a spatial resolution of approximately 100 nm due to the electric field from the cantilever. The photoluminescence at local sites in molybdenum-disulfide (MoS 2 ) monolayers is reversibly modulated, and the inhomogeneity of the charge neutral points and quantum yields is suggested. We successfully etch MoS 2 crystals and fabricate nanoribbons using near-field techniques in combination with an electric field. This study creates a way to tune the local optical properties and to freely design the structural shapes of atomic monolayers using near-field optics.

Computational design of surfaces, nanostructures and optoelectronic materials

NASA Astrophysics Data System (ADS)

Choudhary, Kamal

Properties of engineering materials are generally influenced by defects such as point defects (vacancies, interstitials, substitutional defects), line defects (dislocations), planar defects (grain boundaries, free surfaces/nanostructures, interfaces, stacking faults) and volume defects (voids). Classical physics based molecular dynamics and quantum physics based density functional theory can be useful in designing materials with controlled defect properties. In this thesis, empirical potential based molecular dynamics was used to study the surface modification of polymers due to energetic polyatomic ion, thermodynamics and mechanics of metal-ceramic interfaces and nanostructures, while density functional theory was used to screen substituents in optoelectronic materials. Firstly, polyatomic ion-beams were deposited on polymer surfaces and the resulting chemical modifications of the surface were examined. In particular, S, SC and SH were deposited on amorphous polystyrene (PS), and C2H, CH3, and C3H5 were deposited on amorphous poly (methyl methacrylate) (PMMA) using molecular dynamics simulations with classical reactive empirical many-body (REBO) potentials. The objective of this work was to elucidate the mechanisms by which the polymer surface modification took place. The results of the work could be used in tailoring the incident energy and/or constituents of ion beam for obtaining a particular chemistry inside the polymer surface. Secondly, a new Al-O-N empirical potential was developed within the charge optimized many body (COMB) formalism. This potential was then used to examine the thermodynamic stability of interfaces and mechanical properties of nanostructures composed of aluminum, its oxide and its nitride. The potentials were tested for these materials based on surface energies, defect energies, bulk phase stability, the mechanical properties of the most stable bulk phase, its phonon properties as well as with a genetic algorithm based evolution theory of the materials to ensure that no spurious phases had a lower cohesive energy. Thirdly, lanthanide doped and co-doped Y3Al5O 12 were examined using density functional theory (DFT) with semi-local and local functional. Theoretical results were compared and validated with experimental data and new co-doped materials with high efficiency were predicted. Finally, Transition element doped CH3NH3PbI3 were studied with DFT for validation of the model with experimental data and replacement materials for toxic Pb were predicted.

Combining the Finite Element Method with Structural Connectome-based Analysis for Modeling Neurotrauma: Connectome Neurotrauma Mechanics

PubMed Central

Kraft, Reuben H.; Mckee, Phillip Justin; Dagro, Amy M.; Grafton, Scott T.

2012-01-01

This article presents the integration of brain injury biomechanics and graph theoretical analysis of neuronal connections, or connectomics, to form a neurocomputational model that captures spatiotemporal characteristics of trauma. We relate localized mechanical brain damage predicted from biofidelic finite element simulations of the human head subjected to impact with degradation in the structural connectome for a single individual. The finite element model incorporates various length scales into the full head simulations by including anisotropic constitutive laws informed by diffusion tensor imaging. Coupling between the finite element analysis and network-based tools is established through experimentally-based cellular injury thresholds for white matter regions. Once edges are degraded, graph theoretical measures are computed on the “damaged” network. For a frontal impact, the simulations predict that the temporal and occipital regions undergo the most axonal strain and strain rate at short times (less than 24 hrs), which leads to cellular death initiation, which results in damage that shows dependence on angle of impact and underlying microstructure of brain tissue. The monotonic cellular death relationships predict a spatiotemporal change of structural damage. Interestingly, at 96 hrs post-impact, computations predict no network nodes were completely disconnected from the network, despite significant damage to network edges. At early times () network measures of global and local efficiency were degraded little; however, as time increased to 96 hrs the network properties were significantly reduced. In the future, this computational framework could help inform functional networks from physics-based structural brain biomechanics to obtain not only a biomechanics-based understanding of injury, but also neurophysiological insight. PMID:22915997

Water polygons in high-resolution protein crystal structures.

PubMed

Lee, Jonas; Kim, Sung-Hou

2009-07-01

We have analyzed the interstitial water (ISW) structures in 1500 protein crystal structures deposited in the Protein Data Bank that have greater than 1.5 A resolution with less than 90% sequence similarity with each other. We observed varieties of polygonal water structures composed of three to eight water molecules. These polygons may represent the time- and space-averaged structures of "stable" water oligomers present in liquid water, and their presence as well as relative population may be relevant in understanding physical properties of liquid water at a given temperature. On an average, 13% of ISWs are localized enough to be visible by X-ray diffraction. Of those, averages of 78% are water molecules in the first water layer on the protein surface. Of the localized ISWs beyond the first layer, almost half of them form water polygons such as trigons, tetragons, as well as expected pentagons, hexagons, higher polygons, partial dodecahedrons, and disordered networks. Most of the octagons and nanogons are formed by fusion of smaller polygons. The trigons are most commonly observed. We suggest that our observation provides an experimental basis for including these water polygon structures in correlating and predicting various water properties in liquid state.

Water polygons in high-resolution protein crystal structures

PubMed Central

Lee, Jonas; Kim, Sung-Hou

2009-01-01

We have analyzed the interstitial water (ISW) structures in 1500 protein crystal structures deposited in the Protein Data Bank that have greater than 1.5 Å resolution with less than 90% sequence similarity with each other. We observed varieties of polygonal water structures composed of three to eight water molecules. These polygons may represent the time- and space-averaged structures of “stable” water oligomers present in liquid water, and their presence as well as relative population may be relevant in understanding physical properties of liquid water at a given temperature. On an average, 13% of ISWs are localized enough to be visible by X-ray diffraction. Of those, averages of 78% are water molecules in the first water layer on the protein surface. Of the localized ISWs beyond the first layer, almost half of them form water polygons such as trigons, tetragons, as well as expected pentagons, hexagons, higher polygons, partial dodecahedrons, and disordered networks. Most of the octagons and nanogons are formed by fusion of smaller polygons. The trigons are most commonly observed. We suggest that our observation provides an experimental basis for including these water polygon structures in correlating and predicting various water properties in liquid state. PMID:19551896

Modeling Coupled Thermal-Hydrological-Chemical Processes in the Unsaturated Fractured Rock of Yucca Mountain, Nevada: Heterogeneity and Seepage

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

S. Mukhopadhyay; E.L. Donnenthal; N. Spycher

An understanding of processes affecting seepage into emplacement tunnels is needed for correctly predicting the performance of underground radioactive waste repositories. It has been previously estimated that the capillary and vaporization barriers in the unsaturated fractured rock of Yucca Mountain are enough to prevent seepage under present day infiltration conditions. It has also been thought that a substantially elevated infiltration flux will be required to cause seepage after the thermal period is over. While coupled thermal-hydrological-chemical (THC) changes in Yucca Mountain host rock due to repository heating has been previously investigated, those THC models did not incorporate elements of themore » seepage model. In this paper, we combine the THC processes in unsaturated fractured rock with the processes affecting seepage. We observe that the THC processes alter the hydrological properties of the fractured rock through mineral precipitation and dissolution. We show that such alteration in the hydrological properties of the rock often leads to local flow channeling. We conclude that such local flow channeling may result in seepage under certain conditions, even with nonelevated infiltration fluxes.« less

A micromechanical approach for homogenization of elastic metamaterials with dynamic microstructure.

PubMed

Muhlestein, Michael B; Haberman, Michael R

2016-08-01

An approximate homogenization technique is presented for generally anisotropic elastic metamaterials consisting of an elastic host material containing randomly distributed heterogeneities displaying frequency-dependent material properties. The dynamic response may arise from relaxation processes such as viscoelasticity or from dynamic microstructure. A Green's function approach is used to model elastic inhomogeneities embedded within a uniform elastic matrix as force sources that are excited by a time-varying, spatially uniform displacement field. Assuming dynamic subwavelength inhomogeneities only interact through their volume-averaged fields implies the macroscopic stress and momentum density fields are functions of both the microscopic strain and velocity fields, and may be related to the macroscopic strain and velocity fields through localization tensors. The macroscopic and microscopic fields are combined to yield a homogenization scheme that predicts the local effective stiffness, density and coupling tensors for an effective Willis-type constitutive equation. It is shown that when internal degrees of freedom of the inhomogeneities are present, Willis-type coupling becomes necessary on the macroscale. To demonstrate the utility of the homogenization technique, the effective properties of an isotropic elastic matrix material containing isotropic and anisotropic spherical inhomogeneities, isotropic spheroidal inhomogeneities and isotropic dynamic spherical inhomogeneities are presented and discussed.

A micromechanical approach for homogenization of elastic metamaterials with dynamic microstructure

PubMed Central

Haberman, Michael R.

2016-01-01

An approximate homogenization technique is presented for generally anisotropic elastic metamaterials consisting of an elastic host material containing randomly distributed heterogeneities displaying frequency-dependent material properties. The dynamic response may arise from relaxation processes such as viscoelasticity or from dynamic microstructure. A Green's function approach is used to model elastic inhomogeneities embedded within a uniform elastic matrix as force sources that are excited by a time-varying, spatially uniform displacement field. Assuming dynamic subwavelength inhomogeneities only interact through their volume-averaged fields implies the macroscopic stress and momentum density fields are functions of both the microscopic strain and velocity fields, and may be related to the macroscopic strain and velocity fields through localization tensors. The macroscopic and microscopic fields are combined to yield a homogenization scheme that predicts the local effective stiffness, density and coupling tensors for an effective Willis-type constitutive equation. It is shown that when internal degrees of freedom of the inhomogeneities are present, Willis-type coupling becomes necessary on the macroscale. To demonstrate the utility of the homogenization technique, the effective properties of an isotropic elastic matrix material containing isotropic and anisotropic spherical inhomogeneities, isotropic spheroidal inhomogeneities and isotropic dynamic spherical inhomogeneities are presented and discussed. PMID:27616932

A micromechanical approach for homogenization of elastic metamaterials with dynamic microstructure

NASA Astrophysics Data System (ADS)

Muhlestein, Michael B.; Haberman, Michael R.

2016-08-01

An approximate homogenization technique is presented for generally anisotropic elastic metamaterials consisting of an elastic host material containing randomly distributed heterogeneities displaying frequency-dependent material properties. The dynamic response may arise from relaxation processes such as viscoelasticity or from dynamic microstructure. A Green's function approach is used to model elastic inhomogeneities embedded within a uniform elastic matrix as force sources that are excited by a time-varying, spatially uniform displacement field. Assuming dynamic subwavelength inhomogeneities only interact through their volume-averaged fields implies the macroscopic stress and momentum density fields are functions of both the microscopic strain and velocity fields, and may be related to the macroscopic strain and velocity fields through localization tensors. The macroscopic and microscopic fields are combined to yield a homogenization scheme that predicts the local effective stiffness, density and coupling tensors for an effective Willis-type constitutive equation. It is shown that when internal degrees of freedom of the inhomogeneities are present, Willis-type coupling becomes necessary on the macroscale. To demonstrate the utility of the homogenization technique, the effective properties of an isotropic elastic matrix material containing isotropic and anisotropic spherical inhomogeneities, isotropic spheroidal inhomogeneities and isotropic dynamic spherical inhomogeneities are presented and discussed.

Process Design of Aluminum Tailor Heat Treated Blanks.

PubMed

Kahrimanidis, Alexander; Lechner, Michael; Degner, Julia; Wortberg, Daniel; Merklein, Marion

2015-12-09

In many industrials field, especially in the automotive sector, there is a trend toward lightweight constructions in order to reduce the weight and thereby the CO₂ and NO x emissions of the products. An auspicious approach within this context is the substitution of conventional deep drawing steel by precipitation hardenable aluminum alloys. However, based on the low formability, the application for complex stamping parts is challenging. Therefore, at the Institute of Manufacturing Technology, an innovative technology to enhance the forming limit of these lightweight materials was invented. The key idea of the so-called Tailor Heat Treated Blanks (THTB) is optimization of the mechanical properties by local heat treatment before the forming operation. An accurate description of material properties is crucial to predict the forming behavior of tailor heat treated blanks by simulation. Therefore, within in this research project, a holistic approach for the design of the THTB process in dependency of the main influencing parameters is presented and discussed in detail. The capability of the approach for the process development of complex forming operations is demonstrated by a comparison of local blank thickness of a tailgate with the corresponding results from simulation.

Process Design of Aluminum Tailor Heat Treated Blanks

PubMed Central

Kahrimanidis, Alexander; Lechner, Michael; Degner, Julia; Wortberg, Daniel; Merklein, Marion

2015-01-01

In many industrials field, especially in the automotive sector, there is a trend toward lightweight constructions in order to reduce the weight and thereby the CO2 and NOx emissions of the products. An auspicious approach within this context is the substitution of conventional deep drawing steel by precipitation hardenable aluminum alloys. However, based on the low formability, the application for complex stamping parts is challenging. Therefore, at the Institute of Manufacturing Technology, an innovative technology to enhance the forming limit of these lightweight materials was invented. The key idea of the so-called Tailor Heat Treated Blanks (THTB) is optimization of the mechanical properties by local heat treatment before the forming operation. An accurate description of material properties is crucial to predict the forming behavior of tailor heat treated blanks by simulation. Therefore, within in this research project, a holistic approach for the design of the THTB process in dependency of the main influencing parameters is presented and discussed in detail. The capability of the approach for the process development of complex forming operations is demonstrated by a comparison of local blank thickness of a tailgate with the corresponding results from simulation. PMID:28793727

Unraveling the formation mechanism of graphitic nitrogen-doping in thermally treated graphene with ammonia

NASA Astrophysics Data System (ADS)

Li, Xiao-Fei; Lian, Ke-Yan; Liu, Lingling; Wu, Yingchao; Qiu, Qi; Jiang, Jun; Deng, Mingsen; Luo, Yi

2016-03-01

Nitrogen-doped graphene (N-graphene) has attractive properties that has been widely studied over the years. However, its possible formation process still remains unclear. Here, we propose a highly feasible formation mechanism of the graphitic-N doing in thermally treated graphene with ammonia by performing ab initio molecular dynamic simulations at experimental conditions. Results show that among the commonly native point defects in graphene, only the single vacancy 5-9 and divacancy 555-777 have the desirable electronic structures to trap N-containing groups and to mediate the subsequent dehydrogenation processes. The local structure of the defective graphene in combining with the thermodynamic and kinetic effect plays a crucial role in dominating the complex atomic rearrangement to form graphitic-N which heals the corresponding defect perfectly. The importance of the symmetry, the localized force field, the interaction of multiple trapped N-containing groups, as well as the catalytic effect of the temporarily formed bridge-N are emphasized, and the predicted doping configuration agrees well with the experimental observation. Hence, the revealed mechanism will be helpful for realizing the targeted synthesis of N-graphene with reduced defects and desired properties.

Random-growth urban model with geographical fitness

NASA Astrophysics Data System (ADS)

Kii, Masanobu; Akimoto, Keigo; Doi, Kenji

2012-12-01

This paper formulates a random-growth urban model with a notion of geographical fitness. Using techniques of complex-network theory, we study our system as a type of preferential-attachment model with fitness, and we analyze its macro behavior to clarify the properties of the city-size distributions it predicts. First, restricting the geographical fitness to take positive values and using a continuum approach, we show that the city-size distributions predicted by our model asymptotically approach Pareto distributions with coefficients greater than unity. Then, allowing the geographical fitness to take negative values, we perform local coefficient analysis to show that the predicted city-size distributions can deviate from Pareto distributions, as is often observed in actual city-size distributions. As a result, the model we propose can generate a generic class of city-size distributions, including but not limited to Pareto distributions. For applications to city-population projections, our simple model requires randomness only when new cities are created, not during their subsequent growth. This property leads to smooth trajectories of city population growth, in contrast to other models using Gibrat’s law. In addition, a discrete form of our dynamical equations can be used to estimate past city populations based on present-day data; this fact allows quantitative assessment of the performance of our model. Further study is needed to determine appropriate formulas for the geographical fitness.

Spectral statistics and scattering resonances of complex primes arrays

NASA Astrophysics Data System (ADS)

Wang, Ren; Pinheiro, Felipe A.; Dal Negro, Luca

2018-01-01

We introduce a class of aperiodic arrays of electric dipoles generated from the distribution of prime numbers in complex quadratic fields (Eisenstein and Gaussian primes) as well as quaternion primes (Hurwitz and Lifschitz primes), and study the nature of their scattering resonances using the vectorial Green's matrix method. In these systems we demonstrate several distinctive spectral properties, such as the absence of level repulsion in the strongly scattering regime, critical statistics of level spacings, and the existence of critical modes, which are extended fractal modes with long lifetimes not supported by either random or periodic systems. Moreover, we show that one can predict important physical properties, such as the existence spectral gaps, by analyzing the eigenvalue distribution of the Green's matrix of the arrays in the complex plane. Our results unveil the importance of aperiodic correlations in prime number arrays for the engineering of gapped photonic media that support far richer mode localization and spectral properties compared to usual periodic and random media.

On the long-range dependence properties of annual precipitation using a global network of instrumental measurements

NASA Astrophysics Data System (ADS)

Tyralis, Hristos; Dimitriadis, Panayiotis; Koutsoyiannis, Demetris; O'Connell, Patrick Enda; Tzouka, Katerina; Iliopoulou, Theano

2018-01-01

The long-range dependence (LRD) is considered an inherent property of geophysical processes, whose presence increases uncertainty. Here we examine the spatial behaviour of LRD in precipitation by regressing the Hurst parameter estimate of mean annual precipitation instrumental data which span from 1916-2015 and cover a big area of the earth's surface on location characteristics of the instrumental data stations. Furthermore, we apply the Mann-Kendall test under the LRD assumption (MKt-LRD) to reassess the significance of observed trends. To summarize the results, the LRD is spatially clustered, it seems to depend mostly on the location of the stations, while the predictive value of the regression model is good. Thus when investigating for LRD properties we recommend that the local characteristics should be considered. The application of the MKt-LRD suggests that no significant monotonic trend appears in global precipitation, excluding the climate type D (snow) regions in which positive significant trends appear.

Critical V2O5/TeO2 Ratio Inducing Abrupt Property Changes in Vanadium Tellurite Glasses.

PubMed

Kjeldsen, Jonas; Rodrigues, Ana C M; Mossin, Susanne; Yue, Yuanzheng

2014-12-26

Transition metal containing glasses have unique electrical properties and are therefore often used for electrochemical applications, such as in batteries. Among oxide glasses, vanadium tellurite glasses exhibit the highest electronic conductivity and thus the high potential for applications. In this work, we investigate how the dynamic and physical properties vary with composition in the vanadium tellurite system. The results show that there exists a critical V(2)O(5) concentration of 45 mol %, above which the local structure is subjected to a drastic change with increasing V(2)O(5), leading to abrupt changes in both hardness and liquid fragility. Electronic conductivity does not follow the expected correlation to the valence state of the vanadium as predicted by the Mott-Austin equation but shows a linear correlation to the mean distance between vanadium ions. These findings could contribute to designing optimum vanadium tellurite compositions for electrochemical devices. The work gives insight into the mechanism of electron conduction in the vanadium tellurite systems.

Tensile Properties and Microstructural Characterization of Hi-Nicalon SiC/RBSN Composites

NASA Technical Reports Server (NTRS)

Bhatt, Ramakrishna T.

1998-01-01

The room temperature physical and mechanical properties of silicon carbide fiber-reinforced reaction-bonded silicon nitride matrix composites (SiC/RBSN) were measured, and the composite microstructure was analyzed. The composites consist of nearly 24 vol% of aligned Hi-Nicalon SiC fiber yarns in a approx. 30 vol% porous silicon nitride matrix. The fiber yarns were coated by chemical vapor deposition with a 0.8 mm layer of boron nitride (BN) followed by a 0.2 mm layer of SiC. In the as-fabricated condition, both 1-D and 2-D composites exhibited high strength and graceful failure, and showed improved properties w en compared with unreinforced matrix of comparable density. No indication of reaction between the SiC fiber and BN coating was noticed, but the outer SiC layer reacted locally with the nitridation enhancing additive in the RBSN matrix. A comparison is made between the predicted and measured values of matrix cracking strength.

Tensile Properties and Microstructural Characterization of Hi-Nicalon SiC/RBSN Composites

NASA Technical Reports Server (NTRS)

Bhatt, Ramakrishna T.

1998-01-01

The room temperature physical and mechanical properties of silicon carbide fiber-reinforced reaction-bonded silicon nitride matrix composites (SiC/RBSN) were measured, and the composite microstructure was analyzed. The composites consist of nearly 24 vol% of aligned Hi-Nicalon SiC fiber yarns in a approx. 30 vo1% porous silicon nitride matrix. The fiber yarns were coated by chemical vapor deposition with a 0.8 micron layer of boron nitride (BN) followed by a 0.2 micron layer of SiC. In the as-fabricated condition, both 1-D and 2-D composites exhibited high strength and graceful failure, and showed improved properties when compared with unreinforced matrix of comparable density. No indication of reaction between the SiC fiber and BN coating was noticed, but the outer SiC layer reacted locally with the nitridation enhancing additive in the RBSN matrix. A comparison is made between the predicted and measured values of matrix cracking strength.

Predictive performance of rainfall thresholds for shallow landslide triggering in Switzerland from daily gridded precipitation data

NASA Astrophysics Data System (ADS)

Leonarduzzi, E.; Molnar, P.; McArdell, B. W.

2017-12-01

In Switzerland floods are responsible for most of the damage caused by rainfall-triggered natural hazards (89%), followed by landslides (6%, almost 600 M USD) as reported in Hilker et al. (2009) for the period 1972-2007. A high-resolution gridded daily precipitation dataset is combined with a landslide inventory containing over 2000 events in the period 1972-2012 to analyze rainfall thresholds that lead to landsliding in Switzerland. First triggering rainfall and landslides are co-located obtaining the distributions of triggering and non-triggering rainfall event properties at the scale of the precipitation data (2*2 km2) and considering 1 day as the interarrival time to separate events. Then rainfall thresholds are obtained by maximizing true positives (accurate predictions) while minimizing false negatives (false alarms), using the True Skill Statistic. The best predictive performance is obtained by the intensity-duration ID threshold curve, followed by peak daily intensity (Imax) and mean event intensity (Imean). Event duration by itself has very low predictive power. In addition to country-wide thresholds, local ones are also defined by regionalization based on surface erodibility and local long-term climate (mean daily precipitation). Different Imax thresholds are determined for each of the regions separately. It is found that wetter local climate and lower erodibility lead to significantly higher rainfall thresholds required to trigger landslides. However, the improvement in model performance due to regionalization is marginal and much lower than what can be achieved by having a high quality landslide database. In order to validate the performance of the Imax rainfall threshold model, reference cases will be presented in which the landslide locations and timing are randomized and the landslide sample size is reduced. Jack-knife and cross-validation experiments demonstrate that the model is robust. The results highlight the potential of using rainfall I-D threshold curves and Imax threshold values for predicting the occurrence of landslides on a country or regional scale even with daily precipitation data, with possible applications in landslide warning systems.

Prediction of the effects of thermal stratification on pressure and temperature response of the Apollo supercritical oxygen tank

NASA Technical Reports Server (NTRS)

Chen, I. M.; Anderson, R. E.

1971-01-01

A semiempirical design-oriented model has been developed for the prediction of the effects of thermal stratification on tank pressure and heater temperature response for the Apollo supercritical oxygen tank. The heat transfer formulation describes laminar free convection at low-g and takes into account the radiation and conduction processes occurring in the tank. The nonequilibrium thermodynamic behavior of the system due to localized heating of the stored fluid is represented by the characteristics of a discrete number of fluid regions and thermal nodes. Solutions to the time dependent variable fluid property problem are obtained through the use of a reference temperature procedure. A criterion which establishes the reference temperature as a function of the fluid density ratio is derived. The analytical results are compared with the flight data.

A model for inferring transport rates from observed confinement times in field-reversed configurations

NASA Astrophysics Data System (ADS)

Steinhauer, Loren C.; Milroy, Richard D.; Slough, John T.

1985-03-01

A one-dimensional transport model is developed to simulate the confinement of plasma and magnetic flux in a field-reversed configuration. Given the resistivity, the confinement times can be calculated. Approximate expressions are found which yield the magnitude and gross profile of the resistivity if the confinement times are known. These results are applied to experimental data from experiments, primarily TRX-1, to uncover trends in the transport properties. Several important conclusions emerge. The transport depends profoundly, and inexplicably, on the plasma formation mode. The inferred transport differs in several ways from the predictions of local lower-hybrid-drift turbulence theory. Finally, the gross resistivity exhibits an unusual trend with xs (separatrix radius rs divided by the conducting wall radius rc ), and is peaked near the magnetic axis for certain predictable conditions.

Neural network modeling of conditions of destruction of wood plank based on measurements

NASA Astrophysics Data System (ADS)

Filkin, V.; Kaverzneva, T.; Lazovskaya, T.; Lukinskiy, E.; Petrov, A.; Stolyarov, O.; Tarkhov, D.

2016-11-01

The paper deals with the possibility of predicting the ultimate load breaking timber sample based on the loading force dependence on the deflection before destruction. Prediction of mechanical properties of wood is handicapped by complex anisotropic structures. The anisotropic nature of the material and, in a great measure, the random nature of wood grain local features defining moment of destruction lead to a significant dependence of the required load on the individual characteristics of a particular bar. The ultimate load is sought as a function of the coefficients of the neural network approximation of the loading force dependence on the deflection. For this purpose, a number of experiments on timber sample loading until the destruction is conducted. Modeling of the conditions of material destruction may provide the required safety control in building industry.

Predicted carbonation of existing concrete building based on the Indonesian tropical micro-climate

NASA Astrophysics Data System (ADS)

Hilmy, M.; Prabowo, H.

2018-03-01

This paper is aimed to predict the carbonation progress based on the previous mathematical model. It shortly explains the nature of carbonation including the processes and effects. Environmental humidity and temperature of the existing concrete building are measured and compared to data from local Meteorological, Climatological, and Geophysical Agency. The data gained are expressed in the form of annual hygrothermal values which will use as the input parameter in carbonation model. The physical properties of the observed building such as its location, dimensions, and structural material used are quantified. These data then utilized as an important input parameter for carbonation coefficients. The relationships between relative humidity and the rate of carbonation established. The results can provide a basis for repair and maintenance of existing concrete buildings and the sake of service life analysis of them.

Prediction and characterization of heat-affected zone formation due to neighboring nickel-aluminum multilayer foil reaction

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

Adams, David P.; Hirschfeld, Deidre A.; Hooper, Ryan J.

2015-09-01

Reactive multilayer foils have the potential to be used as local high intensity heat sources for a variety of applications. Much of the past research effort concerning these materials have focused on understanding the structure-property relationships of the foils that govern the energy released during a reaction. To enhance the ability of researchers to more rapidly develop technologies based on reactive multilayer foils, a deeper and more predictive understanding of the relationship between the heat released from the foil and microstructural evolution in the neighboring materials is needed. This work describes the development of a numerical model for the purposemore » of evaluating new foil-substrate combinations for screening and optimization. The model is experimentally validated using a commercially available Ni-Al multilayer foils and different alloys.« less

Tracking BO6 Coupling in Perovskite Superlattices to Engineer Magnetic Interface Behavior

NASA Astrophysics Data System (ADS)

Borisevich, Albina; He, Qian; Ghosh, Saurabh; Moon, Eun Ju; May, Steve; Lupini, Andrew; Pantelides, Sokrates

In the past several years, control of BO6 octahedral coupling at ABO3 perovskite interfaces has emerged as a new tool for engineering of interface properties due to its strong coupling to polar and magnetic properties. High resolution data on tilt transitions at interfaces is instrumental for evaluating the validity of existing theoretical models and developing predictive theories. Recently, we have developed a unique method to investigate BO6 rotation patterns in complex oxides with unit cell resolution. Our method involves column shape analysis in ABF-STEM images of the perovskite heterointerfaces taken in specific orientations. This method will allow us to determine local symmetry between adjacent unit cells, revealing the BO6 coupling behavior at heterointerfaces in 3D. This technique was used to characterize structure and predict properties via a combined STEM and DFT study of magnetic superlattice of La(Ca)MnO3/La(Sr)MnO3 with different periodicities, which exhibit a range of electromagnetic coupling behaviors. We will also discuss the prospects for tilted structure determination using electron ptychography. The correlations among the BO6 rotation, domain size, superlattice periodicity and the electromagnetic coupling will be discussed in detail. Research supported by the MSED of the U.S.DOE, and through a user project at ORNL's CNMS, sponsored by the SUFD of the U.S. DOE.

Ab initio calculations of the structural, electronic, thermodynamic and thermal properties of BaSe1-x Te x alloys

NASA Astrophysics Data System (ADS)

Drablia, S.; Boukhris, N.; Boulechfar, R.; Meradji, H.; Ghemid, S.; Ahmed, R.; Omran, S. Bin; El Haj Hassan, F.; Khenata, R.

2017-10-01

The alkaline earth metal chalcogenides are being intensively investigated because of their advanced technological applications, for example in photoluminescent devices. In this study, the structural, electronic, thermodynamic and thermal properties of the BaSe1-x Te x alloys at alloying composition x = 0, 0.25, 0.50, 0.75 and 1 are investigated. The full potential linearized augmented plane wave plus local orbital method designed within the density functional theory was used to perform the total energy calculations. In this research work the effect of the composition on the results of the parameters and bulk modulus as well as on the band gap energy is analyzed. From our results, we found a deviation of the obtained results for the lattice constants from Vegard’s law as well as a deviation of the value of the bulk modulus from the linear concentration dependence. We also carried out a microscopic analysis of the origin of the band gap energy bowing parameter. Furthermore, the thermodynamic stability of the considered alloys was explored through the measurement of the miscibility critical temperature. The quasi-harmonic Debye model, as implemented in the Gibbs code, was used to predict the thermal properties of the BaSe1-x Te x alloys, and these investigations comprise our first theoretical predictions concerning the BaSe1-x Te x alloys.

Cohesiveness and hydrodynamic properties of young drinking water biofilms.

PubMed

Abe, Yumiko; Skali-Lami, Salaheddine; Block, Jean-Claude; Francius, Grégory

2012-03-15

Drinking water biofilms are complex microbial systems mainly composed of clusters of different size and age. Atomic force microscopy (AFM) measurements were performed on 4, 8 and 12 weeks old biofilms in order to quantify the mechanical detachment shear stress of the clusters, to estimate the biofilm entanglement rate ξ. This AFM approach showed that the removal of the clusters occurred generally for mechanical shear stress of about 100 kPa only for clusters volumes greater than 200 μm3. This value appears 1000 times higher than hydrodynamic shear stress technically available meaning that the cleaning of pipe surfaces by water flushing remains always incomplete. To predict hydrodynamic detachment of biofilm clusters, a theoretical model has been developed regarding the averaging of elastic and viscous stresses in the cluster and by including the entanglement rate ξ. The results highlighted a slight increase of the detachment shear stress with age and also the dependence between the posting of clusters and their volume. Indeed, the experimental values of ξ allow predicting biofilm hydrodynamic detachment with same order of magnitude than was what reported in the literature. The apparent discrepancy between the mechanical and the hydrodynamic detachment is mainly due to the fact that AFM mechanical experiments are related to the clusters local properties whereas hydrodynamic measurements reflected the global properties of the whole biofilm. Copyright © 2011 Elsevier Ltd. All rights reserved.